Abstract

Building design review is the procedure of checking a design against codes and standard provisions to satisfy the accuracy of the design and identify non-compliances before construction begins. The current approaches for conducting the design review process in an automatic or semi-automatic manner are either based on proprietary, domain-specific or hard-coded rule-based mechanisms. These methods may be effective in their specific applications, but they have the downsides of being costly to maintain, inflexible to modify, and lack a generalized framework of rules and regulations modeling that can adapt to various engineering design realms, and thus don’t support a neutral data standard. They are often referred to as ‘Black Box’ or ‘Gray Box’ approaches. This research offers a new comprehensive framework that reduces the limitations of the cited methods. Building regulations, for instance, are legal documents transcribed and approved by professionals to be interpreted and applied by people. They are hardly as precise as formal logic. Engineers, architects, and contractors can read those technical documents and transform them into scientific notations and software applications. They can extract any data they need, reason about it, and apply it at various phases of the project. How these extraction and use are carried out is a critical component of automating the design review process. The chief goal is to address this issue by developing a Generalized Adaptive Framework (GAF) for a neutral data standard (Industry Foundation Classes (IFC)) that enables automating the code compliance checking processes to achieve design efficiency and cost-effectiveness. The objectives of this study comprise i) to develop a theoretical background to an adaptive framework that supports a neutral data standard for transforming the written code regulations and rules into a computable model, and ii) to define the various modules required for computerizing of the code compliance verification process.

Highlights

  • Design review is the process of evaluating a design against its requirements to verify the quality and performance of the design and identify issues before construction takes place

  • The chief goal is to address this issue by developing a Generalized Adaptive Framework (GAF) for a neutral data standard (Industry Foundation Classes (IFC)) that enables automating the code compliance checking processes to achieve design efficiency and cost-effectiveness

  • The concept of automating the CCC process described in this paper focuses on building regulations compliance checking mechanisms that are defined by the relationship among various design and engineering information management systems and the Building Information Modeling (BIM) and how this computerization will assist in streamlining communication and dissemination of building design review information amongst breadth of stakeholders

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Summary

Introduction

Design review is the process of evaluating a design against its requirements to verify the quality and performance of the design and identify issues before construction takes place. There were some efforts cited in the literature that aimed to automate some of the CCC process [1,2,3] Most of these efforts are either based on proprietary schemas, domain-specific or hard-coded rule-based representations, which may be successful in their implementations, but they have the shortcomings of being expensive to maintain, inflexible to modify, lack a generalized framework of rules and regulations modeling. Quite often regulations can amend provisions and interpretive standards, which generally leads to massive volumes of semi-structured documents that alter, complement and potentially conflict with one another These issues, which indicate complications for both young designers and engineers as well as experienced professionals, are far more disorderly for the fragile traditional knowledge bases in computer systems. Some code provisions are characterized by continuous progressions and open-ended range of exceptions that make it difficult to give exact definitions for any concepts that are learned through experience

A Brief Review of Recent Researches
Limitations
Statement of Purpose
Goals and Objectives
Methodology
II: Requires
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Implementation
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