Applied Thermodynamics - Science topic

good answers above. the short answer is that you're failing to account for energy input requirements and losses at each stage of the process. the only way this works is if the net input is zero once all losses are accounted for.

It's a useful exercise to analyze the system to identify those elements, because they are key to any thermodynamic system design. And you aren't the first person to miss, or usually over/under-estimate such aspects of a thermodynamic system.

I just realized the figure above showing the sound envelop where amplitude expands and contracts is a pseudosphere! It has constant negative Gaussian curvature with a singularity on the peak at equilibrium.

This shows the evolution and involution of the surface motion on the wave. The wave is the potential energy field create by the internal stress of tension. The wave is always there but the surface can move.

Dear Giuma Fellah,

The chemical exergy of a substance is the maximum useful work that can be extracted due to its chemical composition when it is brought into equilibrium with the reference environment, which includes parameters such as temperature, pressure, and composition. This concept applies to gases, liquids, and solutions.

The chemical exergy of combustible gases, such as methane, hydrogen, or propane, is associated with the energy stored in their chemical bonds, which can be released during a reaction, like combustion. The amount of useful work available is determined by the difference between the energy content of these gases and the equilibrium state with the environment, after the reaction produces substances such as CO₂ and H₂O.

Chemical exergy also applies to liquid and gaseous fluids that do not directly participate in chemical reactions but possess a potential for work due to their chemical compositions. For example, in chemical separation or purification processes, chemical exergy can be utilized to maximize energy efficiency. Water, for instance, has its chemical exergy considered in processes like electrolysis, where it is decomposed into hydrogen and oxygen, with hydrogen containing much of the resulting chemical exergy.

In solutions, chemical exergy is related to the concentration of solutes in comparison to the reference state of the environment. A typical example would be that of a saline solution in desalination processes. In this case, the chemical exergy is associated with the difference between the salt concentration in seawater and the reference environment, which is typically the surface water of the sea. The useful work available depends on this concentration difference and can be utilized to separate the salt from the water through processes like reverse osmosis.

Another example is the potential chemical exergy in mixtures of gases dissolved in liquids. For instance, in industrial processes, the dissolution of gases like oxygen or carbon dioxide in liquids may have a chemical exergy potential that can be exploited for separation or purification. These processes are important in optimizing efficiency in chemical operations and separation, where utilizing chemical exergy can result in energy savings and greater efficiency.

Taking advantage of your very relevant question, I would like to inform you that there are several works by the Nucleus of Excellence in Thermoeconomics and Energy Sustainability (NETES) on exergy-based methods for modeling various systems, including cogeneration systems with gas turbines, in which chemical exergy is of paramount importance.

Sincerely,

Atilio.

@Peter Enders Excuse me, i don't need your opinion i am seeking technical insight on it.

The root of the problem is that no one seems to bother questioning the foundation of our current physics: Maxwell's equations. Einstein complained about that, too:

"All my attempts to adapt the theoretical foundation of physics to this new type of knowledge (Quantum Theory) failed completely. It was as if the ground had been pulled out from under one, with no firm foundation to be seen anywhere, upon which one could have built." (P. A Schlipp, Albert Einstein: Philosopher – Scientist, On Quantum Theory, 1949)

"You believe in the God who plays dice, and I in complete law and order in a world which objectively exists, and which I, in a wildly speculative way, am trying to capture. I hope that someone will discover a more realistic way, or rather a more tangible basis than it has been my lot to find. Even the great initial success of the Quantum Theory does not make me believe in the fundamental dice-game, although I am well aware that our younger colleagues interpret this as a consequence of senility. No doubt the day will come when we will see whose instinctive attitude was the correct one." (Albert Einstein to Max Born, Sept 1944, 'The Born-Einstein Letters')

So, in the 162 years since Maxwell published his work, no one has noted that his equations are actually inconsistent and not in alignment with the fundamental theorem of vector calculus.

After the discovery of the quantum circulation constant k, with a value equal to c*c but a unit of measurement in [m^2/s] I have been able to formulate a second order fluid dynamics model for the aether, wherein fluid dynamics and electrodynamics are seemlessly integrated and the Coulomb now has a unit of measurement in [kg/s].

This means a return to real fields and practical math. See the discussion here:

As for the comparison of the new model to Maxwell, ChatGPT summarized this as follows:

"In summary, while Maxwell’s equations provide a mathematically valid formulation, the new model offers a more physically consistent framework by rigorously separating linear and angular components, avoiding the blending of different types of behavior and ensuring adherence to fundamental principles of vector calculus."

Dear Cenker Aktemur,

According to information provided by Saeed Sayadi, there is a complication when total exergies of the flows are used to define fuel and product in a heat exchanger. Besides the dependence on the reference ambient temperature, there is the inconvenience of applying the disaggregation of exergy into thermal and mechanical components. Such disaggregation has already been criticized in the literature due to potential arbitrariness.

On the other hand, there are proposals in the literature to define fuel and product in heat exchangers without the aforementioned problems. Please look for the UFS and A&F Models, which were designed for exergo-economic and exergo-environmental analysis of refrigeration and heat pump systems.

Best regards,

Atilio.

could you pls explain it in a little more detail -- what exactly is meant by the last derivative?

Congrats for the policy draft; it raises key questions, with methodical respect to the applied development of sustainability science.

The mechanical energy produced by a Stirling engine using hot water at around 350K depends on factors like engine efficiency, temperature difference, and design. Generally, small engines might produce a few watts, while larger ones can generate several kilowatts or more. Specific values vary based on these factors.

Hello

You must use fsolve not fmincon. The former is used to solve nonlinear equations, but the latter is used for optimization.

I recommend the article published in the Journal of Petroleum Science and Engineering (JPSE) for measuring the H parameter based on various S (S = ds/de) values. Please read Table 3 in the article.

"Developing a novel procedure in utilizing pendant drop method for determination of ultra-low interfacial tension and surface tension in near-miscibility conditions"

Prof. Henk van Beijeren

You are totally right & thank you for that clarifying answer:

Non equilibrium Statistical Mechanics has to do a lot with damping of a particular case of springs, and also yes, the Boltzmann equation for a decay of a dilute gas is one of the examples (let say that even where the gradient of temperature can be neglected).

But when there are gradients of temperature, the exercise becomes more interesting as a numerical problem.

It took me 28 years since I took my first course on non equilibrium statistical mechanics to understand your remarkable statement.

Kind Regards.

Dear All,

the link suggested above (http://www.magma.ca/~thermal/CHF-LUT-1995.PDF) is not working.

Does anyone know if the LUT database is still available on Internet?

Thank you,

Lorenzo

In fact, it is actually a bit unusual that with regard to gas-liquid absorption, no names of scholars have been assigned to particular equilibrium curves and their corresponding mathematical functions, other than William Henry.

The specific surface area and pore distribution of any sample may be obtained from the measurement and analysis of the adsorption isotherm. The gases are always physically adsorbed on the solid surface at low temperatures in the atmosphere of adsorptive gases. According to the BET multilayer adsorption model, absorption isotherms be used for gas-liquid absorption processes.

If you already know the HHV and composition of your fuel I would apply the following:

LHV = HHV - Lv_H2O(H2O_content_w + 9*H_content_w) [MJ/kg]

where Lv_H2O = 2.441 MJ/kg

9 is the amount of water produced stoichiometrically considering the content of H of your fuel

H2O_content_w is the content of water in your fuel

in the case of 2-Butoxyethanol (C6H14O2, MW = 118)

H2O_content_w = 0

H_content_w = 14/118 = 0.1186

I hope it helps

You are most welcome dear Hasfi F. Nurly . Wish you the best always

explain your idea

No isentropic efficiencies are not the optimization parameters; there is not much control and also not wide range of this efficiency. It depends on the design of the compressor and turbine. Rather you should treat them as external parameters and concentrate on heat exchanger efficiency (regenerator efficiency), maximum cycle temperature, two or three stage compression with intercooling, reheating point, pressure ratio, etc.

You can plot just about anything with NIST's REFPROP. Check it out... https://www.nist.gov/srd/refprop (there's free version if you can find it)

Dear Amirreza Javaherian,

I hope the below-mentioned reference may help you.

Turbochargers

Marine Engines

Hi

I think the exergy of material streams is incorrect, and Aspen does not calculate the chemical exergy.

Best wishes;

i think the article attached will help you a lot to understand.

Although Tm is an easy, convenient index for protein stability and to compare the stability of different proteins constructs and variants, it is quite limited and focusing on Tm alone has important caveats.

It is possible to find two proteins having very similar Tm's and very different stabilization energies at 25 ^oC. And two proteins having different Tm's and very similar stabilization energies at 25 ^oC.

The characterization of structural stability, and assessing differences in structural stability, must always involve estimation of the stabilization Gibbs energy (which requires determining, at least, Tm and unfolding ΔH)

Thank you dear Dr. Shahsavari for your kind answer.

Regards

Excellent answer from Professor Dudley J Benton . I agree with him and recommend his response.

I agree with Ftwi Yohaness Hagos

In addition to the very completed and interesting previous answer, Dr. Purvi Kikani Dave I would like to add that in MHD the process to take small perturbations is considered isentropic flow meaning that the perturbation in pressure field, delta p = c_s² delta rho with c_s the sound speed. That is an adiabatic reversible process to describe magnetoacoustic waves, in a homogenous plasma.

See, for instance, Landau and Lifshitz, electrodynamics of continuous media, 1984, pp. 235, Pergamon.

Thank you for sharing idea Madhukar Baburao Deshmukh

The answer is Yes, the actual lapse rate is changing continuously reflecting the flow of a geophysical fluid and the thermodynamic processes. For the review of different lapse rates please kindly consult: “On Atmospheric Lapse Rates”, the text is free access and it is available on the following site:

The time dependent lapse rate is described in the above paper as ELR (Environmental or actual Lapse Rate)...

I suppose you are talking about normal octadecane (n-C18H38).

You may try several engineering models for a reasonable temperature range up to about 600 K to 700 K. Although there are no extensive data measurements for this fluid. The one-parameter friction theory model: https://doi.org/10.1016/S0378-3812(00)00474-X, combined with the Peng and Robinson EoS can give you some reasonable pvT, viscosity, and phase behavior estimations. This approach can also be extended to thermal conductivity.

But for most of the temperature range you are looking at, the octadecane will certainly be degraded. I even doubt you will have any CH4 left at all, as it starts decomposing at about 1000 K.  

So, you need to first figure out what compounds you will have left.

But, at such temperatures, you are likely only to have some light gases and C. For the fluid phase, a simple model that may be useful to consider would be the one by Chung et al.:

I would start here.

Q=m Cp delta T

Pressure-temperature-concentration can be available in Heat and mass transfer text books. Every chemical temperature and concentration is discussed.

If you want to solve your problem as it appears in the image, I recommend using an equation of state for the enthalpy departure.

I also recommend the following articles:

-A computationally effective formulation of the thermodynamic properties of LiBr-H2O solutions from 273 to 500 K over full composition range

- Exergy calculation of lithium bromide-water solution and its application in the exergetic evaluation of absorption refrigeration systems LiBr-H2O

-Thermodynamic Evaluation of LiCl-H2O and LiBr-H2O Absorption Refrigeration Systems Based on a Novel Model and Algorithm

-Mathematical Model of a Lithium-Bromide/Water Absorption Refrigeration System Equipped with an Adiabatic Absorber

Cenker Aktemur

Each software may be using a different reference state.

To check if this is the case or not you can use a simple trick.

Just try and calculate the enthalpy or entropy difference between two states from the two software, (the same two states). If everything other than the reference state is the same, this should give you the same answer.

Here is link

Hello there.

There are many compounds that are not found in ASPEN databases, new ones are incorporated in each version, but many are still missing.

One option that you have is to be able to create pseudo components and add them to ASPEN.

I leave you some tutorial links.

Regards.

Youssef Hmayed Walaikum assalam warahmatullahi wabarakatuhu.

Have a look: https://www.youtube.com/results?search_query=get+ansys-fluent+tutorial+zip+files+%3F

Sartaj Tanweer

I sorted the issue.

1) Yes your correct, but in HVAC there will be exhaust fan that sucks at particular rate. So if we let the flow dynamics to determine, then there is a chance more flow goes to one outlet than other outlet which might change the streamlines. Also in conventional CFD problem, the flow develops and leaves from one outlet. But here we need specific flow rate at each outlet. Also as there is an option (boundary condition) in openfoam to define flowrateoutletvelocity.

2) Yes as you said p-rgh is computed as you said. We have to define it based on the overall height of the domain, then only hydrostatic pressure will be computed correctly. I do accept it is constant, but if we define it 'zero' then the pressure will become negative.

Sampath Suranjan Salins I am talking about aspen plus not ansys fluent.

Is this Ansys Fluent analysis? its multiphase flow problems. U need to model the packing first the define the desiccant and material. Then apply suitable boundary conditions to solve the problem.

Hi,

For a near Isothermal process: (PR)^n= Pexeit/Pinlet

(4.5)^n=75/1=75, n~3

Three Compressor is optimum for you.

Dear Cenker Aktemur I found a report on the use of potassium formate/water (see attached) in which some severe corrosion problems were observed. They are listed on p. 21 of this report:

Dear Cenker Aktemur I'm not an expert in this field and therefore cannot provide you with a final answer. However, I found a report on the use of potassium formate/water (see attached) in which some severe corrosion problems were observed. They are listed on p. 21 of this report:

I can digitize the curves and obtain a formula that will accurately reproduce them if that would help. It doesn't tell why or reveal the basis but it's something, perhaps a step toward achieving the ultimate goal.

On thermodynamic data on Mg₂Si, cf.:

A. Nadiradze, I. Baratashvili, I. Pulariani, K. Ukleba, "Thermodynamic probability of realization of the process of silicon dioxide reduction by magnesium at high temperatures", Bull. Georgian National Acad. Sci., 3(2), 2009, 95-99.http://science.org.ge/old/moambe/vol3-2.html

Y. Ben-Hai, C. Dong, "Phase transition, structural and thermodynamic properties of Mg₂Si polymorphs", Chin. Phys. B, 20(3) 2011, 030508 (9 pp.); DOI: 10.1088/1674-1056/20/3/030508

It is most fortunate to have both theory and experimental data in this case. The approach I would suggest is to begin with rather simple theory (Otto cycle), incorporating crankshaft angle. Then add a reasonable approximation of the valve timing. You wouldn't need to specifically model the camshaft, lifters, pushrods, and valves, only the finite opening over time, producing a time-variant flow area for the exhaust. Then numerically tune the combustion to match experimental data (simple calculations often don't work here for reasons I discuss elsewhere). Now you would be ready to consider the exhaust process with minimal detail. Look for experimental data that come from one sensor in the combustion chamber plus another in the exhaust manifold near the valve. When you can roughly match the measured values, refine the calculations. A stepped approach from simplistic to complex will give you some encouraging results along the way and also provide insight as to which factors are more important than others. I would implement this entire process in an Excel spreadsheet, such as the one attached. Starting with a 3D transient CFD model of the combustion chamber with Fluent might make some pretty pictures, but won't produce much in the way of insight.

The thermodynamic two-Zone model can be used to estimate the temperature [Reference: John B. Heywood, internal combustion engine fundamentals]. Other calculation methods are presented in the same reference.

First, I think you should investigate on the Gas model.Second, what is the value of the Mach number ? Have you used a pressure or density based solver for the simulation?

Dear Shantanu P. Gawande, these bibliographic material I Guess worth to read. My Regards

Do you mean between the exhaust valves, the exhaust manifold, and where the CC is bolted on? And between the outlet flange of the CC, the front pipe, muffler, and tailpipe? Why not just put a thermocouple on either side of the CC and measure the temperatures? I'm sure this is different for every car design and also operating conditions. The heat loss will also vary from case-to-case.

Equation of Nanofluids

Density .........................(1)

ρ_nf = (1-φ)ρ_f + φρ_s

Heat Capacitance ..............................(1)

(ρC_p )_nf= (1-φ) (ρC_p )_f+𝛗(ρC_p )_s

Thermal Expansion Coefficient .............................(1)

β_nf = (1-φ)β_f + φβ_s

Thermal Diffusivity ..............................(1)

α_nf =Κ_nf/(ρC_p )_nf

Effective Thermal Conductivity ...............................(1)

Κ_nf/Κ_f = (Κ_s+2Κ_f-2φ(Κ_f-Κ_s))/(Κ_s+2Κ_f+2φ(Κ_f-Κ_s))

Viscosity ..................................(1)

Brinkman model

µ_nf = µ_f/〖(1-φ)〗^(2.5)

Pak and Cho correlation

µ_nf = µ_f ( 1+39.11φ+533.9φ^2 )

Reynolds number

Re= 4Ϻ/(π.D.µ)

Ϻ= (Re.π.D.µ)/4;

where,

[M= Mass flow rate]

[Re= Reynolds number]

[D= pipe diameter]

Reference

1. Combined convection flow in triangular wavy chamber filled with water–CuO nanofluid: Effect of viscosity models

Dear Kenkar,

In diffusion absorption coolers regarding to the heat performance of the system, ammonia/water couple with alumina (Al2O3) particles in nano-size can be a better option. It can provide better absorption of heat from the generator and faster evaporation of the cooler from the cooling/absorption fluid. Considering the effect of fluids containing nanoparticles the connection units of the heat transfer in the system operation time of the system might be reduced due to shorter heat transfer periods.

Ashish

I have been in and out of such plants and cooling towers all over the world for the past 40 years. I have written extensively on the subject and also developed the computer program (FACTS), which is the industry standard. You can get many of the papers and the software free at my web site http://dudleybenton.altervista.org/index.html

Natural variables for U: S, V, N_i (for simple systems)

Natural variables for S: U, V, N_i (for simple systems)

T is the partial derivative of U with respect to S, maintaining V and N_i constants:

T=(∂U/∂S)_V,Ni

If from the fundamental relationship U=U(S,V,N) you replace S by T just by solving for S in T=T(U,S,V,N_i) and substituting in U=U(S,V,N), then, you loose information because you are replacing a variable with a derivative with respect to that variable.

This problem is worked out with the Lengendre transform. If you search on internet, you may find simple examples: how to change y=f(x) to z=g(p), where p is ∂y/∂x=2x, in the two ways, the incorrect one (calculation of p and plain substitution of p by removing x) and the correct one (calculation of p and applying the Legendre transform, z=g(p)=px-f). In fact, because you do not loose information with the Legendre transform, you may go backwards from z to y, which is not possible with the incorrect way.

Therefore, it is a mathematical "trick".

Applying the Legendre transform to U, with respect to T and S, you get a new thermodynamic potential F=U-TS, the Helmholtz energy, whose natural variables are T, V, and N_i. Beware of the minus sign applied to the Legendre transform (i.e., F is not equal to TS-U, but U-TS).

For a system at constant U, V, and N_i, any possible process will maximize S.

For a system at constant S, V, and N_i, any possible process will minimize U, but not F.

For a system at constant T, V, and N_i, any possible process will minimize F, but not U.

The Legendre transform connecting two thermodynamic potentials parallels the Laplace transform connecting the corresponding partition functions.

The Legendre transform is not only employed in Thermodynamics and Statistical Physics, but also in Classical Mechanics and other fields.

Interesting thread Dear Prof. Manuel Malaver de la Fuente

I taught stat physics several years & I never asked or heard students asking about this possibility. So both distributions Fermi Dirac & Bose Einstein allow to build a Carnot cycle.

I guess that for electrons it is possible since they carry heat inside a solid (electronic heat transport & electronic specific heat), for phonons is the same

(lattice heat transport & lattice thermal heat) but for photons? Interesting, I thought photons only induce radiation in the atmosphere.

Dear Kanishka Kobbekaduwa,

The thermal conductivity of graphite depends on the anisotropy of the layers but generally it varies from 25-470 W/Mk.Generally it is “GraphiteTIM(Compressible Type) with thermal conductivity : X-Y direction 390-400W/m∙K, and in Z direction (28W/m∙K).

Why this is different?

However, controlling the orientation of GFs still remains a challenge. The corresponding thermal conductivity is as high as the thermal expansion will be less.

Because of the weak binding and the large lattice spacing in the c-direction, the phonon spectrum of graphite is approximately two-dimensional for frequencies above f c = 4 THz. Thus one can model the a-plane thermal conductivity by a two-dimensional phonon gas. That’s why in XY plane conductivity value is high and it is anisotropic when we compare with Z plane.

Hope it is helpful for you.

Ashish

Dear Nicholas,

That is true., By taking care of R41 which is flammable , performance value can be increased.

Ashish

The interface between two phases is very important (regarding to Subhasis's answer)

DOI: 10.1016/j.diamond.2019.107561

The subject of fluid behavior is broad and diverse. I cover this at some length in my book, Thermodynamic and Transport Properties of Fluids, which will be free on 3/24/2020. https://www.amazon.com/dp/B07Q5L1CHT The software is always free at http://dudleybenton.altervista.org/software/FluidProperties.zip The fact that these gases are supercritical actually makes your work in this case easier.

I haven't seen the equation, but I would imagine there are many better ways of solving it than EES. Many common equations can be solved with Excel. If you can't force EES to consider only positive values, you can simply make a change of variables. For example solving for (a^2)^(b/2) is the same as a^b except that you always have a positive result.

I discuss every cubic EoS in this book, https://www.amazon.com/dp/B07Q5L1CHT, which is free on 1/8/2020, 1/16/2020, 1/24/2020, and 2/1/2020. The software (C source code) and VBA (Excel spreadsheet) for every one is free here: http://dudleybenton.altervista.org/software/FluidProperties.zip This includes fugacity, residual enthalpy, and residual entropy too. I also compare 15 of the most common EoS for several measures against real data.

I fully agree with Paul, as long as actual airflow rate and the corresponding actual pressure difference are used.

More info on fan and system curve on https://www.cibsejournal.com/cpd/modules/2011-11/

Thermal conductivity refers to the intrinsic ability of solids to ensure that products behave as expected when subjected to thermal stress. Thermal stress is stress created by any change in temperature to a material. ... This type of stress is highly dependent on the thermal expansion coefficient which varies from material to material. In general the larger the temperature change, the higher the level of stress that can occur.

Thank you all for spending your valuable time.

Thank you C K Gomathy . Still did not work with me.

Thanks all

All answer above involve usage of storage unit for electrical energy, since the question intermittent, basically we want to create constant heat source. Apart from storage, one can focus discussion on efficiency of conversion. Efficiency is kept steady, might also result in constant heat source.

Now, efficiency will depends on solar cell material, which is pretty much saturated from design point of view. Next, will be to maximize the amount of incident sunlight on solar array, which will ensure output power above certain limit i.e. a limit higher than required, so that a portion of energy is stored in storage device, utilized in extreme cases.

Now, how do we maximize amount of incident light ?. Nature provides a solution in the form of sunflower. Sunflower like few other plant, has ability to respond to incident light and change it's direction of top head at different times of daylight time to receive maximum amount of solar energy for photosynthesis.

On similar line, a solar cell array can be mounted on flexible gyro and motor coupled, with combining electronics, we can create a closed loop system, which allow solar mount to rotate and decide optimum orientation for maximum sunlight incidence. gyro would be used to create 3-d map that would have a plot of orientation vs power generated. Power generated can be calculated using a load resistance similar to electrical engineering.

In this way, we can create a closed loop mechanism, targeting maximum power at certain time in daylight, resulting maximum conversion and storage and ensuring that power staying above required levels.