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At least 19 records

An estimate of the second law thermodynamic efficiency of the various units comprising an Environmental Control and Life Support System (ECLSS)

The objective of this paper is to present an estimate of the second law thermodynamic efficiency of the various units comprising an Environmental Control and Life Support System (ECLSS). The technique adopted here is based on an evaluation of the 'lost work' within each functional unit of the subsystem. Pertinent information for our analysis is obtained from a user interactive integrated model of an ECLSS. The model was developed using ASPEN. A potential benefit of this analysis is the identification of subsystems with high entropy generation as the most likely candidates for engineering improvements. This work has been motivated by the fact that the design objective for a long term mission should be the evaluation of existing ECLSS technologies not only the basis of the quantity of work needed for or obtained from each subsystem but also on the quality of work. In a previous study Brandhorst showed that the power consumption for partially closed and completely closed regenerable life support systems was estimated as 3.5 kw/individual and 10-12 kw/individual respectively. With the increasing cost and scarcity of energy resources, our attention is drawn to evaluate the existing ECLSS technologies on the basis of their energy efficiency. In general the first law efficiency of a system is usually greater than 50 percent. From literature, the second law efficiency is usually about 10 percent. The estimation of second law efficiency of the system indicates the percentage of energy degraded as irreversibilities within the process. This estimate offers more room for improvement in the design of equipment. From another perspective, our objective is to keep the total entropy production of a life support system as low as possible and still ensure a positive entropy gradient between the system and the surroundings. The reason for doing so is as the entropy production of the system increases, the entropy gradient between the system and the surroundings decreases, and the system will gradually approach equilibrium with the surroundings until it reaches the point where the entropy gradient is zero. At this point no work can be extracted from the system. This is called the 'dead state' of the system.

Chatterjee, Sharmista↗

Stochastic control and the second law of thermodynamics

The second law of thermodynamics is studied from the point of view of stochastic control theory. We find that the feedback control laws which are of interest are those which depend only on average values, and not on sample path behavior. We are lead to a criterion which, when satisfied, permits one to assign a temperature to a stochastic system in such a way as to have Carnot cycles be the optimal trajectories of optimal control problems. Entropy is also defined and we are able to prove an equipartition of energy theorem using this definition of temperature. Our formulation allows one to treat irreversibility in a quite natural and completely precise way.

Brockett, R. W.↗

Revisiting the First, Second and Combined Laws of Thermodynamics

The present study revisits the first, second, and combined laws of thermodynamics by introducing partial internal energy in the first law, entropy production and partial entropy in entropy change, and partial volume in the context of work exchange. These developments yield a more rigorous and internally consistent thermodynamic framework, within which chemical potential is defined as the partial derivative of internal energy with respect to composition at constant entropy and volume, and is related to partial internal energy, partial entropy, and partial volume.

36 MATERIALS SCIENCE↗

Energy in the environment and the second law of thermodynamics

The relationship between the consumption of energy by technological cultures and the second law of thermodynamics is discussed. The analysis is based on a description of the operation of a mechanical device which consumes energy. It is concluded that the flow of energy in manifold spontaneous conditions, which play a vital role in the operation of any technological process, remove most of the energy flow path from the control of the operator. It is stated that the increased efficiency of a process can benefit the environment only as much as this efficiency enables the total energy input to be reduced for a given level of production and increasing efficiency cannot meet the problems of an increased rate of energy utilization.

Mueller, R. F.↗

A Scale-Invariant Model of Statistical Mechanics and Modified Forms of the First and the Second Laws of Thermodynamics

A scale-invariant statistical theory of fields is presented that leads to invariant definition of density, velocity, temperature, and pressure, The definition of Boltzmann constant is introduced as k(sub k) = m(sub k)v(sub k)c = 1.381 x 10(exp -23) J x K(exp -1), suggesting that the Kelvin absolute temperature scale is equivalent to a length scale. Two new state variables called the reversible heat Q(sub rev) = TS and the reversible work W(sub rev) = PV are introduced. The modified forms of the first and second law of thermodynamics are presented. The microscopic definition of heat (work) is presented as the kinetic energy due to the random (peculiar) translational, rotational, and pulsational motions. The Gibbs free energy of an element at scale Beta is identified as the total system energy at scale (Beta-1), thus leading to an invariant form of the first law of thermodynamics U(sub Beta) = Q(sub Beta) - W(sub Beta) +N(e3)U(sub Beta-1).

Sohrab, Siavash H.↗

Second Law of Thermodynamics Applied to Metabolic Networks

We present a simple algorithm based on linear programming, that combines Kirchoff's flux and potential laws and applies them to metabolic networks to predict thermodynamically feasible reaction fluxes. These law's represent mass conservation and energy feasibility that are widely used in electrical circuit analysis. Formulating the Kirchoff's potential law around a reaction loop in terms of the null space of the stoichiometric matrix leads to a simple representation of the law of entropy that can be readily incorporated into the traditional flux balance analysis without resorting to non-linear optimization. Our technique is new as it can easily check the fluxes got by applying flux balance analysis for thermodynamic feasibility and modify them if they are infeasible so that they satisfy the law of entropy. We illustrate our method by applying it to the network dealing with the central metabolism of Escherichia coli. Due to its simplicity this algorithm will be useful in studying large scale complex metabolic networks in the cell of different organisms.

Nigam, R.↗

The third law of thermodynamics in open quantum systems

In this work, we consider open quantum systems consisting of a finite system of independent fermions with arbitrary Hamiltonian coupled to one or more equilibrium fermion reservoirs (which need not be in equilibrium with each other). A strong form of the third law of thermodynamics, S(T) → 0 as T → 0, is proven for fully open quantum systems in thermal equilibrium with their environment, defined as systems where all states are broadened due to environmental coupling. For generic open quantum systems, it is shown that S(T) → g ln 2 as T → 0, where g is the number of localized states lying exactly at the chemical potential of the reservoir. For driven open quantum systems in a nonequilibrium steady state, it is shown that the local entropy S(x;T)→0 as T(x) → 0, except for cases of measure zero arising due to localized states, where T(x) is the temperature measured by a local thermometer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stability of heterogeneous single-atom catalysts: a scaling law mapping thermodynamics to kinetics

Heterogeneous single-atom catalysts (SACs) hold the promise of combining high catalytic performance with maximum utilization of often precious metals. We extend the current thermodynamic view of SAC stability in terms of the binding energy (E bind ) of single-metal atoms on a support to a kinetic (transport) one by considering the activation barrier for metal atom diffusion. A rapid computational screening approach allows predicting diffusion barriers for metal–support pairs based on E bind of a metal atom to the support and the cohesive energy of the bulk metal (E c ). Metal–support combinations relevant to contemporary catalysis are explored by density functional theory. Assisted by machine-learning methods, we find that the diffusion activation barrier correlates with (E bind ) 2 /E c in the physical descriptor space. This diffusion scaling-law provides a simple model for screening thermodynamics to kinetics of metal adatom on a support.

36 MATERIALS SCIENCE↗

Physical Laws for Mechanobiology

Higher-level physical laws applicable to biological tissues are presented that will permit the modeling of metabolic activity at the cellular level, including variations in the mass of a tissue. Here the tissue is represented as a fluid/solid mixture, wherein molecular solutes transport within the fluid, and cells can migrate throughout the porous solid. Variations in mass can arise via exchanges in mass between the constituent phases within a control volume such that mass is conserved in the tissue overall. The governing balance laws for mass, momentum, energy, and entropy are a special case of those describing a chemically reacting mixture with diffusion. Thermodynamic constraints on the constitutive structure are addressed. Biophysics; Biomechanics; Brownian motion; Cell migration; Mixture theory; Thermodynamic laws; Tissue mechanics

Freed, Alan D.↗

Learning thermodynamically constrained equations of state with uncertainty

Numerical simulations of high energy-density experiments require equation of state (EOS) models that relate a material’s thermodynamic state variables—specifically pressure, volume/density, energy, and temperature. EOS models are typically constructed using a semi-empirical parametric methodology, which assumes a physics-informed functional form with many tunable parameters calibrated using experimental/simulation data. Since there are inherent uncertainties in the calibration data (parametric uncertainty) and the assumed functional EOS form (model uncertainty), it is essential to perform uncertainty quantification (UQ) to improve confidence in EOS predictions. Model uncertainty is challenging for UQ studies since it requires exploring the space of all possible physically consistent functional forms. Thus, it is often neglected in favor of parametric uncertainty, which is easier to quantify without violating thermodynamic laws. This work presents a data-driven machine learning approach to constructing EOS models that naturally captures model uncertainty while satisfying the necessary thermodynamic consistency and stability constraints. We propose a novel framework based on physics-informed Gaussian process regression (GPR) that automatically captures total uncertainty in the EOS and can be jointly trained on both simulation and experimental data sources. A GPR model for the shock Hugoniot is derived, and its uncertainties are quantified using the proposed framework. We apply the proposed model to learn the EOS for the diamond solid state of carbon using both density functional theory data and experimental shock Hugoniot data to train the model and show that the prediction uncertainty is reduced by considering thermodynamic constraints.

Sharma, Himanshu (ORCID:000900050235718X)↗

Space Life Support Engineering Program

This report covers the second year of research relating to the development of closed-loop long-term life support systems. Emphasis was directed toward concentrating on the development of dynamic simulation techniques and software and on performing a thermodynamic systems analysis in an effort to begin optimizing the system needed for water purification. Four appendices are attached. The first covers the ASPEN modeling of the closed loop Environmental Control Life Support System (ECLSS) and its thermodynamic analysis. The second is a report on the dynamic model development for water regulation in humans. The third regards the development of an interactive computer-based model for determining exercise limitations. The fourth attachment is an estimate of the second law thermodynamic efficiency of the various units comprising an ECLSS.

Seagrave, Richard C.↗

tLaSDI: Thermodynamics-informed latent space dynamics identification

Here we propose a latent space dynamics identification method, namely tLaSDI, that embeds the first and second principles of thermodynamics. The latent variables are learned through an autoencoder as a nonlinear dimension reduction model. The latent dynamics are constructed by a neural network-based model that precisely preserves certain structures for the thermodynamic laws through the GENERIC formalism. An abstract error estimate is established, which provides a new loss formulation involving the Jacobian computation of autoencoder. The autoencoder and the latent dynamics are simultaneously trained to minimize the new loss. Computational examples demonstrate the effectiveness of tLaSDI, which exhibits robust generalization ability, even in extrapolation. In addition, an intriguing correlation is empirically observed between a quantity from tLaSDI in the latent space and the behaviors of the full-state solution.

97 MATHEMATICS AND COMPUTING↗

Impact of fuel and engine operating conditions on efficiency of a heavy duty truck engine running compression ignition mode using energy and exergy analysis

Gasoline compression ignition using a single gasoline-type fuel for direct/port injection has been shown as a method to achieve low temperature combustion with low engine-out NO x and soot emissions and high indicated thermal efficiency. However, key technical barriers to achieving low temperature combustion on multi-cylinder engines include the air handling system (limited amount of exhaust gas recirculation) as well as mechanical engine limitations (e.g. peak pressure rise rate). In light of these limitations, high temperature combustion with reduced amounts of exhaust gas recirculation appears more practical. Previous studies by the authors demonstrated that utilizing port and direct injection of E85 gasoline simultaneously resulted in the best performance and the highest brake thermal efficiency of 47.1%, which was 1.2% higher compared to diesel baseline. For further efficiency improvement, a better understanding of energy and exergy loss mechanisms is required. As such, in this work first and second law thermodynamics analysis were applied to experiments with gasoline compression ignition at an engine speed of 1038 rpm and brake mean effective pressure of 1.4 MPa on a 12.4 L multi-cylinder heavy-duty diesel engine. The impact on the efficiency, losses, and irreversibility with respect to various parameters such as fuel, injection strategy, intake condition, and port injected water mass was quantified. The peak efficiency of ideal cycles and the combined efficiency with a waste heat recovery system were also estimated in this study to assess opportunities for further efficiency gains. It was found that the combustion irreversibility was dominated by the combustion temperature rather than the fuel structure. Despite its highest brake thermal efficiency, E85 gasoline generated the highest exergy destruction due to its lowest combustion temperature. For the same reason, retarding the combustion phasing or adopting a port and direct injection strategy increased the exergy destruction. The combustion duration loss was more notable than the phasing loss and was affected by both the combustion duration and shape of heat release profile. Water port injection increased the exhaust energy, but the available energy dropped significantly attributed to the decrease in the exhaust temperature, rendering waste heat recovery ineffective. The second law analysis serves as a helpful tool in conjunction with the first law analysis to explore pathways to maximize engine efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

Thermodynamics-informed latent space dynamics identification

This software showcases a latent space dynamics identification method, namely tLaSDI, that embeds the first and second principles of thermodynamics. The latent variables are learned through an autoencoder as a nonlinear dimension reduction model. The latent dynamics are constructed by a neural network-based model that precisely preserves certain structures for the thermodynamic laws through the GENERIC formalism. An abstract error estimate is established, which provides a new loss formulation involving the Jacobian computation of autoencoder. The autoencoder and the latent dynamics are simultaneously trained to minimize the new loss. Computational examples demonstrate the effectiveness of tLaSDI, which exhibits robust generalization ability, even in extrapolation. In addition, an intriguing correlation is empirically observed between a quantity from tLaSDI in the latent space and the behaviors of the full-state solution.

Cheung, Siu Wun↗

Scaling laws for testing of high lift airfoils under heavy rainfall

The results of studies regarding the effect of rainfall about aircraft are briefly reviewed. It is found that performance penalties on airfoils have been identified in subscale tests. For this reason, it is of great importance that scaling laws be dveloped to aid in the extrapolation of these data to fullscale. The present investigation represents an attempt to develop scaling laws for testing subscale airfoils under heavy rain conditions. Attention is given to rain statistics, airfoil operation in heavy rain, scaling laws, thermodynamics of condensation and/or evaporation, rainfall and airfoil scaling, aspects of splash back, film thickness, rivulets, and flap slot blockage. It is concluded that the extrapolation of airfoil performance data taken at subscale under simulated heavy rain conditions to fullscale must be undertaken with caution.

Bilanin, A. J.↗

A progress report on bolometers operating at 0.1 K using adiabatic demagnetization refrigeration

Bolometers are still the detectors of choice for low background infrared observations at wavelengths longer than 200 microns. In the low background limit, bolometers become more sensitive as their operating temperature decreases, due to fundamental thermodynamic laws. The adiabatic demagnetization technique was evaluated by building a bolometer detection system operating at a wavelength of 1 millimeter for use at a ground based telescope. The system was fit checked at the telescope and is expected to take its first data in November, 1985.

Roellig, T.↗

Composition, Chemistry, and Climate of the Atmosphere. 2: Mean properties of the atmosphere

The atmosphere can be defined as the relatively thin gaseous envelope surrounding the entire planet Earth. It possesses a number of properties related to its physical state and chemical composition, and it undergoes a variety of internal processes and external interactions that can either maintain or alter these properties. Whereas descriptions of the atmosphere's chemical properties form much of the remaining chapters of this book, the present chapter will highlight the atmosphere's gases, and these define its temperature structure. In contrast, the larger-scale motions comprise the winds, the global organization of which is often referred to as the general circulation. The framework of the dynamical and thermodynamical laws, including the three principles of conversation of mass, momentum, and energy, are fundamental in describing both the internal processes of the atmosphere and its external interactions. The atmosphere is not a closed system, because it exchanges all three of these internally conservative quantities across the atmosphere's boundary below and receives input from regions outside it. Thus surface fluxes of moisture, momentum, and heat occur to and from the underlying ocean and land. The atmosphere exchanges very little mass and momentum with space, though it absorbs directly a portion of the solar radiational energy received from above.

Singh, Hanwant B.↗