Thermodynamic Principles Research Articles

A finite strain viscoelastic model with damage and tension–compression asymmetry considerations for solid propellants

A short survey on the experimental testing of solid propellants has highlighted finite strain responses that are temperature-dependent, viscoelastic with damage, and exhibit tension/compression asymmetry. Consequently, a finite strain viscoelastic model that satisfies the principles of thermodynamics has been developed. This model is based on the common multiplicative decomposition of the deformation gradient into elastic and viscous components, with considerations for damage and asymmetry. The model has been tested against three sets of data from the literature, carefully selected to represent the various characteristics of solid propellants. The model accurately reproduces uniaxial tension responses at different strain rates and temperatures, with the capability to account for superimposed hydrostatic pressure. Notably, these satisfactory representations require only five fitting parameters, in addition to the typical identification of polymer linear viscoelasticity and time–temperature superposition. Finally, an attempt to reproduce both tension and compression tests conducted independently on the same material underscores the need to account for tension–compression asymmetry, as defined in the proposed constitutive equations. This finding advocates for new tests, such as compression following tension and vice versa.

Thermodynamic properties and geometries of bardeen black hole surrounded by string clouds

In this work, we investigate the thermodynamic properties of Bardeen black hole which is coupled with cloud of strings and minimally coupled to nonlinear electrodynamics. The modified entropy in the form of Sharma–Mittal entropy is used to discuss these properties which include mass, temperature, pressure, Gibbs free energy and trace of Hessian matrix. We obtain stable behavior along with physical solution for some specific values of parameters a and q. Furthermore, our work provides a thermodynamic metric using the Hessian matrix of black hole mass, changing the conformal connection between Quevedo and Ruppeiner’s geometries. Investigating the first principle of thermodynamics for regular black holes, such as the Bardeen AdS black hole, exposes significant behavior changes during phase transitions in an extended phase space.

Overview of steam turbines and efficiency

Thermal power plants, which produce energy from the burning of fossil fuels that in turn generate turbine-turning steam, contribute a large proportion of energy in the world. Research on how we could apply fluid dynamic and thermodynamic principles in the design of turbines is crucial to improving their efficiency and fuel consumption. This paper mainly aims to explore and summarize how the power efficiency of turbines is maximized in thermal power plants and analyze the designs of turbines that increase proficiency. Literature and past paper review will be the primary method of this research. The main findings of this research are that efficiency in thermal turbines can be increased in three principal ways: a multi-stage expansion mechanism, the application of alternating blades, and in implementation of a reheating system. Using these methods, efficiency has been increased almost a million-fold in steam turbines. The purpose of this paper is to gain insights into how energy output in thermal power plant turbines is maximized and the specific designs of turbines that improve its efficiency.

Statistical uncertainty principle in Markov kinetics

A reciprocality between the statistical variance of observables of a thermodynamic state and that of their conjugate variables, as entropic forces, originates from the thermodynamic conjugacy with respect to an entropy function. This thermodynamic uncertainty principle in equilibrium can be derived from the Maximum Entropy principle and is independent upon underlying mechanistic details. We present, based on the Maximum Caliber principle as the dynamic generalization of Maximum Entropy, the formalism of the uncertainty principle in kinetics in time homogeneous Markov processes between transitional observables and their conjugate path entropic forces. A stochastic biophysical model for molecular motors is used as an illustrating example. The present work generalizes the phenomenological thermodynamics of uncertainties/fluctuations and is applicable to data ad infinitum.

Maximizing interface stability in all-solid-state lithium batteries through entropy stabilization and fast kinetics

The positive electrode|electrolyte interface plays an important role in all-solid-state Li batteries (ASSLBs) based on garnet-type solid-state electrolytes (SSEs) like Li6.4La3Zr1.4Ta0.6O12 (LLZTO). However, the trade-off between solid-solid contact and chemical stability leads to a poor positive electrode|electrolyte interface and cycle performance. In this study, we achieve thermodynamic compatibility and adequate physical contact between high-entropy cationic disordered rock salt positive electrodes (HE-DRXs) and LLZTO through ultrafast high-temperature sintering (UHS). This approach constructs a highly stable positive electrode|electrolyte interface, reducing the interface resistance to 31.6 Ω·cm2 at 25 °C, making a 700 times reduction compared to the LiCoO2 | LLZTO interface. Moreover, the conformal and tight HE-DRX | LLZTO solid-state interface avoids the transition metal migration issue observed with HE-DRX in liquid electrolytes. At 150 °C, HE-DRXs in ASSLBs (Li|LLZTO | HE-DRXs) exhibit an average specific capacity of 239.7 ± 2 mAh/g at 25 mA/g, with a capacity retention of 95% after 100 cycles relative to the initial cycle—a stark contrast to the 76% retention after 20 cycles at 25 °C in conventional liquid batteries. Our strategy, which considers the principles of thermodynamics and kinetics, may open avenues for tackling the positive electrode|electrolyte interface issue in ASSLBs based on garnet-type SSEs.

Predicting Energy Consumption for Hybrid Energy Systems toward Sustainable Manufacturing: A Physics-Informed Approach Using Pi-MMoE

Hybrid energy supply systems are widely utilized in modern manufacturing processes, where accurately predicting energy consumption is essential not only for managing productivity but also for driving sustainable development. Effective energy management is a cornerstone of sustainable manufacturing, reducing waste and enhancing efficiency. However, conventional studies often focus solely on predicting single types of energy consumption and overlook the integration of physical laws and information, which are essential for a comprehensive understanding of energy dynamics. In this context, this paper introduces a multi-task physics-informed multi-gate mixture-of-experts (pi-MMoE) model that not only considers multiple forms of energy consumption but also incorporates physical principles through the integration of physical information and multi-task modeling. Specifically, a detailed analysis of manufacturing processes and energy patterns is first conducted to study various energy types and extract relevant physical laws. Next, using industry insights and thermodynamic principles, key equations for energy balance and conversion are derived to create a physics-based loss function for model training. Finally, the pi-MMoE model framework is constructed, featuring multi-expert networks and gating mechanisms to balance cross-task knowledge sharing and expert learning. In a case study of a textile factory, the pi-MMoE model reduced electricity and steam prediction errors by 14.28% and 27.27%, respectively, outperforming traditional deep learning methods. This demonstrates that the model can improve prediction performance, providing a novel approach to intelligent energy management and promoting sustainable development in manufacturing.

Research of influence of diluent on the mechanical behavior of triaxial warp-knitted composites

The composites are prepared by different processes of reinforcement and matrix, which are affected by the properties of reinforcement and matrix. In this study, composite specimens were fabricated using vacuum-assisted resin infusion (VARI) with varying mass fractions (0%, 5%, 10%, and 15%) of a diluent mixed with the resin and curing agent, serving as the matrix. Triaxial warp-knitted glass fabric was employed as the reinforcement material. The impact of the diluent mass fraction on the bending, impact, and creep properties of the composites was investigated. The least squares fitting method was applied to analyze the experimental data, leading to the establishment of a mathematical model correlating the diluent mass fraction with the bending strength. The optimal diluent mass fraction for achieving the best bending properties was determined. Furthermore, the failure mechanisms of the composites were examined through an analysis of their thermodynamic properties, reaction principles, and fracture morphologies. The results show that the epoxy group in the diluent will be connected to the cross-linking network structure of epoxy resin by ring-opening reaction, and excessive addition will lead to the increase of flexible chain segments, which makes the mechanical properties of the specimens increase first and then decrease. The mathematical model was verified by experiments, and the mass fraction of diluent was 9.65% when the bending property was optimal.

Influence of fire severity and concrete properties on the thermo‐hygral behavior of concrete during fire exposure

AbstractSince the world is transitioning toward performance based design, the study of thermo‐hygral behavior of concrete when subjected to real fire becomes crucial. Fire accidents have revealed that nominal fire curves cannot be applied because of varying severity of real fire. In 2008, traveling fire concept was developed in which severity is dependent on heat release rate and fire size. This study explores the effect of fire severity and other concrete properties like strength, aggregate type, and relative humidity. The proposed model has been developed by combining the principles of mechanics and thermodynamics and upon validation with the experimental results, a reasonable agreement has been observed. It can be concluded that severity of fire is directly related to thermo‐hygral behavior of concrete. On the other hand, this study also highlights the influence of type of aggregate and moisture content in addition to the traditional variables like volume fraction of solid and permeability. On studying the influence of type of aggregate, it can be concluded that recycled aggregate concrete performed better than conventional concrete. The integration of proposed model in the performance based design is a leap toward development of resilient structure subjected to dynamic fire conditions.

Interface stabilization and propagation in phase field models of solidification: resolving the issue of large driving forces

Abstract One of the long-standing problems in the phase field, namely, combining the principles of thermodynamics and capillarity with the numerical aspects of interface propagation in simulations, is re-investigated. Numerical schemes are discussed which allow for stable simulations with arbitrary driving forces, considering or excluding capillarity. We re-investigate a classical stabilization scheme that decouples interface stabilization from curvature evaluation, ensuring stable simulations even under large driving forces. A novel mathematical analysis gives a rigorous estimate for the time stepping and a numerical value of the required stabilization strength. The proposed stabilization scheme is benchmarked for 3-dimensional dendritic growth under directional solidification conditions for different solidification speeds.

Recent Trends in the Mathematical Modelling of Electrochemical Impedance Spectroscopy of Lithium-Ion Batteries

Electrochemical Impedance Spectroscopy (EIS) has emerged as a great alternative tool to characterize electrochemical energy storage systems such as batteries[1, 2]. A commercial Li-ion battery is essentially an electrochemical system having a multitude of physical and chemical processes occurring simultaneously while in operation. Each of these processes is governed by thermodynamic and kinetic principles and possesses a characteristic time scale. Thus, based on the frequency response, we can distinguish between individual mechanisms operating within the battery in a non-destructive manner via EIS [1].Numerical modeling is a powerful tool to understand the battery system from a theoretical perspective[3]. Development of high-fidelity, multiscale, and multicomponent models can be a complex and computationally expensive endeavor. Therefore, simple models, with generalization about the physics of the problem, are sought initially upon which more complex models are built.Traditional EIS simulation approaches include Equivalent Circuit Models (ECMs), which aim to represent the battery as an electrical circuit. This approach suffers from its empirical nature and lack of physical interpretability[2]. Another approach is to work with physics-based models. Electrochemical Impedance Spectroscopy, being a frequency domain technique, needs a special treatment to be done on the time domain Partial Differential Equations (PDEs) to be solved in a steady state. This process involves linearizing the model equations and applying the Laplace transform. Physics-based models have a better fidelity but suffer from high computational costs.[4] Therefore, fast, reduced-order physics-based models have been developed by researchers that aim to maintain the physical consistency of the model at the same time reducing the computational cost.[5] Recent years have also seen a surge in new machine learning-based techniques to replicate the impedance response of the batteries.[6]The present work aims to summarize the various techniques of EIS modeling and discuss their relative advantages and shortcomings in a comprehensive manner.

Advancements in Aqueous Two-Phase Systems for Enzyme Extraction, Purification, and Biotransformation.

In recent years, the increasing need for energy conservation and environmental protection has driven industries to explore more efficient and sustainable processes. Liquid-liquid extraction (LLE) is a common method used in various sectors for separating components of liquid mixtures. However, the traditional use of toxic solvents poses significant health and environmental risks, prompting the shift toward green solvents. This review deals with the principles, applications, and advantages of aqueous two-phase systems (ATPS) as an alternative to conventional LLE. ATPS, which typically utilize water and nontoxic components, offer significant benefits such as high purity and single-step biomolecule extraction. This paper explores the thermodynamic principles of ATPS, factors influencing enzyme partitioning, and recent advancements in the field. Specific emphasis is placed on the use of ATPS for enzyme extraction, showcasing its potential in improving yields and purity while minimizing environmental impact. The review also highlights the role of ionic liquids and deep eutectic solvents in enhancing the efficiency of ATPS, making them viable for industrial applications. The discussion extends to the challenges of integrating ATPS into biotransformation processes, including enzyme stability and process optimization. Through comprehensive analysis, this paper aims to provide insights into the future prospects of ATPS in sustainable industrial practices and biotechnological applications.

Exergy, exergoeconomic optimization and exergoenvironmental analysis of a hybrid solar, wind, and marine energy power system: A strategy for carbon-free electrical production

In this research, aligned with global policies aimed at reducing CO2 emissions from traditional power plants, we developed a holistic energy system utilizing solar, wind, and ocean thermal energy sources, tailored to regions optimal for ocean thermal energy conversion (OTEC). The selected site, characterized by favorable wind and solar conditions close to areas with high OTEC potential, is designed to meet the electricity needs of a coastal community. The system's core components include an Organic Rankine Cycle, turbines, thermoelectric elements, pumps, a heat exchanger, a wind turbine, and a solar collector. A detailed system analysis and thermodynamic evaluation based on thermodynamic principles were carried out using the Engineering Equation Solver (EES) software. Key factors such as wind speed, solar radiation, and collector area were critical in determining system performance. To enhance the system's effectiveness, we conducted a comprehensive comparison of optimization algorithms, incorporating the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and utilizing a Pareto front for value optimization. This approach significantly outperformed other algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Simulated Annealing (SA) in terms of system efficiency and cost-effectiveness. The developed system achieved an exergy efficiency of 14.46 % and a cost rate of $74.98 per hour, demonstrating its suitability for its intended functions. Moreover, exergoenvironmental evaluation was conducted for the proposed plant. The findings revealed that key component HEX has a high exergoenvironmental factor due to their use of hot water, which has zero unit exergoenvironmental impact. Additionally, pumps demonstrated a zero exergoenvironmental impact factor, indicating negligible component-related environmental impacts. Sensitivity analysis further evaluated critical performance parameters, revealing that increases in solar irradiation lead to decreased total system cost rates, while higher turbine temperatures resulted in a remarkable 14.08 % reduction in the system's cost rate. These results underscore the economic viability of operating the system at higher temperatures and strengthen the argument for its adoption from a financial perspective.

A phase-field framework for modeling multiple cohesive fracture behaviors in laminated composite materials

This work proposes a phase-field (PF) framework to characterize the multiple fracture behaviors and quasi-brittle failure mechanisms in fiber reinforced laminated composites. The multi-phase field model considering the distinct failure mechanisms of composites is first derived based on thermodynamic principles. A hybrid PF formulation is proposed through the reasonable definition of the energy functional for each field, and a PF regularized cohesive zone model (CZM) combined with Hashin failure criteria is achieved for the typical failure modes in composites. The proposed PF-CZM is endowed with a linear softening behavior and is proven to be independent of the internal length scale parameter. The multiple fracture modeling of composite laminates is achieved by coupling the PF model for intralaminar failure with the cohesive interface element for interlaminar one. The model’s validation is demonstrated by several representative numerical examples, and results show that both the intralaminar fiber/matrix fractures and the induced interlaminar delamination, as well as their complex interactions, are well captured by the proposed model.

Remarkable enhancement of the corrosive-wear resistance for Ti-Zr-Hf-Nb-Fe high-entropy alloys by a facile high-temperature oxidation treatment

The surface performances of TiZrHfNbFe refractory high-entropy alloys (RHEAs) were improved by a facile oxidation treatment at 1000 °C. Results indicated that the anomalous retarded oxidation behavior of the RHEA enabled the formation of a dense and robust oxide layer, demonstrating superior wear and corrosion resistance. The oxidation resistance of the RHEA was related to the development of Ti2ZrO6 on the surface and acicular HfO2 in the inner oxide layer. Additionally, the oxidation mechanism of the RHEA was elucidated, based on principles of oxidation thermodynamics and kinetics, providing foundations for applications as implant materials.

Directionality of gravitational and thermal diffusive transport in geologic fluid storage.

Diffusive transport has implications for the long-term status of underground storage of hydrogen (H_{2}) fuel and carbon dioxide (CO_{2}), technologies which are being pursued to mitigate climate change and advance the energy transition. Once injected underground, CO_{2} and H_{2} will exist in multiphase fluid-water-rock systems. The partially soluble injected fluids can flow through the porous rock in a connected plume, become disconnected and trapped as ganglia surrounded by groundwater within the storage rock pore space, and also dissolve and migrate through the aqueous phase once dissolved. Recent analyses have focused on the concentration gradients induced by differing capillary pressure between fluid ganglia which can drive diffusive transport ("Ostwald ripening"). However, studies have neglected or excessively simplified important factors, namely the nonideality of gases under geologic conditions, the opposing equilibrium state of dissolved CO_{2} and H_{2} driven by the partial molar density of dissolved solutes, and entropic and thermodiffusive effects resulting from geothermal gradients. We conduct an analysis from thermodynamic first principles and use this to provide numerical estimates for CO_{2} and H_{2} at conditions relevant to underground storage reservoirs. We show that while diffusive transport in isothermal systems is upwards for both gases, as indicated by previous analysis, entropic contributions to the free energy are so significant as to cause a reversal in the direction of diffusive transport in systems with geothermal gradients. For CO_{2}, even geothermal gradients less than 10^{∘}C/km (far less than typical gradients of 25^{∘}C/km) are sufficient to induce downwards diffusion at depths relevant to storage. Diffusive transport of H_{2} is less affected but still reverses direction under typical gradients, e.g., 30^{∘}C/km, at a depth of 1000m. This reversal occurs independent of the solute's thermophobicity or thermophilicity in aqueous solutions. The entropic contribution also modifies the magnitude of flux where geothermal gradients are present, with the largest diffusive fluxes estimated for CO_{2} with a 30^{∘}C/km gradient, despite the higher diffusion coefficient of H_{2}. We find a maximum flux on the order of 10^{-13} mol/(cm^{2}s) for CO_{2} in the 30^{∘}C/km scenario; significantly lower than literature estimates for maximum convective fluxes in moderate to high permeability formations. Contrary to previous studies, we find that in diffusion and convection will likely work in concert-both driving CO_{2} downwards, and both driving H_{2} upwards-for conditions representative of their respective storage reservoirs.

Process Modeling and Optimization of Supercritical Carbon Dioxide-Enhanced Geothermal Systems in Poland

This paper presents a comprehensive analysis of supercritical carbon dioxide (sCO2)-enhanced geothermal systems (EGSs) in Poland, focusing on their energetic performance through process modeling and optimization. EGSs harness the potential of geothermal energy by utilizing supercritical carbon dioxide as the working fluid, offering promising avenues for sustainable power generation. This study investigates two distinct configurations of sCO2-EGS: one dedicated to power generation via a binary system with an organic Rankine cycle and the other for combined power and heat production through a direct sCO2 cycle. Through accurate process modeling and simulation, key parameters influencing system efficiency and performance are identified and optimized. The analysis integrates thermodynamic principles with geological and operational constraints specific to the Polish context. The results highlight the potential of sCO2-EGSs to contribute to the country’s energy transition, offering insights into the optimal design and operation of such systems for maximizing both power and thermal output while ensuring economic viability and environmental sustainability.

Discretisations of mixed-dimensional Thermo-Hydro-Mechanical models preserving energy estimates

In this study, we explore mixed-dimensional Thermo-Hydro-Mechanical (THM) models in fractured porous media accounting for Coulomb frictional contact at matrix fracture interfaces. The simulation of such models plays an important role in many applications such as hydraulic stimulation in deep geothermal systems and assessing induced seismic risks in CO2 storage. We first extend to the mixed-dimensional framework the thermodynamically consistent THM models derived in [19] based on first and second principles of thermodynamics. Two formulations of the energy equation will be considered based either on energy conservation or on the entropy balance, assuming a vanishing thermo-poro-elastic dissipation. Our focus is on space time discretisations preserving energy estimates for both types of formulations and for a general single phase fluid thermodynamical model. This is achieved by a Finite Volume discretisation of the non-isothermal flow based on coercive fluxes and a tailored discretisation of the non-conservative convective terms. It is combined with a mixed Finite Element formulation of the contact-mechanical model with face-wise constant Lagrange multipliers accounting for the surface tractions, which preserves the dissipative properties of the contact terms. The discretisations of both THM formulations are investigated and compared in terms of convergence, accuracy and robustness on 2D test cases. It includes a Discrete Fracture Matrix model with a convection dominated thermal regime, and either a weakly compressible liquid or a highly compressible gas thermodynamical model.

KnowTD─An Actionable Knowledge Representation System for Thermodynamics.

We demonstrate that thermodynamic knowledge acquired by humans can be transferred to computers so that the machine can use it to solve thermodynamic problems and produce explainable solutions with a guarantee of correctness. The actionable knowledge representation system that we have created for this purpose is called KnowTD. It is based on an ontology of thermodynamics that represents knowledge of thermodynamic theory, material properties, and thermodynamic problems. The ontology is coupled with a reasoner that sets up the problem to be solved based on user input, extracts the correct, pertinent equations from the ontology, solves the resulting mathematical problem, and returns the solution to the user, together with an explanation of how it was obtained. KnowTD is presently limited to simple thermodynamic problems, similar to those discussed in an introductory course in Engineering Thermodynamics. This covers the basic theory and working principles of thermodynamics. KnowTD is designed in a modular way and is easily extendable.

Commercial Carbon Fibers as Host for Sodium Deposition to Achieve High Volumetric Capacity

AbstractThe advancement of flexible electronic devices necessitates the utilization of electrode materials that offer robustness and high capacity. In this paper, it is revealed that commercially available carbon fibers with specific microcrystalline structures not only have high mechanical strength but also a high volumetric capacity of up to 300 mAh cm−3, surpassing conventional carbon materials. When multiple structural parameters of carbon fiber reach certain thresholds, a breakthrough in sodium storage capacity and rate performance can be achieved. This study further elucidates the mechanism whereby this specific carbon fiber primarily utilizes an all‐plateau sodium deposition mechanism, which occurs in pore‐like grain boundaries. Through in situ spectroscopy and synchrotron techniques, the reversible deposition process of metallic sodium has been revealed at different scales. Theoretical calculations and thermodynamic principles further confirm the desolvation and deposition mechanisms in carbon fibers. As a result, this research discovers the modulating effects and patterns of crystallinity, defect, and orientation of carbon materials on sodium storage sites and diffusion kinetics, thereby achieving controlled sodium storage. This work shows that commercial carbon fibers can serve as robust hosts for sodium deposition and enhances the theoretical understanding of how the microcrystalline structure of carbon materials relates to sodium storage properties.

Unravelling the thermodynamic properties of soil ecosystems in mature beech forests

Thermodynamics is a vast area of knowledge with a debatable role in explaining the evolution of ecosystems. In the case of soil ecosystems, this role is still unclear due to difficulties in determining the thermodynamic functions that are involved in the survival and evolution of soils as living systems. The existing knowledge is largely based on theoretical approaches and has never been applied to soils using thermodynamic functions that have been experimentally determined. In this study, we present a method for the complete experimental thermodynamic characterization of soil organic matter. This method quantifies all the thermodynamic functions for combustion and formation reactions which are involved in the thermodynamic principles governing the evolution of the universe. We applied them to track the progress of soil organic matter with soil depth in mature beech forests. Our results show that soil organic matter evolves to a higher degree of reduction as it is mineralized, yielding products with lower carbon but higher energy content than the original organic matter used as reference. These products have higher entropy than the original one, demonstrating how the soil ecosystem evolves with depth, in accordance with the second law of thermodynamics. The results were sensitive to soil organic matter transformation in forests under different management, indicating potential applicability in elucidating the energy strategies for evolution and survival of soil systems as well as in settling their evolutionary states.