Search Results (3,753)

The WELL Building Standard (WELL) is a certification system designed to enhance occupant health and well-being in indoor environments. Conventional building energy-saving strategies typically rely on fixed temperature setpoint adjustments, which may conflict with WELL thermal comfort requirements. However, achieving high energy efficiency remains essential. This study uses a quantitative evaluation framework with TRNSYSs to examine the effectiveness of integrating load reset control (LRC) into simultaneous heating and cooling (SHC) systems. It compares LRC with conventional fixed setpoint (SP) and predicted mean vote (PMV) control strategies, based on WELL’s thermal comfort criteria (maintaining the PMV between −0.5 and +0.5). Six simulation cases were analyzed, considering radiant (RAD) and convection (CONV) terminals. The results indicate that radiant terminals provide more stable PMV performance while consuming less energy than convection terminals, demonstrating better compliance with WELL objectives. Although PMV control achieves the highest thermal comfort, it substantially increases energy consumption. In contrast, LRC emerges as an optimal strategy, effectively balancing the energy efficiency of SP control with the comfort of PMV control. The RAD-LRC configuration delivers the best overall performance. It achieves higher thermal comfort than SP, with comparable energy consumption, making it a highly practical approach for modern building energy management. Full article

This study investigates unsteady magnetohydrodynamic free convection flow past a rotating vertical plate embedded in a Darcy–Forchheimer porous medium. The formulation incorporates Hall current, thermal radiation, viscous dissipation, Joule heating, and an Arrhenius-type chemical reaction with activation energy to represent thermo-reactive transport in an electrically conducting fluid. The coupled nonlinear equations governing momentum, thermal energy, and species concentration are transformed into dimensionless form and solved numerically using the Crank–Nicolson scheme. Grid independence and validation tests confirm the accuracy and stability of the numerical procedure. The results show that electromagnetic forces, rotation, porous resistance, and thermo-reactive effects significantly influence wall shear stress, heat transfer, and mass transport. In particular, the interaction between magnetic field strength and Hall current alters near-wall transport behavior, highlighting the role of electromagnetic coupling in rotating porous systems. The study provides physical insight relevant to the design and analysis of transport processes in high-temperature energy systems, rotating reactors, and porous thermal management devices. Full article

Industrial tunnel pasteurizers are widely used for bottled liquid products because they provide a robust and continuous thermal treatment. However, operating conditions are often conservatively selected to ensure microbiological safety, which may result in excessive energy consumption and limited thermal efficiency. This study experimentally investigates the thermal behavior and energy performance of an industrial tunnel pasteurizer used for a sealed bottled herbal-based high-viscosity liquid formulation under both nominal and modified operating conditions. An instrumented bottle was developed to measure temperature evolution at different locations inside the bottle, including the product core. In parallel, the overall heat capacity of the bottle–product system was determined by differential scanning calorimetry, enabling the estimation of the thermal energy absorbed by the bottles. Mass and energy balances were applied to quantify the heat exchanged in each process stage and to estimate phase-specific and overall heat-transfer efficiencies. Under nominal conditions, the pasteurization requirement, defined as a temperature above 72 °C for at least 12 min at the coldest point, was fully satisfied, with the temperature remaining above 72 °C for approximately 22 min near the bottle wall and 17–18 min at the product core. The energy analysis showed that overall process efficiency was limited, indicating room for improvement. Three additional experimental tests were therefore carried out under modified temperature and flow-rate conditions. In all cases, the pasteurization target was maintained. The results demonstrate that the process complies with the prescribed pasteurization target while offering significant opportunities for energy savings through optimization of the operating parameters. Full article

To address the demands of large-scale production in the photovoltaic industry for laminators with a small footprint, low energy consumption, and high encapsulation quality, this paper presents research on the structural design, simulation optimization, and performance validation of a multi-layer laminator for photovoltaic modules. Different from existing single-layer or double-layer structures, this paper proposes for the first time an eight-layer, three-stage overall scheme, develops modular lamination units, completes the design of core systems, and achieves multi-chamber coordination. Simulation validation was conducted on the temperature uniformity of the heating plates and the thermo-mechanical coupling under vacuum conditions. A prototype, model HCDL2743DSiT, was developed and subjected to a 30-day production trial. The results show that the equipment reaches a vacuum degree of 92 Pa within 100 s and drops to 38 Pa within 120 s; the temperature uniformity error of the heating plates is ±1.3 °C; the maximum positioning deviation of the transmission is ±2.8 mm. All core indicators meet the design requirements, and the module encapsulation pass rate reaches 99.9%. At the same production rate, the footprint is reduced by approximately 72% compared with that of a traditional double-layer laminator, achieving dual optimization of space utilization and energy consumption and providing technical equipment support for the high-efficiency encapsulation of photovoltaic modules. Full article

A novel open-loop thermosyphon heat engine driven by low-temperature waste heat is proposed for simultaneous power generation and freshwater production. Large quantities of low-grade thermal energy from sources such as data centres remain underutilised due to the limited efficiency and mechanical complexity of conventional heat engines at low temperatures. The proposed system employs thermosyphon-driven circulation and gravity-assisted condensate return, eliminating mechanical pumping and reducing parasitic losses. A mathematical model was developed to evaluate system performance under low-grade heat input conditions. For a baseline case with 50% turbine isentropic efficiency and 5000 W thermal input, the model predicts an overall efficiency of 3.8% and freshwater production of 143 kg/day. A parametric study was conducted to identify the dominant performance parameters and assess sensitivity to operating conditions. While the predicted power output does not exceed that of optimised Organic Rankine Cycle systems, the proposed configuration offers reduced mechanical complexity and inherent freshwater production through phase change. Unlike membrane-based desalination systems, the open-loop design can accommodate high-salinity feeds, including concentrated brine streams, enabling high recovery operation. These characteristics suggest potential application in low-temperature waste heat recovery scenarios where simplified operation, high-salinity tolerance, and combined energy–water generation are desirable. Full article

Air-to-air heat pumps are a key technology for improving energy efficiency and reducing carbon emissions in residential buildings, yet their optimal control remains challenging under real-world conditions. This study evaluates the performance of a hybrid physical–LSTM model for controlling an air-to-air heat pump in a residential building in Zadar, Croatia. The hybrid framework integrates a first-order energy balance model of the building envelope with LSTM-based temperature correction using adaptive weighting. The physical model was calibrated and validated against 52,128 real IoT measurements collected during the 2024/2025 heating season, achieving high accuracy (RMSE ≈ 0.076 °C). Rolling one-day and continuous multi-day closed-loop simulations (up to 15 days) show that the hybrid model yields slightly lower RMSE in long-term runs compared to the pure physical model. However, this apparent statistical improvement is accompanied by systematic underestimation of indoor temperature and significantly higher simulated energy consumption. The results indicate that the observed effect originates from an implicit virtual heat flux introduced by the LSTM correction, which affects thermodynamic consistency in closed-loop operation. The findings highlight that short-term error metrics such as RMSE alone are insufficient for evaluating hybrid models intended for model predictive control (MPC). The main contribution of this study is the explicit demonstration and quantification of an implicit virtual heat flux generated by the LSTM correction in closed-loop multi-day operation, which leads to misleading statistical improvements while causing significant thermodynamic inconsistency and energy overconsumption. In 15-day continuous simulations the hybrid model (ω = 0.05–0.10) caused an indoor temperature underestimation of 1.25–1.31 °C and increased simulated electricity consumption by more than 300% (316 kWh vs. 72 kWh) compared to the physical model. These results have direct implications for the development of reliable digital twins and model predictive control strategies in residential HVAC systems. Full article

Proteomic research in the genus Vitis has progressed from early biochemical studies of soluble proteins to high-resolution, quantitative analyses encompassing all major organs and derived products. This review provides a comprehensive synthesis of advances in grapevine and wine proteomics. In leaves, studies have revealed extensive remodeling of photosynthetic, antioxidant, and defense pathways under biotic (e.g., Plasmopara viticola, Erysiphe necator, Xylella fastidiosa, Candidatus Phytoplasma vitis) and abiotic stresses (drought, salinity, heat, light). Bud proteomics elucidated hormonal regulation and mechanisms of dormancy release, while root studies identified nitrate-dependent metabolic shifts and adaptive protein networks. Cell culture models enabled controlled investigation of elicitor responses, stilbene biosynthesis, and temperature-induced proteome changes. In berries, proteomics clarified developmental transitions from fruit set to ripening, emphasizing proteins related to secondary metabolism, vacuolar transport, and stress tolerance. Comparative analyses across cultivars and environments identified biomarkers linked to aroma, color, and texture. The wine proteome revealed selective persistence of grape-derived proteins (e.g., thaumatin-like proteins, chitinases) and yeast peptides influencing stability and sensory properties, while Botrytis cinerea infection significantly alters this balance by degrading PR proteins and introducing fungal enzymes. Altogether, the Vitis proteome emerges as a dynamic, multifunctional system crucial for understanding plant adaptation, enological quality, and biomarker discovery. Full article

Selenium-sand melon (Cucumis melo L.) juice (SSJ) is valued for its lycopene and organic selenium content, but its shelf-life is limited by heat-labile nutrients and postharvest microbial spoilage. Non-thermal strategies that combine UV-C with natural antioxidants are therefore of interest. This study quantified the individual and interactive effects of UV-C alone or with four antioxidant systems on microbial safety, bioactive retention, and the flavor stability of SSJ under extreme contamination conditions (Escherichia coli D25015 at 5.19 log₁₀ CFU/mL; Mucor circinelloides D11624 at 4.36 log₁₀ CFU/mL). For this, we evaluated the efficacy of five treatments: UV-C alone (Group Z) and UV-C combined with catechin (Group EC, 0.01%), sodium erythorbate (Group K, 0.01%), ascorbic acid (Group VC, 0.1%), and catechin-ascorbic acid (Group HH, 0.005% + 0.05%). Conventional pasteurization (high-temperature short-time, HTST; low-temperature long-time, LTLT) served as controls. UV-C alone (Group Z) preserved lycopene and volatile flavor compounds better than HTST or LTLT. The combined use of UV-C and antioxidants exhibited synergistic effects, with no viable bacteria detected in Group K (sodium erythorbate) within four weeks. UV-C combined with antioxidants offer a scalable, non-thermal strategy that maintains nutritional and sensory quality while achieving pathogen reduction. These findings provide a quantitative framework for clean-label preservation of functional melon beverages. Full article

Fuel vapor can be ignited by lightning through various means, particularly through hot spot formation on fuel tank skins. The wing fuel tank cover and its surrounding outer plates together form part of the aerodynamic shape of an aircraft. The lightning protection design of the fuel system, including wing fuel tank, is of great significance for ensuring the aircraft safety. Based on the Joule heating and implosion effect, the damage response of a composite fuel tank cover subjected to lightning strikes is analyzed in this paper. The adopted method combines electrical–thermal coupling with explicit dynamics analysis. Firstly, a finite element model of the fuel tank cover is established using electrical–thermal coupling elements, and the lightning current impact simulation is carried out under given electrical boundary conditions and thermal boundary conditions. On one hand, the ablation criterion is determined by the Joule heating effect and the sublimation temperature of materials. The thermal damage of composite materials subjected to transient high currents is obtained through transient thermal analysis. On the other hand, special implosion elements are selected according to the temperature distribution obtained from the electrical–thermal coupling analysis. The original composite material model in the implosion region needs to be replaced with a new material model described by the high-explosive material model and the JWL equation of state. The von Mises stress distribution and pressure distribution on the structure after implosion are discussed in detail. The results show that concave pits are formed near the implosion zone. Unlike the thermal damage morphology defined by the ablation criterion, the implosion effect makes the damage distribution deviate from the initial fiber direction of each layer. The implosion dynamic method reveals the internal damage and pit and bulge phenomenon around the lightning attachment area to a certain extent. Full article

Bidirectional power converters generate significant heat losses during high-frequency operation, posing a severe challenge to the performance of heat dissipation systems. Traditional thermal design methods often struggle to balance multiple objectives, such as cooling efficiency, cost, weight, and size, thereby limiting the reliability and safety of the system. To address these challenges, this paper proposes a novel Multi-Objective Exponential Distribution Optimizer algorithm based on the Exponential Distribution Optimizer. Subsequently, key design variables of the heat dissipation system are selected. Next, the Optimal Latin Hypercube Sampling method is employed to generate sample points, and a second-order response surface surrogate model for the heat pipe radiator’s volume and temperature is developed. Lastly, by integrating elite non-dominated sorting, crowding distance mechanisms, and an information feedback mechanism, the multi-objective challenge is decomposed into subproblems, thereby enhancing optimization efficiency. Through comparative simulation experiments on benchmark functions, the Wilcoxon signed-rank test results for the MOEDO algorithm on the majority of the three metrics are denoted as ‘+’, indicating statistically significant advantages over the compared algorithms, thereby demonstrating its superior performance in addressing multi-objective optimization problems. The study further conducts simulation verification of the heat pipe heat dissipation system before and after optimization using ANSYS Icepak. The simulation results demonstrate that, compared with the conventional design, the maximum Insulated Gate Bipolar Transistor (IGBT) temperature is reduced by 17.12% and the heat sink volume is reduced by 14.61%. Full article

With the accelerated transformation of green shipping and the advancement of ship electrification, lithium-ion batteries have become the core solution for ship propulsion due to their advantages of high energy density and zero emission. Efficient thermal management serves as a key technical support to ensure the safe and stable operation of batteries, extend their service life, and mitigate the risk of thermal runaway. Lithium-ion batteries accumulate heat during discharge, and pure phase change material (PCM) cooling systems are limited by low thermal conductivity, leading to excessive battery temperature rise and poor temperature uniformity. To address this problem, RT42 (a paraffin-based PCM with a melting temperature range of 311.15–316.15 K) was selected as the PCM in this study. The battery thermal management system (BTMS) coupling RT42 with a three-dimensional fin network structure was designed. Numerical simulations were conducted via ANSYS Fluent, and the enthalpy-porosity method was adopted to simulate the PCM phase change process. The effects of fin distribution, spacing and layer number on BTMS performance were systematically investigated and compared. Results show that the heat transfer process in the PCM can be significantly improved due to the three-dimensional fin network, and the battery maximum temperature can be reduced by 7.53 K compared with the pure PCM system. This study provides theoretical support for the design and optimization of high-efficiency BTMS. Full article

To address the problems of insufficient precision reserve, limited rotational speed, and excessive temperature rise in high-speed ultra-precision machine tool spindle bearings, the influence of frictional power loss on the thermo-mechanical behavior of the bearing system was investigated. Firstly, based on the analysis of the heat source of the bearing, the friction power consumption model of the bearing assembly is established, and the analysis of the bearing temperature field is realized by studying the heat energy transfer. Secondly, the test bench is built for experimental verification. Finally, through the study of thermal-mechanical coupling performance, the influence of different rotational speeds on bearing stress and life is analyzed. The results show that the friction power consumption generated by the spin sliding of the bearing rolling element accounts for the largest proportion, accounting for 31% of the total friction power consumption; the increase in bearing speed will increase the bearing temperature. At 55,000 r/min, the highest temperature at the rolling element is close to 75 °C, followed by the inner ring up to 68 °C, and the lowest outer ring temperature is 57 °C. The temperature has a great influence on the bearing performance. Under the same working conditions, the equivalent stress is increased by 21%, the contact pressure is increased by 25%, and the fatigue life of the bearing is reduced by 5.6%. Bearing performance is significantly affected by thermodynamic behavior. Full article

Seafloor hydrothermal systems at mid-ocean ridges are focal points for heat and matter exchange between the seawater and lithosphere. While seafloor seismographs (OBS) and pressure recorders (BPR) are standard for regional monitoring, achieving high-precision, vertical sub-surface data in complex hydrothermal terrains remains a significant technical objective. This study presents a novel in situ penetration probe designed for multi-parameter monitoring of marine hydrothermal vent areas. A key innovation of this work is its operational versatility and engineering efficiency: the probe is specifically designed for post-drilling deployment in boreholes, effectively utilizing existing coring sites to achieve direct coupling with the deep-seated crust, or for targeted placement via Remotely Operated Vehicles (ROVs). The device integrates a titanium-alloy conical tip and cylindrical chamber, housing tri-axial accelerometers and dual temperature-pressure sensors. Numerical simulations using the SST k-ω turbulence model and finite element analysis optimized the cone aperture and assessed fluid–structure stability under deep-sea conditions. Laboratory vibration tests and shallow-water sea trials validated the probe’s basic dynamic response, electromechanical integrity, and capability to acquire coupled environmental parameters. This compact, modular design provides a scalable and cost-effective framework for precise three-dimensional observation of sub-surface hydrothermal processes and deep-sea resource exploration. Full article

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

Preparing a highly wear-resistant AlTiN coating on a powder metallurgy (PM) M42 high-speed steel substrate is a key strategy to enhance tool performance and meet the demands of efficient machining. This study adopted a process route comprising substrate preparation, heat treatment regulation, and arc-PVD deposition of AlTiN coatings to systematically investigate the influence of sintering temperature (1130, 1160, and 1190 °C) and austenitizing time (1150 °C for 0, 15, 60, and 120 min) on the microstructure and mechanical properties of the substrate, as well as on the tribological performance of the AlTiN coatings. The results indicate that elevating the sintering temperature promotes densification of the matrix, with Vickers hardness increasing from 366 HV to 462 HV and bending strength (σ) increasing from 1064 MPa to 1310 MPa. The predominant carbide phases identified are MC, M₂C, and M₆C. During austenitizing, microstructural changes consistent with a progressive transformation from M₂C to MC and M₆C carbides were indicated by SEM and XRD analyses. Precipitation strengthening was most evident after 60 min, with hardness reaching 868 HV. In contrast, bending strength (σ) exhibited a progressive decline with increasing austenitizing time, decreasing from 1310 MPa to 1015 MPa after 120 min, illustrating a clear trade-off between hardness and toughness. The wear behavior of the coating is governed synergistically by substrate hardness, bending strength (σ), coating–substrate interfacial adhesion strength (L_C), and carbide phase transformation. Elevated substrate hardness enhances anti-wear performance; bending strength influences crack propagation and spallation tendency; and L_C determines the efficiency of interfacial load transfer. The carbide phase evolution appears to modulate the coating’s wear behavior by regulating both the microstructure and mechanical properties of the substrate. Among the six sample conditions evaluated, the A3 sample (sintered at 1190 °C and austenitized for 120 min) exhibited the lowest wear rate (2.38 × 10⁻⁶ mm³·N⁻¹·m⁻¹), demonstrating superior wear resistance. These findings provide a reference for process optimization and rational design of M42/AlTiN composite coating systems. Full article