Search Results (4,665)

In the split main transformer room of the indoor substation studied in this paper, the heat dissipation area of the transformer main body and part of the convection pipeline accounts for approximately 5.4% of the total heat dissipation area, with the outdoor radiator responsible for releasing most of the heat. Compared with the integrated main transformer room of indoor substations, the split-type design features a smaller building size and lower ventilation energy consumption, thus it is widely applied in urban areas. This study employs computational fluid dynamics (CFD) simulation to investigate the natural ventilation and heat dissipation performance of the main transformer room in a 110 kV indoor substation located in the Shijiazhuang area. A thermal imager is used to capture the surface temperature distribution of the main transformer, and the data is fitted into a polynomial function. During the numerical simulation, the surface temperature of the main transformer is set using a user-defined function (UDF), and the total heat dissipation of each heat-dissipating surface of the transformer is extracted via FLUENT(Ansys 2024 R2) software as the basis for evaluating the ventilation and heat dissipation effectiveness. The effects of different ventilation window sizes on the natural ventilation heat dissipation and air change rate of the indoor substation’s main transformer room under thermal pressure are compared. The feasibility of this numerical simulation method is verified through experimental measurements and theoretical analysis. Full article

Orthopaedic plates are long-established medical devices conventionally manufactured from metals, most notably titanium alloys. The introduction of Additive Manufacturing (AM) has created new opportunities to design implants with complex internal architectures, enabling precise control over infill patterns and densities that directly influence mechanical properties and fatigue performance. Biodegradable polymers such as polylactic acid (PLA) have attracted growing interest in biomedical engineering, potentially reducing the need for secondary implant-removal surgery if degradation rates are carefully controlled and clinically approved. Additionally, AM offers the ability to customise internal structure for improved mechanical performance and load-bearing, while also providing the possibility of integrating advanced functionalities, such as controlled drug delivery. Building on previous work by our research group at the University of Belgrade, this study investigates the fatigue behaviour of the best-performing AM-optimised orthopaedic plate design. Numerical models incorporating honeycomb infill structures with the full range of achievable densities were developed to assess structural integrity under fatigue loading. Fatigue crack growth was simulated in ANSYS Mechanical (ANSYS Inc., Canonsburg, PA, USA) software, employing a four-point bending configuration in accordance with the ASTM F382 standard. A validated PLA material model was implemented at a reduced load level (10%) relative to previous studies. Direct comparison with titanium plates was avoided due to fundamentally different material properties, focusing instead on infill architecture to identify optimal AM design strategies for orthopaedic plates. Full article

Francis turbines are renowned for their high efficiency and adaptability across a wide range of head and discharge conditions. However, internal mechanical friction losses (IMFLs), resulting from rotational frictional resistance between the rotating runner and the surrounding fluid, remain a significant obstacle to further performance optimisation. This study introduced a CFD-derived integral friction torque framework, validated through theoretical analysis, that enables the spatially resolved quantification of IMFLs in Francis turbine runners. Building on this framework, a comprehensive computational approach was established to quantify IMFLs in a Francis turbine runner using a CFD-derived integral torque method combined with a theoretical verification model. Three runner configurations were analysed: the original runner model (ORM), a modified runner (RM1) with selective exit height reduction, and a modified runner (RM2) with uniform exit height reduction. Transient simulations were conducted at the best efficiency point (BEP) using the shear stress transport (SST) k–ω turbulence model and a sliding mesh approach. The numerical results were verified using the theoretical model and systematically evaluated to assess IMFL mechanisms and runner performance. The findings demonstrate that variations in runner geometry significantly influence internal frictional resistance and turbine efficiency. Compared with ORM, both RM1 and RM2 reduced the rotational friction torque, with RM2 exhibiting the greatest improvement: a 2.83% reduction in total friction resistance torque, a 14.74% reduction in total power losses, and a 1% absolute increase in efficiency. These improvements are primarily attributed to reduced wall shear stress and a more uniform pressure distribution across the runner surface. Full article

One of the ways to decarbonize cities and to enhance grid stability is to convert existing buildings into prosumers equipped with power plants able to supply electrical and thermal energy. The simulation of such multi-energy systems permits the analysis of their performance in steady-state and dynamic conditions, with the aim of defining effective operating strategies able to reduce emissions and costs. The present paper describes a dynamic simulation model, implemented in the Matlab/Simulink R2025a environment, developed to simulate the daily and weekly operation of a prosumer building equipped with a small-sized cogeneration unit, a Photovoltaic (PV) plant, a back-up boiler, a thermal storage system and some charging points for Electric Vehicles (EVs). The mathematical model is reported in detail, and the main results of the study are described, referring to operating days characterized by different weather conditions. Then, energy, economic and environmental performance indicators are defined and calculated for the different simulated scenarios. Over the considered time horizons, the simulation results highlight a significant increase in the electrical self-sufficiency of the facility up to 91.1% and an important reduction in total net operating costs up to 59.8%, compared to the AS-IS case (i.e., without the newly installed technologies). Full article

Large temperature gradients encountered in aerospace, energy, and microelectronics systems impose stringent requirements on material thermal performance. Functionally graded materials (FGMs), characterized by a continuous variation in composition and properties, offer significant advantages in regulating heat transfer and mitigating thermal stresses. This review provides a systematic summary of recent progress in heat transfer design optimization of FGMs under large temperature gradient conditions. From a methodological perspective, advancements in structural and compositional optimization, topology optimization, and multi-objective optimization are reviewed. Numerical simulation techniques, including conventional finite element and finite volume methods, as well as emerging approaches such as peridynamics, isogeometric analysis, and meshfree methods, are discussed with an emphasis on multiphysics coupling. In addition, representative applications of FGMs in electronic thermal management, aerospace thermal protection, energy systems, and building energy conservation are reviewed. Current challenges, including idealized modeling assumptions, limited coordination among multiple optimization objectives, and insufficient reliability evaluation in complex service environments, are identified. Finally, future research directions are outlined, highlighting intelligent design methods, multiscale modeling, advanced manufacturing technologies, and multifunctional integration. This review seeks to provide a comprehensive reference for both fundamental research and engineering applications of heat transfer optimization in functionally graded materials. Full article

The integration of Foamed Concrete (FC) into 3D Concrete Printing (3DCP) processes facilitates the design of energy-efficient building envelopes. However, strategies for optimizing material porosity and printing topology to balance winter and summer performance remain underexplored. This study presents a 2D numerical thermal analysis of an innovative 3D-printed building envelope block characterized by sinusoidal internal partitions. Through a parametric variation in porosity (ranging from 10% to 50%) and internal geometry (amplitude and period of the partitions), 45 distinct configurations were simulated. Performance was evaluated by calculating the steady-state thermal transmittance (U) and the periodic thermal transmittance (Y_ie) under dynamic climatic conditions. The results demonstrate that porosity is the governing parameter; increasing porosity from 10% to 50% reduces U by 31% and, contrary to traditional assumptions for massive structures, also improves Y_ie by 12.3%. These outcomes are physically driven by the drastic reduction in thermal conductivity, which overcompensates for the loss of thermal mass, leading to a net reduction in overall thermal diffusivity. While internal topology plays a secondary role, its optimization allows for fine-tuning dynamic damping without compromising insulation. The study confirms that 3D printing with foamed concrete enables the overcoming of the traditional trade-off between insulation and thermal inertia. High-porosity configurations (50%) with optimized internal topology emerge as the most effective solution, simultaneously guaranteeing beneficial steady-state and dynamic thermal performance for sustainable buildings. Full article

This study proposes a systematic methodology to evaluate the energy flexibility and operational performance of air-conditioning systems (ACSs) in residential buildings, leveraging the passive thermal storage capacity of building thermal mass through indoor temperature setpoint adjustment. A comparative analysis was conducted between inverter-controlled and intermittent on-off air conditioners under a baseline indoor temperature of 24 °C. Two additional temperature setpoint scenarios (26 °C and 28 °C) were tested to quantify variations in the building’s electricity consumption demand. To characterize the dynamic thermal response across different floor levels, ground-floor, middle-floor, and top-floor apartments were investigated in a three-story residential building, enabling a controlled, floor-level comparison under identical control logic and climatic conditions. Dymola simulation software was employed to model and calculate ACS energy consumption and energy flexibility under the three temperature setpoint conditions (24 °C, 26 °C, and 28 °C). Results indicate that a strategy of scheduled ACS shutdown and automatic restart, enabled by the thermal inertia capacity of building thermal mass, effectively enhances ACS energy flexibility. Specifically, adjusting the zone temperature setpoint reduced the total ACS load by approximately 40% in two hours of a demand response event. This temperature setpoint adjustment strategy demonstrates significant potential to mitigate grid peak-load demand without compromising indoor thermal comfort and requiring additional building retrofitting investments. The findings provide a technical basis for optimizing residential ACS operation and promoting demand-side management in power systems. Full article

This study presents an integrated engineering methodology aligned with the planning phase of the ISO 50001:2018 (Energy Management Systems—Requirements with Guidance for Use. International Organization for Standardization (ISO): Geneva, Switzerland, 2018) energy management standard for the design, sizing, and assessment of a solar thermal system applied to domestic hot water production in a medium-scale hotel building. The proposed framework focuses on the energy review stage of ISO 50001, incorporating site-specific climatic assessment, spatial layout optimization, structural feasibility analysis, and energy performance evaluation to support informed technology selection and system viability. Thermal performance is assessed using real operational data from the case study, complemented by a data-driven multivariable regression-based energy performance indicator (EnPI) that relates electricity consumption to cooling degree days and room occupancy. This regression model, developed in accordance with ISO 50001 recommendations, enables transparent monitoring of energy performance under real operating conditions without relying on black-box predictive techniques. Material selection criteria for absorber plates, heat-transfer components, transparent covers, and insulation layers are discussed to support both initial efficiency and performance stability under site-specific climatic conditions. In addition, an indicative and qualitative analysis of material-dependent performance evolution is introduced to support comparative decision-making, without implying quantitative lifetime prediction. Structural feasibility of the collector support system is examined through finite-element simulations under combined gravitational and wind loads, providing illustrative verification of stress distribution under representative operating conditions. The installed system delivers an annual thermal energy contribution of 8468 kWh, resulting in an estimated reduction of 7.79 t of CO${}_2$ emissions per year. Economic indicators suggest a short payback period and a favorable internal rate of return, which should be interpreted as order-of-magnitude estimates within the planning scope of the methodology. Overall, the proposed methodology provides a replicable and multidisciplinary planning-phase framework aligned with ISO 50001 for the design and assessment of solar thermal systems in medium-scale buildings under real operating conditions. Full article

Building-integrated photovoltaics (BIPVs) can substantially increase renewable electricity utilization in buildings under China’s “dual-carbon” targets. Yet, fixed photovoltaic (FPV) windows cannot respond to seasonal and diurnal variations in solar altitude and azimuth, limiting their ability to jointly optimize power generation, shading, and solar heat gains. This study proposes a shading-type sun-tracking photovoltaic (STPV) window for south-facing residential glazing and evaluates its annual performance for a detached house in Hangzhou (hot-summer and cold-winter climate). Representative clear-sky field measurements were combined with annual EnergyPlus simulations to quantify PV yield, radiation regulation, and impacts on air-conditioning (HVAC) and lighting electricity use. STPV windows deliver an additional annual PV gain of ~336 kWh relative to FPV windows, mainly during transition seasons and around summer noon. Using the no-shading case as the baseline (4967 kWh/year), FPV windows reduce total electricity use to 4010 kWh (−957 kWh), while STPV windows further reduce it to 3281 kWh (−1686 kWh), providing an extra −729 kWh versus FPV. Accounting for PV generation, the annual net electricity demand decreases from 2929 kWh (FPV) to 1864 kWh (STPV), i.e., −1065 kWh (36.4%). These results highlight the synergy of tracking-enabled generation enhancement and cooling-load reduction for façade PV in Hangzhou-like climates. Full article

In response to growing energy demands and climate pressure in hot regions, this study presents an integrated techno-economic and environmental assessment of building envelope retrofit strategies aimed at facilitating the transition of existing buildings toward Nearly Zero-Energy Building (NZEB) targets. Three advanced retrofit solutions—radiative coatings (RC), glazing-integrated photovoltaic (GIPV) systems, and solar green roofs—are evaluated using a validated building performance simulation framework across four representative climatic zones in Egypt. The results demonstrate that radiative coatings provide the most favorable economic performance, achieving return on investment (ROI) values between 12.37% and 21.72% and payback periods ranging from 3.5 to 6.2 years. Solar green roofs and GIPV systems deliver substantial reductions in annual electricity consumption and operational CO₂ emissions, with their performance strongly influenced by climatic conditions and cooling demand intensity. Solar green roofs achieve ROI values of 5.15–6.54% with payback periods of 11.7–14.9 years, while GIPV systems yield ROI values of 4.0–5.24% and payback periods between 14.6 and 17.1 years. Overall, the findings indicate that climate-adapted envelope retrofit strategies can significantly enhance building energy performance while providing measurable economic and environmental benefits. This study offers a robust, data-driven basis for retrofit prioritization and policy formulation in hot regions. Full article

In high-density urban environments, residential design often faces a conflict between maximizing landscape access and maintaining energy-oriented compactness. This study proposes a target-based visibility analysis framework to optimize high-rise forms under strict performance constraints. Utilizing a Quad-mesh reconstruction strategy and Inverse Targeted Ray-Casting, the method accurately quantifies visibility via the cumulative Landscape Visible Surface (LVS) on the target building and Viewpoint-Specific Surface Visibility Rate (R_v) for precise verification against specific landscape targets. The framework is applied to evaluate three morphological prototypes: Compact Tower, Dispersed Tower, and Slab–Tower Hybrid. Quantitative simulations identified the Slab–Tower Hybrid as the optimal solution, demonstrating superior “Visual Morphological Efficiency.” While maintaining a moderate Shape Coefficient (SC = 0.326) to satisfy energy standards, the Hybrid achieved a cumulative Park-View LVS approximately 1.8 times that of the Compact Tower. Furthermore, environmental simulations indicated the Hybrid fosters stable wind environments (0.4–0.7 m/s) and equitable sunlight distribution. The research concluded that through differentiated massing, high-rise architecture can achieve a synergistic balance between visual openness and physical compactness, transforming view analysis from a passive check into an active design driver. Full article

School buildings are important in terms of energy performance, and their energy demand varies significantly across different climates. Early design decisions strongly influence this demand; however, building energy simulations are computationally intensive and limit rapid evaluation of alternative design options at scale. This study proposes a machine learning-based surrogate modeling framework to support early design energy assessment of school buildings across Türkiye’s six TS 825 climatic regions. A comprehensive design space is defined by varying key parameters, including building shape, orientation, window-to-wall ratio, shading, glazing systems, and insulation alternatives. Representative design configurations are generated using stratified random sampling, and then simulated in EnergyPlus, resulting in a dataset of 30,000 samples. Random Forest, Support Vector Regression, and Multilayer Perceptron models are developed within a multi-output regression framework to predict annual heating and cooling energy demand across climatic regions. The models achieve high predictive accuracy and consistent generalization, with test R² values exceeding 0.93, while exhibiting performance differences among the evaluated algorithms. Feature importance analysis identifies window-to-wall ratio and glazing-related parameters as the most influential early design variables. Overall, the results demonstrate that machine learning-based surrogate models can substantially reduce computational effort while providing reliable, climate-responsive support for early design decision-making. Full article

This study investigates the use of smart material technologies, particularly smart coatings, to enhance thermal comfort, reduce energy consumption, and lower carbon emissions in residential buildings in Karbala, Iraq, a city with a hot, dry climate. Using DesignBuilder and EnergyPlus simulations, the performance of cool reflective coatings and thermal coatings was compared across various temperature conditions. Results showed that smart coatings significantly reduced indoor temperatures, cooling and heating loads, and overall energy use. The W&R(RS) and W&R(TS) models consistently outperformed their counterparts, offering improved thermal stability and comfort. Life-cycle analysis revealed that the operational phase accounted for the majority (52.6%) of carbon emissions, highlighting the importance of early-stage integration of smart materials. Overall, the findings underscore the potential of smart coatings to enhance energy efficiency and environmental performance in hot-climate architecture. Full article

In multirotor unmanned aerial vehicle (UAV) GNSS/INS integrated navigation systems, a single filter such as the extended Kalman filter (EKF) or the error-state extended Kalman filter (ESKF) is commonly adopted. However, both methods have inherent performance limitations. The EKF suffers from significant linearization errors in highly nonlinear flight scenarios, leading to degraded estimation accuracy. Although ESKF achieves higher precision during steady flight, its model assumptions may no longer strictly hold during aggressive maneuvers, causing performance degradation in complex flight missions. To address the limitations of using a single filter, this study proposes a dynamic filter selection strategy under the interaction multi-filter (IMF) framework. The approach builds on the interactive multiple model (IMM) method and establishes a cooperative mechanism between EKF and ESKF. By computing the filter likelihoods at each time step and updating the probability switching matrix, the framework adaptively selects the optimal filter based on the current flight conditions. Simulation results demonstrate that the proposed IMF-based strategy effectively avoids the performance bottlenecks of individual filters. In highly nonlinear environments, it reduces linearization errors and suppresses divergence trends; compared with traditional ESKF, the proposed algorithm 3D RMSE is reduced by 57.2%, compared with the adaptive robust EKF (AREKF), the proposed approach reduces positioning errors by up to 21.3%. The results confirm that IMF-based adaptive switching between EKF and ESKF yields a robust, high-precision solution for UAV navigation in complex operational scenarios. Full article

Facing 2050 climate uncertainties, enhancing building resilience is critical3. This study addresses the “black-box” and interoperability gaps in traditional multi-objective optimization (MOO) by proposing an intelligent framework based on the Model Context Protocol (MCP) and Large Language Models (LLMs). Unlike stochastic algorithms, the MCP-LLM framework uses semantic reasoning to bridge building performance simulation (BPS) engines like EnergyPlus 24.2.0 and Radiance 5.4. Through a case study of an educational building in Taiwan under the IPCC RCP 8.5 scenario, results show the framework improves optimization convergence speed by 55% compared to NSGA-II. The optimized shading system reduced peak cooling loads by 18.5% and annual EUI by 12.3%, while maintaining uncomfortable glare (DGP > 0.35) below 5% of annual hours. Crucially, the system provides explainable design logic via natural language, marking a shift from automated simulation to human-machine collaboration. This framework offers a transparent decision-support tool for forward-looking climate adaptation in educational environments. Full article