Block-Level Building Transformation Strategies for Energy Efficiency, Thermal Comfort, and Visibility Using Bayesian Multilevel Modeling

Author:

Chang Soowon1,Yoshida Takahiro2ORCID,Castro-Lacouture Daniel3,Yamagata Yoshiki4

Affiliation:

1. Assistant Professor, School of Construction Management Technology, Polytechnic Institute, Purdue Univ., 401 N. Grant St., West Lafayette, IN 47097 (corresponding author).

2. Project Assistant Professor, Dept. of Urban Engineering, School of Engineering, The Univ. of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan; formerly, Research Associate, Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki Prefecture 305-8506, Japan. ORCID: .

3. Professor, School of Building Construction, College of Design, Georgia Institute of Technology, 280 Ferst Drive, Atlanta, GA 30332-0680.

4. Professor, Graduate School of System Design and Management, Keio Univ., Yokohama, Japan; formerly, Principal Researcher, Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki Prefecture 305-8506, Japan.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Visual Arts and Performing Arts,Building and Construction,Civil and Structural Engineering,Architecture

Reference45 articles.

1. Investigating the thermal behavior of double-skin perforated sheet façades: Part A: Model characterization and validation procedure;Blanco J. M.;Build. Environ.,2014

2. Bürklin, T., and M. Peterek. 2017. Basics urban building blocks. 1 ed. Basel, Switzerland: Birkhäuser.

3. brms: An R Package for Bayesian Multilevel Models Using Stan

4. Advanced Bayesian Multilevel Modeling with the R Package brms

5. CEN (European Committee for Standardization). 2007. Indoor environmental input parameters for design and assessment of energy performance of buildings-addressing indoor air quality, thermal environment, lighting and acoustics. CEN-EN 15251. Brussels, Belgium: CEN.

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