GCRIS

Now showing 1 - 3 of 3

Citation - WoS: 5
Citation - Scopus: 6
An Investigation of the Design Process's Effect on a High-Performance Building's Actual Energy System Performance
(Ios Press, 2022) Terim Çavka, Belgin; Çavka, Hasan Burak; Salehi, M. Mahdi
The design intent and the performance targets of projects may sometimes fail to match a building's actual post-occupancy performance. The mismatch of intended and actual building performance can be attributed to multifarious reasons. This study focuses on the role of project decisions made during design as one of the reasons of shortfall. The aim of the study is to unveil the design decision-making process of a state-of-the-art research building through the analysis of project's available set of IDP (Integrated Design Process) documentation. To understand the relationship and correlation between the energy performance gap and the decision-making process of the case building, we investigated the design decisions' effect on the actual performance. The particular emphasis is on the decisions that were based on assumptions rather than measured actual test data for the proposed innovative building systems. The designed heat recovery system, which was dependent on recovered heat from the neighboring research building, had a significant effect on the building's poor energy performance. We investigated collected project data from coordination meetings, thoroughly analyzed project documentation, and quantified the building's actual energy performance data. The analysis of the project information shows the ripple effect of decisions that were made based on assumptions, that triggered shortfalls in the building's overall actual performance. Our qualitative analysis indicates that the poor system performance during operations was related with the design decisions that were not based on the measurement of the actual performance of the existing systems in the neighboring building. The performance of the heat recovery from the neighboring building as a highly dependent Energy Conservation Measure (ECM) analyzed through collected documents and data. The ambiguity of the available heat potential from the neighboring building and related testing issues defined on an explanatory timeline of process coding. The conclusion includes recommendations for the design decision-making process for innovative system integrations for high-performance buildings, and underlines the importance of IDP for complex buildings.
Citation - WoS: 66
Citation - Scopus: 76
Using Decision Trees for Determining Attribute Weights in a Case-Based Model of Early Cost Prediction
(American Society of Civil Engineers (ASCE), 2008) Doğan, Sevgi Zeynep; Arditi, David; Günaydın, Hüsnü Murat
This paper compares the performance of three different decision-tree-based methods of assigning attribute weights to be used in a case-based reasoning (CBR) prediction model. The generation of the attribute weights is performed by considering the presence, absence, and the positions of the attributes in the decision tree. This process and the development of the CBR simulation model are described in the paper. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of residential building projects. The CBR results indicate that the attribute weights generated by taking into account the information gain of all the attributes performed better than the attribute weights generated by considering only the appearance of attributes in the tree. The study is of benefit primarily to researchers, as it compares the impact of attribute weights generated by three different methods and, hence, highlights the fact that the prediction rate of models such as CBR largely depends on the data associated with the parameters used in the model.
Citation - WoS: 87
Citation - Scopus: 100
Determining Attribute Weights in a Cbr Model for Early Cost Prediction of Structural Systems
(American Society of Civil Engineers (ASCE), 2006) Doğan, Sevgi Zeynep; Arditi, David; Günaydın, Hüsnü Murat
This paper compares the performance of three optimization techniques, namely feature counting, gradient descent, and genetic algorithms (GA) in generating attribute weights that were used in a spreadsheet-based case based reasoning (CBR) prediction model. The generation of the attribute weights by using the three optimization techniques and the development of the procedure used in the CBR model are described in this paper in detail. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of 29 residential building projects. The results indicated that GA-augmented CBR performed better than CBR used in association with the other two optimization techniques. The study is of benefit primarily to researchers as it compares the impact attribute weights generated by three different optimization techniques on the performance of a CBR prediction tool.

Architecture / Mimarlık

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