T
Tripp Shealy
Researcher at Virginia Tech
Publications - 78
Citations - 808
Tripp Shealy is an academic researcher from Virginia Tech. The author has contributed to research in topics: Sustainability & Computer science. The author has an hindex of 14, co-authored 64 publications receiving 522 citations. Previous affiliations of Tripp Shealy include Clemson University.
Papers
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Using Framing Effects to Inform More Sustainable Infrastructure Design Decisions
TL;DR: To measure framing effects in engineering decisions, the Envision rating system for sustainable infrastructure is used, which aims to help the authors better understand how choice structures influence engineering decisions.
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Beyond rationality in engineering design for sustainability
TL;DR: The extent to which cognitive biases can either limit or help engineering design for sustainability is analyzed, and possible changes to the decision settings of engineers are suggested as new ways to achieve sustainability.
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Empirical evidence that concept mapping reduces neurocognitive effort during concept generation for sustainability
TL;DR: Neurocognitive evidence is provided to support the benefits of concept mapping and the added advantages of neuroimaging to study systems thinking are demonstrated.
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Application of Functional Near-Infrared Spectroscopy to Measure Engineering Decision-Making and Design Cognition: Literature Review and Synthesis of Methods
Mo Hu,Tripp Shealy +1 more
TL;DR: The emergence of a novel neuroimaging technique, which combines fMRI with 3D image analysis, shows the emergence of new ways of thinking about decision-making and design in engineering.
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Sustainable Construction Risk Perceptions in the Kuwaiti Construction Industry
Dalya Ismael,Tripp Shealy +1 more
TL;DR: In this paper, a survey was conducted to understand how the Kuwaiti construction industry perceives risks associated with more sustainable construction, and the results indicated that industry professionals perceive a lack of public awareness as the risk element with the highest probability of occurrence.