been developed using computational BIM [42,53,56]. All these systems aimed to support decision-making regarding building envelope materials using computational BIM. However, compared to the other two systems, the one proposed by Seghier et al. [56] used a multioptimization algorithm customised in MATLAB to perform the optimization process. In addition, a study was conducted to model an architectural element using Rhinoceros and Grasshopper that forms a dynamic shell that prevents or allows the perpendicular incidence of the sun into the infrastructure at different times of the year [55].
使用计算BIM开发[42，53，56]。所有这些系统都旨在支持使用计算BIM进行建筑围护结构材料的决策。然而，与其他两个系统相比，Seghier等人提出的系统[56]使用MATLAB中定制的多重优化算法来执行优化过程。此外，还进行了一项研究，使用Rhinoceros和Grasshopper对建筑元素进行建模，形成动态外壳，防止或允许太阳在一年中的不同时间垂直入射到基础设施中[55]。

Several studies employed computational BIM optimisation algorithms to solve multi-optimization problems linked to building performance. For instance, Rahmani Asl et al. [9] developed a BIM-based framework (BPOpt) for building performance optimization. This framework allows designers to study the performance of multiple design options using Dynamo and Revit. It employs a multi-objective optimization algorithm NASG-II with two objective functions to minimize and maximise energy usage and daylight, respectively. Similarly, Seghier et al. [56] proposed a BIM-based method for retrofitting building information modelling (RBIM) to achieve a trade-off design set between two conflicting objectives: minimizing OTTV and minimizing the retrofit cost. Besides, computational BIM has been used to develop workflows for building energy usage simulation, controlling a BIM model’s response via light level sensors, and simultaneously updating shading components for a building facade based on solar angles [8]. They were also used to find the most efficient layout of the photovoltaic (PV) modules installed on building surfaces by calculating and comparing the annual cumulative radiation on PV surfaces [47]. A new method has been developed to incorporate solar thermal systems in BIM workflows
一些研究采用计算BIM优化算法来解决与建筑性能相关的多重优化问题。例如，Rahmani Asl等人[9]开发了一个基于BIM的建筑性能优化框架（BPOpt）。该框架允许设计人员使用Dynamo和Revit研究多个设计选项的性能。它采用了多目标优化算法NASG-II与两个目标函数，以最大限度地减少和最大限度地减少能源使用和日光，分别。类似地，Seghier等人[56]提出了一种基于BIM的方法，用于改造建筑信息模型（RBIM），以实现两个冲突目标之间的权衡设计集：最小化OTTV和最小化改造成本。 此外，计算BIM已被用于开发建筑能源使用模拟的工作流程，通过光照水平传感器控制BIM模型的响应，并同时根据太阳角度更新建筑立面的遮阳组件[8]。它们还用于通过计算和比较光伏表面的年累积辐射来找到安装在建筑物表面上的光伏（PV）模块的最有效布局[47]。 开发了一种新方法，将太阳能热系统纳入BIM工作流程
for the early design stage of single houses in Chile, utilizing parametric families, Dynamo, energy estimation with Ladybug and piping design in MEP [52].
在智利的独立房屋的早期设计阶段，利用参数化家庭，发电机，能量估计与瓢虫和管道设计在MEP [52]。

Various research works employed computational BIM to integrate and automate the evaluation of LCA in the BIM environment. For instance, a BIM-based tool for manufacturer-based LCA has been developed to obtain environmental profiles for decision-making in the initial design stages, requiring less time, effort and ad hoc experts [51]. Similarly, a new method was developed to calculate the LCA of the embodied carbon of the HVAC system for a new office building in Switzerland using computational BIM to combine the LCA database with BIM [48]. In addition, a multi-objective optimization algorithm was combined with BIM and LCA approaches to search for the optimum trade-off between embodied and operational energy [63]. As a result, the proposed system reduced about $65\mathrm{\%}$$65\mathrm{\%}$65%65 \% of the building’s entire life cycle energy compared to the baseline of the construction industry in Iran.
各种研究工作采用计算BIM来集成和自动化BIM环境中的LCA评估。例如，已经开发了一个基于BIM的工具，用于基于建筑师的生命周期评估，以便在初始设计阶段获得用于决策的环境概况，需要更少的时间、精力和特设专家[51]。同样，开发了一种新方法，使用计算BIM将LCA数据库与BIM联合收割机结合，计算瑞士新办公楼HVAC系统隐含碳的LCA [48]。此外，将多目标优化算法与BIM和LCA方法相结合，以寻求体现能源和运营能源之间的最佳权衡[63]。因此，与伊朗建筑业的基线相比，拟议的系统减少了建筑物整个生命周期能源的约 $65\mathrm{\%}$$65\mathrm{\%}$65%65 \% 。

Furthermore, computational BIM was employed to develop a BIMbased method to respond to the footprint and energy demand of sustainable cities by including a holistic view of the design process made possible by using lifecycle assessment (LCA) procedures and VP [60]. A BIM-based decision-making tool was developed to assist designers in evaluating several building construction solutions environmental, economic, and functional performance. The tool automates the LCA and LCC analysis during the project’s early stages by dint of VP [58].
此外，计算BIM被用于开发基于BIM的方法，通过使用生命周期评估（LCA）程序和VP [60]，包括设计过程的整体视图，以响应可持续城市的足迹和能源需求。开发了一个基于BIM的决策工具，以帮助设计师评估几种建筑施工解决方案的环境，经济和功能性能。该工具借助VP [58]在项目早期阶段自动进行LCA和LCC分析。

In terms of acoustical and thermal comfort, several methods and systems using computational BIM have been proposed. For example, a BIM-based tool has been proposed to perform acoustical analysis and
在声学和热舒适性方面，已经提出了几种使用计算BIM的方法和系统。例如，已经提出了基于BIM的工具来执行声学分析，

Fig. 6. Keyword co-occurrence network.
图6.关键词共现网络。

Table 3  表3
Key research themes of computational BIM application in building research.
计算BIM在建筑研究中应用的关键研究主题。

calculate the reverberation time (RT60) with acceptable accuracy and details for classrooms [62]. Furthermore, a BIM-based tool has been developed using VP to solve the issue of data interoperability during acoustical evaluation [59]. In contrast, Uddin et al. [57] developed a
以可接受的精度和教室细节计算混响时间（RT 60）[62]。此外，使用VP开发了一个基于BIM的工具，以解决声学评估期间的数据互操作性问题[59]。相反，Uddin等人[57]开发了一种
new framework for automatically assessing occupants’ comfort and indoor building performance using BIM and the system dynamic SD-ABM platform. Finally, Gan et al. [54] developed an integrated approach using computational BIM and virtual reality (VR) to analyse the aerodynamic design and wind comfort for modular buildings.
使用BIM和系统动态SD-ABM平台自动评估居住者舒适度和室内建筑性能的新框架。最后，Gan等人[54]开发了一种使用计算BIM和虚拟现实（VR）的集成方法，以分析模块化建筑的空气动力学设计和风舒适度。

Other studies employed computational BIM to develop systems and workflows related to building performance and analysis. For instance, a BIM-based workflow has been developed for water efficiency (WE) assessment based on Green Building Index (GBI) requirement [49]. In this workflow, Dynamo was used to develop new functionalities to overcome the current limitations of WE assessment using Revit Green Project Template (RGPT) and Autodesk Green Building Studio (GBS). Apart from that, a new BIM-based method was proposed to evaluate the flexibility level of buildings during the design phases using computational BIM [50]. The results have shown that it is possible to automatically calculate the flexibility of buildings during the design process phases. The authors claimed that the proposed method supports designers in decision-making towards more flexible and sustainable design choices. Furthermore, computational BIM was also used to develop a new method which combines BIM and web service into an integrated tool for assessing the building surroundings of the possible construction site [111]. Moreover, a previous study has developed a framework for
其他研究采用计算BIM来开发与建筑性能和分析相关的系统和工作流程。例如，已经根据绿色建筑指数（GBI）要求[49]开发了一个基于BIM的工作流程，用于水效率（WE）评估。在此工作流程中，Dynamo用于开发新功能，以克服使用Revit绿色项目模板（RGPT）和Autodesk绿色建筑工作室（GBS）进行WE评估的当前限制。除此之外，还提出了一种新的基于BIM的方法，用于使用计算BIM [50]在设计阶段评估建筑物的灵活性水平。结果表明，在设计过程阶段自动计算建筑物的灵活性是可能的。作者声称，所提出的方法支持设计师做出更灵活和可持续的设计选择。 此外，计算BIM还用于开发一种新方法，将BIM和Web服务结合到一个集成工具中，用于评估可能的施工现场的建筑环境[111]。 此外，以前的研究已经建立了一个框架，

Fig. 7. Life Cycle Stage of the application of the study.
图7.生命周期阶段的应用研究。
assessing the deconstructability of steel structures using computational BIM [45].
使用计算BIM评估钢结构的可解构性[45]。

Overall, computational BIM was used to develop new tools to analyse building performance in a more automated and customized approach. Previous studies acknowledged the advantages of VP tools in data interoperability between design and simulation software and the various simulation engines and optimization algorithms that one can choose from [9]. It is worth noting that most building performance studies which relied on simulation engines (e.g., EnergyPlus) and optimization algorithms employed Grasshopper as the VP platform. On the other hand, studies focusing more on data extraction, management, and automation (e.g., LCA analysis) used Dynamo for Revit as the VP platform.
总体而言，计算BIM被用于开发新的工具，以更自动化和定制的方式分析建筑性能。以前的研究承认VP工具在设计和仿真软件之间的数据互操作性以及各种仿真引擎和优化算法之间的优势，可以选择[9]。值得注意的是，大多数依赖于模拟引擎的建筑性能研究（例如，EnergyPlus）和优化算法采用Grasshopper作为VP平台。另一方面，研究更多地关注数据提取、管理和自动化（例如，LCA分析）使用Dynamo for Revit作为VP平台。

The application of computational BIM can evaluate a building’s performance and further optimize its design. Studies integrating computational BIM under design optimisation focused on automating the design process and optimizing the use of materials to reduce fabrication and construction wastes. For example, a study developed a structural design optimization prototype that can semi-automate tall buildings’ structural design process at the early design stages [84]. Similarly, a prototype tool for aiding the design of DIY-oriented houses was developed using computational BIM to optimize the use of timber panels, which can reduce the construction waste of timber panels by at least $50\mathrm{\%}$$50\mathrm{\%}$50%50 \% compared to the non-optimized scheme [86]. In addition, a novel BIM-based workflow using VP was proposed for construction waste reduction during the design stage by integrating modular construction (MC) and parametric design [39].
计算BIM的应用可以评估建筑物的性能并进一步优化其设计。在设计优化下整合计算BIM的研究集中在自动化设计过程和优化材料的使用，以减少制造和建筑浪费。例如，一项研究开发了一种结构设计优化原型，可以在早期设计阶段半自动化高层建筑的结构设计过程[84]。类似地，使用计算BIM开发了一种用于帮助DIY房屋设计的原型工具，以优化木材面板的使用，与非优化方案相比，这可以减少至少 $50\mathrm{\%}$$50\mathrm{\%}$50%50 \% 的木材面板建筑浪费[86]。此外，提出了一种新的基于BIM的工作流程，使用VP，通过集成模块化施工（MC）和参数化设计，在设计阶段减少建筑垃圾[39]。

Moreover, a BIM-based multi-stakeholder workflow employing VP was developed to support the design and optimization of plant walls [85]. Another study employed computational BIM and generative design to design curtain wall geometries based on predetermined parameters, such as level information, shadow zones, and cost [87]. Furthermore, using Graphisoft ArchiCAD, Rhinoceros and Grasshopper, two different workflows have been developed to generate and optimize the layout design intelligently of floor tiles globally [88,89]. Finally, another BIMbased method employed VP and used topology-based parametric modelling to reconstruct building envelopes from point clouds to retrofit building facades [90].
此外，开发了一个基于BIM的多利益相关者工作流程，采用VP来支持植物墙的设计和优化[85]。另一项研究采用计算BIM和生成式设计，根据预先确定的参数（如水平信息、阴影区和成本）设计幕墙几何形状[87]。此外，使用Graphisoft ArchiCAD，Rhinoceros和Grasshopper，开发了两种不同的工作流程，以智能地生成和优化全球地砖的布局设计[88，89]。最后，另一种基于BIM的方法采用VP并使用基于拓扑的参数化建模来从点云重建建筑物包络，以改造建筑物立面[90]。

An exploratory study was conducted on the various advantages of
对以下各种优点进行了探索性研究：
employing computational BIM-based parametric design in contemporary architectural practice through three case studies to generate, document and fabricate complex designs with greater detail and differentiation [6]. Surprisingly, a key finding of this study revealed that none of the cases industry employed the mainstream BIM (except for major structural elements). Instead, they developed customized digital workflows to manage design, prefabrication, and assembly using a CAD environment, where Rhinoceros and its VP tool, Grasshopper, were used as the main software. This is because the traditional BIM-modelling approach is not viable when dealing with complex geometry and high degrees of variation.
通过三个案例研究，在当代建筑实践中采用基于BIM的参数化设计，以生成、记录和制造具有更多细节和差异的复杂设计[6]。令人惊讶的是，这项研究的一个关键发现显示，没有一个案例行业采用了主流BIM（除了主要的结构元素）。相反，他们开发了定制的数字工作流程，使用CAD环境管理设计、预制和装配，其中Rhinoceros及其VP工具Grasshopper用作主要软件。这是因为传统的BIM建模方法在处理复杂的几何形状和高度变化时是不可行的。

Overall, the aim of the design optimization under this topic was driven by the need to reduce material waste. Additionally, most of the reviewed workflows under this topic used CAD (e.g., Rhinoceros), BIM tools (e.g., ArchiCAD) and Grasshopper as the VP tool. Moreover, parametric and generative design approaches dominated this research area.
总的来说，本主题下的设计优化目标是由减少材料浪费的需求驱动的。此外，本主题下审查的大多数工作流程都使用CAD（例如，Rhinoceros）、BIM工具（例如，ArchiCAD）和Grasshopper作为VP工具。此外，参数化和生成式设计方法主导了该研究领域。

Besides building performance and optimization, computational BIM is also applied in heritage building studies, especially when the requirements to conserve historical buildings become more complex. In HBIM-related research, 3D laser scanning is widely used to create point cloud data which is later used as the primary input for data analysis and investigation. However, converting 3D point clouds into BIM requires manual work, which is labour-intensive and time-consuming. Therefore, computational BIM algorithms in this research area are used to improve the basic process of geometric manipulation, information enhancement and interoperability of HBIM models [19].
除了建筑性能和优化，计算BIM还应用于遗产建筑研究，特别是当保护历史建筑的要求变得更加复杂时。在HBIM相关研究中，3D激光扫描被广泛用于创建点云数据，这些数据随后用作数据分析和调查的主要输入。然而，将3D点云转换为BIM需要手动工作，这是劳动密集型和耗时的。因此，该研究领域的计算BIM算法用于改进HBIM模型的几何操作、信息增强和互操作性的基本过程[19]。

Several studies investigated different methods of using computational BIM for converting point cloud data to BIM models. For instance, computational BIM-based algorithms were developed to convert point cloud data of historical buildings into 3D meshes and assign object attributes to those 3D meshes in a BIM environment [72]. Similarly, a semi-automatic method was developed to convert point cloud data into a BIM model and then integrate the BIM model with the historical data to form a knowledge model [75]. Furthermore, a study proposed an automated transformation of 3D point clouds of old wooden trusses into BIM elements using Grasshopper and an optimization algorithm [71]. In addition, research conducted by Jiang et al. [73] also focused on ancient wooden architecture, where they developed a complex algorithm using VP to reconstruct the “Dou-gong”, a Chinese architectural component, from input data. Moreover, Angulo et al. [76] conducted a virtual anastylosis of the portal of the forecourt of the old monastery of San Agustín in Seville (Spain) by combining four main technologies: digital photogrammetry, reverse engineering and computational BIM. This integration allowed the team to create BIM models to verify the feasibility of the hypothetical assembly and propose future solutions regarding missing information. Besides, computational BIM was used to develop a method to integrate point cloud data in a GIS system using a historical city as a case study [74].
几项研究调查了使用计算BIM将点云数据转换为BIM模型的不同方法。例如，开发了基于BIM的计算算法，以将历史建筑的点云数据转换为3D网格，并在BIM环境中为这些3D网格分配对象属性[72]。同样，开发了一种半自动方法，将点云数据转换为BIM模型，然后将BIM模型与历史数据集成，形成知识模型[75]。此外，一项研究提出了使用Grasshopper和优化算法将旧木桁架的3D点云自动转换为BIM元素[71]。此外，Jiang等人进行的研究[73]也集中在古代木结构建筑上，他们开发了一种复杂的算法，使用VP从输入数据中重建“斗拱”，这是一种中国建筑构件。此外，Angulo et al. [76]通过结合四种主要技术：数字摄影测量、逆向工程和计算BIM，对塞维利亚（西班牙）圣奥古斯汀老修道院前院的门户进行了虚拟分析。这种集成使团队能够创建BIM模型，以验证假设装配的可行性，并提出有关缺失信息的未来解决方案。此外，计算BIM被用于开发一种方法，将点云数据集成到GIS系统中，并将历史城市作为案例研究[74]。

Computational BIM was also employed to support decision-making regarding historical building conservation works and defect detection. For instance, an AI-based decision support system (DSS) was developed using computational BIM to suggest which actions to undertake concerning the thermo-hygrometric conditions to improve the preventive conservation of the collections in historic buildings [61]. A new knowledge-based taxonomy and data enrichment for HBIM was established, outlining new criteria that include both the temporal sequence and the constructive features of historical buildings [69]. A new method for managing Cultural Heritage ( CH ) was proposed to transform the point cloud generated by geomatics surveys into parameterized BIM objects [70]. A novel digital workflow of parametric modelling for analysing and conserving historical buildings was developed by applying VP to support the HBIM methodology [19]. Bruno and de Fino
计算BIM也被用于支持有关历史建筑保护工程和缺陷检测的决策。例如，使用计算BIM开发了一个基于AI的决策支持系统（DSS），以建议在温湿度条件下采取哪些行动，以改善历史建筑中藏品的预防性保护[61]。为HBIM建立了一个新的基于知识的分类和数据丰富，概述了包括历史建筑的时间顺序和建筑特征的新标准[69]。提出了一种管理文化遗产（CH）的新方法，将地理信息调查生成的点云转换为参数化BIM对象[70]。通过应用VP来支持HBIM方法，开发了一种用于分析和保护历史建筑的参数化建模的新型数字工作流程[19]。布鲁诺和德菲诺