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Evaluation of optimization schemes and determination of solid fuel properties for CFD fire models using bench-scale pyrolysis tests

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PROCEEDINGS OF THE COMBUSTION INSTITUTE 2011年第2期33卷 2599-2606页

作者： Chaos, Marcos Khan, Mohammed M. Krishnamoorthy, Niveditha de Ris, John L. Dorofeev, Sergey B. FM Global Res Norwood MA 02062 USA

CFD fire modeling tools are continuously developed and improved to increase their predictive capability of phenomena observed in practical applications. Such models require that "effective" material properties be provided so that the pyrolysis codes used in the models can properly estimate the thermal degradation of solid fuels involved in a fire situation. This paper presents analyses aimed at evaluating the plausibility of obtaining material properties numerically from pyrolysis data collected in a Fire Propagation Apparatus (FPA). A theoretical pyrolysis model is used to simulate the experimental data and the input parameters (i.e. the material properties) are adjusted to provide the best possible agreement between simulations and experiments. This is done via the application of evolutionary optimization methodologies. First, available optimization techniques are evaluated using synthetic data and it is shown that the Shuffled Complex Evolution approach ([17]) can recover the input parameters with high accuracy, efficiency, and robustness. Second, the algorithm is applied to experimental FPA pyrolysis data of practical materials: polymethyl methacrylate (PMMA), single-wall corrugated board, and chlorinated polyvinyl chloride (CPVC). (C) 2010 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

关键词： Material properties optimization algorithms Fire Propagation Apparatus Pyrolysis

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optimization of hydro energy storage plants by using differential evolution algorithm

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ENERGY 2014年 77卷 97-107页

作者： Glotic, Arnel Glotic, Adnan Kitak, Peter Pihler, Joze Ticar, Igor Univ Maribor Fac Elect Engn & Comp Sci SI-2000 Maribor Slovenia Holding Slovenske Elekt Grp SI-1000 Ljubljana Slovenia

The optimal dispatching of cascade Hydro Power Plants is known as a complex optimization problem. In order to solve this problem the authors have applied an adapted differential evolution algorithm by using a fixed and dynamic population size. According to the dynamic population size, the proposed algorithm uses novel random and minimum to maximum sort strategy in order to create new populations with decreased or increased sizes. This implementation enables global search with fast convergence. It also uses a multi-core processor, where all the necessary optimization data are sent to the individual core of a central processing unit The main aim of the optimization process is to satisfy 24 h demand by minimizing the water quantity used per electrical energy produced. This optimization process also satisfies the desired reservoir levels at the end of the day. The models used in this paper were the real parameters' models of eight cascade Hydro Power Plants located in Slovenia (Europe). Also the standard model from the literature is used in order to compare the performance of the adapted optimization algorithm. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Cascade hydro power plants Energy storage Hydro generation scheduling optimization algorithms

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Multidisciplinary design optimization for aeromechanics and handling qualities

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JOURNAL OF AIRCRAFT 2006年第1期43卷 241-252页

作者： Fusato, D Celi, R Univ Maryland Dept Aerosp Engn Alfred Gessow Rotorcraft Ctr College Pk MD 20742 USA

A design optimization study is presented in which rotor dynamics and flight dynamics are simultaneously taken into account to maximize the damping of a rotor lag mode. The design variables include rotor, airframe, and flight control system parameters. The constraints address rotor stability and loads and handling qualities. Two design optimization cases are considered, one with only constraints computed from the linearized model of the helicopter and the other with additional constraints that require the integration of the nonlinear equations of motion. Both finite difference and semi-analytical gradients are used for some constraints. The optimization procedure increases the lag mode damping by up to 90%, while satisfying all of the constraints, primarily by reducing the blade torsion stiffness. The aeromechanic design problem is a multidisciplinary problem. The constraint active at the optimum is the level I handling qualities requirement in the pitch axis. optimization provides a framework to manage multidisciplinary problems systematically and efficiently. Using semi-analytical gradients of the constraints computed from the linearized model yields the same results as with finite difference gradients, but more efficiently. The computational advantage increases with problem size. Further advances in computer hardware and in optimization algorithms, including efficient sensitivity analyses, will help make numerical optimization a practical design tool.

关键词： Constraint multidisciplinary design optimization Finite differences redundant constraint Mechanical Torsion design tools absorption of shock optimization Procedure optimization algorithms Equations of motion Computer hardware Optimal design controllability Flight dynamics Aviation Mechanics

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A novel metaheuristic algorithm inspired by COVID-19 for real-parameter optimization

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NEURAL COMPUTING & APPLICATIONS 2023年第14期35卷 10147-10196页

作者： Mohammadi, Soleiman Kadkhoda Nazarpour, Daryoush Beiraghi, Mojtaba Islamic Azad Univ Dept Elect Engn Urmia Branch Orumiyeh Iran Urmia Univ Dept Elect Engn Orumiyeh Iran

In this modern world, we are encountered with numerous complex and emerging problems. The metaheuristic optimization science plays a key role in many fields from medicine to engineering, design, etc. Metaheuristic algorithms inspired by nature are among the most effective and fastest optimization methods utilized to optimize different objective functions to minimize or maximize one or more specific objectives. The use of metaheuristic algorithms and their modified versions is expanding every day. However, due to the abundance and complexity of various problems in the real world, it is always necessary to select the most proper metaheuristic method;hence, there is a strong need to create new algorithms to achieve our desired goal. In this paper, a new and powerful metaheuristic algorithm, called the coronavirus metamorphosis optimization algorithm (CMOA), is proposed based on metabolism and transformation under various conditions. The proposed CMOA algorithm has been tested and implemented on the comprehensive and complex CEC2014 benchmark functions, which are functions based on real-world problems. The results of the experiments in a comparative study under the same conditions show that the CMOA is superior to the newly-developed metaheuristic algorithms including AIDO, ITGO, RFOA, SCA, CSA, CS, SOS, GWO, WOA, MFO, PSO, Jaya, CMA-ES, GSA, RW-GWO, mTLBO, MG-SCA, TOGPEAe, m-SCA, EEO and OB-L-EO, indicating the effectiveness and robustness of the CMOA algorithm as a powerful algorithm. As it was observed from the results, the CMOA provides more suitable and optimized solutions than its competitors for the problems studied. The CMOA preserves the diversity of the population and prevents trapping in local optima. The CMOA is also applied to three engineering problems including optimal design of a welded beam, a three-bar truss and a pressure vessel, showing its high potential in solving such practical problems and effectiveness in finding global optima. According to the

关键词： optimization Real-world optimization functions Engineering optimization optimization algorithms Coronavirus metamorphosis optimization algorithm (CMOA)

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Hydrate formation prediction model for binary gases of methane plus ethane and methane plus propane by using optimization algorithm

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PETROLEUM SCIENCE AND TECHNOLOGY 2020年第1期38卷 36-42页

作者： Abbasi, Aijaz Hashim, Fakhruldin Mohd Univ Teknol PETRONAS Mech Engn Dept Seri Iskandar Malaysia

This research model equation is based on constant coefficients which were used for multiple sets of experimental data. The developed optimized based prediction model is examined by the experimental data of binary gases methane + ethane and methane + propane hydrates, respectively. This research model holds a wide range of datasets from 190.2 to 326.8 K and 0.08251 to 590 MPa for binary gases of methane + ethane and methane + propane, respectively. The developed algorithm validated by experimental data of binary gases of hydrate formation, statistical analysis, thermodynamic equations and fundamental empirical models for hydrate formation, respectively. This research enhances the existing study by presenting a systematic model which predicts and provides a guideline for users to forecast gas-hydrate-forming conditions.

关键词： pressure temperature statistical analyses thermodynamics hydrate formation model optimization algorithms

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CUCKOO SEARCH ALGORITHM FOR optimization PROBLEMS-A LITERATURE REVIEW AND ITS APPLICATIONS

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APPLIED ARTIFICIAL INTELLIGENCE 2014年第5期28卷 419-448页

作者： Mohamad, Azizah Binti Zain, Azlan Mohd Bazin, Nor Erne Nazira Univ Teknol Malaysia Fac Comp Soft Comp Res Grp Utm Skudai 81310 Johor Malaysia

Cuckoo Search (CS) is an optimization algorithm developed by Yang and Deb in 2009. This article describes an overview of CS, which is inspired by the life of a bird family, as well as an overview of CS applications in various categories for solving optimization problems. optimization is a process of determining the best solution to make something as functional and effective as possible by minimizing or maximizing the parameters involved in the problems. The categories reviewed are Engineering, Pattern Recognition, Job Scheduling, Networking, Object-Oriented Software (Software Testing), and Data Fusion in Wireless Sensor Networks. From the reviewed literature, CS is mostly applied in the engineering area for solving optimization problems. The objective of this study is to provide an overview and to summarize the review of applications of the CS.

关键词： Literature Review Cuculidae Data fusion algorithms Wireless sensor networks optimization algorithms

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Are dose calculations during dose optimization in brachytherapy necessary?

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MEDICAL PHYSICS 2003年第9期30卷 2368-2375页

作者： Lahanas, M Baltas, D Klinikum Offenbach Strahlenklin Dept Med Phys & Engn D-63069 Offenbach Germany Natl Tech Univ Athens Dept Elect & Comp Engn GR-15773 Athens Greece

We consider the problem of anatomy based dose optimization in brachytherapy. A calculation method for some objective functions and their derivatives is proposed which significantly reduces the number of required operations. The optimization in some cases, ignoring a preprocessing step, is independent of the number of sampling points. The idea is that some of the objectives and their derivatives used for dose optimization do not require the explicit calculation of dose values. Dose optimization with the new modified computation method for the objectives and derivatives is, depending on the number of sampling points, up to 100 times faster than the conventional method with dose calculation. (C) 2003 American Association of Physicists in Medicine.

关键词： brachytherapy optimization algorithms

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optimization OF LOAD SHEDDING SYSTEM

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IEEE TRANSACTIONS ON ENERGY CONVERSION 1993年第2期8卷 207-213页

作者： HALEVI, Y KOTTICK, D ISRAEL ELECT CORP LTD DIV RES & DEVHAIFAISRAEL

An optimization algorithm for a load shedding system is presented. The Israeli power system is not interconnected with any neighbouring system. Being a relatively small system, an outage of a single generating unit may cause blackouts. One way of preventing this is an underfrequency load shedding system, which is composed of several stages that are tripped at preset frequencies. The paper considers the optimization of this system with respect to a cost function that includes a dynamic part, i.e. integral of the deviation from nominal frequency,and a static part which is the total load shedding. The optimization is constrained by the requirement of minimum allowed frequency and limitation on the total load of the shedding system. A projected gradient method is used for the solution where analytic expressions for the partial derivatives are used to simplify the computation. Results concerning application of the optimization to a model of the actual Israeli power system are given together with a study of the cost parameters.

关键词： total offered load nominal frequency load shedding optimization algorithms shedding

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Shape optimization of streamlined decks of cable-stayed bridges considering aeroelastic and structural constraints

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JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS 2018年 177卷 429-455页

作者： Montoya, M. Cid Hernandez, S. Nieto, F. Univ A Coruna Struct Mech Grp Sch Civil Engn La Coruna 15071 Spain

Structural optimization techniques have the potential to become a powerful tool in the design of long-span bridges. The search for more efficient and reliable designs involves considering shape variations in the deck cross-section, which is one of the key features of the bridge. This affects the deck aerodynamics and its mechanical properties, and consequently to the aeroelastic response of the bridge. A numerical approach pursuing to optimize a long-span bridge needs to explore changes in the deck shape, including structural and aeroelastic responses as design constraints. Therefore, the flutter response of the bridge must be computed numerically for every candidate proposed by the optimization algorithm. This work presents a novel approach to conduct the optimization of deck shape and cables size of a long-span cable-stayed bridge considering simultaneously aeroelastic and structural constraints. The design variables are the cross-section area and prestressing force of each stay, the deck plates thickness and the width and depth of a streamlined box deck. The aeroelastic constraint is evaluated based on the fully numerical procedure developed in an authors' previous work. A series of parameter variation studies, that are instrumental for the sound interpretation of the optimum designs, are also reported.

关键词： Bridge aerodynamics CFD Quasi-steady formulation Aeroelasticity Surrogate models Structural design optimization algorithms Multidisciplinary optimization Shape optimization

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Design and optimization of Future Hybrid and Electric Propulsion Systems: An Advanced Tool Integrated in a Complete Workflow to Study Electric Devices

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OIL & GAS SCIENCE AND TECHNOLOGY-REVUE D IFP ENERGIES NOUVELLES 2012年第4期67卷 547-562页

作者： Le Berr, F. Abdelli, A. Postariu, D. -M. Benlamine, R. IFP Energies Nouvelles F-92852 Rueil Malmaison France

Design and optimization of Future Hybrid and Electric Propulsion Systems: An Advanced Tool Integrated in a Complete Workflow to Study Electric Devices - Electrification to reduce greenhouse effect gases in transport sector is now well-known as a relevant and future solution studied intensively by the whole actors of the domain. To reach this objective, a tool for design and characterization of electric machines has been developed at IFP Energies nouvelles. This tool, called EMTool, is based on physical equations and is integrated to a complete workflow of simulation tools, as Finite Element Models or System Simulation. This tool offers the possibility to study several types of electric machine topologies: permanent magnet synchronous machine with radial or axial flux, induction machines, etc. This paper presents the main principles of design and the main equations integrated in the EMTool, the methods to evaluate electric machine performances and the validations performed on existing machine. Finally, the position of the EMTool in the simulation tool workflow and application examples are presented, notably by coupling the EMTool with advanced optimization algorithms or finite element models.

关键词： simulation tool design theory finite element model Integrate electric machines machine performance Permanent magnet synchronous machines systems simulation optimization algorithms ELECTRIC PROPULSION Electric devices Greenhouse gases

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