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Aerodynamic optimization using analytic descriptions of the design space

JOURNAL OF AIRCRAFT 1998年第6期35卷 882-890页

作者： Toomer, CA Topliss, ME Hills, DP British Aerosp Operat Ltd Sowerby Res Ctr CFD Grp Bristol BS12 7QW Avon England

This paper discusses a strategy for performing aerodynamic single-point and multipoint optimization studies. The approach uses a combination of three methods: an Euler computational fluid dynamics (CFD) code that provides accurate information at one chosen point in the design space, a linear approximation method of the quasianalytic type that rapidly evaluates data at many design points, and a function-fitting algorithm that maps aerodynamic and geometric data across the whole design space. As the method proceeds, a good quality database of aerodynamic and geometric quantities is rapidly constructed at a fraction of the cost of using conventional methods. The availability of this database and the analytic representation of the quantities over the whole design space permits optimizations to be performed using constraints on specific aerodynamic parameters, e.g,, maximum surface Mach number and pressure gradients, over chosen regions of the aerofoil, The approach is also highly flexible, enabling optimization problems of increasing complexity to be built up quickly, and is easily integrated within modern engineering methods. Results are presented for a typical transonic aerofoil giving comparisons with individual CFD analyses.

关键词： Aerofoil Freestream Mach Number Angle of Attack Leading Edges Total Variation Diminishing sequential quadratic programming Chord Line Computing Facilities Sensitivity Analysis Aerospace Industry

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Chaos-infused wind power integration in the grey wolf optimal paradigm for combine thermal-wind power plant systems

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FRONTIERS IN ENERGY RESEARCH 2024年 12卷

作者： Wadood, Abdul Khan, Babar Sattar Khurshaid, Tahir Kim, Ki-Chai Rhee, Sang Bong Univ Tabuk Renewable Energy & Environm Technol Ctr Tabuk Saudi Arabia Univ Tabuk Fac Engn Elect Engn Dept Tabuk Saudi Arabia Air Univ Islamabad Dept Elect Engn Kamra Pakistan Univ Engn & Technol Peshawar Dept Elect Energy Syst Engn USPCAS E Peshawar Khyber Pakhtunk Pakistan Comsats Univ Dept Elect & Comp Engn Lahore Pakistan Yeungnam Univ Dept Elect Engn Gyongsan South Korea

This research presents a novel methodology for tackling the combined thermal-wind economic load dispatch (ELD) issue in contemporary power system. The proposed approach involves hybridizing active-set algorithm (ASA), interior point algorithm (IPA) and sequential quadratic programming (SQP) into grey wolf optimization (GWO) algorithm, while effectively incorporating the intricacies associated with renewable energy sources (RES). A more accurate model is made possible by hybridization for complex systems with memory and hereditary characteristics. The GWO is used as a tool for global search while ASA, IPA and SQP methods are used for rapid local optimization mechanism. The performance evaluation of the design heuristics is carried out on 37 thermal and 3 wind power generating units and outcomes endorse the effectiveness of the proposed scheme over state-of-the-art counterparts. The worthy performance is further validated on statistical assessments in case of thermal-wind integrated ELD problem in terms of measure of central tendency and variation on cost and complexity indices.

关键词： grey wolf optimization interior point algorithm active set algorithm sequential quadratic programming economic load dispatch problem stochastic wind

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Non-Newtonian Fluids in Action: Revisiting Hydraulic Conductivity and Pore Size Distribution of Porous Media

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VADOSE ZONE JOURNAL 2016年第9期15卷 1-15页

作者： Abou Najm, Majdi R. Atallah, Nabil M. Amer Univ Beirut Fac Engn & Architecture Dept Civil & Environm Engn POB 11-0236 Riad El Solh Beirut Lebanon

Classic porous media flow experiments focus on water as the fluid of choice, thus limiting estimates of saturated hydraulic conductivity to a single averaged value that is rarely informative of the complexity of the pore structure. A theoretical framework is presented for a new method for experimentally estimating a functional pore structure of porous media using a combination of Newtonian and non-Newtonian fluids. The proposed method builds an analog geometry of parallel capillary tubes (with tortuosity) that has the same functional behavior of real porous media in terms of saturated flow and porosity. The equivalent pore structure is formed by transforming results from N saturated infiltration experiments, comprised of water and N - 1 non-Newtonian solutions, into a system of equations that yields N representative pore radii (R-i) (size distribution of tubes) and their corresponding number (derived from percent contribution to water flow, w(i)). This feature further allows estimating the soil water retention curve using only saturated experiments. We further show the ability of the proposed theoretical framework to infer additional information about flow in the porous medium as compared to what can be inferred from N (or even more) Newtonian fluids. This example shows the potential of this method and the ability of the proposed framework to extract additional information that an equal or larger number of experiments with only Newtonian fluids cannot extract.

关键词： APRE absolute percent relative error NSE Nash-Sutcliffe efficiency coefficient PBIAS percent bias SQP sequential quadratic programming

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Dynamics of circularly towed cable systems, Part 1: Optimal configurations and their stability

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2007年第3期30卷 753-765页

作者： Williams, Paul Trivailo, Pavel RMIT Univ Sch Aerosp Mech & Mfg Engn Melbourne Vic 3083 Australia

When a long cable. is towed in a circular flight path, the system can exhibit quasi-stationary solutions for which the cable tip appears to remain stationary relative to the orbiting aircraft. For applications involving pickup and delivery of payloads, tighter turns at high speeds lead to nearly stationary motion of the cable tip in an inertial frame. This work studies the dynamics of such a system, focusing on the stability and equilibria of solutions. A numerical analysis of the system is carried out using a discretized lumped mass model of the cable. By using constrained numerical optimization, practical towing solutions that achieve small motion of the towed body are obtained.

关键词： Aerodynamic Force Aerodynamic Performance Light Aircraft Aircraft Configurations Flight Testing Aircraft Performance Aircraft Altitude Ultimate Tensile Strength sequential quadratic programming Aircraft Towing

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Parallel Lagrange-Newton-Krylov-Schur methods for PDE-constrained optimization. Part I: The Krylov-Schur solver

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SIAM JOURNAL ON SCIENTIFIC COMPUTING 2005年第2期27卷 687-713页

作者： Biros, G Ghattas, O NYU Courant Inst Math Sci Dept Comp Sci New York NY 10012 USA Carnegie Mellon Univ Dept Biomed Engn Ultrascale Simulat Lab Pittsburgh PA 15213 USA Carnegie Mellon Univ Dept Civil & Environm Engn Ultrascale Simulat Lab Pittsburgh PA 15213 USA

Large-scale optimization of systems governed by partial differential equations ( PDEs) is a frontier problem in scientific computation. Reduced quasi-Newton sequential quadratic programming (SQP) methods are state-of-the-art approaches for such problems. These methods take full advantage of existing PDE solver technology and parallelize well. However, their algorithmic scalability is questionable;for certain problem classes they can be very slow to converge. In this two-part article we propose a new method for steady-state PDE-constrained optimization, based on the idea of using a full space Newton solver combined with an approximate reduced space quasi-Newton SQP preconditioner. The basic components of the method are Newton solution of the first-order optimality conditions that characterize stationarity of the Lagrangian function;Krylov solution of the Karush - Kuhn - Tucker ( KKT) linear systems arising at each Newton iteration using a symmetric quasi-minimum residual method;preconditioning of the KKT system using an approximate state/decision variable decomposition that replaces the forward PDE Jacobians by their own preconditioners, and the decision space Schur complement ( the reduced Hessian) by a BFGS approximation initialized by a two- step stationary method. Accordingly, we term the new method Lagrange - Newton - Krylov - Schur (LNKS). It is fully parallelizable, exploits the structure of available parallel algorithms for the PDE forward problem, and is locally quadratically convergent. In part I of this two- part article, we investigate the effectiveness of the KKT linear system solver. We test our method on two optimal control problems in which the state constraints are described by the steady-state Stokes equations. The objective is to minimize dissipation or the deviation from a given velocity field;the control variables are the boundary velocities. Numerical experiments on up to 256 Cray T3E processors and on an SGI Origin 2000 include scalability and

关键词： sequential quadratic programming adjoint methods PDE constrained optimization optimal control Lagrange-Newton-Krylov-Schur methods Navier-Stokes finite elements preconditioners indefinite systems nonlinear equations parallel algorithms

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Optimization of formworks shoring location as a continuous optimization problem

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STRUCTURES 2023年 56卷

作者： Mizushima, Yasunori Inoue, Honoka Morikawa, Sota Taira, Shojiro Univ Hyogo Sch Human Sci & Environm Himeji Hyogo 6700092 Japan PanaHome Hyogo Bldg Dept Sumaizukuri Div Himeji Hyogo 6700940 Japan Takenaka Corp Construct Engn Div Osaka Head Off Osaka 5410053 Japan

For the construction of reinforced concrete buildings, partial striking of props and formworks a few days after casting is frequently employed, confirming its safety based on structural calculations or analyses to improve the construction productivity. Three-dimensional finite element (FE) models are sometimes used for these kinds of structural analyses to obtain precise results. However, considerable effort is required to determine the remaining prop arrangement by trial and error via FE analysis because of time-consuming operations. This study presents continuous optimization methods for the determination of the arrangement of remaining props that can speedily provide a single valid solution based on design sensitivity;the solution guarantees local optimality. Continuous optimizations employ a function that transforms the continuous design variables into the number of remaining props at each candidate location that is inherently represented by integer values. The optimization problems have been formulated in two forms: one is to maximize the safety of the structure, and the other is to minimize the number of remaining props. These optimization methods provided valid local optimal solutions that could reduce the amount of material required for formwork and shoring by almost half within a realistic calculation time. In addition, compared with multi-objective discrete optimization by a genetic algorithm, the first method provided the optimal solution with less than half the number of FE analyses of discrete method, and the second method provided a more efficient solution than the discrete method with a total of 10,000 individuals.

关键词： Building Formwork Shores Construction Finite element analysis sequential quadratic programming Structural optimization

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Heuristic computing performances based Gudermannian neural network to solve the eye surgery corneal model

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APPLIED SOFT COMPUTING 2024年 157卷

作者： Sabir, Zulqurnain Umar, Muhammad Wahab, Hafiz Abdul Bhat, Shahid Ahmad Unlu, Canan Hazara Univ Dept Math & Stat Mansehra Pakistan Lebanese Amer Univ Dept Comp Sci & Math Beirut Lebanon LUT Univ LUT Business Sch POB 20 FIN-53851 Lappeenranta Finland Istanbul Univ Fac Sci Dept Math Istanbul Turkiye

The current work is related to present the solutions of the corneal shape -based eye surgery model (CSESM) by applying the novel procedures of Gudermannian neural network (GNN) along with the hybrid optimization of the global and local approaches of heuristic genetic algorithm (GA) and sequential quadratic programing (SQP), i.e., GNN-GASQP. An error function is constructed using the terminologies of the differential model along with the corresponding boundary conditions of the CSESM and then the optimization of the parameter is approved by the global operator GA at the start and then local refinements of SQP is implemented. Six different cases of the CSESM have been numerically treated using the GNN-GASQP and the scheme's correctness is performed through the numerical Runge-Kutta (RK) results. The analysis based small and larger neurons is also implemented to authenticate the stability of GNN-GASQP. Moreover, the analysis through statistics using different measures of root mean square error, Theil's inequality coefficient and variance account for is presented to check the consistency of GNN-GASQP for solving the CSESM.

关键词： Corneal shape -based eye surgery Gudermannian function Neural Network Genetic algorithm Neuron analysis sequential quadratic programming

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Numerical treatment for the nonlinear fifth kind of multi-singular differential model: a neuro-swarming approach

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PHYSICA SCRIPTA 2022年第7期97卷 075203-075203页

作者： Sabir, Zulqurnain Ali, Mohamed R. Alhazmi, Sharifah E. Raja, Muhammad Asif Zahoor Sadat, R. Hazara Univ Dept Math & Stat Mansehra Pakistan Future Univ Fac Engn & Technol Cairo Egypt Benha Univ Benha Fac Engn Basic Engn Math Dept Banha Egypt Umm Al Qura Univ Al Qunfudah Univ Coll Math Dept Mecca Saudi Arabia Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan Zagazig Univ Zagazig Fac Engn Dept Math Zagazig Egypt

In this study, a numerical scheme is proposed for the fifth order (FO) singular differential model (SDM), FO-SDM. The solutions of the singular form of the differential models are always considered difficult to solve and huge important in astrophysics. A neural network study together with the hybrid combination of global particle swarm optimization and local sequential quadratic programming schemes is provided to find the numerical simulations of the FO-SDM. An objective function is constructed using the differential FO-SDM along with the boundary conditions. The correctness of the scheme is observed by providing the comparison of the obtained and exact solutions. The justification of the proposed scheme is authenticated in terms of absolute error (AE), which is calculated in good measures for solving the FO-SDM. The efficiency and reliability of the stochastic approach are observed using the statistical performances to solve the FO-SDM.

关键词： fifth order singular models neural network sequential quadratic programming particle swarm optimization statistical measures

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Aerodynamic design and optimization of sCO2 turbomachinery: Two-Stage optimization approach

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ENERGY CONVERSION AND MANAGEMENT 2023年 297卷

作者： Cetin, Tugberk Hakan Zhu, Jie Univ Nottingham Dept Architecture & Built Environm Univ Pk Nottingham NG7 2RD England

The application of supercritical CO2 (sCO2) in power generation systems is getting attractive recently owing to high energy efficiency and compact component size, but there are big design challenges for turbines and com-pressors due to the supercritical fluid characteristics. In this paper, a novel turbomachinery design optimization framework, "Turbine-Delta h-Compressor" (T Delta hC) tool, is proposed to generate the optimal flow feature and ge-ometry. The T Delta hC tool based on sequential quadratic programming formulation extends the design parameter search spaces and compares the optimized turbomachinery geometries by coupling with genetic algorithm, its capability is demonstrated by three sCO2 systems with 100, 200 and 250 kW turbine output power under different operating conditions. It is found that the maximum turbine total-to-static efficiency of these systems is 86.99 % and the maximum compressor isentropic efficiency is 77.06 %. In the optimal design case, the system thermal efficiency could reach 33.43 %.

关键词： Supercritical carbon dioxide Radial inflow turbine Centrifugal compressor sequential quadratic programming Optimization

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MEYER WAVELET NEURAL NETWORKS PROCEDURES TO INVESTIGATE THE NUMERICAL PERFORMANCES OF THE COMPUTER VIRUS SPREAD WITH KILL SIGNALS

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FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY 2023年第2期31卷

作者： Sabir, Zulqurnain Baleanu, Dumitru Raja, Muhammad Asif Zahoor Alshomrani, Ali S. S. Hincal, Evren Near East Univ Dept Math CY-99138 Nicosia Cyprus Lebanese Amer Univ Dept Comp Sci & Math Beirut Lebanon Cankaya Univ Dept Math Ankara Turkiye Inst Space Sci Magurele Romania China Med Univ China Med Univ Hosp Dept Med Res Taichung Taiwan Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ Rd TechnolSect 3 Touliu 64002 Yunlin Taiwan King Abdulaziz Univ Fac Sci Dept Math Jeddah 21589 Saudi Arabia

This study shows the design of the Meyer wavelet neural networks (WNNs) to perform the numerical solutions of the spread of computer virus with kill signals, i.e. SEIR-KS system. The optimization of the SEIR-KS system is performed by the Meyer WNNs together with the optimization through the genetic algorithm (GA) and sequential quadratic (SQ) programming, i.e. Meyer WNNs-GASQ programming. A sigmoidal-based log-sigmoid function is implemented as an activation function, while 10 numbers of neurons work with 120 variables throughout this study. The correctness of the proposed Meyer WNNs-GASQP programming is observed through the comparison of the obtained and reference numerical solutions. For the consistency and reliability of the Meyer WNNs-GASQ programming, an analysis based on different statistical procedures is performed using 40 numbers of independent executions. Moreover, the use of different statistical operators like mean, median, minimum, standard deviation and semi-interquartile range further validates the correctness of the Meyer WNNs-GASQ programming for solving the SEIR-KS system.

关键词： Meyer Wavelet Neural Networks SEIR-KS Computer Virus Genetic Algorithm Nonlinear sequential quadratic programming Reference Solutions

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