Analysis and Sensitivity Calculation using High Fidelity Spectral Formulation-Based FSI and Coupled Adjoint Method

2016 ◽  
Author(s):  
Rachit Prasad ◽  
Hyun Soon Kim ◽  
Dongkyun Im ◽  
Seongim Choi ◽  
Seulgi Yi
Keyword(s):  
Adjoint Method ◽  
High Fidelity ◽  
Sensitivity Calculation

Development of Adjoint Solvers for Engineering Gradient-Based Turbomachinery Design Applications

2009 ◽  
Author(s):  
Andre C. Marta ◽  
Sriram Shankaran ◽  
D. Graham Holmes ◽  
Alexander Stein
Keyword(s):  
Adjoint Method ◽  
Automatic Differentiation ◽  
High Fidelity ◽  
Optimization Approach ◽  
Discrete Adjoint ◽  
Gradient Based ◽  
Computational Fluid Dynamics Cfd ◽  
And Function ◽  
Turbomachinery Design ◽  
Fine Tune

High-fidelity computational fluid dynamics (CFD) are common practice in turbomachinery design. Typically, several cases are run with manually modified parameters based on designer expertise to fine-tune a machine. Although successful, a more efficient process is desired. Choosing a gradient-based optimization approach, the gradients of the functions of interest need to be estimated. When the number of variables greatly exceeds the number of functions, the adjoint method is the best-suited approach to efficiently estimate gradients. Until recently, the development of CFD adjoint solvers was regarded as complex and difficult, which limited their use mostly to academia. This paper focuses on the problem of developing adjoint solvers for legacy industrial CFD solvers. A discrete adjoint solver is derived with the aid of an automatic differentiation tool that is selectively applied to the CFD code that handles the residual and function evaluations. The adjoint-based gradients are validated against finite-difference and complex-step derivative approximations.

Aerofoil profile and sweep optimisation for a blended wing-body aircraft using a discrete adjoint method

2006 ◽  
Vol 110 (1111) ◽  
pp. 589-604 ◽  
Author(s):  
A. Le Moigne ◽  
N. Qin
Keyword(s):  
Sequential Quadratic Programming ◽  
Adjoint Method ◽  
Navier Stokes ◽  
High Fidelity ◽  
Sweep Angle ◽  
Sqp Method ◽  
Discrete Adjoint ◽  
Design Variables ◽  
Variable Fidelity ◽  
Blended Wing Body

Abstract Aerodynamic optimisations of a blended wing-body (BWB) aircraft are presented. A discrete adjoint solver is used to calculate efficiently the gradients, which makes it possible to optimise for a large number of design variables. The optimisations employ either a variable-fidelity method that combines low- and high-fidelity models or a direct sequential quadratic programming (SQP) method. Four Euler optimisations of a BWB aircraft are then presented. The optimisation is allowed to change a series of master sections defining the aircraft geometry as well as the sweep angle on the outer wing for two of the optimisations. Substantial improvements are obtained, not only in the Euler mode but also when the optimised geometries are evaluated using Reynolds-averaged Navier-Stokes solutions. Some interesting features of the optimised wing profiles are discussed.

scholarly journals Generalized Perturbation Theory Based Total Sensitivity and Uncertainty Analysis for High-Fidelity Neutronics Calculation

2021 ◽  
Vol 9 ◽  
Author(s):  
Ji Ma ◽  
Chen Hao ◽  
Guanghao Liu ◽  
Le Kang ◽  
Peijun Li ◽  
...  
Keyword(s):  
Perturbation Theory ◽  
Uncertainty Analysis ◽  
Sensitivity Coefficient ◽  
Numerical Results ◽  
High Fidelity ◽  
Two Dimensional ◽  
Sensitivity Calculation ◽  
Generalized Perturbation Theory ◽  
Fuel Pin ◽  
Total Sensitivity

Neutronics calculation for nuclear reactor with high-fidelity technology can significantly reduce the uncertainties propagated from numerical approximation error and model error. However, the uncertainty of input parameters inevitably exists, especially for nuclear data. On the other hand, resonance self-shielding calculation is essential for multi-group assumption based high-fidelity neutronics calculation, which introduce the implicit effect for calculation responses. In order to fully consider the implicit effects in the process of uncertainty quantification, a generalized perturbation theory (GPT) based implicit sensitivity calculation method is proposed in this paper. Combining the explicit sensitivity coefficient, which can be quantified using classic perturbation theory, the total sensitivity coefficient of calculation responses is obtained. Then the total sensitivity and uncertainty module is established in self-developed neutron transport code with high-fidelity technology-HNET. To verify the accuracy of the sensitivity calculation methods proposed in this paper, a two-dimensional fuel pin problem is chosen to verify the sensitivity results, and the numerical results show good agreement with results calculated by a direct perturbation method. Finally, uncertainty analysis for two-dimensional fuel pin problem is performed and some general conclusions are obtained from the numerical results.

Fast and Efficient Sensitivity Calculation Using Adjoint Method for 3 Phase Field-Scale History Matching

2009 ◽  
Author(s):  
Ramez Masoud Azmy ◽  
Ahmed Mohamed Daoud ◽  
Khaled Abdlel-Fattah ◽  
Mohamed H.M. Sayyouh
Keyword(s):  
Phase Field ◽  
History Matching ◽  
Adjoint Method ◽  
Field Scale ◽  
Sensitivity Calculation

Using the Theory of Planned Behavior to Predict Faking in Selection Exercises Varying in Fidelity

2018 ◽  
Vol 17 (3) ◽  
pp. 155-160 ◽  
Author(s):  
Daniel Dürr ◽  
Ute-Christine Klehe
Keyword(s):  
Theory Of Planned Behavior ◽  
Planned Behavior ◽  
Predictive Validity ◽  
Group Discussion ◽  
Role Play ◽  
Selection Procedure ◽  
High Fidelity ◽  
Selection Research ◽  
Play Group

Abstract. Faking has been a concern in selection research for many years. Many studies have examined faking in questionnaires while far less is known about faking in selection exercises with higher fidelity. This study applies the theory of planned behavior (TPB; Ajzen, 1991 ) to low- (interviews) and high-fidelity (role play, group discussion) exercises, testing whether the TPB predicts reported faking behavior. Data from a mock selection procedure suggests that candidates do report to fake in low- and high-fidelity exercises. Additionally, the TPB showed good predictive validity for faking in a low-fidelity exercise, yet not for faking in high-fidelity exercises.

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