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The importance of lower-bound capaci...

Najjar, Shadi Sam.

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The importance of lower-bound capacities in geotechnical reliability assessments.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The importance of lower-bound capacities in geotechnical reliability assessments./
作者:	Najjar, Shadi Sam.
面頁冊數:	347 p.
附註:	Source: Dissertation Abstracts International, Volume: 66-08, Section: B, page: 4377.
Contained By:	Dissertation Abstracts International66-08B.
標題:	Engineering, Civil. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3185712
ISBN:	9780542278426

The importance of lower-bound capacities in geotechnical reliability assessments.
Najjar, Shadi Sam.

The importance of lower-bound capacities in geotechnical reliability assessments. - 347 p.

Source: Dissertation Abstracts International, Volume: 66-08, Section: B, page: 4377.

Thesis (Ph.D.)--The University of Texas at Austin, 2005.

The ability to manage risk in geotechnical engineering relies on a realistic assessment of the probability of failure for designs. Most reliability analyses focus on the mean and variance and an assumed, mathematically convenient distribution to model the left-hand tail of the distribution for capacity. However, the reliability of a geotechnical engineering system is governed by a physical constraint on the smallest available capacity. This lower-bound capacity is usually neglected in conventional reliability analyses.

ISBN: 9780542278426Subjects--Topical Terms:

783781
Engineering, Civil.

The importance of lower-bound capacities in geotechnical reliability assessments.
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245 1 4 $a The importance of lower-bound capacities in geotechnical reliability assessments.
300 $a 347 p.
500 $a Source: Dissertation Abstracts International, Volume: 66-08, Section: B, page: 4377.
500 $a Supervisor: Robert B. Gilbert.
502 $a Thesis (Ph.D.)--The University of Texas at Austin, 2005.
520 $a The ability to manage risk in geotechnical engineering relies on a realistic assessment of the probability of failure for designs. Most reliability analyses focus on the mean and variance and an assumed, mathematically convenient distribution to model the left-hand tail of the distribution for capacity. However, the reliability of a geotechnical engineering system is governed by a physical constraint on the smallest available capacity. This lower-bound capacity is usually neglected in conventional reliability analyses.
520 $a In this study, databases of load tests conducted on offshore and onshore deep foundations are analyzed to provide evidence for the existence of a lower-bound capacity that can be calculated using site-specific soil properties and information about the geometry of the foundation. Next, realistic probability distributions that can accommodate a lower-bound capacity are proposed and used to relate reliability to the lower-bound capacity. Multiple Load and Resistance Factor Design (LRFD) design-checking formats that include information on the lower-bound capacity in addition to the conventional design information are then introduced. Finally, practical approaches are presented for updating information about lower-bound capacities using installation data, proof-load data, and historical performance of foundations under load.
520 $a Databases with deep foundations show clear evidence of the existence of a lower-bound capacity that typically ranges from 0.4 to 0.8 of the predicted capacity in both cohesive and cohesionless soils. Results from reliability analyses indicate that the presence of a lower-bound capacity can have a significant effect on increasing the reliability of a deep foundation. The effect of the lower-bound capacity increases as the coefficient of variation for the capacity increases and as the target reliability index increases. This result indicates that reliability-based design codes need to incorporate information about lower-bound capacities. Incorporation of a lower-bound capacity into design is expected to provide a more realistic quantification of reliability for decision-making purposes and therefore a more rational basis for design.
590 $a School code: 0227.
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791 $a Ph.D.
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