student and faculty conducting research

PhD Students and Post-Doctoral Researchers

Peng Zhou

  • Advisor:
      • El-Gohary Nora
  • Departments:
    • Civil and Environmental Engineering
  • Areas of Expertise:
      • Automated Code Compliance Checking
      • Automation in Construction
      • Building Information Modeling
      • Information Technology
      • Environmental Sustainability
      • Semantic Modeling
      • Automated Reasoning
      • Data Analytics
      • Sustainable Infrastructure System
      • Computing in Construction

  • Thesis Title:
  • Thesis abstract:
      • Compliance checking aims to ensure the compliance of a project with applicable norms such as laws, regulations, codes, and contract requirements. Manual compliance checking is a time-consuming and error-prone task. Automated compliance checking (ACC) has, therefore, attracted both academia and industrical effort to reduce the cost and time of this task. Despite the significance of these efforts, four main gaps in existing ACC systems and methods are identified. First, there is lack of ACC systems and methods for compliance checking of building designs with environmental codes, specifically building energy codes. Second, the majority of existing ACC efforts are not entirely automated. They rely on the use of hard-coded rules for representing code requirements, which requires major manual effort in extracting requirements from textual codes/documents and coding these requirements into a computer-processable rule format. Third, existing ACC systems and methods lack the capability of compliance checking with project contracts. Fourth, fully automated ACC efforts in the construction domain focused on building code compliance checking, without testing energy compliance checking or specifications compliance checking. To address these gaps, this research aims to develop a set of methods and algorithms for text classification, information extraction, information transformation, and logic reasoning for automated compliance checking of BIM-represented building designs with energy requirements (specifically thermal insulation requirements and lighting power requirements) in both energy codes and contract specifications. Semantic text classification is used for classifying the text in codes and specifications to filter out irrelevant and noisy text. Semantic, NLP-based information extraction is used to extract energy requirements from codes and specifications. EXPRESS-based information extraction is used to extract design information from BIMs. Semantic information transformation is used to transform the extracted energy requirements and design information into logic rules and facts, respectively. Logic reasoning is used to reason about the logic rules and facts for compliance checking and reporting. NLP techniques are used to facilitate text processing and analysis. Semantic modeling is used to enable deep and domain-specific information (both text information and BIM information) processing and reasoning. Logic representation and reasoning is used to facilitate automated reasoning. The proposed ACC system will be implemented in a JAVA programming language-developed prototype and will be tested on a real case study including (1) a BIM model of an educational building project of of Illinois; (2) contract specifications from the same project; and (3) Chapter 4 of 2012 International Energy Conservation Code.
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