这是用户在 2025-1-12 24:36 为 https://app.immersivetranslate.com/pdf-pro/8782de5b-5b88-4a36-9284-e021bddeb5b1 保存的双语快照页面，由 沉浸式翻译 提供双语支持。了解如何保存？
Review Article  评论文章

From BIM to computational BIM: A systematic review of visual programming application in building research
从BIM到计算BIM：可视化编程在建筑研究中的应用系统综述

Taki Eddine Seghier a a  ^("a "){ }^{\text {a }}, Chavanont Khosakitchalert b,** b,**  ^("b,** "){ }^{\text {b,** }}, Ziwen Liu c,d c,d  ^("c,d "){ }^{\text {c,d }}, Chukwuka Christian Ohueri e e ^(e){ }^{\mathrm{e}}, Yaik-Wah Lim f , g f , g ^(f,g){ }^{\mathrm{f}, \mathrm{g}}, Ahmad Fahmi Bin Zainazlan h , i h , i ^(h,i){ }^{\mathrm{h}, \mathrm{i}}
Taki Eddine Seghier a a  ^("a "){ }^{\text {a }} 、Chavanont Khosakitchalert b,** b,**  ^("b,** "){ }^{\text {b,** }} 、Ziwen Liu c,d c,d  ^("c,d "){ }^{\text {c,d }} 、Chukwuka Christian Ohueri e e ^(e){ }^{\mathrm{e}} 、Yaik-Wah Lim f , g f , g ^(f,g){ }^{\mathrm{f}, \mathrm{g}} 、Ahmad Fahmi Bin Zainazlan h , i h , i ^(h,i){ }^{\mathrm{h}, \mathrm{i}} a a  ^("a "){ }^{\text {a }} Department of Architecture, Effat University, Jeddah 22332, Saudi Arabia
a a  ^("a "){ }^{\text {a }} 建筑系，埃法特大学，吉达22332，沙特阿拉伯 b b ^(b){ }^{\mathrm{b}} Department of Architecture, Faculty of Architecture, Chulalongkorn University, Bangkok, Thailand
b b ^(b){ }^{\mathrm{b}} 泰国曼谷朱拉隆功大学建筑学院建筑系 c c  ^("c "){ }^{\text {c }} Department of the Built Environment, College of Design and Engineering, National University of Singapore, 4 Architecture Drive, 117566, Singapore
c c  ^("c "){ }^{\text {c }} 新加坡国立大学建筑环境学院，地址：4 Architecture Drive，117566，新加坡 d d ^(d){ }^{\mathrm{d}} BuildingSMART China (bSC), 9 Shouti Road South, Haidian District, Beijing 100044, China
中国北京市海淀区朝阳南路9号智造大厦0#楼（bSC）100044 e e  ^("e "){ }^{\text {e }} Department of Construction Project Management, School of Housing, Building and Planning, Universiti Sains Malaysia (USM), 11800 Penang, Malaysia
e e  ^("e "){ }^{\text {e }} 马来西亚Sains大学（USM）住房、建筑和规划学院建筑项目管理系，11800 Penang，Malaysia f f ^(f){ }^{\mathrm{f}} Department of Architecture, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Johor Bahru, Malaysia
f f ^(f){ }^{\mathrm{f}} 马来西亚科技大学建筑环境与测量学院建筑系，柔佛巴鲁，马来西亚 g g ^(g){ }^{\mathrm{g}} Centre for the Study of Built Environment in the Malay World (KALAM), Institute for Smart Infrastructure and Innovative Construction (ISIIC), UTM, Malaysia
g g ^(g){ }^{\mathrm{g}} 马来世界建筑环境研究中心（KALAM），智能基础设施和创新建筑研究所（ISIIC），UTM，马来西亚 h h  ^("h "){ }^{\text {h }} School of Architecture, Building and Design, Taylor's University, Malaysia
h h  ^("h "){ }^{\text {h }} 马来西亚泰勒大学建筑与设计学院 i i ^(i){ }^{\mathrm{i}} College of Creative Arts, Universiti Teknologi MARA, 40450 Shah Alam, Selangor Darul Ehsan, Malaysia
i i ^(i){ }^{\mathrm{i}} 创意艺术学院，Universiti Teknologi MARA，40450 Shah Alam，Selangor Darul Ehsan，Malaysia

ARTICLE INFO  产品信息

Keywords:  保留字：

Computational design  计算设计
Building information modelling
建筑信息模型
Algorithm  算法
Generative design  生成设计
Automation  自动化
Parametric  参数化

Abstract  摘要

The architecture, engineering, construction, and operation (AECO) industry has embraced the combination of building information modelling (BIM) and computational algorithms to advance digital transformations. Computational BIM has enabled the development and testing of various BIM-based solutions for the building industry. This study conducted a systematic review of the application of computational BIM through visual programming (VP) in building research. The study employed a hybrid approach of bibliometrics and content analyses using seventy-nine publications filtered from Scopus and Web of Science databases. The bibliometric analysis identified publication frequency trends, journal distributions, country distributions, eminent authors, coauthorship networks, and keyword co-occurrence networks. The content analysis identified six key research themes and four major methodological roles of computational BIM in building research. A research framework is proposed to summarize and articulate the state of the art of computational BIM application in building research, research gaps, and future research directions.
建筑、工程、施工和运营（AECO）行业已经接受了建筑信息建模（BIM）和计算算法的结合，以推进数字化转型。计算BIM为建筑行业开发和测试各种基于BIM的解决方案提供了可能。本研究通过可视化编程（VP）对计算BIM在建筑研究中的应用进行了系统的回顾。该研究采用了文献计量学和内容分析的混合方法，使用了从Scopus和Web of Science数据库中筛选出的79种出版物。文献计量学分析确定了出版频率趋势，期刊分布，国家分布，著名作者，合著网络和关键词共现网络。内容分析确定了计算BIM在建筑研究中的六个关键研究主题和四个主要方法论角色。 提出了一个研究框架，总结和阐述了计算BIM在建筑研究中的应用，研究差距和未来的研究方向的艺术状态。

1. Introduction  1.介绍

Since the invention of computer-aided design (CAD), the architecture, engineering, construction, and operation (AECO) industry has been enhanced by computer technology. Building design has moved from drawings on paper to drafting on computers. As technology developed, building information can be represented as 3D digital models, and building data can be stored and categorized in a computer database, which led to the emergence of the concept of object-oriented modelling, nowadays known as building information modelling (BIM) [1].
自从计算机辅助设计（CAD）发明以来，建筑、工程、施工和运营（AECO）行业已经通过计算机技术得到了加强。建筑设计已经从纸上绘图转向计算机绘图。随着技术的发展，建筑信息可以表示为3D数字模型，建筑数据可以在计算机数据库中存储和分类，这导致了面向对象建模概念的出现，现在被称为建筑信息建模（BIM）[1]。
BIM is a collaborative process of using a digital representation of a building as a reliable source of information for assisting design, construction, and operation-related decisions [2]. Nowadays, BIM has become mainstream in the AECO industry and is increasingly adopted to
BIM是一个协作过程，使用建筑物的数字表示作为可靠的信息来源，以协助设计，施工和运营相关的决策[2]。如今，BIM已成为AECO行业的主流，并越来越多地被采用，
empower digital transformation in the built environment, which is usually regarded as poor performing compared to other industries [3]. BIM can assist practitioners from the conceptual design phase to the operation phase [4]. During the design and construction phases, BIM can be used for visualization, analysing building performances, documentation, checking clashes among disciplines, and estimating the construction cost [5]. Additionally, BIM can provide an accurate data source for managing building assets during the operation phase. Moreover, BIM can be used as a digital archive of historic buildings, providing a reliable conservation or monitoring source of information.
在建筑环境中实现数字化转型，与其他行业相比，这通常被认为是表现不佳的[3]。BIM可以帮助从业者从概念设计阶段到运营阶段[4]。在设计和施工阶段，BIM可用于可视化，分析建筑性能，记录，检查学科之间的冲突，并估计施工成本[5]。此外，BIM还可以为运营阶段的建筑资产管理提供准确的数据源。此外，BIM可用作历史建筑的数字档案，提供可靠的保护或监控信息来源。
Working with BIM is dealing with data and geometries. On the one hand, modelling geometries while managing building data can be challenging since buildings nowadays are complex and have various components generated by many disciplines in different stages of the
使用BIM是处理数据和几何图形。一方面，在管理建筑物数据的同时对几何形状进行建模可能是具有挑战性的，因为当今的建筑物是复杂的，并且具有由许多学科在建筑的不同阶段生成的各种组件。
project lifecycle. The issue in modelling complex geometries can be solved by applying computational algorithms in the modelling process [6]. Computational algorithms are also used in parametric design or parametric modelling, in which the process of creating geometries is tied with manipulable variables. On the other hand, managing BIM data could be time-consuming and error-prone because the BIM model contains many data. Therefore, computational algorithms for automated data processing should be developed and applied to improve the data management process in the BIM environment [7].
项目生命周期。复杂几何形状建模的问题可以通过在建模过程中应用计算算法来解决[6]。计算算法也用于参数化设计或参数化建模，其中创建几何形状的过程与可操纵变量联系在一起。另一方面，管理BIM数据可能非常耗时且容易出错，因为BIM模型包含许多数据。因此，应开发和应用自动数据处理的计算算法，以改善BIM环境中的数据管理过程[7]。
It is argued that efficient modelling, data management and automation of the different tasks in the BIM environment cannot be achieved with conventional BIM workflows and without enabling customized computational algorithms within existing BIM software [6,8-10]. As a result, most BIM software developers nowadays provide an open Application Programming Interface (API) for their software to hasten product development, enable customized computational workflows, and involve the BIM community in the development process [11]. Consequently, in the last decade, the concept of “Computational BIM” emerged in the AECO industry. Computational BIM is the innovative problem-solving approach where computational algorithms are developed to manage BIM model-related information to improve work efficiency, effectiveness, and productivity gains [12,13]. Computational BIM entails the integration of algorithms, parametric modeling, and visual programming within the BIM framework to automate tasks, manage dynamic data, and optimize design processes [12,13]. This approach enables more efficient workflows, design optimization, performance analysis, and handling of complex iterative processes that would be challenging or time-consuming using traditional BIM methods. There are different tools and workflows for developing computational algorithms in the BIM environment; however, they all interact with the BIM software’s API [12].
有人认为，BIM环境中不同任务的有效建模、数据管理和自动化无法通过传统的BIM工作流程实现，也无法在现有的BIM软件中启用定制的计算算法[6，8 -10]。因此，现在大多数BIM软件开发人员为其软件提供开放的应用程序编程接口（API），以加速产品开发，实现定制的计算工作流程，并使BIM社区参与开发过程[11]。因此，在过去的十年中，“计算BIM”的概念出现在AECO行业。计算BIM是一种创新的解决问题的方法，其中开发了计算算法来管理BIM模型相关信息，以提高工作效率，有效性和生产力收益[12，13]。 计算BIM需要在BIM框架内集成算法，参数化建模和可视化编程，以自动化任务，管理动态数据并优化设计流程[12，13]。这种方法可以实现更高效的工作流程、设计优化、性能分析以及处理复杂的迭代过程，而使用传统的BIM方法将是一项挑战或耗时的工作。在BIM环境中开发计算算法有不同的工具和工作流程;然而，它们都与BIM软件的API交互[12]。
The API allows practitioners and researchers to customise the BIM software by creating new functionalities to solve different problems and enhance AECO industry productivity (e.g., automating repetitive tasks and improving interoperability and data management) [14]. According to Wortmann and Tunçer [6], there are four primary programming paradigms employed in the AECO industry applied in the customization process of BIM software through the API: (1) objected-oriented programming, (2) functional programming, (3) Distributed visual data flow programming and (4) visual programming. Object-oriented programming constructs computer programs into objects made of data and operations, while functional programming constructs them into nested operations using higher-order functions [15]. Distributed visual data flow programming combines several visual programs into a more extensive network. Despite the advantages of these approaches, skill is an essential barrier to the broader adoption of textual and visual data flow programming in practice and research [6]. Visual programming (VP) environments, such as Dynamo and Grasshopper, allow users to create a computer program by connecting predefined visual nodes to form computational algorithms instead of typing texts [13,16,17]. VP was developed to be more user-friendly, simple to learn, and easy to design algorithms. As a result, researchers and practitioners with nonprogramming backgrounds have usually selected VP tools for developing their computational algorithms in a BIM environment [18].
API允许从业者和研究人员通过创建新功能来定制BIM软件，以解决不同的问题并提高AECO行业的生产力（例如，自动化重复性任务并改进互操作性和数据管理）[14]。根据Wortmann和Tunçer [6]的说法，AECO行业通过API应用于BIM软件的定制过程中的主要编程范式有四种：（1）面向对象编程，（2）函数编程，（3）分布式可视化数据流编程和（4）可视化编程。面向对象编程将计算机程序构造成由数据和操作组成的对象，而函数式编程使用高阶函数将它们构造成嵌套操作[15]。分布式可视化数据流编程将多个可视化程序组合成一个更广泛的网络。 尽管这些方法具有优势，但技能是在实践和研究中更广泛采用文本和可视化数据流编程的重要障碍[6]。可视化编程（VP）环境，如Dynamo和Grasshopper，允许用户通过连接预定义的可视化节点来创建计算机程序，以形成计算算法，而不是键入文本[13，16，17]。VP被开发成更加用户友好，简单易学，易于设计算法。因此，具有非编程背景的研究人员和从业人员通常选择VP工具在BIM环境中开发其计算算法[18]。
In recent years, VP has increasingly become a subject of study in the AECO industry [19], and it is becoming a solution-oriented tool for various computational BIM topics in practice and research fields. Furthermore, recent study findings revealed that “visual programming” was among the key emerging themes in BIM-related research [20]. It is worth noting that VP has been widely used in the CAD environment in the last fifteen years (since the integration of the first version of Grasshopper to Rhino 3D by David Rutten at Robert McNeel & Associates in 2007). The main goal of its usage at that time was to manipulate the geometry of the design parametrically and perform specific analyses (e. g., environmental and structural analysis) [8]. However, nowadays, with the wide adoption of the BIM approach and technology, the role of
近年来，VP越来越多地成为AECO行业的研究主题[19]，它正在成为实践和研究领域各种计算BIM主题的解决方案导向工具。此外，最近的研究结果显示，“视觉编程”是BIM相关研究中的关键新兴主题之一[20]。值得一提的是，VP在过去的十五年中已经被广泛应用于CAD环境中（自2007年Robert McNeel & Associates的大卫·鲁顿（David Rutten）将Grasshopper的第一个版本集成到Rhino 3D以来）。当时使用它的主要目标是参数化地操纵设计的几何形状并执行特定的分析（例如，例如，在一个实施例中，环境和结构分析[8]。然而，如今，随着BIM方法和技术的广泛采用，
VP has expanded to more aspects related to data management, process automation, and computation, which have opened new possibilities in this research area.
VP已经扩展到与数据管理，过程自动化和计算相关的更多方面，这为该研究领域开辟了新的可能性。
Despite the promising applications of computational BIM using VP in the AECO industry, there has been no comprehensive literature review on its application to solve different problems in the built environment, particularly building projects. It is argued that adopting VP-enabled computational BIM algorithms in the AECO industry has created more opportunities for scholars to develop and test innovative solutions for the AECO industry than ever before. This will eventually speed up the digital transformation in the AECO industry and, therefore, contribute to achieving Construction 4.0, which aims to digitize the construction industry [3].
尽管在AECO行业中使用VP的计算BIM的应用前景广阔，但尚未对其应用进行全面的文献综述，以解决建筑环境中的不同问题，特别是建筑项目。有人认为，在AECO行业中采用支持VP的计算BIM算法为学者们创造了比以往任何时候都更多的机会来开发和测试AECO行业的创新解决方案。这将最终加速AECO行业的数字化转型，从而有助于实现旨在改善建筑行业的建筑4.0。
Consequently, this paper reviews existing literature on applying computational BIM via VP in building research. It is only limited to research works dealing with building projects (see Fig. 1). Articles focusing on other projects in the AECO industry, such as infrastructure projects, are out of the scope of this study. However, computational BIM application in infrastructure projects has been recently reviewed in the work of Collao et al. [10]. The objectives of this article are as follows. First, to identify the current trends and approaches of computational BIM application in building research. Second, to characterize the methodological role of computational BIM enablers, mainly VP, in these research works. Last, to develop a research framework to address the research gaps and challenges in implementing computational BIM workflows in building research.
因此，本文回顾了现有的文献中应用计算BIM通过VP在建筑研究。它仅限于处理建筑项目的研究工作（见图1）。关注AECO行业其他项目（如基础设施项目）的文章不在本研究范围内。然而，Collao等人的工作最近对基础设施项目中的计算BIM应用进行了审查。[10]。本文的目的如下。首先，确定计算BIM在建筑研究中应用的当前趋势和方法。其次，在这些研究工作中，描述计算BIM使能者（主要是VP）的方法论作用。最后，开发一个研究框架，以解决在建筑研究中实施计算BIM工作流程的研究差距和挑战。
This systematic review contributes to the literature by clarifying how traditional BIM can be extended by integrating visual programming within the BIM environment, highlighting its unique role in enhancing automation, parametric design, and performance optimization. In practice, this study provides practitioners with a clear pathway for understanding how visual programming optimizes BIM workflows, automates repetitive tasks, and improves data manipulation, offering actionable insights for implementing computational BIM to address complex design and construction challenges more efficiently. This paper begins with the introduction in section 1 . Section 2 describes the review methodology. Section 3 is the results of descriptive statistics and bibliometric analysis. Section 4 presents the thematic analysis of computational BIM application in building research. Section 5 describes the methodological role of VP-enabled computational BIM in the reviewed studies. Section 6 discusses the future research agendas, and section 7 summarizes our conclusions.
这一系统性综述有助于文献澄清如何传统的BIM可以通过集成可视化编程BIM环境中扩展，突出其在增强自动化，参数化设计和性能优化的独特作用。在实践中，这项研究为从业者提供了一个清晰的途径，了解可视化编程如何优化BIM工作流程，自动化重复任务，并改善数据操作，为实施计算BIM提供可操作的见解，以更有效地解决复杂的设计和施工挑战。本文从第一部分的引言开始。第2节描述了审查方法。第三部分是描述性统计和文献计量分析的结果。第四部分介绍了计算BIM在建筑研究中的应用的专题分析。第5节描述了VP支持的计算BIM在回顾研究中的方法学作用。 第6节讨论了未来的研究议程，第7节总结了我们的结论。
Fig. 1. Scope of the study.
图1.研究范围。

2. Material and methods  2.材料和方法

2.1. Paper retrieval  2.1.论文检索

Because of the immense increase in the number of research outputs in the body of knowledge, it is challenging to determine what work has been done in a field of study. Therefore, a systematic review is usually employed and defined as “the application of scientific strategies that limit bias by the systematic assembly, critical appraisal and synthesis of all relevant studies on a specific topic” [21]. Furthermore, a systematic review is considered one of the "most reliable and comprehensive
由于知识体系中研究成果的数量大幅增加，确定在某个研究领域中完成了哪些工作是一项挑战。因此，系统性综述通常被采用并定义为“通过系统组装、批判性评估和综合所有特定主题相关研究来限制偏倚的科学策略的应用”[21]。此外，系统性综述被认为是“最可靠和最全面的
statements regarding what has been accomplished in a specific field [22]. In this study, the overall systematic review methodology was designed based on the guidelines by Kitchenham and Charter [23]. According to this guideline, there are two main reasons for performing systematic literature reviews: 1) to reveal any gaps in current research to suggest areas for further study and 2) to establish a research framework/ background in order to position new research investigations appropriately.
在特定领域取得的成就[22]。在本研究中，根据Kitchenham和Charter [23]的指南设计了总体系统评价方法。根据该指南，进行系统性文献综述有两个主要原因：1）揭示当前研究中的任何差距，以建议进一步研究的领域; 2）建立研究框架/背景，以便适当定位新的研究调查。
To ensure transparency and complete reporting of systematic reviews and meta-analyses, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [24] were used to
为了确保系统性综述和荟萃分析的透明度和完整报告，使用系统性综述和荟萃分析首选报告项目（PRISMA）指南[24]，
Fig. 2. Literature search and screening strategy based on PRISMA guidelines [24].
图2.基于PRISMA指南的文献检索和筛选策略[24]。
    • Corresponding author.  通讯作者。
    E-mail addresses: taseghier@effatuniversity.edu.sa (T.E. Seghier), Chavanont.k@chula.ac.th (C. Khosakitchalert).
    电子邮件地址：taseghier@effatuniversity.edu.sa（T.E. Seghier），Chavanont. chula.ac.th（C. Khosakitchalert）。