Methodological tool P-Balance for integrated façade performance assessment

Authors

DOI:

https://doi.org/10.46421/entac.v20i1.6119

Keywords:

Integrated Building Assessment, Building Performance Simulation, Data Visualization, Project Decision Making, Multi-objective Optimization

Abstract

In building façade integrated assessment consultancies, multiple performance indicators for environmental comfort and energy efficiency, tight project deadlines, the complexity of analyses, and the difficulty of communicating results to non-specialist decision-makers present challenges to be overcome. To simplify the process of this type of assessment and make it more objective, agile, user-friendly, and scientific, the P-balance methodological tool was developed. It offers graphical visualization and an evaluation method that supports integrated design approaches. Aligned with the Design Science Research (DSR) methodology, the development included the careful application of data visualization techniques (DVT) to condense large amounts of data obtained through computer simulation. The application of P-Balance prototypes demonstrated its usefulness in simplifying multi-objective evaluation processes and reducing evaluation and consulting time, as it speeds up analyses and decisions, promoting effective communication, integration, and enhancing the technical maturity of project teams.

Author Biographies

Melissa Marina Freitas Cacciatori, BEM+arch

Ph.D. in Architecture Technology Area, from Faculty of Architecture and Urbanism at the São Paulo University (São Paulo - SP, Brazil)

Marcelo de Andrade Roméro, Centro Universitário Belas Artes de São Paulo

Doutorado em Estruturas Ambientais e Urbanas pela Universidade de São Paulo, Brasil(1994). Professor Livre Docente pela Faculdade de Arquitetura e Urbanismo da Universidade de São Paulo

References

KOKARAKI, N. et al. Testing the reliability of deterministic multi-criteria decision-making methods using building performance

simulation. Renewable and Sustainable Energy Reviews, n. 112, 2019. p. 991-1007.

BRACHT, M. K.; MELO, A. P.; LAMBERTS, R. A metamodel for building information modeling-building energy modeling integration

in early design stage. Automation in Construction, n. 121, 2021.

HOSAMO, H. H. et al. Multiobjective optimization of building energy consumption and thermal comfort based on integrated BIM

framework with machine learning-NSGA II. Energy & Buildings, n. 277, 2022.

SINGH, M. M.; DEB, C.; GEYER, P. Early-stage design support combining machine learning and building information modelling.

Automation in Construction, n. 136, 2022.

CICHOCKA, J. M.; BROWNE, W. N.; RODRIGUEZ, E. Optimization in the architectural practice. In: 22nd International Conference of

the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), 2017, Hong Kong, Asia. Protocols, Flows and

Glitches, Proceedings. Hong Kong: The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA). 2017. p.

-397. Disponível em: http://papers.cumincad.org/data/works/att/caadria2017_155.pdf. Acesso em: 17 fev. 2020.

YAN, H.; YAN, K.; JI, G. Optimization and prediction in the early design stage of office buildings using genetic and XGBoost

algorithms. Building and Environment, n. 2018, 2022.

SCHERZ, M. et al. A hierarchical reference-based know-why model for design support of sustainable building envelopes.

Automation in Construction, n. 139, 2022.

SRIVASTAV, A. et al. A review and comparison of data visualization techniques used in building design and in building simulation.

In: ELEVENTH INTERNATIONAL IBPSA CONFERENCE. Proceedings., Glasgow, 2009. p. 1972-1949.

DÍAZ, H. et al. Multidisciplinary Design Optimization through process integration in the AEC industry: Strategies and challenge.

Automation in Construction, n. 72, 2017. p. 102-119.

LI, X. et al. Venis: A designer-centric support tool for building performance design at early design stages. Journal of Building

Engineering, n. 63, 2023.

KAHNEMAN, D. Rápido e Devagar: duas formas de pensar. Rio de Janeiro: Objetiva, 2011.

FISKE, S. T.; TAYLOR, S. E. Social Categories and Schemas. In: FISKE, S. T.; TAYLOR, S. E. Social Cognition: From Brain to Culture.

Nova York: McGraw-Hill, 1991. Cap. 4, p. 96-141.

MLODINOW, L. Subliminar: Como o inconsciente influencia nossas vidas. Rio de Janeiro: Zahar, 2012. Edição Brasileira: 2014.

LI, C. Z. et al. Advances in the research of building energy saving. Energy & Buildings, n. 254, 2022.

MUKHERJEE, A.; MUGA, H. An integrative framework for studying sustainable practices and its adoption in the AEC industry: A case

study. Journal of Engineering and Technology Management, n. 27, 2010. p. 197-214.

CACCIATORI, M. M. F. Diretrizes dinâmicas para projeto de fachadas de edifícios de escritórios de alto padrão, na cidade de São

Paulo, com base no potencial de eficiência energética e viabilidade econômica. 2016. 2v.: Dissertação (Mestrado) – Instituto de

Pesquisas Tecnológicas - IPT, São Paulo, 2016.

CACCIATORI, M. M. F.; VALDIVIA, J. D. Redução de Consumo Energético com o uso de Persianas Automatizadas | ETAPA 2: Uma

comparação entre tipos de controles de persianas automatizadas e arquivos climáticos. Série Simulação de Persianas

automatizadas em EnergyPlus, São Paulo, 2021.

CACCIATORI, M. M. F. Ferramenta metodológica P-Balance para avaliação integrada de desempenho de fachadas. 2023: Tese

(Doutorado) - Faculdade de Arquitetura e Urbanismo da Universidade de São Paulo - FAUUSP, São Paulo, 2023.

FEW, S. Show me the numbers: Designing tables and graphs to enlighten. El Dorado Hills, CA: Analytics Press, 2012.

FEW, S. Now You See It: Simple Visualization Techniques for Quantitative Analysis. El Dorado Hills, CA: Analytics Press, 2009.

CAIRO, A. El arte funcional: infografia e visualización de información. Madrid: Alamut, 2012.

SOLLEMA. ClimateStudio User Guide. Visita à seção Learn, Documentation, 2023. Disponivel em: <https://climatestudiodocs.com/

docs/daylightCustom.html>. Acesso em: 29 set. 2023.

Published

2024-10-07

How to Cite

CACCIATORI, Melissa Marina Freitas; ROMÉRO, Marcelo de Andrade. Methodological tool P-Balance for integrated façade performance assessment. In: NATIONAL MEETING OF BUILT ENVIRONMENT TECHNOLOGY, 20., 2024. Anais [...]. Porto Alegre: ANTAC, 2024. p. 1–23. DOI: 10.46421/entac.v20i1.6119. Disponível em: https://eventos.antac.org.br/index.php/entac/article/view/6119. Acesso em: 25 nov. 2024.

Issue

Section

Tecnologia da Informação e Comunicação

Similar Articles

<< < 48 49 50 51 52 53 54 55 56 57 > >> 

You may also start an advanced similarity search for this article.