Heat Transfer - Science topic

No.

Jose Fernandez, I have addressed a similar question before, although I don't recall the specific instance. If you're encountering issues like those described above, it's likely due to an incorrect material definition being employed. To resolve this, I recommend removing any temperature-dependent data from your analysis and systematically examining each parameter to identify which one has the most destabilizing impact on the simulation. In other words, when encountering problems in your FEA simulation as mentioned earlier, it's crucial to review and possibly refine your material definitions. Start by eliminating temperature-dependent properties from your analysis. Then, carefully analyze each parameter, one by one, to pinpoint which one is causing the most significant destabilization in your simulation results. This systematic approach will help you identify and rectify the root cause of the issues you're experiencing.

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.

Moiching Ahamed How do you suggest I can assemble a Stiffness Matrix with Negative Nodal id ?

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.

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

Dr Murtadha Shukur thank you for your contribution to the discussion

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.

Burning fossil fuels like coal and oil puts more carbon dioxide into our atmosphere. NASA has observed increases in the amount of carbon dioxide and some other greenhouse gases in our atmosphere. Too much of these greenhouse gases can cause Earth's atmosphere to trap more and more heat. This causes Earth to warm up. The added greenhouse gases absorb the heat. They then radiate this heat. Some of the heat will head away from the Earth, some of it will be absorbed by another greenhouse gas molecule, and some of it will wind up back at the planet's surface again. With more greenhouse gases, heat will stick around, warming the planet. Conduction, radiation, and convection all play a role in moving heat between Earth's surface and the atmosphere. Since air is a poor conductor, most energy transfer by conduction occurs right near Earth's surface. Conduction directly affects air temperature only a few centimeters into the atmosphere. Greenhouse gas molecules in the atmosphere absorb light, preventing some of it from escaping the Earth. This heats up the atmosphere and raises the planet's average temperature. Earth's greenhouse gases trap heat in the atmosphere and warm the planet. The main gases responsible for the greenhouse effect include carbon dioxide, methane, nitrous oxide, and water vapor. In addition to these natural compounds, synthetic fluorinated gases also function as greenhouse gases. Certain gases in the atmosphere absorb energy, slowing or preventing the loss of heat to space. Those gases are known as “greenhouse gases.” They act like a blanket, making the earth warmer than it would otherwise be. This process, commonly known as the “greenhouse effect,” is natural and necessary to support life. Greenhouse gases are transparent to incoming (short-wave) radiation from the sun but block infrared (long-wave) radiation from leaving the earth's atmosphere. This greenhouse effect traps radiation from the sun and warms the planet's surface. On its own, methane is 30 times stronger than CO2. It contributes between 10-25% of global warming and though it remains in the atmosphere for less time than CO2 does methane eventually turns into more CO2. Greenhouse gases affect our environment by absorbing high amounts of heat from the sun. Greenhouse gases trap heat from the rays of the sun and warm the atmosphere. As the amount of greenhouse gases are increasing in the atmosphere, they are trapping more and more heat. Global warming is the change in the climate of the earth causing it to heat up whereas the greenhouse effect is a naturally occurring phenomenon, constantly occurring due to the atmosphere and sunlight. As greenhouse gas emissions from human activities increase, they build up in the atmosphere and warm the climate, leading to many other changes around the world in the atmosphere, on land, and in the oceans. The Greenhouse effect is when the heat goes up into space, Greenhouse Gases, block the heat going into space and it goes back to earth. Global Warming is when the earth being overheated by Fossil fuels and Greenhouse gases causing Greenhouse effect. Greenhouse gas = one of the causes of global warming, adding a “blanket” so the Earth cannot lose heat (as infrared) to space as fast as it comes in (as visible light) without warming up.

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:

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.

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.

The heat transfer coefficient (h) is a crucial parameter in heat transfer analysis that quantifies the rate of heat transfer between a solid surface and a fluid (liquid or gas) that is stagnant or in motion. It represents the ability of the fluid to conduct heat and is influenced by factors such as fluid properties, flow conditions, and surface characteristics. There are different methods to determine the heat transfer coefficient for a stagnant fluid, and the choice of method depends on the specific situation and available data. Here are a few common methods:

When determining the heat transfer coefficient, it's important to consider factors such as fluid properties (viscosity, thermal conductivity, density), surface characteristics (roughness, geometry), and the type of heat transfer (conduction, convection, radiation). Additionally, ensure that the units of the variables used in calculations are consistent.

It's recommended to consult relevant literature, textbooks, or seek guidance from experts in heat transfer to choose the most appropriate method for your specific case and to ensure accurate results.

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.

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:

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.

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.

To simulate the heat flow in a cylinder with different top and bottom surface temperatures in Ansys Workbench, you can follow these steps:

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.

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.

To simulate evaporation through porous media with the evaporation-condensation method in Ansys Fluent, follow these steps:

Set up your porous media: Define the porous zone in your domain where you want to simulate evaporation. Assign the appropriate porous media properties, such as permeability and porosity.

Enable the evaporation-condensation model: In Fluent, go to the "Models" panel and enable the "evaporation-condensation" model.

Define phase change settings: Set the appropriate parameters for the evaporation-condensation model, such as the evaporation rate, condensation rate, and heat transfer coefficients.

Specify the initial conditions: Define the initial temperature, pressure, and other relevant properties for the domain and porous media.

Set boundary conditions: Apply appropriate boundary conditions, such as inlet and outlet conditions for the fluid flow and evaporation.

Initialize and solve: Initialize the simulation and run it to solve the fluid flow, heat transfer, and evaporation-condensation phenomena.

Post-process results: Analyze and interpret the simulation results to understand the evaporation behavior within the porous media.

Remember to consult Ansys Fluent documentation or tutorials for more detailed information on specific settings and inputs relevant to your simulation

Yes of course its possible. There are a couple of ways to maintain the outlet temperature of the fluid in parabolic trough.

here are some of the ways:

Control the Flow Rate: The flow rate of the heat transfer fluid can be controlled to adjust the fluid's exit temperature. Higher flow rates result in a lower temperature increase of the fluid, as the fluid spends less time in the collector. Conversely, lower flow rates allow the fluid to heat up to higher temperatures.

Usage of Thermal storage: When the environmental conditions is unfavourable and it is hard to maintain 500C, some of the fluid that is stored in the thermal storage can be used.

Automated Control System: To precisely control the temperature to 500 degrees Celsius, you might need an automated control system. This system would monitor the temperature in real-time and make adjustments as necessary to maintain the desired temperature. These adjustments might involve changing the flow rate, altering the alignment of the trough, or activating the cooling system.

Tracking Control: Parabolic trough systems often include sun-tracking features that can adjust the amount of solar radiation received by the trough. By fine-tuning this feature, you can control the amount of heat absorbed by the fluid.

one or the combinations of these strategy can help to maintain the fluid at 500C or at least close to it.

Alessio Pricci

Thanks my friend

but I take another procedure, I made work work plane and portionmt domain into a quarter of the original shape and made finer meshing,

notes ..

i used heat flax instead of input temperature ..

if this didn't work . can i send you the mph file , if that possible?

explain your idea

Kristaq Hazizi please check this out

Jack,

You will find that Dr Naresh has asked, and then answered, an astonishing number of questions.

I have repeatedly asked him this same question - as it surely is in conflict with the role of ResearchGates's 'question' section where we:

"Ask a technical question to get answers from experts, or start a scientific discussion with your peers."

He is not asking an honest question, and is not interested in discussion.

I fear that he is attempting to 'game' the system.

Dr Jack broughton thank you for your contribution to the discussion

I also find the use of Boiling number in the boiling heat transfer correlation and Bond number in the condensation heat transfer correlation along with Nusselt number, Reynolds number, and Prandtl number.

Can you clarify your question a bit? If I understood correctly, you would like to calculate the Darcy-Forcheimer coefficients for porous media modelling, for a given set of inlet velocities and static outlet pressures. Am I correct?

The theoretical and practical answer to your concern rest on the axial Biot number, which is smalll enough, so most of the generated heat is dissipated radially and not axially when axial heat transfer is suppresed by either symmetric boundary conditions or a good combinations of axial thermalconductivity, chararacteristic length and heat transfer coefficient. When/if the axial symmetry broken for any reason, then, the above scenario must not realize.

Paraffin wax is commonly used as a phase change material (PCM) in various heat transfer applications due to its favorable properties. Its effectiveness in winter season applications depends on specific factors and system design considerations. Here are some key points to consider:

1. Thermal Energy Storage: Paraffin wax has a high latent heat of fusion, meaning it can store a significant amount of thermal energy when transitioning from solid to liquid phase and vice versa. This property allows it to act as a thermal buffer, absorbing and releasing heat during phase change. In winter applications, paraffin wax can store heat during the day when ambient temperatures are higher and release it at night when temperatures drop, providing a more constant and comfortable indoor environment.

2. Temperature Range: The choice of paraffin wax as a PCM should consider its phase change temperature range. Paraffin waxes are available in various grades with different melting points, allowing for customization based on the desired application temperature range. Selecting a paraffin wax with a phase change temperature suitable for winter conditions can help optimize the system's performance.

3. Thermal Conductivity: While paraffin wax has desirable thermal storage properties, its thermal conductivity is relatively low compared to other materials. This can affect the rate of heat transfer between the PCM and the surrounding environment. To enhance heat transfer, strategies such as incorporating high-conductivity additives or using fins or heat exchangers can be employed.

4. Encapsulation and System Design: Paraffin wax is typically encapsulated to contain it within a specific volume and shape, making it easier to integrate into heat transfer systems. The design and configuration of the PCM system, including the arrangement of PCM containers, heat exchangers, and insulation, are crucial for efficient heat transfer and ensuring that the stored energy effectively contributes to maintaining desired temperatures.

5. Compatibility and Stability: Consider the compatibility of paraffin wax with other system components and materials to avoid any undesired interactions. Additionally, stability and durability of the PCM should be evaluated over long-term use and repeated thermal cycling.

It's worth noting that the effectiveness of paraffin wax as a PCM in winter applications depends on the specific requirements, such as the scale of the application, the thermal load, and the desired temperature range. Detailed analysis, including simulations or experimental studies, can provide insights into the performance and suitability of paraffin wax in a specific heat transfer system for winter conditions.

To formulate of this model you need to consider the amount of information included in it:

1.

2.

Both Ansys and COMSOL are popular software tools for simulating heat transfer, and both have their strengths and capabilities. The choice between the two ultimately depends on your specific needs, preferences, and the nature of your simulation.

Ansys is a comprehensive suite of engineering simulation software that offers a wide range of capabilities, including heat transfer simulations. Ansys Fluent, in particular, is widely used for computational fluid dynamics (CFD) simulations, which can be used to analyze heat transfer in fluid flows. Ansys also provides specialized tools like Ansys Mechanical and Ansys Icepak, which focus on structural and electronics cooling simulations, respectively. Ansys is known for its robustness, accuracy, and versatility across various engineering domains.

COMSOL, on the other hand, is a multiphysics simulation software that allows for the coupled simulation of multiple physical phenomena, including heat transfer. COMSOL provides a user-friendly interface and a wide range of pre-built physics modules, including those specifically designed for heat transfer simulations. COMSOL's strength lies in its ability to handle complex multiphysics problems and its flexibility in customizing simulation models to specific needs.

The choice between Ansys and COMSOL depends on several factors:

1. Simulation Focus: If your primary focus is on fluid flow and CFD simulations, Ansys Fluent might be a more suitable choice. If you require coupled multiphysics simulations or a broader range of physical phenomena, COMSOL's multiphysics capabilities might be advantageous.

2. User Experience: COMSOL is often praised for its user-friendly interface and ease of use, making it accessible to engineers and scientists without extensive simulation experience. Ansys has a steeper learning curve but provides more advanced features and customization options.

3. Application-Specific Capabilities: Consider the specific industry or application you are working on. Ansys has specialized tools tailored to different industries, such as automotive, aerospace, or electronics, which may be advantageous if you require specific features for your field.

4. Support and Community: Both Ansys and COMSOL have active user communities, support forums, and documentation. Research the availability of resources, online communities, and support options to determine which software aligns better with your preferences.

In summary, both Ansys and COMSOL are powerful software tools for simulating heat transfer. Ansys excels in CFD and specialized applications, while COMSOL offers a flexible multiphysics platform. It is recommended to evaluate your specific requirements, trial both software tools if possible, and consider factors such as simulation focus, user experience, application-specific capabilities, and available support to make an informed decision.

Berkan,

I used to operate a thermal conductivity laboratory.

The idea that any material, especially a fluid, has a thermal conductivity that can be measured with high repeatability to six decimals in W/m/K is laughable.

How well do you need to know these qualities?

To +- 1% (a typical industrial *good* measure)

To +-0.1% (an analytical *excellent* measure)

to +-0.01% (NIST and their ilk)

For example, a typical thermal conductivity rig relies on knowing the power needed to maintain a given temperature difference. And that's achieved by knowing the voltage across a heating resistor. A typical resistor might have a resistance uncertainty of +-0.1% - limiting the certainty on the thermal conductivity to the same factor.

For Therminol VP-3, I'd call it 0.117 W/m/K at rtp.

I strongly suspect that there are far greater uncertainties or simplifications in any model that you might be building.

Dear friend Dr Janardhan Narambhatla

The error message you are seeing suggests that there might be some inconsistency between the element types used in your heat transfer analysis. Specifically, the error message is indicating that you have stress-displacement elements or other elements without temperature degree of freedom, which are not allowed in a heat transfer analysis.

In ANSYS, there are different element types available for different types of analyses, such as mechanical, thermal, and coupled analyses. It is important to select the appropriate element type for your specific analysis to ensure accurate results.

Based on the error message you are seeing; it is possible that you have not fully updated all of the elements in your model to the appropriate element type for a heat transfer analysis. Even if you have updated most of the elements, if there are still a few elements that are not updated, this could cause the error message to appear.

To resolve this issue, you will need to ensure that all elements in your model are compatible with the type of analysis you are running. This may involve changing the element type for some or all of the elements in your model.

If you have already changed the element type for all elements in your model and the error message still persists, it is possible that there are other issues with your model that need to be addressed. In this case, it may be helpful to consult ANSYS documentation or support resources for further guidance.

Additionally, it is worth noting that the appropriate minimum number of samples for running a PMF model will depend on the specific application and the complexity of the model. Generally, it is recommended to have a sufficiently large sample size to ensure statistical significance and accuracy of results. However, the exact minimum number of samples will depend on the specific requirements of your analysis.

Here are some references related to your previous question about block size in the base model bootstrap:

- Efron, B. (1979). Bootstrap methods: another look at the jackknife. Annals of Statistics, 7(1), 1-26. https://doi.org/10.1214/aos/1176344552

- Davison, A. C., & Hinkley, D. V. (1997). Bootstrap methods and their application. Cambridge University Press. https://doi.org/10.1017/CBO9780511802843

- Hall, P. (1988). Theoretical comparison of bootstrap confidence intervals. Annals of Statistics, 16(3), 927-953. https://doi.org/10.1214/aos/1176350949

And here are some references related to your question about the impact of electricity reduction/loadshedding on the small business sector:

- Steyn, L., & Brent, A. C. (2016). A framework for assessing the impact of power outages on SMMEs in South Africa. Energy Policy, 92, 602-611. https://doi.org/10.1016/j.enpol.2016.02.024

- Barnes, D. F., Samad, T., & Dijk, M. P. (2016). The impact of power outages on small and medium enterprises in Jamaica. Energy Policy, 96, 674-682. https://doi.org/10.1016/j.enpol.2016.06.019

- Shekhar, S., & Bazilian, M. (2016). Impact of electricity access on rural income generation: Evidence from Guatemala. Energy for Sustainable Development, 32, 43-50. https://doi.org/10.1016/j.esd.2016.02.006

Dear Kaushik Shandilya,

Grateful for your detailed answer. I am familiar with all the points you have mentioned except the first one. As you've suggested I m receiving assistance from ANSYS technical support team to solve this problem. But not yet solved. Could you please guide me how to incorporate the EOS models in ANSYS Fluent? I mean, where to start and how to implement that model in ANSYS? I have a hydraulic oil having different properties. Is there any such EOS available for hydraulic oils to predict it's properties at elevated pressures and temperatures? Need your inputs

Thanks

Hello Alina Fatima,

looking at the illustration provided, the first possible problem that came to mind is that the material properties are not defined correctly. Check carefully the Specific Heat and Conductivity properties you have defined for the material. Chack if they really correspond to mm-tonne-mJ. For example for Specific Heat for concret should be about 880 J/(kg°C) = 880 mJ/(tonn°C), and conductivity is around 1 W/(m°C) = 1 J/(m°Cs) = 1 mJ/(mm°Cs).

Hi,

Assuming that your composite material is made of two layers initially at room temperature T_0, a temperature T_A is suddenly applied to the external surface of layer 1 (point A) whereas the external surface of layer 2 is insulated (point B). The transient evolution of the temperature at point B is proportional to the temperature difference (T_A-T_0) and depends non-linearly on time and on 3 parameters: the square root of diffusion time (SRDT) in layer 1 , (i.e. thickness divided by the thermal diffusivity of layer 1, denoted by xi1), the SRDT in layer 2 (denoted by xi2), and the ratio of the thermal effusivities of layer 1 (i.e. b1) and layer 2 (i.e. b2). By applying the quadrupole method we can find that the normalised temperature in the Laplace space is expressed by 1/(ch1*ch2+b2/b1*sh1*sh2) where, for example, ch1 denotes cosh(xi1*sqrt(p)) and sh2 denotes sinh(xi2*sqrt(p)), where p is the Laplace variable. The Laplace inversion can be performed easily with the Gaver-Stehfest method.

I can send you a short matlab script to calculate the temperature evolution, given the 3 parameters.

As an example, if the diffusion time is the same in layer 1 and 2 (i.e. xi1=xi2), the temperature rise at point B reaches the following values at the particular time corresponding to (xi1+xi2)^2 :

- 29% of the temperature difference if b2=10*b1

- 99.7% of the temperature difference if b2=0.1*b1

In summary, point B will come faster close to the imposed temperature if the layer with the highest effusivity is at position 1. The main reason for this is that more power is required to impose T_A on the material with high effusivity. This is valid at least at the beginning of the process; this is however enough to make the difference. As a consequence, the asymptotic equilibrium temperature T_A is then reached faster on the opposite surface B.

This result remains valid for other values of the ratio xi2/xi1.

BR.

Jean-Claude

Kern's Text gives heat transfer correlations for most situations that are commonly encountered. Single phase and multi-phase heat transfer and fluid flow are very different: orders of magnitude different commonly.

I do not know of Bell's work I'm afraid.

Thankyou for your response

Hi Mohammad,

The original formulation is the best way to assess the NU and heat transfer ratio as it finds in enormous high-quality papers. For example, to calculate Nu make use of NU=hD/k. So it would help if you calculate h based on the formulation(Q=mct and ...). For T calculation in the inlet and outlet, use mass average or surface average temperature in the software. See when it gives a closer answer to your experimental trends. Also, for Wall temperature use surface average temperature.

Best,

Just to be clear, if i define heat flux using heat flux boundary condition to be zero then it would make heat transfer due to convection as well as conduction to be zero however i only wanted to have conduction from top surface of battery cell.

Using convective boundary condition , defining h to be zero at top surface will it cause only heat transfer due to convection to be zero ?

Dear Yasser

it depends on your simulation and what you want from your simulation, I myself used COMSOL software. it really helped me about that because of coupling optic, CFD and heat equations.

Hello.

Thanks for your response Farid SIr.

But, I am having difficulty in the simulation part in ABAQUS.

These are what I would try:

1. Check your mesh size, change it and see if you still see the issue.

2. Use a higher order discretization for temperature (quadratic, etc).

3. In your results, look for the regions that are below the initial temperature. They are usually at the singular points (i.e. corners). If this is the case, try to refine the mesh in those regions.

4. Sometimes, the time step that the software selects automatically is not small enough. Try to set it manually and see if the issue is resolved.

Umat to script load and interaction film conditions

I advise you to run two simulations ( two boundary conditions) if there is no function according to which the flux varies with time. Good luck.

Hello Zahra Kamali ,

I am not exactly sure of what your are doing, i.e., your explanation of your model system is terse. There has been experimental and theoretical work on heat transfer at small distances. I have not kept up with this field, but let me give some citations that might be of some help.

Experimental:

Jianbin Xu; Heat transfer between Two Metallic Surfaces at Small Distances; PhD Dissertation, Universitat Konstänz; März 1993; 88 pp. [N.B., this dissertation is in English.]

C. C. Williams, H. K. Wickramasinghe; Thermal and photothermal imaging on a sub 100 nanometer scale; Proceedings of SPIE; Vol. 897; 13-15 January 1988; Los Angeles, California; pp. 129-134.

K. Dransfeld, J. Xu; The heat transfer between a heated tip and a substrate; fast thermal micrscopy; Journal of Microscopy; Vol. 152; Pt. 1; October 1988; pp. 35-42.

Theory:

R. P. Caren, C. K. Liu; Emission, total internal reflection, and tunneling of thermal radiation in metals; in Jerry T. Bevans (Editor); Thermal Design Principles of Spacecraft and Entry Bodies; Academic Press; Vol. 21; 1969; 509-530.

I was interested, as a graduate student, in the use of SThMs (Scanning Thermal Microscopes) and STPs (Scanning Thermal Probes). You can find some of my heat transfer derivations for SThMs and STPs on my RG page:

Regards,

Tom Cuff

You can find the answer on your question in the treatise of Schlichting, chapter Thermal boundary layer.

Thank you Dr. Hanasoge Mukunda for your answer. The building heat transfer calculations are not very complicated as you mentioned. What I want is how to model the combustion of the pellet stove in order to get the required fuel temperature to ensure thermal comfort in a small space.

Measure the heat transfer. Vary the inputs. Switch to water on the outside and air on the inside. Use Reynolds Analogy, St=f/2. Kays & London is an excellent reference. So is TEMA and HEI and various ASME documents.

TEMA, HEI, HEDH, ASME and many more textbooks, handbooks, standards, and countless published papers are available on the subject. A world of information is waiting for you to explore. I've already done that and I don't want to spoil the adventure for you.

Sir Nicholas Robert Jankowski thank you for sharing your observation. Yes Sir i obtained the correct results for non-temp dependent properties. Sir, can you suggest me the contact option i can provide between the two plates in my model.

متابعه

I've looked at the polynomials that you have noted: none of them make sense, whether using actual temperatures or reduced temperatures.

I suggest going back to the original data and making your own, (lower order) curve fit using Excel.

One further comment, you would be mis-calculating enthalpy if you used your last equation as it assumes a constant specific heat over the temperature range: the correct form is to integrate Cp.dT over the range, I would integrate the secific heat equation (if it was correct).

Since at the heat transfer is convection to air which the convection co eff is always less than the conduction before from one element to another.

The VDI Heat Atlas is far outside of my budget, but is probably available in Universities. Most of the correlations are based on a small number of experiments in the early half of 20th Century and are at best good approximations. I regularly see people quoting htcs to several decimal places (computers can make one believe that high precision is easy with no consideration of accuracy).

Patricia Fehrentz

HYDROTHERM is good.

Erling Næss Thank you for your reply.

I understand.

what about dimensionless numbers? if Reynold, Prandtl and Nusselt numbers are the same (+-10%), can we say that simulation is validated?

and also there are correlations....as well

There is some work being done on carbon nano-structured surfaces which can collect a wide range of wavelengths. Aside from potentially improving on silicon based solar panels, there is also the possibility of collecting low grade waste heat in the form of IR radiation. Still early days though.

Boiling is a large topic and long-studied phenomenon. There are countless published papers on the subject going back more than a century. There is much to learn and many have forged a trail for you to follow in. Search the Web for "nucleation" and "onset" and "boiling". You might even spend some time in a university library if you can find one that's still open for business.

I reasoned by analogy of heat transfer in a plane air layer (e.g in double pane windows). At ambient temperature, convection starts at 2 cm (see attached file)

At higher temperatures however, this may change.

More details can be found in

Can you let me know the actual geometry of your conduits?

Kindly attach a file.

Vadym Chibrikov Thank you for your curiosity!

Tzero Lid was pressed using the DSC Tzero Press. What do you mean by "pressing should be done in triplicate" ? Maybe it helps to know, that many of my Tzero lids were displaced and pressed out. It was not a singular event. Additional info, I use the black pressing die with the concave top.

The material is powdery formulation of zein and glycerol (around 20% glycerol w/w). heating rate 15°C/min. Preliminary measurements (which didn't show lid displacement allowed me to tell that there is some amount of water contained in my material, which results in an endothermic deformation during the first heating cycle. second and third heating cycles usually coincide, suggesting that all water evaporated during the first cycle and that the curve form the second (or the third) cycle is "analysable". Note: the material becomes sticky when in the viscous state, so the lid isn't fully pressed out, it just stays half open, oblique, with some material peaking through.

https://folk.ntnu.no/deng/fra_nt/other%20stuff/DSC_manuals/QDSC/Preparing_DSC_Samples.htm this manual suggest using samples 10 - 20 mg for Glass Transition measurement, which is what I'm aiming to analyse here.

Following...

It seems that this problem needs super-positioning of a conduction and convection heat transfer theory based model. Probably the most difficult issue is contact resistance between the tube and skin, as this must vary with fixing method (pressure) and dryness; however the assumption of constant temperature at the skin surface seems probable. The free convection part is very surface temperature dependent and is also orientation dependent. A test and measurement system would be my recommendation as any CFD based model must be verified to be credible and CFD has no means of modelling contact conductance so far as I know.

We have found that using 60% ethylene glycol (freezing point -52.8 °C) works in our SpeedVac (UVS800 DDA). If you use 100% ethylene glycol, it will ice up as the freezing point is -12°C, so it is necessary to dilute. Much cheaper than cryocool!

Hi Muhammad,

The equation mentioned above is nothing but the energy balance (conduction=convection at that surface), you still need to have the heat transfer coefficient (h) except which all other parameters could be iteratively solved. 'h' need to be an input to the numerical study.

Considering its natural convection, i would expect h to be somewhere between 0-10 W/m2 K. What i would suggest is to use a value of 5 ( convective heat transfer boundary condition at that wall) and compare the results. Trail and error could help you find that h value.

Hope it helps.

Thanks & Regards,

Rajesh.

Thanks very much for your insightful response, Sir!

Sensible heat transfer is solely due to temperature difference and ceases to occur in the absence of it. Heat transfer due to mass transfer, on the other hand, continues to occur as long as there is mass transfer between phases regardless of the temperatures of the respective phases.

For instance, if N_i is the flux of gas species 'i' from phase-A to phase-B, then, heat flux associated with this interphase mass transfer is: (N_i)*(Cp_i_AB)*(T_A - T_Ref); where, T_A is temperature of Phase A. T_Ref is reference temperature. Cp_i_AB is average specific heat of gas species 'i' in the temperature range [T_Ref, T_A].

If it were to occur in the reverse direction, heat flux carried from phase-B to phase-A would be: (N_i)*(Cp_i_BA)*(T_B - T_Ref); here, T_B is temperature of phase-B. Cp_i_BA is average specific heat of gas species 'i' in the temperature range [T_Ref, T_B].

So, heat transfer associated with mass transfer proceeds as long as there exists mass transfer even when both phases are in thermal equilibrium.

I hope I understood your explanation well.