D
Duzgun Agdas
Researcher at Queensland University of Technology
Publications - 49
Citations - 713
Duzgun Agdas is an academic researcher from Queensland University of Technology. The author has contributed to research in topics: Project management & Supply chain. The author has an hindex of 12, co-authored 45 publications receiving 469 citations. Previous affiliations of Duzgun Agdas include University of Florida.
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Comparison of Visual Inspection and Structural-Health Monitoring As Bridge Condition Assessment Methods
TL;DR: This paper presents the results of a research project aimed at examining the capabilities and challenges of two distinct but not mutually exclusive approaches to in-service bridge assessment: visual inspection and installed monitoring systems.
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Impact of the COVID-19 Pandemic on the U.S. Electricity Demand and Supply: An Early View from Data
Duzgun Agdas,Prabir Barooah +1 more
TL;DR: Analysis of electricity data until the end of May 2020, examining both electricity demand and variables that can indicate stress on the power grid indicates that a 10% (95% CI [2%, 18%]) increase in electricity demand is likely to have occurred due to COVID-19 for the city analyzed.
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Making the Case for Improved Structural Design: Tornado Outbreaks of 2011
David O. Prevatt,John W. van de Lindt,Edward Back,Andrew J. Graettinger,Shiling Pei,William Coulbourne,Rakesh Gupta,Darryl L. James,Duzgun Agdas +8 more
TL;DR: The authors in this article examined observations by tornado damage assessment teams led by the first author in these two medium-sized cities and suggested that the evolution of building codes and past approaches to construction have led to conditions that made this extent of damage possible.
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Energy use assessment of educational buildings: Toward a campus-wide sustainable energy policy
TL;DR: In this paper, the authors analyzed the energy consumption trends of 10 LEED-certified buildings and 14 non-LEED certified buildings at a major university in the US and found that the average energy use intensity (EUI) of the LEED buildings was significantly higher than non-leeds buildings.
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Utility of genetic algorithms for solving large scale construction time/cost trade-off problems
TL;DR: A number of simple, yet effective, techniques that improve GA performance for TCT problems are demonstrated; the most effective of which is a novel problem encoding, based on weighted graphs, that enables the critical path problem to be partially solved for all candidate solutions a priori, thus significantly increasing fitness evaluation.