Prakash Kripakaran

Works (3)

Updated: July 5th, 2023 15:54

2008 journal article

Computational framework for remotely operable laboratories

ENGINEERING WITH COMPUTERS, 24(4), 405–415.

By: P. Kripakaran*, A. Gupta n & V. Matzen n

author keywords: internet-enabled experiments; remote control; remote observation; web-based experiments; LabVIEW; distance education
TL;DR: A computational framework that uses LabVIEW and web technologies to enable observation and control of laboratory experiments via the internet via theinternet, which is illustrated for a shaketable experiment. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Source: Web Of Science
Added: August 6, 2018

2007 journal article

A novel optimization approach for minimum cost design of trusses

COMPUTERS & STRUCTURES, 85(23-24), 1782–1794.

By: P. Kripakaran*, A. Gupta n & J. Baugh n 

Contributors: P. Kripakaran*, A. Gupta n & J. Baugh Jr.

author keywords: truss design; structural optimization; hybrid search; genetic algorithms; member grouping; discrete sizing optimization; cost minimization
TL;DR: A new sizing approach that involves two algorithms applied in sequence - a novel approach to generate a ''good'' initial solution and a local search that attempts to generate the optimal solution by starting with the final solution from the previous algorithm is proposed. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: August 6, 2018

2005 journal article

Genetic algorithm-based decision support for optimizing seismic response of piping systems

Journal of Structural Engineering, 131(3), 389–398.

By: A. Gupta n, P. Kripakaran n, G. Mahinthakumar  n & J. Baugh n 

Contributors: A. Gupta n, P. Kripakaran n, G. Mahinthakumar  n & J. Baugh Jr.

TL;DR: This paper describes computational approaches used in a prototype decision support system (DSS) for seismic design and performance evaluation of piping supports and a novel seeding technique, which overcomes the inefficiencies of conventional methods in the context of pipe support optimization. (via Semantic Scholar)
Sources: NC State University Libraries, ORCID, NC State University Libraries
Added: August 6, 2018

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