Entropy Production Rate Research Articles

Entropy generation and Cattaneo–Christov heat flux analysis of binary and ternary hybrid Maxwell nanofluid flows with slip and convective conditions

Hybrid nanomaterials significantly enhance thermal systems through improved thermal conductivity, efficient energy storage, and customized thermomechanical properties. Due to their superior thermophysical characteristics, binary/ternary hybrid nanofluids are crucial in fields such as industry, biomedicine, transportation, and pharmaceuticals. This study examines the hydromagnetic flows and heat transfer properties of binary (CuO+Fe3O4/sodium alginate) and ternary (CuO+Fe3O4+MoS2/sodium alginate) hybrid Maxwell nanofluids over a radially stretching rotating disk. The governing flow equations incorporate Cattaneo–Christov heat flux, mixed convection, velocity and thermal slips, nonlinear radiation, viscous dissipation, and Joule heating in a Darcy–Forchheimer porous medium. These axisymmetric partial differential equations are transformed into ordinary differential equations using similarity variables, and the spectral quasilinearization method (SQLM) is applied for numerical solutions. Results reveal the effects of relevant parameters on velocity, temperature, skin friction, and heat transfer rates. Novelty lies in the comparative analysis of flow behaviors and entropy production rates between binary and ternary hybrid Maxwell nanofluids. When the heat source is included, the Nusselt number increases by 12.9% for ternary nanofluids and 16.07% for binary nanofluids as the thermal relaxation number increases from 0.5 to 1.5. Furthermore, the ternary hybrid nanofluid shows greater resistance to Lorentz and porous medium forces and exhibits a higher temperature distribution and better thermal management capabilities compared to the binary hybrid nanofluid.

Uncovering nonequilibrium from unresolved events.

Closely related to the laws of thermodynamics, the detection and quantification of disequilibria are crucial in unraveling the complexities of nature, particularly those beneath observable layers. Theoretical developments in nonequilibrium thermodynamics employ coarse-graining methods to consider a diversity of partial information scenarios that mimic experimental limitations, allowing the inference of properties such as the entropy production rate. A ubiquitous but rather unexplored scenario involves observing events that can possibly arise from many transitions in the underlying Markov process-which we dub multifilar events-as in the cases of exchanges measured at particle reservoirs, hidden Markov models, mixed chemical and mechanical transformations in biological function, composite systems, and more. We relax one of the main assumptions in a previously developed framework, based on first-passage problems, to assess the non-Markovian statistics of multifilar events. By using the asymmetry of event distributions and their waiting times, we put forward model-free tools to detect nonequilibrium behavior and estimate entropy production, while discussing their suitability for different classes of systems and regimes where they provide no new information, evidence of nonequilibrium, a lower bound for entropy production, or even its exact value. The results are illustrated in reference models through analytics and numerics.

Cotunneling Effects in the Geometric Statistics of a Nonequilibrium Spin‐Resolved Junction

AbstractIn the nonequilibrium steady state of electronic transport across a spin‐resolved quantronic junction, the role of cotunneling on the emergent statistics under phase‐different adiabatic modulation of the reservoirs' chemical potentials is investigated. By explicitly identifying the sequential and inelastic cotunneling rates, the geometric or Pancharatnam–Berry contribution to the spin exchange flux between the spin system and the right reservoir is numerically evaluated. The relevant conditions wherein the sequential and cotunneling processes compete and selectively influence the total geometric flux upshot are identified. The Fock space coherences are found to suppress the cotunneling effects when the system reservoir couplings are comparable. The cotunneling contribution to the total geometric flux can be made comparable to the sequential contribution by creating a right‐sided asymmetrically stronger system‐reservoir coupling strength. Using a recently proposed geometric thermodynamic uncertainty relationship, the total rate of minimal entropy production is estimated. The geometric flux and the minimum entropy is found to be nonlinear as a function of the interaction energy of the junctions' spin orbitals.

Hydrothermal performance and irreversibility production of distilled H2O flowing in outwardly-corrugated converging pipes

The study of performance parameters that characterize the convective heat transfer performance (CHTP) and entropy production rates (EPR) of fluids is of great importance in science and engineering due to its widespread applications in the design of new thermal devices. This study considers the turbulent CHTP and EPR of distilled H 2 O flowing in outwardly-corrugated converging pipes (OCCPs) and investigates the influence of the diameter ratio DR ( 1 ≤ DR ≤ 2 ) on the behavior of performance parameters against the Reynolds numbers (Re) within the range ( 5.0 × 10 3 ≤ Re ≤ 5.0 × 10 4 ). The governing equations and boundary conditions are solved with the use of SST k − ω turbulence model. The considered OCCP is designed such that its average diameter is 0.03m while its normalized length is 26.6. It is obtained that increasing DR enhances the average Nusselt number (Nu), Poiseuille number (fRe), and EPR whereas the reverse is the case for thermal effective number ( I G ), Bejan number (Be), and performance evaluation criterion (PEC). At Re = 2.0 × 10 4 in OCCPs of DR = 1.00, 1.25, 1.50, 1.75, and 2.00, EPR is increased by factors 0.88, 1.42, 2.64, 4.84, and 9.61; fRe is improved by factors 3.39, 8.54, 16.27, 27.74, and 49.22; and Nu is enhanced by factors 1.28, 1.31, 1.34, 1.37, and 1.43, respectively. The enhancement is attributed to the flow acceleration, vortices production, and high mixing rate of the hot fluid near the wall with the cold fluid at the core fluid zone. Finally, and among other things it is revealed that the OCCPs of DR = 1.00, 1.25, and 1.50 are advantageous ( I G > 1 ) over the straight tube within the range 5 × 10 3 ≤ Re < 2.25 × 10 4 .

Energy loss analysis in two-stage turbine of compressed air energy storage system: Effect of varying partial admission ratio and inlet pressure

The compressed air energy storage (CAES) system experiences decreasing air storage pressure during energy release process. To ensure system stability, maintaining a specific pressure difference between air storage and turbine inlet is necessary. Hence, adopting a judicious air distribution scheme for the turbine is crucial. Partial admission, based on reasoned nozzle governing methods, enhances system performance. This investigation explores the impact of varying partial admission ratio (PAR) and inlet pressure on flow dynamics and loss characteristics under rated output power. Full circumferential numerical simulations of a two-stage axial turbine within CAES system elucidates insights. First-stage efficiency declines linearly with decreasing PAR, while second-stage displays escalating reductions. Principally, turbine energy losses primarily stem from the entropy production rate (EPR) by turbulent dissipation and EPR arising from heat transfer with fluctuating temperature gradients. Partial admission significantly affects losses within the rotor, especially within the second stage. Leaving velocity loss for 50 % PAR is about 3 times that of 100 % PAR. The percentage of losses within R2 for 50 % PAR increases by 6.7 % compared with that for 100 % PAR. This research provides theoretical insights for designing, regulating, and optimizing nozzle governing and partial admission turbines in CAES systems.

Entropy production rate and correlations in a cavity magnomechanical system

We present the irreversibility generated by a stationary cavity magnomechanical system composed of a yttrium iron garnet (YIG) sphere with a diameter of a few hundred micrometers inside a microwave cavity. In this system, the magnons, i.e., collective spin excitations in the sphere, are coupled to the cavity photon mode via magnetic dipole interaction and to the phonon mode via magnetostrictive force (optomechanical-like). We employ the quantum phase-space formulation of the entropy change to evaluate the steady-state entropy production rate and associated quantum correlation in the system. We find that the behavior of the entropy flow between the cavity photon mode and the phonon mode is determined by the magnon-photon coupling and the cavity photon dissipation rate. Interestingly, the entropy production rate can increase/decrease depending on the strength of the magnon-photon coupling and the detuning parameters. We further show that the amount of correlations between the magnon and phonon modes is linked to the irreversibility generated in the system for small magnon-photon coupling. Our results demonstrate the possibility of exploring irreversibility in driven magnon-based hybrid quantum systems and open a promising route for quantum thermal applications. Published by the American Physical Society 2024

Non-Equilibrium Enhancement of Classical Information Transmission.

Information transmission plays a crucial role across various fields, including physics, engineering, biology, and society. The efficiency of this transmission is quantified by mutual information and its associated information capacity. While studies in closed systems have yielded significant progress, understanding the impact of non-equilibrium effects on open systems remains a challenge. These effects, characterized by the exchange of energy, information, and materials with the external environment, can influence both mutual information and information capacity. Here, we delve into this challenge by exploring non-equilibrium effects using the memoryless channel model, a cornerstone of information channel coding theories and methodology development. Our findings reveal that mutual information exhibits a convex relationship with non-equilibriumness, quantified by the non-equilibrium strength in transmission probabilities. Notably, channel information capacity is enhanced by non-equilibrium effects. Furthermore, we demonstrate that non-equilibrium thermodynamic cost, characterized by the entropy production rate, can actually improve both mutual information and information channel capacity, leading to a boost in overall information transmission efficiency. Our numerical results support our conclusions.

Entropy generation and heatline visualization of magnetized thermal convection in an irregular enclosure filled with nanofluid and subject to non-uniform heating: FEM-machine learning hybrid approach

This investigation's primary objective is to analyze the fluid dynamics and heat transfer enhancement in an irregular enclosure. Several physical phenomena such as Alumina-water nanofluids, magnetic field, non-uniform heating and amplitude of non-uniform heating are taken into account. A thorough investigation using machine learning algorithms (MLAs) and computational fluid dynamics (CFD) is carried out. Initially, for CFD phase the coupled non-linear dimensionless governing equations of the considered problem are solved numerically by adapting a Finite Element method (FEM) using appropriate boundary conditions. The analysis considers a range of physical parameters, such as the Hartmann number (0–20), nanoparticle volume friction (0–0.04), Ryleigh number (103-105), offset temperature (0.1–1), frequency (1-10) and non-uniform heating amplitude (0.1–1). The numerical results are explicated in the form of streamlines, isotherms, heatlines structures. The impact of these factors on entropy generation is also explored. In addition, three popular MLAs, Random Forest (RF), Artificial Neural Network (ANN) and Support Vector Machine (SVM) were used to save the computational costs. The finding explore Hartmann number and nanoparticle volume friction has decreasing trend on total entropy production and heat transfer rate. The entropy production decreases up to 42.02 % for Hartman number and for nanoparticles it decreases 12.61 %. However, the non-uniform heating amplitude has opposite effect on irreversibility factor. Also, compared to other MLAs, the ANN model demonstrates more accurate predictions. The objective is to propose novel concept for enhancing the performance of cooling systems and optimizing energy utilization across diverse technical domain.

Hydraulic loss analysis of turbodrill blade cascades based on entropy production theory

Turbodrill is a kind of high-temperature resistant downhole motor which is commonly used in drilling deep and high-temperature wells. It belongs to multi-stage axial flow turbomachinery. There are complex flow losses in turbodrill blade cascades, but conventional flow-loss evaluation methods cannot obtain the location of losses in cascades. The entropy production method constructs the relationship between flow field parameters and flow losses, so the location where flow losses generate can be obtained, which is commonly used to analyze the flow losses in various flows. In this paper, entropy production method is used to obtain the magnitude and position of hydraulic losses in turbodrill blade cascades. The single passage calculation model of three-stage stator and rotor is established, and CFD method is employed to compute the flow field parameters at different viscosities and rotary speeds. Different kinds of entropy production rates and values are calculated. Finally, the total flow loss calculated by entropy production method is compared with that calculated by pressure difference method, and the contrastive result is very similar, which indicates the correctness of entropy production method. The results show that the high entropy production regions are mainly located near the walls and the position changes with variations in rotary speed and viscosity, and the stator entropy production value is always lower than that in rotor. In addition, when the fluid viscosity is low, the main types of entropy production are turbulent entropy production and wall friction entropy production, while when the fluid viscosity is high, the main types of entropy production are direct entropy production and turbulent entropy production. Furthermore, the rotary speed variation has a greater impact on turbulent entropy production and wall friction entropy production compared to viscosity change, while the viscosity change has a greater impact on direct entropy production than the variation rotary speed. This paper introduces entropy production method into flow losses analysis for turbodrill, presenting a new approach for studying flow losses and providing a reference for improving turbodrill design.

Improvement of energy performance of a two-way pumping station based on controllable diffusion technology

Energy performance is a crucial parameter for evaluating a two-way pumping station. However, the sharp decrease in efficiency within overload flow rates presents a challenge. To address this issue, the controllable diffusion technology (CDT) is developed based on asymmetric inflow theory. Transient numerical simulation is carried out under five different distortion angles. The energy performance and entropy production dissipation before and after the application of CDT are comprehensively studied. (a) First, CDT successfully improves the operation efficiency within the overload flow rate range. The reverse distortion has a better improvement effect than the syntropic distortion. (b) Second, under asymmetric inflow conditions, the reduction in the axial velocity causes the best-efficiency point to deviate toward the overload flow rate. This leads to an increase in the total entropy production (TEP) within 0.7Qdes–0.95Qdes, followed by a decrease within 1.05Qdes–1.3Qdes. (c) Third, the CDT-induced horizontal velocity causes a mismatch between the impeller inflow angle and blade placement angle, which leads to uneven spatial distribution of the total entropy production rate inside the pumping station.

Thermo-magnetic convection of MHD Casson fluid in a wavy triangular porous cavity with embedded a cold inverted triangle obstacle

The design of enclosures is crucial in thermal engineering applications and technologies, encompassing areas such as electronics, heat transfer devices, power reactors, heating systems, solar panels, and nuclear power plants. Thermal efficiency in microchannels is optimized and improved by using triangular enclosures with varying aspect ratios. Specifically, the purpose of these triangular enclosures with cool cylinders is to reduce energy loss in nanoscale thermal sinks and thermal exchange devices. The current study aims to explore the thermal radiation effects on magnetohydrodynamic MHD Casson fluid flow within a wavy triangular cavity that includes an embedded cold inverted triangle. The inner inverted triangle is kept at a lower temperature, while the wavy bottom wall of the outer triangular cavity acts as an isothermal heat source at a higher temperature. The numerical solution for this mathematical model is obtained using the open-source finite element software COMSOL. In this study, the wavy triangular enclosure is analyzed for key parameters such as Casson parameter β , Hartmann number Ha , Rayleigh number Ra , numbers of undulation N , radiation Rd and inclination γ . The study presents the local distribution of streamlines, velocity profiles, isothermals, and entropy production, along with the Nu avg . The results reveal the rate of heat transport and total entropy production raise with the increasing number of undulations N and the Casson parameter β , while they decrease with increasing Hartmann number Ha . The number Nu avg rises with the increasing radiation parameter Rd and Rayleigh number Ra . The maximum stream function is observed at an inclination angle of 60 ° .

Research on Internal Flow and Pressure Fluctuation Characteristics of Centrifugal Pumps as Turbines with Different Blade Wrap Angles

The use of pumps as turbines has been gaining more and more attention in recent years. The present work mainly investigates the influence of blade wrap angle on the internal flow and pressure fluctuation characteristics of centrifugal pumps as turbines. Five different wrap angles (35°,45°, 55°, 65°, and 75°) for a forward-curved impeller were numerically analyzed under multiple operating conditions. The accuracy of numerical simulation was validated by experimental results. The results show that maximum efficiency is achieved with a blade wrap angle of 35°, and the highest efficiency flow point gradually decreases as the blade wrap angle increases. It is found by conducting entropy production theory analysis that the high-entropy production rate regions in PATs are concentrated in the volute tongue and impeller blade inlet regions, and that the entropy production rate at the impeller inlet region increases and then decreases as the blade wrap angle decreases. In addition, pressure pulsation was affected not only by dynamic and static interference but also by an irregular vortex around the impeller; its magnitude under Qt is higher than 0.8Qt for blade wrap angles of 55° and 75°. The primary frequency of pressure pulsation within the impeller is the axial frequency fn and its multiples, and the frequency with the largest amplitude is 3fn. The periodicity of vortices is closely related to the periodicity of pressure pulsation. And it is suggested that a PAT with a 35° blade wrap angle is advantageous for improving the stability of a turbine.

Understanding underlying physical mechanism reveals early warning indicators and key elements for adaptive infections disease networks.

The study of infectious diseases holds significant scientific and societal importance, yet current research on the mechanisms of disease emergence and prediction methods still face challenging issues. This research uses the landscape and flux theoretical framework to reveal the non-equilibrium dynamics of adaptive infectious diseases and uncover its underlying physical mechanism. This allows the quantification of dynamics, characterizing the system with two basins of attraction determined by gradient and rotational flux forces. Quantification of entropy production rates provides insights into the system deviating from equilibrium and associated dissipative costs. The study identifies early warning indicators for the critical transition, emphasizing the advantage of observing time irreversibility from time series over theoretical entropy production and flux. The presence of rotational flux leads to an irreversible pathway between disease states. Through global sensitivity analysis, we identified the key factors influencing infectious diseases. In summary, this research offers valuable insights into infectious disease dynamics and presents a practical approach for predicting the onset of critical transition, addressing existing research gaps.

Flow and Heat Transfer Experimental Study for 3D-Printed Solar Receiving Tubes With Helical Fins at Internal Surface

Abstract 3D-printing technology was applied to fabricate novel solar thermal collection tubes that have internal heat transfer enhancement fins and external surfaces with high solar absorptivity and low emissivity due to the ability to use different materials in one tube. Helical fins were selected to introduce circumferential flow and thus minimize the circumferential temperature difference of the tube that receives sunlight on one side. The structures of the helical fins were previously optimized from computational fluid dynamics (CFD) analysis with the objective of low entropy production rate by looking for high heat transfer coefficient and relatively lower pressure loss. High-temperature alloy, Inconel-718, was used to 3D print the tubes, which can resist corrosion for the potential application of molten chloride salts as heat transfer fluid. Experimental tests were carried out using water as the heat transfer fluid with the high heat flux provided by a tubular furnace heater. The tested Reynolds number ranges from 3.9 × 103 to 6.1 × 104. Heat transfer coefficients of up to 2.8 times that of the smooth tube could be obtained with the expense of increased pressure loss compared to that of the smooth tube. The total system entropy generation can be significantly reduced due to the benefit of heat transfer enhancement that is greater than the expenses of the increased pressure loss. The experimental results of the 3D-printed heat transfer tubes confirmed the CFD-based results of fin optimization. The novel heat transfer tube is recommended for application in concentrating solar power systems.

Estimate of entropy production rate can spatiotemporally resolve the active nature of cell flickering

We use the short-time inference scheme [Manikandan , ], obtained within the framework of stochastic thermodynamics, to infer a lower bound to entropy production rate from flickering data generated by interference reflection microscopy of HeLa cells. We can clearly distinguish active cell membranes from their adenosine-triphosphate-depleted selves and even spatiotemporally resolve activity down to the scale of about 1 µm. Our estimate of activity is . Published by the American Physical Society 2024

Analysis of the temporal, spatial, and frequency law of the internal flow in a prototype vaned mixed‐flow pump

AbstractMixed‐flow pump is a typical pump using in low‐head cases of water lifting. The flow field pulsation is usually an important issue in the operation of mixed‐flow pumps and their pumping statins. Due to its large size, it is difficult to monitor the internal flow characteristics well, based on computational fluid dynamics, we use 5678 monitoring points which arranged in the impeller and fixed vane with using the high pulsation tracking network, and the pressure pulsation signals are analyzed by fast Fourier transform and variable mode decomposition to decompose the main frequency and intensity of the pressure pulsation signals, then analyze the energy dissipation with the entropy production rate (EPR). It is found that there are strong low‐frequency (0.416, 0.625, and 1.67 Hz) pressure pulsation near hub, and the pressure pulsation on the shroud is stronger than that on the hub (at least three times or more); there are strong and stable pressure pulsation (25 Hz) on the shroud generated by the rotor–stator interference (RSI); and the EPR in the flow field can be well combined with the signal. Reasonably allocating material strength and controlling the number of vanes and impellers to avoid producing a common multiple can avoid pressure pulsation caused by RSI and reduce energy dissipation. Therefore, it is very effective in improving the efficiency of this part. Under low flow conditions, the siphon outflow passage can predict the high‐frequency (45.833 Hz) attenuation area well through the phase signal decomposition of the signal, which has certain significance for improving its stability and efficiency.

Entropy production for diffusion processes across a semipermeable interface

The emerging field of stochastic thermodynamics extends classical ideas of entropy, heat, and work to nonequilibrium systems. One notable finding is that the second law of thermodynamics typically only holds after taking appropriate averages with respect to an ensemble of stochastic trajectories. The resulting average rate of entropy production then quantifies the degree of departure from thermodynamic equilibrium. In this paper we investigate how the presence of a semipermeable interface increases the average entropy production of a single diffusing particle. Starting from the Gibbs-Shannon entropy for the particle probability density, we show that a semipermeable interface or membrane S increases the average rate of entropy production by an amount that is equal to the product of the flux through the interface and the logarithm of the ratio of the probability density on either side of the interface, integrated along S. The entropy production rate thus vanishes at thermodynamic equilibrium, but can be nonzero during the relaxation to equilibrium, or if there exists a nonzero stationary equilibrium state (NESS). We then give a probabilistic interpretation of the interfacial entropy production rate using so-called snapping out Brownian motion. This also allows us to construct a stochastic version of entropy production. Finally, we illustrate the theory using the example of diffusion with stochastic resetting on a circle, and find that the average rate of interfacial entropy production is a nonmonotonic function of the resetting rate and the permeability. Published by the American Physical Society 2024

Deep learning probability flows and entropy production rates in active matter

Active matter systems, from self-propelled colloids to motile bacteria, are characterized by the conversion of free energy into useful work at the microscopic scale. They involve physics beyond the reach of equilibrium statistical mechanics, and a persistent challenge has been to understand the nature of their nonequilibrium states. The entropy production rate and the probability current provide quantitative ways to do so by measuring the breakdown of time-reversal symmetry. Yet, their efficient computation has remained elusive, as they depend on the system's unknown and high-dimensional probability density. Here, building upon recent advances in generative modeling, we develop a deep learning framework to estimate the score of this density. We show that the score, together with the microscopic equations of motion, gives access to the entropy production rate, the probability current, and their decomposition into local contributions from individual particles. To represent the score, we introduce a spatially local transformer network architecture that learns high-order interactions between particles while respecting their underlying permutation symmetry. We demonstrate the broad utility and scalability of the method by applying it to several high-dimensional systems of active particles undergoing motility-induced phase separation (MIPS). We show that a single network trained on a system of 4,096 particles at one packing fraction can generalize to other regions of the phase diagram, including to systems with as many as 32,768 particles. We use this observation to quantify the spatial structure of the departure from equilibrium in MIPS as a function of the number of particles and the packing fraction.

Two applications of stochastic thermodynamics to hydrodynamics

Recently, the theoretical framework of stochastic thermodynamics has been revealed to be useful for macroscopic systems. However, despite its conceptual and practical importance, the connection to hydrodynamics has yet to be explored. In this Letter, we reformulate the thermodynamics of compressible and incompressible Newtonian fluids so that it becomes comparable to stochastic thermodynamics and unveil their connections; we obtain the housekeeping–excess decomposition of the entropy production rate (EPR) for hydrodynamic systems and find a lower bound on EPR given by relative fluctuation similar to the thermodynamic uncertainty relation. These results not only prove the universality of stochastic thermodynamics but also suggest the potential extensibility of the thermodynamic theory of hydrodynamic systems. Published by the American Physical Society 2024

Probabilistic and maximum entropy modeling of chemical reaction systems: Characteristics and comparisons to mass action kinetic models.

We demonstrate and characterize a first-principles approach to modeling the mass action dynamics of metabolism. Starting from a basic definition of entropy expressed as a multinomial probability density using Boltzmann probabilities with standard chemical potentials, we derive and compare the free energy dissipation and the entropy production rates. We express the relation between entropy production and the chemical master equation for modeling metabolism, which unifies chemical kinetics and chemical thermodynamics. Because prediction uncertainty with respect to parameter variability is frequently a concern with mass action models utilizing rate constants, we compare and contrast the maximum entropy model, which has its own set of rate parameters, to a population of standard mass action models in which the rate constants are randomly chosen. We show that a maximum entropy model is characterized by a high probability of free energy dissipation rate and likewise entropy production rate, relative to other models. We then characterize the variability of the maximum entropy model predictions with respect to uncertainties in parameters (standard free energies of formation) and with respect to ionic strengths typically found in a cell.