Jia‐Rui Lin

Tsinghua University

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Zhen‐Zhong Hu

Tsinghua University

Yucheng Zhou

Hangzhou Medical College

Xinzheng Lu

China University of Petroleum, Beijing

Jianping Zhang

East China Jiaotong University

Keyin Chen

Second Affiliated Hospital of Zhejiang University

Zhe Zheng

Moderna Therapeutics (United States)

Yichuan Deng

South China University of Technology

Zhe Zheng

China National Commission for Disaster Reduction

Xiang-Rui Ni

Tsinghua University

Zhe Zheng

Tianjin Normal University

Cooperative Institutions

Tsinghua University

Institute of Seismology

Chinese Academy of Sciences

Huazhong University of Science and Technology

Alexion Pharma (Switzerland)

Geomechanica (Canada)

Sun Yat-sen University

Shanghai Jiao Tong University

Nanchang University

Shantou University

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Framing and Evaluating the Best Practices of IFC-Based Automated Rule Checking: A Case Study

Buildings (2021)

Soroush Sobhkhiz Yucheng Zhou Jia‐Rui Lin Tamer E. El-Diraby

This research reviews recent advances in the domain of Automated Rule Checking (ARC) and argues that current systems are predominantly designed to validate models in post-design stages, useful for applications such as e-permitting. However, such a design-check-separated paradigm imposes a burden on designers as they need to iteratively fix the fail-to-pass issues. Accordingly, the study reviews the best-practices of IFC-based ARC systems and proposes a framework for ARC system development, aiming to achieve proactive bottom-up solutions building upon the requirements and resources of end-users. To present and evaluate its capabilities, the framework is implemented in a real-life case study. The case study presents all the necessary steps that should be taken for the development of an ARC solution from rule selection and analysis, to implementation and feedback. It is explained how a rule checking problem can be broken down into separate modules implemented in an iterative approach. Results show that the proposed framework is feasible for successful implementation of ARC systems and highlight that a stable data standard and modeling guideline is needed to achieve proactive ARC solutions. The study also discusses that there are some critical limitations in using IFC which need to be addressed in future studies.

Framing (construction)

Rule-based system

10.3390/buildings11100456

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Citations (15)

BIM-based automatic compliance checking

Journal of Tsinghua University(Science and Technology) (2020)

Jia‐Rui Lin Jianfeng Guo

10.16511/j.cnki.qhdxxb.2020.25.013

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Citations (3)

Enhanced Earthquake Impact Analysis based on Social Media Texts via Large Language Model

International Journal of Disaster Risk Reduction (2024)

Jin Han Zhe Zheng Xinzheng Lu Keyin Chen Jia‐Rui Lin

10.1016/j.ijdrr.2024.104574

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Citations (1)

Knowledge-informed semantic alignment and rule interpretation for automated compliance checking

Automation in Construction (2022)

Zhe Zheng Yucheng Zhou Xinzheng Lu Jia‐Rui Lin

Semantic interpretation

Rule-based system

10.1016/j.autcon.2022.104524

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Citations (48)

Adaptive Control of Resource Flow to Optimize Construction Work and Cash Flow via Online Deep Reinforcement Learning

arXiv (Cornell University) (2023)

Can Jiang Xin Li Jia‐Rui Lin Ming Liu Zhiliang Ma

Due to complexity and dynamics of construction work, resource, and cash flows, poor management of them usually leads to time and cost overruns, bankruptcy, even project failure. Existing approaches in construction failed to achieve optimal control of resource flow in a dynamic environment with uncertainty. Therefore, this paper introducess a model and method to adaptive control the resource flows to optimize the work and cash flows of construction projects. First, a mathematical model based on a partially observable Markov decision process is established to formulate the complex interactions of construction work, resource, and cash flows as well as uncertainty and variability of diverse influence factors. Meanwhile, to efficiently find the optimal solutions, a deep reinforcement learning (DRL) based method is introduced to realize the continuous adaptive optimal control of labor and material flows, thereby optimizing the work and cash flows. To assist the training process of DRL, a simulator based on discrete event simulation is also developed to mimic the dynamic features and external environments of a project. Experiments in simulated scenarios illustrate that our method outperforms the vanilla empirical method and genetic algorithm, possesses remarkable capability in diverse projects and external environments, and a hybrid agent of DRL and empirical method leads to the best result. This paper contributes to adaptive control and optimization of coupled work, resource, and cash flows, and may serve as a step stone for adopting DRL technology in construction project management.

Stochastic control

10.48550/arxiv.2307.10574

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System reliability analysis for independent and nonidentical components based on survival signature

Probabilistic Engineering Mechanics (2023)

Yide Zheng Yi Zhang Jia‐Rui Lin

Component (thermodynamics)

Signature (topology)

10.1016/j.probengmech.2023.103466

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Citations (2)

Bibliometric review of visual computing in the construction industry

Visual Computing for Industry Biomedicine and Art (2020)

Heng-Wei Wang Zhen‐Zhong Hu Jia‐Rui Lin

In the construction area, visuals such as drawings, photos, videos, and 3D models, play a significant role in the design, build and maintenance of a facility, bringing efficiency to generate, transfer, and store information. Advanced visual computing techniques facilitate the understanding of design contents, work plans, and other types of information shared in the construction industry. Automatic visual data collection and analysis provide many possibilities to the construction industry and a large number of works have investigated how visual computing can improve construction management processes and other problems in the construction area. However, a comprehensive literature review is needed. This study uses bibliometric approaches to review the works published to date, and analyses the development of knowledge, significant research results, and trends. The purpose of this study is to help newcomers to this research field understand knowledge structure and formulate research directions, thereby enhancing knowledge development. From this study, it can be concluded that computer vision is a key axis of improvement. Moreover, building information modeling, laser scanning, and other visualization-related techniques are also important in advancing the construction area.

Building Information Modeling

10.1186/s42492-020-00050-0

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Citations (1)

Research on Impact Modeling and Risk Assessment of Software Requirements Change based on Dependency Structure Matrix

Jia‐Rui Lin Bing Li

Design Structure Matrix

Change impact analysis

10.1109/icdm63232.2024.10762046

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Citations (0)

Ontology-Based Semantic Retrieval Method of Energy Consumption Management