Building Design Advisor: automated integration of multiple simulation tools
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Cited by (40)
Linking BIM and Design of Experiments to balance architectural and technical design factors for energy performance
2018, Automation in ConstructionCitation Excerpt :A large body of research exists that couples parametric building modeling, environmental simulation and optimization. The study of Gero et al. [5] and the Building Design Advisor [6] represent early, integrated design approaches combining multiple analysis and visualization tools. Caldas and Norford [7] utilize genetic algorithms to search for optimized environmental design solutions, focusing on façade configurations.
Development of an automated modeler of environment and energy geographic information (E-GIS) for ecofriendly city planning
2016, Automation in ConstructionCitation Excerpt :As a tool for integrating space modeling, environment and energy analysis, and evaluation and feedback, at the site level, Melo et al. [25] constructed a Google SketchUp plug-in to evaluate the irradiation environment on the urban surface and to deduce the PV design from the 3D solar modeling. At the building level, Papamichael et al. [26] suggested a computing environment that connects space planning, sunlight, and energy analysis by linking DOE-2 with the RADIANCE tool. With respect to decision-making or evaluation tools for space modeling, at the urban level, Johnston et al. [27] created an environmental modeler to collect environmental data, automatically standardize the data, perform simulations, and validate the simulations for bio-habitat planning support and Carlon et al. [28] constructed a GIS-based S/W incorporated with multi-criteria analysis using a scenario decision module to evaluate urban environment and technical risk.
Evolutionary energy performance feedback for design: Multidisciplinary design optimization and performance boundaries for design decision support
2014, Energy and BuildingsCitation Excerpt :Examples of these efforts can be found in data model and process standardizations [39–41], along with collaborative framework developments. A selection of the representative efforts is found here [26,42–50]. In summary, these efforts focus on collaborative frameworks to overcome interoperability between expert domains and to facilitate the inclusion of performance feedback.
Designing-in performance: A framework for evolutionary energy performance feedback in early stage design
2014, Automation in ConstructionCitation Excerpt :One focus has been on the interoperability issue among software and different domain expertise. Examples of these efforts can be found in data model and process standardization [15–17] along with collaborative framework development [18–22]. While solutions to interoperability would ease in the generation and evaluation of design alternatives, it is arguably insufficient [23] and cannot fulfill all the identified requirements for “designing-in performance” in early stage conceptual design.
Simulation and evaluation of building information modeling in a real pilot site
2014, Applied EnergyCitation Excerpt :They were designed to be used by research scientists. Usage of these tools generally requires a steep learning curve and as a consequence these tools are mainly used by domain experts [25]. “Simulation tools are neither used to support the generation of design alternatives nor to make informed choices between different design options, and they are neither used for building and/or system optimization” [26].
G-BIM framework and development process for integrated AEC design automation
2014, Procedia Engineering