Directing Exploration with 3D FEM Sensitivity and Data Uncertainty

Graettinger, Andrew J.; Dowding, Charles H.

doi:10.1061/(asce)1090-0241(1999)125:11(959)

Cited by 14 publications

(11 citation statements)

References 12 publications

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“…The estimated performance variance is analysed with two methods. First, in Figure 1 column 4, quantitatively directed exploration (QDE) is employed to identify the location of greatest performance variance, thereby identifying the location of the next sampling point [10]. After new information from a site is obtained, it is incorporated into a new model run and an updated performance variance is calculated.…”

Section: Methods For Calculating Project Performance Variancementioning

confidence: 99%

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Efficient conditional modeling for geotechnical uncertainty evaluation

Graettinger

Lee

Reeves

2001

Num Anal Meth Geomechanics

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SUMMARYA first-order Taylor series method including direct derivative coding (DDC) is presented as a computationally efficient method for producing the probability distribution associated with calculated geotechnical performance. The probability distribution is employed in reliability analyses to calculate the probability of failure, valuable information that is not typically associated with deterministic analyses. The probability distribution also is used to identify important input parameters and to direct sampling efforts. Another approach to generate the probability distribution is the Monte Carlo (MC) method, however, Taylor series results generally are calculated in less time than the MC approach. One key to the implementation of the Taylor series approach is efficient approximation of the sensitivities required by the Taylor series calculation. DDC provides the technique to produce an efficient Taylor series algorithm. Directly coding the sensitivity analysis into the engineering model is accomplished by automatic and hand programming of derivatives. ADIFOR 2.0 was employed to automatically add derivatives to an existing engineering analysis model. For this paper a meshing program and 3D FEM for soil deformation is used to demonstrate the DDC approach. Although DDC requires a large up-front programming effort, it is not site or data specific. Therefore, once the derivative programming has been performed, the numerical model can be applied to a wide variety of problems without additional user intervention.

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Section: Methods For Calculating Project Performance Variancementioning

confidence: 99%

“…Where R R R dV is the integral over the volume of the element. Employing Leibniz rule, (9) is rewritten as (10) @Se @z ¼…”

Section: Hand Differentiation Of the Engineering Analysis Programsmentioning

confidence: 99%

Efficient conditional modeling for geotechnical uncertainty evaluation

Graettinger

Lee

Reeves

2001

Num Anal Meth Geomechanics

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“…The sensitivity matrix was calculated by the DDC method [22,26]. In the DDC method, derivatives of dependent variables are coded directly in to the original program, which then simultaneously produces model outputs and derivatives of those outputs.…”

Section: Model Sensitivitymentioning

confidence: 99%

“…The LV identifies the location of the largest output uncertainty produced from input parameters. This is the original QDE approach proposed by Graettinger and Dowding [26] and Lee [22] that directs exploration to the next sampling location where the output variance is the largest. The output variances are the diagonal elements of Cov[h l , h k ] in Eq.…”

Section: Qde Approachesmentioning

confidence: 99%

Directed site exploration for permeable reactive barrier design

Lee¹,

Graettinger²,

Moylan³

et al. 2009

Journal of Hazardous Materials

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“…surface has been used to identify regions of greatest estimation error, implying that those areas would benefit from denser sampling during a revisit to the study site (Graettinger andDowding 1999, Wang et al 2000). The variograms from previous surveys have also been used to optimize sampling schemes (McBratney et al 1981, Domburg et al 1994.…”

Section: Introductionmentioning

confidence: 99%

A Real–time Adaptive Sampling Method for Field Mapping in Patchy, Heterogeneous Environments

Graniero

Robinson

2003

Transactions in GIS

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Many environmental studies require detailed maps describing the spatial distribution of various environmental characteristics. These distributions tend to be 'patchy'; that is, their structure and their relationships vary from place to place according to the influences of the local setting. We present a simple sampling method that adapts the sample spacing on a point-by-point basis as the data are collected. The resulting sample is denser in areas of higher variability and sparser in more 'well-behaved' areas, and is collected in a single traverse of the transect. It uses a combination of simple fuzzy functions representing the concepts 'too close' and 'too far' that are adaptively parameterized based on current measurements. The adaptive sampler produced better representations for 47% of simulated reference transects than uniform or random samples of the same size under perfect measurement conditions, increasing to best performance for 71% of the transects when measurement error was severe with only minimal increase in sampling density. The rapid calculations can be easily incorporated into real-time data acquisition software, and the method may be extended to achieve some type of compromise when faced with the need to sample multiple simultaneous variables.

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Directing Exploration with 3D FEM Sensitivity and Data Uncertainty

Cited by 14 publications

References 12 publications

Efficient conditional modeling for geotechnical uncertainty evaluation

Efficient conditional modeling for geotechnical uncertainty evaluation

Directed site exploration for permeable reactive barrier design

A Real–time Adaptive Sampling Method for Field Mapping in Patchy, Heterogeneous Environments

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