Open Access. Powered by Scholars. Published by Universities.®
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Systems Engineering and Multidisciplinary Design Optimization
- Keyword
-
- Kriging (2)
- Antenna design (1)
- Bisection algorithm (1)
- Branch-line couplers (1)
- Co-simulation modeling (1)
-
- Cokriging (1)
- Compact couplers (1)
- Design under uncertainty (1)
- Dual-band patch antenna (1)
- EM-driven design (1)
- Electromagnetic simulations (1)
- Kriging metamodels (1)
- MAPOD (1)
- MCS (1)
- Metamodeling (1)
- Multi-objective optimization (1)
- NDT (1)
- Nondestructive evaluation (1)
- Nondestructive testing (1)
- PC-Kriging (1)
- Polynomial chaos expansion (1)
- Polynomial chaos expansions (1)
- Sensitivity analysis (1)
- Simulations (1)
- Stochastic metamodeling (1)
- Stochastic surrogates (1)
- Surrogate modeling (1)
- Surrogate-based optimization (1)
- Transonic airfoil design (1)
- Ultrasonic testing (1)
Articles 1 - 13 of 13
Full-Text Articles in Aerospace Engineering
Applications Of Polynomial Chaos-Based Cokriging To Aerodynamic Design Optimization Benchmark Problems, Jethro Nagawkar, Leifur Leifsson, Xiaosong Du
Applications Of Polynomial Chaos-Based Cokriging To Aerodynamic Design Optimization Benchmark Problems, Jethro Nagawkar, Leifur Leifsson, Xiaosong Du
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In this work, the polynomial chaos-based Cokriging (PC-Cokriging) is applied to a benchmark aerodynamic design optimization problem. The aim is to perform fast design optimization using this multifidelity metamodel. Multifidelity metamodels use information at multiple levels of fidelity to make accurate and fast predictions. Higher amount of lower fidelity data can provide important information on the trends to a limited amount of high-fidelity (HF) data. The PC-Cokriging metamodel is a multivariate version of the polynomial chaos-based Kriging (PC-Kriging) metamodel and its construction is similar to Cokriging. It combines the advantages of the interpolation-based Kriging metamodel and the regression-based polynomial chaos …
A B-Spline-Based Generative Adversarial Network Model For Fast Interactive Airfoil Aerodynamic Optimization, Xiaosong Du, Ping He, Joaquim R.R.A. Martins
A B-Spline-Based Generative Adversarial Network Model For Fast Interactive Airfoil Aerodynamic Optimization, Xiaosong Du, Ping He, Joaquim R.R.A. Martins
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Airfoil aerodynamic optimization is of great importance in aircraft design; however, it relies on high-fidelity physics-based models that are computationally expensive to evaluate. In this work, we provide a methodology to reduce the computational cost for airfoil aerodynamic optimization. Firstly, we develop a B-spline based generative adversarial networks (BSplineGAN) parameterization method to automatically infer design space with sufficient shape variability. Secondly, we construct multi-layer neural network (MNN) surrogates for fast predictions on aerodynamic drag, lift, and pitching moment coefficients. The BSplineGAN has a relative error lower than 1% when fitting to UIUC database. Verification of MNN surrogates shows the root …
Fast Yield Estimation Of Multi-Band Patch Antennas By Pc-Kriging, Xiaosong Du, Leifur Leifsson, Slawomir Koziel
Fast Yield Estimation Of Multi-Band Patch Antennas By Pc-Kriging, Xiaosong Du, Leifur Leifsson, Slawomir Koziel
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The PC-Kriging metamodeling method is proposed for yield estimation of multi-band patch antennas. PC-Kriging is a combination of polynomial chaos expansion (PCE) and Kriging metamodeling, where PCE is used as a trend function for the Kriging interpolation metamodel. The method is demonstrated on the Ishigami analytical function and a dual-band patch antenna. The PC-Kriging is shown to reach the prescribed accuracy limit with significantly fewer training points than both PCE and Kriging. This translates into considerable computational savings of yield estimation over alternative metamodel-based procedures and direct EM-driven Monte Carlo simulation. The saving are obtained without compromising evaluation reliability.
Multifidelity Modeling Of Ultrasonic Testing Simulations With Cokriging, Leifur Leifsson, Xiaosong Du, Slawomir Koziel
Multifidelity Modeling Of Ultrasonic Testing Simulations With Cokriging, Leifur Leifsson, Xiaosong Du, Slawomir Koziel
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Multifidelity methods are introduced to the nondestructive evaluation (NDE) of measurement systems. In particular, Cokriging interpolation metamodels of physics-based ultrasonic testing (UT) simulation responses are utilized to accelerate the uncertainty propagation in model-assisted NDE. The proposed approach is applied to a benchmark test case of UT simulations and compared with the current state-of-the-art techniques. The results show that Cokriging captures the physics of the problem well and is able to reduce the computational burden by over one order of magnitude compared to the state of the art. To the best of the author's knowledge, this the first time multifidelity methods …
Fast Uncertainty Propagation Of Ultrasonic Testing Simulations For Mapod And Sensitivity Analysis, Xiaosong Du, Leifur Leifsson, Praveen Gurrala, Jiming Song, Slawomir Koziel
Fast Uncertainty Propagation Of Ultrasonic Testing Simulations For Mapod And Sensitivity Analysis, Xiaosong Du, Leifur Leifsson, Praveen Gurrala, Jiming Song, Slawomir Koziel
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Model-assisted probability of detection (MAPOD) and sensitivity analysis (SA) are widelyused for measuring the reliability of nondestructive testing (NDT) systems., such as ultrasonictesting (UT), and understanding the effects of uncertainty parameters. In this work, a stochastic expansion-based metamodel is used in lieu of the physics-based NDT simulation model for efficient uncertainty propagation while keeping satisfactory accuracy. The proposed stochasticmetamodeling approach is demonstrated for MAPOD and SA on a benchmark case for UT simulations on a fused quartz block with a spherically-void defect. The proposed approach is compared with direct Monte Carlo sampling (MCS), and MCS with Kriging metamodels. The results …
Efficient Inverse Design Of Transonic Airfoils Using Variable-Resolution Models And Manifold Mapping, Xiaosong Du, Leifur Leifsson, Slawomir Koziel
Efficient Inverse Design Of Transonic Airfoils Using Variable-Resolution Models And Manifold Mapping, Xiaosong Du, Leifur Leifsson, Slawomir Koziel
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This paper presents an efficient approach for simulation-based inverse design of airfoil shapes using variable-fidelity computational fluid dynamics models and manifold mapping (MM). Inverse design involves determining an airfoil shape fulfilling a given target performance characteristic. In particular, the pressure coefficient distribution is typically used in aerodynamic inverse design. Such a task can be challenging when using computationally expensive simulations. In the context of local optimization, the MM technique searches for a new design in the vicinity of the current design by constructing a fast multi-fidelity model, which is setup by the available evaluations of each of the high- and …
Surrogate Modeling Of Ultrasonic Simulations Using Data-Driven Methods, Xiaosong Du, Robert Grandin, Leifur Leifsson
Surrogate Modeling Of Ultrasonic Simulations Using Data-Driven Methods, Xiaosong Du, Robert Grandin, Leifur Leifsson
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Ultrasonic testing (UT) is used to detect internal flaws in materials and to characterize material properties. In many applications, computational simulations are an important part of the inspection-design and analysis processes. Having fast surrogate models for UT simulations is key for enabling efficient inverse analysis and model-assisted probability of detection (MAPOD). In many cases, it is impractical to perform the aforementioned tasks in a timely manner using current simulation models directly. Fast surrogate models can make these processes computationally tractable. This paper presents investigations of using surrogate modeling techniques to create fast approximate models of UT simulator responses. In particular, …
Aerodynamic Design Of A Rectangular Wing In Subsonic Inviscid Flow By Surrogate-Based Optimization, Xiaosong Du, Anand Amrit, Andrew Thelen, Leifur Leifsson, Yu Zhang, Zhong Hua Han, Slawomir Koziel
Aerodynamic Design Of A Rectangular Wing In Subsonic Inviscid Flow By Surrogate-Based Optimization, Xiaosong Du, Anand Amrit, Andrew Thelen, Leifur Leifsson, Yu Zhang, Zhong Hua Han, Slawomir Koziel
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The paper presents results of aerodynamic design of a rectangular wing in subsonic inviscid flow using surrogate-based local and global search algorithms. The aerodynamic design problem is formulated in Benchmark Cases 3 and 6 developed by the AIAA Applied Aerodynamics Discussion Group. Both involve lift-constrained drag minimization at a Mach number of 0.5 with relatively low lift coefficients (0.2625 and 0.375) with several nonlinear constraints and a small number design variables (up to 15). In this work, the local search is performed using variable-fidelity modelling and output space mapping, whereas the global search is performed using approximation-based surrogates. The paper …
Robust Airfoil Design Optimization Using Stochastic Expansions And Utility Theory, Xiaosong Du, Leifur Leifsson, Slawomir Koziel
Robust Airfoil Design Optimization Using Stochastic Expansions And Utility Theory, Xiaosong Du, Leifur Leifsson, Slawomir Koziel
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Efficient and effective robust airfoil design optimization is proposed by integrating stochastic expansions and utility theory. In this work, the stochastic expansions are generated efficiently using non-intrusive polynomial chaos (NIPC) expansions. The robust design problem is formulated using utility functions which transfer a targeted response using a prescribed mathematical function to represent the designers' risk preferences. The proposed approach is demonstrated using examples of lift-constrained airfoil drag minimization in transonic viscous flow using the Mach number as an uncertain variable in the range of 0.70 to 0.75. The results are compared with the common problem formulation for robust design of …
Aerodynamic Design Of The Rae 2822 In Transonic Viscous Flow: Single- And Multi-Objective Optimization Studies, Anand Amrit, Xiaosong Du, Andrew Thelen, Leifur Leifsson, Slawomir Koziel
Aerodynamic Design Of The Rae 2822 In Transonic Viscous Flow: Single- And Multi-Objective Optimization Studies, Anand Amrit, Xiaosong Du, Andrew Thelen, Leifur Leifsson, Slawomir Koziel
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This paper addresses a benchmark aerodynamic design problem proposed by the AIAA Aerodynamic Design Optimization Discussion Group: Drag minimization of the RAE 2822 in transonic viscous flow at a fixed lift coefficient with constraints on the pitching moment coefficient and the cross-sectional area. The single-objective optimization (SOO) problem is solved using surrogate-based optimization (SBO) with the surrogates constructed through output space mapping and variable-resolution Reynolds-Averaged Navier-Stokes computational fluid dynamics models. Improving the implementation of our search algorithms enabled us to obtain the SOO optimal design four times faster than in our prior work in terms of CPU time. To explore …
Airfoil Design Under Uncertainty Using Non-Intrusive Polynomial Chaos Theory And Utility Functions, Xiaosong Du, Leifur Leifsson, Slawomir Koziel, Adrian Bekasiewicz
Airfoil Design Under Uncertainty Using Non-Intrusive Polynomial Chaos Theory And Utility Functions, Xiaosong Du, Leifur Leifsson, Slawomir Koziel, Adrian Bekasiewicz
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Fast and accurate airfoil design under uncertainty using non-intrusive polynomial chaos (NIPC) expansions and utility functions is proposed. The NIPC expansions provide a means to efficiently and accurately compute statistical information for a given set of input variables with associated probability distribution. Utility functions provide a way to rigorously formulate the design problem. In this work, these two methods are integrated for the design of airfoil shapes under uncertainty. The proposed approach is illustrated on a numerical example of lift-constrained airfoil drag minimization in transonic viscous flow using the Mach number as an uncertain variable. The results show that compared …
Pareto Ranking Bisection Algorithm For Em-Driven Multi-Objective Design Of Antennas In Highly-Dimensional Parameter Spaces, Adrian Bekasiewicz, Slawomir Koziel, Leifur Leifsson, Xiaosong Du
Pareto Ranking Bisection Algorithm For Em-Driven Multi-Objective Design Of Antennas In Highly-Dimensional Parameter Spaces, Adrian Bekasiewicz, Slawomir Koziel, Leifur Leifsson, Xiaosong Du
Mechanical and Aerospace Engineering Faculty Research & Creative Works
A deterministic technique for fast surrogate-assisted multi-objective design optimization of antennas in highly-dimensional parameters spaces has been discussed. In this two-stage approach, the initial approximation of the Pareto set representing the best compromise between conflicting objectives is obtained using a bisection algorithm which finds new Pareto-optimal designs by dividing the line segments interconnecting previously found optimal points, and executing poll-type search that involves Pareto ranking. The initial Pareto front is generated at the level of the coarsely-discretized EM model of the antenna. In the second stage of the algorithm, the high-fidelity Pareto designs are obtained through optimization of corrected local-approximation …
Expedite Design Of Variable-Topology Broadband Hybrid Couplers For Size Reduction Using Surrogate-Based Optimization And Co-Simulation Coarse Models, Piotr Kurgan, Slawomir Koziel, Leifur Leifsson, Xiaosong Du
Expedite Design Of Variable-Topology Broadband Hybrid Couplers For Size Reduction Using Surrogate-Based Optimization And Co-Simulation Coarse Models, Piotr Kurgan, Slawomir Koziel, Leifur Leifsson, Xiaosong Du
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In this paper, we discuss a computationally efficient approach to expedite design optimization of broadband hybrid couplers occupying a minimized substrate area. Structure size reduction is achieved here by decomposing an original coupler circuit into low- and high-impedance components and replacing them with electrically equivalent slow-wave lines with reduced physical dimensions. The main challenge is reliable design of computationally demanding low-impedance slow-wave structures that feature a quasi-periodic circuit topology for wideband operation. Our goal is to determine an adequate number of recurrent unit elements as well as to adjust their designable parameters so that the coupler footprint area is minimal. …