Trade space exploration of satellite datasets using a design by shopping paradigm

Stump, Gary; Yukish, Michael A.; Simpson, Timothy W.; O'Hara, John

doi:10.1109/aero.2004.1368206

Cited by 35 publications

(26 citation statements)

References 15 publications

(4 reference statements)

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“…Although our research on trade space exploration has studied most of these data manipulation tasks (Stump et al 2003(Stump et al , 2004, it is rare to see systems to support engineering design with interactive data clustering across different scale levels of analysis. This research investigates the design, implementation, and application of the proposed approach.…”

Section: View Controllingmentioning

confidence: 99%

“…Virtual reality has supported a wide variety of engineering design problems (Jayaram et al 2001); however, such environments tend not to support trade space exploration since they are used to visualise a single point solution, not explore the entire trade space. Cloud visualisation (Eddy and Lewis 2002), the visual design steering methods (Winer and Bloebaum 2001, Winer and Bloebaum, 2002a, 2002b), the ATSV system (Stump et al 2003(Stump et al , 2004, and the U.S. Naval Research Laboratory's visual steering methods in their Virtual Reality Lab and High Performance Computing Center (Smith et al 1999) are exceptions to this, but these methods are used in an ad hoc manner to support design decision-making -none of the research in engineering design has investigated the knowledge discovery process during trade space exploration or formalised systematic procedures to support it.…”

Section: Visualisation In Engineering Designmentioning

confidence: 99%

“…This approach can be classified as an a posterior articulation of preferences to solve a multi-objective optimisation (Hwang and Masud 1979) in that designers first form their preferences based on visualisation of the entire design space and then choose an optimal design that is based on their formed preference. The basic steps to such an approach include (1) creating a simulation model to analyse the system being designed, (2) generating thousands of simulated design alternatives by varying design variables and storing the corresponding values of the performance variables for each alternative, and (3) using visualisation tools to explore these design alternatives and 'shop' for the best design (Stump et al 2003(Stump et al , 2004.…”

Section: Visualisation In Engineering Designmentioning

confidence: 99%

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Supporting knowledge exploration and discovery in multi-dimensional data with interactive multiscale visualisation

Zhang

Simpson

Frecker

et al. 2012

Journal of Engineering Design

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Knowledge discovery in multi-dimensional data is a challenging problem in engineering design. For example, in trade space exploration of large design data sets, designers need to select a subset of data of interest and examine data from different data dimensions and within data clusters at different granularities. This exploration is a process that demands both humans, who can heuristically decide what data to explore and how best to explore it, and computers, which can quickly extract features that may be of interest in the data. Thus, to support this process of knowledge discovery, we need tools that can go beyond traditional computeroriented optimisation approaches and support advanced designer-centred trade space exploration and data interaction. This paper is an effort to address this need. In particular, we propose the interactive multiscalenested clustering and aggregation framework to support trade space exploration of multi-dimensional data common to design optimisation. A system prototype of this framework is implemented to allow users to visually examine large design data sets through interactive data clustering, aggregation, and visualisation. The paper also presents an evaluation study involving morphing wing design using this prototype system.

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Section: View Controllingmentioning

confidence: 99%

Section: Visualisation In Engineering Designmentioning

confidence: 99%

Section: Visualisation In Engineering Designmentioning

confidence: 99%

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Supporting knowledge exploration and discovery in multi-dimensional data with interactive multiscale visualisation

Zhang

Simpson

Frecker

et al. 2012

Journal of Engineering Design

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“…The visual display of quantitative information is important as the complexity of a system increases. In particular, with multi-dimensional systems both in terms of input and output variables, methods and software tools have been developed to help reduce the complexity of the design consideration space when one wants to explicitly understand the trade-offs between large numbers of designs (Stump et al 2004). In terms of exploring these designs from different angles, the area of visualization known as coordinated and multiple views has received research attention addressing data processing and preparation, view generation, exploration techniques, coordination, tools, human interface, and perception (Roberts 2007).…”

Section: Visualization Techniquesmentioning

confidence: 99%

Applications of Systems Engineering to the Research, Design, and Development of Wind Energy Systems

Dykes¹,

Meadows²,

Felker³

et al. 2011

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Executive SummaryOver the past 30 years, wind energy has evolved from a small industry active in a few countries to a large international industry involving major players in the manufacturing, development, and utility sectors. Coinciding with the industry growth, significant innovation in the technology has resulted in larger sized turbines with lower associated costs of energy and more complex designs in all subsystems-from the rotor to the drivetrain to the electronics and control systems. However, as the deployment of the technology grows and its role within the electricity sector has become more prominent, so have the expectations of the technology in terms of performance, reliability, and cost. For the industry to continue to succeed and become a sustainable source of electricity, innovation in wind energy technology must continue to improve performance and lower the cost of energy while supporting seamless integration of wind energy into the electric grid without creating significant negative impacts on local communities and environments. At the same time, the nature of the issues associated with wind energy design and development are noticeably more complex than in the past due to a variety of factors such as, for example, large turbines sizes, offshore deployment or complex terrains. Looking toward the future, the industry would benefit from an integrated approach that simultaneously addresses turbine design, plant design and development, grid interaction and operation, and mitigation of adverse community and environmental impacts. These activities must be integrated in order to meet this diverse set of goals while recognizing trade-offs that exist between them.In order to address these challenges, National Renewable Energy Laboratory (NREL) has embarked on the Wind Energy Systems Engineering (WESE) initiative to evaluate how methods of systems engineering can be applied to the research, design, and development of wind energy systems. Systems engineering is a field within engineering that has a long history of application to complex technical systems such as aerospace. As such, the field holds much potential for addressing critical issues that face the wind industry today. This paper represents a first step for understanding this potential and lays out a conceptual design for the development of a WESE framework and tool. It reviews systems engineering methods as applied to related technical systems and illustrates how these methods can be combined in a WESE framework to meet the research, design, and development needs for the future of the industry. Subsequent efforts will focus on developing and implementing a framework based on the conceptual design illustrated in the last chapter of this report.In general, systems engineering approaches have the following four characteristics: holistic, multidisciplinary, integrated/value-driven, and long-term/life-cycle oriented. The approach is holistic in that it considers the full technical system, including any number of performance criteria, as well as potential...

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“…Moreover, these samples do not lie on the boundary of the design space. Nevertheless, these points are then visualized using parallel coordinates, glyph plots and histograms among others [3].…”

Section: Related Workmentioning

confidence: 99%

Creating Polytope Representations of Design Spaces for Visual Exploration Using Consistency Techniques

Devanathan

Ramani

2010

Journal of Mechanical Design

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Trade space exploration of satellite datasets using a design by shopping paradigm

Cited by 35 publications

References 15 publications

Supporting knowledge exploration and discovery in multi-dimensional data with interactive multiscale visualisation

Supporting knowledge exploration and discovery in multi-dimensional data with interactive multiscale visualisation

Applications of Systems Engineering to the Research, Design, and Development of Wind Energy Systems

Creating Polytope Representations of Design Spaces for Visual Exploration Using Consistency Techniques

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