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ASME Turbo Expo: Turbine Technical Conference and Exposition

作者： Pietropaoli, M. Ahlfeld, R. Montomoli, F. Ciani, A. D'Ercole, M. Imperial Coll London Dept Aeronaut London England GE Oil & Gas Nuovo Pignone Srl Via F Matteucci 2 I-50127 Florence Italy

ISBN: (纸本)9780791849798

The new possibilities offered by Additive Manufacturing (AM) can be exploited in gas turbines to produce a new generation of complex and efficient internal coolant systems. The flexibility offered by this new manufacturing method needs a paradigm shift in the design approach and a possible solution is offered by Topology optimization. The overall goal of this work is to propose an innovative method to design internal channels in gas turbines that that fully exploit AM capabilities. The present work contains a new application of a Fluid Topology sedimentation method to optimize the internal coolant geometries with minimal pressure losses while maximizing the heat exchange. The domain is considered as a porous medium with variable porosity: the solution is represented by the final solid distribution that constitutes the optimised structure. In this work the governing equations for an incompressible flow in a porous medium are considered together with a conjugate heat transfer equation that includes porosity dependent thermal diffusivity. An adjoint optimisation approach with steepest descent method is used to build the optimisation algorithm. The simulations are carried out on two different geometries: a U-Bend and a straight duct. For the U-Bend a series of splitter is automatically generated by the code, minimizing the stagnation pressure losses. In the straight duct the impact of different porosity dependant thermal diffusivity is analysed to achieve high thermal exchange. The results show "rib like" structures that enhance the heat transfer

关键词： optimization Porosity Gas turbines Ducts optimization algorithms Sedimentation Topology Manufacturing Flow (Dynamics) Engineering simulation Pressure Fluids Porous materials Heat Coolants Additive manufacturing Simulation Heat transfer Thermal diffusivity Design

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optimization-Enabled EMT Modeling for Transformer Impulse Test

Optimization-Enabled EMT Modeling for Transformer Impulse Te...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Samarawickrama, Kasun Gole, Aniruddha M. Kordi, Behzad Jacob, Nathan D. Univ Manitoba Dept Elect & Comp Engn Winnipeg MB R3T 5V6 Canada Manitoba Hydro High Voltage Test Facil Winnipeg MB R3T 1Y6 Canada

ISBN: (纸本)9781509041688

A novel method is proposed to enhance the performance of optimization algorithms to obtain impulse generator settings. This method resolves two major problems encountered in tradition optimization-enabled electromagnetic transient simulation (OE-EMTS) approach. First, a new technique is introduced to model a transformer in an electromagnetic transient (EMT) simulator. This technique uses the frequency response of the transformer to calculate time-domain quantities without synthesizing the transformer circuit. As a results, most of the major issues attributed to the frequency-response based EMT modeling are solved, such as appearance of negative resistive elements in the synthesized circuit and generation of highly complex/dense branch networks. Second, multiple optimization algorithms are implemented to optimize impulse generator settings. Combination of multiple algorithms has balanced the effects of convergence speed and accuracy for better results. The proposed approach is verified by two case studies, involving different resistor arrangements. The simulated waveforms are compared with those obtained from measurements.

关键词： Electromagnetic transient model high voltage transformers lightning impulse test optimization algorithms recursive convolution

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A NOVEL MACHINE-LEARNING AIDED optimization TECHNIQUE FOR MATERIAL DESIGN: APPLICATION IN THIN FILM SOLAR CELLS

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ASME Summer Heat Transfer Conference

作者： Hajimirza, Shima Texas A&M Univ Dept Mech Engn College Stn TX 77843 USA

ISBN: (纸本)9780791850336

Patterned thin film structures can offer spectrally selective radiative properties that benefit many engineering applications including photovoltaic energy conversion at extremely efficient scales. Inverse design of such structures can be expressed as an interesting optimization problem with a specific regime of complexity;namely moderate number of optimization parameters but highly time-consuming forward problem. For problems like this, a search technique that can somehow learn and parameterize the multi-dimensional behavior of the objective function based on past search points can be extremely useful in guiding the global search algorithm and expediting the solution for such complexity regimes. Based on this idea, we have developed a novel search algorithm for optimizing absorption coefficient of visible light in a multi-layered silicon based nano-scale thin film solar cell. The proposed optimization algorithm uses a machine-learning predictive tool called regression-tree in an intermediary step to learn (i.e. regress) the objective function based on a previous generation of random search points. The fitted model is then used as a guide to resample from a new generation of candidate solutions with a significantly higher average gain. This process can be repeated multiple times and better solutions are obtained with high likelihood at each stage. Through numerical experiments we demonstrate how in only one resampling stage, the propose technique dominates the state-of-the-art global search algorithms such as gradient based techniques or MCMC methods in the considered nano-design problem.

关键词： Absorption Solar cells algorithms Silicon Engineering systems and industry applications optimization Light Visible spectrum Machine learning Design optimization algorithms Thin films Energy conversion Nanoscale phenomena

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MACHINE LEARNING AND METAMODEL-BASED DESIGN optimization OF NONLINEAR MULTIMATERIAL STRUCTURES

MACHINE LEARNING AND METAMODEL-BASED DESIGN OPTIMIZATION OF ...

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ASME International Design Engineering Technical Conference / Computer and Information in Engineering Conference (IDETC/CIE)

作者： Liu, Kai Detwiler, Duane Tovar, Andres Purdue Univ Sch Mech Engn W Lafayette IN 47907 USA Honda R&D Amer Inc Raymond OH USA Indiana Univ Purdue Univ Indianapolis Dept Mech Engn Indianapolis IN 46202 USA

ISBN: (纸本)9780791850114

This study presents an efficient multimaterial design optimization algorithm that is suitable for nonlinear structures. The proposed algorithm consists of three steps: conceptual design generation, design characterization by machine learning, and metamodel-based multi-objective optimization. The conceptual design can be generated from extracting finite element analysis information or by using structure optimization. The conceptual design is then characterized by using machine learning techniques to dramatically reduce the dimension of the design space. Finally, metamodels are derived using Efficient Global optimization (EGO) followed by multi-objective design optimization to find the optimal material distribution. The proposed methodology is demonstrated using examples from multiple physics and compared with traditional multimaterial topology optimization method.

关键词： optimization Finite element analysis Physics Topology Pareto optimization Machine learning Design algorithms optimization algorithms Dimensions Conceptual design

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MUSCLE FORCE PREDICTION OF 2D GAIT USING PREDICTIVE DYNAMICS optimization

MUSCLE FORCE PREDICTION OF 2D GAIT USING PREDICTIVE DYNAMICS...

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ASME International Design Engineering Technical Conference / Computer and Information in Engineering Conference (IDETC/CIE)

作者： Xiang, Yujiang Univ Alaska Fairbanks Dept Mech Engn Fairbanks AK 99775 USA

ISBN: (纸本)9780791850077

Cyclic human gait is simulated in this work by using a 2D musculoskeletal model with 12 degrees of freedom (DOF). Eight muscle groups are modeled on each leg. Predictive dynamics approach is used to predict the walking motion. In this process, the model predicts joints dynamics and muscle forces simultaneously using optimization schemes and task based physical constraints. The results indicated that the model can realistically match human motion, ground reaction forces (GRF), and muscle force data during walking task. The proposed optimization algorithm is robust and the optimal solution is obtained in seconds. This can be used in human health domain such as leg prosthesis design.

关键词： Musculoskeletal system Prostheses Muscle Dynamics (Mechanics) optimization Design optimization algorithms Degrees of freedom

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Reliability optimization of wind farms considering constraints and regulations 5

Reliability optimization of wind farms considering constrain...

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5th IEEE International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Tazi, Nacef Chatelet, Eric Meziane, Rachid Bouzidi, Youcef Univ Technol Troyes ICD LM2S UMR CNRS Troyes France Univ Saida Electrotech Engn Lab Saida Algeria Univ Technol Troyes ICD CREIDD ITMR CNRS Troyes France

ISBN: (纸本)9781509033881

Optimal power in wind farms has been a problem for constructors and managers during recent years, onshore wind farms are subject to more and more regulations and constraints. The goal is to define optimal installed capacity with maximum reliability and profits. A number of algorithms have thus been developed for the optimization of wind farm power plants. However, according to the literature, no methods have so far been tested on wind farms using real data and wind based conditions. In this Article, we continue the work that has recently been done on wind farm reliability optimization and apply an algorithm to find the best topology. The proposed resolution technique is based on finding the best topology of the system under the constraints of Performance (Availability), Costs and the Global Warming Potential of the system. A case study is done using data and constraints similar to those collected from wind farm constructors, managers and maintainers. Multi-state systems (MSS), Universal generating function (UGF), Wind and Load charge functions are applied. An economic study was conducted to assess the wind farm investment. Net present value (NPV) and levelized cost of energy (LCOE) were calculated for best topologies founded.

关键词： wind farm wind function availability MSS UGF power optimization constraints optimization algorithms NIT LCOE

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TIME-DEPENDENT STRUCTURAL TOPOLOGY optimization USING A CONTINUOUS ADJOINT FORMULATION

TIME-DEPENDENT STRUCTURAL TOPOLOGY OPTIMIZATION USING A CONT...

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ASME International Design Engineering Technical Conference / Computer and Information in Engineering Conference (IDETC/CIE)

作者： Papadimitriou, Dimitrios I. Mourelatos, Zissimos P. Oakland Univ Dept Mech Engn Rochester MI 48309 USA

ISBN: (纸本)9780791850114

A new time-dependent topology optimization methodology is presented based on a time-dependent continuous adjoint approach. The main advantage is its non-intrusiveness which allows us not to interfere with the discretization scheme of the finite-element or finite-volume topology optimization software. The discretization of the differential adjoint equations can be different from the discretization of the structural equations. The objective is to minimize the time-average compliance of a structure subject to a volume-based constraint. A gradient-based optimization algorithm is used. The sensitivity derivatives of a time-average compliance function with respect to the topology design parameters are computed using a time-dependent adjoint formulation. The self-adjoint feature is first presented for discrete time-dependent topology optimization and then extended to the continuous case. The proposed methodology is demonstrated using the topology optimization of a two dimensional and a three dimensional structure under time-dependent excitations.

关键词： Computer software Finite element analysis Topology Excitation optimization Design optimization algorithms

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optimization Methods for Solving the Low Autocorrelation Sidelobes Problem 17

Optimization Methods for Solving the Low Autocorrelation Sid...

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17th International Radar Symposium (IRS)

作者： Tan, U. Rabaste, O. Adnet, C. Arlery, F. Ovarlez, J. -P. Thales Air Syst F-91470 Limours France SONDRA CentraleSupelec F-91192 Gif Sur Yvette France Off Natl Etud & Rech Aerosp French Aerosp Lab F-91123 Palaiseau France

ISBN: (纸本)9781509025183

In this paper, a discussion is made on the optimization methods that can solve the low autocorrelation sidelobes problem for polyphase sequences. This paper starts with a description and a comparison of two algorithms that are commonly used in the literature: a stochastic method and a deterministic one (a gradient descent). Then, an alternative method based on the Random Walk Metropolis-Hastings algorithm is proposed, that takes the gradient as a search direction. It provides better results than a steepest descent alone. Finally, this autocorrelation question is handled differently, considering a mismatched tiller. We will see that a mismatched filter performs impressively well on optimized sequences.

关键词： Aperiodie autocorrelation optimization algorithms Gradient descent Mismatched filter

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World Competitive Contests (WCC) algorithm: A novel intelligent optimization algorithm for biological and non-biological problems

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Informatics in Medicine Unlocked 2016年 3卷 15-28页

作者： Masoudi-Sobhanzadeh, Yosef Motieghader, Habib Department of Computer Engineering Payam Noor University Tabriz Iran Laboratory of Systems Biology and Bioinformatics (LBB) Institute of Biochemistry and Biophysics University of Tehran Tehran Iran

Since different sciences face lots of problems which cannot be solved in reasonable time order, we need new methods and algorithms for getting acceptable answers in proper time order. In the present study, a novel intelligent optimization algorithm, known as WCC (World Competitive Contests), has been proposed and applied to find the transcriptional factor binding sites (TFBS) and eight benchmark functions discovery processes. We recognize the need to introduce an intelligent optimization algorithm because the TFBS discovery is a biological and an NP-Hard problem. Although there are some intelligent algorithms for the purpose of solving the above-mentioned problems, an optimization algorithm with good and acceptable performance, which is based on the real parameters, is essential. Like the other optimization algorithms, the proposed algorithm starts with the first population of teams. After teams are put into different groups, they will begin competing against their rival teams. The highly qualified teams will ascend to the elimination stage and will play each other in the next rounds. The other teams will wait for a new season to start. In this paper, we're going to implement our proposed algorithm and compare it with five famous optimization algorithms from the perspective of the following: the obtained results, stability, convergence, standard deviation and elapsed time, which are applied to the real and randomly created datasets with different motif sizes. According to our obtained results, in many cases, the WCC׳s performance is better than the other algorithms’. © 2016

关键词： optimization algorithms The motif discovery Transcriptional factor binding sites World Competitive Contests

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optimization OF REINFORCING RIBS OF A HOLLOW FAN BLADE USING METAMODEL-BASED optimization ALGORITHM

OPTIMIZATION OF REINFORCING RIBS OF A HOLLOW FAN BLADE USING...

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ASME Turbo Expo: Turbine Technical Conference and Exposition

作者： Ma, Ying Xu, Shengli Liu, Haitao Wang, Xiaofang Dalian Univ Technol Sch Energy & Power Engn Dalian Liaoning Peoples R China

ISBN: (纸本)9780791849712

With the development of aero-engine technology, the demand for fan blade with light weight and better structural performances is urgent. This paper focuses on the weight optimization of a hollow fan blade through changing the thickness and distribution of the inner triangular reinforcing ribs under the constraints of equivalent stress, displacement, bending and torsional frequencies. A fmite element analysis process was established in the paper, considering the load of centrifugal force and gas pressure. In the CAD-based model parameterization, to avoid possible interference problems brought by design parameters, the relative locations of control points are applied to determine the locations of control points on the vane profile curves. A metamodel-based global optimization scheme is employed for improving the optimization efficiency. An optimal design with about 13.7% weight reduction is finally obtained by the above optimization procedure. The triangular reinforcing ribs of hollow fan blade were rearranged with the constraints of the stress, displacement and natural frequencies satisfied.

关键词： Aircraft engines Stress Finite element analysis Weight (Mass) Centrifugal force Pressure optimization Design Displacement optimization algorithms Blades Computer-aided design

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