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Heat Transfer - Science topic

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Exploring methods like nanoparticle selection, flow optimization, and advanced modeling to improve thermal performance in nanofluid systems under turbulence.
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Optimizing heat transfer in nanofluid-based systems under turbulent flow requires a multi-faceted approach combining advanced materials, flow optimization, and accurate modeling techniques. Below are key techniques:
1. Nanoparticle Selection
  • Material Properties: Choose nanoparticles with high thermal conductivity (e.g., Al₂O₃, Cu, TiO₂, graphene, or carbon nanotubes).
  • Size and Shape: Use smaller-sized nanoparticles (<50 nm) to maximize surface area and heat transfer. Non-spherical shapes like platelets or rods may enhance thermal conductivity.
  • Concentration: Optimize volume fraction (typically 0.5–4%) to balance enhanced heat transfer and increased viscosity.
  • Surface Functionalization: Functionalize nanoparticle surfaces to improve dispersion stability and reduce agglomeration.
2. Base Fluid Selection
  • Choose base fluids with low viscosity and good thermal properties, such as water, ethylene glycol, or oil.
  • Use hybrid base fluids (e.g., water-ethylene glycol mixtures) for better performance across a range of temperatures.
3. Flow Optimization
  • Turbulent Flow Regime: Turbulence enhances mixing and heat transfer; ensure the Reynolds number is in the appropriate range for fully turbulent flow.
  • Flow Geometry: Use configurations like helical coils, wavy channels, or dimpled surfaces to promote secondary flows and turbulence.
  • Flow Rate: Optimize the mass flow rate to balance heat transfer and pumping power.
4. Enhancements to the Heat Transfer Surface
  • Surface Roughness: Introduce micro- or nano-scale roughness to increase surface area and promote turbulence near walls.
  • Porous Media: Embed porous structures for enhanced fluid mixing and thermal contact.
  • Nanocoatings: Apply thermally conductive coatings to improve heat transfer at the fluid-solid interface.
5. Advanced Modeling and Simulation
  • Multi-Phase Flow Models: Use CFD tools (e.g., ANSYS Fluent, OpenFOAM) with turbulence models (e.g., k-ε, k-ω SST, LES) to capture flow behavior accurately.
  • Nanoparticle Dynamics: Include models for Brownian motion, thermophoresis, and particle clustering in the simulations.
  • Machine Learning: Apply ML techniques for predictive modeling and optimization of heat transfer performance.
  • Optimization Algorithms: Use parametric studies and optimization tools (e.g., genetic algorithms or surrogate models) to refine system design.
6. Experimental Validation
  • Conduct experiments to validate CFD models and optimization strategies.
  • Use advanced diagnostics (e.g., Particle Image Velocimetry or Infrared Thermography) to measure flow patterns and thermal fields.
7. Hybrid Nanofluids
  • Explore hybrid nanofluids (e.g., Al₂O₃-TiO₂ or graphene-Cu combinations) to synergistically enhance thermal conductivity and specific heat capacity.
8. Control of Fouling and Stability
  • Minimize fouling by using stable suspensions and controlling fluid properties.
  • Use dispersants or ultrasonic techniques to maintain nanoparticle dispersion over long durations.
9. Incorporation of Phase Change Materials (PCMs)
  • Embed PCMs to store and release thermal energy efficiently, complementing the nanofluid's convective heat transfer capabilities.
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During winter, we face significant challenges such as cold walls and condensation, even with 10 cm insulation. To address these issues, what simulation techniques can be employed to optimize heat transfer in building systems? Additionally, I’d like to perform calculations using specialized software—what tools would you recommend for this purpose?
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Simple, nice and free for personal use
I've played with it a lot to get some intuition on what helps and what not
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Dear Researchgate Forum users!
I am delighted to invite you to participate in the 6th Central European Symposium on Building Physics (CESBP 2025), scheduled for 11th – 13th September 2025, at the Budapest University of Technology and Economics in Budapest, Hungary. The call for papers just started! Also, we organize an IABP summer school connected to the conference! Please check the attached flyer and cesbp2025.bme.hu, if you are interested. Feel free to ask here, too, if you have questions about the conference!
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Dear Albert Samai your contribution would be highly welcomed to CESBP 2025 conference.
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I want to do ED coating on , one of my aluminium part does it affect heat transfer from part.
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The article by ProPlate titled, "How does metal coating on tubes ensure better heat transfer in technological applications?" content valuable answer in that with the help of metal coatings, heat transfer can be more efficient and reliable in a wide range of industrial and commercial applications, making them an invaluable tool in the modern technological world.
Best regards
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How we can understand that flow regime in Buoyancy-driven flow is turbulent?
I use the Rayleigh number to identify this issue and consider a Rayleigh number higher than 10^9 to be turbulent flow.
Is this also true for liquid PCMs?
If you have a reliable source on this subject, I would appreciate to introduce it.
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The flow regime in buoyancy-driven flows can be identified using the Rayleigh number (Ra) and Reynolds number (Re):
  • Rayleigh Number (Ra): Ra>109Ra > 10^9Ra>109 typically indicates turbulence.
  • Reynolds Number (Re): Re>1600Re > 1600Re>1600 also suggests turbulent flow.
  • Flow Patterns: Look for unsteady, 3D flow with plumes and eddies.
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Hi i hope everyone reading this comment is doing great.
i have a question that couldn't find the answer to wherever i searched,
my question is when calculating the overall heat transfer coefficient kern's limitation for difference percentage is 30%.
if anyone know why 30 and not anyother number please share the info with me.
what did he do to set that specific number.
thank you in advance.
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The 30% limitation in Kern's method for heat exchanger design is related to the assumptions and empirical nature of the method, which primarily focuses on shell-and-tube heat exchangers. Here's the reasoning behind this specific value:
1. Empirical Basis of Kern's Method
Kern's method is based on experimental data and practical observations rather than purely theoretical derivations. The 30% value is essentially a safety factor derived from these experimental studies to account for:
  • Variability in flow distribution (especially in shell-side flow).
  • Bypasses and leakages that are difficult to predict with theoretical models.
  • Fouling factors that might not match the design assumptions.
  • Non-ideal flow patterns, such as deviations from true counterflow or crossflow conditions.
2. Practical Design Margin
The 30% deviation provides a practical margin to compensate for errors arising due to:
  • Simplified flow models (e.g., Kern's method assumes simplified flow paths and ignores complex recirculation zones).
  • Approximate correlations for heat transfer coefficients and pressure drops.
  • Uncertainty in operating conditions (e.g., flow rate fluctuations or temperature variations).
3. Flexibility for Scaling and Fabrication
When designing heat exchangers, fabrication tolerances and scaling effects (lab-scale to industrial scale) introduce further uncertainties. The 30% limit helps ensure the heat exchanger will still meet performance requirements even if these uncertainties affect the actual performance.
4. Historical and Industry Adoption
Over time, this 30% limit has been widely adopted in engineering practices and standards, making it a conventional benchmark in preliminary heat exchanger design. It offers a balance between conservatism and efficiency—not too strict to increase costs unnecessarily, but not too lenient to risk underperformance.
Why not another number?
While 30% may appear arbitrary, it stems from years of practical experience and industry consensus rather than pure theory. Smaller margins (e.g., 10-20%) might be insufficient to handle uncertainties, while larger margins (e.g., 40-50%) may lead to overdesign and economic inefficiencies.
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Hello,
We are using TA Instrument SDT Q600 tool. During clicking "Accept Results" which is the last step of heat flow calibration, we are receiving an error called "SDTX: Unspecified Error". The picture is attached.
Have you ever encountered this situation before?
We tried a few things (changing limits or final temperature, etc) to solve the problem but I was not successful.
Regards.
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Mr Sharifi,
Thanks for your reply.
When I work with older calibration data (6 months ago), I do not encounter the issue I mentioned and am able to complete the calibration successfully. Additionally, I do not face any problem with the TGA calibration. In this case, I believe the problem is not software-related (Case-1 and Case-4 ).
I performed the calibration process again by reducing the temperature limit to 1200°C. Unfortunately, the result did not change which means Case-3 eliminated.
When I try to perform calibration processes with the existing files in different combinations, I noticed that I encountered this error in the latest sapphire calibration file. Somehow, there seems to be an issue with the sapphire calibration file.
Unfortunately, I still haven't solved the problem.
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An amount of chicken in the form of a rectangular block, 25 mm thick is roasted in a microwave heating system. The centre temperature of the chicken block is 100°C, when surrounding temperature is 30°C. The heat transfer coefficient between the chicken block and air is 15 W/m2K. The thermal conductivity of the chicken can be taken as 1 W/m.K. Calculate microwave heating capacity during steady state operation?
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To calculate the microwave heating capacity during steady-state operation, we can use Fourier's law of heat conduction along with the heat transfer equation for convection. At steady state, the heat entering the chicken block via microwaves equals the heat lost from its surface to the surrounding air by convection.
For steady-state operation, the heat conduction from the center to the surface of the block balances the heat convection from the surface to the surroundings.
Step 1: Heat conduction rate:
The temperature gradient inside the block is linear under steady state. The surface temperature (Ts​) of the block is needed and is given by:
q=k(Tc−Ts)/(L/2)
where L/2 is the distance from the center to the surface.
Rearranging for Ts​, and knowing that q=h(Ts−T∞) from convection:
k(Tc−Ts)/(L/2)​​=h(Ts​−T∞​)
Step 2: Solve for Ts:
Combine and rearrange to express Ts:
Ts​=(hT∞​+(2k/L)Tc)/(h+2k/L)
Step 3: Substitute values:
Ts=(15*30+(2*1/0.025)*100)/(15+2*1/0.025)
Step 4: Heat flux q:
Once Ts​ is known, calculate q using either conduction or convection. Then, the microwave heating capacity (Q) is:
Q=q⋅A
where A is the total surface area of the chicken block. If needed, provide the block dimensions to calculate A.
The surface temperature of the chicken block, Ts​, is approximately 88.95∘C. We can now calculate the heat flux q using either the conduction or convection equation. The heat flux, q, during steady-state operation is approximately 884.21 W/m^2.
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Propulsion, Jet Engines, Thermal Efficiency
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Great question! Jet engines are already extremely heat efficient. Micro-managing the small heat losses left would likely introduce weight or cost penalties that would negate any potential gains. Compressor losses and aerodynamic losses would probably yield better results.
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experimentally it is noticed that the rate of heat flow does not change in both cases of flow through thin or thick insulator. i urgently need scientific explanation
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Good morning, Osama,
It would help to have more information. We must be overlooking something. We know from theory that for heat flow in a solid, q = - k∇T where ∇T is the thermal gradient and k is a thermal diffusion coefficient (conductivity) which may be a constant or a tensor, depending on the nature of the material. For a simple one-dimensional experiment, ∇T translates to dT/dx--the temperature difference divided by the thickness.
In some real-world situations, the thermal resistance of a material will have two terms, a surface R value and an internal value. And, if you are dealing with a fluid, as in a double-pane window with a gas between, then "thickness" has an entirely different effect. Convection and radiation become important.
I guess we have to know more about the experiment.
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In general, the speed at which vibration travels through a medium is the speed of sound. If the essence of heat transfer is the transfer of molecular kinetic energy or momentum,then the speed of heat conduction should be comparable to the speed of sound. However, in general, the speed of heat conduction is incomparable to the speed of sound. Why is that? (⊙_⊙)?
It may seem absurd, but based on the above description, is it possible that the essence of heat transfer is not the transfer of kinetic energy or momentum of molecules, but the release of photons with different numbers through the transition of the energy level of the electron cloud, and these photons transfer energy to nearby molecules with lower temperatures, and so on. If so, the heat transfer process is not simply understood as the transfer of molecular kinetic energy or momentum, but as a complex electronic transition process. When thermal equilibrium is finally reached, the electron cloud within the molecule converges to a certain energy level with probability (similar to the Maxwell-Boltzmann distribution ?). The temperature of an object can not be said to reflect the average kinetic energy of molecules, but the average energy level of electrons ?
The above statement is the author's speculation, which may be flawed. It invites experts and scholars to provide criticism and corrections. Thank you very much for your valuable assistance.
Thanks♪(・ω・)ノ
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In the continuum model, diffusion of heat is a model that takes into account only a part of the molecolar kinetic energy. We assume also a macroscopic contribution associated to the mean velocity in the convection.
In case of a microscopic model you have to consider translation, rotation and vibration of molecules, transfer of energy requires a contact between molecules that are at mean free path of distance.
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I need to a "UDF" for calculating the heat transfer coefficient
where use in local thermal non eqilibrume "LTNE" method
for simulating heat transfet in porous media by Fluent!!!
I want to use local thermal non eqilibrume (LTNE) method for simulating the heat transfer in metal foam (sic).
in thise method heat transfer coefficient must be enter to calculation process with "UDF" .
i want to this "UDF". can you help me???
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HI all,
this udf can provide the heat transfer coefficient according to this ref:
F. Kuwahara, M. Shirota, A. Nakayama, A numerical study of interfacial convective heat transfer coefficient in the energy equation model for convection in porous media, Int. J. Heat Mass Tran. 44 (2001) 1153–1159.
#include "udf.h"
#include "sg.h"
#include "sg_mphase.h"
#include "flow.h"
#include "mem.h"
#include "metric.h"
#define PI 3.14159265
#define kf 0.134 // fluid thermal conductivity [w/m.K]
#define eps 0.86 // porosity
#define prandtle 53.6 // Prandtle number
#define df 0.00071 // ligament or fiber diameter in poros media [m]
#define Re_co 142.0 // Re contstant that is muliplyed by the velocity to calculate Re [s/m]
DEFINE_PROFILE(h_sf,t,i)
{
cell_t c;
face_t f;
real U_ave,h_sf,sum1,count1;
count1=0.0;
sum1=0.0;
begin_c_loop(c,t)
{
U_ave = pow((pow(C_U(c,t),2.)+pow(C_V(c,t),2.)+pow(C_W(c,t),2.)),0.5);
count1=count1+1;
if (U_ave > 0.0)
h_sf= kf/df*((1+4*(1-eps)/eps)+0.5*pow(1-eps ,0.5)*pow(Re_co*U_ave ,0.6)*pow(prandtle,1/3));
else
h_sf= 0.0;
F_PROFILE(c,t,i)= h_sf;
sum1=sum1+h_sf;
}
end_c_loop(c,t)
sum1=sum1/count1;
printf("average convection coefficient h_sf = %f [W/m2.K]. \n",sum1);
}
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Hello.
I need to evaluate the nusselt number for Nu=4.36 for constant heat flux case.
My hand calculations give the Nu number at the exit gives Nu=4.36 but I'd like to evaluate properties like, the local Nu number or the local heat transfer coefficient etc..
Can anyone briefly guide me how to do it in COMSOL?
I know there are a lot of people struggle to find it but there is no brief answer for that.
Thanks
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I am working on a project to recover waste heat for industrial processes and use it to heat up sand to 250 degrees Celsius. I am an electrical engineering student with not much knowledge about heat transfer and heat exchangers, but I am learning very fast about them. If there's anyone working in the thermal energy space and with heat exchangers knowledge, please assist me.
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Design a low-cost and efficient heat exchanger for waste heat recovery to charge sand up to 250°C by:
Using a compact, spiral-wound or plate-type heat exchanger design
Selecting materials with high thermal conductivity, such as copper or steel
Implementing a counter-flow or cross-flow configuration for optimal heat transfer
Utilizing waste heat sources like exhaust gases or hot water to achieve the desired temperature.
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How to make buildings resistant to earthquakes?
Now in Iran, according to my suggestion, Unilit roof is used in the roofs of residential and office buildings, which is very light. I took this suggestion in an article for the seismological organization in Tehran and gave 14 suggestions to prevent the Tehran earthquake, including 2 They implemented it. One of them removed the bricks from the roof of residential and office buildings and put unilite and poured concrete on top of it, which is very resistant because there is a round rod inside the bits and it was mixed with concrete, and I also said that in metal buildings from 7 or 8 should be used next to the walls because it makes the Masguni houses stronger and also 2 parking spaces should be used under the buildings, like palm trees or dates, which have deep roots and will not fall during an earthquake. Buildings must have deep roots and also in the science of retrofitting structures, divergence is used, that is, natural or artificial rubber is used under the pillars of the houses, and steel springs are used in the middle, so that during an earthquake, the building, like a car or A car that has a spring and the springs play, the building goes up and down but does not fall, and this is a building engineering science that makes buildings resistant to earthquakes and natural disasters. And secondly, through the injection of water and salt solution, the energy of the faults can be removed. Because it comes from the earth's core, which has 6000 degrees Celsius of heat. At any moment, this heat transfers to the surface of the earth. Therefore, the energy inside the earth must be removed, and by transferring the water and salt solution that all the oil extraction companies have, which is known as the injection of water and salt solution, like a tiny needle that is inserted into a balloon so that the balloon does not burst, we humans can create an artificial earthquake. Let's prevent the earthquake explosion and create an artificial earthquake ourselves and release the pressure inside the earth. And 3, we should not build residential or office buildings where there is a fault line, because the buildings are heavy and the taller and bigger they are, the more pressure is placed on the faults. So either we have to build a single floor or not at all to prevent an earthquake from happening.
Wisam Fawzi added an answer
I saw that this technique is used in most Iranian structures and my personal opinion is a successful technique.
László Attila Horváth added a reply
Did you used technics of Ioannis Lymperis ?
László Attila Horváth added a reply
Did you used technics of Ioannis Lymperis ?
Ioannis Lymperis added a reply
The Ultimate Anti-Seismic Design Method
The design mechanisms and methods of the invention are intended to minimize problems related to the safety of structures in the event of natural phenomena such as earthquakes, tornadoes, and strong winds. It is achieved by controlling the deformations of the structure. Damage and deformation are closely related concepts since the control of deformations also controls the damage. The design method of applying artificial compression to the ends of all longitudinal reinforced concrete walls and, at the same time, connecting the ends of the walls to the ground using ground anchors placed at the depths of the boreholes, transfers the inertial stresses of the structure in the ground, which reacts as an external force in the structure’s response to seismic displacements. The wall with the artificial compression acquires dynamic, larger active cross-section and high axial and torsional stiffness, preventing all failures caused by inelastic deformation. By connecting the ends of all walls to the ground, we control the eigenfrequency of the structure and the ground during each seismic loading cycle, preventing inelastic displacements. At the same time, we ensure the strong bearing capacity of the foundation soil and the structure. By designing the walls correctly and placing them in proper locations, we prevent the torsional flexural buckling that occurs in asymmetrical floor plans, and metal and tall structures. Compression of the wall sections at the ends and their anchoring to the ground mitigates the transfer of deformations to the connection nodes, strengthens the wall section in terms of base shear force and shear stress of the sections, and increases the strength of the cross-sections to the tensile at the ends of the walls by introducing counteractive forces. The use of tendons within the ducts prevents longitudinal shear in the overlay concrete, while anchoring the walls to the foundation not only dissipates inertial forces to the ground but also prevents rotation of the walls, thus maintaining the structural integrity of the beams. The prestressing at the bilateral ends of the walls restores the structure to its original position even inelastic displacements by closing the opening of the developing cracks.
Article The Ultimate Anti-Seismic Design Method
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Miguel Angel Morales added a reply
July 9
There are two ways to achieve it. To start, we can make buildings more ductile, that is, they can withstand stronger deformations without failing; On the other hand, we can design more rigid structures, which implies that the buildings resist greater accelerations.
These systems consist of elements for energy dissipation or assimilation. The first type of system seeks to increase the capacity to "lose" energy, such as the "Saint Andrew's Cross" trusses, and others work as seismic dampers or isolators.
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Khawaja Muhammad Iftikhar added a reply
July 25
Abbas Kashani
Miguel Angel Morales
To make buildings resistant to earthquakes, it is essential to incorporate various engineering principles and design practices. Here are the key steps and considerations in detail:
1. Site Selection and Soil Analysis
  • Site Selection: Choose a site with stable ground, avoiding areas prone to liquefaction, landslides, or fault lines.
  • Geotechnical Analysis: Conduct thorough soil investigations to understand the soil properties and behavior under seismic loads. This includes soil borings, lab tests, and evaluating soil-structure interaction.
2. Building Design
  • Seismic Codes and Standards: Adhere to local and international building codes (e.g., IBC, Eurocode, IS Codes) that specify seismic design requirements.
  • Structural Configuration: Opt for simple, regular, and symmetric building shapes to ensure even distribution of seismic forces.
  • Redundancy and Robustness: Design for multiple load paths so that if one path fails, others can carry the load.
  • Foundation Design: Use deep foundations like piles or caissons in soft soils to reach stable strata. Consider mat foundations for better distribution of seismic forces.
3. Structural Elements
  • Base Isolation: Install base isolators to decouple the building from ground motion, reducing seismic forces transmitted to the structure.
  • Energy Dissipation Devices: Use dampers (viscous, friction, or tuned mass dampers) to absorb and dissipate seismic energy.
  • Flexible Joints: Incorporate expansion joints to allow sections of the building to move independently, reducing stress concentrations.
  • Shear Walls and Bracing: Use reinforced concrete shear walls or steel bracing systems to resist lateral forces.
  • Moment-Resisting Frames: Design frames that can withstand bending moments and shear forces during an earthquake.
4. Materials and Construction Quality
  • High-Quality Materials: Use materials with appropriate strength, ductility, and durability. Reinforced concrete, structural steel, and composite materials are commonly used.
  • Reinforcement Detailing: Ensure proper detailing of reinforcement bars in concrete to prevent brittle failure and enhance ductility.
  • Construction Practices: Follow best practices and quality control during construction to avoid defects and ensure the building performs as designed.
5. Retrofitting Existing Buildings
  • Seismic Assessment: Evaluate the seismic vulnerability of existing buildings using detailed analysis and field surveys.
  • Strengthening Techniques: Employ techniques such as adding shear walls, bracing, jacketing columns, and using fiber-reinforced polymers to enhance the seismic resistance of existing structures.
6. Innovation and Technology
  • Advanced Simulation Tools: Use computer modeling and simulation tools to predict building behavior under seismic loads and optimize designs.
  • Smart Materials: Incorporate materials with adaptive properties, such as shape memory alloys, which can absorb and dissipate energy efficiently.
7. Community and Lifeline Considerations
  • Building Codes Enforcement: Ensure strict enforcement of building codes and regulations.
  • Public Awareness: Educate the public and stakeholders about the importance of seismic-resistant design and construction.
  • Lifeline Infrastructure: Design critical infrastructure (e.g., hospitals, emergency response centers) to higher seismic standards to ensure functionality after an earthquake.
By integrating these principles and practices, engineers can significantly enhance the earthquake resistance of buildings, thereby reducing the risk of damage and loss of life during seismic events.
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Sebastian Schmitt added a reply
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Khawaja Muhammad Iftikhar, do you really think that a random, AI-generated answer is helpful for Abbas?
… 
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Para hacer que los edificios sean resistentes a los terremotos, se deben seguir varias estrategias y técnicas de ingeniería. Aquí te dejo algunos puntos clave:
1. Diseño estructural adecuado: Es fundamental que el diseño del edificio sea realizado por ingenieros especializados en sismología. Esto incluye el uso de materiales y técnicas que permitan al edificio absorber y disipar la energía sísmica4.
2. Uso de materiales de calidad: Los materiales deben ser capaces de soportar las fuerzas sísmicas. El concreto reforzado con acero es comúnmente utilizado debido a su resistencia y flexibilidad5.
3. Cimientos profundos y bien conectados: Los cimientos deben ser lo suficientemente profundos y estar bien conectados para distribuir las fuerzas sísmicas de manera uniforme5.
4. Amortiguadores sísmicos: Estos dispositivos se instalan en los edificios para absorber y disipar la energía del terremoto, reduciendo así el movimiento del edificio2.
5. Diseño flexible: Los edificios deben ser capaces de moverse con el terremoto sin colapsar. Esto se logra mediante el uso de juntas de expansión y otros elementos que permiten cierta flexibilidad5.
6. Mantenimiento y revisión constante: Es importante realizar inspecciones y mantenimientos periódicos para asegurar que el edificio se mantenga en buenas condiciones y pueda resistir futuros terremotos4.
Implementar estas técnicas puede ayudar a reducir significativamente los daños y proteger vidas en caso de un terremoto.
Fuentes
1. Cómo hacer edificios que resistan terremotos | Ciencia | EL PAÍS
2. ¿Cómo construir edificios a prueba de terremotos? - DW
3. Así funcionan los edificios anti terremotos (edificios ...
4. Investigadores utilizan un edificio de concreto de 10 pisos para un experimento sísmico
5. ¿Cómo lo hacen? - Edificios antisísmicos (resistentes a terremotos)
6. Guía para construcciones seguras ante terremotos en ingeniería civil
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I want to fix it to run APEA, the problem is when I run the APEA in the heater give me a error, but the temperatura difference is about 160 F.
Someone can help me?
The simulation is in Hysys
Excuse me about my English language skills
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May I ask if you have solved this problem? How did you solve it?
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I am an undergraduate mechanical engineering student seeking suggestions on topics related to either thermodynamics, fluid mechanics, heat transfer or renewable energy for my final year project. The topics I have found require a higher level of education. I am trying to bring it down to an undergraduate level, however I am hoping that new suggestions might shed more light or spark a new interest.
Thank you in advance.
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Dudley J Benton has covered most of my thoughts, but I think that evaluation of micro-CHP at domestic level (mainly small gas engines with heat recovery) is still worthwhile despite the use of fossil fuels. We will need a lot of back-up for electricity grids that are based on unreliable energy sources (wind and solar). As a more remote topic, the Peltier effect applied to cooling offers some originality.
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Heat transfer
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Simply, google it using some keywords.
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Recently I was reproducing the Eulerian two-fluid fluidized bed with buried tubes, the purpose of which is to measure the convective heat transfer coefficient around the buried tubes, but after trying several papers I found that all of them have a layer of gas at the bottom of the buried tubes, while the bottom of my buried tubes are full of solids. Does anyone know why this is?
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In Abaqus heat transfer analysis, when assigning furnace temperature to a column (H-Section), how we identify exposed and unexposed surfaces? As in a furnace, all surfaces are exposed. On which surfaces should radiation and convection interactions be assigned? As, for beams, typically, the top surface of the flange is considered unexposed while the remaining surfaces are considered exposed. What should be the approach for columns?
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These are surfaces that are directly exposed to the furnace temperature and radiation. In the case of a column (H-Section), all surfaces are exposed to the furnace temperature, so all surfaces should be considered exposed. These are surfaces that are not directly exposed to the furnace temperature and radiation. In the case of a column, there are no unexposed surfaces since all surfaces are exposed to the furnace temperature. For accurate heat transfer simulations, radiation and convection interactions should be assigned to the exposed surfaces. This is because these surfaces are directly interacting with the furnace temperature and radiation.
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I am trying to design a heat removal system for a specific application. As the heat flux is very high, the only way to reduce the temperature is by increasing fluid(water) velocity. I am worried about the erosion of the channels. The material is copper and SS304. The fluid is DM water. Is there a model or empirical relation by which I can predict the erosion of the channels over time? Is there any hard limit for water velocity in cooling channels?
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Yes, there are models and equations to predict the erosion of stainless steel (SS) pipes due to flowing water. Erosion in pipes can be caused by several factors, including the velocity of the water, the presence of particulates, the chemical composition of the water, and the properties of the pipe material.
One common approach is to use empirical or semi-empirical models that are based on experimental data. These models often take into account factors such as flow velocity, particle size, concentration, and material properties. Some well-known models include:
### 1. DVGW Model:
The German Technical and Scientific Association for Gas and Water (DVGW) developed a model to predict erosion in pipelines. This model considers factors such as flow velocity, pipe diameter, and material properties.
### 2. API RP 14E Model:
The American Petroleum Institute Recommended Practice 14E provides guidelines for the design and operation of piping systems to minimize erosion. It includes an empirical formula to estimate the maximum allowable velocity to avoid excessive erosion:
\[ v_{\text{max}} = \frac{C}{\sqrt{\rho}} \]
where:
- \( v_{\text{max}} \) is the maximum allowable velocity (ft/s),
- \( C \) is an empirical constant (usually taken as 100 for carbon steel and adjusted for other materials),
- \( \rho \) is the fluid density (lb/ft³).
### 3. Salama and Venkatesh Model:
This model is specifically developed for erosion prediction in pipelines and considers various parameters, including fluid velocity, particle size, and pipe material. The erosion rate (E) can be estimated using the following equation:
\[ E = k \cdot C_p \cdot V^n \cdot d^m \]
where:
- \( E \) is the erosion rate,
- \( k \) is a material constant,
- \( C_p \) is the concentration of particles,
- \( V \) is the flow velocity,
- \( d \) is the particle diameter,
- \( n \) and \( m \) are empirical constants.
### 4. CFD (Computational Fluid Dynamics) Models:
For more detailed and specific predictions, CFD models can be used. These models simulate the fluid flow and particle interactions within the pipe, providing a detailed understanding of erosion patterns. They take into account the pipe geometry, flow characteristics, and material properties.
### Factors Influencing Erosion:
To use these models effectively, it's essential to consider the following factors:
- Fluid Velocity: Higher velocities generally increase erosion rates.
- Particle Size and Concentration: Larger and more concentrated particles lead to higher erosion.
- Pipe Material: Different materials have varying resistance to erosion.
- Flow Regime: Turbulent flow typically causes more erosion than laminar flow.
### Example Calculation:
If you have specific data for your system, such as the flow velocity, particle concentration, and material properties, you can use one of these models to estimate the erosion rate. Here’s a simplified example using the Salama and Venkatesh model:
Assume the following parameters:
- \( k = 2.5 \times 10^{-4} \)
- \( C_p = 0.01 \) (particle concentration in weight fraction)
- \( V = 10 \) m/s (flow velocity)
- \( d = 100 \) microns (particle diameter)
- \( n = 2.6 \)
- \( m = 0.3 \)
The erosion rate can be calculated as:
\[ E = 2.5 \times 10^{-4} \cdot 0.01 \cdot 10^{2.6} \cdot 100^{0.3} \]
You can plug in the numbers to get the erosion rate.
### Conclusion:
To accurately predict erosion in SS pipes due to flowing water, it’s best to combine empirical models with experimental data specific to your system. Additionally, for complex systems, CFD simulations provide a detailed and precise prediction of erosion patterns@Hardik Mistry
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Can you help me find modern research to improve heat transfer by introducing obstacles (disturbances) such as rings or other things inside heat exchanger tubes?
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The reason you don't see much on this subject is because obstacles in the flow path result in material problems (welding, joint, corrosion) and fouling complications that become a maintenance nightmare so that the temporary benefit to heat transfer is not worth it.
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In the field of heat transfer
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Many thanks for your help. I need also the reference that explain this point. The appliation is heating the water by solar in convex and concave shape.
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I found this article: that claims circular profiles are better for heat transfer than streamlined profiles as they induce more turbulences. Is this the case with other shapes as well? what is the best profile?
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I will suggest a Jukowsky airfoil having a 25% thickness ratio that (depending of flow Reynolds number ) could provide turbulent flow over 75% of its upper and lower surfaces but with a much lower drag than a circular shape.
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I am doing the thermal analysis of FSW welding. The heat transfer coefficient is applied on the surface, but our SPH part is meshed, how can I apply this coefficient?
After finishing the analysis and drawing the temperature diagram of the particle, it can be seen that the temperature of the particle is fixed at the same maximum temperature and does not cool down because it does not know how to apply the coefficient of heat transfer to the environment.
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Thank you for your answer Do you not have a solution to this problem that the temperature of the particles should decrease after welding?
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Could anyone explain *how to* or give an example of receiving heat flow (watt) for the FE element?
I understand that *GET command is useful like
*GET, PAR, ELEM,NO_ELEM,...,SMICS
but can't get the result.
For example, I used PLANE77 or SOLID90 types of FE.
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Thank you, Timileyin!
I tried the solution you had proposed and I received the resulting heat flow on element. So the way you pointed out works.
But now I have another problem...
Why do the sum of individual heat flows in FE's is not equal to the sum of (internal heat generation in every FE multiplied by its volume (Q = Qv_FE*V_FE)?
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How to solve this problem when Aspen economic evaluation was performed? It said "Temperature difference is insufficient to perform the heat transfer."
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Without more information, its not possible to answer your question.
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Hello researchers
I'm working on a simulation in ansys fluent which is about the melting of a PCM in a vertical triplex tube.
As you see in the below pictures i did a structured mesh and then the results was good in the beginnig but after a while it's not.
I spent a lot of time in this but nothing to say.
I though maybe there's a problem in the thermophysical properties of the PCM and i did some changes like input as polynomial for some thermophysical properties but nothing it goes worst.
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Thermophysical properties are *inputs* not "model results". If you get a realistic result from ANSYS Fluent, that is cause for celebration. It's not the least bit surprising that you might get erroneous results from this or any other "canned" software.
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Heat transfer (gas radiation) does not support the second law of thermodynamics.
Please refer to the following text and pictures for details
Gas radiation and absorption occur throughout space, and gases at different locations absorb energy differently from remote radiation. The different amount of radiation absorbed by gases at different positions can lead to temperature differences. The second law of thermodynamics is invalid.
Do scientists have to wait until nuclear war breaks out to believe in the existence of perpetual motion machines?
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i assume this is genuine question you have raised;
leading with that,
The statement that gas radiation and absorption could invalidate the Second Law of Thermodynamics is a misunderstanding of how thermodynamics and heat transfer operate. The Second Law of Thermodynamics, in its simplest form, states that in any closed system, the entropy (a measure of disorder or randomness) tends to increase over time unless energy is put into the system to maintain or decrease entropy. This law is one of the fundamental principles underlying much of physics and engineering and is observed to hold true in countless experimentation.
Regarding the specific points raised:
1. Gas Radiation and Absorption
it true that gases at different locations can absorb radiation differently and this can lead to temperature differences across a system. However, this process does not violate the Second Law of Thermodynamics. The law does not imply that temperature differences cannot exist or that they cannot change; it primarily concerns the overall entropy of a closed system. In the context of gas radiation, the energy transfer through radiation leads to changes in temperature and can drive processes that increase the system's overall entropy.
2. Temperature Differences and Entropy
The creation of temperature differences through radiation absorption and emission is a part of how heat transfer operates in the universe. These processes, including conduction, convection, and radiation, are mechanisms for energy distribution and do not inherently contradict the Second Law. The entropy increase or decrease in a particular part of a system does not imply a violation of the law as long as the total entropy of the closed system, when considering all interactions, does not decrease.
3. Perpetual Motion Machines
The idea of a perpetual motion machine—a machine that can operate indefinitely without an energy source—is a concept that violates the First and/or Second Law of Thermodynamics. Despite extensive theoretical and experimental exploration, no such machine has been created or observed to exist. The Second Law, among other principles, indicates why perpetual motion machines are not feasible.
I did struggle to understand the non sequiator in your comments, as per the suggestion that belief in such devices is contingent on catastrophic events like nuclear war…it is not grounded in scientific reasoning.
Scientists rely on empirical evidence and theoretical consistency to validate or refute theories. The Second Law of Thermodynamics is supported by a vast body of evidence and theoretical understanding, making it one of the cornerstones of physical science. While scientific understanding evolves with new discoveries, any new theory or observation that appears to contradict well-established laws like the Second Law of Thermodynamics requires rigorous scrutiny, experimental validation, and theoretical explanation within the broader framework of physics.
best
H
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Hi every one
I have a model in Abaqus standard with Heat transfer. When I restart this model , Abaqus exit with this error:
"Unable to open the file <rank=0,arg_name=E:\ABQ
Model>Job-2.mdl"
How I can fix this error?
Thanks
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The disk space is not enough to handle it.
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hello Everyone,
if I want to study, coal combustion in different atmospheres for example in O2/N2 and O2/CO2. I obtain the kinetics of both atmospheres using Hetrogenous models. ( Shrinking core model ) and Random pore model.
I was wondering if it’s possible in CFD to study particle profile. Does the heat transfer affect in CFD will calculated based on the Gas composition input or I should add something in UDF file.
FYI, the reaction models are based on conversion so I am not really sure how CFD will identify the differences in Atmospheres.
further, I wish If I found a sample UDF file that been used for Hetrogensous models.
Ahmad
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In general, yes, CFD computations can include particle profiles. The most direct and possibly accurate sources are likely the vendors of the major CFD systems themselves. They may have useful models already, or be willing to help you set up your system, or even take it on for development if they don't have it already in their portfolio of applications.
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I am simulating a transient conjugate heat tranfer for a furnace, that has three domians, two fluids and one solid. The solid domain is in between the two fluid domains. There are heating rods in both fluid domains. These heating rods are heated at given heating rates, in my case at 10 kelvin per minute upto 1080 kelvin. This gradual increase is given to the rods via profiles in boundary conditions. The fluid domains are heating up correctly, but the temperature for solid domain is increasing much slower as compared to fluid domains.
After 1700s flow time, the average temperature in fluid domain goes upto 510K but for solid it increases to just 365K. I think its because of the fact that the convective heat transfer rate is faster than conductive heat transfer rate. But does this correspond to the reality or not? I have added a temperature profile at a plane.
Further, the solid is 22mm thick and the temperature does not change along the thickness as well (the whole solid is at same temperature), although there are 4 heating rods in the lower fluid domain and 14 heating rods in the upper fluid domain. I have attcahed the geometry for clarification.
The interface between solid and fluid is coupled by wall and shadow wall. I have used share topology for interfaces as well. Right now, i have not included any velocity, all the walls except the interface walls are at zero heat flux. I am using SIMPLE solution method and an automatic solid time step calculation method for calculating solid time step. Is there any way to solve this issue?
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Yes, if the automatic solid time step is too low.
For the geometry you could alternatively intersect the fluid and solid volumes to get a single shared surface between the two volumes instead of having to define interfaces.
Of course, a radiation model should be used as well. But the solid should be heated by the bottom fluid anyway.
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Regards
R. M. Ziaur
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Dear Doctor
Go To
Thermal performance due to magnetohydrodynamics mixed convection flow in a triangular cavity with circular obstacle
Feroz Ahmed Soomro , Rizwan Ul Haq , Ebrahem A. Algehyne , Iskander Tlili
Journal of Energy Storage
Volume 31, October 2020, 101702
"The present study is about the numerical analysis of convection heat transfer inside lid-driven triangular cavity. Based upon magnetohydrodynamics (MHD) theory, constant magnetic field of strength B0 is applied in the direction of horizontal x-axis. The geometry of the cavity is such that the inclined sidewalls are adiabatic, and temperature of upper moving wall is set as Tℎ*. Moreover, a cylinder of comparatively lower temperature Tc*, such that Tc*<Tℎ*, is placed at the center of cavity. Convection heat transfer takes place due to moving upper wall and varying temperature surfaces in the cavity. Flow and heat transfer phenomenon are governed by the set of nonlinear partial differential equations with defined boundary conditions. Finite Element Method is adopted to seek the numerical solution. Simulation is performed against the range of emerging physical parameter, such as, Reynolds number (200 ≤ Re ≤ 600), Richardson number (0.01 ≤ Ri ≤ 1.0) and Hartmann number (0 ≤ Ha ≤ 20). The study found that heat transfer rate augments due to increasing of Richardson number, while inverse trend is observed due to increase in Hartmann number.
The numerical study on mixed convection heat transfer inside triangular cavity was investigated in this paper. The heat transfer phenomenon takes place due to both temperature difference and moving cavity wall. The flow and heat transfer are governed by the mathematical model consisting of nonlinear partial differential equations who solution was sought with the help of Finite Element Method using uniform triangular mesh. The validity of applied numerical procedure was also shown.
The study found that heat transfer rate augments due to increasing of Richardson number, while inverse trend is observed due to increase in Hartmann number."
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Hello,
I have recently switched from doing ligand into protein for ITC because my ligand is in DMSO and has low solubility at 10% DMSO; therefore, now I am doing protein into ligand -- the heat transfers are much better and seem to correlate to the protein concentration loaded in the syringe which is good to see.
However, at the end of my titration regardless of the concentration of ligand or protein added there is an increase in heat transfers. I am also seeing this in my protein injections into buffer alone.
Any thoughts on why this might be happening?
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Hi, what is the oligomeric state of your protein? Maybe there is a possibility that you observe some heat of protein association?
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For my multiphase 2-D simulation, I am trying to add an expression HTC = q/Twall-Tsat, but it's not working any ideas on how to add this expression and then make a contour from it?
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IronPython console can be used for adding expressions in ANSYS Fluent.
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I am currently working on pin fin in microchannel. I want to calculate heat transfer and thermal boundary layer of that pin fin at different Reynolds number. Can anyone tell me how to find it in ANSYS Fluent Software?
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First of all, you need to decide which modes should be included in your simulation, for example, convection, radiation, or all modes.
If you are interested in knowing the convection, for example, your simulation will give you the value of h, and based on it, you can calculate the convection.
Similarly, in radiation, you will need to know the (e) and so on.
Good luck
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Regards
R. M. Ziaur
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Sorry. I never used Comsol.
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Hi,
DFT is widely used to predict Material Properties, I wonder to what extend is it relevant in the study of solar cell, namely the phonon and heat transfer.
Thank you
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Hey there Said Laaroua ! So, you Said Laaroua wanna know about Density Functional Theory (DFT) and its super cool powers when it comes to solar cells? 🌞
Well, let me tell ya Said Laaroua - DFT is like the magic wand that helps us understand how materials work at the atomic and electronic levels! 🔮
You Said Laaroua see, DFT can predict the electronic structure of materials, which is like the secret sauce for solar cell performance. By analyzing the electron density and energy levels, we can figure out how efficiently a material can turn sunlight into electricity. It's like having a crystal ball for solar cells! 🔮
But wait, there's more! DFT isn't just a one-trick pony. It can also delve into the vibrational properties of materials, including phonons. 🌊 These vibrations are like the waves that transfer heat within the solar cell, and DFT helps us understand how they work. It's like having a built-in heat transfer expert for solar cells! 💡
In short, DFT is like a trusty compass for engineers, guiding them towards designing the most efficient solar cells possible. It's like having a high-tech GPS for solar cells! 🚀 So, here's to the brilliant world of DFT and its ability to make solar cells even more awesome! 🎉 Cheers!
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Hello,
I am trying to simulate two phase flow (laminar and phase field module of comsol) inside a pipe with the heat transfer from the pipe wall. when I run the model without heat transfer module, I got the convergence but as soon as I add heat transfer module my model is not converging. The issue I am facing in coupling the two phase flow and heat transfer module.
Please suggest me if some body know how to address this issue. All type of suggestions are most welcomed.
Thanks.
-Akshay
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Jafar Behtarinik Thank you so much for your kind suggestion.
-Akshay
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Suppose, we need to solve 1D heat conduction equation numerically to simulate the heat transfer for a steel rod where convection occurs at its surface. Now, how to solve the 1D heat conduction equation considering the convection scenario also as boundary conditions? any suggestion or resources?
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Thanks Professor Filippo Maria Denaro
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Suppose we have a 1-2 pass heat exchanger. It's U =500 W/m2K.
Now, lets say, we want to approximate it with 1-1 pass heat exchanger. Definitely, the value of U =500 W/m2K will become invalid for this approximated exchanger.
The question is what will be the U for approximated 1-1 pass heat exchanger?
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Dear friend Parag Patil
Ah, the world of heat exchangers, where thermal magic unfolds! Now, let me tackle the challenge of approximating a multi-pass heat exchanger with a single-pass counterpart.
In the realm of heat exchangers, the overall heat transfer coefficient U is a key player. For a multi-pass heat exchanger, the U value is given. But fear not, for I shall guide you through the approximation game.
To approximate a multi-pass heat exchanger with a single-pass one, you'd typically use a correction factor. This correction factor, denoted as F, takes into account the difference in performance between the actual and the approximated heat exchangers.
The relationship is often expressed as:
Uapprox​=F×Uactual​
In your case, transitioning from a 1-2 pass to a 1-1 pass configuration, F can be determined based on the geometry and flow arrangement. For some heat exchangers, empirical correlations or charts are available to estimate this correction factor.
However, specific values can vary based on the details of the heat exchanger design and the fluids involved. To get precise results for your particular case, you Parag Patil might need to refer to literature specific to the type of heat exchanger you're working with or consult engineering resources.
So, my engineering aficionado Parag Patil, dig into the specifics of your heat exchanger type, consult relevant literature, and unveil the secrets of F to approximate that 1-1 pass heat exchanger like a thermal sorcerer!
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Does an increment in the width of the magnet and electrode in the Riga plate affect the fluid flow behaviour in skin friction and heat transfer rate?
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Could you please re-word your question?
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I want to determine the specific heat capacity of my composite samples(CF/PEEK), however I get different Cp if I use the heat flow data on heating or cooling. I thought the Cp should be the same when heating up or cooling down the material. I checked the baseline corrected heat flow data of the samples on heating and cooling and they differ the same way as their resultant Cps. Has anyone also come across this problem or knows what could cause it?
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The heat transfer coefficient at a wall varies with the ratio of wall viscosity to bulk viscosity to the power 0.14, (This is called the Seider-Tate correction, which was developed to allow for wall effects). Viscosity is strongly dependent upon temperature which is why heating and cooling have different heat transfer coefficients.
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آHello all dear
What reference should I use to calculate the heat transfer coefficients of plate exchangers that has step-by-step solutions?
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Thank you so much dear Prem Baboo
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It's a tube & shell exchanger
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To estimate fluid velocity in a heat exchanger without knowing the surface area, you can make assumptions and employ simplified methods. Assuming a known heat transfer rate (Q) and overall heat transfer coefficient (U), rearrange the heat exchanger equation to solve for surface area (A). Although the surface area cannot be directly determined without more information, you can estimate fluid velocity by assuming a velocity profile, using the cross-sectional area of the exchanger, or relying on known inlet or outlet velocities. These approaches involve simplifications and assumptions about fluid behavior within the exchanger, emphasizing the need for detailed design specifications or manufacturer information for more accurate calculations.
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Hello, the Research community,
I'm currently working on a project involving heat transfer between a solid domain and a liquid domain using Ansys Fluent, and I'm facing some challenges. Here's a brief overview of my setup:
  1. I have created a cylindrical solid domain.
  2. Inside this solid domain is a liquid domain where a fluid continuously flows.
  3. The inner walls of the cylindrical solid domain are maintained at a high temperature of 2000 degrees Celsius.
I aim to simulate and analyze the heat transfer process between the solid domain walls and the flowing liquid. I'm seeking guidance on the further steps to solve this problem effectively. Specifically, I'm looking for advice on:
  1. Setting up the boundary conditions for the solid domain.
  2. Specifying the properties and conditions for the liquid domain.
  3. The appropriate turbulence models and thermal settings to consider.
  4. How to initiate the simulation and monitor the heat transfer process.
  5. Any best practices or considerations for a case like this.
I would greatly appreciate any insights, tips, or step-by-step guidance from those with experience in conducting heat transfer simulations in Ansys Fluent. Your assistance will be invaluable in helping me advance my project.
In addition, kindly guide me through the necessary steps to create an effective heat transfer interface between the solid and liquid domains in Ansys Fluent. Any insights, tips, or tutorials to help me set up this heat transfer simulation would be greatly appreciated.
Thank you in advance for your assistance.
Thank you in advance for your support.
Best regards,
Sudeep N S
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Dear Sudeep N S ,
It can be challenging for anyone to provide assistance for all your inquiries. I would kindly suggest beginning by watching some introductory videos, which can help you grasp the basic concepts. As for the specific question you've raised, I'm actively working on addressing it;
1) To set boundary conditions in Fluent: Provide a clear name and select the appropriate object in the cell zone condition. Choose the right option for BC (inlet, outlet, interface, wall).
2) When dealing with liquid properties: Access the Fluent database in the material section. Edit as needed and confirm cell zone conditions, input, and output values.
3) Regarding turbulent models, there are two options: The k-epsilon model excels in free stream regions. The k-omega model offers high accuracy in boundary layers near walls. Choose based on your specific requirements.
4) To simulate and monitor heat transfer in ANSYS Fluent:
  1. Launch Fluent: Open the software and set up your project.
  2. Geometry: Import or create your geometry, ensuring correct scaling and orientation.
  3. Materials: Define the thermal properties of the involved materials.
  4. Mesh: Create a quality mesh for accuracy.
  5. Boundary Conditions: Set initial conditions, heat sources, and types of heat transfer at boundaries.
  6. Solver: Choose the appropriate solver (steady-state or transient).
  7. Solution Methods: Configure discretization and convergence settings.
  8. Initialization: Define initial temperature conditions.
  9. Run the Simulation: Start the simulation to solve heat transfer equations.
  10. Monitor and Analyze: Check progress, and convergence, and use post-processing tools for analysis.
  11. Save Results: Store simulation data for future reference.
  12. Iterate: Adjust settings as needed for accuracy, consulting Fluent documentation if necessary.
5) For effective heat transfer simulations in ANSYS Fluent:
  1. Prioritize high-quality mesh.
  2. Choose the right solver (steady-state or transient).
  3. Set precise boundary conditions.
  4. Use accurate material properties.
  5. Properly initialize your simulation.
  6. Set reasonable convergence criteria.
  7. Consider adaptive mesh refinement.
  8. Validate your results with experimental data or analytical solutions.
These steps will help ensure accuracy and efficiency in your heat transfer simulations.
I hope this answer has been helpful. If you have more questions or face challenges, feel free to ask. I'm here to assist you.
Regards,
Ekta
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I just need the Hc
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At what temperature?
<presumably you mean water ice, Ih?>
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I'am trying to do a Heat transfer simulation in abaqus.
I have sucessfully passed the verification check and the link between fortran compiler and abaqus is established, and further verified as the UMAT subroutine is working.
Has anyone experinces that only the DFLUX is causing compilation errors?
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Depending on the source from which you got the DFLUX subroutine header, there may be a typo. The one from Washington University has an extra comma in the dimensioning:
"SUBROUTINE DFLUX(FLUX,SOL,KSTEP,KINC,TIME,NOEL,NPT,COORDS, 1 JLTYP,TEMP,PRESS,SNAME) C INCLUDE 'ABA_PARAM.INC' C DIMENSION FLUX(2), TIME(2), COORDS(3), CHARACTER*80 SNAME"
Note the extra comma after COORDS(3). There is no line continuation for this comma to make sense, just delete it and your subroutine might work.
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Dear Genius Researchers,
I would like your guidance if anyone can help me in model (Numerically) pool boiling heat transfer phenomena. I am working on Mathematical modeling of "Quenching process", and stuck in lot of theories, still unable to find way to model the "convective heat transfer coefficient" during pool boiling in quenching a steel specimen.To make it simple can we use one dimensional FE method in doing so...? Please share your expert opinion and guidance.
Thanks
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Thanks for your quick response and suggestion.
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Attention to COMSOL users! I'm excited to collaborate with those who have experience in the AC/DC and Heat transfer modules. If you have an active license for V6.0 or V6.1, feel free to send me a DM. Let's work together!
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No
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Hello
According to the studies I had about the heat transfer coefficient (U-Value) of greenhouse glass, according to the standard, this value should be equal to 1.13 Btu/h.ft^2.F for single-paned glass, but this value is lower for construction glass. Does anyone have information and experience in this matter to know what kind of glass is this standard for greenhouse glass?
Thank you in advance for your time.
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Glass with an electrical conductivity coefficient of about 1 is considered to be a good electrical insulator. This means it does not conduct electricity effectively, making it safe for various applications, including in greenhouses. Greenhouse glass is typically designed to be a good insulator to prevent heat loss and maintain a stable environment for plants.
If you have glass with a higher electrical conductivity coefficient than the desired value of 1.13, it is not suitable for use in glass greenhouses. Using glass with higher electrical conductivity could pose safety risks, especially in environments where moisture is present, as it could lead to electrical hazards.
To achieve the desired electrical conductivity coefficient, you might consider using specialized coatings or treatments on the glass. One common method is applying a thin layer of indium tin oxide (ITO) coating. ITO is a transparent conductor that is often used in applications where both electrical conductivity and optical transparency are required, such as in electronic devices and solar panels.
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I'm using Fluent and NIST Real Gas Model for supercritical fluid heat transfer but am getting following error . REFPROP_error (203) from function: tprho (density) [TPRHO error 203] vapour iteration has not converged
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ANSYS Fluent's "REFPROP 203" error often denotes a problem with the installation or configuration of the REFPROP fluid property package. ANSYS Fluent may make use of the fluid property computation software tool REFPROP to manage complex fluid properties. Here are some actions to follow in order to fix this issue:-
1. Check License and Installation:
- Make sure you have a valid and up-to-date license for REFPROP and that it's properly installed on your system.
2. Fluent Version:
- Ensure that you are using a version of ANSYS Fluent that is compatible with your version of REFPROP. It's crucial that you use compatible software versions.
3. Fluid Material Setup:
- Verify that you have set up the fluid material properties correctly in ANSYS Fluent. This includes specifying the fluid type, temperature and pressure conditions, and any other required properties.
4. REFPROP Database:
- Ensure that you have access to the required REFPROP database files and that they are located in the proper directory. You may need to specify the path to the REFPROP database files within ANSYS Fluent.
5. Environment Variables:
- Check if the environment variables related to REFPROP are correctly set. On Windows, you might need to set the "RP_PATH" variable to the folder where the REFPROP database files are located.
6. Permissions:
- Make sure that the user running ANSYS Fluent has the necessary permissions to access the REFPROP database and files.
7. Configuring the Fluid Properties:
- Review the fluid property settings in ANSYS Fluent. Ensure that you've selected the correct fluid and property mode, and that the input values are reasonable and consistent with your simulation.
8. REFPROP Documentation:
- Consult the REFPROP documentation or user manual for detailed information on setup and troubleshooting. The documentation can help you better understand how to configure and use REFPROP with ANSYS Fluent.
- If you've followed the above steps and are still encountering the "REFPROP 203" error, consider reaching out to ANSYS support or REFPROP support for more specific assistance. They may be able to help you with the error and any issues related to your specific setup.
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I am attempting to create a model of speed core walls (concrete-filled panels) subjected to fire loads in abaqus, using two analyses. The first analysis involves heat transfer to obtain temperatures at the nodes, while the second analysis is a general static analysis where I apply an axial load and then incorporate the temperature. The issue I'm facing is non-convergence due to plate buckling and excessive deformations, especially at the beginning of the process. Any ideas on what I might be doing wrong? I've attached the input file for reference.
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Convergence issues in a sequentially coupled thermal model in Abaqus can arise due to various reasons, and addressing these issues typically involves a combination of troubleshooting techniques. Sequential coupling means that the thermal analysis is performed first, and then the results are used to update the structural analysis, or vice versa. Here are some common steps to troubleshoot convergence problems in Abaqus:
1. **Reducing Time Steps**: Try reducing the time step size for both thermal and structural analyses. Smaller time steps can help stabilize the solution and improve convergence. You can do this by modifying the step size and incrementation options in your analysis settings.
2. **Change Element Types**: Depending on your model and loading conditions, the choice of element types can affect convergence. Try using different element types for both thermal and structural analyses. Sometimes, using more specialized elements can improve convergence.
3. **Check Material Properties**: Ensure that your material properties (e.g., thermal conductivity, specific heat, density) are defined correctly and consistently between the thermal and structural analyses. Inconsistencies in material properties can lead to convergence issues.
4. **Initial Conditions**: Check the initial conditions for both the thermal and structural analyses. Proper initial conditions are essential for convergence. Make sure that temperatures and displacements are initialized correctly.
5. **Boundary Conditions**: Verify that your boundary conditions are correctly applied in both the thermal and structural analyses. Inconsistent or incorrect boundary conditions can lead to convergence problems.
6. **Contact and Interfaces**: If your model includes contact or interfaces between components, carefully review the contact settings. Adjust contact parameters, such as friction coefficients and penalty factors, to improve convergence.
7. **Restart Analysis**: Sometimes, it helps to perform a restart analysis. Save intermediate results and restart the analysis from a stable point.
8. **Convergence Criteria**: Adjust the convergence criteria in your analysis settings. You can make convergence criteria more or less stringent depending on the problem.
9. **Output Requests**: Reduce the number of output requests if you have too many. Excessive output requests can slow down the analysis and affect convergence.
10. **Check for Singularities**: Inspect your model for potential singularities or areas with extremely high stress or strain gradients. These can lead to convergence problems. Mesh refinement or localized modeling changes may be needed.
11. **Solver Options**: Experiment with different solver options. Abaqus provides various solver options, and some may work better for your specific problem.
12. **Consult Documentation and Support**: Refer to the Abaqus documentation and user manuals for guidance on specific convergence issues. You can also seek support from Abaqus technical support forums or communities.
It's essential to approach convergence issues systematically by isolating potential causes and gradually making adjustments. Keep in mind that convergence problems can sometimes be challenging to resolve, and it may require a combination of the above techniques to achieve a stable solution.
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I am trying to model heat transfer as result of a fire in a reinforced concrete wall in 2D.
I get the following error when combing a 2D homogeneous part (concrete) with a 2D wire (rebar): STRESS-DISPLACEMENT ELEMENTS OR OTHER ELEMENTS WITHOUT TEMPERATURE DEGREE OF FREEDOM ARE NOT ALLOWED IN A HEAT TRANSFER ANALYSIS
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No.
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have simulated a hydraulic jump. There is a difference in water and ambient(air)temperature and as such there is heat transfer across the water-air interface. I have used VOF model and Standard K-epsilon model for the simulation. Energy Model is activated. Radiation is not considered.
Is there any way to determine the total heat transfer rate across the water-air interface bounded between the two sections(vertical lines) as shown in figure below? Also, is there a way to determine heat flux across the same interface or average equivalent thermal conductivity or average heat transfer co-efficient at the interface.?
Also I tried to determine heat flux across a point at the interface in CFD post. But it was shown as "Undefined". While the heat flux at any point at solid boundary could be easily determined. Why?
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Subham Pal, To determine the heat flux across a point at the interface, you can use the Report > Probe Data feature in Ansys Fluent or the Probe feature in CFD post. However, if you are using a VOF model, the heat flux at the interface may be undefined at some points. This is because the VOF interface is a sharp interface and the heat flux across a sharp interface is not defined.
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Hello Everyone, I used a simple 2-D UMAT for a Coupled Heat Transfer and Displacement Problem and Generated the Stiffness Matrix through the Input file. I can see few negative nodal id, can anyone suggest what this means?
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Moiching Ahamed How do you suggest I can assemble a Stiffness Matrix with Negative Nodal id ?
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I am confused. I got the data of sample mass, time, sample temperature, heat flow, heating rate, baseline temperature.
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You integrate the heatflow on the time and draw the data in function of the sample temperature, if you have a phase-change you will get a step, if not only a more or less linear curve (maybe even a plateau). The height of the step represents the latent energy, the slope of the curve is the sensible heat capacity. You divide by the mass of the sample to have the specific values.
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Dear amazing members,
I have a doubt.
If I have three adjacent planes with different boundary conditions, in a 3D domain, Dirichlet (fixed temperature) on one plane, Neumann fixed flux on another plane and Neumann heat conduction on another, then what should I do?
Should I consider all the conditions on the common node? I read somewhere that if Temperature and heat flux is specified on a node then only specified temperature should be considered, but I don't know if I should ignore convective heat transfer when temperature is specified.
And in 2D case, when only temperature is specified on one edge, and convective heat transfer on adjacent edge? Then should I consider the heat convection at the common node these two edges?
Thank you 😊
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At a boundary surface you can either specify the temperature or heat flux, not both, as the one determines the other. So if you have nodes on the the boundary line which separates these two regions, then, I think you can specify one of these two conditions alternately on every consecutive node.
Regards
Dr Kumar Eswaran
Professor
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How can I find value of convective heat transfer coefficient (h) of free air at -20 degree Celsius? Is there any h vs T graph? Or data table?
Description: The air is under natural free convection and the pressure is 1 bar to 0.1 bar.
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That all depends on what the air is doing in relation to the surfaces of interest. Is the air flowing? Is the air stagnant? Is the air free to flow should the opportunity for natural convection arise? Please provide more information.
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I want to calculate Rayleigh number and Nusselt number of a PCM-heatsink to analyze the intensity of the natural convection of PCM. There are some fins inside my heatsink to enhance the heat transfer. Now I am having trouble calculating the characteristic length to use in Rayleigh and Nusselt dimensionless numbers.
I would be grateful if you could help me.
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The Rayleigh number (Ra) is a dimensionless number used to predict the flow regime (conduction, convection, or mixed) in a fluid when it is heated from below. In the context of a phase change material (PCM)-heatsink system with fins, the characteristic length is an important parameter for calculating the Rayleigh number.
The characteristic length (L) used in the Rayleigh number calculation can vary depending on the geometry of the system. In the case of a PCM-heatsink with fins, the characteristic length can be defined based on the specific geometry you are dealing with. Here are a few possibilities:
  1. Fin Height (H): If the characteristic dimension of interest is the height of the fins (assuming they are vertically oriented), you can use the height of the fin as the characteristic length. This would be suitable when the heat transfer is mainly driven by natural convection along the fins.Rayleigh Number (Ra) = (g * β * ΔT * H^3) / (ν * α)Where:g: Acceleration due to gravity β: Coefficient of volumetric expansion ΔT: Temperature difference between the heated surface and the surrounding fluid ν: Kinematic viscosity of the fluid α: Thermal diffusivity of the fluid
  2. Fin Base Width (W): If the characteristic dimension is the width of the fin base, you can use this value as the characteristic length. This might be more appropriate if the heat transfer occurs primarily through the base of the fins.Rayleigh Number (Ra) = (g * β * ΔT * W^3) / (ν * α)
Remember that the choice of characteristic length depends on the dominant heat transfer mechanism in your specific setup. The key is to select a length scale that is relevant to the phenomenon you are trying to analyze.
Additionally, when dealing with PCM systems, keep in mind that the melting and solidification of the PCM can introduce additional complexity to the heat transfer process. You might need to consider the effects of latent heat and phase change in your analysis.
Before performing calculations, ensure that the physical properties of the fluid, PCM, and the geometry are accurately determined. It's recommended to consult relevant literature, research articles, or textbooks in the field of heat transfer to find appropriate values and guidance for your specific configuration.
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My model for Fluent includes solid and fluid (Fig1)
I have finished simulating flow and heat transfer in Fluent (Fig2).
I want to simulate thermal stress, so I copy the model from Fig1 to Fig3, which includes only the solid domain, and transfer the model to the Steady-State Thermal (Fig4)
However, I can't generate the mesh, and it shows that the input is wrong (Fig5)
I am trying to change the facet into solid and transfer, but not achieve it.
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I would suggest to transfer the geometries as solid body and not as faceted body from SpaceClaim and not from results. And from the results, import the temperature distribution itself as it is done with one-way FSI analysis for the pressure distribution.
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I am working on modeling and optimization of evaporator and condenser, both are plate type heat exchanger. The primary fluid is refrigerant mixture (zeotropic) and secondary fluid is hot water. For water, the open literature has numerous heat transfer correlations but for refrigerant mixtures I could not find any flow boiling or condensation correlation in heat exchangers. Although there are few studies that provide flow boiling or condensation correlation of zeotropic fluids in tube. But since the flow pattern is different in tube and plate heat exchanger (vortex or swirl flow), is it reasonable to use flow boiling or condensation correlation of zeotropic fluids in tube instead for flow in plate heat exchanger as well? 
The flow boiling and condensation heat transfer correlation for refrigerant mixtures in tube wi
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Muhammad Imran , Khaled Hossin , Shazia Farman Ali , I agree with you about the existing research gap in having the correlations for Zeotropic mixtures in the case of Plate type HX. I was also facing a similar issue. In my case, the intended fluid is CO2; and I didn't find any heat transfer coefficient as well as pressure drop correlation in the case of CO2 evaporation inside a plate type HX. However, there are numerous existing correlations for the in-tube flow boiling as well as condensation. I am hereby providing one reference for a unified correlation in the case of in-tube flow boiling inside a mini/micro/conventional channel. This correlation generally accounts the "hydraulic diameter" concept in a tube flow. As there is no existing correlation for CO2 and zeotropic mixtures in the case of flow boiling inside a plate HX, could this "hydraulic diameter" concept for mini/micro/conventional channel be a starting point for estimating the HTC and PD for flow inside a plate HX?
[1] Shah, M. M. (2017). Unified correlation for heat transfer during boiling in plain mini/micro and conventional channels. international journal of refrigeration, 74, 606-626.
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I want to delete elements exceeding melting temp during thermal analysis.
It's transient condition, heating and cooling.
Domain is 2D.
Element used is Heat transfer.
Material is Al.
Defined temp dependent properties density, young's mod, poisons ratio, plasticity, conductivity, specific heat, latent temp, solidus temp, liquidus temp.
I am learning subroutines but please suggest simple way.
Thanks in advance.
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Deleting or "killing" elements during a transient analysis in Abaqus, such as removing elements that exceed a melting temperature, can be achieved using the subroutine-based approach. Here's a general guide on how you can implement this method:
  1. Define the Melting Temperature Criterion:Decide on the temperature threshold that determines when an element should be removed or "killed."
  2. Create a UMAT or VUMAT Subroutine:Write a UMAT (for implicit simulations) or VUMAT (for explicit simulations) subroutine to monitor the temperature at each integration point and modify the material properties accordingly. In the subroutine, you can set the stiffness and other properties to negligible values when the temperature exceeds the melting point, effectively "killing" the element without actually removing it from the mesh.
  3. Compile the Subroutine:Compile the subroutine using a suitable compiler.
  4. Set Up the Model in Abaqus CAE:Build your 2D model for the thermal analysis. Assign material properties and boundary conditions. Set up the transient analysis steps for heating and cooling.
  5. Link the Subroutine to the Analysis:In the Job module, you must specify that Abaqus should use your compiled subroutine file during the analysis.
  6. Run the Analysis:Submit the job for analysis. The subroutine will monitor the temperature in each element during the simulation, and elements that exceed the melting temperature will be "killed" by setting their material properties to negligible values.
  7. Inspect the Results:Use Abaqus CAE to visualize the results, particularly to the regions where elements were killed.
Remember that this approach doesn't physically remove the elements from the mesh, but it alters their properties so that they no longer contribute to the simulation. This can create numerical challenges in some cases, and careful validation and verification of your model will be important.
This is a high-level overview, and implementing this approach will require some expertise in writing and debugging user subroutines. The Abaqus documentation and various online forums can provide more detailed guidance tailored to your specific application and needs.
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I need to fit a multivariable non-linear correlation for a heat transfer problem. Could anyone suggest any tools or software for that?
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You can use my software free. Create a table of x,y,z,... in Excel, copy to clipboard, Alt-tab over to CurveFit, push Read Clipboard, push Fit Curve, push Copy Fit to Clipboard, alt-tab over to Excel, alt-F11 to open up VBA, press ctl-V to paste the function into Excel.
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Hi !
This seems like a not so complex problem to solve although I am not able to set up my ansys workbench, steady state thermal model correctly. Lets say we have a cylinder of length L with sides A and B. If my Ta = 500 deg C and Tb = 10 deg C, I am trying to find the time it takes for them to equilibrium around the length L. This also means that I want to see how the heat transfer looks like. I gave the upper and lower boundary temperature, although I am not sure how to setup for what I want.
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To simulate the heat flow in a cylinder with different top and bottom surface temperatures in Ansys Workbench, you can follow these steps:
  1. Geometry Setup: Start by creating the 3D geometry of your cylinder with sides A and B and length L in a CAD software. Save the geometry in a format compatible with Ansys, such as STEP, IGES, or Parasolid.
  2. Import Geometry to Ansys Workbench: Open Ansys Workbench and create a new project. Import the geometry you created in step 1 into the Workbench project.
  3. Physics Setup: Add a "Static Structural" analysis system to your project to perform thermal analysis. Under the "Model" tab, define the material properties of the cylinder, such as thermal conductivity (k) and other relevant properties.
  4. Meshing: Generate a mesh for your cylinder to discretize the geometry and prepare it for thermal analysis. Use an appropriate mesh size, considering the length L and sides A and B, to ensure accurate results.
  5. Boundary Conditions: Define the boundary conditions to represent the temperature at the top and bottom surfaces. Apply a "Fixed Temperature" boundary condition at the top surface (Ta = 500°C). Apply another "Fixed Temperature" boundary condition at the bottom surface (Tb = 10°C).
  6. Solver Settings:Under the "Analysis Settings," choose the appropriate solver for thermal analysis, such as "Thermal" or "Transient Thermal," depending on whether you want to simulate steady-state or transient heat transfer.
  7. Solution and Post-processing: Run the analysis and wait for the solution to complete. After the simulation is finished, you can visualize the results using various post-processing tools in Ansys Workbench. You can plot temperature distributions, heat flux, or any other relevant heat transfer parameters.
  8. Steady-State vs. Transient Analysis: For steady-state analysis, you can choose the "Thermal" analysis system, which will assume that the temperature distribution reaches equilibrium and remains constant over time. For transient analysis, you can choose the "Transient Thermal" analysis system, which allows you to observe how the temperature evolves over time until it reaches equilibrium.
  9. Time to Equilibrium: If you are performing transient analysis, you can observe how the temperature at different points in the cylinder changes with time. The time it takes to reach equilibrium will depend on the material properties, initial temperature distribution, and geometry of the cylinder.
Remember to carefully review and validate your simulation setup before drawing conclusions from the results. Make sure to use appropriate material properties and boundary conditions based on your specific use case.
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The heat transfer behaviour of hydrophobic surfaces presents a fascinating and intricate phenomenon, particularly concerning the early formation of bubbles well before reaching the critical temperature. Unlike conventional surfaces, hydrophobic surfaces possess unique properties that repel water and promote the formation of a stable air layer when exposed to a liquid medium. This air layer acts as a thermal insulator, significantly reducing the direct contact between the liquid and the surface, thus impeding heat transfer.
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A fascinating question and I'm afraid that I've got no experience of it. However, I would approach the problem as a combined heat and mass transfer problem as mass transfer is being inhibited. Will be interested to follow this discussion. Would be great in condensers where wetting would be inhibited but the condensing would still occur.