Gradient-based resolution enhancement optimization methods based on vector imaging model

2012 ◽  
Author(s):  
Xu Ma ◽  
Yanqiu Li ◽  
Lisong Dong
Keyword(s):  
Resolution Enhancement ◽  
Optimization Methods ◽  
Imaging Model ◽  
Gradient Based

An Adjoint Based Approach for Optimal Design of Morphing SMP

2013 ◽  
Author(s):  
Shuang Wang ◽  
John C. Brigham
Keyword(s):  
Shape Change ◽  
Mechanical Energy ◽  
Optimization Methods ◽  
Design Parameters ◽  
Optimization Strategy ◽  
Thermally Activated ◽  
Gradient Based ◽  
Nonlinear Optimization Methods ◽  
Numerical Representations ◽  
Objective Functional

This work presents a strategy to identify the optimal localized activation and actuation for a morphing thermally activated SMP structure or structural component to obtain a targeted shape change or set of shape features, subject to design objectives such as minimal total required energy and time. This strategy combines numerical representations of the SMP structure’s thermo-mechanical behavior subject to activation and actuation with gradient-based nonlinear optimization methods to solve the morphing inverse problem that includes minimizing cost functions which address thermal and mechanical energy, morphing time, and damage. In particular, the optimization strategy utilizes the adjoint method to efficiently compute the gradient of the objective functional(s) with respect to the design parameters for this coupled thermo-mechanical problem.

scholarly journals Benchmarking Adaptive Variational Quantum Eigensolvers

2020 ◽  
Vol 8 ◽  
Author(s):  
Daniel Claudino ◽  
Jerimiah Wright ◽  
Alexander J. McCaskey ◽  
Travis S. Humble
Keyword(s):  
Quantum State ◽  
Energy Eigenvalue ◽  
Molecular Size ◽  
Optimization Methods ◽  
Superior Performance ◽  
Prepared State ◽  
Gradient Based ◽  
Structure Problem ◽  
Relevant Finding ◽  
Electronic Ground

By design, the variational quantum eigensolver (VQE) strives to recover the lowest-energy eigenvalue of a given Hamiltonian by preparing quantum states guided by the variational principle. In practice, the prepared quantum state is indirectly assessed by the value of the associated energy. Novel adaptive derivative-assembled pseudo-trotter (ADAPT) ansatz approaches and recent formal advances now establish a clear connection between the theory of quantum chemistry and the quantum state ansatz used to solve the electronic structure problem. Here we benchmark the accuracy of VQE and ADAPT-VQE to calculate the electronic ground states and potential energy curves for a few selected diatomic molecules, namely H2, NaH, and KH. Using numerical simulation, we find both methods provide good estimates of the energy and ground state, but only ADAPT-VQE proves to be robust to particularities in optimization methods. Another relevant finding is that gradient-based optimization is overall more economical and delivers superior performance than analogous simulations carried out with gradient-free optimizers. The results also identify small errors in the prepared state fidelity which show an increasing trend with molecular size.

Non-Probabilistic Based Topology Optimization Under External Load Uncertainty With Eigenvalue-Superposition of Convex Models

2013 ◽  
Author(s):  
Xike Zhao ◽  
Hae Chang Gea ◽  
Wei Song
Keyword(s):  
Topology Optimization ◽  
External Load ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimization Method ◽  
Convex Model ◽  
Structure Response ◽  
Gradient Based ◽  
Bounded Convex ◽  
Topology Optimization Method

In this paper the Eigenvalue-Superposition of Convex Models (ESCM) based topology optimization method for solving topology optimization problems under external load uncertainties is presented. The load uncertainties are formulated using the non-probabilistic based unknown-but-bounded convex model. The sensitivities are derived and the problem is solved using gradient based algorithm. The proposed ESCM based method yields the material distribution which would optimize the worst structure response under the uncertain loads. Comparing to the deterministic based topology optimization formulation the ESCM based method provided more reasonable solutions when load uncertainties were involved. The simplicity, efficiency and versatility of the proposed ESCM based topology optimization method can be considered as a supplement to the sophisticated reliability based topology optimization methods.

Estimation of Thermal Boundary Conditions by Gradient Based and Genetic Algorythms

2012 ◽  
Vol 729 ◽  
pp. 144-149 ◽  
Author(s):  
Imre Felde
Keyword(s):  
Heat Transfer ◽  
Boundary Conditions ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Nsga Ii ◽  
Thermal Boundary Conditions ◽  
Treatment Processes ◽  
Gradient Based ◽  
Type Boundary

The prediction of third type boundary conditions occurring during heat treatment processes is an essential requirement for characterization of heat transfer phenomena. In this work, the performance of four optimization techniques is studied. These models are the Conjugate Gradient Method, the Levenberg-Marquardt Method, the Simplex method and the NSGA II algorithm. The models are used to estimate the heat transfer coefficient during transient heat transfer. The performance of the optimization methods is demonstrated using numerical techniques.

scholarly journals Fast Yaw Optimization for Wind Plant Wake Steering Using Boolean Yaw Angles

2021 ◽  
Author(s):  
Andrew P. J. Stanley ◽  
Christopher Bay ◽  
Rafael Mudafort ◽  
Paul Fleming
Keyword(s):  
Greedy Algorithm ◽  
Traditional Method ◽  
Mathematical Optimization ◽  
Optimization Methods ◽  
Optimization Method ◽  
New Method ◽  
Computationally Efficient ◽  
Gradient Based ◽  
Boolean Optimization ◽  
Plant Power

Abstract. In wind plants, turbines can be yawed into the wind to steer their wakes away from downstream turbines and achieve an overall increase in plant power. Mathematical optimization is typically used to determine the best yaw angles at which to operate the turbines in a plant. In this paper, we present a new method to rapidly determine the yaw angles in a wind plant. In this method, we define the turbine yaw angles as Boolean—either yawed at a predefined angle or nonyawed—as opposed to the typical methods of formulating yaw angles as continuous or with fine discretizations. We then optimize which turbines should be yawed with a greedy algorithm that sweeps through the turbines from the most upstream to the most downstream. We demonstrate that our new Boolean optimization method can find turbine yaw angles that perform well compared to a traditionally used gradient-based optimizer where the yaw angles are defined as continuous. There is less than 0.6 % difference in the optimized power between the two optimization methods for randomly placed turbine layouts. Additionally, we show that our new method is much more computationally efficient than the traditional method. For plants with nonzero optimal yaw angles, our new method is generally able to solve for the turbine yaw angles 50–150 times faster, and in some extreme cases up to 500 times faster, than the traditional method.

Metamodel-Based Optimum Design Examples of Structures

2014 ◽  
pp. 667-676
Author(s):  
Kwon-Hee Lee ◽  
Ji-In Heo
Keyword(s):  
Weight Reduction ◽  
Performance Enhancement ◽  
Fuel Efficiency ◽  
Optimization Methods ◽  
Optimization Method ◽  
The Other ◽  
True Response ◽  
Design Variables ◽  
Weight One ◽  
Gradient Based

In order to achieve greater fuel efficiency and energy conservation, the reduction of weight and enhancement of the performance of structures has been sought. In general, there are two approaches to reducing structural weight. One of which is to use materials that are lighter than steel and the other is to redesign the structure. However, conventional structural optimization methods using gradient-based algorithm directly have difficulties in defining complex shape design variables and preventing mesh distortions. To overcome these difficulties a metamodel-based optimization method is introduced in order to replace the true response by an approximate one. This research presents four case studies of structural design using a metamodel-based approximation model for weight reduction or performance enhancement.

Multidisciplinary Design Optimization of a Naval Surface Combatant

2003 ◽  
Vol 47 (01) ◽  
pp. 1-12 ◽  
Author(s):  
Daniele Peri ◽  
Emilio F. Campana
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimization Methods ◽  
Ship Design ◽  
Multidisciplinary Design ◽  
Construction Costs ◽  
Gradient Based ◽  
Numerical Tools ◽  
Surface Combatant ◽  
Hydrodynamic Optimization

Whereas shape optimal design has received considerable attention in many industrial contexts, the application of automatic optimization procedures to hydrodynamic ship design has not yet reached the same maturity. Nevertheless, numerical tools, combining together modern computational fluid dynamics and optimization methods, can aid in the ship design, enhancing the operational performances and reducing development and construction costs. This paper represents an attempt of applying a multidisciplinary design optimization (MDO) procedure to the enhancement of the performances of an existing ship. At the present stage the work involves modeling, development, and implementation of algorithms only for the hydrodynamic optimization. For a naval surface combatant, the David Taylor Model Basin (DTMB) model ship 5415, a three-objective functions optimization for a two-discipline design problem is devised and solved in the framework of the MDO approach. A simple decision maker is used to order the Pareto optimal solutions, and a gradient-based refinement is performed on the selected design.

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