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Optimization of Daylighting and Ener...

ProQuest Information and Learning Co.

Optimization of Daylighting and Energy Performance Using Parametric Design, Simulation Modeling, and Genetic Algorithms.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Optimization of Daylighting and Energy Performance Using Parametric Design, Simulation Modeling, and Genetic Algorithms./
Author:	Fang, Yuan.
Description:	1 online resource (139 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 78-10(E), Section: A.
Contained By:	Dissertation Abstracts International78-10A(E).
Subject:	Architecture. -
Online resource:	click for full text (PQDT)
ISBN:	9781369855944

Optimization of Daylighting and Energy Performance Using Parametric Design, Simulation Modeling, and Genetic Algorithms.
Fang, Yuan.

Optimization of Daylighting and Energy Performance Using Parametric Design, Simulation Modeling, and Genetic Algorithms. - 1 online resource (139 pages)

Source: Dissertation Abstracts International, Volume: 78-10(E), Section: A.

Thesis (Ph.D.)--North Carolina State University, 2017.

Includes bibliographical references

With the increasing demand for sustainable design and green buildings, performance is becoming an important driving force behind design decisions. Currently, however, only limited design options have been explored, and there are limited performance evaluation methods available for designers in the early design stages. This research proposes a new building performance optimization process that can help designers evaluate both daylighting and energy performance, generate optimized design options, and understand the relationship between design variables and performance metrics.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369855944Subjects--Topical Terms:

555123
Architecture.
Index Terms--Genre/Form:

554714
Electronic books.

Optimization of Daylighting and Energy Performance Using Parametric Design, Simulation Modeling, and Genetic Algorithms.
LDR:02586ntm a2200325Ki 4500 001 919593
005 20181129115238.5
006 m o u
007 cr mn||||a|a||
008 190606s2017 xx obm 000 0 eng d
020 $a 9781369855944
035 $a (MiAaPQ)AAI10610711
035 $a AAI10610711
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Fang, Yuan. $3 1194205
245 1 0 $a Optimization of Daylighting and Energy Performance Using Parametric Design, Simulation Modeling, and Genetic Algorithms.
264 0 $c 2017
300 $a 1 online resource (139 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 78-10(E), Section: A.
502 $a Thesis (Ph.D.)--North Carolina State University, 2017.
504 $a Includes bibliographical references
520 $a With the increasing demand for sustainable design and green buildings, performance is becoming an important driving force behind design decisions. Currently, however, only limited design options have been explored, and there are limited performance evaluation methods available for designers in the early design stages. This research proposes a new building performance optimization process that can help designers evaluate both daylighting and energy performance, generate optimized design options, and understand the relationship between design variables and performance metrics.
520 $a The proposed method of performance optimization utilizes various tools and technologies including parametric design, building simulation modeling, and Genetic Algorithms. In this method, building design alternatives are extensively explored through parametric design. Daylighting and energy modeling and simulation are performed to evaluate building performance. Genetic Algorithms is used to identify design options with optimal energy and daylighting performance. A case study was conducted to test and verify the effectiveness of the optimization process. The geometry of the case study building was optimized through the test in three different climate conditions. Various results were analyzed and potential influence of design decisions in different environments were discussed.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Architecture. $3 555123
650 4 $a Architectural engineering. $3 1180400
655 7 $a Electronic books. $2 local $3 554714
690 $a 0729
690 $a 0462
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a North Carolina State University. $b Design. $3 1194194
773 0 $t Dissertation Abstracts International $g 78-10A(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10610711 $z click for full text (PQDT)

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