Generation Method for HVAC Systems Design Schemes in Office Buildings Based on Deep Graph Generative Models DOI Creative Commons
Hongxin Wang,

Ruiying Jin,

Peng Xu

и другие.

Buildings, Год журнала: 2024, Номер 14(11), С. 3405 - 3405

Опубликована: Окт. 26, 2024

The design process of heating, ventilation, and air conditioning (HVAC) systems is complex time consuming due to the need follow codes. Since standards are not fixed, final outcome often depends on designer’s experience. development building information modeling (BIM) technology has made throughout lifecycle more integrated. BIM-based forward now widely used, providing a data foundation for combining HVAC system with machine learning. This paper proposes an unsupervised learning method based deep graph generative models uncover hidden patterns optimization strategies from results. We trained validated four models—GAE, GNF, GAN, diffusion—using terminal pipeline layout data. Accuracy precision metrics were used compare generated designs automated solutions, assessing models’ ability capture both local variations broader changes in logic. A graph-neural-network-based evaluation was employed measure capacity detect changes. results indicate that all achieved prediction accuracies exceeding 90% rates above 75%. effectively captured modifications by designers global changes, showing greater sensitivity adjustments than updates. When comparing actual design, it obvious accuracy predictions varies significantly complexity test buildings.

Язык: Английский

Energy Transition: Semi-Automatic BIM Tool Approach for Elevating Sustainability in the Maputo Natural History Museum DOI Creative Commons
Giuseppe Piras, Francesco Muzi

Energies, Год журнала: 2024, Номер 17(4), С. 775 - 775

Опубликована: Фев. 6, 2024

Mozambique is experiencing the consequences of a severe energy crisis with economic and social impacts. Its strict dependence on hydroelectric sources being severely tested by recent droughts that have drastically reduced water levels in dams. However, addressing poverty exploring renewable thanks to investments sector European Union. The research concerns an analysis profile country penetration energy, presenting upgrading scope through semi-automatic calculation methodology Building Information Modeling (BIM) environment. building under study, located Maputo, Natural History Museum, which plays important role biodiversity conservation. Therefore, this paper proposes BIM for sizing environmental control system tailored serve museum. proposed replaces previous one includes photovoltaic not only meets museum’s load but also supplies electricity surrounding area. Energy production from surplus 30% has been achieved. digital identified maximum gap 1.5% between dimensions duct those traditional plant design, meeting ASHRAE requirements control.

Язык: Английский

Процитировано

13
BIM-based multi-objective optimization of clash resolution: A NSGA-II approach DOI

Xinnan Liu,

Junxiang Zhao,

Yi Yu

и другие.

Journal of Building Engineering, Год журнала: 2024, Номер 89, С. 109228 - 109228

Опубликована: Апрель 6, 2024

Язык: Английский

Процитировано

6
Barriers to BIM Implementation in the HVAC Industry: An Exploratory Study DOI Creative Commons
İsmail Cengiz Yılmaz, Deniz Yılmaz,

Onur Kandemir

и другие.

Buildings, Год журнала: 2024, Номер 14(3), С. 788 - 788

Опубликована: Март 14, 2024

In recent times, the rise of urbanization, industrialization, population growth, food security, and COVID-19 pandemic have led to an increased demand for indoor spaces with efficient air conditioning systems. As a result, there is growing interest in creating more complex HVAC systems improve spaces. Building information modeling (BIM) offers numerous benefits industry, such as clash detection, budget time reductions, efficiency. However, its implementation currently hindered by various challenges. This research aims identify major barriers BIM industry Turkey, using questionnaire survey 224 domain experts working 42 different companies across fields industry. The study utilized several statistical analyses categorize prioritize most critical barriers, including reliability tests, exploratory factor analysis (EFA), confirmatory (CFA), Kaiser–Meyer–Olkin (KMO) test, Bartlett’s ranking factors (IRI). results indicate that “Deficiencies Infrastructure Lack Qualified Personnel (DIP)” group constituted significant barrier, followed “Lack Documentation Specifications (LDS)”, Case Studies Project Drawings (DCP)”, Motivation Resistance (LMR)”. Moreover, our revealed 60% participants’ allocate less than 40% their budgets technological infrastructure, which hinders adoption BIM. To promote sector, we recommend enhancing personnel capacity building, improving skills knowledge about BIM, promoting guidelines, providing free access documentation practitioners.

Язык: Английский

Процитировано

5
Design–operation gap caused by parameter variance in HVAC system control sequences: A simulation-based study on energy efficiency and temperature controllability DOI

Akari Nomura,

Shanrui Shi, Shohei Miyata

и другие.

Journal of Building Engineering, Год журнала: 2024, Номер 87, С. 109112 - 109112

Опубликована: Март 23, 2024

Язык: Английский

Процитировано

4
Review of Module Division Methods for Mechanical, Electrical, and Plumbing Systems in Construction DOI
Xuefeng Zhao,

Qiantai Yang,

Xiongtao Fan

и другие.

Journal of Building Engineering, Год журнала: 2025, Номер unknown, С. 111753 - 111753

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
An optimization design method for ductwork of air distribution systems in open spaces DOI
Xinxin Tang, Jili Zhang,

Baojun Hou

и другие.

Building and Environment, Год журнала: 2025, Номер unknown, С. 112596 - 112596

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Automated process for generating an air conditioning duct model using the CAD-to-BIM approach DOI

Seonghun Park,

Minso Shin,

Jun Young Jang

и другие.

Journal of Building Engineering, Год журнала: 2024, Номер 91, С. 109529 - 109529

Опубликована: Май 8, 2024

Язык: Английский

Процитировано

3
Generation Method for HVAC Systems Design Schemes in Office Buildings Based on Deep Graph Generative Models DOI Creative Commons
Hongxin Wang,

Ruiying Jin,

Peng Xu

и другие.

Buildings, Год журнала: 2024, Номер 14(11), С. 3405 - 3405

Опубликована: Окт. 26, 2024

The design process of heating, ventilation, and air conditioning (HVAC) systems is complex time consuming due to the need follow codes. Since standards are not fixed, final outcome often depends on designer’s experience. development building information modeling (BIM) technology has made throughout lifecycle more integrated. BIM-based forward now widely used, providing a data foundation for combining HVAC system with machine learning. This paper proposes an unsupervised learning method based deep graph generative models uncover hidden patterns optimization strategies from results. We trained validated four models—GAE, GNF, GAN, diffusion—using terminal pipeline layout data. Accuracy precision metrics were used compare generated designs automated solutions, assessing models’ ability capture both local variations broader changes in logic. A graph-neural-network-based evaluation was employed measure capacity detect changes. results indicate that all achieved prediction accuracies exceeding 90% rates above 75%. effectively captured modifications by designers global changes, showing greater sensitivity adjustments than updates. When comparing actual design, it obvious accuracy predictions varies significantly complexity test buildings.

Язык: Английский

Процитировано

0