Gradient projection for reliability-based design optimization using evidence theory

Alyanak, Edward J.; Grandhi, Ramana V.; Bae, Ha-Rok

doi:10.1080/03052150802168942

Cited by 42 publications

(15 citation statements)

References 9 publications

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“…To reduce computation cost and omit the intermediate function approximation required in Bae's metric, Alyanak et al (2008) introduced a PL_dec approximation metric termed the element boundary intersection method. This PL_dec approximation method focuses on determining where the limit state function intersects the boundary of the hypercube.…”

Section: Plausibility Decision Approximation Methodsmentioning

confidence: 99%

“…Plausibility decision also provides the ability to conduct a sensitivity analysis that can identify the relative importance of the individual uncertain variables. To reduce computational cost, Alyanak et al (2008) approximated the plausibility decision measure with a linear assumption. Each of the two plausibility decision methods mentioned requires numerical integration techniques, increasing in difficulty in multi-variable problems.…”

Section: Introductionmentioning

confidence: 99%

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Quantification of epistemic uncertainty in re-usable launch vehicle aero-elastic design

King

Grandhi

Benanzer

2012

Engineering Optimization

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Due to the inherent natural variability of parameters with re-usable launch vehicles, design without consideration of reliability measures may be unreliable and vulnerable to failure. Generally, in preliminary air vehicle design little information is known regarding design variable uncertainties, therefore requiring a technique that can quantify epistemic uncertainties. Evidence theory is employed to accomplish this task resulting in a reliability bound of belief and plausibility. Due to the discontinuous nature of the belief and plausibility function it is necessary to implement a continuous function known as plausibility decision to be used to calculate sensitivities that can be implemented in a gradient-based reliability-based design optimization algorithm. This research develops a new plausibility decision approximation that calculates sensitivities with respect to uncertain variables without introducing extra computational cost or numerical integration. This new metric was demonstrated in a sensitivity analysis of the aero-elastic flutter reliability of a re-usable launch vehicle's wing.

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Section: Plausibility Decision Approximation Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantification of epistemic uncertainty in re-usable launch vehicle aero-elastic design

King

Grandhi

Benanzer

2012

Engineering Optimization

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“…Using an EBDO framework (e.g., [23][24][25], the optimum geometric dimensions are sought to maximize the specific energy absorption (SEA) of the tube while keeping the maximum crush force ܲ ௫ less than its critical value ܲ ௫ . In light of the uncertainties in the material behavior over large plastic deformation, the corresponding EBDO problem of the stiffened tube is formulated as where is the vector of design variables (i.e., X 1 = t, X 2 = d, X 3 = S) and is the vector of uncertain material parameters (i.e., Y 1 = R, Y 2 = H) introduced in the previous section.…”

Section: Figure 5 Externally Stiffened Circular Tube With Associatedmentioning

confidence: 99%

Evidence-Based Design Optimization of Energy Absorbing Components under Material Field Uncertainty

Salehghaffari¹,

Rais‐Rohani²

2012

53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference

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An evidence-based framework for optimization of structural components under material field uncertainty is developed. The approach is applied to the evidence-based design optimization (EBDO) of a stiffened tube under axial impact load using an isotropic-elastic-plastic constitutive model to simulate dynamic material behavior. Uncertainty modeling considers the changes in material parameters that are caused by variability in material properties as well as incertitude in the experimental data and the procedure for determination of these parameters. Spatial variability is modeled using a joint field belief structure that includes the effects of both incertitude and randomness on the estimated material properties across the structural component. With propagation of field uncertainties, the evidence-based objective and design constraint functions are modeled. Surrogate models are used in different steps to facilitate both the field uncertainty propagation and subsequent solution of the EBDO problem. The results of the application of the developed methodology to EBDO of an energy-absorbing component are presented and discussed.

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“…Agarwal et al proposed a multidisciplinary EBDO approach based upon the sequential approximate optimization strategy [38]. An EBDO approach through using a gradient projection technique was proposed by Alyanak et al [39]. Three meta-modeling techniques for evidence-based reliability analysis were compared by Bai et al [40].…”

Section: Introductionmentioning
confidence: 99%

Evidence-theory-based analysis for the prediction of exterior acoustic field with epistemic uncertainties
Chen
¹
,
Yu
²
,
Xia
³

2015
Engineering Analysis with Boundary Elements
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Gradient projection for reliability-based design optimization using evidence theory

Cited by 42 publications

References 9 publications

Quantification of epistemic uncertainty in re-usable launch vehicle aero-elastic design

Quantification of epistemic uncertainty in re-usable launch vehicle aero-elastic design

Evidence-Based Design Optimization of Energy Absorbing Components under Material Field Uncertainty

Evidence-theory-based analysis for the prediction of exterior acoustic field with epistemic uncertainties

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