Search Results (96)

Phase change material (PCM)-based latent heat storage (LHS) systems help address the mismatch between renewable energy supply and thermal demand. However, their practical implementation is constrained by the strongly nonlinear and multiphysics nature of phase change, which makes high-fidelity simulations and real-time applications computationally expensive. This review examines mathematical reduced-order modeling (ROM) as an effective strategy to overcome this limitation by combining physics-based simplifications, projection methods, interpolation techniques, and data-driven models for PCM-based LHS systems. While physical simplifications (such as dimensional reduction and effective property approximations) represent an important first layer of model reduction, the primary focus of this work is on the mathematical ROM methodologies that operate on the governing equations after such physical simplifications have been applied. The review covers approaches including two-temperature non-equilibrium and analytical thermal-resistance models, Proper Orthogonal Decomposition (POD), CFD-derived look-up tables, kriging and ε-NTU grey/black-box metamodels, and machine-learning methods such as artificial neural networks and gradient-boosted regressors trained from CFD data. These ROM techniques have been applied to packed beds, PCM-integrated heat exchangers, finned enclosures, triplex-tube systems, and solar thermal components, achieving speed-ups from tens to over 80,000 times faster than full CFD simulations while maintaining prediction errors typically below 5% or within sub-Kelvin temperature deviations. A critical comparative analysis exposes the fundamental trade-off between interpretability, data dependence, and computational efficiency, leading to a practical decision-making framework that guides method selection for specific applications such as design optimization, real-time control, and system-level simulation. Remaining challenges—including accurate representation of phase change nonlinearity, moving phase boundaries, multi-timescale dynamics, generalization across geometries, experimental validation, and integration into industrial workflows—motivate a structured roadmap for future hybrid physics–machine learning developments, standardized validation protocols, and pathways toward industrial deployment. Full article

Precise manipulation of two-phase flow in micro-confined electrowetting pixels is limited by contact angle hysteresis (CAH). To elucidate this non-equilibrium process, we establish a high-fidelity electrohydrodynamic (EHD) phase-field simulation framework. The model rigorously couples Navier–Stokes equations with molecular kinetic theory (MKT) to characterize energy dissipation at the three-phase contact line (TCL) and further integrates charge transport kinetics. Numerical results reveal CAH is driven by physical pinning and interfacial charge trapping, with the latter dominating interfacial retreat and causing significant residual displacement. Furthermore, analysis shows alternating current (AC) waveforms mitigate charge accumulation and promote depinning via micro-oscillations, minimizing the hysteresis loop compared to direct current (DC) waveforms. Additionally, an overdrive strategy utilizing a suprathreshold Maxwell stress pulse rapidly overcomes static friction. This strategy significantly improves transient dynamics, substantially reducing the time to reach 90% of the steady-state target from 19.6 ms (under standard DC waveform driving) to 7.4 ms. This work provides a comprehensive theoretical basis and design criteria for optimizing active driving strategies in optofluidic and digital microfluidic systems. Full article

This work presents a comprehensive quantum transport modeling and simulation framework to evaluate parasitic effects and radio frequency (RF) performance in stacked silicon (Si) nanosheet (NS) lateral gate-all-around (LGAA) nFETs targeting the sub-2 nm technology node. Leveraging the non-equilibrium Green’s function (NEGF) method, the proposed framework integrates detailed modeling of parasitic resistances (R_para) and capacitances (C_para) to enable a holistic analysis of both intrinsic and extrinsic figures-of-merit, including transconductance (g_m), output conductance (g_d), cutoff frequency (f_T), and maximum oscillation frequency (f_max). The effects of nanosheet geometry, crystal orientations, and dual-k spacers on high-frequency performance are systematically investigated. The analysis reveals key design trade-offs, with optimized device configurations yielding f_T exceeding 400 GHz and f_max approaching 1.2 THz. These findings highlight the potential of stacked NS LGAA-nFETs for future millimeter-wave and terahertz applications, providing critical insights into parasitics management and quantum-transport-aware design strategies at advanced CMOS nodes. Full article

This study proposes an efficient numerical scheme for simulating heat transfer governed by the diffusion equation with moving singular sources. The work addresses two-dimensional problems with line sources and three-dimensional problems with plane sources, which are prevalent in irreversible thermodynamic processes. Developed within a finite difference framework, the method employs a partitioned discretization strategy to accurately resolve the solution singularity near the heat source—a region critical for precise local entropy production analysis. In the immediate vicinity of the source, we analytically derive and incorporate the solution’s “jump” conditions to construct specialized finite difference approximations. Away from the source, standard second-order-accurate schemes are applied. This hybrid approach yields a globally second-order convergent spatial discretization. The resulting sparse system is efficient for large-scale simulation of dissipative systems. The accuracy and efficacy of the proposed method are demonstrated through numerical examples, providing a reliable tool for the detailed study of energy distribution in non-equilibrium thermal processes. Full article

In order to address the difficulty in acquiring degraded images for star sensors under hypersonic conditions, this paper proposes a star sensor imaging simulation model which can effectively analyze the influence of thermochemical non-equilibrium flow on the star sensor. Firstly, the two-temperature model is adopted to describe the relaxation phenomenon of hypersonic non-equilibrium flow, and the chemical reaction is simulated by Arrhenius law. Then, the effects of optical transmission and thermal radiation on star sensor imaging are quantitatively analyzed. Based on this degradation model, the degraded star images under two typical working conditions are simulated. The simulation results show that the radiation of the solid media has the most significant influence on the imaging of the star sensor. The detectable limit magnitudes of the star sensor obtained under the two working conditions are 3.28 and 4.55, respectively. The research results can provide important theory and technical support for the system design and algorithm testing of star sensors on near-space hypersonic platforms. Full article

Mesoscopic particles levitated by optical, electrical or magnetic fields act as mechanical oscillators with a range of surprising properties, such as tuneable oscillation frequencies, access to rotational motion, and remarkable quality factors. Coupled levitated particles display rich dynamics and non-reciprocal interactions, with applications in sensing and the exploration of non-equilibrium and quantum physics. In this work, we present a single levitated particle displaying coupled-oscillator dynamics by generating an interaction with a virtual or “ghost” particle. This ghost levitated particle is simulated on an analogue computer, and its properties can thus be dynamically varied. Our work represents a new angle on measurement-based bath engineering and physical simulation and, in the future, could lead to the generation of novel cooling mechanisms and complex physical simulation. Full article

Accurate conjugate heat transfer (CHT) analysis is critical to the thermal management of hypersonic vehicles operating in rarefied environments, where non-equilibrium gas dynamics dominate. While numerous sophisticated CHT solvers exist for continuum flows, they are physically invalidated by rarefaction effects. This paper presents a novel partitioned coupling framework that bridges this methodological gap by utilizing the preCICE library to non-intrusively integrate the Direct Simulation Monte Carlo (DSMC) method, implemented in SPARTA, with the finite element method (FEM) via FEniCS for high-fidelity simulations of rarefied hypersonic CHT. The robustness and accuracy of this approach are validated through three test cases: a quasi-1D flat plate benchmark confirms the fundamental coupling mechanism against a reference finite difference solution; a 2D flat-nosed cylinder demonstrates the capability of the framework to handle highly non-uniform heat flux distributions and resolve the ensuing transient thermal response within the solid; finally, a standard cylinder case confirms the compatibility with curved geometries and its stability and accuracy in long-duration simulations. This work establishes a validated and accessible pathway for high-fidelity aerothermal analysis in rarefied gas dynamics, effectively decoupling the complexities of multi-physics implementation from the focus on fundamental physics. Full article

In order to meet the dual requirements of low-energy heating and flexible operation, a comprehensive heating system with multi-mode and wide-load capabilities was constructed, incorporating a heat pump, a back-pressure turbine, and two 350 MW coal-fired condensing units. Based on the heat transfer characteristics of this system, the simulation model of this comprehensive thermal system was constructed through a commercial software (EBSILON). A dynamic coal consumption prediction method based on the non-equilibrium state parameters was first proposed, which was primarily designed for system operation optimization. Subsequently, the converted load and load change rate were integrated into the dynamic correction model to refine prediction accuracy. The results showed that while basic coal consumption primarily correlates with heat load and electricity load, dynamic coal consumption is influenced by both the converted load and the load change rate. Based on this, the three-dimensional surface plot of converted load, load charge rate, and dynamic coal consumption offset coefficient was calculated. Then, the accuracy of the prediction model was verified by the variable working condition parameter group, and its reliability was confirmed. Further, by developing online software, theoretical guidance for industrial production was realized. In a heating season case study, it was demonstrated the prediction method can effectively reflect the dynamic parameter deviation in the system, with the annual coal saving being able to reach 841.5 tons. It is expected to provide theoretical guidance for the research on multi-heat sources heating distribution and operation parameter optimization. Full article

Quantum spin transport in integrable systems reveals a rich nonequilibrium phenomena that challenges the conventional hydrodynamic framework. Recent advances in ultracold atom experiments with state preparation and single-site addressing have enabled the understanding of this anomalous behavior. Particularly, the full universality characterization of exotic initial states, as well as their measurement representation, remain unknown. By employing tensor network and contrast methods, we systematically investigate spin transport in the quantum XXZ spin chain and extract dynamical scaling exponents emerging from two paradigmatic and experimentally attainable initial states, i.e., multi-periodic domain-wall (MPDW) and spin-helix (SH) states. Our results using different values of anisotropic parameters $\Delta \in [0,1.2]$ demonstrate the evident impeded transport and the difference between the two states with increasing $\Delta$ values. Large-scale and consistent simulations confirm the contrast method as a viable scaling extraction approach for exotic states with periodicity within experimentally accessible timescales. Our work establishes a foundation for studying initial memory and the corresponding relations of emergent transport behavior in nonequilibrium quantum systems, opening avenues for the identification of their unique universality classes. Full article

Exciton–polariton condensates (EPCs) have emerged as a paradigmatic platform for investigating nonequilibrium quantum many-body phenomena, particularly due to their intrinsic open-dissipative nature and strong nonlinear interactions governed by the interplay between stimulated scattering and reservoir-mediated damping. Recent advances in Feshbach resonance engineering now enable precise tuning of interaction strengths, opening new avenues to explore exotic nonlinear excitations in these driven-dissipative systems. In this work, we systematically investigate the quench dynamics and stability of dark solitons in repulsive one-dimensional EPCs under sudden parameter variations in both nonlinear interaction strength g and pump intensity P. Through a Hamiltonian variational approach that incorporates reservoir damping effects, we derive reduced equations of motion for soliton velocity evolution that exhibit remarkable qualitative agreement with direct numerical simulations of the underlying open-dissipative Gross–Pitaevskii equation. Our results reveal three distinct dynamical regimes: (i) stable soliton propagation at intermediate pump powers, (ii) velocity-dependent soliton breakup above critical pumping thresholds, and (iii) parametric excitation of soliton trains under simultaneous interaction quenches. These findings establish a quantitative framework for understanding soliton dynamics in nonresonantly pumped EPCs, with implications for quantum fluid dynamics and nonequilibrium Bose–Einstein condensates. Full article

The Anderson localization of phonons in disordered superlattices has been proposed as a route to suppress thermal conductivity beyond the limits imposed by conventional scattering mechanisms. A commonly used signature of phonon localization is the emergence of the nonmonotonic dependence of thermal conductivity $\kappa$ on system length L, i.e., a $\kappa$-L maximum. However, such behavior has rarely been observed. In this work, we conduct extensive non-equilibrium molecular dynamics (NEMD) simulations, using the LAMMPS package, on both periodic superlattices (SLs) and aperiodic random multilayers (RMLs) constructed from Si/Ge and Lennard-Jones materials. By systematically varying acoustic contrast, interatomic bond strength, and average layer thickness, we examine the interplay between coherent and incoherent phonon transport in these systems. Our two-phonon model decomposition reveals that coherent phonons alone consistently exhibit a strong nonmonotonic $\kappa$-L. This localization signature is often masked by the diffusive, monotonically increasing contribution from incoherent phonons. We further extract the ballistic-limit mean free paths for both phonon types, and demonstrate that incoherent transport often dominates, thereby concealing localization effects. Our findings highlight the importance of decoupling coherent and incoherent phonon contributions in both simulations and experiments. This work provides new insights and design principles for achieving phonon Anderson localization in superlattice structures. Full article

Two-phase expansion processes have emerged as a promising technology for enhancing energy efficiency in power generation, refrigeration, waste heat recovery systems (for example, partially evaporated organic Rankine cycle, organic flash cycle, and trilateral flash cycle), oil and gas, and other applications. However, despite their potential, widespread adoption is hindered by inherent challenges, particularly energy losses that reduce operational efficiency. This review systematically evaluates the current state of two-phase expansion technologies, focusing on the root causes, impacts, and mitigation strategies for expansion losses. This work used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Using the PRISMA framework, 52 relevant publications were identified from Scopus and Web of Science to conduct the systematic review. A preliminary co-occurrence analysis of keywords was also conducted using VOSviewer version 1.6.20. Three clusters were observed in this co-occurrence analysis. However, the results may not be significant. Therefore, the extended work was done through a comprehensive analysis of experimental and simulation studies from the literature. This study identifies critical loss mechanisms in key components of two-phase expanders, such as the nozzle, diffuser, rotor, working chamber, and vaneless space. Also, losses arising from wetness, such as droplet formation, interfacial friction, and non-equilibrium phase transitions, are examined. These phenomena degrade performance by disrupting flow stability, increasing entropy generation, and causing mechanical erosion. Several losses in the turbine and volumetric expanders operating in two-phase conditions are reported. Ejectors, throttling valves, and flashing flow systems that exhibit similar challenges of losses are also discussed. This review discusses the mitigation and the strategy to minimize the two-phase expansion losses. The geometry of the inlet of the two-phase expanders plays an important role, which also needs improvement to minimize losses. The review highlights recent advancements in addressing these challenges and shows optimization opportunities for further research. Full article

Extreme conditions induced by shock exert unprecedented force on crystal lattice and push atoms away from their equilibrium positions. Nonequilibrium molecular dynamics (MD) simulations are one of the best ways to describe material behavior under shock but are limited by the availability and reliability of potential functions. In this work, a specific embedded atom (EAM) potential of molybdenum (Mo) is built for shock and tested by quasi-isentropic and piston-driven shock simulations. Comparisons of the equation of state, lattice constants, elastic constants, phase transitions under pressure, and phonon dispersion with those in the existing literature validate the reliability of our EAM potential. Quasi-isentropic shock simulations reveal that critical stresses for the beginning of plastic deformation follow a [111] > [110] > [100] loading direction for single crystals, and then polycrystal samples. Phase transitions from BCC to FCC and BCC to HCP promote plastic deformation for single crystals loading along [100] and [110], respectively. Along [111], void directly nucleates at the stress concentration area. For polycrystals, voids always nucleate on the grain boundary and lead to early crack generation and propagation. Piston-driven shock loading confirms the plastic mechanisms observed from quasi-isentropic shock simulation and provides further information on the spall strength and spallation process. Full article

The contact process is a nonequilibrium Hamiltonian model that, even in one dimension, lacks an exact solution and has been extensively studied via Monte Carlo simulations, both in steady-state and time-dependent scenarios. Although the effects of particle mobility and diffusion on criticality have been preliminarily explored, they remain poorly understood in many aspects. In this work, we examine how the critical rate of the model varies with the probability of particle mobility. By analyzing different stochastic evolutions of the system, we employ two modern approaches: (1) Random Matrix Theory (RMT): By building on the success of RMT, particularly Wishart-like matrices, in studying statistical physics of systems with up-down symmetry via magnetization dynamics [R. da Silva, IJMPC 2022], we demonstrate its applicability to models with an absorbing state; (2) Optimized Temporal Power Laws: By using short-time dynamics, we optimize power laws derived from ensemble-averaged evolutions of the system. Both methods consistently reveal that the critical rate decays with mobility according to a simple Belehradek function. Additionally, a straightforward mean-field analysis supports the decay of the critical parameter with mobility, although it predicts a simpler linear dependence. We also demonstrate that the more sophisticated pair approximation mean-field model developed by ben-Avraham and Köhler aligns closely with the Belehradek function, precisely matching our lattice simulation results. Full article

The Taylor–Quinney coefficient (TQC) is a critical parameter quantifying the thermal conversion of plastic work during deformation in metallic crystals. This review provides a comprehensive summary of recent advances in TQC research, spanning experimental, theoretical, and computational perspectives. The fundamental principles of the TQC are introduced, emphasizing its thermodynamic background and dependence on microstructural features. Experimental studies demonstrate how the strain rate, temperature, and microstructure influence the TQC, with advanced techniques such as infrared thermography and high-speed imaging enabling precise measurements under dynamic conditions. Theoretical models, including internal variable frameworks and nonequilibrium thermodynamics, offer insights into the energy distribution mechanisms and provide predictive capabilities across diverse loading scenarios. Computational simulations, using methods like finite element analysis and molecular dynamics, reveal multiscale thermal conversion mechanisms and the role of dislocation motion and localized heat accumulation in governing TQC values. Challenges and opportunities for TQC research are highlighted, including the need for multiscale modeling, the exploration of complex stress states, and applications under extreme environments. Future directions should focus on integrating advanced experimental techniques and computational models to optimize material design and performance. This review aims to deepen the understanding of the TQC and its implications for energy dissipation and material reliability in high-performance applications. Full article