Rave: A Computational Framework to Facilitate Research in Design Decision Support

2012 ◽  
Vol 12 (2) ◽  
Author(s):  
Matthew J. Daskilewicz ◽  
Brian J. German
Keyword(s):  
Decision Support ◽  
Wide Spectrum ◽  
Problem Formulation ◽  
Design Decision ◽  
Computational Framework ◽  
Complex Engineered Systems ◽  
Research Platform ◽  
Engineered Systems ◽  
Support Methods ◽  
Design Decision Support

The cognitive challenges in the design of complex engineered systems include the scale and scope of decision problems, nonlinearity of the trade space, subjectivity of the problem formulation, and the need for rapid decision making. These challenges have motivated an active area of research in design decision-support methods and the development of commercial and openly available design frameworks. Although these frameworks are extremely capable, most are limiting as a basis for research relating to design decision support because they offer little user flexibility for incorporating and evaluating new features or techniques. This paper describes Rave (www.rave.gatech.edu), a computational framework designed specifically as a research platform for design decision-support methods. Rave has been structured to be flexible and adaptable, handle data with systematic data structures and descriptive metadata, facilitate a wide spectrum of visualization types, provide features to enable user interactivity and linking of graphics, and incorporate surrogate modeling and optimization as enabling capabilities. This framework is envisioned to provide the research and industrial communities an easily expandable and customizable baseline capability to facilitate investigation of further design decision-support advancements.

Ontology-Based Representation of Design Decision Hierarchies

2016 ◽  
Author(s):  
Zhenjun Ming ◽  
Yan Yan ◽  
Guoxin Wang ◽  
Jitesh H. Panchal ◽  
Chung Hyun Goh ◽  
...  
Keyword(s):  
Decision Support ◽  
Engineering Design ◽  
Building Blocks ◽  
Design Decision ◽  
Information Flows ◽  
Knowledge Modeling ◽  
Frame Design ◽  
Complex Engineered Systems ◽  
Portal Frame ◽  
Engineered Systems

It is efficacious to capture and represent the knowledge for decision support in engineering design. Ontology is a promising knowledge modeling scheme in the engineering domain. In this paper, an ontology is proposed for capturing, representing and documenting the knowledge related to hierarchical decisions in the design of complex engineered systems. The ontology is developed based on the coupled Decision Support Problem (DSP) construct, taking into consideration the requirements for a computational model that represents a decision hierarchy. Key to the ontology is the concept of two classes, namely, Process which represents the basic hierarchy building blocks where the DSPs are embedded, and Interface which represents the DSP information flows that link different Processes to a hierarchy. The efficacy of the ontology is demonstrated using a portal frame design example.

scholarly journals Continuous Design Decision Support

2019 ◽  
pp. 107-139
Author(s):  
Anja Kleebaum ◽  
Marco Konersmann ◽  
Michael Langhammer ◽  
Barbara Paech ◽  
Michael Goedicke ◽  
...  
Keyword(s):  
Decision Support ◽  
Design Decision ◽  
Design Decision Support

On Validating Design Decision Methodologies

2003 ◽  
Author(s):  
Andrew T. Olewnik ◽  
Kemper E. Lewis
Keyword(s):  
Decision Support ◽  
Design Methodology ◽  
Critical Evaluation ◽  
General Definition ◽  
Design Decision ◽  
Formal Definition ◽  
House Of Quality ◽  
Decision Methods ◽  
Definition Of ◽  
Support Methods

In this paper an argument for validation of design decision methods is presented. In the process of justifying the need for validation, the elements of what a valid design methodology is are derived and a formal definition is presented. Under this definition, critical evaluation of two popular decision support methods, the House of Quality and Suh’s Axiomatic Design, is presented using a simple design problem and both are shown to be flawed under the proposed definition of validity. This does not imply that the methods are ineffective. In fact, under the appropriate assumptions, they are quite useful. However, in this paper, an investigation of the validity of these assumptions is conducted, including a more general definition of validity with respect to decision support methods in design.

scholarly journals Simulation of Imagined Realities: Environmental Design Decision Support Tools in Architecture

2021 ◽  
Author(s):  
◽  
Michael Robert Donn
Keyword(s):  
Quality Assurance ◽  
Decision Support ◽  
Environmental Design ◽  
Building Design ◽  
Building Performance ◽  
Design Decision ◽  
Decision Support Tools ◽  
Design Tools ◽  
Support Tools ◽  
Design Decision Support

<p>The spur for this research was a lack of use by architecture practitioners of the environmental design decision support tools (eddst’s) they learn to use during their education. It was hypothesised that lessons for the improvement of eddst’s could be found in a systematic examination of the problems encountered by design teams with a range of currently available eddst’s. The research plan was to establish through surveys and case studies how practising architects who have tried to use building eddst’s assess the effectiveness of these tools. A range of different types of eddst was examined, each addressing a different aspect of the environment in buildings. The research did not achieve its original goal of developing a formula for the generation of new eddst’s for architects in the fields of building acoustics, lighting, thermal design and aerodynamics. What was found is a more fundamental common denominator underlying building design eddst’s: the need for built-in Quality Assurance measures that assure not only the architect, but also the simulationist and the client of the reality of the ebuilding performance predictions. It was found that contrary to their general reputation, designers do want detailed quantitative environmental information. They want to be able to discuss costs and benefits of decisions. However, they also want to be able to understand and trust this information. The output from eddst’s must therefore also be qualitative in the sense that it communicates the quality of life resulting from a design decision. What is proposed therefore for designers and simulationists is Quality Assurance (QA) procedures that are codified and incorporated into the design tools themselves. These are to ensure that the ‘black box’ of a digital simulation of building performance yields information that designers feel they can trust. The research demonstrates that to address the issues identified in the practitioner surveys, a Quality Control (QC) reality test is the single most important feature needed in any QA process. This would be a reality test that examines whether the ebuildings constructed with an eddst behave in a believable manner - like a ‘real’ building. The proposed Simulation QA (SimQA) approach is an internet web service. It is a database of the databases available on the internet of Quality Assured performance data. Each time a person sets up a new Quality tested eddst input file or measures a building, it becomes another “data point” - another database listed in the SimQA metadata. Also required in a robust QA process is the development of international norms for the simulation of building performance. www.aecsimqa.net is proposed as the venue for the development of an international documentation standard for simulation. Finally, modern computer-based building performance simulation has not rid the design profession of its traditional problem with design tools: that they evaluate completed designs. The proposed database will make web-accessible a set of tested building designs and their associated performance measures. Placed at the designer’s fingertips this will reveal insights into how their current building design should perform. It should be possible to generate initial design ideas based on systematic study of the successful precedents!</p>

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