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A novel minimum weight formulation of topology optimization implemented with reanalysis approach

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING 2019年第5期120卷 567-579页

作者： Long, Kai Gu, Chunlu Wang, Xuan Liu, Jie Du, Yixian Chen, Zhuo Saeed, Nouman North China Elect Power Univ State Key Lab Alternate Elect Power Syst Renewabl Beijing 102206 Peoples R China Hefei Univ Technol Coll Civil Engn Hefei Anhui Peoples R China Guangzhou Univ Sch Mech & Elect Engn Ctr Res Leading Technol Special Equipment Guangzhou Guangdong Peoples R China China Three Gorges Univ Coll Mech & Power Engn Yichang Peoples R China

In this paper, we develop an efficient diagonal quadratic optimization formulation for minimum weight design problem subject to multiple constraints. A high-efficiency computational approach of topology optimization is implemented within the framework of approximate reanalysis. The key point of the formulation is the introduction of the reciprocal-type variables. The topology optimization seeking for minimum weight can be transformed as a sequence of quadratic program with separable and strictly positive definite Hessian matrix, thus can be solved by a sequential quadratic programming approach. A modified sensitivity filtering scheme is suggested to remove undesirable checkerboard patterns and mesh dependence. Several typical examples are provided to validate the presented approach. It is observed that the optimized structure can achieve lighter weight than those from the established method by the demonstrative numerical test. Considerable computational savings can be achieved without loss of accuracy of the final design for 3D structure. Moreover, the effects of multiple constraints and upper bound of the allowable compliance upon the optimized designs are investigated by numerical examples.

关键词： approximate reanalysis multigrid preconditioned conjugate gradients preconditioned conjugate gradient sequential quadratic programming topology optimization

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Nondeterministic Kriging for Engineering Design Exploration

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AIAA JOURNAL 2019年第4期57卷 1659-1670页

作者： Bae, Harok Clark, Daniel L. Forster, Edwin E. Wright State Univ Dept Mech & Mat Engn Dayton OH 45435 USA US Air Force Res Lab Wright Patterson AFB OH 45433 USA

In this paper, the nondeterministic kriging (NDK) method is proposed, aiming for the applications of engineering design exploration, especially when only a limited number of random samples is available from either nondeterministic simulations or physical experiments under uncertainty. To handle nondeterministic data, the proposed NDK method uses separate aleatory and epistemic uncertainty processes. In a general situation in which resources are limited in generating random samples, an aleatory variance is assessed via a local regression kernel process. It is often found that a prediction model built with a conventional kriging suffers from the overfitting issue, which becomes worse with noisy and random data. The proposed NDK method can provide physically meaningful insights into both the main trend and the prediction uncertainty of system behaviors by capturing uncertainty in the sample data and suppressing the numerical instability. The predicted uncertainty from the proposed approach can be represented in terms of distinguishable aleatory and epistemic uncertainties, which will be useful in a decision-making process for an adaptive model building and design exploration. The potential benefits of using the proposed NDK method are demonstrated with multiple numerical examples, including mathematical and aircraft concept design problems.

关键词： Statistical Distributions Trusses Bréguet Range Equation Fatigue Strength Numerical Stability Numerical Optimization Structural Integrity Kernel Functions sequential quadratic programming Maximum Likelihood Estimation

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Fourier Pseudospectral Method for Trajectory Optimization with Stability Requirements

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2020年第11期43卷 2073-2090页

作者： Laad, Dhruv Elango, Purnanand Mohan, Ranjith Indian Inst Technol Madras Dept Aerosp Engn Chennai 600036 Tamil Nadu India

Periodic trajectories that satisfy stability-based requirements are useful in many engineering applications. In this work, a time-domain approach using Fourier collocation for solving the Floquet eigenvector boundary value problem, and consequently estimating Floquet exponents and eigenvectors, is introduced. This method is incorporated into a Fourier pseudospectral trajectory optimization framework for generating open-loop stable solution, and for improving the damping of a specific mode identified using the information from Floquet eigenvectors. These applications are illustrated on the dynamic soaring solutions of three- and six-degree-of-freedom aircraft models, and numerical results highlighting the effectiveness of the pseudospectral Floquet computation over the traditional time-march approach are also presented.

关键词： Trajectory Optimization Pseudospectral Methods Dynamic Soaring Lyapunov Equation Boundary Value Problems Three Degrees of Freedom Fixed Wing Aircraft Numerical Optimization sequential quadratic programming Aircraft Dynamics

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Large deformation axial element for implicit constitutive relations

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INTERNATIONAL JOURNAL OF NON-LINEAR MECHANICS 2019年 110卷 9-15页

作者： Vivek, P. V. Saravanan, U. Indian Inst Technol Madras Dept Civil Engn Chennai 600036 Tamil Nadu India

This work documents the formulation of an axial element that could handle implicit constitutive relations. This formulation uses nodal displacements, member forces, and reaction forces as primary unknowns. For some assumed values of these primary unknowns satisfying the nodal equilibrium equations, the computed stretch and stress in the members need not be in agreement with the constitutive relation. Hence, these primary unknowns are found such that the error in the constitutive relation for the members are minimized subjected to the constraint that the nodal equilibrium equations hold. Axial element developed using this concept is used to analyze a few trusses. The results of this formulation are in agreement with the results obtained from ABAQUS when stress is an explicit function of the stretch ratio. Also, some statically determinate as well as indeterminate trusses are solved for an implicit constitutive relation and the reasonableness of the obtained results established.

关键词： Elasticity Implicit constitutive relation Truss Large deformation sequential quadratic programming

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Integrated intelligent computing paradigm for the dynamics of micropolar fluid flow with heat transfer in a permeable walled channel

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APPLIED SOFT COMPUTING 2019年 79卷 139-162页

作者： Mehmood, Ammara Afsar, Khan Zameer, Aneela Awan, Saeed Ehsan Raja, Muhammad Asif Zahoor Pakistan Inst Engn & Appl Sci Dept Elect Engn Islamabad Pakistan Allama Iqbal Open Univ Dept Phys Islamabad Pakistan PIEAS Dept Comp & Informat Sci Islamabad 45650 Pakistan COMSATS Univ Islamabad Dept Elect & Comp Engn Attock Campus Attock 43600 Pakistan

In this work, a novel application of bio-inspired computational heuristic paradigm is presented for micropolar fluid flow and heat transfer system in a channel with permeable walls by modeling competency of neural networks, global search of genetic algorithms, and rapid local convergence of sequential quadratic programming. Approximation theory in the mean squared error sense is exploited for the formulation of an objective function to solve the governing nonlinear fluidics system. The designed scheme is employed to study the dynamics of the model in terms of stream function, microrotation, concentration, and temperature profiles for prominent factors based on Reynolds number, Peclet number for diffusion of heat and mass, coupling, spin-gradient viscosity, micro inertia density parameters. The consistency and robustness of the solver are validated through statistical performance indices based on comparison with state of art Adams numerical method for accuracy and complexity measures. (C) 2019 Elsevier B.V. All rights reserved. In this work, a novel application of bio-inspired computational heuristic paradigm is presented for micropolar fluid flow and heat transfer system in a channel with permeable walls by modeling competency of neural networks, global search of genetic algorithms, and rapid local convergence of sequential quadratic programming. Approximation theory in the mean squared error sense is exploited for the formulation of an objective function to solve the governing nonlinear fluidics system. The designed scheme is employed to study the dynamics of the model in terms of stream function, microrotation, concentration, and temperature profiles for prominent factors based on Reynolds number, Peclet number for diffusion of heat and mass, coupling, spin-gradient viscosity, micro inertia density parameters. The consistency and robustness of the solver are validated through statistical performance indices based on comparison with state of art Adams numerical met

关键词： Micropolar fluidics systems Genetic algorithms Neural networks sequential quadratic programming Bio-inspired computing

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A Robust Iterative Learning Switching Controller for following Virtual Constraints: Application to a Hybrid Neuroprosthesis

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IFAC-PapersOnLine 2019年第34期51卷 28-33页

作者： Molazadeh, Vahidreza Sheng, Zhiyu Bao, Xuefeng Sharma, Nitin Department of Mechanical Engineering and Materials Science University of Pittsburgh PittsburghPA15261 United States Department of Bioengineering at the University of Pittsburgh United States

In this paper, a robust iterative learning switching controller that uses optimal virtual constraint is designed for a hybrid walking exoskeleton that uses functional electrical stimulation and a powered exoskeleton. The synthesis of iterative learning control with sliding-mode control improves tracking performance and accuracy. The motivation for designing this switching controller was to obtain joint torques either from functional electrical stimulation or electric motor. A generalized switching controller is utilized to switch based on the stimulated muscle fatigue state. For achieving stability in walking cycle, the controller is used to force the system to follow the designed virtual constraints. The combination of sequential quadratic programming and genetic-particle swarm optimization algorithm is used for deriving the virtual constraints. The effectiveness of the new iterative learning control for output tracking is verified in a simple model of walking (3-link) that has active actuation at the hip joints. © 2019

关键词： Controllers E learning Exoskeleton (Robotics) Functional electric stimulation Iterative methods Learning algorithms Neurosurgery Particle swarm optimization (PSO) quadratic programming Sliding mode control Switching Two term control systems Functional electri cal stimulations Genetic particle swarm optimizations Iterative learning control sequential quadratic programming Switching controllers Tracking performance Virtual constraints Walking exoskeleton

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Fault Location Observability Using Phasor Measurement Units in a Power Network Through Deterministic and Stochastic Algorithms

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2019年第3期47卷 212-229页

作者： Theodorakatos, Nikolaos P. Natl Tech Univ Athens ECE Dept Iroon Polytech 9 Athens 15780 Greece

This article studies deterministic and stochastic algorithms for placing minimum number of phasor measurement units (PMUs) in a power system in order to locate any fault in the power system. The optimization problem is initially formulated in a mixed integer linear programing framework with binary-valued variables as well as in a binary integer linear programing model. Then, the optimization problem is formulated as an equivalent non-linear programing model, minimizing a quadratic objective function subject to equality non-linear constraints defined over a bounded and closed set. The problem is solved by using a sequential quadratic programming algorithm. The non-linear program is illustrated with a 7-bus test system. Also, stochastic algorithms such as binary-coded genetic algorithm and particle swarm optimization have been implemented in solving the optimal PMU placement under fault condition. The accuracy of suggested algorithms is independent from the fault type and its resistance. The optimization models are applied to the IEEE systems. The numerical results indicate that the proposed algorithms locate minimizers at the optimal objective function value in complete agreement with those obtained by branch-and-bound algorithms.

关键词： phasor measurement unit fault network observability mixed integer programming branch-and-bound algorithm non-linear programming sequential quadratic programming genetic algorithm particle swarm optimization

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Fast Estimation of Perturbed Impulsive Rendezvous via Semi-Analytical Equality-Constrained Optimization

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2020年第12期43卷 2383-2390页

作者： Huang, An-Yi Luo, Ya-Zhong Li, Heng-Nian Natl Univ Def Technol Coll Aerosp Sci & Engn Changsha 410073 Peoples R China Xian Satellite Control Ctr State Key Lab Astronaut Dynam Xian 710043 Peoples R China Xian Satellite Control Ctr Xian Peoples R China

Researchers involved initial and final coasting arcs and obtained a contour plot of the cost versus separation angle and transfer time to find the global optimal two-impulse solution in a study. They proposed an analytical method to solve the out-of-plane rendezvous problem between two close elliptic orbits. The study described how to formulate and solve the equality-constrained optimization problem when only the right ascension of the ascending node (RAAN) difference between the chaser and target is considered using a J₂-perturbed analytical dynamics model. The equality-constrained optimization problem is first extended to include the differences of orbital semi-major axis, inclination, and RAAN together. The proposed estimation method was verified by comparing with Jet Propulsion Laboratory’s (JPL’s) champion solution for a debris removal mission and the recently reported solutions for the 2003/2005 Mars sample return (MSR) mission.

关键词： Numerical Optimization sequential quadratic programming Trajectory Optimization Mars Orbit Rendezvous Orbital Elements Jet Propulsion Laboratory Argument of Latitude Perigee FORTRAN Monte Carlo Simulation

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Improved optical tomography based on hybrid frequency-domain and time-domain radiative transfer model

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INFRARED PHYSICS & TECHNOLOGY 2020年 111卷 103484-103484页

作者： Zhao, Fang-Zhou Qi, Hong Liu, Shao-Bin Ren, Ya-Tao Harbin Inst Technol Sch Energy Sci & Engn 92 West Dazhi St Harbin 150001 Peoples R China Minist Ind & Informat Technol Key Lab Aerosp Thermophys Harbin 150001 Peoples R China

Based on the hybrid frequency-domain (FD) and time-domain (TD) radiative transfer equation (RTE), a novel reconstruction strategy is developed to retrieve the optical parameter fields in the participating medium. The discrete ordinate method is employed to solve the forward FD and TD RTE to simulate the radiative transfer process. The sequential quadratic programming is utilized to solve the inverse problem for obtaining the optical parameters combined with an adjoint method. The Otsu algorithm is applied to the FD reconstructed results to distinguish the target region and the background region. To overcome the ill-posedness of the inverse problem, the generalized Gaussian Markov random field model is employed as the regularization term in the objective function. Various numerical experiments are studied and all results demonstrate that the proposed hybrid reconstruction scheme is suitable for efficient and accurate optical tomography by combining the FD and TD radiative transfer models. Meanwhile, the crosstalk of the ill-posed inverse problem can be alleviated effectively.

关键词： Optical tomography Otsu algorithm sequential quadratic programming Frequency-domain and time-domain Radiative transfer equation

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SIMSHOL: A Predictive Simulation Approach to Inform Helicopter-Ship Clearance Trials

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JOURNAL OF AIRCRAFT 2020年第5期57卷 854-875页

作者： Memon, Wajih A. Owen, Ieuan White, Mark D. Univ Liverpool Sch Engn Liverpool L69 3GH Merseyside England Univ Liverpool Mech Engn Sch Engn Liverpool L69 3GH Merseyside England

This paper presents the development of a simulation framework, SIMSHOL, which has a predictive capability to inform and support real-world ship-helicopter operating limit trials for a range of helicopter-ship combinations. SIMSHOL is a desktop-based predictive simulation tool that presents an objectively optimized human pilot modeling technique within an integrated pilot-vehicle-environment that represents the helicopter-ship dynamic interface (HSDI). The overall scheme employs a multiloop pursuit "paper" pilot model, a linearized helicopter flight dynamics model with a new enhanced spatial turbulence model, together with an objective optimization loop. To simulate the ship-airwake turbulence effect, a new spatial airwake disturbance modeling technique has been developed, which, in real time, captures the spectral characteristics of the turbulence around the ship from acomputational fluid dynamics-computed ship airwake. Time- and frequency-domain comparisons have been made between SIMSHOL and piloted simulation flight trial experiments. It was observed that the performance of the SIMSHOL tool in maintaining sufficient clearance between the aircraft and the ship's landing deck and hangar, while rejecting airwake disturbances, is well within the desired task performance boundaries. These investigations have shown that the tool is capable of representing the dynamics of a pilot-vehicle-task system in the challenging HSDI environment. Moreover, an automatic error-minimization-based response optimization methodology has been developed and used, which uses the iterative gradient descent optimization algorithm to objectively tune the pilot-vehicle loop transfer functions to represent a pilot's performance in the simulator. The results show that SIMSHOL is able to predict operational limits for a range of different helicopter-ship and environmental combinations.

关键词： Helicopter Rotor Test Pilots Pilot Modeling Proportional Integral Derivative CFD Helicopter Flight Dynamics Turbulence Models sequential quadratic programming Power Spectral Density Atmospheric Turbulence

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