Building and Environment最新文献_第3页

Heat waves in buildings: A review of detection methods and performance assessment 建筑物中的热浪：检测方法和性能评估综述

IF 7.6 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2026-01-04 DOI: 10.1016/j.buildenv.2026.114205

Matheus Körbes Bracht, Ana Paula Melo, Roberto Lamberts

Heat waves are among the most critical climate hazards, threatening both human health and the resilience of energy systems. Despite increasing attention in recent years, research on the interaction between heat waves and building thermal performance remains heterogeneous, with varied definitions and metrics across studies. This study presents a systematic review dedicated to this topic, analyzing 93 peer-reviewed articles to identify how heat waves are defined, detected, and linked to building performance and occupant well-being. Heat wave detection methods were categorized into climatological (absolute or relative threshold definitions), commonly accepted events, and simulation based. The relative threshold definition was identified as an effective method for selecting heat waves for building performance analysis. However, recent studies using simulation-based detection methods showed that external heat waves do not necessarily coincide with periods of extreme indoor heat. Investigators recommend using comprehensive heat stress indicators for simulation-based detection in future studies, while noting that current indices generally fail to capture cumulative heat stress. Vulnerability is also unevenly addressed, with comfort models still centered on young, healthy adults. In parallel, emerging metamodels offer opportunities to reduce the computational burden of large simulation studies. Finally, results indicate that peak cooling demand can arise during heat wave events that differ from those most critical for indoor environmental quality. Close collaboration among thermal simulation experts, meteorologists, public health officials, and urban planners is needed to develop comprehensive heat wave definitions and heat warning systems tailored to local contexts.

热浪是最严重的气候灾害之一，威胁着人类健康和能源系统的复原力。尽管近年来受到越来越多的关注，但对热浪与建筑热性能之间相互作用的研究仍然是异质的，在不同的研究中有不同的定义和指标。本研究对这一主题进行了系统回顾，分析了93篇同行评议的文章，以确定热浪是如何定义、检测的，并将其与建筑性能和居住者福祉联系起来。热浪探测方法分为气候学（绝对或相对阈值定义）、普遍接受的事件和基于模拟的方法。相对阈值定义是建筑性能分析中选择热浪的有效方法。然而，最近使用基于模拟的检测方法的研究表明，外部热浪并不一定与室内极端高温的时期一致。研究人员建议在未来的研究中使用综合热应力指标进行基于模拟的检测，同时注意到目前的指标通常无法捕获累积热应力。脆弱性也得到了不均衡的处理，舒适模型仍然以年轻健康的成年人为中心。同时，新兴的元模型为减少大型模拟研究的计算负担提供了机会。最后，研究结果表明，峰值制冷需求可能出现在热浪事件期间，而这些热浪事件与对室内环境质量最关键的事件不同。热模拟专家、气象学家、公共卫生官员和城市规划者之间需要密切合作，以开发适合当地情况的综合热浪定义和热预警系统。

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引用次数: 0

Multi-constraint physics-informed generative adversarial networks (PIGAN) enable small-data learning for urban wind field prediction 多约束物理信息生成对抗网络（PIGAN）为城市风场预测提供了小数据学习

IF 7.6 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2026-01-04 DOI: 10.1016/j.buildenv.2026.114202

Yihan Wu , Zihan Cao , Yubin Lei , Yuxuan Han , Man Yuan , Lihui Wang , Xingang Zhou

Urban wind field prediction is critical for air quality assessment, pedestrian comfort evaluation, and sustainable city design. Traditional computational fluid dynamics methods impose prohibitive computational costs, while conventional deep learning approaches demand datasets with excessive samples. We introduce a physics-informed generative adversarial network (PIGAN) framework achieving practical predictions using only around 200 training samples. Taking building height data as input, our model simultaneously predicts horizontal velocity components (u, v), turbulent kinetic energy (κ), and Reynolds stress (τ). A customized four-component physics-informed loss enforces continuity, x-momentum, y-momentum, and eddy viscosity constraints through staged training that progressively introduces reconstruction, adversarial, and physics objectives. This prevents convergence degradation, achieving L1 loss of 2.385 compared to 4.116 for simultaneous loss function optimization. Ablation studies demonstrate multi-constraint integration reduces RMSE by 11-36% across predicted variables, with physics losses providing strong regularization capacities. On realistic urban test sets from various countries, the framework achieves R² of 0.60 for u and 0.42 for κ. Transfer learning to idealized geometries demonstrates considerably stronger performance (R² = 0.92 for u, 0.80 for v), validating that the framework learns generalizable flow physics. Monte Carlo dropout with variance scaling calibration achieves near-ideal coverage, with prediction interval coverage probability (PICP) of 92.3-92.7%. Spatial uncertainty analysis finds reliable performance in open areas but elevated uncertainty in building wakes and street canyon intersections where 2D steady-state assumptions break down. Our study establishes a framework for physics-constrained machine learning in data-scarce environmental modeling, which enables real-time, risk-sensitive urban planning and design applications.

城市风场预测对空气质量评价、行人舒适度评价和可持续城市设计具有重要意义。传统的计算流体动力学方法带来了高昂的计算成本，而传统的深度学习方法需要大量样本的数据集。我们引入了一个物理信息生成对抗网络（PIGAN）框架，仅使用大约200个训练样本实现实际预测。该模型以建筑物高度数据为输入，同时预测水平速度分量（u, v）、湍流动能（κ）和雷诺应力（τ）。定制的四组分物理损失通过分阶段训练，逐步引入重建、对抗和物理目标，加强了连续性、x动量、y动量和涡流粘度约束。这可以防止收敛退化，实现L1损失为2.385，而同时损失函数优化的L1损失为4.116。消融研究表明，多约束集成可将预测变量的RMSE降低11-36%，物理损失提供了强大的正则化能力。在来自不同国家的现实城市测试集上，该框架的R²为0.60的u和0.42的κ。向理想化几何的迁移学习显示出相当强的性能（u的R²= 0.92，v的R²= 0.80），验证了该框架学习了可推广的流动物理。方差标度校正的蒙特卡罗dropout覆盖接近理想，预测区间覆盖概率（PICP）为92.3-92.7%。空间不确定性分析发现，在开放区域具有可靠的性能，但在建筑物尾迹和街道峡谷路口的不确定性较高，其中二维稳态假设失效。我们的研究为数据稀缺环境建模中物理约束的机器学习建立了一个框架，使实时、风险敏感的城市规划和设计应用成为可能。

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引用次数: 0

Evaluation of localized radiant heating effectiveness and physiological response in an electric vehicle cabin 电动汽车舱内局部辐射加热效能及生理反应评价

IF 7.6 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2026-01-03 DOI: 10.1016/j.buildenv.2026.114203

Mohammad F.B. Suhaimi , Woo Geun Kim , Chung-Won Cho , Jung Kyung Kim , Hyunjin Lee

Electric vehicles lose range in winter because heating, ventilation, and air conditioning systems require substantial battery power. Bulk air heating remains the common solution but is inefficient at low ambient temperatures. Localized radiant heating (LRH) offers a targeted alternative that can reduce energy use, although quantitative evidence on segmental physiological warming under realistic cabin conditions is still limited. This study developed a physiology-based framework to evaluate LRH effectiveness using a validated thermophysiological model. Experimental heater-on skin temperatures were validated with a root mean square error threshold of 1.0 C over a forty-minute window A matched heater-off reference was generated by re-simulating the validated model with radiant panels inactive. The LRH signal, defined as the skin temperature difference between heater-on and heater-off states for each body segment, isolates the direct physiological contribution of radiant heating. Localized radiant heating produced detectable warming in distal segments. The analysis applied indicator metrics that quantify warming magnitude, duration above a 0.5 C physiological detection threshold, and an exposure-weighted projection ratio that reflects radiant access. When considered together, these indicators allowed the body segments to be classified into LRH-driven, LRH-assisted, and constrained zones, representing the combined effects of radiant exposure and local physiological response. The framework provides a physiology-based foundation for identifying effective heating zones in electric vehicle cabins. It also establishes the basis for future work that combines the present objective indicators with subjective comfort metrics to determine design parameters for key heating zones and to support multi-objective optimization involving comfort, energy use, and cost.

电动汽车在冬天会失去行驶里程，因为供暖、通风和空调系统需要大量的电池电量。大量空气加热仍然是常见的解决方案，但在低环境温度下效率不高。局部辐射供暖（LRH）提供了一种有针对性的替代方案，可以减少能源使用，尽管在实际客舱条件下，局部生理供暖的定量证据仍然有限。本研究开发了一个基于生理学的框架，使用一个经过验证的热生理学模型来评估LRH的有效性。在40分钟的窗口内，以均方根误差阈值1.0 C验证了实验加热器打开的皮肤温度。通过重新模拟验证过的模型，在辐射板不活动的情况下，生成了匹配的加热器关闭参考。LRH信号被定义为每个身体部位开加热器和关加热器状态下的皮肤温度差，它隔离了辐射加热的直接生理贡献。局部辐射加热在远端节段产生可检测的升温。该分析应用了量化变暖幅度、高于0.5℃生理检测阈值的持续时间以及反映辐射通道的暴露加权投影比的指标度量。综合考虑这些指标，可以将身体部分划分为lrh驱动区、lrh辅助区和受限区，代表辐射暴露和局部生理反应的综合效应。该框架为确定电动汽车舱室的有效加热区域提供了基于生理学的基础。它还为未来的工作奠定了基础，将目前的客观指标与主观舒适度指标相结合，以确定关键供暖区域的设计参数，并支持涉及舒适度、能源使用和成本的多目标优化。

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引用次数: 0

From open plan to cooler meeting rooms (and back): Evidence of sex-specific psychophysiological responses to indoor–indoor transitions 从开放式计划到更凉爽的会议室（和回来）：性别对室内-室内过渡的心理生理反应的证据

IF 7.6 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2026-01-03 DOI: 10.1016/j.buildenv.2026.114200

Mateus Bavaresco , Larissa Pereira de Souza , Matheus Körbes Bracht , Matheus Soares Geraldi , Michelli Luvison , Ana Paula Melo

Indoor thermal transitions are common in offices but remain understudied, especially considering their potential sex-specific effects on occupants’ thermoregulation and thermal perceptions. This study investigated thermophysiological and perceptual responses to indoor-to-indoor transitions in a living lab. Twelve participants (six males, six females) completed three experimental rounds, each involving step-changes from a warmer open-plan office (PMV 0.46 ± 0.24) to a cooler meeting room (PMV –0.43 ± 0.35), and back. Skin temperatures, heart rate, thermal sensation, and thermal pleasure were continuously monitored, and the JOS-3 thermoregulation model was applied to simulate and compare predicted thermal dynamics. Results revealed pronounced sex-specific differences: females exhibited stronger distal-to-proximal gradients and lower hand temperatures than males, persisting even after returning to the warmer environment. These patterns indicate that routine indoor transitions can induce temporal and spatial alliesthesia that differ between sexes. Regarding thermal perceptions, females displayed larger overshoots in thermal sensation when entering cooler spaces, consistent with their skin heat loss. Thermal pleasure was slightly lower in females across both transitions, while the cooler room elicited higher pleasure in both sexes, likely reflecting occupants’ expectations in hot climates. Comparisons with JOS-3 simulations indicated accurate capture of overall thermal dynamics but underestimation of sex-specific distal cooling. These findings underscore the importance of considering sex-specific thermophysiological responses in indoor environments and support the development of adaptive comfort strategies and refined physiological models.

室内热转换在办公室中很常见，但仍未得到充分研究，特别是考虑到它们对居住者的温度调节和热感知的潜在性别特异性影响。本研究调查了室内到室内过渡的热生理和知觉反应。12名参与者（6男6女）完成了三轮实验，每一轮都包括从温暖的开放式办公室（PMV 0.46±0.24）到凉爽的会议室（PMV -0.43±0.35），然后再回来。连续监测皮肤温度、心率、热感觉和热愉悦，并应用JOS-3热调节模型模拟和比较预测的热动力学。结果显示了明显的性别差异：女性表现出较强的远端到近端梯度和较低的手部温度，即使在返回较温暖的环境后也会持续存在。这些模式表明，常规的室内过渡可以诱导不同性别的时间和空间联觉。在热感知方面，女性在进入较冷的空间时表现出更大的热感觉超调，这与她们的皮肤热损失一致。在两个过渡阶段，女性的热愉悦感都略低，而凉爽的房间会让两性都感到更高的愉悦感，这可能反映了居住者对炎热气候的期望。与JOS-3模拟的比较表明，它准确地捕获了整体热动力学，但低估了性别特异性的远端冷却。这些发现强调了在室内环境中考虑性别特异性热生理反应的重要性，并支持适应性舒适策略和精细生理模型的发展。

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引用次数: 0

Source term estimation based on the reduced-order adjoint equation 基于降阶伴随方程的源项估计

IF 7.6 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2026-01-03 DOI: 10.1016/j.buildenv.2026.114197

Yichen Zhang , Xuanyi Zhou , Jianjie Zhu , Hideki Kikumoto

To enhance the efficiency of pollutant source identification for emergency scenarios, a novel source term estimation (STE) method based on the reduced-order model (ROM) is proposed in this paper. Firstly, the original (full-order) adjoint equation is projected onto a Krylov subspace to achieve the model order reduction, thereby enabling the rapid solution of the reduced-order adjoint equation. The solution of full-order model (FOM) can be reconstructed by combining the solution of ROM with the projection matrix. Finally, the STE process is accomplished by incorporating the measured concentrations and the simulated concentrations (i.e. the solution of numerical simulation) into Bayesian inference. In this study, the performances of STE based on two type ROM (the single-input and the multiple-input) are investigated. The results demonstrate that the multiple-input ROM yields higher estimation accuracy than the single-input ROM. Furthermore, the discrepancies between ROM and FOM are analyzed. Under an idealized condition (the simulated results closely match measurement data), both FOM and ROM can estimate the source parameters accurately during the initial stage of STE, meaning ROM exhibits no distinct advantages in this scenario. However, under a non-idealized condition (the simulated results deviate from measurement data, a scenario that is more representative of real-world emergencies), accurate estimation results can only be obtained after acquiring sufficient long-term measurement data. Given that the computational cost of FOM scales linearly with simulation time while that of ROM scales with model order, ROM demonstrates a distinct efficiency advantage.

为了提高应急环境下污染源识别的效率，提出了一种基于降阶模型的污染源项估计方法。首先，将原（全阶）伴随方程投影到Krylov子空间上，实现模型降阶，从而实现降阶伴随方程的快速求解。将全阶模型（FOM）的解与投影矩阵相结合，可以重构全阶模型的解。最后，STE过程通过将测量浓度和模拟浓度（即数值模拟的解）合并到贝叶斯推理中来完成。本文研究了基于两种类型ROM（单输入和多输入）的STE的性能。结果表明，多输入ROM比单输入ROM具有更高的估计精度，并分析了ROM与FOM之间的差异。在理想条件下（模拟结果与测量数据接近），FOM和ROM都可以在STE初始阶段准确估计源参数，这意味着ROM在该场景中没有明显的优势。然而，在非理想条件下（模拟结果与测量数据偏离，更能代表现实世界突发事件的场景），只有在获得足够的长期测量数据后才能获得准确的估计结果。考虑到FOM的计算成本与仿真时间成线性关系，而ROM的计算成本与模型阶数成线性关系，ROM具有明显的效率优势。

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引用次数: 0

Assessing the economic, environmental, and energy impacts of natural gas-powered VRF system for building sector decarbonization: An integrated all-in-one package methodology based on open BIM approach 评估以天然气为动力的VRF系统对建筑行业脱碳的经济、环境和能源影响：基于开放式BIM方法的一体化一揽子方法

IF 7.6 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2026-01-03 DOI: 10.1016/j.buildenv.2026.114201

Chahrazed Mebarki , Adel Mohamed Ben Aissa Tidadini , Lotfi Derradji , Abdelatif Merabtine , Abderrahmane Mejedoub Mokhtari

In the context of the global energy transition, innovative HVAC solutions are essential, particularly those suited to temperate climates and local energy strategies. This study evaluates the potential of natural gas-powered Variable Refrigerant Flow (NG-VRF) systems, functioning as Gas Heat Pumps (GHPs), as a decarbonization strategy for countries reliant on natural gas power plants. A key aspect of this research is the comparison between NG-VRF systems and electric VRF systems with boilers for domestic hot water production. Using Life Cycle Assessment (LCA), the study assesses energy, environmental, and economic impacts in three climatic zones in Algeria: Mediterranean, semi-arid, and arid. The analysis incorporates the OpenBIM workflow and "Price Generator" database, offering an all-in-one package methodology as decision-support tool for energy consumption, environmental impact assessment, and economic evaluation aligning with trends in digitalization and energy transition. The findings reveal that the NG-VRF system, with its trigeneration capability, providing heating, cooling, and hot water from a single unit, achieves lower environmental impacts and energy consumption compared to mono-generation electric VRF systems. Heat recovery from the NG-VRF system eliminates the need for a separate hot water boiler, further enhancing efficiency. Paradoxically, promoting GHP systems in natural gas-producing countries helps preserve natural gas resources while reducing operational CO₂ emissions and primary energy consumption by 40% in Mediterranean climates, 35% in semi-arid, and 25% in arid climates. Furthermore, energy cost savings of up to 63% are achieved compared to international pricing. Consequently, energy savings in subsidized energy markets can increase natural gas exports, benefiting national revenues.

在全球能源转型的背景下，创新的暖通空调解决方案至关重要，特别是那些适合温带气候和当地能源战略的解决方案。本研究评估了天然气驱动的可变制冷剂流量（NG-VRF）系统作为气体热泵（GHPs）的潜力，作为依赖天然气发电厂的国家的脱碳战略。本研究的一个关键方面是比较NG-VRF系统和带锅炉的电动VRF系统用于生活热水生产。利用生命周期评估（LCA），该研究评估了阿尔及利亚三个气气带（地中海、半干旱和干旱）对能源、环境和经济的影响。该分析结合了OpenBIM工作流程和“价格生成器”数据库，提供了一个一体化的一揽子方法，作为能源消耗、环境影响评估和经济评估的决策支持工具，与数字化和能源转型的趋势保持一致。研究结果表明，与单电VRF系统相比，NG-VRF系统具有三联发能力，可从单个机组提供加热、冷却和热水，对环境的影响和能源消耗更低。NG-VRF系统的热回收消除了对单独热水锅炉的需求，进一步提高了效率。矛盾的是，在天然气生产国推广GHP系统有助于保护天然气资源，同时在地中海气候条件下减少40%的二氧化碳排放和一次能源消耗，在半干旱气候条件下减少35%，在干旱气候条件下减少25%。此外，与国际定价相比，可节省高达63%的能源成本。因此，在有补贴的能源市场上节约能源可以增加天然气出口，从而使国家收入受益。

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引用次数: 0

On-site measurement and machine learning prediction of age-specific outdoor thermal and humidity comfort in urban microclimates in summer 城市小气候夏季不同年龄室外热湿舒适度的现场测量与机器学习预测

IF 7.6 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2026-01-02 DOI: 10.1016/j.buildenv.2026.114199

Jianlin Ren , Jilong Wang , Yanhui Mao , Xiaodong Cao , Xiangfei Kong

The accurate assessment of human thermal and humidity comfort in dynamic outdoor urban environments remains a critical challenge. On-site measurements with advanced machine learning (ML) are advancing. The lack of comprehensive field datasets hinders robust predictions across diverse age groups. This study conducted 12-day outdoor experiments with 12 participants (6 young and 6 elderly) to gather microclimate, physiological, and voting data from diverse urban environments and age groups. Three ML algorithms—backpropagation neural network (NN), random forest (RF), and support vector machine (SVM)—were evaluated. A Bayesian-optimized, SMOTE-Tomek method further improved performance. Spatiotemporal microclimatic variations in urban areas induced significant (p < 0.05) physiological responses in electrocardiogram (ECG) and electroencephalogram (EEG) activity. Preliminary findings suggest age-based divergences in outdoor thermal comfort. Young subjects tended to feel hotter and showed greater physiological stress, while the elderly appeared to perceive greater humidity yet remained more comfortable. Based on statistical results, eight input and three output parameters were selected, with emphasis on humidity sensation votes. RF performed best for the thermal comfort vote (TCV) and humidity sensation vote (HSV). After optimization, the RF model achieved final accuracies of 71 % for TCV (n = 394), 75 % for HSV (dry) (n = 196), and 83 % for HSV (wet) (n = 330). Including age as a predictor substantially improved accuracy, by up to 11 %. A post-hoc power analysis (power = 0.82) confirmed statistical adequacy for detecting large effects. This exploratory age-related model may inform more adaptive, age-specific urban planning pending validation with larger cohorts.

动态室外城市环境中人体热湿舒适度的准确评估仍然是一个关键的挑战。先进机器学习（ML）的现场测量正在发展。缺乏全面的现场数据集阻碍了对不同年龄组的可靠预测。本研究对12名参与者（6名年轻人和6名老年人）进行了为期12天的户外实验，以收集来自不同城市环境和年龄组的微气候、生理和投票数据。对三种机器学习算法——反向传播神经网络（NN）、随机森林（RF）和支持向量机（SVM）进行了评估。贝叶斯优化的SMOTE-Tomek方法进一步提高了性能。城市地区的时空小气候变化在心电图（ECG）和脑电图（EEG）活动上引起了显著的生理反应（p < 0.05）。初步研究结果表明，室外热舒适存在年龄差异。年轻的受试者往往感到更热，表现出更大的生理压力，而老年人似乎感觉到更大的湿度，但仍然更舒适。根据统计结果，选择了8个输入参数和3个输出参数，重点是湿度感觉投票。RF在热舒适投票（TCV）和湿度感觉投票（HSV）中表现最好。优化后，RF模型对TCV （n = 394）的最终准确度为71%，对HSV （n = 196）的最终准确度为75%，对HSV （n = 330）的最终准确度为83%。将年龄作为预测因素，大大提高了准确率，最高可达11%。事后功率分析（功率= 0.82）证实了检测大效应的统计充分性。这个探索性的年龄相关模型可能会为更有适应性的、针对年龄的城市规划提供信息，等待更大的队列验证。

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引用次数: 0

Improved methods for assessing summer thermal environments in tropical urban beaches: Combining field measurements and simulation 评估热带城市海滩夏季热环境的改进方法：实地测量与模拟相结合

IF 7.6 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2026-01-01 DOI: 10.1016/j.buildenv.2026.114195

Jiahao Yang , Zhaosong Fang , Shaolin Gan , Jiacheng Wen , Xiang Zhang , Yini Fan , Zhiyi Huang , Yuyang Lin , Jun Lu

Strong solar radiation and unique surface properties in tropical beach areas create extreme outdoor thermal environments during summer, posing significant challenges for accurate thermal environment assessment. This study conducted field measurements at a beach site in Haikou, China, followed by computational simulations and model optimization. The main findings include: 1) Unshaded areas exhibited mean radiant temperatures (MRT) exceeding 70 °C, downward short-wave radiation over 1000 W/m², and surface temperatures reaching 61.4 °C; 2) Significant measurement errors were observed in the black-globe thermometer method, particularly when using smaller globes. After implementing segmented convective heat transfer coefficient calibration based on T_a thresholds, the accuracy of all black-globe thermometer methods was significantly improved, achieving performance metrics of d (Consistency Index) > 0.89, RMSE (Root Mean Square Error) < 4.57, MAE (Mean Absolute Error) < 3.29, MBE (Mean Bias Error) < 0.87, and R² (Correlation coefficient) > 0.83; 3) While ENVI-met effectively simulated spatial MRT distribution, thermal indices (especially PET, Physiological Equivalent Temperature) required calibration. Post-optimization, the maximum RMSE between simulated and measured values decreased to 4.64 for PET and 2.05 for UTCI (Universal Thermal Climate Index), with MAE values of 3.85 and 1.79, and MBE values of 0.91 and 0.96, indicating substantially improved accuracy. This study provides methodological support for thermal environment assessment in beach areas and offers practical insights for thermal safety planning and management in coastal regions.

热带海滩地区强烈的太阳辐射和独特的地表特性在夏季造成了极端的室外热环境，为准确的热环境评估带来了重大挑战。本研究在中国海口的一个海滩进行了实地测量，然后进行了计算模拟和模型优化。结果表明：1)无遮挡区域的平均辐射温度（MRT）超过70℃，短波向下辐射超过1000 W/m²，地表温度达到61.4℃；2)黑球温度计法的测量误差显著，特别是当使用较小的球时。采用基于Ta阈值的分段对流换热系数校正后，所有黑球温度计方法的精度都得到了显著提高，达到了d（一致性指数）> 0.89、RMSE（均方根误差）< 4.57、MAE（平均绝对误差）< 3.29、MBE（平均偏置误差）<； 0.87和R²（相关系数）> 0.83；3)虽然ENVI-met能有效模拟MRT的空间分布，但热指标（尤其是PET、生理等效温度）需要标定。优化后，PET和UTCI （Universal Thermal Climate Index）模拟值与实测值之间的最大RMSE分别降至4.64和2.05，MAE分别为3.85和1.79，MBE分别为0.91和0.96，精度显著提高。本研究为滩涂热环境评价提供了方法支持，为滩涂热安全规划与管理提供了实践启示。

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引用次数: 0

Dynamic outdoor thermal comfort and activity adaptation in community parks: An AI-based metabolic modeling approach 社区公园动态室外热舒适和活动适应：基于人工智能的代谢建模方法

IF 7.6 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2026-01-01 DOI: 10.1016/j.buildenv.2025.114194

Zhiyuan Shao , Yudong Guo , Junliang Wu , Zhuobiao Ni , Yue Wang , Yuhan Liang , Yafei Wang , Shaoqing Chen

Urban heat stress poses critical public health and outdoor comfort challenges, yet conventional thermal comfort indices, such as the Outdoor Standard Effective Temperature (OUT_SET*), rely on static metabolic assumptions, limiting their applicability in dynamic outdoor settings. This study introduces a multi-module AI-driven framework integrating behavioral recognition (i.e. YOLOv5, DeepSORT, and SlowFast networks), combined with microclimate monitoring, to assess thermal comfort in urban community parks. Using Guanggang Park, Guangzhou, China as the study site, we quantified real-time attendance, activity duration and types, and metabolic rates at 10-minute intervals (n = 459 intervals) over a one-year period. These data were integrated with on-site environmental measurements to develop an adaptive thermal comfort index (OUT_aSET*), refining OUT_SET* by incorporating activity-driven metabolic variations. Seasonal field observations revealed distinct behavioral thermal adaptation patterns. Attendance peaked at 25.2 °C in winter and 30.2 °C during transitional season, but declined linearly in summer. High-intensity activities (e.g. running) markedly decreased during hot periods, while low-intensity behaviors persisted, suggesting a dual adaptation strategy of reduced exertion under heat stress and extended stays in thermally comfortable conditions. Compared to OUT_SET*, OUT_aSET* more effectively captured thermal variability and heat stress, particularly in transitional or cold seasons, where activity-induced metabolic adjustments are pronounced. This framework enhances the ecological validity of thermal comfort assessments and provides evidence-based insights for microclimate-sensitive park design and urban heat mitigation. By aligning thermal indices with observed behaviors, this study informs accurate public health risk assessments and supports climate-resilient urban planning.

城市热应激对公共健康和室外舒适构成了严峻的挑战，然而传统的热舒适指数，如室外标准有效温度（OUT_SET*），依赖于静态代谢假设，限制了它们在动态室外环境中的适用性。本研究引入了一个集成行为识别（即YOLOv5、DeepSORT和SlowFast网络）的多模块ai驱动框架，结合小气候监测，对城市社区公园的热舒适性进行了评估。以中国广州广港公园为研究地点，我们在一年的时间里，每隔10分钟（n = 459次）量化实时出勤率、活动持续时间和类型以及代谢率。将这些数据与现场环境测量相结合，得出自适应热舒适指数（OUT_aSET*），并通过纳入活动驱动的代谢变化来完善OUT_SET*。季节性野外观察显示了不同的行为热适应模式。冬季最高时为25.2°C，过渡季节最高时为30.2°C，但夏季呈线性下降。高强度活动（如跑步）在炎热季节明显减少，而低强度活动持续存在，表明热应激下减少运动和延长热舒适条件下停留的双重适应策略。与OUT_SET*相比，OUT_aSET*更有效地捕获了热变异性和热应激，特别是在过渡季节或寒冷季节，活动引起的代谢调节是明显的。该框架增强了热舒适评估的生态有效性，并为微气候敏感型公园设计和城市热缓解提供了基于证据的见解。通过将热指数与观察到的行为相结合，本研究为准确的公共卫生风险评估提供信息，并支持气候适应型城市规划。

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引用次数: 0

Enhancing the dynamic thermal performance of wall components through shape optimization: Method and application to extruded blocks and 3D-printed walls 通过形状优化增强墙体构件的动态热性能：挤压块和3d打印墙体的方法及应用

IF 7.6 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2026-01-01 DOI: 10.1016/j.buildenv.2025.114193

Eduardo Gascón Alvarez, Alexander Curth, Caitlin T. Mueller, Leslie K. Norford

Building components with integrated air cavities, such as thermal-insulating clay blocks or 3D-printed earthen walls, leverage the low thermal conductivity of still air to increase their thermal resistance (R-value) while removing an often high-carbon material. Yet, the design of these components (referred to in this work as multi-hollowed wall components) usually neglects their ability to store heat, hindering the development of blocks and walls with enhanced thermal mass performance. Moreover, blocks and walls are seldom designed for an optimal balance between their embodied and operational performance, a critical aspect when considering the whole-cycle impact of buildings. This research fills these gaps through a novel shape-optimization method that combines state-of-the-art computational design tools with fundamental heat transfer theory to facilitate the discovery of wall designs with optimal passive cooling performance (measured as the heat capacity [kJ/m²K]) and minimum weight [kg/m²]. The benefits of applying this method are illustrated through the multi-objective optimization of two distinct wall systems: (1) extruded ceramic blocks with multiple air cavities and (2) 3D-printed earthen wall systems. The results provide quantifiable evidence in favor of designing building components specifically for heat resilience, achieving shape-optimized blocks that increase their heat capacity by 60 % without additional material and 3D-printed walls with an 84 % improved time constant and only 5 % more weight. Finally, the construction and monitoring of three full-scale prototypes in a temperate climate provide additional validation by experimentally measuring their dynamic thermal performance.

具有集成空腔的建筑组件，如隔热粘土块或3d打印土墙，利用静止空气的低导热性来增加其热阻（r值），同时去除通常高碳的材料。然而，这些组件的设计（在本工作中称为多空心墙体组件）通常忽略了它们储存热量的能力，阻碍了具有增强热质量性能的砌块和墙体的发展。此外，在设计街区和墙壁时，很少考虑到其具体性能和使用性能之间的最佳平衡，这是考虑建筑物全周期影响的一个关键方面。本研究通过一种新颖的形状优化方法填补了这些空白，该方法将最先进的计算设计工具与基本的传热理论相结合，以促进发现具有最佳被动冷却性能（以热容量[kJ/m²K]测量）和最小重量[kg/m²]的墙壁设计。通过对两种不同的墙体系统进行多目标优化，说明了应用该方法的好处：(1)具有多个空腔的挤压陶瓷块和(2)3d打印土墙系统。研究结果为建筑构件的热弹性设计提供了可量化的证据，实现了形状优化的砌块，在不增加材料的情况下，其热容量增加了60%，3d打印墙体的时间常数提高了84%，重量仅增加了5%。最后，通过实验测量其动态热性能，在温带气候下构建和监测了三个全尺寸原型，提供了额外的验证。

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引用次数: 0