Search Results (632)

The thermal performance of multilayer building wall systems under variable outdoor temperature conditions is an important factor in evaluating building energy efficiency and indoor thermal comfort. This study presents a simplified analytical formulation based on the classical transient heat conduction theory together with a numerical model based on the finite difference method (FDM) implemented in the MATLAB R2026a (Update 5) environment. The analysis includes five types of multilayer wall systems with different structural compositions and thermal masses, combined with three thermal insulation materials (expanded polystyrene (EPS), mineral wool, and aerogel) and various insulation thicknesses, resulting in a total of 55 wall assembly configurations. The investigated wall systems are evaluated using the thermal transmittance coefficient (U-value), decrement factor, time lag, maximum heat flux, and the temporal variation in the interior wall surface temperature. The results demonstrated that the dynamic thermal behavior of multilayer wall systems depends on the combined effects of the thermal mass of the load-bearing layer, the type and thickness of the thermal insulation, and the thermophysical properties of the constituent materials. The comparison between the analytical formulation and the MATLAB simulations demonstrates consistent trends in the predicted thermal behavior of the investigated wall systems, supporting the applicability of the proposed analytical–numerical approach for the preliminary assessment of the thermal performance of multilayer building wall systems. Full article

A systematic numerical simulation and analysis of the temperature field were conducted for the laser cladding process of CuCrZr alloy onto a 316L stainless steel substrate. First, the thermal properties of the material (density, thermal conductivity, and specific heat capacity) as a function of temperature were calculated using JMatPro software. The equilibrium phase diagram of the CuCrZr alloy was obtained using Thermo-Calc, clarifying the stability of each phase and the solid–liquid phase transition ranges. Based on these findings, three-dimensional transient heat transfer models for single-layer single-pass and single-layer multi-pass cladding were established using ANSYS finite element software and a double-ellipsoidal moving heat source model. The effects of laser power on the evolution of the temperature field, peak temperature, and thermal cycling characteristics were systematically investigated. The simulation results indicate that the temperature field exhibits typical rapid heating and rapid cooling characteristics; the peak temperature increases significantly with rising laser power, and the extent of the high-temperature region expands. A combined analysis of the phase diagram and temperature field results indicates that the peak cladding temperature exceeds the complete melting temperature of the alloy, ensuring sufficient melting. This study provides a reliable theoretical foundation and data support for optimizing laser cladding process parameters, predicting the microstructure of the cladding layer, and controlling thermal stress. Full article

As power densities in Wide Band Gap (WBG) semiconductors increase, traditional steady-state cooling methods often fail to address the rapid thermal transients. This paper investigates a diversity of cooling architectures for discrete Silicon Carbide (SiC) MOSFETs, and a frequency-dependent thermal characterization of different cooling technologies. This paper also presents a new measurement method of heat transfer through multilayer systems, which determines the thermal diffusivity of the power device in real dynamic operation. The measurement of the stored energy in the active component using temperature sensors proves itself to be a practical, rapid, low-cost, and non-invasive method. The results show that the active Peltier stage significantly allows for more frequent current bursts before reaching the thermal limit, thereby proving the system’s capability in high-frequency transient applications to be thermally stable. The analysis of different power systems with different types of cooling, for a range of frequencies of the drive signal for SiC MOSFETs, enables power electronic engineers to evaluate the efficacy of the cooling systems related to the operating frequency and not only as a function of the dissipated power. Analysis of thermal faults in MOSFETs with SEM/EDS methods reveals the weak points in the design of these WBG devices. Full article

Under ground-based observation geometry, infrared radiant-intensity sequences of space objects are jointly influenced by object micromotion, thermal radiation, time-varying viewing conditions, and atmospheric propagation. Existing simulation studies often prescribe the line of sight or simplify the coupling between viewing geometry and atmospheric attenuation, which limits long-duration ground-based sequence analysis. This study develops a physics-informed framework for generating atmosphere-attenuated infrared radiant-intensity sequences of space objects undergoing precession or tumbling. The framework reconstructs observation geometry from azimuth–elevation–range trajectories, updates facet normals through a unified micromotion attitude model, computes visible projected area and transient facet temperature, and incorporates MODTRAN-derived elevation-dependent atmospheric transmittance. Using this framework, we construct IRPeriodic, an eight-class simulated dataset for long-duration univariate time-series classification. We further propose LPD-Net, which integrates large-kernel residual feature extraction, prototype-guided dynamic temporal alignment, and differential periodic representation to capture long-range waveform morphology, sample-dependent temporal correspondence, and segment-level local variation. On IRPeriodic, LPD-Net achieves an accuracy of 0.8618 ± 0.0057, a macro-F1 of 0.8615 ± 0.0061, and a Matthews correlation coefficient of 0.8426 ± 0.0065, outperforming the evaluated neural-network and ROCKET-type baselines. Ablation and synthetic-noise sensitivity analyses indicate that the performance gain is mainly associated with long-context feature extraction, with additional improvements from dynamic alignment and differential periodic statistics. Auxiliary experiments on selected public UCR datasets suggest that the representation is also competitive for univariate time-series classification. These results demonstrate the effectiveness of LPD-Net on the proposed physics-informed benchmark for long-duration ground-based infrared radiant-intensity sequence classification. Full article

The increasing penetration of renewable energy has significantly intensified the demand for flexible operation of thermal power plants, making dynamic simulation an essential tool for understanding transient behaviors and developing advanced operational strategies for circulating fluidized bed (CFB) power plants. This review critically examines the existing dynamic modeling approaches for industrial-scale CFB power plants, with particular emphasis on their applicability to flexibility studies. Existing CFB flue-gas side models are systematically classified into three categories: 3D physics-based CFD models, behavioral/data-driven models, and semi-empirical mechanistic models. Their characteristics are critically compared in terms of spatial and temporal scales, empirical dependence, model generality, computational and implementation burden, and applicability to CFB flexibility studies. Dynamic modeling of the steam–water cycle is also reviewed, showing that it has reached a relatively mature stage owing to well-established thermo-hydraulic theories and standardized modeling platforms. The current research bottleneck is therefore identified as the dynamic coupling between the flue-gas side and the steam–water cycle for integrated CFB whole-plant simulation. Based on the comparative analysis, semi-empirical mechanistic models are identified as a particularly suitable framework for industrial-scale CFB flexibility studies requiring minute-to-hour transient simulation, physical interpretability, and whole-plant coupling. Finally, future research directions are discussed, highlighting how integrated dynamic models can support CFB flexibility-enhancement technologies and the development of new-generation coal-fired power plants. Full article

A simply supported rectangular isotropic ferromagnetic plate with magnetocaloric properties subjected to convective heating on its upper surface is considered. The governing equations comprise a system of two-dimensional transient equations for the thickness-averaged temperature characteristics of the plate and the two-dimensional bending equations for isotropic plates expressed in terms of generalized displacements within the framework of first-order shear deformation theory. Closed-form solutions to the governing equations are obtained by expanding all thermal and mechanical field quantities in double Fourier sine series satisfying the prescribed boundary conditions, combined with the Laplace transform in time applied to the thermal quantities. A comparative numerical analysis is carried out for the magnetocaloric ferromagnetic plate and a carbon steel plate under ambient temperature rising at a finite rate to a prescribed value. The dependences of all quantities under investigation on the ambient temperature rise rate, time, convective heat transfer coefficient, thermal conductivity of the ferromagnetic material, and geometric parameters of the plate are analyzed and presented graphically. The results obtained provide a quantitative basis for assessing the thermoelastic state and for optimizing the geometry and operating conditions of active magnetic regenerator plate stacks with a view to enhancing their structural reliability. Full article

This paper presents the development of a multi-domain simulation for the Porsche Taycan’s all-wheel-drive (AWD) electric propulsion system to investigate the impact of the rear drive unit’s two-speed transmission on performance and drive quality during maximum acceleration. This study was undertaken independent of the vehicle and propulsion system OEM. A lumped-parameter model of the front and rear electric drive units (EDU) and the high-voltage battery was developed and calibrated against the published data for key benchmarks, including 0–100 kph acceleration times and peak longitudinal acceleration. The mechanical shifting mechanism was reverse-engineered to simulate high-performance shift trajectories. To manage the transition, a clutch control scheme integrates a reduced-order clutch-to-clutch model featuring a feedforward (FF) torque estimator and a closed-loop feedback (FB) controller to achieve target input shaft speeds and shift durations. The study concludes with a comprehensive analysis of the propulsion system’s behavior at a battery state of charge of 96% and 25% and three electric motor speeds at which the upshift is commanded. The simulation results demonstrate that executing an early upshift at 10,700 rpm with 96% of SOC yields a 0.100-s inertia phase shift time, restricts the clutch thermal dissipation to 21 kJ, and achieves an 8-s velocity of 203.4 kph, outperforming the upshift at 15,300 rpm (0.210 s, 34 kJ, and 202.8 kph). Furthermore, the transient regenerative braking on the rear axle during the inertia phase reduces the peak current draw from 675 A to 87 A, recovering the DC bus voltage to enable cross-axle torque boosting on the front axle. Full article

This study investigates the influence of unsteady heat and mass transfer processes on the formation of gas composition and thermal conditions in a large cross-section (132 m²) blind-end chamber of a gypsum mine during the operation of diesel-powered mining equipment, including a front-end loader representing the LHD class and a dump truck. The modeled system considers a chamber where the LHD operates continuously, while the dump truck enters periodically to perform haulage cycles. Ventilation is provided from an adjacent panel haulage drift using a booster fan. Numerical simulations were carried out using ANSYS Fluent within the RANS framework, employing the realizable k-ε turbulence model, with consideration of thermal and gas convection. A dynamic mesh approach was applied to explicitly represent the motion of the dump truck. Both steady-state scenarios, corresponding to extreme equipment positions, and a fully transient case involving dump truck entry into the chamber followed by idling were analyzed. The results demonstrate that the movement of the dump truck generates a pronounced piston effect, which alters the jet flow structure and temporarily increases the supply of fresh air to the working face. It is shown that steady-state assumptions based on prolonged equipment presence near the face overestimate the total NO_x concentration within the large chamber and may not adequately reflect actual gas conditions over typical loading cycle durations. The analysis of unsteady processes using the dynamic mesh approach reveals significant inertia in contaminant accumulation within the chamber. This finding enables a more accurate estimation of the required airflow rate, reducing excessive safety margins compared to calculations based on the assumption of continuous equipment operation near the face. Full article

Artificial intelligence (AI) data centers are creating large, power-dense loads, often faster than transmission lines, substations, transformers, and grid interconnections can be expanded. This review assesses whether solid oxide fuel cells (SOFCs) can provide dependable on-site power during these grid delivery constraints and remain competitive after grid capacity becomes available. We critically synthesized evidence on AI electricity demand, competing power supply options, SOFC efficiency and durability, commercial deployments, environmental impacts, thermal and electrical integration, and hybrid SOFC–battery–grid systems. We also performed a screening-level levelized cost of electricity sensitivity analysis covering natural gas prices, carbon costs, stack replacement, grid electricity prices, and the avoided cost of delayed grid access. The evidence indicates that commercial SOFC systems can achieve approximately 50–60% net electrical efficiency and scale modularly from 325 kW units to a planned deployment of up to 2.45 GW. A nominal 100 MW installation would require approximately 308 such modules and at least 3600 m² of direct equipment area, excluding auxiliary systems and safety setbacks. However, multi-year durability targets of about 40,000 h, fuel and carbon price exposure, slow transient response, lifecycle methane emissions, and limited opportunities to use high temperature exhaust heat remain important constraints. The economic analysis indicates that avoided grid delay costs can justify SOFCs as bridge assets, whereas long-term retention requires competitiveness without this temporary benefit. SOFCs are therefore most suitable for sites that prioritize rapid access to firm power, modularity, reliability, and low local air pollutant emissions, rather than as a universal alternative to grid expansion. Full article

Ultra-supercritical (USC) steam turbines combine severe steam conditions with increasingly frequent start-up, shutdown, and load-following operations. Their main steam valves must preserve pressure boundary integrity, sealing, and rapid actuation while non-uniform heating, creep, cyclic plasticity, oxidation, wear, and contact redistribution alter component geometry. However, the relevant evidence remains fragmented across alloy development, component thermo-mechanics, valve aerodynamics, and lifetime monitoring. This short, mechanism-oriented review integrates these domains through a material structure–function framework in which deformation relative to assembly clearance governs jamming risk. It synthesizes evidence on heat-resistant body and surface materials, 9–12% Cr steel stability, weldability and repair sensitivity, and cold, warm, and hot start-up histories. It also evaluates creep–fatigue interaction, contact, flow-induced vibration, multi-physics modeling, validation, uncertainty, monitoring, and digital twins. The synthesis shows that neither peak equivalent stress nor steady-state temperature alone can establish functional reliability. Credible assessment requires temperature-dependent material data, realistic steam-side heat transfer, cyclic constitutive behavior, initial and residual clearances, manufacturing and assembly tolerances, state-dependent friction, uncertainty analysis, and corroborating plant or inspection evidence. The most consequential research needs are valve-level validation datasets, thermal contact testing, function-oriented life criteria, and uncertainty-aware digital twins that jointly inform materials, geometry, and transient operation. Full article

Annular trapped pressure is an important factor affecting wellbore integrity during the production of high-temperature and high-pressure oil and gas wells. In wells with multilayer casing structures, one or more enclosed annuli may form because of cement top, packer setting, wellbore structural constraints and wellhead sealing. When the temperature and pressure fields in the wellbore change during production, the annular fluid undergoes thermal expansion, compressive deformation and possible phase-state changes, causing trapped pressure to evolve continuously with time. Conventional annular pressure prediction methods are usually based on a single annulus, quasi-static assumptions or simplified fluid properties, and therefore cannot fully describe deformation transfer among annuli, thermal expansion of tubular strings and nonlinear gas–liquid compression. To address this problem, this study analyses the formation mechanism of annular trapped pressure from the perspective of thermal–fluid–solid coupling and develops a dynamic pressure evolution model that accounts for transient temperature variation, annular fluid thermal expansion and compression, elastic deformation of tubular strings and multi-annulus coupling. The analysis indicates that annular trapped pressure is essentially a pressure response produced by fluid thermal expansion under structural confinement. A multi-annulus system is not a set of independent annuli, but a pressure–deformation–volume feedback system coupled through shared casing walls. The proposed solution framework and pressure evolution analysis provide a theoretical basis for annular pressure prediction, casing safety assessment and wellbore-integrity management in high-temperature and high-pressure gas wells. Full article

The characterization of high-temperature plastic deformation behavior in centrifugally cast alloys has historically been based on curve fitting of experimentally obtained creep data. Although this approach provides acceptable results within the range of experimental conditions used for curve fitting, performance predictions under conditions outside conventional tests—typically derived from constant temperature and stress—remain insufficiently accurate for petrochemical engineering applications. In this study, constant-load creep tests were performed across a stress range of 5–33 MPa at 950–1100 °C. The minimum creep rate was calculated from the creep curves and used to fit Norton-law parameters by log–log regression. A global Norton-law fit was first carried out for each temperature, and an additional segmented fit was then performed by separating the low- and high-stress domains. The results reveal a systematic variation in the apparent Norton stress exponent (n) with the stress range considered. This variation suggests that the creep response changes from one apparent stress domain to another, contradicting the assumption of a single-valued Norton exponent inherent in standard curve-fitting procedures. Although the experimental database was obtained from conventional constant-load and constant-temperature creep tests, the results are discussed in terms of their implications for creep modeling under non-stationary operating conditions, where local stress and temperature fields may evolve during service. Parameters fitted over a broad stress range may produce systematic local errors when applied to stress domains with different apparent sensitivities. Furthermore, it is well known that classical steady-state creep models may be insufficient when their fitted parameters are transferred to non-stationary loading conditions, where thermal transients during start-up and shutdown generate differential thermal strains and high local stress levels. Geometric constraints, combined with these peak stresses, may lead to values exceeding the yield strength, a condition under which classical methods fail to adequately describe material behavior and stress relaxation mechanisms. This manuscript directly addresses this limitation through the analysis of three heats of the same centrifugally cast alloy. Full article

To address the challenge of balancing junction temperature prediction accuracy and computational efficiency for high-power multi-chip IGBT modules in automotive applications during complex electro-thermal conversion processes, this study proposes an improved three-dimensional thermal network model based on equivalent power loss injection. Firstly, the effective heat conduction area of each packaging layer under actual heat flow distribution is extracted through three-dimensional finite element simulation, and the single-chip self-heating network parameters are constructed. Secondly, targeting the thermal cross-coupling effect among multiple chips, an elliptical thermal diffusion model is applied to accurately define the thermal coupling region, and a dynamic equivalent power loss compensation mechanism is introduced. Efficient decoupling of multi-heat-source interference is achieved without increasing the state-space dimension of the model. An experimental benchmarking results comparison indicates that the absolute error of junction temperature prediction by this model under steady-state operating conditions is 0.5 °C. Further comparative analysis under the full CLTC-P (China Light-duty Vehicle Test Cycle for Passenger Car) cycle verifies that the improved model not only overcomes the shortcomings of the traditional Foster model, which severely underestimates the transient peak junction temperature and alternating stress amplitude, but also effectively filters out non-physical overshoots caused by short-term ultra-narrow pulses, thus reasonably estimating the device’s maximum junction temperature within the real physical boundary. This method provides efficient theoretical support for accurate dynamic junction temperature predictions and reliability evaluations of electric vehicles under complex operating conditions. Full article

During ultra-deep well drilling, the bottomhole circulating temperature (BHCT) can easily exceed 150 °C, causing a series of problems such as drilling-fluid degradation, downhole instrument failure, and intensified well-control risks. Conventional surface-cooling methods experience sharply diminishing effectiveness under deep well conditions, while an insulated drill-pipe (IDP) offers good engineering feasibility as a passive cooling technique. However, existing studies lack a transient wellbore-formation coupled model validated by field data, and the influence patterns and interaction mechanisms of key parameters of the insulation coating under varying well depths remain unclear. Therefore, this study integrates a thermal-resistance representation into a transient wellbore-formation heat-transfer framework to characterize the insulation effect via an overall heat-transfer coefficient. Based on this framework, the cooling mechanism is systematically investigated from two perspectives: heat-absorption rate and cumulative blocked heat. Based on this model, the cooling mechanism is systematically investigated from two perspectives: heat-absorption rate and cumulative blocked heat. The results show that a 2000 m IDP section reduces BHCT from 161.81 °C (with a conventional drill-pipe, CDP) to 144.15 °C after 50 h of circulation. This yields an additional cooling of 17.66 °C and a cumulative blocked heat of 180.03 GJ. Parameter analysis further shows that lower thermal conductivity, longer coating length, and placement 200–400 m above the bottomhole enhance cooling, whereas coating thickness exhibits a marginal benefit threshold of 1 mm. More importantly, Sobol’ global sensitivity analysis reveals a distinct evolution of the dominant parameter controls with increasing well depth: at 6000 m measured depth (MD), coating length is the absolute governing factor; at 8000 m, coating position and length become equally important; at 10,000 m, the coupling between thermal conductivity and length emerges as critical; and at 12,000 m, thermal conductivity, thickness, position, and length jointly determine the cooling performance. This evolutionary pattern provides a depth-dependent priority framework for IDP parameter design, offering clear guidance for engineering application across varying well depths. Full article

The integrity of cold chains is critical for preserving the quality, safety, and efficacy of temperature-sensitive products, including pharmaceuticals, vaccines, and perishable goods. However, real-world cold-chain operations are subject to environmental variability, operational disturbances, and transport-related uncertainties that are often inadequately captured by deterministic models. This study presents a stochastic modeling methodology that integrates a physics-based heat-transfer model with a machine-learning residual correction to predict temperature dynamics and product degradation under uncertainty. Temperature evolution is represented through a stochastic heat-transfer model incorporating random perturbations, while product degradation is quantified using Arrhenius-based kinetics that link thermal exposure to quality loss. A machine-learning-based residual correction is subsequently incorporated to improve predictive accuracy while preserving the physical structure of the governing model. The proposed methodology is evaluated through computational experiments using a representative pharmaceutical cold-chain transportation scenario. Numerical experiments based on the Euler–Maruyama method and Monte Carlo analysis are performed to assess the proposed methodology under representative operating conditions. Results indicate that stochastic variability can produce transient temperature excursions even when average operating conditions remain acceptable, leading to increased degradation and higher failure probabilities. The computational results demonstrate the feasibility of the proposed methodology for the probabilistic estimation of thermal risk and product quality deterioration by integrating physics-based modeling, uncertainty analysis, and data-driven residual correction within a unified computational methodology. The proposed methodology provides a computational basis for the future development of intelligent cold-chain monitoring and decision-support systems. Overall, it offers practical capabilities for uncertainty quantification, reliability assessment, and informed decision making in temperature-sensitive supply chains. Full article