Showing posts from September, 2020

An Exploratory Multi-objective Retrofit Decision-making Process

The retrofit processes for buildings necessitates long-term planning and costly operations and requires a collaborative approach where a high number of alternative solutions should be explored by stakeholders. However, the evaluation of a range of retrofit solutions is a complex process wherein various design parameters and objectives are involved. The identification of the most effective solutions requires a collaborative evaluation in order to satisfy all stakeholders' expectations; however, during the decision-making process, stakeholders may generally have conflicting objectives. This paper discusses different user preference-based decision-making approaches for building retrofit that involves the collaborative evaluation of multiple design parameters and objectives simultaneously. For this purpose, we demonstrate a simulation-based approach for performative exploration for building retrofits, which may allow a broader consideration of alternative retrofit solutions to increase

The Comparative Study on the Influence of Early Architectural Design Decisions on Energy Demand: A Case Study in Turkey

The early design process has the most salient design decisions for architects. It is crucial to observe the impact of these design decisions in terms of performance-based design. However, because of the large amount of variance of the performance criteria in the early design parameters, the decision-making is highly arduous. The current study proposes a method to quantify output uncertainty and presents the relationship between independent and dependent variables for providing insight into the decision-making process. The energy simulations for hypothetical office building based on TS-825 requirements are executed with cooling and heating demand (kWh/m 2-year) outputs for two different regions, i.e., Erzurum as a cold climate and Izmir as a hot-humid climate. Researchers compute the input parameters' impact on building performance with quasi-random statistical sampling and filtering techniques. Respectively, ineffective parameters are eliminated with factor fixing, and factor prior