Search Results (885)

Balancing low segment wear with stable cutting forces remains a challenge in granite sawing. This work compares diamond-impregnated saw segments produced by microwave– hybrid sintering (MWHS) and hot pressing (HP) when cutting Rosa Porriño granite. Tests were performed under tap-water cooling (22 L min⁻¹) while varying peripheral speed (20–40 m s⁻¹), feed speed (22–38 mm s⁻¹), and cutting depth (9–18 mm). Cutting forces were recorded during successive slots, and wear was quantified as mass loss per machined area (1.2–3.0 m² per test). MWHS segments exhibited lower wear than HP segments, with reductions up to ~20%, consistent with improved diamond retention and reduced binder exposure to debris-driven abrasion. Under higher cutting severity, however, MWHS segments developed higher forces, indicating reduced grit renewal and progressive blunting, plausibly linked to stronger diamond–matrix bonding and the low-friability diamond grade used. In contrast, HP segments operated at lower forces but showed higher wear, consistent with greater surface renewal through controlled grit release. Tuning diamond friability and matrix compliance in MWHS is proposed to stabilize forces while preserving the wear advantage. Overall, MWHS is a viable route for granite cutting segments, but further optimization is required to achieve HP-equivalent behavior across the tested conditions. Full article

As the core of digital infrastructure, the exceptionally rapid development of data centers (DCs) faces serious challenges due to their high electricity costs. Traditional approaches treat computational task scheduling separately from different physical control mechanisms, such as server group management, overlooking the synergistic potential between the two aspects. To address this problem, this paper proposes a computational–physical collaborative optimization model that realizes spatiotemporal task migration on the computational side and adaptive parameter regulation of IT equipment and cooling devices on the physical side. In response to the lack of global coordination in conventional distributed optimization, a two-layer partially observable Markov game (POMG) is constructed to unify global cooperative decision-making and local autonomous control. On this basis, the hierarchical multi-agent deep deterministic policy gradient (H-MADDPG) algorithm is designed by introducing task priority ranking and a variable-dimension action mask mechanism, which effectively handles the discrete–continuous hybrid action space and adapts to the dynamic variation in action dimensions caused by uncertain task arrivals. Comparative experiments with various benchmark schemes are conducted to verify the effectiveness and superiority of the proposed strategy in total cost, power usage effectiveness (PUE), resource utilization, and load balancing. Full article

Ground-source heat pump (GSHP) systems are widely used because of their energy-saving and environmentally friendly characteristics. However, the long-term operation of a standalone GSHP system leads to heat accumulation in the soil for cooling load-dominated buildings, which results in a decline in system performance. To address this issue, in this study, a high-speed railway station in Jinan was considered as the research object, and a hybrid system scheme in which a GSHP is coupled with an air-source heat pump (ASHP) was developed. The system uses the outdoor dry-bulb temperature as the control parameter and establishes a multi-unit operation control strategy. A dynamic simulation model of the hybrid system was constructed using TRNSYS software, and then the energy consumption, soil thermal balance, economics and environmental benefits of the system under various schemes and operating conditions were simulated and analyzed. Through a comparative analysis of the operating strategies, the optimal strategy that achieved the best performance was determined. Under the optimal strategy, the soil thermal imbalance rate after 10 years of operation was only 1%, the total energy consumption was significantly lower than that of a standalone ASHP system, and the initial investment was clearly lower than that of a standalone GSHP system. The results demonstrate that the hybrid system ensures soil thermal balance and high-efficiency operation while providing significant energy savings (a 28% primary energy savings rate compared to a standalone ASHP) and environmental benefits (reducing annual CO₂, SO₂, NOx, and dust emissions by 56.5 t, 384.2 kg, 361.6 kg, and 339 kg, respectively). Therefore, the emission of atmospheric pollutants such as CO₂, SO₂, NOx, and dust can be effectively reduced, thus providing an important reference for the development of building energy-saving technologies under the “dual carbon” goals. Full article

To address the issue of performance degradation resulting from continuous thermal accumulation in the soil for conventional ground source heat pump (GSHP) systems in cooling-dominated regions, a hybrid ground source heat pump–domestic hot water system (HGSHP-DHW) is proposed, along with a corresponding mode-switching control strategy. The heat pumps for cooling, heating, and domestic hot water in the HGSHP-DHW share the same ground heat exchanger (GHE) group. To accommodate varying energy demands in different seasons, the configuration of the ground source/side loop is switched according to signals from the control strategy. The average soil temperature rise, the coefficient of performance (COP) of the heat pump units, the system performance factor (SPF), the life cycle climate performance (LCCP), and the net present value (NPV) are selected as comprehensive evaluation indicators for fifteen years of operation. A comparative analysis with traditional systems, including chiller–boiler (CB), cooling tower coupled hybrid ground source heat pump (CT-HGSHP) and GSHP, which are all equipped with an air source heat pump (ASHP) for DHW, is also conducted. By the 15th year, the average soil temperature rise in the HGSHP-DHWs is 4.94 °C, a reduction of 55.5%, effectively alleviating soil thermal accumulation. In terms of energy efficiency, the SPF is 3.79, an increase of 70.8% with 43% reduction in the accumulation of energy consumption (P_ac), achieving high-efficiency and energy-saving operation. For environmental performance, the LCCP is 2,435,587 kgCO₂, a reduction 38.8% in carbon emissions, showing a remarkable emission reduction effect. In respect of economic returns, the NPV is 644,867 CNY, which is positive and indicates favorable investment viability. Full article

Outdoor thermal comfort in university courtyards is a key factor influencing students’ environmental experience and the usability of outdoor spaces in hot-arid climates. Courtyard design may also affect the environmental conditions of adjacent classrooms by modifying solar exposure, shading, air movement, and surface heat gain. Accordingly, this study aims to develop optimized design scenarios for improving outdoor thermal comfort in university courtyards through hybrid passive strategies, including vegetation, shading systems, and cool pavements. To achieve this goal, the research adopted a combined field-based and simulation-based methodology. Field measurements and student questionnaires for 292 students were conducted in courtyards and classrooms of three university buildings in Luxor, Egypt. These buildings represent different urban morphologies, courtyard aspect ratios, geometric configurations, and student densities. In parallel, simulation models were developed using ENVI-met V5.6.1 and Rhinoceros V8 with Grasshopper, to test and compare various design scenarios. Field monitoring revealed that wider courtyards with low aspect ratios (0.28–0.38), lacking trees and finished with concrete paving, recorded lower CO₂ concentrations (around 800 ppm), but experienced higher surface and air temperatures. These elevated temperatures negatively affected outdoor thermal comfort and increased heat gain in classrooms overlooking the courtyards. In contrast, courtyards with higher aspect ratios (0.63–0.82) demonstrated better microclimatic moderation and improved comfort conditions. Simulation results indicate that integrating a belt vegetation pattern of Cassia leptophylla, combined with textile shading and cool pavements with an albedo of 0.5, can reduce the Universal Thermal Climate Index (UTCI) by up to 14.7 °C, shifting conditions toward moderate heat stress. The findings provide practical design guidance for upgrading existing university courtyards and designing future educational buildings in hot-arid climates to enhance student comfort and environmental performance. Full article

Green building façades are increasingly recognized as a key strategy for decarbonizing the built environment, addressing climate change, urbanization, and the urban heat island effect. This paper investigates two main façade approaches: nature-based solutions (NBS), such as green façades and living walls, and Building-Integrated Solar Energy Systems (BI-SES), including photovoltaic, solar thermal, and hybrid BIPV/T systems. The building envelope is framed as an active interface for both energy efficiency and on-site renewable energy generation. Through a structured state-of-the-art review, the study compares these systems in terms of energy performance, environmental benefits, costs, maintenance, lifecycle implications, and adaptability across climatic contexts. Results show that NBS provide consistent benefits in thermal regulation and cooling-load reduction, while solar façades are strongly influenced by orientation, geometry, and urban shading. To complement the qualitative analysis, a preliminary energy–environmental assessment is conducted for three façade configurations (conventional wall, green façade, and combined green–PV façade) across three Italian climates (Milan, Rome, and Palermo). Results indicate that vegetation reduces heat losses and CO₂ emissions, with further improvements in integrated systems. Overall, NBS and solar façades emerge as complementary strategies whose integration can enhance building performance and support the transition towards net-zero carbon environments. Full article

Renewable energy sources, such as solar and biomass, represent sustainable alternatives to meet the growing energy demands of the residential sector. This study evaluated the energy, exergy, and environmental performance of two Brayton configurations using supercritical carbon dioxide: a recompression cycle (SRC) and a recompression cycle with intercooling in the main compression (SMC), both coupled to a dual-loop organic Rankine cycle (DORC) and powered by a hybrid solar-biomass thermal system. Mass, energy, and exergy balances were developed, and a life cycle assessment was performed to quantify the environmental impact. The systems were designed to cover a cooling load of 130 kW corresponding to 200 dwellings constructed with Asbestos cement in the Colombian Caribbean region. The results show that both configurations meet the required demand; the SMC-DORC cycle operates at 650 °C, while the SRC-DORC requires 750 °C. The SRC-DORC exhibits higher thermal efficiency (53.24%), while the SMC-DORC achieves a slightly higher exergy efficiency (28.15%). Environmental analysis shows that the construction phase accounts for the majority of the total impact, exceeding 95% of emissions. Overall, both configurations are technically feasible, with the SRC-DORC standing out for its balance between efficiency and environmental impact. Full article

The integration of Selective Laser Melting (SLM) into high-end manufacturing necessitates robust machine-condition monitoring and subsystem fault classification to navigate the intricate coupling and dynamic transients inherent in these systems. Current diagnostic frameworks often struggle to decouple high-dimensional state variables or track their underlying temporal evolution. To overcome these bottlenecks, this paper develops a spatiotemporal deep learning architecture by coupling Convolutional Neural Networks (CNNs) with Long Short-Term Memory (LSTM) units. This hybrid approach leverages CNNs to distill multi-dimensional spatial features from subsystem sensor arrays, while LSTMs interpret the sequential dependencies critical for identifying systemic drifts. The proposed framework was validated using an extensive industrial dataset comprising over 310,000 temporal samples across seven critical SLM subsystems, including optical, cooling, and energy units. We systematically investigated three data-handling strategies—feature weighting, balancing, and distribution-based synthesis—to optimize the model’s sensitivity to rare-event anomalies. Benchmarking across six architectural variants reveals that a specific CNN × 3 + LSTM × 1 configuration yields superior diagnostic fidelity, achieving a classification accuracy of 98.81%. Visualization of the feature space confirms high inter-class separability, demonstrating the model’s ability to isolate faults within complex manufacturing cycles. This research offers a scalable paradigm for the intelligent monitoring of SLM equipment and provides a technical benchmark for equipment health management and predictive maintenance in advanced additive manufacturing. Full article

This study addresses a critical methodological gap in evaluating building envelope performance in hot, arid climates, the overreliance on annual energy indicators, which fail to capture transient thermal behavior during peak-load periods. In such environments, instantaneous heat gains, their intensity, and temporal distribution are decisive factors for cooling demand, occupant comfort, and grid stability. To overcome this limitation, a dynamic evaluation framework—the Thermal Adaptation Rating (TAC) system—is proposed. TAC integrates three interrelated indices—peak temperature reduction (ΔT_peak), relative peak cooling load reduction (ΔP_peak, %), and peak thermal delay (Δt_delay), representing thermal damping, load intensity mitigation, and temporal redistribution, respectively. A typical residential building in Karbala was modeled in DesignBuilder using the EnergyPlus engine, with inputs documented and calibration performed against real consumption data following ASHRAE standards (MBE and CV(RMSE)) to ensure reliability. The study examined advanced envelope systems, including thermochromic glass (TG), phase-change materials (PCMs), aerogel materials (AMs), and hybrid combinations. Results revealed that while AM achieved the greatest annual energy savings, its impact on instantaneous cooling load was limited. PCM, by contrast, effectively mitigated and delayed peak loads, enhancing thermal comfort (PMV/PPD). Hybrid systems, particularly TG-PCM, delivered the most balanced performance, simultaneously reducing peak cooling load and shifting its occurrence to reshape the cooling demand curve during critical periods. These findings demonstrate that annual indices alone are insufficient for evaluating envelope performance in extreme climates. Peak-condition analysis, expressed in terms of instantaneous cooling load, as operationalized through TAC, provides a more accurate representation of thermal behavior and offers a practical tool to guide envelope design decisions in hot, dry regions. Full article

AI data-center (DC) growth is increasingly constrained by limited deliverable electricity, interconnection capacity, and cooling demand. This study develops a boundary-consistent screening framework for waste-to-energy (WtE)-coupled AI DC cooling, treating cooling as an energy service that can be supplied through grade matching rather than solely through electricity-driven mechanical chilling. The framework translates plant-side exportable heat into corridor-level planning objects by explicitly accounting for thermal attenuation, absorption-based conversion, and parasitic electricity associated with delivery and auxiliaries. Three results structure the analysis. First, a reference-case energy-service ledger shows how a representative regulated WtE plant with municipal solid-waste throughput of 1500 t/day and lower heating value of 10 MJ/kg yields ~78.1 MWth of exportable driving heat and, at a 20 km corridor, ~53.0 MWcool of delivered cooling and ~8.0 MWe of net avoided cooling electricity after parasitic debiting. Second, the coupled system is governed by operating regimes, not a single efficiency score. Under the baseline package, full thermal coverage is maintained up to ~20.9 km, the stricter quality-adjusted criterion remains positive to ~22.9 km, and the electricity–relief criterion remains positive to ~44.7 km. Third, deployment-scale translation for a 1 GW IT campus (u = 0.70, L = 5 km) implies a net grid relief of ~116.9–264.4 MW across scenario packages, while the required WtE footprint ranges from roughly three to 148 equivalent representative plants, or about 0.6–40 full-load-equivalent plants at a 25% displacement target. The contribution is a siting-ready planning framework that identifies when WtE-coupled cooling remains corridor-feasible, when it becomes hybrid and marginal, and when infrastructure scale rather than thermodynamic benefit becomes the binding constraint. It is intended as a screening tool for planning and comparison, not as a project-specific hydraulic or plant-cycle design. Full article

Due to advancements in thermal engineering and nanotechnology, nanofluids—base fluids containing dispersed nanoparticles (1–100 nm)—have emerged as promising high-performance coolants. Their enhanced thermal properties make them attractive for application in hybrid-electric aircraft, which require efficient Thermal Management Systems (TMS) to dissipate significant heat loads. This study employs a dynamic TMS model to assess the influence of key nanofluid features, including nanoparticle type, volume fraction, particle diameter, and base fluid. Metal nanoparticles provided the greatest thermal improvement (up to 19%). Increasing concentration enhanced cooling efficiency, with 0.5%, 1%, and 2% volume fractions reducing mean temperature by 14%, 19%, and 24%, respectively. Smaller particles performed better, as 20 nm nanoparticles achieved a 21.3% temperature reduction compared to 17.5% for 60 nm. Water-based nanofluids exhibited the best overall thermal behaviour, although they remain unsuitable for aeronautical applications. Full article

Decarbonising greenhouse food production requires improvements in thermal management, energy efficiency, and system integration. Greenhouse energy demand is shaped by coupled heat and mass transfer processes, particularly envelope performance, ventilation, and latent heat associated with humidity control. This article synthesises recent advances in greenhouse microclimate control with emphasis on heat transfer, low-carbon heating and cooling, thermal storage, renewable and waste heat integration, and advanced modelling and control approaches. The review shows that humidity control and latent load management are primary drivers of winter energy use, as moisture removal through ventilation and dehumidification directly increases the sensible heating required to maintain indoor temperature setpoints. When assessed using realistic psychrometric relationships, ventilation and dehumidification can dominate peak heating demand and seasonal consumption. The performance of heat pumps, storage systems, semi-closed greenhouse concepts, and renewable heat pathways depends on how thermal loads are defined, how system boundaries are set, and how technologies are integrated in operation. Digital twins, predictive control, and hybrid physics-data models are increasingly used to manage variability in weather, energy prices, and infrastructure constraints. Greenhouse decarbonisation cannot be treated as a simple substitution of energy sources. System performance depends on coordinated design and operation, including heat recovery, moisture removal, and integration of supply technologies. Semi-closed and heat recovery-based configurations can reduce the ventilation–heating penalty and lower primary energy demand compared with vent-to-dry approaches. Long-term market projections suggest that the commercial greenhouse sector could expand substantially by 2050 under plausible growth scenarios, reflecting increased capital investment rather than a proportional rise in global food output. Net-zero greenhouse production is achievable through combined improvements in thermal management, electrification, and renewable energy integration. However, large-scale deployment depends on consistent modelling assumptions, credible economic assessment, and alignment with heat and CO₂ supply infrastructure. The transition is therefore shaped by system integration and planning as much as by individual technologies. Full article

Efficient thermal management is critical for maintaining the safety, durability, and performance of lithium-ion batteries used in electric vehicles (EVs). In this study, a comprehensive numerical investigation is conducted to evaluate the heat transfer characteristics of mono- and hybrid-nanofluids in a microchannel-cooled lithium-ion battery module. A three-dimensional computational model of a 5S7P battery module composed of cylindrical 21700 cells is developed. Battery heat generation during 3C high discharge rate operation is predicted using the Newman-Tiedemann-Gu-Kim (NTGK) electrochemical model, while coolant flow and heat transfer are simulated using the governing conservation equations for mass, momentum, and energy. The cooling system consists of six liquid-cooling plates with circular microchannels. The performance of water-glycol (50/50) coolant is compared with several mono nanofluids of Al₂O₃ and Cu, and hybrid nanofluids of Al₂O₃-Cu, Al₂O₃-MWCNT, Al₂O₃-Graphene, Cu-MWCNT, and Cu-Graphene across multiple coolant flow rates from 1–5 LPM. The results demonstrate that nanofluids significantly enhance convective heat transfer and reduce battery temperature compared with the conventional water-glycol coolant. Among the investigated coolants, the Al₂O₃-Cu hybrid nanofluid (0.45–0.45%) operating at 1 LPM achieves the best overall thermo-hydraulic performance with a performance evaluation criterion (PEC) of 1.065. Further analysis of nanoparticle composition ratios shows that a Cu-dominant hybrid mixture (Al₂O₃-Cu: 0.27–0.63%) slightly improves the PEC to 1.0657, indicating marginally superior cooling performance. The findings highlight the potential of hybrid nanofluids as advanced coolants for microchannel-based battery thermal management systems in EVs, particularly under moderate coolant flow conditions. Full article

With the growing demand for hybrid and electric vehicles, the accurate prediction of NVH (Noise, Vibration, and Harshness) behavior in Permanent Magnet Synchronous Machines (PMSMs) has become a critical aspect of electric motor design. This paper presents a detailed modeling approach for electromagnetic-induced noise and vibrations in PMSMs, integrating both analytical and numerical methods. The model focuses on quantifying the contributions of radial and tangential electromagnetic forces, which are key drivers of vibro-acoustic responses. The analytical part employs curved beam theory and a simplified acoustic model, offering rapid insights during early design stages. In parallel, a detailed numerical model based on finite element analysis is developed using a physics-based approach that accounts for the actual geometry and material properties of the PMSM prototype. This allows for enhanced accuracy without relying on experimental material parameter identification. Moreover, the detailed model includes the fluid–structure interaction introduced by the channels of the cooling fluid of the electric machine, which, although poorly addressed by the existing literature, was found to play a key role in driving the vibrational behaviour of the structure. By combining analytical speed with numerical precision, the proposed approach enables consistent and physically-based NVH predictions across various design phases, ultimately supporting improved electric machine performance and reducing development time and costs. Validation against experimental data confirms the ability of the model to accurately predict both sound pressure levels and housing surface vibrations. The novelty of this work lies in its integration of fluid–structure interaction and material modeling without the need for empirical parameter tuning, offering a robust tool for NVH design in electric vehicle applications. Full article

Decarbonizing the transportation sector requires quick adoption of low-carbon energy carriers, with green hydrogen becoming a promising option for zero/low-emission mobility. Hydrogen refueling stations powered by renewable energy sources present a practical way to cut down lifecycle greenhouse gases and ease grid congestion. Nonetheless, most existing photovoltaic (PV)-based hydrogen production systems focus solely on electrical aspects, overlooking thermal energy flows and temperature effects that greatly impact PV and Electrolyzer performance. This study provides a thorough techno-economic evaluation of a hybrid PV/photovoltaic-thermal (PVT) green hydrogen system for refueling stations. The simulation framework models the combined electrical, thermal, and hydrogen subsystems under realistic conditions, incorporating rooftop PV/PVT collectors, battery storage, a water Electrolyzer, and hydrogen storage. Thermal energy from the PVT is used to pre-heat Electrolyzer feedwater, lowering electricity demand for hydrogen production and boosting PV efficiency via active cooling. Hydrogen production follows a demand-driven control strategy based on randomly generated stochastic daily refueling events. Three configurations are compared: (i) grid-only electrolysis, (ii) PV-only assisted electrolysis, and (iii) fully integrated PV/PVT-assisted electrolysis. The results show that the integrated PV/PVT setup significantly increases self-consumption, autarky rate, and overall efficiency, while lowering reliance on grid electricity and hydrogen production costs. Developed case studies highlight the economic feasibility and real-world viability of PV/PVT-assisted (decentralized) hydrogen refueling infrastructure. Full article