Building and Environment最新文献_第4页

Transition to Net-Zero Energy Communities: Investigating Techno-Financial Feasibility and Social Acceptance 向净零能源社区过渡：调查技术-财务可行性和社会接受度

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.2025.114184

S.U.M. Jagoda , Kasun Hewage , Ravihari Kotagodahetti , Rehan Sadiq

The escalating threats from climate change, mainly resulting from greenhouse gas (GHG) emissions have highlighted the importance of decarbonization. Net zero energy (NZE) has been identified as the most promising strategy for reducing emissions from community energy with renewable resources. Yet, one of the major barriers to NZE is public acceptance. There is a lack of aggregated knowledge on gaining public acceptance for NZE. Therefore, this paper aims to critically review opportunities and challenges for NZE strategies under technical and financial dimensions to derive interventions to improve public awareness and acceptance. This paper categorizes NZE strategies under demand reduction and renewable energy. The demand reduction strategies focus on improving appliance efficiency and thermal insulation. Following demand reduction, the integration of renewable energy resources into communities is discussed. Solar photovoltaics, wind, and geothermal systems are the different types of renewable energy resources included in the paper, considering their high adaptability and availability of resources. The review highlights public acceptance of NZE measures as the pivotal point for the successful execution of NZE transition. This paper discusses five different types of public acceptance: attitudinal, socio-political, market, community, and behavioural. Financial incentives/ or surcharge schemes, awareness programs, and participatory decision-making have been identified as key social mechanisms for gaining public acceptance. This dual focus on techno-financial analysis along with strategies to promote public acceptance provides valuable insights for policymakers, town and country planners, energy stakeholders, and researchers about essential areas that need attention in the transition towards NZE communities.

主要由温室气体（GHG）排放造成的气候变化威胁不断升级，凸显了脱碳的重要性。净零能耗（NZE）已被确定为利用可再生资源减少社区能源排放的最有前途的战略。然而，NZE的主要障碍之一是公众的接受度。关于如何让公众接受NZE，目前还缺乏综合知识。因此，本文的目的是在技术和财务方面批判性地审查NZE战略的机遇和挑战，以获得干预措施，以提高公众的认识和接受度。本文将NZE策略分为需求减少和可再生能源两大类。减少需求的策略侧重于提高电器效率和隔热。在需求减少之后，讨论了可再生能源与社区的整合。考虑到太阳能光伏、风能和地热系统具有较高的适应性和资源可用性，本文将其作为不同类型的可再生能源。该审查强调，公众对国家可持续发展措施的接受程度是成功实施国家可持续发展转型的关键。本文讨论了五种不同类型的公众接受：态度、社会政治、市场、社区和行为。财政激励/附加费计划、宣传计划和参与性决策已被确定为获得公众接受的关键社会机制。这种对技术金融分析的双重关注，以及促进公众接受的策略，为政策制定者、城镇和乡村规划者、能源利益相关者和研究人员提供了有价值的见解，了解了向NZE社区过渡过程中需要关注的关键领域。

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引用次数: 0

Fast and accurate indoor airflow prediction using multi-scale attention graph neural network 基于多尺度注意图神经网络的室内气流快速准确预测

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.2025.114183

Xuqiang Shao , Xiaofan Liu , Sixuan Chen , Jianyong Zhu , Liang Wang , Zhaobing Jiang , Jiancai Huang

With the rapid advancement of urbanization and the increasing amount of time individuals spend indoors, there has been a growing emphasis on indoor environmental quality. The accurate prediction of indoor airflow field is essential for optimizing building design, enhancing ventilation efficiency, minimizing energy consumption, and achieving low-carbon operations in enclosed environments. Computational Fluid Dynamics (CFD) remains a powerful tool for simulating airflow through the solution of the Navier-Stokes equations. However, its dependence on fine mesh resolution and iterative computations restricts its real-time applicability, particularly in complex indoor environments. To facilitate efficient predictions of indoor airflow and address prevalent challenges associated with traditional Graph Neural Networks (GNN), this study introduces a Multi-Scale Attention Graph Neural Network (MSA-GNN). The model integrates a multi-scale graph architecture to enhance spatial feature representation and incorporates a self-attention mechanism to enhance the transmission efficiency of long-range dependencies. Trained on time-resolved airflow data generated by transient CFD simulations in realistic indoor scenes, the MSA-GNN achieves an R² of 0.98 and is computationally 7–10 times faster than CFD solvers. These results demonstrate its potential as a high-fidelity, real-time alternative for airflow prediction in building environmental design and smart ventilation control.

随着城市化的快速发展和人们在室内的时间越来越长，人们越来越重视室内环境质量。室内气流场的准确预测对于优化建筑设计、提高通风效率、降低能耗、实现封闭环境下的低碳运行至关重要。计算流体动力学（CFD）仍然是通过求解Navier-Stokes方程来模拟气流的有力工具。然而，它对细网格分辨率和迭代计算的依赖限制了它的实时性，特别是在复杂的室内环境中。为了促进室内气流的有效预测，并解决与传统图神经网络（GNN）相关的普遍挑战，本研究引入了多尺度注意力图神经网络（MSA-GNN）。该模型集成了多尺度图体系结构，增强了空间特征表征能力；引入了自关注机制，提高了远程依赖关系的传输效率。MSA-GNN在真实室内场景瞬态CFD模拟生成的时间分辨气流数据上进行训练，R²为0.98，计算速度比CFD求解器快7-10倍。这些结果证明了它在建筑环境设计和智能通风控制中作为高保真、实时的气流预测替代方案的潜力。

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引用次数: 0

Turbulent fluctuation around a semi-open structure - influencing assessment on building aspect ratio and wind probability by wind tunnel test 半开式结构周围湍流波动——风洞试验对建筑展弦比和风概率的影响评估

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

Building and Environment

Pub Date : 2025-12-31 DOI: 10.1016/j.buildenv.2025.114192

Yujie Chu , Xuelin Zhang , Yaojia Guo , Yu Liao , Xingyu Qian , Wenbing Liu , Jianlin Liu

Semi-open structures are essential for improving urban wind comfort and safety. The aerodynamic behavior of widely used buildings with large openings remains poorly understood, limiting the applicability of existing empirical models. This study adopts wind tunnel to investigate airflow around a semi-open structure, focusing on mean wind speed, instantaneous wind flow pattern, and gust characteristics. The study also explores how the aspect ratio and approaching wind direction affect the probability distribution of the pedestrian-level wind (PLW) environment. Results show that opening enhances airflow at the windward corner and reduces separation on the lateral side, resulting in a narrow wake region. The gust effect diminishes as mean wind speed increases. Under weak wind conditions (U/U_H < 0.3), the value of peak factor at 3.03 adequately represents short-term gusts. Increasing building height amplifies localized acceleration near the opening while hindering internal flow penetration. Increasing building width strengthens flow blockage and enlarges low wind speed areas to about 1.8 times that of the reference building case. The airflow around the building is highly sensitive to different wind directions. Although the wind speed distribution is mostly positively skewed, only a 0° wind direction produces relatively high wind speed with minimal fluctuation. Oblique and reverse wind directions lead to fluctuations or decreased airflow. These findings provide a scientific basis for understanding the aerodynamic behavior around semi-open structures, guiding design strategies to improve local wind comfort and safety.

半开放式结构是提高城市风舒适性和安全性的重要手段。广泛使用的大开口建筑的空气动力学行为仍然知之甚少，限制了现有经验模型的适用性。本研究采用风洞法研究半开放式结构周围的气流，重点研究平均风速、瞬时风型和阵风特征。研究还探讨了纵横比和接近风向对行人水平风环境概率分布的影响。结果表明，开孔增强了迎风角的气流，减少了侧面的分离，使尾迹区域变窄。阵风效应随着平均风速的增加而减弱。在弱风条件下（U/UH < 0.3），峰值因子值为3.03足以代表短期阵风。增加建筑高度会放大开口附近的局部加速度，同时阻碍内部流动的渗透。增加建筑宽度加强了气流阻塞，并将低风速区域扩大到参考建筑案例的1.8倍左右。建筑周围的气流对不同风向非常敏感。虽然风速分布多为正偏斜，但只有0°风向风速较大，波动最小。倾斜和反向的风向导致气流波动或减少。这些研究结果为了解半开放式结构周围的空气动力学行为，指导设计策略以提高局部风舒适性和安全性提供了科学依据。

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引用次数: 0

Radon-222 entry rate in homes and workplaces determined with modern electronic radon detectors 用现代电子氡探测器测定家庭和工作场所氡-222的进入率

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

Building and Environment

Pub Date : 2025-12-31 DOI: 10.1016/j.buildenv.2025.114190

Krasimir Mitev , Vladislav Todorov , Strahil Georgiev , Philippe Cassette , Benoit Sabot , Zornitza Daraktchieva , Stefan Röttger , Ivelina Dimitrova

Radon is the second leading cause of lung cancer after smoking. While radon exposure is assessed by the annual average radon concentration, the radon entry rate, which is fundamental to understanding radon behaviour and mitigation, has received less attention due to measurement challenges. Technological advancements over the past decade have led to the development of affordable and widely available consumer-grade electronic detectors that can provide time-resolved radon measurements. A novel method for estimating the radon entry rate from radon time series measured by fast-response, consumer-grade electronic monitors is presented. It was validated through experiments conducted in a primary metrology laboratory and test-bed studies. It was implemented in a three-year radon monitoring campaign in 36 occupied dwellings and workplaces located in both radon-priority and non-priority areas. During the campaign data on the dynamics of radon entry rate and air change rate were gathered remotely without interrupting the buildings’ usage cycle. A correlation between the radon entry rate and the air change rate at low ventilation was observed in about 80

% of the buildings, which demonstrates that the radon entry rate can be studied in relation to other dynamic parameters. This new approach can be used by scientists developing models for radon transport in buildings, as well as by remediation and mitigation professionals to provide smart and energy-efficient mitigation strategies. The method proposed herein provides insights into radon dynamics and can revolutionize our efforts to maintain a healthy indoor environment with respect to radon.

氡是肺癌的第二大诱因，仅次于吸烟。虽然氡暴露是通过年平均氡浓度来评估的，但由于测量方面的挑战，氡进入率受到的关注较少，而氡进入率是了解氡行为和减缓的基础。过去十年的技术进步导致了价格合理且广泛可用的消费级电子探测器的发展，这些探测器可以提供时间分辨的氡测量。提出了一种从快速响应消费级电子监测仪测量的氡时间序列中估计氡进入率的新方法。在初级计量实验室和试验台研究中进行了实验验证。它是在一项为期三年的氡监测运动中实施的，该运动在氡优先和非优先地区的36个被占用住宅和工作场所进行。在活动期间，在不中断建筑物使用周期的情况下，远程收集了氡进入率和空气变化率的动态数据。在低通风条件下，约80%的建筑物的氡进入率与换气率之间存在相关性，这表明氡进入率可以与其他动态参数进行研究。这种新方法可用于开发建筑物内氡传输模型的科学家，也可用于补救和缓解专业人员，以提供智能和节能的缓解战略。本文提出的方法提供了对氡动力学的见解，并可以彻底改变我们在氡方面维持健康室内环境的努力。

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引用次数: 0

A coupled heat and moisture transfer model for smart clothing with temperature adaptive porosity and thermal emissivity 具有温度自适应孔隙率和热发射率的智能服装热湿耦合传递模型

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

Building and Environment

Pub Date : 2025-12-31 DOI: 10.1016/j.buildenv.2025.114181

Yedan Zhao , Yinghong Xu , Jintu Fan

With the increasing energy consumption and environmental concerns, personal thermal management via smart thermoregulatory clothing has emerged as a crucial strategy for significant energy savings, which is essential for reducing the reliance on air conditioning. However, most existing research on intelligent textiles remains at the experimental stage, lacking well-established quantitative thermoregulatory models. In this study, we innovatively developed coupled heat and mass transfer partial differential equations that incorporate temperature-adaptable porosity and surface emissivity. In order to validate the model, we conducted experiments using a multimodal temperature-regulating garment equipped with temperature-responsive actuators. The simulation results of the developed model highly agree with measured data. The maximum relative errors in thermal and moisture resistance are

0.0673

and

0.0167

, respectively, which confirms the model’s reliability and accuracy in evaluating the thermal and moisture comfort of smart clothing. Moreover, compared with existing models, our model considers temperature-dependent structural variations in smart textiles and their impact on human thermal comfort. Our findings present an innovative solution for personal thermal management. The framework guides advanced fabric design, and also offers insights into practical challenges and solutions, promoting the smart textile industry.

随着能源消耗和环境问题的日益增加，通过智能体温调节服装进行个人热管理已经成为一种重要的节能策略，这对于减少对空调的依赖至关重要。然而，大多数现有的智能纺织品研究仍停留在实验阶段，缺乏完善的定量热调节模型。在这项研究中，我们创新地开发了包含温度适应性孔隙率和表面发射率的耦合传热和传质偏微分方程。为了验证该模型，我们使用配备温度响应执行器的多模态温度调节服装进行了实验。该模型的仿真结果与实测数据吻合较好。热阻和湿阻的最大相对误差分别为0.0673和0.0167，验证了该模型在评价智能服装热湿舒适性方面的可靠性和准确性。此外，与现有模型相比，我们的模型考虑了智能纺织品中温度依赖的结构变化及其对人体热舒适的影响。我们的研究结果为个人热管理提供了一种创新的解决方案。该框架为先进的面料设计提供指导，并为实际挑战和解决方案提供见解，促进智能纺织行业的发展。

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引用次数: 0

Spatiotemporal evolution of 222Rn concentration in enclosed spaces: diffusion-decay model and experimental validation 封闭空间中222Rn浓度的时空演化：扩散衰减模型与实验验证

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

Building and Environment

Pub Date : 2025-12-30 DOI: 10.1016/j.buildenv.2025.114186

Yujie Wu , Zhanjie Wang , Zhan Li , Angui Li

Accurate prediction of indoor ²²²Rn concentration in enclosed spaces is essential for environmental safety and public health. This study develops a one-dimensional analytical diffusion-decay model with a closed-form solution that describes the full spatiotemporal evolution of radon in confined air. The model explicitly includes a uniform areal source, molecular diffusion and radioactive decay, while neglecting advection. The latter simplification is justified by first-principles quantum-chemistry calculations of gravitational energy differences, scaling analysis of sedimentation versus diffusion, and source-position comparison experiments. Using separation of variables, the one-dimensional diffusion-decay equation is solved in terms of the characteristic diffusion length

L = \sqrt{D / λ}

and the dimensionless height

ξ = H / L

. Parameter analysis shows a linear amplification effect of source strength

S

, a nonlinear attenuation of top-layer concentration with increasing height

H

, and the central role of

L

in controlling vertical uniformity. Controlled sealed-chamber experiments under diffusion-dominated conditions demonstrate high predictive accuracy: steady-state vertical profiles are reproduced with a root-mean-square error of 45 Bq·m⁻³ (1.4 - 2.7% of measurements), an overall mean relative bias of -1.0%, and R² ≈ 0.97; transient build-up is captured within about 5% deviation. A decision chart based on

ξ

is proposed to classify near-uniform, moderately stratified and strongly stratified regimes and to recommend monitoring heights, providing a lightweight tool for radon risk assessment and ventilation design in diffusion-dominated enclosed spaces.

准确预测封闭空间室内222Rn浓度对环境安全和公众健康至关重要。本研究开发了一个一维解析扩散衰减模型，该模型具有封闭形式的解，描述了氡在密闭空气中的完整时空演化。该模型明确地包括了均匀面源、分子扩散和放射性衰变，而忽略了平流。后一种简化是由第一原理量子化学的引力能差计算、沉降与扩散的尺度分析和源位置比较实验证明的。采用分离变量法，求解一维扩散衰减方程，得到特征扩散长度L=D/λ，无量纲高度ξ=H/L。参数分析表明，源强度存在线性放大效应，顶层浓度随高度th的增加呈非线性衰减，而l在控制垂直均匀性方面起核心作用。在扩散主导条件下的受控密封室实验显示出较高的预测精度：稳态垂直剖面的再现均方根误差为45 Bq·m−3（测量值的1.4 - 2.7%），总体平均相对偏差为-1.0%,R2≈0.97；在大约5%的偏差范围内捕获瞬态累积。提出了一种基于onξ的决策图，对接近均匀、中等分层和强烈分层的区域进行分类，并建议监测高度，为扩散为主的封闭空间的氡风险评估和通风设计提供了一种轻量级工具。

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引用次数: 0

Dynamic interpretable prediction and Spatio-temporal reduction pathways analyses of embodied carbon emission in China's building sector 中国建筑隐含碳排放动态可解释预测及时空减排路径分析

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

Building and Environment

Pub Date : 2025-12-30 DOI: 10.1016/j.buildenv.2025.114191

Zhike Zheng, Qing Shuang

With rapid urbanization and construction, China is facing severe environmental challenges from excessive carbon emissions of the building sector, where the embodied carbon emission (ECE) occupies a significant proportion. Under the national decarbonization strategies and sustainable urgencies, this study focuses on the prediction and reduction pathways of ECE in China’s building sector. Through an interpretable hybrid machine learning model, this study proposes an accurate national ECE prediction and extends the spatial heterogeneity analysis to 31 provinces. Besides, with the combination of carbon intensity prediction and Tapio decoupling analysis, this study provides explicit temporal carbon reduction pathways. These findings offer unique insights: First, China’s building sector is predicted to peak at 2030 with 1.6 billion tons of ECE, with production and demolition stages accounting for the majority. Second, the spatial heterogeneity analysis reveals the major contributions from the southeast coasts and central plains, which are mainly influenced by economic development and sectoral transformation. Third, the temporal carbon reduction pathways reveal the crucial period from 2031 to 2041, demonstrating the effectiveness and efficiency of decarbonization during these times. These results offer essential directions for carbon regulation and sustainable transition, providing targeted recommendations for global carbon mitigation and sustainable development.

随着城市化和建设的快速发展，中国面临着建筑行业碳排放过高的严峻环境挑战，其中隐含碳排放（ECE）占很大比例。在国家脱碳战略和可持续紧迫性的背景下，本研究重点研究了中国建筑行业ECE的预测和减少途径。通过可解释的混合机器学习模型，本研究提出了准确的全国ECE预测，并将空间异质性分析扩展到31个省份。此外，结合碳强度预测和Tapio解耦分析，本研究提供了明确的时间碳减排路径。这些发现提供了独特的见解：首先，中国建筑行业预计将在2030年达到16亿吨ECE的峰值，其中生产和拆除阶段占大部分。②东南沿海和中原地区对气候变化贡献最大，主要受经济发展和产业转型的影响；第三，时间碳减排路径揭示了2031 - 2041年这一关键时期，证明了这一时期脱碳的有效性和效率。这些结果为碳调控和可持续转型提供了重要方向，为全球碳减排和可持续发展提供了有针对性的建议。

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引用次数: 0

Psychophysiological responses to indoor wood use: A systematic literature review of indicators, methods, and research trends 室内木材使用的心理生理反应：指标、方法和研究趋势的系统文献综述

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

Building and Environment

Pub Date : 2025-12-29 DOI: 10.1016/j.buildenv.2025.114188

Greta Cavaliere , Silvana Calvano , Paola Molina , Francesco Negro

Wood can significantly improve human well-being in indoor environments and enhance biophilic design. This systematic review examines studies on psychophysiological responses to wood exposure, focusing on experimental designs and measurement methods (Q1), involved participants (Q2), and types and features of wood products (Q3). A systematic literature search was conducted in Scopus and Web of Science databases following the PRISMA protocol. The search strategy combined keywords related to indoor wood-based products, well-being and interactions. Only primary research articles published in English over the last 20 years were considered. Fifty studies assessing psychophysiological responses to wood through physiological (e.g., cardiovascular, cerebral, hormonal, ocular, thermal, electrodermal, muscular, respiratory) and/or psychological (e.g., cognitive tests, questionnaires) indicators, were included. Results revealed diverse exposure modalities (visual, tactile, olfactory, multisensory) and measurement approaches. Studies predominantly involved university students (20–50 participants) and short exposure durations (1–15 mins). Both solid and engineered wood products were investigated, with attention to their colour, finishing, and thermal properties. Three main research needs emerged: extending exposure time to study long-term effects, diversifying participant demographics, especially in terms of age range, and combining questionnaires with physiological measures, to foster a broader approach. Research on psychophysiological responses to wood is a complex field that combines human and applied sciences. Through a structured overview of current methodological approaches, this review guides future interdisciplinary research across environmental psychology, design and material science. It also provides practical insights for architects and interior designers seeking to incorporate biophilic principles to improve occupant well-being.

木材可以显著改善室内环境中人的幸福感，增强亲生物设计。本系统综述考察了对木材暴露的心理生理反应的研究，重点关注实验设计和测量方法（Q1），参与者（Q2）以及木制品的类型和特征（Q3）。按照PRISMA协议在Scopus和Web of Science数据库中进行了系统的文献检索。搜索策略结合了与室内木制品、健康和互动相关的关键词。仅考虑了过去20年用英语发表的初级研究文章。通过生理指标（如心血管、大脑、荷尔蒙、眼、热、皮肤电、肌肉、呼吸）和/或心理指标（如认知测试、问卷调查）评估对木材的心理生理反应的研究有50项。结果显示不同的暴露方式（视觉，触觉，嗅觉，多感官）和测量方法。研究主要涉及大学生（20-50名参与者），暴露时间较短（1-15分钟）。对实木和工程木制品进行了研究，重点关注它们的颜色、整理和热性能。三个主要的研究需求出现了：延长暴露时间以研究长期影响，使参与者的人口统计多样化，特别是在年龄范围方面，以及将问卷调查与生理测量相结合，以促进更广泛的方法。对木材的心理生理反应的研究是一个人文科学与应用科学相结合的复杂领域。通过对当前方法的结构化概述，本综述指导了未来跨环境心理学、设计和材料科学的跨学科研究。它还为建筑师和室内设计师提供了实用的见解，以寻求结合亲生物原则来改善居住者的福祉。

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引用次数: 0

AI-based personal conditioning with physiological awareness: Fine-tuned small and large language models vs. neural networks 基于人工智能的个人调节与生理意识：微调的小型和大型语言模型与神经网络

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

Building and Environment

Pub Date : 2025-12-29 DOI: 10.1016/j.buildenv.2025.114189

Lingzhe Wang, Gautam Vanama, Jelena Srebric

Current personal conditionings mostly rely on manual adjustments, limiting their adaptabilities to dynamic environment. This study employs fine-tuned small/large language models (SLMs/LLMs) and neural networks (NN) to enable AI-based personal conditioning with physiological awareness, allowing them to accurately predict users’ thermal comfort from real-time physiological measurements. We used a multimodal dataset with 100 K data collected at different thermal comfort levels created by personal conditioning in human subject experiments. This dataset provided a basis for SLMs/LLMs fine-tuning and further allowed their performance comparison with NN. Pre-trained SLMs/LLMs exhibited poor performance (F1 near 0), while fine-tuned SLMs/LLMs showed significantly improved performances (F1 up to 0.99). Fine-tuning included feature groups of varying dimensionalities: temperature-based low-dimensional (FG1), HRV-based medium-dimensional (FG2), and multimodal high-dimensional (FG3). Incorporating HRV features markedly enhanced accuracy (FG2, NN: 0.73, SLM: 0.93, LLM: 0.96) comparing to temperature-based features (FG1, NN: 0.45, SLM: 0.42, LLM: 0.43), while multimodal features achieved near-perfect performance (FG3, NN: 0.91, SLM/LLM: 0.99). Overall, our findings offer clear guidance for model selection. With low-dimensional features, NN delivers the best performance. However, overall accuracies remain low across all three models. For medium to high dimensional data, the simple NN architecture provides satisfactory performance with minimal costs, enabling efficient deployment on IoT devices. Fine-tuned SLMs further improve performance, achieving near-perfect results comparable to fine-tuned LLMs but at substantially lower cost. Accordingly, for future human-centric personal conditioning, we recommend using medium to high dimensional data with NN as a cost-effective, moderate-performance solution, or with fine-tuned SLMs as a high-performance, moderate-cost solution.

目前的个人调节大多依靠人工调节，限制了其对动态环境的适应性。本研究采用微调的小/大语言模型（SLMs/LLMs）和神经网络（NN），使基于人工智能的个人调节具有生理意识，使其能够从实时生理测量中准确预测用户的热舒适。我们使用了一个多模态数据集，收集了100 K的数据，这些数据是在人体受试者实验中由个人调节产生的不同热舒适水平下收集的。该数据集为slm / llm的微调提供了基础，并进一步允许其与神经网络的性能比较。预训练的slm / llm表现出较差的性能（F1接近0），而微调后的slm / llm表现出显著提高的性能（F1高达0.99）。微调包括不同维度的特征组：基于温度的低维（FG1）、基于hrv的中维（FG2）和多模态高维（FG3）。与基于温度的特征（FG1, NN: 0.45, SLM: 0.42, LLM: 0.43）相比，结合HRV特征显著提高了精度（FG2, NN: 0.73, SLM: 0.93, LLM: 0.96），而多模态特征取得了近乎完美的性能（FG3, NN: 0.91, SLM/LLM: 0.99）。总的来说，我们的发现为模型选择提供了明确的指导。由于具有低维特征，神经网络提供了最佳性能。然而，这三种模型的总体准确性仍然很低。对于中高维数据，简单的神经网络架构以最小的成本提供了令人满意的性能，实现了在物联网设备上的高效部署。微调后的slm进一步提高了性能，获得了与微调后的llm相当的近乎完美的结果，但成本却低得多。因此，对于未来以人为中心的个人调节，我们建议使用中到高维数据与神经网络一起作为成本效益高、性能中等的解决方案，或者使用微调的slm作为高性能、成本中等的解决方案。

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引用次数: 0

Risk of cross-infection in a four-bed hospital ward with synthetic fountain jet ventilation in winter 冬季合成喷射器通风四床病房交叉感染风险分析

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

Building and Environment

Pub Date : 2025-12-29 DOI: 10.1016/j.buildenv.2025.114176

Teng Li , Jiangang Lei , Jianjian Wei , Yong Cheng

An innovative air distribution, synthetic fountain jet ventilation (SFV), was proposed in this study to reduce cross-infection risk in hospital wards in winter. A computational fluid dynamics (CFD) method validated by experimental data was employed to investigate airflow pattern and exhaled particle dispersion in a four-bed ward under SFV and two configurations of mixing ventilation (MV). Zoning effect on particles under SFV was quantified using the concentration gradient between sub-zones (η). The significance and correlation of supply air velocity (V_s), supply air temperature (T_s), and supply inlet height (H_s) with the zoning effect were statistically evaluated. An improved Wells-Riley model was employed to quantify the potential of SFV in reducing the cross-infection risk. Results showed that upward fountain jet under SFV followed the direction of positive buoyancy, thereby restricting lateral and longitudinal dispersion of exhaled particles in winter. The zoning effect was significantly affected by V_s and the average air velocity in the central zone (V_ave). A highly significant positive correlation was found between η and V_ave (p < 0.01), as V_ave significantly affected particle removal and suspension. A “vertical air channel” formed between the ceiling-level outlet and the floor under a high V_ave, enhancing particle removal whilst reducing particle suspension. Calculations of infection probability demonstrated that SFV effectively reduced the risk of cross-infection among patients in winter. Compared with the two configurations of MV, the average infection probability in Sub-zones 2, 3, and 4 located outside the source zone under SFV was reduced by 55.04% and 76.52%, respectively.

本研究提出了一种创新的气流组织——合成喷泉喷射通风（SFV），以降低冬季医院病房的交叉感染风险。采用经实验验证的计算流体力学（CFD）方法研究了四床病房在SFV和两种混合通风（MV）配置下的气流模式和呼出颗粒的分散。利用分区间浓度梯度（η）量化了SFV作用下颗粒的分区效应。统计评价送风速度（Vs）、送风温度（Ts）和送风入口高度（Hs）与分区效果的显著性和相关性。采用改进的Wells-Riley模型来量化SFV在降低交叉感染风险方面的潜力。结果表明：冬季气流下喷流沿正浮力方向向上，限制了呼出颗粒的横向和纵向扩散；分带效应受v和中心区平均风速（Vave）的影响显著。η与Vave之间存在极显著的正相关关系（p < 0.01），因为Vave对颗粒去除和悬浮有显著影响。在高气阀下，在天花板出口和地板之间形成“垂直风道”，增强颗粒去除同时减少颗粒悬浮。感染概率计算表明，SFV有效降低了冬季患者间交叉感染的风险。与两种MV配置相比，SFV源区外2、3、4分区的平均感染概率分别降低了55.04%和76.52%。

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