Building and Environment最新文献_第6页

Environmental chamber analysis of objective volatile organic compounds emissions and subjective olfactory perception from main automotive interior components 对汽车内饰主要部件的客观挥发性有机化合物排放和主观嗅觉感知进行环境室分析

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-09-30 DOI: 10.1016/j.buildenv.2024.112136

This study examined the emissions of volatile organic compounds (VOCs) and their associated odors from five key automotive interior components: door panels, weatherstrips, seats, headliners, and carpets. Objective VOC emissions and subjective odor evaluations were conducted in an environmental chamber with controlled temperature, humidity, and ventilation rates. VOC analysis revealed that alkanes and aromatic compounds were the predominant emissions, together accounting for 43 %–61 % of the total number of emission types. Other notable emissions included aldehydes and ketones. The overlap in the emitted compounds was substantial, with 13 % of the compounds being universally emitted, 42 % emitted by two or more components, and 45 % unique to individual components. Subjective odor evaluations identified distinct odor fingerprints for each component, with weatherstrips having the highest odor intensity and headliners having the lowest. Perceived pleasantness (PP) ratings were generally negative, indicating the unappealing nature of the odors. Odor activity value (OAV) analysis showed a weak linear relationship with odor intensity, particularly because of the negative correlation in weatherstrips, suggesting significant masking or enhancement effects among odor molecules. Aldehydes and acids were the major contributors to OAV, whereas alkanes, which are often overlooked, were also significant because of their high emission levels.

这项研究检测了门板、耐候胶条、座椅、顶篷和地毯这五种主要汽车内饰部件的挥发性有机化合物（VOC）排放量及其相关气味。客观挥发性有机化合物排放和主观气味评估是在一个温度、湿度和通风率均受控的环境室中进行的。挥发性有机化合物分析表明，烷烃和芳香族化合物是主要的排放物，共占排放物类型总数的 43 %-61 %。其他值得注意的排放物包括醛和酮。排放化合物的重叠率很高，其中 13% 的化合物是普遍排放，42% 由两个或更多组件排放，45% 为单个组件独有。主观气味评估确定了每个部件的独特气味指纹，其中耐候胶条的气味强度最高，顶篷的气味强度最低。感知愉悦度（PP）一般为负值，表明气味不令人愉悦。气味活性值（OAV）分析表明，气味活性值与气味强度呈微弱的线性关系，特别是在挡风玻璃上呈负相关，这表明气味分子之间存在明显的掩蔽或增强效应。醛类和酸类是造成 OAV 值的主要因素，而经常被忽视的烷类由于其排放水平较高，也对 OAV 值产生了重要影响。

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引用次数: 0

Early-stage design support for ice-shell architecture with integrated snow drift simulation tool 冰壳结构的早期设计支持，集成雪漂移模拟工具

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-09-30 DOI: 10.1016/j.buildenv.2024.112143

The data on snow distribution on roofs can aid in optimizing the weatherability of ice-shell architecture. However, there is currently a lack of technology for predicting snow drift in early-stage design. The study proposes a snow drift simulation method for ice shells, utilizing Butterfly to call the OpenFOAM solver. A snow drift simulation tool based on this method was developed and validated through three case studies. The validation results provide suggestions for mesh accuracy and time steps for typical ice-shell architecture simulation with the tool. Simulation results from the tool are used to analyze the impact of ice-shell architectural specific features (texture, plane, orientation) on weatherability, focusing on the coupling optimization of snow and radiation for typical ice shells. The study demonstrates the tool's effectiveness, simplifying the simulation process and extending its applicability to other cold-region buildings. The feature analysis indicates that the ribbed texture more effectively blocks solar radiation through snow distribution.

屋顶积雪分布数据有助于优化冰壳建筑的耐候性。然而，目前还缺乏在早期设计阶段预测雪飘移的技术。本研究提出了一种冰壳雪漂移模拟方法，利用 Butterfly 调用 OpenFOAM 求解器。基于该方法开发了雪漂移模拟工具，并通过三个案例研究进行了验证。验证结果为使用该工具进行典型冰壳结构模拟的网格精度和时间步骤提供了建议。该工具的模拟结果用于分析冰壳建筑的具体特征（纹理、平面、方向）对耐候性的影响，重点是典型冰壳的雪和辐射耦合优化。这项研究证明了该工具的有效性，简化了模拟过程，并将其适用性扩展到其他寒冷地区的建筑。特征分析表明，肋状纹理能更有效地通过雪的分布阻挡太阳辐射。

引用次数: 0

Machine learning-based surrogate models for fast impact assessment of a new building on urban local microclimate at design stage 基于机器学习的代用模型，用于在设计阶段快速评估新建筑对城市局部小气候的影响

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-09-30 DOI: 10.1016/j.buildenv.2024.112142

The rapid urbanization introduces changes in the local urban microclimate. Many efforts have been paid on the impact assessment of building design on local microclimate. However, there is still a lack of efficient and accurate prediction method for assessing the impacts on local microclimate when making the design of individual buildings. Two complementary machine learning-based surrogate models are proposed, including an SVR-based local air temperature model and a LightGBM-based local wind velocity model. They are identified by evaluating and comparing eight alternative machine learning models, four for each model development. 200 sets of CFD simulation data corresponding to different building designs are used for the model training and validation. The results show that the developed surrogate models can dramatically reduce computation time (from over 5 h to less than a second for a single prediction) while keeping the same order of accuracy of CFD simulations for local microclimate prediction of individual buildings. It therefore facilitates the fast, comprehensive and accurate prediction of the impacts on the local microclimate at the early design stage of new construction and renovation of individual buildings, for designers to deliver preferred local microclimate and/or avoid unacceptable microclimate changes.

快速城市化带来了当地城市小气候的变化。人们在评估建筑设计对当地小气候的影响方面做了很多努力。然而，在评估单个建筑设计对当地小气候的影响时，仍然缺乏高效、准确的预测方法。本文提出了两种基于机器学习的互补代用模型，包括基于 SVR 的局部气温模型和基于 LightGBM 的局部风速模型。通过评估和比较八个可供选择的机器学习模型（每个模型开发四个），确定了这两个模型。模型的训练和验证使用了 200 组不同建筑设计的 CFD 模拟数据。结果表明，所开发的代用模型可显著缩短计算时间（单次预测时间从 5 小时以上缩短到 1 秒以内），同时保持与单个建筑物局部微气候预测 CFD 模拟相同的精度等级。因此，它有助于在新建建筑和单体建筑翻新的早期设计阶段快速、全面、准确地预测对当地微气候的影响，以便设计师提供理想的当地微气候和/或避免不可接受的微气候变化。

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引用次数: 0

Evaluating common supply air temperature setpoint reset strategies with varying occupancy patterns and behaviours 评估不同占用模式和行为下的普通送风温度设定点重设策略

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-09-28 DOI: 10.1016/j.buildenv.2024.112129

The supply air temperature (SAT) setpoint of a multi-zone variable air volume (VAV) air handling unit (AHU) systems significantly affects the system’s performance. ASHRAE Guideline 36 introduces a so-called trim and respond logic defining the SAT reset behaviour of these systems. The trim and respond logic for SAT reset relies on demand-based feedback. Many studies have assessed ASHRAE Guideline 36, however there is a literature gap in addressing the performance of the trim and respond SAT reset with varying occupancy patterns and behaviours. This paper studies four SAT reset strategies under different thermal preferences and irregular occupancy patterns: (1) constant 13°C SAT, (2) SAT reset based on outdoor air temperature (OAT), (3) trim and respond, and (4) trim and respond combined with OAT reset. Different cases of zone-level setpoints and irregular occupancy schedules have been simulated in EnergyPlus with the studied SAT setpoint reset methods. The results show that varying setpoints across different zones lead to higher energy use with all studied SAT reset strategies. The highest variation in energy use was accompanied with constant SAT, with a standard deviation of 16

{kWh/m}^{2}

, and the highest variation in averaged discomfort fraction was accompanied with OAT reset, with a standard deviation of 5.3%. Both trim and respond methods achieved better comfort results with varying setpoints. These findings establish a basis for future work on developing a SAT reset strategy that utilizes occupant-centric control (OCC) that optimally balances thermal comfort and energy use.

多区变风量（VAV）空气处理机组（AHU）系统的送风温度（SAT）设定点会对系统性能产生重大影响。ASHRAE 指南 36 引入了所谓的 "调整和响应逻辑"，定义了这些系统的 SAT 复位行为。SAT 复位的调整和响应逻辑依赖于基于需求的反馈。许多研究都对 ASHRAE 准则 36 进行了评估，但在研究不同占用模式和行为下的微调和响应 SAT 重置性能方面还存在文献空白。本文研究了不同热偏好和不规则占用模式下的四种 SAT 重置策略：（1）恒定 13°C SAT，（2）基于室外空气温度（OAT）的 SAT 重置，（3）微调和响应，以及（4）微调和响应与 OAT 重置相结合。利用所研究的 SAT 设定点重置方法，在 EnergyPlus 中模拟了区域级设定点和不规则占用时间表的不同情况。结果表明，在所有研究的 SAT 重置策略中，不同分区的设定点变化会导致更高的能耗。恒定 SAT 的能耗变化最大，标准偏差为 16 kWh/m2，OAT 重置的平均不适度变化最大，标准偏差为 5.3%。在设定点变化的情况下，微调法和响应法都能获得更好的舒适度。这些研究结果为今后开发 SAT 重置策略奠定了基础，该策略利用了以居住者为中心的控制（OCC），能够优化热舒适度和能源使用之间的平衡。

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引用次数: 0

Instant infrared: Estimating urban surface temperatures from street view imagery 即时红外线从街景图像估算城市地表温度

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-09-28 DOI: 10.1016/j.buildenv.2024.112122

As the impact of climate change on cities intensifies, the analysis and modeling of the urban microclimate are becoming increasingly important. A key parameter to this end is the estimation of urban surface temperatures. Traditional approaches for such estimates, that use urban micrometeorology models, are based on simulations that require heavy computations and complex inputs — including urban geometry, radiative parameters, and meteorological conditions. As a result, they cannot be applied extensively in all cities, where some of the input parameters might be missing and computational power might not be available. In this paper, we propose an alternative approach founded upon a deep learning framework, requiring markedly simplified inputs: street view imagery and meteorological conditions. We use our model to estimate building facade surface temperatures in the city of London (Ontario, Canada) and compare results both with simulated values obtained from an established simulation software TUF-3D and ground truth data collected through an onsite campaign with a FLIR thermal imager. Results substantiate the superiority of our proposed approach over TUF-3D, concurrently emphasizing its advantages in terms of input simplicity and computational resource efficiency. As street view imagery is becoming ubiquitous across the world – for instance, through platforms such as Google Street View – our approach lays the foundation for a new paradigm of fast, cost-effective, and highly scalable models, empowering urban designers and local authorities to better understand a changing urban climate.

随着气候变化对城市影响的加剧，城市小气候的分析和建模变得越来越重要。其中一个关键参数就是城市地表温度的估算。利用城市微气象模型进行估算的传统方法是基于模拟，需要繁重的计算和复杂的输入，包括城市几何形状、辐射参数和气象条件。因此，这些方法无法广泛应用于所有城市，因为这些城市可能缺少某些输入参数，也可能没有计算能力。在本文中，我们提出了一种基于深度学习框架的替代方法，要求明显简化输入：街景图像和气象条件。我们使用我们的模型估算了伦敦市（加拿大安大略省）的建筑外墙表面温度，并将结果与从成熟的模拟软件 TUF-3D 中获得的模拟值以及通过 FLIR 热成像仪现场采集的地面实况数据进行了比较。结果证明我们提出的方法优于 TUF-3D，同时强调了其在输入简单性和计算资源效率方面的优势。随着街景图像在全球范围内变得无处不在（例如通过谷歌街景等平台），我们的方法为建立快速、经济、高度可扩展的模型新模式奠定了基础，使城市设计师和地方当局能够更好地了解不断变化的城市气候。

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引用次数: 0

Adversarial image-to-image model to obtain highly detailed wind fields from mesoscale simulations in urban environments 从城市环境中的中尺度模拟中获取高精细风场的逆向图像对图像模型

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-09-28 DOI: 10.1016/j.buildenv.2024.112123

We propose a conditional Generative Adversarial Network (cGAN) that can produce detailed local wind fields in urban areas, comparable in level of detail to those from Computational Fluid Dynamics (CFD) simulations, that are generated from coarser Numerical Weather Prediction (NWP) data.

In our approach, the cGAN is trained using NWP data as input and CFD as targets. Both CFD and NWP data are presented to the network as images, using an image-to-image model based on Pix2Pix to transform coarse meteorological conditions into detailed local wind fields.

The methodology is tested in a residential district in a large Spanish city, Zaragoza. The model predictions show significant agreement with the actual CFD results, while reducing the computational time from eight hours to seconds. Feature engineering of image channels effectively reduces the model error, especially in the wind direction, achieving a mean absolute error in the wind speed of

0.35 m/s

and a wind direction error of

27.0 °

.

我们提出了一种条件生成对抗网络（cGAN），它可以生成城市地区的详细本地风场，其详细程度可与计算流体动力学（CFD）模拟的风场相媲美，而计算流体动力学模拟是由较粗的数值天气预报（NWP）数据生成的。CFD 和 NWP 数据都以图像的形式呈现给网络，使用基于 Pix2Pix 的图像到图像模型，将粗略的气象条件转换为详细的本地风场。该方法在西班牙大城市萨拉戈萨的住宅区进行了测试。模型预测结果与实际的 CFD 结果非常吻合，同时将计算时间从 8 小时缩短到几秒钟。图像通道的特征工程可有效减少模型误差，尤其是风向误差，风速的平均绝对误差为 0.35 米/秒，风向误差为 27.0°。

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引用次数: 0

Towards sustainable living in high radiation cold climates: A two-phase genetic algorithm approach for residential building optimization 在高辐射寒冷气候中实现可持续生活：住宅建筑优化的两阶段遗传算法方法

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-09-28 DOI: 10.1016/j.buildenv.2024.112133

The High Radiation Cold (HRC) region's unique climatic conditions, characterized by high solar radiation and low air temperatures, present distinct challenges for optimizing building climate responsiveness. In this study, residential building design is bifurcated into two phases: building geometry (Phase I) and envelope design (Phase II). In Phase II, we propose a heterogeneous vertical envelope (HVE) design to suit HRC climates. This research framework establishes multiple objectives: energy efficiency, indoor comfort, and economy. It aims to identify a balanced and sustainable design by optimizing various parameters and materials using a Multi-Objective Genetic Algorithms（MOGA). The results indicate enhanced building adaptability in HAV climates through MOGA. The optimal solution in phase I results in an annual heating load of 59.12 W/m², 33.38 % annual indoor visual comfort hours and the adaptive model predicts 35.59 % annual comfort hours. Incorporating phase II optimization, the total annual energy demand is reduced by 34.42 % with an 11.35 % improvement in thermal comfort hours, culminating at 37.8 %.

高辐射寒冷地区（HRC）独特的气候条件具有太阳辐射强、气温低的特点，为优化建筑的气候响应能力带来了独特的挑战。在本研究中，住宅建筑设计分为两个阶段：建筑几何（第一阶段）和围护结构设计（第二阶段）。在第二阶段，我们提出了一种异质垂直围护结构（HVE）设计，以适应 HRC 气候。这一研究框架确立了多重目标：能源效率、室内舒适度和经济性。其目的是利用多目标遗传算法（MOGA）优化各种参数和材料，从而确定一种平衡且可持续的设计。结果表明，通过多目标遗传算法（MOGA）提高了建筑在高空气流气候下的适应性。第一阶段的最佳解决方案可实现 59.12 W/m2 的年采暖负荷，33.38 % 的年室内视觉舒适度时间，而自适应模型可预测 35.59 % 的年舒适度时间。通过第二阶段的优化，年总能源需求减少了 34.42%，热舒适度提高了 11.35%，最终达到 37.8%。

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引用次数: 0

Detailed thermal environment classification of high geothermal tunnel based on thermal comfort indices 基于热舒适指数的高地热隧道详细热环境分类

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-09-28 DOI: 10.1016/j.buildenv.2024.112135

High temperature and high humidity in geothermal tunnels pose significant risks to the well-being of construction workers. This study aims to establish critical environmental thresholds to protect workers in these challenging conditions. Field tests were conducted in a high geothermal tunnel in southwest China, continuous measuring parameters such as dry bulb temperature, relative humidity, wet bulb globe temperature (WBGT), skin temperature, and heart rate. The collected data were analyzed, leading to the development of a nonlinear programming mathematical model. This model enabled a systematic classification of the tunnel's environmental conditions and the calculation of threshold values for various environmental parameters. Furthermore, critical thresholds for heat stress indicators such as the discomfort index (DI), heat index (HI), and relative strain index (RSI) were determined. The study categorized the tunnel's hot and humid environment into five distinct zones: comfortable zone, general comfortable zone, safety zone, heat tolerance zone, and danger zone. The findings indicate that in this geothermal tunnel, the comfort zone thresholds are 26 °C for dry bulb temperature, 30 % for relative humidity, and 20 °C for the WBGT index. The safety zone thresholds are 37 °C, 64 %, and 32 °C, while the danger zone thresholds are 43 °C, 81 %, and 40 °C, respectively. For heat stress indices, the safety thresholds for DI, HI, and RSI are 25.42 °C, 26.31 °C, and 0.28, while the danger thresholds are 28.59 °C, 35.30 °C, and 0.38, respectively. This research provides essential insights for safeguarding the health of construction workers operating in high geothermal tunnel environments.

地热隧道中的高温和高湿度对建筑工人的健康构成了重大风险。本研究旨在建立关键的环境阈值，以保护在这些挑战性条件下工作的工人。在中国西南部的高地热隧道中进行了实地测试，连续测量干球温度、相对湿度、湿球温度（WBGT）、皮肤温度和心率等参数。对收集到的数据进行分析后，建立了一个非线性编程数学模型。通过该模型，可以对隧道的环境条件进行系统分类，并计算出各种环境参数的临界值。此外，还确定了热应力指标的临界阈值，如不适指数（DI）、热指数（HI）和相对应变指数（RSI）。研究将隧道的湿热环境划分为五个不同的区域：舒适区、一般舒适区、安全区、热耐受区和危险区。研究结果表明，在该地热隧道中，舒适区的阈值为干球温度 26 °C、相对湿度 30 % 和 WBGT 指数 20 °C。安全区阈值分别为 37 °C、64 % 和 32 °C，而危险区阈值分别为 43 °C、81 % 和 40 °C。在热应力指数方面，DI、HI 和 RSI 的安全阈值分别为 25.42 ℃、26.31 ℃ 和 0.28，而危险阈值分别为 28.59 ℃、35.30 ℃ 和 0.38。这项研究为保障在高地热隧道环境中工作的建筑工人的健康提供了重要启示。

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引用次数: 0

Lab study on the physiological thermoregulatory abilities of older people with different frailty levels 关于不同虚弱程度的老年人生理体温调节能力的实验室研究

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-09-27 DOI: 10.1016/j.buildenv.2024.112130

The advent of an aging society has increased the need for a better understanding of thermal comfort requirements, especially for older people's health. Differences in thermal comfort needs among older individuals with varying frailty levels are noted, but the impact of health on physiological thermoregulation is underexplored. This study, based on the frailty classification method characterized by Fried, selected 12 non-frail (age:71.00 ± 5.41) and 12 pre-frail (age:72.68 ± 5.7) older individuals for laboratory experiments. This experiment set sudden temperature change experiments to illustrate differences in subjective perceptions and physiological changes between non-frail and pre-frail older people. Results show that non-frail individuals are more likely to complain in warmer environments. Significant differences in perception only emerged when the temperature differential between neutral and warm conditions exceeded 5 °C. Pre-frail individuals exhibited slower skin temperature changes and required more time to stabilize with the environment, particularly in the foot. Pre-frail individuals tend to sweat less in changing environments and require more time to reach stable sweating. There is positive evidence indicating that heart rate of pre-frail individuals is higher than non-frail individuals, with different changing trends observed between the two groups. When the temperature difference exceeds 5 °C, the pulse intensity trend in pre-frail individuals diverges from that of non-frail individuals. In controlling indoor environments for older people, it is essential to consider both subjective comfort and physiological thermoregulation capabilities. For older adults with frailty characteristics, applying localized warming, using small temperature differences, gradually adjusting the environment may better meet their comfort needs.

随着老龄化社会的到来，人们越来越需要更好地了解热舒适需求，尤其是老年人的健康状况。人们注意到不同虚弱程度的老年人对热舒适度的需求存在差异，但对健康状况对生理体温调节的影响却缺乏深入研究。本研究根据弗里德的虚弱分类方法，选择了 12 名非虚弱（年龄：71.00 ± 5.41）和 12 名前期虚弱（年龄：72.68 ± 5.7）的老年人进行实验室实验。本实验设置了温度骤变实验，以说明非失能老年人和失能前期老年人在主观感受和生理变化方面的差异。结果表明，非失能者在较暖的环境中更容易抱怨。只有当中性和温暖环境之间的温差超过 5 °C时，感知上才会出现显著差异。虚弱前期的人皮肤温度变化较慢，需要更多时间来稳定环境温度，尤其是脚部。体弱前期的人在不断变化的环境中往往出汗较少，需要更多时间才能达到稳定出汗。有确凿证据表明，虚弱前期的人心率高于非虚弱期的人，两组人的心率变化趋势不同。当温差超过 5 °C，虚弱前人的脉搏强度趋势就会与非虚弱人的不同。在控制老年人的室内环境时，必须同时考虑主观舒适度和生理体温调节能力。对于具有虚弱特征的老年人来说，局部加温、使用小温差、逐步调节环境可能更能满足他们的舒适需求。

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引用次数: 0

Uncertainty quantification: For an IAQ and energy performance assessment method for smart ventilation strategies 不确定性量化：用于智能通风策略的 IAQ 和能效评估方法

IF 7.1 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Building and Environment

Pub Date : 2024-09-26 DOI: 10.1016/j.buildenv.2024.112115

In new low-energy buildings or buildings after thermal refurbishment, the envelope high airtightness could have an impact on air renewal and could decrease the indoor air quality (IAQ). In this context smart-ventilation systems with variable airflows could play a role in providing better IAQ without compromising the energy performance.

However, smart-ventilation strategies are quite recent, and their benefits need to be clearly quantified. This article, proposes to quantify the uncertainty of a recent multi-criteria performance assessment method, using global RBD-FAST sensitivity analysis. The impact of the pollutant emissions scenarios, model input parameters and ventilation strategies is assessed.

Five ventilation systems were studied: two constant airflow, one humidity-controlled and two humidity/CO2 controlled, applied on a French low-energy house. 2500 simulations were performed to calculate 504 sensitivity indices across 12 input variables and 9 output performance indicators. The sensitivity analysis shows that occupant bio-effluent, formaldehyde and PM2.5 emissions rates are responsible for 11 %–87 % of the uncertainty for the IAQ performance indicators. The PM2.5 deposition velocity parameter is responsible for 50 % of the uncertainty on the PM2.5 indicator, which was an unknown impact. In addition, the benefits of humidity-controlled ventilation were highlighted regarding energy performance, with, in average, 20 % lower heat-loss compared to constant airflow ventilation. Moreover, smart-ventilation provides clear IAQ benefits without drastically increasing the energy demand. This work demonstrates the potential of the proposed evaluation method for ventilation performance assessment.

在新建的低能耗建筑或经过热翻新的建筑中，围护结构的高气密性可能会影响空气的更新，并降低室内空气质量（IAQ）。在这种情况下，具有可变气流的智能通风系统可以在不影响能源性能的前提下提供更好的室内空气质量。然而，智能通风策略是最近才出现的，其好处需要明确量化。本文建议采用全局 RBD-FAST 敏感性分析方法，量化最新多标准性能评估方法的不确定性。研究了五种通风系统：两种恒定气流系统、一种湿度控制和两种湿度/二氧化碳控制，应用于法国的低能耗住宅。对 12 个输入变量和 9 个输出性能指标进行了 2500 次模拟，计算出 504 个敏感性指数。敏感性分析表明，室内空气质量性能指标的不确定性中，11%-87%与居住者的生物废水、甲醛和 PM2.5 排放率有关。PM2.5 沉积速度参数造成了 PM2.5 指标不确定性的 50%，这是一个未知影响。此外，湿度控制通风在能源性能方面的优势也得到了强调，与恒定气流通风相比，热损失平均降低了 20%。此外，智能通风在不大幅增加能源需求的情况下，还能带来明显的室内空气质量优势。这项工作证明了所提出的通风性能评估方法的潜力。

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引用次数: 0