检索结果-内蒙古大学图书馆

Refined ensemble-based waterflooding optimization subject to field-wide constraints

COMPUTATIONAL GEOSCIENCES 2020年第2期24卷 871-887页

作者： Tueros, Juan Alberto Rojas Horowitz, Bernardo Willmersdorf, Ramiro Brito de Oliveira, Diego Felipe Barbosa Univ Fed Pernambuco Dept Civil Engn Recife PE Brazil PETROBRAS Petr Brasileiro SA Rio De Janeiro RJ Brazil

In this work, we present a modification (refinement) of the ensemble-based method for constrained waterflooding optimization. The problem of determining life-cycle rate controls for both producer and injector wells that maximize the net present value, NPV, subject to well and field-wide capacity constraints is formulated and solved using sequential quadratic programming, SQP. The required gradient is approximately computed by an ensemble-based method. Field NPV is decomposed as the sum of the NPVs of each well. Sensitivity matrix of well NPVs with respect to controls of all wells is obtained from ensemble-based covariance matrices of controls and of well NPVs to controls. For efficiency reasons, ensemble size should be kept small which results in sampling errors. The approximate gradient is the sum of the columns of the refined sensitivity matrix. Using small-sized ensembles introduces spurious correlations that degrade gradient quality. Novel nondistance-based localization technique is employed to mitigate the deleterious effects of spurious correlations to refine the sensitivity of NPV of production wells with respect to injector controls. The localization technique is based on the connectivity of each injector/producer pair using a producer-based capacitance resistance model (CRMP). Competitiveness coefficients are developed to refine sensitivity of NPV of production wells with respect to producer controls, obtained using an interference test. A new procedure is proposed for consideration of maximum water-cut limit resulting in producer shut-in during the optimization process. Smoothing techniques are also introduced to avoid excessive abrupt jumps in well controls and to improve the overall optimization efficiency. Procedures and refinements are applied to a realistic reservoir taken from the literature, TNO Brugge Field, to demonstrate the resulting level of objective function improvement and variability reduction of the obtained solutions. NPV solution statist

关键词： Large-scale algorithm Ensemble-based method Waterflooding optimization sequential quadratic programming Refined sensitivity matrix Constrained optimization

来源：评论

学校读者我要写书评

暂无评论

A QCQP-based splitting SQP algorithm for two-block nonconvex constrained optimization problems with application

引用

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2021年 390卷 113368-113368页

作者： Jian, Jinbao Liu, Pengjie Yin, Jianghua Zhang, Chen Chao, Miantao Guangxi Univ Nationalities Guangxi Key Lab Hybrid Computat & IC Design Anal Coll Math & Phys Ctr Appl Math & Artificial Intelligence Nanning 530006 Peoples R China Guangxi Univ Coll Math & Informat Sci Nanning 530004 Peoples R China Guangxi Sci & Technol Normal Univ Coll Math & Comp Sci Laibin 546199 Peoples R China Univ Shanghai Sci & Technol Sch Mech Engn Shanghai 200093 Peoples R China

This paper discusses a class of two-block nonconvex smooth optimization problems with nonlinear constraints. Based on a quadratically constrained quadratic programming (QCQP) approximation, an augmented Lagrangian function (ALF), and a Lagrangian splitting technique into small-scale subproblems, we propose a novel sequential quadratic programming (SQP) algorithm. First, inspired by the augmented Lagrangian method (ALM), we penalize the quadratic equality constraints associated with the QCQP approximation subproblem in its objective by means of the ALF, and then split the resulting subproblem into two small-scale ones, but both of them are not quadratic programming (QP) due to the square of the quadratic equality constraints in the objective. Second, by ignoring the three-order infinitesimal arising from the squared term, the two small-scale subproblems are reduced to two standard QP subproblems, which can yield an improved search direction. Third, taking the ALF of the discussed problem as a merit function, the next iterate point is generated by the Armijo line search. As a result, a new SQP method, called QCQP-based splitting SQP method, is proposed. Under suitable conditions, the global convergence, strong convergence, iteration complexity and convergence rate of the proposed method are analyzed and obtained. Finally, preliminary numerical experiments and applications were carried out, and these show that the proposed method is promising. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Two-block nonconvex constrained optimization quadratically constrained quadratic programming sequential quadratic programming Splitting method Convergence analysis

来源：评论

学校读者我要写书评

暂无评论

Uncertainty Propagation by Linear Regression Kalman Filters for Stochastic NMPC

引用

IFAC-PapersOnLine 2021年第6期54卷 76-82页

作者： Rien Quirynen Karl Berntorp Mitsubishi Electric Research Laboratories Cambridge MA 02139 USA

Stochastic nonlinear model predictive control (SNMPC) allows to directly take model uncertainty into account, e.g., by including probabilistic chance constraints. This paper proposes linear-regression Kalman filtering to perform high-accuracy propagation of mean and covariance information for the nonlinear system dynamics in a tractable approximation of the stochastic optimal control problem. In addition, a tailored adjoint-based sequential quadratic programming (SQP) algorithm is presented to considerably reduce the computational cost and allow a real-time implementation of the resulting SNMPC. The prediction accuracy and control performance of the proposed approach are illustrated on a vehicle control application subject to external disturbances, while highlighting a worst-case computation time of 10 ms for SNMPC which is close to that of deterministic NMPC for this particular case study.

关键词： Stochastic nonlinear model predictive control linear-regression Kalman filtering sequential quadratic programming real-time optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

Force density sensitivity form-finding design method for cable-mesh reflector antennas considering interactive effects between cable network and supporting truss

引用

ENGINEERING STRUCTURES 2021年 244卷 112722-112722页

作者： Zhang, Shunji Zhang, Shuxin Zhang, Yiqun Ye, Jing Shaanxi Key Lab Space Solar Power Stn Syst Xian 710071 Peoples R China Xidian Univ Sch Electromech Engn Xian 710071 Peoples R China

Form-finding design is critical in determining whether a cable-mesh reflector antenna can meet electrical performance requirements. However, the current methods rarely consider the interactive effects between the cable network and the supporting truss in the form-finding process, which requires more iteration steps for good design results. This study presents a force density sensitivity form-finding design method for cable-mesh reflector antennas based on systematic equilibrium equations. The sensitivity matrix of the support truss vertex and the cable network free node is derived with respect to force density, and the form-finding process of the reflector antenna is transformed into a sequential quadratic programming problem that can be easily solved. The antenna meets the accuracy requirements, and has a more uniform distribution of internal cable net tension and a smaller truss deformation as a result of constraining the vertex deformation of the supporting truss and cable tension. For practical engineering problems, more accurate design results can be obtained quickly. The effectiveness of the proposed method is verified through numerical examples.

关键词： Form-finding Force density sensitivity matrix sequential quadratic programming Cable-mesh reflector

来源：评论

学校读者我要写书评

暂无评论

APPLICATIONS OF GUDERMANNIAN NEURAL NETWORK FOR SOLVING THE SITR FRACTAL SYSTEM

引用

FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY 2021年第8期29卷 2150250-2150250页

作者： Sabir, Zulqurnain Umar, Muhammad Raja, Muhammad Asif Zahoor Baleanu, Dumitru Hazara Univ Dept Math & Stat Mansehra Pakistan Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan Cankaya Univ Dept Math Ankara Turkey Inst Space Sci Magurele Romania

This study is related to explore the Gudermannian neural network (GNN) for solving a nonlinear SITR COVID-19 fractal system by using the optimization efficiencies of a genetic algorithm (GA), a global search technique and sequential quadratic programming (SQP) and a quick local search scheme, i.e. GNN-GA-SQP. The nonlinear SITR COVID-19 fractal system is dependent on four collections: "susceptible", "infected", "treatment" and "recovered". For the optimization procedures through the GNN-GA-SQP, a merit function is constructed using the nonlinear SITR COVID-19 fractal system and its corresponding initial conditions. The description of each collection of the nonlinear SITR COVID-19 fractal system is provided along with comprehensive detail. The comparison of the achieved numerical result performances of each collection of the nonlinear SITR COVID-19 fractal system is performed with the Adams results to verify the exactness of the designed computational GNN-GA-SQP. The statistical processes based on different operators are presented for 30 independent trials using 5 neurons to authenticate the consistency of the designed computational GNN-GA-SQP. Moreover, the graphs of absolute error (AE), performance indices, and convergence measures along with the boxplots and histograms are also plotted to check the stability, exactness and reliability of the designed computational GNN-GA-SQP.

关键词： Gudermannian Function SITR COVID-19 Fractal System Nonlinear Genetic Algorithm Reference Solutions sequential quadratic programming

来源：评论

学校读者我要写书评

暂无评论

Modified accelerate iteration for optical property reconstruction based on time-domain radiative transfer equation

引用

LASER PHYSICS 2021年第9期31卷 095601-095601页

作者： Zhao, Fang-Zhou Qi, Hong Zhao, Ying He, Ming-Jian Ren, Ya-Tao Harbin Inst Technol Sch Energy Sci & Engn Harbin 150001 Peoples R China Minist Ind & Informat Technol Key Lab Aerosp Thermophys Harbin 150001 Peoples R China

A modified diffusion synthetic acceleration method is proposed to speed up the convergence process of TD-RTE calculation by employing the finite element method, combined with OpenMP parallel technology to further enhance the computational efficiency. In addition, the sequential quadratic programming algorithm is applied with Gaussian Markov random field (GGMRF) regularization to reconstruct the absorption and scattering parameter fields simultaneously. The accuracy and efficiency of the proposed model are investigated. It was observed that the modified DSA model is more efficient with the increase of the optical thickness, where the acceleration ratio is improved to 6 for the optical thicker media. In addition, similar acceleration effect was witnessed for both scattering dominated and non-scattering dominated media. Furthermore, by employing the modified DSA model into the reconstruction, it is interesting to remark that not only the reconstruction time is significantly reduced with the acceleration ratio of 8-11, but also the reconstructed image is further improved. All the results indicate that the developed scheme is efficient and robust based on TD-RTE, showing great potential in optical imaging.

关键词： optical parameter mapping diffusion synthetic acceleration OpenMP time-domain radiative transfer equation sequential quadratic programming

来源：评论

学校读者我要写书评

暂无评论

A penalty-free approach to PDE constrained optimization: application to an inverse wave problem

引用

INVERSE PROBLEMS 2021年第5期37卷 055002-055002页

作者： Hoffmann, Alexandre Monteiller, Vadim Bellis, Cedric Aix Marseille Univ CNRS Cent Marseille LMAUMR 7031 Marseille France Univ Grenoble Alpes ISTerre Grenoble France

Inverse wave problems (IWPs) amount in non-linear optimization problems where a certain distance between a state variable and some observations of a wavefield is to be minimized. Additionally, we require the state variable to be the solution of a model equation that involves a set of parameters to be optimized. Typical approaches to solve IWPs includes the adjoint method, which generates a sequence of parameters and strictly enforces the model equation at each iteration, and, the wavefield reconstruction inversion (WRI) method, which jointly generates a sequence of parameters and state variable but does not strictly enforce the model. WRI is considered to be an interesting approach because, by virtue of not enforcing the model at each iteration, it expands the search space, and can thus find solutions that may not be found by a typical adjoint method. However, WRI techniques generally requires the tuning of a penalty parameter until the model equation is considered satisfied. Alternatively, a fixed penalty parameter can be chosen but, in such case, it is impossible for the algorithm to find a solution that satisfies the model equation exactly. In the present work, we present a, to our knowledge, novel technique of WRI type which jointly generates a sequence of parameters and state variable, and which loosely enforces the model. The method is based on a TR-SQP method which aims at minimizing, at each iteration, both the residual relative to the linearized model and a quadratic approximation of the cost functional. Our method approximately solves a sequence of quadratic subproblems by using a Krylov method. The Hessian-vector product is computed using the second-order adjoint method. The method is demonstrated on a synthetic case, with a configuration relevant to medical imaging.

关键词： full waveform inversion trust region method sequential quadratic programming wavefield reconstruction inversion adjoint method second order adjoint method

来源：评论

学校读者我要写书评

暂无评论

A hybrid gradient-based/metaheuristic method for Eurocode-compliant size, shape and topology optimization of steel structures

引用

ENGINEERING STRUCTURES 2021年 239卷 112137-112137页

作者： Dillen, Wouter Lombaert, Geert Schevenels, Mattias Katholieke Univ Leuven Fac Engn Sci Dept Architecture Kasteelpk Arenberg 1 B-3001 Leuven Belgium Katholieke Univ Leuven Fac Engn Sci Dept Civil Engn Kasteelpk Arenberg 40 B-3001 Leuven Belgium

The production and processing of building materials is responsible for a significant share of global greenhouse gas emissions. Nevertheless, in current building practice, a lot of material is wasted, because load-bearing structures are often grossly overdimensioned. Numerical optimization tools have the potential to reduce the consumption of structural materials, but the lack of customized algorithms prohibits their use in daily design practice. This is because real-life structural optimization problems are complex, involving both discrete and continuous design variables as well as large numbers of building code constraints. In the literature, such problems are usually solved using metaheuristic (often genetic) algorithms, although gradient-based algorithms are better suited for continuous design variables. In this article, a new hybrid gradient-based/metaheuristic algorithm is proposed. It combines gradient-based and metaheuristic methods in a nested approach, exploiting the strengths of both: the ability to handle discrete design variables and fast convergence in terms of continuous design variables. The applicability and usefulness of the new hybrid algorithm is demonstrated in two realistic case studies to minimize the weight of the structure, taking into account all relevant design rules of Eurocode 3. Within identical computing time, the hybrid algorithm obtains significant material savings compared to a conventional genetic algorithm.

关键词： Structural optimization Eurocode design Real-life optimization Genetic algorithm sequential quadratic programming Active set

来源：评论

学校读者我要写书评

暂无评论

Nonlinear Model Predictive Control based Missile Guidance for Target Interception

Nonlinear Model Predictive Control based Missile Guidance fo...

引用

AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Bhattacharjee, Diganta Chakravarthy, Animesh Subbarao, Kamesh Univ Texas Arlington Dept Mech & Aerosp Engn Arlington TX 76019 USA Univ Texas Arlington Dept Mech & Aerosp Engn Box 19018 Arlington TX 76019 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

A nonlinear model predictive control (NMPC) based missile guidance algorithm for target interception is proposed. The planar engagement between a missile and a target is considered where both are assumed to be point masses. The lateral acceleration (or latax) commands for the missile are synthesized based on the numerical solutions to a quadratic program for the NPMC which does not require explicit information on the target acceleration. A cost function suitable for the problem is chosen and constraints are imposed on the latax, on the rate of change of latax, and on the relative velocity component along the line-of-sight (LOS). The quadratic program is shown to be a convex one. Suitable modifications are introduced in the quadratic program such that the guidance algorithm can accommodate constraint infeasibilities if required. Detailed simulations are included to illustrate the effectiveness of the proposed approach. Also, performance of the proposed guidance algorithm is compared with the performances of the pure proportional navigation (PPN) and a modified augmented proportional navigation (APN) (namely, augmented pure proportional navigation (APPN)) guidance laws. It is shown that the proposed guidance algorithm leads to performances comparable to the APPN guidance law, without requiring explicit knowledge of the target acceleration.

关键词： Model Predictive Control Missile Guidance Guidance Algorithms Control Guidance sequential quadratic programming Proportional Navigation Heading Angle Target Missiles Engagement Kinematics Nonlinear programming

来源：评论

学校读者我要写书评

暂无评论

Multi-Stage Trajectory Optimization for Multiple Aircraft Approaching an Airport 18

Multi-Stage Trajectory Optimization for Multiple Aircraft Ap...

引用

18th European Control Conference (ECC)

作者： Semenov, Valeriy Kostina, Ekaterina Heidelberg Univ Fac Math & Comp Sci D-2019 Heidelberg Germany

ISBN: (纸本)9783907144022

In the paper, a multi-stage approach for numerical trajectory optimization of multiple aircraft in the vicinity of an airport is presented. The method for solving the problem consists of 5 stages where the first four solve the problem of ordering, fixing the final times and hierarchical distance separation, and the solution of the hierarchical formulation is then used as the initial guess for the combined problem with pairwise distance constraints. The approach proved to be very efficient in terms of computation speed resulting in computation time of less than 3 minutes for all stages of solving the trajectory optimization problem for 5 aircraft. The numerical experiments were carried out with MUSCOD-II optimization software.

关键词： Trajectory optimization flight dynamics multiple shooting sequential quadratic programming

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：