Energy and Buildings最新文献_第2页

Applicability of the safe and sustainable by design framework to thermochemical energy storage materials in buildings: A readiness assessment 安全和可持续设计框架对建筑热化学储能材料的适用性：准备评估

IF 7.1 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2026-04-15 Epub Date: 2026-02-11 DOI: 10.1016/j.enbuild.2026.117146

Dinh Linh Le , Roberta Salomone , Teresa Maria Gulotta , Patrizia Primerano , Giuseppe Saija

Thermochemical energy storage (TCES) can support decarbonising the building sector by offering high storage density and the potential for long-duration retention with low standing losses; it can be charged using low-grade solar or waste heat and discharged on demand for peak shaving and renewable integration, though realised benefits depend on material stability and system design. Because units are installed close to occupied buildings, occupant and worker safety is a primary criterion; material selection must therefore look beyond energy metrics to evaluate safety and sustainability. The Safe and Sustainable by Design (SSbD) framework provides a structured lens for such assessment. This study evaluates the applicability of SSbD to reaction-based TCES materials for buildings. A review of reviews in Scopus identifies 11 reviews and compiles 50 materials. Safety and hazard data are gathered from regulatory sources (ECHA, PubChem) and supplier safety data sheets. Life cycle inventories are screened via the Global Life Cycle Assessment Data Access network and supplemented by literature-based datasets and transparently documented proxies. Cost data are derived from supplier catalogues, market quotations, and literature. Readiness for SSbD assessment spans: 8/50 very high (e.g., CaCl₂·6H₂O, MgSO₄·7H₂O), 5/50 high (e.g., LiCl·H₂O, MgCl₂·6H₂O), 10/50 medium (e.g., Na₂S·5H₂O, SrBr₂·6H₂O), 3/50 low (MgSO₄·6H₂O, FeCl₂·2H₂O, CuCl₂·H₂O), and 24/50 not ready yet (mainly minor hydrates and all ammonia adducts). Cross-cutting gaps include PMT/vPvM indicators, selected chronic aquatic and endocrine endpoints, and basic occupational safety and health descriptors. The results provide an actionable evidence base for prioritising safer, sustainability-aligned TCES materials to support energy-efficient and climate-resilient buildings.

热化学储能（TCES）可以通过提供高存储密度和低站立损失的长期保留潜力来支持建筑部门的脱碳；它可以使用低品位的太阳能或废热充电，并根据调峰和可再生能源整合的需求排放，尽管实现的效益取决于材料稳定性和系统设计。由于机组安装在被占用建筑物附近，因此居住者和工人的安全是首要标准；因此，材料选择必须超越能源指标来评估安全性和可持续性。安全与可持续设计（SSbD）框架为这种评估提供了一个结构化的视角。本研究评估了SSbD对反应基TCES建筑材料的适用性。对Scopus上的评论进行审查，确定了11篇评论并汇编了50篇材料。安全和危害数据是从监管来源（ECHA, PubChem）和供应商安全数据表收集的。生命周期清单通过全球生命周期评估数据访问网络进行筛选，并辅以基于文献的数据集和透明记录的代理。成本数据来源于供应商目录、市场报价和文献。SSbD评估的准备程度范围为：8/50非常高（例如CaCl2·6H2O， MgSO4·7H2O）， 5/50高（例如LiCl·H2O， MgCl2·6H2O）， 10/50中等（例如Na2S·5H2O， SrBr2·6H2O）， 3/50低（MgSO4·6H2O, FeCl2·2H2O, CuCl2·H2O）， 24/50尚未准备好（主要是少量水合物和所有氨加合物）。跨领域差距包括PMT/vPvM指标、选定的慢性水生和内分泌终点以及基本职业安全和健康描述符。研究结果为优先考虑更安全、符合可持续性的TCES材料提供了可操作的证据基础，以支持节能和气候适应型建筑。

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引用次数: 0

Computationally efficient smart building energy management via deep reinforcement learning-enhanced model predictive control 基于深度强化学习增强模型预测控制的高效计算智能建筑能源管理

IF 7.1 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2026-04-15 Epub Date: 2026-02-09 DOI: 10.1016/j.enbuild.2026.117128

Bo Li, Gangquan Si, Minglin Xu, Detao Fan, Qianyue Wang, Xin Wang

Model predictive control (MPC) is a powerful strategy for optimizing building energy management, but its high computational burden hinders its deployment on resource-constrained hardware. To address this challenge, this paper presents a novel hierarchical control framework that synergizes MPC with deep reinforcement learning (DRL) to navigate the trade-off between control performance and computational burden. Within this framework, a low-level MPC controller is responsible for precise building energy management with the objective of maximizing energy efficiency and ensuring user thermal comfort, while a high-level DRL agent adaptively tunes the MPC’s meta-parameters to reduce unnecessary computational burden without significantly degrading performance. To implement this framework, an adaptive meta-parameter MPC algorithm is developed based on expert-guided proximal policy optimization by using an expert demonstrator to enhance the DRL training efficiency. Simulation results show that the proposed algorithm significantly outperforms standalone MPC and DRL methods. Compared to a fixed-long-horizon MPC, the proposed method reduces the actual computation time by 75.8% with only a marginal 2.6% increase in operational cost. Furthermore, by coordinately adjusting both the recomputation frequency and prediction horizon of the MPC controller, the framework achieves a more favorable trade-off between control performance and computational efficiency than a standard event-triggered MPC. Finally, robustness analyses confirm that the DRL agent learns an intelligent policy that adaptively intensifies computational effort to mitigate the impact of prediction errors and strategically allocates resources in response to price volatility, thereby maintaining high performance and efficiency even under extreme conditions.

模型预测控制（MPC）是优化建筑能源管理的一种有效策略，但其高昂的计算负担阻碍了其在资源受限的硬件上的部署。为了解决这一挑战，本文提出了一种新的分层控制框架，该框架将MPC与深度强化学习（DRL）协同起来，在控制性能和计算负担之间进行权衡。在这个框架内，低级MPC控制器负责精确的建筑能源管理，目标是最大限度地提高能源效率并确保用户热舒适，而高级DRL代理自适应调整MPC的元参数，以减少不必要的计算负担，而不会显著降低性能。为了实现该框架，利用专家演示器，提出了一种基于专家引导的近端策略优化的自适应元参数MPC算法，以提高DRL的训练效率。仿真结果表明，该算法明显优于独立的MPC和DRL方法。与固定的长视距MPC相比，该方法将实际计算时间缩短了75.8%，而运行成本仅增加了2.6%。此外，通过协调调整MPC控制器的重计算频率和预测范围，该框架在控制性能和计算效率之间实现了比标准事件触发MPC更有利的权衡。最后，鲁棒性分析证实，DRL代理学习了一种智能策略，该策略可以自适应地加强计算工作量，以减轻预测错误的影响，并根据价格波动有策略地分配资源，从而即使在极端条件下也能保持高性能和高效率。

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引用次数: 0

Optimizing Ventilation Performance of a Solar Chimney with Transparent Insert: A Synergistic Study on Depth, Height, and Configurational Parameters 透明嵌套太阳能烟囱的通风性能优化：深度、高度和配置参数的协同研究

IF 7.1 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2026-04-15 Epub Date: 2026-02-10 DOI: 10.1016/j.enbuild.2026.117137

Yuxing Yan, Shenglan Jing, Yonggang Lei, Yang Guo, Tianci Liang, Jupeng Xie

To address the inherent limitation of traditional solar chimneys—where ventilation efficiency is constrained by their heavy reliance on single-sided heating—this study explores the performance enhancement potential of integrating transparent glass inserts. Employing a synergistic approach combining experimental tests and Computational Fluid Dynamics (CFD) simulations, the research clarifies the nonlinear coupling mechanism between the insert-induced efficiency improvement and key geometric parameters (i.e., chimney depth and height).

In the experimental phase, an electrically heated aluminum plate was used as a controllable heat source to avoid external weather interference, with benchmark tests conducted on ventilation performance under three depths (0.2, 0.3, 0.4 m) with/without inserted plates at constant power. In CFD simulations, 500 W/m² incident solar radiation was applied to the glass outer surface as a boundary condition. Extended simulations were further performed to systematically investigate the impacts of chimney height (1.0–2.2 m), depth-to-height ratio and plate length ratio (λ) on ventilation performance.

The results demonstrate that the integration of transparent inserts double the effective plume area, thereby reducing flow resistance and significantly enhancing the mass flow rate. While, the ventilation rate increases monotonically with both chimney depth and height, but the relative efficiency increment exhibits a distinct nonlinear characteristic, with an optimal depth-to-height ratio of 0.1–0.3. Additionally, optimizing λ to 0.8 effectively the formation of bottom recirculation vortices, leading to a further 7% improvement in ventilation rate. This study not only provides actionable design optimization guidelines for solar chimney systems but also reveals the intrinsic coupling mechanism among geometric parameters, built-in components, and flow field structures, thereby laying a solid theoretical foundation for the development of high-performance passive ventilation technologies in buildings.

为了解决传统太阳能烟囱的固有局限性，即通风效率受到严重依赖单面加热的限制，本研究探索了集成透明玻璃嵌套的性能增强潜力。采用实验测试与计算流体力学（CFD）模拟相结合的协同方法，阐明了插入效率提高与关键几何参数（烟囱深度和高度）之间的非线性耦合机制。在实验阶段，采用电热铝板作为可控热源，避免外界天气干扰，在恒定功率下，对有无插板在三种深度（0.2、0.3、0.4 m）下的通风性能进行基准测试。在CFD模拟中，在玻璃外表面施加500 W/m2的入射太阳辐射作为边界条件。进一步进行了扩展模拟，系统地研究了烟囱高度（1.0-2.2 m）、深高比和板长比（λ）对通风性能的影响。结果表明，透明插片的集成使有效羽流面积增加了一倍，从而降低了流动阻力，显著提高了质量流量。通风量随烟囱深度和烟囱高度单调增加，但相对效率增量表现出明显的非线性特征，最佳深高比为0.1 ~ 0.3。此外，优化λ至0.8有效地形成底部再循环涡，导致通风率进一步提高7%。本研究不仅为太阳能烟囱系统提供了可操作的设计优化指导，而且揭示了几何参数、内建构件、流场结构之间的内在耦合机制，为建筑高性能被动通风技术的发展奠定了坚实的理论基础。

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引用次数: 0

Reduction of heating energy demand by combining IR heaters and IR reflective walls: An experimental study 通过结合红外加热器和红外反射墙减少加热能源需求：一项实验研究

IF 7.1 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2026-04-15 Epub Date: 2026-02-05 DOI: 10.1016/j.enbuild.2026.117112

Lukas Anselm Wille , Björn Schiricke , Kai Gehrke , Tobias Dehne , Bernhard Hoffschmidt

In this study, we build upon previous simulation research that advocates the use of infrared (IR) heaters in conjunction with IR reflective interior walls to meet heating demand in buildings. This combination allows the walls to reflect the heat emitted by the IR heaters back to the occupants in a room, rather than absorbing the radiation. As a result, the radiant temperature increases and the air temperature can be lowered in order to maintain constant thermal comfort and to reduce heat loss through the building envelope. We conducted experiments in a climate chamber to isolate the effects of four factors on thermal comfort: the heating power of IR heaters, the IR emittance of the interior walls, the interior wall surface temperature, and the air temperature. The emittance was modified by applying an increasing number of adhesive aluminium foil stripes. Heat conduction through the wall to the outside is not part of this study. To minimize the number of required experiments, we employed a Central Composite Design, from which we derived a response surface function. The experimental results confirm a correlation between wall emittance and occupant thermal comfort in a room, particularly at higher IR heater power levels. The Predicted Mean Vote (PMV) value increases at lower wall emittance (corresponding to higher radiant temperatures), highlighting the potential for energy savings through reduced air temperatures. However, the observed impact of low emittance surfaces on the PMV is less pronounced than previously estimated in simulation studies.

在本研究中，我们在先前的模拟研究的基础上，提倡使用红外加热器与红外反射内墙相结合，以满足建筑物的供暖需求。这种组合允许墙壁将红外加热器发出的热量反射回房间内的居住者，而不是吸收辐射。因此，辐射温度增加，空气温度可以降低，以保持恒定的热舒适，并减少通过建筑围护结构的热量损失。在气候室内进行了红外加热器加热功率、内墙红外发射率、内墙表面温度和空气温度四个因素对热舒适的影响实验。通过增加粘贴铝箔条纹的数量来改变发射度。通过墙壁到外部的热传导不是本研究的一部分。为了尽量减少所需实验的数量，我们采用了中心复合设计，并从中得出了响应面函数。实验结果证实了墙体发射度与室内人员热舒适之间的相关性，特别是在较高的红外加热器功率水平下。预测平均投票（PMV）值在较低的墙壁发射度（对应于较高的辐射温度）下增加，突出了通过降低空气温度节省能源的潜力。然而，观测到的低发射率表面对PMV的影响不如以前在模拟研究中估计的那么明显。

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引用次数: 0

Climate change impact on envelope retrofit effectiveness: energy and carbon performance of Italian residential and office buildings today vs. 2050 气候变化对围护结构改造效果的影响：今天与2050年意大利住宅和办公楼的能源和碳性能

IF 7.1 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2026-04-15 Epub Date: 2026-02-12 DOI: 10.1016/j.enbuild.2026.117145

Francesca Villano , Fabrizio Ascione , Tomasz Cholewa , Rosa Francesca De Masi , Gerardo Maria Mauro , Silvia Ruggiero

Buildings significantly contribute to global energy consumption and CO₂ emissions, and their performance is increasingly challenged by rising cooling demands under climate change. While many studies assess envelope retrofit measures, most focus on a single building use. This study addresses this gap through a comparative analysis across building typologies, uses, and climatic conditions. The effects of climate change and envelope retrofit strategies on thermal energy demand (TED) and CO₂ emissions are evaluated for four representative Italian building typologies—apartment block, multifamily building, terraced house, and single-family house—considering residential and office uses, standard and high internal loads, and current and 2050 climate conditions. Dynamic simulations are performed using EnergyPlus for four Italian climatic zones. Several retrofit options are analyzed, including insulation measures, window replacement, cool roofs, and a global retrofit. The global retrofit provides the largest benefits, reducing TED and CO₂ emissions by up to 65% and 60% under current conditions, with a slight decrease in effectiveness (2–4%) toward 2050. Office buildings with high internal loads show smaller improvements than residential ones. Compact buildings exhibit greater climate resilience, whereas less compact typologies experience larger performance declines. Cool roofs are effective in mitigating cooling-related emissions under warmer climates, though their impact is limited in high-load office scenarios. Results highlight the need for adaptive and climate-resilient retrofit strategies in Mediterranean contexts.

建筑对全球能源消耗和二氧化碳排放做出了重大贡献，在气候变化的背景下，其性能受到日益增长的冷却需求的挑战。虽然许多研究评估了围护结构改造措施，但大多数研究都集中在单一建筑的使用上。本研究通过对建筑类型、用途和气候条件的比较分析来解决这一差距。气候变化和围护结构改造策略对热能需求（TED）和二氧化碳排放的影响评估了四种具有代表性的意大利建筑类型——公寓楼、多户建筑、排屋和单户住宅——考虑到住宅和办公用途、标准和高内部负荷，以及当前和2050年的气候条件。使用EnergyPlus对意大利的四个气候带进行了动态模拟。分析了几种改造方案，包括隔热措施、窗户更换、冷却屋顶和全球改造。全球改造提供了最大的效益，在目前的条件下，减少了高达65%和60%的TED和CO2排放，到2050年的有效性略有下降（2-4%）。内部负荷较大的办公楼的改善幅度小于住宅。紧凑型建筑表现出更强的气候适应能力，而紧凑型建筑的性能下降幅度更大。在气候变暖的情况下，凉爽的屋顶可以有效地减少与冷却有关的排放，尽管在高负荷的办公环境下，它们的影响有限。研究结果强调了地中海环境下适应性和气候适应性改造战略的必要性。

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引用次数: 0

A study on the influence mechanism of residents’ willingness to participate in the carbon generalised system of preferences from a configuration perspective 配置视角下居民碳广义偏好体系参与意愿的影响机制研究

IF 7.1 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2026-04-15 Epub Date: 2026-02-06 DOI: 10.1016/j.enbuild.2026.117105

Liu Xingmin , Zhang Xiaoxue , Qin Beibei , Ma Yinghao , Liu Jingrui

The Carbon Generalised System of Preferences (CGSP) is an institutional innovation strategy designed to promote low-carbon behaviours at the individual level. China’s CGSP remains in its embryonic stages of development. Although the CGSP has been launched in several Chinese cities, the level of public participation has not yet met expectations, thus affecting its sustainable operations. Individual willingness to participate in CGSP is a critical factor determining the effective implementation of this approach. This study applies grounded theory to identify factors influencing the desire to participate in CGSP and constructs a theoretical model of these influencing factors. Subsequently, the fuzzy-set qualitative comparative analysis (fsQCA) method is employed to examine the configurational effects of multiple factors and their causal mechanisms. Research indicates that the elements impacting residents’ willingness to participate in CGSP are complex, encompassing social norms, incentives, psychological cognition, self-regulation, demographic characteristics, and the convenience and reliability of CGSP platforms. The fsQCA analysis identified four pathways indicating a high willingness to participate in CGSP among residents, along with three pathways reflecting a low willingness to participate. Based on these findings, this paper analysed which combinations of influencing factors are more effective in furthering residents’ willingness to participate in CGSP. This study evaluates the multiple concurrent factors and causal mechanisms underlying residents’ intentions to engage in CGSP from a configuration perspective. It enhances industry decision-makers’ understanding of such behavioural intentions and offers practical recommendations for fostering CGSP.

碳普遍优惠制度（CGSP）是一项制度创新战略，旨在促进个人层面的低碳行为。中国的CGSP仍处于萌芽阶段。虽然CGSP已经在中国的几个城市启动，但公众参与的水平还没有达到预期，从而影响了它的可持续运行。个人参与CGSP的意愿是决定该方法有效实施的关键因素。本研究运用扎根理论识别影响CGSP参与意愿的因素，并构建这些影响因素的理论模型。随后，采用模糊集定性比较分析（fsQCA）方法对多因素的配置效应及其因果机制进行了研究。研究表明，影响居民参与CGSP意愿的因素是复杂的，包括社会规范、激励机制、心理认知、自我调节、人口统计学特征以及CGSP平台的便利性和可靠性。fsQCA分析确定了居民中参与CGSP的高意愿的四条途径，以及反映低意愿的三条途径。在此基础上，本文分析了哪些影响因素的组合更有效地促进了居民参与社区服务计划的意愿。本研究从配置的角度，评估了居民参与CGSP意愿的多重并发因素及其因果机制。它提高了行业决策者对这种行为意图的理解，并为促进企业综合服务计划提供了实用建议。

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引用次数: 0

The role and CO2 emission reduction cost of battery energy storage in fully integrated, optimally controlled micro energy communities 电池储能在完全集成、最优控制的微能源群落中的作用和CO2减排成本

IF 7.1 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2026-04-15 Epub Date: 2026-02-09 DOI: 10.1016/j.enbuild.2026.117123

Lucas Verleyen , Lieve Helsen

Battery Energy Storage (BES) is often seen as an attractive component in residential (district) energy systems. Typically, BES is considered the sole source of flexibility. However, thermal energy systems inherently offer significant flexibility through the thermal capacity of the buildings and hydronic systems. Therefore, this paper presents a fully integrated approach that combines all relevant energy services (space heating, domestic hot water and electricity for appliances), detailed building models representing a flexible demand side, and proper hydronic and electrical connections between all components into one non-linear physics-based energy system model. An optimal controller acts as the system integrator, fully exploiting the inherent system flexibility and leveraging synergies between heat and electricity. The proposed method is applied to a Micro Energy Community (MEC) under Belgian boundary conditions. A comparative analysis of 33 energy system layouts is conducted to investigate the role and quantify the CO₂ emission reduction cost of BES in fully integrated MECs optimised for minimal CO₂ emissions. The analysis demonstrates that neglecting thermal system flexibility leads to biased results. The most cost-effective system for emission reduction is a scenario with a collective heat pump, without BES, and where heat and electricity are shared. This system reduces annual emissions by 11.6 tonnes at the cost of 215 EUR/tonne. A collective BES further reduces emissions by 0.1 tonnes, but at a significantly higher cost of 5,430 EUR/tonne. Therefore, BES is not cost-effective for emission reduction in buildings. However, this conclusion may change when considering grid support or applying other policy frameworks.

电池储能（BES）通常被视为住宅（地区）能源系统中一个有吸引力的组成部分。通常，BES被认为是灵活性的唯一来源。然而，热能系统本身通过建筑物和水力系统的热容量提供了显著的灵活性。因此，本文提出了一种完全集成的方法，将所有相关的能源服务（空间供暖，家庭热水和电器用电），代表灵活需求端的详细建筑模型，以及所有组件之间适当的水力和电气连接结合到一个基于非线性物理的能源系统模型中。最优控制器作为系统集成商，充分利用系统固有的灵活性，并利用热电之间的协同效应。将该方法应用于比利时边界条件下的微能源共同体（MEC）。通过对33种能源系统布局的对比分析，探讨了BES在以最小二氧化碳排放为优化目标的全集成mec中的作用，并量化了其二氧化碳减排成本。分析表明，忽略热系统的灵活性会导致结果偏差。最具成本效益的减排系统是使用集体热泵，不使用BES，并共享热量和电力的方案。该系统每年减少11.6吨的排放量，每吨成本为215欧元。集体BES进一步减少了0.1吨的排放量，但每吨5,430欧元的成本要高得多。因此，BES对于建筑物的减排并不具有成本效益。然而，在考虑网格支持或应用其他策略框架时，这个结论可能会改变。

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引用次数: 0

Improvement strategies based on airflow characteristic in a row-based cooling data center 基于行式冷却数据中心气流特性的改进策略

IF 7.1 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2026-04-15 Epub Date: 2026-02-09 DOI: 10.1016/j.enbuild.2026.117136

Yingying Lyu , Xuelian Bai , Ligang Wang , Yating Wang , Chaoqiang Jin

The short airflow paths of row-based cooling systems can enhance cooling efficiency for data centers (DCs). However, the placement of row-based air conditioning units (ACUs) close to the racks significantly increases the airflow velocity in the aisles. Meanwhile, different power modules share one hot aisle, which is easy to occur the hot exhaust air mixing problem. Existing researches neglect the airflow interaction, which leads to the return air temperatures inaccurately reflecting the cooling demand of each module. To address this issue, this study investigates the interaction phenomena within the row-based cooling system, through the combination of experimental observations and numerical simulations. To evaluate the interaction, a new index ΔT, defined as the return air temperature difference of in-row ACUs between different power modules, was presented. Then the effect of varying the shared hot aisle width on the interaction under different power ratios are analyzed. The results indicate that the airflow interaction intensifies with power ratios, and there exists a proper hot aisle width at different power ratios. To further relieve the interaction, improvement strategies involving airflow deflectors, vertical isolation, and horizontal isolation were proposed. With these strategies implemented, the airflow becomes more organized in the hot aisle, and ΔT increases from 0.75 °C to 1.06 °C, 1.64 °C, and 1.66 °C, respectively. Finally, installing a vertical curtain in the shared hot aisle central and sealing the top effectively alleviated the hot exhaust air interaction in higher power modules scenarios, with ΔT increased from 0.86 °C to 1.578 °C.

排式冷却系统的短气流路径可以提高数据中心的冷却效率。然而，排式空调机组（acu）靠近机架的位置显著增加了通道内的气流速度。同时，不同的电源模块共用一个热通道，容易出现热排气混流问题。现有研究忽略了气流相互作用，导致回风温度不能准确反映各模块的冷却需求。为了解决这一问题，本研究通过实验观察和数值模拟相结合的方法研究了排基冷却系统内部的相互作用现象。为了评估这种相互作用，提出了一个新的指标ΔT，定义为不同功率模块间的排acu回风温差。然后分析了不同功率比下共享热通道宽度对相互作用的影响。结果表明：气流相互作用随功率比的增大而加剧，且在不同功率比下存在合适的热通道宽度；为了进一步缓解相互作用，提出了包括气流偏转、垂直隔离和水平隔离在内的改进策略。随着这些策略的实施，热通道中的气流变得更加有组织，ΔT分别从0.75°C增加到1.06°C， 1.64°C和1.66°C。最后，在共享热通道中央安装垂直幕帘并密封顶部，有效缓解了高功率模块场景下的热排气相互作用，ΔT从0.86°C提高到1.578°C。

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引用次数: 0

Predicting and alleviating urban heat stress for early adolescents: an integrated environmental and physiological study 预测和缓解早期青少年的城市热应激：一项综合环境和生理研究

IF 7.1 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2026-04-15 Epub Date: 2026-02-10 DOI: 10.1016/j.enbuild.2026.117130

Jie Wu , Shimin Li , Hongtao Xu , Mincheng Jiang , Ye Zhao , Tukuan Huang

With the increasing frequency of extreme heat events and the intensification of the urban heat island effect, thermal safety for children in outdoor urban environments has become a critical concern. Traditional heat stress indicators have limited applicability for early adolescents, leading to ambiguous predictions. Using experimental data collected from 36 junior high school students (aged 12 ± 1 years) in Nanning, China, from June to August 2024, we introduced an enhanced two-node model integrated with a genetic algorithm to predict and mitigate heat stress. Through real-time monitoring of core/skin temperatures and microclimate data via wireless sensors and a mobile thermal comfort device, four key physiological parameters in the model were optimized. The optimized model improved the predictive accuracy for group trends in skin and core temperatures, reducing the RMSE by 76.07% and 75.86%, respectively. Furthermore, by incorporating six spatial scenarios with different shading conditions and underlying surfaces into ENVI-met, the model quantitatively revealed significant effects of various environmental factors on the body temperature changes of early adolescents (p < 0.05). This study lays a theoretical foundation for evidence-based child-friendly design strategies and provides scientific support for protecting adolescents’ health in the context of climate change.

随着极端高温事件的频繁发生和城市热岛效应的加剧，儿童在城市室外环境中的热安全已成为人们关注的焦点。传统的热应激指标对早期青少年的适用性有限，导致预测不明确。利用2024年6月至8月对中国南宁市36名（12±1岁）初中生的实验数据，提出了一种结合遗传算法的增强型双节点模型来预测和缓解热应激。通过无线传感器和移动热舒适装置实时监测核心/皮肤温度和小气候数据，优化模型中的四个关键生理参数。优化后的模型提高了皮肤和核心温度群体趋势的预测精度，RMSE分别降低了76.07%和75.86%。此外，通过将6种不同遮阳条件和下垫面的空间情景纳入ENVI-met，该模型定量揭示了不同环境因素对早期青少年体温变化的显著影响（p < 0.05）。本研究为基于证据的儿童友好型设计策略提供理论基础，为气候变化背景下保护青少年健康提供科学支持。

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引用次数: 0

A dynamic time warping-enhanced transfer learning framework for cooling load prediction in data-scarce buildings: a multi-building case study 一种用于数据稀缺建筑冷负荷预测的动态时间翘曲增强迁移学习框架：一个多建筑案例研究

IF 7.1 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2026-04-15 Epub Date: 2026-02-13 DOI: 10.1016/j.enbuild.2026.117148

Jiakai Liu , Yongbao Chen , Zhe Chen

Improving building energy efficiency and optimizing building energy management are critical steps toward achieving a sustainable low-carbon society, among which accurate prediction of building load is the key. However, for actual buildings with scarce historical data, physical models are often highly complex, computationally difficult, and costly. Developing reliable data-driven models also faces challenges related to generalization problems. Although transfer learning (TL) offers a potential solution, its effectiveness heavily depends on the appropriate selection of source domains—improper selection may lead to negative transfer. To address this, first, this study proposes a TL framework based on multidimensional dynamic time warping (DTW) similarity measurement to optimize source building selection. This framework incorporates key operational features such as cooling load and meteorological parameters into weighted similarity analysis. Under data–scarce conditions, we develop and rigorously evaluate five types of prediction models using data from five real office buildings: a LightGBM baseline model, a LightGBM weight initialization model (LightGBM-WI), an LSTM baseline model, a fine-tuned LSTM transfer model (LSTM-FT), and a feature extraction-based LSTM transfer model (LSTM-FE). Empirical results demonstrate that TL (LightGBM–WI and LSTM–FT) outperform baseline models, with CVRMSE reduced by an average of 15.75% and 13.19%, respectively. More importantly, compared to using all available source domain data, the proposed DTW-enhanced source domain screening strategy can reduce CVRMSE of 1.62% and 13.65% for LightGBM-WI and LSTM-FT, effectively mitigating negative transfer. This study provides a practical, reliable, and interpretable data–driven framework for accurate cooling load prediction in scenarios with limited historical data.

提高建筑能效，优化建筑能源管理是实现可持续低碳社会的关键步骤，其中建筑负荷的准确预测是关键。然而，对于缺乏历史数据的实际建筑，物理模型通常非常复杂，计算困难，并且成本高昂。开发可靠的数据驱动模型也面临着与泛化问题相关的挑战。虽然迁移学习（TL）提供了一种潜在的解决方案，但其有效性在很大程度上取决于源域的适当选择，不适当的选择可能导致负迁移。为了解决这一问题，本研究首先提出了一种基于多维动态时间翘曲（DTW）相似性度量的TL框架，以优化源构建选择。该框架将关键操作特征（如冷负荷和气象参数）纳入加权相似度分析。在数据稀缺的条件下，我们利用五座真实办公楼的数据开发并严格评估了五种预测模型：LightGBM基线模型、LightGBM权重初始化模型（LightGBM- wi）、LSTM基线模型、微调LSTM迁移模型（LSTM- ft）和基于特征提取的LSTM迁移模型（LSTM- fe）。实证结果表明，TL （LightGBM-WI和LSTM-FT）优于基线模型，CVRMSE平均分别降低了15.75%和13.19%。更重要的是，与使用所有可用的源域数据相比，本文提出的dtw增强源域筛选策略可使LightGBM-WI和LSTM-FT的CVRMSE分别降低1.62%和13.65%，有效减轻负迁移。该研究为在历史数据有限的情况下准确预测冷负荷提供了一个实用、可靠和可解释的数据驱动框架。

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引用次数: 0