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Assessing the Stability of Slopes Using Vector-Sum-Based Numerical Manifold Method and pattern search algorithm

ROCK MECHANICS AND ROCK ENGINEERING 2022年第6期55卷 3659-3673页

作者： Yang, Yongtao Wu, Wenan Chinese Acad Sci Inst Rock & Soil Mech State Key Lab Geomech & Geotech Engn Wuhan 430071 Peoples R China Beijing Univ Technol Key Lab Urban Secur & Disaster Engn Minist Educ Beijing 100124 Peoples R China

The Numerical Manifold Method (NMM) has been considered as an effective analysis method for geotechnical problems. A vector-sum-based numerical manifold method (VSNMM) combined with a pattern search algorithm (PSA), termed VSNMM-PSA, is further proposed to assess the stability of slopes. In this numerical method, PSA is applied for the determination of failure surface location. With the stress field of the slope obtained from a NMM-based elastoplastic calculation, the vector sum method (VSM) is used to predict trial safety factors for a series of trial failure surfaces (TFSs) during the failure-surface determination process. Stability analyses about three standard slopes are investigated with the proposed VSNMM-PSA model. Numerical results indicate that slopes' safety factors and failure surfaces can be accurately determined through the proposed VSNMM-PSA method. The proposed VSNMM-PSA method provides an effective tool to evaluate slopes' stability, and may improve their designs.

关键词： Vector sum method Numerical manifold method Failure surface pattern search algorithm Safety factor

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Fiber optic active alignment method based on a pattern search algorithm

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OPTICAL ENGINEERING 2006年第4期45卷 045005-1-045005页

作者： Chun, J Wu, YL Dai, YF Li, SY Natl Univ Def Technol Coll Mechatron Engn & Automat Changsha 410073 Peoples R China

Automation of fiber optic alignment is critical to reduce the cost of fiber optic devices packaging and ensure the quality of the products. The conventional fiber optic alignment method based on a hill-climbing algorithm is usually time consuming and it often fails to search the optimal alignment position. The reason is that the hill-climbing algorithm is a 1-D method, while multiple degrees of freedom (DOF) adjustments are needed in fiber optic alignment processes. The hill-climbing algorithm will be subject to noise because of intercoupling among axes. Thus, application of the pattern search algorithm in fiber optic alignment automation is developed in this work. The pattern search algorithm can adjust misalignments on multiple axial directions simultaneously. The intercoupling problem can be solved, and then the potential risk of missing the real peak can be avoided. Comparison of the simulation and experimental results between the pattern search and the hill-climbing algorithm is presented. Simulation results indicate that the pattern search algorithm converges nine times faster than the hill-climbing algorithm;it converges to the maximum coupling efficiency within eight iterations for the five degrees of freedom alignment between the laser diode and the single mode fiber. The experimental results demonstrate that the average time for locating the optimal coupling position in the x-y plane using the pattern search algorithm is reduced compared to the conventional hill-climbing algorithm;and the global convergence of the pattern search algorithm is much better than that of the hill-climbing algorithm. (c) 2006 Society of Photo-Optical Instrumentation Engineers.

关键词： fiber optic alignment pattern search algorithm hill-climbing algorithm fiber devices packaging automation

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Structural damage detection based on incomplete modal data using pattern search algorithm

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JOURNAL OF VIBRATION AND CONTROL 2013年第6期19卷 821-833页

作者： Kourehli, S. S. Amiri, G. Ghodrati Ghafory-Ashtiany, M. Bagheri, A. Islamic Azad Univ Dept Civil Engn Sci & Res Branch Tehran Iran Iran Univ Sci & Technol Sch Civil Engn Ctr Excellence Fundamental Studies Struct Engn Tehran Iran Int Inst Earthquake Engn & Seismol Struct Dept Tehran Iran Univ Pittsburgh Dept Civil & Environm Engn Pittsburgh PA USA

Incomplete sensed data in structures have made exact structural damage detection a serious challenge. In this paper, an effective method is presented for damage detection and estimation in structures based on incomplete modal data of a damaged structure via a pattern search algorithm. An objective function based on the condensed mass and stiffness matrices is formulated. The proposed method determines the damage to structural elements using optimization of the objective function by using pattern search algorithm. The performance of the presented method has been verified through two numerical examples, namely, a two-span continuous beam and a three-story plane frame with and without noise in the modal data containing several damages. Also, the effect of the discrepancy in mass and stiffness between the finite-element model and the actual tested dynamic system has been investigated. Furthermore, the experimental data from the vibration test of a mass-stiffness system are used for verification of the proposed approach. The results show that the presented method is sensitive to the location and severity of structural damage in spite of the incomplete modal data.

关键词： Damage detection incomplete modal data optimization pattern search algorithm

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Hybrid adaptive "gbest'-guided gravitational search and pattern search algorithm for automatic generation control of multi-area power system

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IET GENERATION TRANSMISSION & DISTRIBUTION 2017年第13期11卷 3257-3267页

作者： Khadanga, Rajendra Kumar Kumar, Amit Natl Inst Sci & Technol Dept Elect Engn Berhampur Odisha India Natl Inst Technol Dept Elect Engn Rourkela Odisha India

In this research article, a maiden approach of hybrid adaptive gbest' guided gravitational search and pattern search (hGGSA-PS) optimization method are proposed for load frequency control (LFC) of multi-area interconnected power system considering the nonlinear effect of generation rate constraint (GRC). At first, the two area single stage thermal-thermal power system with conventional proportional integral derivative (PID) controller is analyzed and the parameters of the PID controller are optimized by the proposed technique. Initially, the gbest' guided gravitational search algorithm (GGSA) using integral time absolute error (ITAE) fitness function is used and then pattern search (PS) technique is employed to fine-tune the obtained best solution from the GGSA. The supremacy of the hGGSA-PS optimized PID controller is presented by comparing its results with other modern soft computing techniques. Later in order to demonstrate the robustness of the proposed controller, the sensitive analysis is performed. Finally, the proposed technique is extended to a two area multi-source power system. The parameters of the controller for each area are optimized using the novel hGGSA-PS technique. From the simulation results, it can be seen that the proposed technique has superior performance than the prior results with lesser settling time and different performance index values.

关键词： power generation control search problems optimisation thermal power stations load regulation frequency control nonlinear control systems three-term control hydrothermal power systems performance index power system interconnection Hybrid adaptive gbest-guided gravitational search pattern search algorithm hGGSA-PS optimisation method automatic generation control multi-area interconnected power system load frequency control nonlinear effect generation rate constraint two-area single-stage thermal-thermal power system proportional integral derivative controller PID controller integral time absolute error ITAE fitness function multisource power system hydrothermal power system tie-line power deviation performance index

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Design of reduced search space strategy based on integration of Nelder-Mead method and pattern search algorithm with application to economic load dispatch problem

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NEURAL COMPUTING & APPLICATIONS 2018年第12期30卷 3693-3705页

作者： Chouhdry, Zafar-ur-Rehman Hasan, Khalid M. Raja, Muhammad Asif Zahoor Univ Engn & Technol Dept Elect Engn Lahore Pakistan COMSATS Inst Informat Technol Dept Elect Engn Attock Campus Attock Pakistan

This paper presents a novel hybrid technique for the solution of economic load dispatch problem with valve point loading effect using Nelder-Mead (NM) simplex method and pattern search (PS) algorithm. Strength of globalized NM optimization algorithm has been employed to explore the search space for near optimal solution, and PS algorithm is used in combination with a search space reduction strategy, incorporating the principles of selection and stochastic reproduction, to fine-tune the result. The proposed technique has been applied to three different systems having 3, 13 and 40 generating units to demonstrate the application for small to large load dispatch set-up. The efficacy of the design scheme is established from comparison of the results with the state-of-the-art solvers, and it is found that the proposed scheme gives the best result in terms of mean cost while the average computational time is less than most of the reported methods.

关键词： Economic load dispatch Nelder-Mead method pattern search algorithm Hybrid techniques

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Determination of particle size distribution by light extinction method using improved pattern search algorithm with Tikhonov smoothing functional

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JOURNAL OF MODERN OPTICS 2012年第21期59卷 1829-1840页

作者： Wang, Li Sun, Xiaogang Xing, Jian Harbin Inst Technol Dept Automat Measurement & Control Engn Harbin 150001 Peoples R China Harbin Engn Univ Coll Sci Harbin 150001 Peoples R China

An inversion technique which combines the pattern search algorithm with the Tikhonov smoothing functional for retrieval of particle size distribution (PSD) by light extinction method is proposed. In the unparameterized shape-independent model, we first transform the PSD inversion problem into an optimization problem, with the Tikhonov smoothing functional employed to model the objective function. The optimization problem is then solved by the pattern search algorithm. To ensure good convergence rate and accuracy of the whole retrieval, a competitive strategy for determining the initial point of the pattern search algorithm is also designed. The accuracy and limitations of the proposed technique are tested by the inversion results of synthetic and real standard polystyrene particles immersed in water. In addition, the issues about the objective function and computation time are further discussed. Both simulation and experimental results show that the technique can be successfully applied to retrieve the PSD with high reliability and stability in the presence of random noise. Compared with the PhillipsTwomey method and genetic algorithm, the proposed technique has certain advantages in terms of reaching a more accurate and steady optimal solution with less computational effort, thus making this technique more suitable for quick and accurate measurement of PSD.

关键词： light extinction method particle size distribution retrieval pattern search algorithm inversion method

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Hypersonic flight vehicle trajectory optimization using pattern search algorithm

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OPTIMIZATION AND ENGINEERING 2018年第1期19卷 125-161页

作者： Kumar, G. Naresh Ikram, Mohammad Sarkar, A. K. Talole, S. E. Def Res & Dev Lab Kanchanbagh PO Hyderabad 500058 Andhra Pradesh India Def Inst Adv Technol Dept Aerosp Engn Pune 411025 Maharashtra India

In this work, trajectory optimization of an aerodynamically controlled hypersonic boost glide class of flight vehicle is presented. In order to meet the mission constraints such as controllability, skin temperature, and terminal conditions etc., the trajectory is optimized using a pattern search algorithm with the lift to drag (L/D) ratio as a control parameter. It is brought out that the approach offers a viable tool for optimizing trajectories for the considered class of vehicles. Further, the effects of the constraints on trajectory shape and performance are studied and the analysis is used to bring out an optimal vehicle configuration at the initial stage of the design process itself. The research also reveals that the pattern search algorithm offers superior performance in comparison with the genetic algorithm for this class of optimization problem.

关键词： Hypersonic boost-glide vehicle Trajectory optimization pattern search algorithm Aerodynamic configuration design Skin temperature

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Mixed variable optimization of a load-bearing thermal insulation system using a filter pattern search algorithm

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OPTIMIZATION AND ENGINEERING 2004年第2期5卷 157-177页

作者： Abramson, MA USAF Inst Technol Dept Math & Stat Wright Patterson AFB OH 45433 USA

This paper describes the optimization of a load-bearing thermal insulation system characterized by hot and cold surfaces with a series of heat intercepts and insulators between them. The optimization problem is represented as a mixed variable programming (MVP) problem with nonlinear constraints, in which the objective is to minimize the power required to maintain the heat intercepts at fixed temperatures so that one surface is kept sufficiently cold. MVP problems are more general than mixed integer nonlinear programming (MINLP) problems in that the discrete variables are categorical;i.e., they must always take on values from a predefined enumerable set or list. Thus, traditional approaches that use branch and bound techniques cannot be applied. In a previous paper, a linearly constrained version of this problem was solved numerically using the Audet-Dennis generalized pattern search (GPS) method for MVP problems. However, this algorithm may not work for problems with general nonlinear constraints. A new algorithm that extends that of Audet and Dennis by incorporating a filter to handle nonlinear constraints makes it possible to solve the more general problem. Additional nonlinear constraints on stress, mass, and thermal contraction are added to that of the previous work in an effort to find a more realistic feasible design. Several computational experiments show a substantial improvement in power required to maintain the system, as compared to the previous literature. The addition of the new constraints leads to a very different design without significantly changing the power required. The results demonstrate that the new algorithm can be applied to a very broad class of optimization problems, for which no previous algorithm with provable convergence results could be applied.

关键词： mixed variable programming categorical variables filter algorithm pattern search algorithm thermal insulation heat intercepts nonlinear constraints

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Improved pattern search algorithm Based on Optimal Design of Fixture Locator Layout

Improved Pattern Search Algorithm Based on Optimal Design of...

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10th IEEE International Conference on Mechatronics and Automation (ICMA)

作者： Guo, Hua Wang, Kedian Liu, Zhihui Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Sch Mech Engn State Key Lab Mfg Syst Engn Xian 710049 Shaanxi Peoples R China

ISBN: (纸本)9781467355605

In the machining and detecting process, fixture is always one important part. Because it offers apropriate locating and clamping for the process, and a fixture with its locating accuracy affects much on the final accuracy. Therefore it is necessary to analysis the performance of a fixture, and the optimal design of fixture layout is a common way to improve its performance. Around the optimization design of fixture locator layout, firstly, the model of locators' tiny displacement and location variation of a workpiece was built and linearized to achieve a measurement of the fixture locating accuracy;secondly, to improve the optimal result of optimization algorithm, pattern search algorithm was introduced into locator layout design and improved;finally, one blade model was taken into an example, corresponding fixture layout optimization design was achieved. It is proved by the example that the optimization design method proposed can get a better computing result and a much less iterate steps.

关键词： Locating accuracy fixture design locator layout design pattern search algorithm

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Dynamic Optimal Operation of Microgrid for Reduced Costs Based on pattern search algorithm

Dynamic Optimal Operation of Microgrid for Reduced Costs Bas...

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International Conference on Electrical Machines and Systems (ICEMS)

作者： Xiao, Hao Pei, Wei Qu, Hui Kong, Li Ouyang, Hong Mu, Lianshun Univ Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Inst Elect Engn Beijing Peoples R China State Grid Elect Power Res Inst Beijing Peoples R China

ISBN: (纸本)9781479914463;9781479914470

To improve the economic and environmental friendliness of the Microgrid(MG), this paper presents a comprehensive model to determine the distributed generation (DG) optimum output power, which can be formulated as a high-dimensional nonlinear constrained "black box" optimization problem. pattern search (PS)-an effective optimization algorithm is introduced to solve this optimization problem. Simulations are performed on the IEEE 13-node test feeder with various load profile, and comparisons are performed with other existing mature algorithms, the results have demonstrated the efficiency of the proposed approach.

关键词： Microgrid Economic Optimal Operation pattern search algorithm OpenDSS

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