Paper Conference

Proceedings of Building Simulation 2013: 13th Conference of IBPSA

     

Automatic Simulation And Carbon Analysis For Architecture Design

Yi Chun HUANG, Yuezhong LIU

DOI: https://doi.org/10.26868/25222708.2013.1243
Abstract: This paper presents computational work in building information management, data interoperability, and data population, to support automatic carbon analysis. The goal is to build an effective design support tool to help maintain a carbon perspective during building design, and as such accuracy and ease of use are pertinent objectives. This entails computational capability to automatically manage information flows between different domains and tools and generate useful operative information for design decisions, including 1) processing incomplete building models into well-formed and complete models, 2) integrating and matching data sets of material properties and emission factors, 3) automatic EnergyPlus simulation, and 4) analysis & visualization (post-processing). The computational approach in this research attempts to address well-recognized challenges in automating and delivering easy-to-use simulation-based design support tools: 1. Disparate data sources, ontologies and schemas 2. Missing data in early design stages required for energy simulation By leveraging on existing research in building information modelling, expert systems, and casebased reasoning, this paper presents application findings and developments in computational approaches to enable automatic simulation and carbon analysis in a prototypical design support tool. Specifically, prevalent software and information schemas were adapted to work with a split Shared Object Model (SOM) and Domain Object Model (DOM), case-based reasoning and heuristics were developed to facilitate automatic simulation, and the various computational approaches were integrated to deliver an expert system that is fully automatic, and does not deviate from existing industry practices and processes. While the current implementation utilizes a decision tree, the implementation also supports data analytics in completing building models, suspending the need for a priori ontological models.
Pages: 1055 - 1062
Paper:
bs2013_1243