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ASME International Mechanical Engineering Congress and Exposition (IMECE)

作者： Balasubramanian, Prabakaran Franchini, Giulio Ferrari, Giovanni Painter, Brian Karazis, Kostas Amabili, Marco McGill Univ Dept Mech Engn Montreal PQ Canada Framatome Inc Lynchburg VA USA Univ Parma Dipartimento Ingn & Architettura Parma PR Italy

ISBN: (纸本)9780791885611

Several structures of important industrial relevance feature large-amplitude vibration, which can have an initially hardening or a softening behavior. Models with quadratic and cubic nonlinear stiffness terms are often used to predict the nonlinear dynamics of such structures. If boundary conditions constitute an important cause of nonlinearity, however, it may not be possible to describe the nonlinear behavior of these systems by means of these nonlinear terms. The bundles of fuel rods immersed in the coolant flow of pressurized water reactors constitute an important example of extreme softening behavior, which is not described accurately by the simple adoption of nonlinear stiffness terms proportional to the square and to the cube of displacement in the equation of motion. In fact, the spacer grids, which support the nuclear fuel rods inside the reactors, constitute nonlinear boundary conditions, and are responsible of the peculiar softening behavior. Dedicated experiments on the rotational constraint applied by the spacer grids were performed, revealing a softening stiffness, which conforms extremely well with a bilinear model with hysteresis, such as the one formulated by Caughey. Therefore, a single degree-of-freedom equation with bilinear stiffness terms was employed to model the large-amplitude vibrations of single and bundled fuel rods immersed in quiescent water, which were detailed by previous stepped-sine experiments. A viscous dissipative term was initially retained for modelling damping, since several sources of dissipation are present for fuel rods immersed in water, besides hysteresis at the spacer grid supports. A satisfying fit of the experimental frequency- and time-domain curves was achieved through the use of an optimization algorithm for the tuning of stiffness and damping terms. Viscous damping, however, is not constant during large-amplitude vibrations, but is amplitude-dependent. Therefore, the value of the relevant parameter had to be change

关键词： Vibration Stiffness Damping Fuel rods Boundary-value problems Switches Water Equations of motion Fluids Coolants Hardening Energy dissipation Degrees of freedom Modeling Nonlinear dynamics Pressurized water reactors Displacement optimization algorithms Rods Flow (Dynamics)

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A Review of Existing Multi-Motor Electric Powertrain Sizing Strategies 24

A Review of Existing Multi-Motor Electric Powertrain Sizing ...

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24th International Conference on Electrical Machines and Systems (ICEMS)

作者： Castro, Marco Veliz Mukundan, Shruthi Filho, Claudio Lopes Byczynski, Glenn Minaker, Bruce Tjong, Jimi Kar, Narayan C. Univ Windsor Windsor ON N9B 3P4 Canada Nemak USA CAN 2 Towne Sq 300 Southfield MI 48076 USA

ISBN: (纸本)9788986510218

Multi-Motor Electric Vehicles (MMEVs) have been identified as a solution to the current disadvantages of Single Motor Electric Vehicles (EVs) in energy consumption and driving range. These improvements are achieved by operating each motor in its peak efficiency region, as appropriate for the driving scenario. Although MMEVs have increased efficiency, the extent is highly dependent on the sizes of the motors. Thus, some researchers have begun to determine the optimal motor sizes. This paper reviews existing literature on motor sizing techniques and analyzes their performance through overall powertrain dynamic and efficiency performance.

关键词： Motor sizing multi-motor electric vehicles optimization algorithms vehicle dynamics modelling

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Multi-Objective Information Retrieval-Based NSGA-II optimization for Requirements Traceability Recovery

Multi-Objective Information Retrieval-Based NSGA-II Optimiza...

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IEEE International Conference on Electro Information Technology (EIT)

作者： Rodriguez, Danissa, V Carver, Doris L. Louisiana State Univ Div Comp Sci & Engn Baton Rouge LA 70803 USA

ISBN: (纸本)9781728153179

The recovery of requirements traceability links assists multiple software development activities, including analyzing impact of changes, validating requirements, maintenance and evolution of software. Poor communication and time pressure problems often have resulted in organizations being unsuccessful in implementing traceability practices. A number of solutions for automatic recovery of links across software artifacts have been developed, including the application of textual analysis and information retrieval techniques. Link recovery with information retrieval has seen some success, but there is a need for methods that further enable the automatic generation of links. We investigate the requirements traceability recovery problem as an optimization problem;we study it as a multi-objective search in which we assign one-to-many relationships between each requirement to a code element by considering the semantic similarity between the textual content of requirements and the source code. We adapt the Non-dominated Sorting Genetic Algorithm, NSGA-II, to seek the optimal solution between two objective functions based on textual similarity using the similarity measures of Jaccard similarity and term frequency (TF-idf) combined with cosine similarity. Our IR-based NSGA-II returned values on average above 75% for both precision and recall for the recovered links. High precision and recall are positive results for our approach to requirements traceability recovery.

关键词： Requirements traceability link recovery optimization algorithms genetic algorithms NSGA-II

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Reduction of side lobes in the entire azimuth plane in a planar elliptical array antenna

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2022年第6期35卷

作者： Misra, Bitan Mahanti, Gautam Kumar Panda, Ganapati Natl Inst Technol Dept Elect & Commun Engn Durgapur India CV Raman Global Univ Bhubaneswar India

A novel synthesis method to reduce the maximum side lobe in the entire azimuth plane and for achieving a desired value of directivity of a concentric elliptical array antenna is addressed in this paper. Three well-performing meta-heuristic optimization algorithms, teaching learning-based optimization (TLBO), symbiotic organism search (SOS), and quantum particle swarm optimization (QPSO), are employed to optimize the cost function and to obtain the desired radiation pattern. Different simulation-based experiments are performed to obtain the best possible set of angular positions and the distribution of isotropic antennas across the ellipses by rigorously maintaining non-overlapping constraints. The major benefit of the proposed design is the deprecation of interference in all phi planes. The statistical analysis of the simulation results demonstrate perceptible improvement compared with that of a uniformly spaced concentric elliptical array and hence show the efficiency of the proposed algorithms. In both simulation studies, the results obtained using TLBO, SOS, and QPSO are compared. Analysis of the results exhibits that for the stated objective, the TLBO- and SOS-based side lobe reduction approach performs superior to QPSO method. Proposed multi-objective research work could lead to reduce payload and can simultaneously achieve isoflux coverage in entire azimuth plane on the earth surface which can essentially be utilized in (Low Earth Orbit) LEO and (Geostationary Earth Orbit) GEO satellites applications.

关键词： computation concentric elliptical array antenna directivity optimization algorithms planar array side lobe level

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A SAFETY-SPACE-BASED APPROACH TO INSPECTION PATH PLANNING FOR THE SHEET METAL ASSEMBLIES

A SAFETY-SPACE-BASED APPROACH TO INSPECTION PATH PLANNING FO...

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ASME International Mechanical Engineering Congress and Exposition (IMECE)

作者： Liu, Yinhua An, Chao Duan, Zhenxia Univ Shanghai Sci & Technol Shanghai Peoples R China

ISBN: (纸本)9780791885567

The inspection path planning of sheet metal assemblies plays an important role in the measurement efficiency of large free-form surfaces. In the path generation of a 5-axis coordinate measurement machine (CMM), large calculation of collision detection and obstacle avoidance are needed in the traditional computer-aided inspection planning methods. Owing to structure complexity of large free-form surfaces, the planning procedures for collision detection and automatic collision-free trajectory generation is time-consuming and low-efficiency. To address this problem, a safety-space-based modeling approach is proposed to generate a feasible collision-free path for a large number of key measurement points. At first, based on the decomposition of the dynamic motion trajectory of the probe and discretizing of the inspected object, a continuous envelope space, i.e., safety space is constructed for candidate path generation of the probe. In the proposed planning strategy, the work of collision detection and avoidance are eliminated. Then, a heuristic optimization algorithm is used to generate the feasible trajectory in the constructed safety space for all the measurement points. At last, an inspection path planning case of a car door assembly was used to illustrate the procedure of the proposed method.

关键词： Inspection Safety Sheet metal Path planning Collisions (Physics) Trajectories (Physics) Probes Modeling optimization algorithms Coordinate measuring machines Machinery Doors Manufacturing Computer-aided engineering

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EFFICIENT COMPUTATION OF SPARSE AND ROBUST MAXIMUM ASSOCIATION ESTIMATORS

arXiv

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arXiv 2023年

作者： Pfeiffer, Pia Alfons, Andreas Filzmoser, Peter Institute of Statistics and Mathematical Methods in Economics TU Wien Austria Department of Econometrics Erasmus Universiteit Rotterdam Netherlands

Robust statistical estimators offer resilience against outliers but are often computationally challenging, particularly in high-dimensional sparse settings. Modern optimization techniques are utilized for robust sparse association estimators without imposing constraints on the covariance structure. The approach splits the problem into a robust estimation phase, followed by optimization of a decoupled, biconvex problem to derive the sparse canonical vectors. An augmented Lagrangian algorithm, combined with a modified adaptive gradient descent method, induces sparsity through simultaneous updates of both canonical vectors. Results demonstrate improved precision over existing methods, with high-dimensional empirical examples illustrating the effectiveness of this approach. The methodology can also be extended to other robust sparse estimators. © 2023, CC BY.

关键词： optimization algorithms

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A review of parallel computing applications in calibrating watershed hydrologic models

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ENVIRONMENTAL MODELLING & SOFTWARE 2022年 151卷

作者： Asgari, Marjan Yang, Wanhong Lindsay, John Tolson, Bryan Dehnavi, Maryam Mehri Univ Guelph Dept Geog Environm & Geomat Guelph ON Canada Univ Waterloo Dept Civil & Environm Engn Waterloo ON Canada Univ Toronto Dept Comp Sci Toronto ON Canada

In recent decades, parallel computing has been increasingly applied to address the computational challenges of calibrating watershed hydrologic models. The purpose of this paper is to review these parallelization studies to summarize their contributions, identify knowledge gaps, and propose future research directions. These studies parallelized models based on either random-sampling-based algorithms or optimization algorithms and demonstrated considerable parallel speedup gain and parallel efficiency. However, the speedup gain/efficiency decreases as the number of parallel processing units increases, particularly after a threshold. In future, various combinations of hydrologic models, optimization algorithms, parallelization strategies, parallelization architectures, and communication modes need to be implemented to systematically evaluate a suite of parallelization scenarios for improving speedup gain, efficiency, and solution quality. A standardized suite of performance evaluation metrics needs to be developed to evaluate these parallelization approaches. Interactive multiobjective optimization algorithms and/or integrated sensitivity analysis and calibration algorithms are potential future research fields, as well.

关键词： Parallel computing Hydrologic model calibration optimization algorithms Parallel speedup Parallel efficiency

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Comparative Analysis of Heuristic-based Energy Efficient Protocol for M2M Communications in Green IoT

Comparative Analysis of Heuristic-based Energy Efficient Pro...

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3rd IEEE International Conference on Emerging Smart Computing and Informatics (IEEE-ESCI)

作者： Tupe, Umakant L. Kadam, Sonali Mahalle, Parikshit N. Marathwada Mitramandals Inst Technol Dept Comp Engn Pune Maharashtra India Bharati Vidyapiths Coll Engn Women Pune Maharashtra India SKNCOE Dept Comp Engn Pune Maharashtra India

ISBN: (纸本)9781728185194

There is a huge development in the Internet of Things (IoT) that causes massive deployment of sensors and thus automatic reconfigurable energy-efficient protocol for Green IoT is required. Machine-to-Machine (M2M) interactions are one of the core features of IoT. The M2M means the exchange of data among two or more entities, objects or machines, which do not require human interaction. To tackle the sustainability constraints of present IoT models, few developing models are thought to have been promised with new models. However, the fully usage of these models from communication, computing, and data processing for enhancing the energy efficiency of IoT still faces several basic defects. This paper tactics to plan for the comparative analysis on diverse heuristic approaches incorporated with Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol for energy-efficient M2M communication in Green IoT. The minimization of energy consumption by nodes in Green IoT is the main objective of the model. The algorithms like Genetic Algorithm (GA), Particle Swarm optimization (PSO), Artificial Bee Colony (ABC), Dargonfly Algorithm (DA), and Deer Hunting optimization Algorithm (DHOA) is adopted making the comparison part in energy-efficient Green IoT. This energy-efficient model maximizes the network lifetime finally.

关键词： Energy Efficient Protocol M2M Communications Green IoT Low Energy Adaptive Clustering Hierarchy optimization algorithms

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River water level prediction in coastal catchment using hybridized relevance vector machine model with improved grasshopper optimization

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JOURNAL OF HYDROLOGY 2021年 598卷

作者： Tao, Hai Al-Bedyry, Najah Kadhim Khedher, Khaled Mohamed Shahid, Shamsuddin Yaseen, Zaher Mundher Baoji Univ Arts & Sci Comp Sci Dept Baoji Shaanxi Peoples R China Univ Babylon Coll Engn Dept Civil Engn Babylon Iraq King Khalid Univ Coll Engn Dept Civil Engn Abha 61421 Saudi Arabia High Inst Technol Studies Dept Civil Engn Mrezgua Univ Campus Nabeul 8000 Tunisia Univ Teknol Malaysia UTM Fac Engn Sch Civil Engn Johor Baharu 81310 Malaysia Al Ayen Univ Sci Res Ctr New Era & Dev Civil Engn Res Grp Thi Qar 64001 Iraq Univ Teknol MARA Inst Big Data Analyt & Artificial Intelligence IB Shah Alam 40450 Selangor Malaysia

Modelling river water level (WL) of a coastal catchment is much complex due to the tidal influences on river WL. A hybrid machine learning model based on relevance vector machine (RVM) and improved grasshopper optimization (IGOA) is proposed in this study for modelling hourly WL in a catchment located in the east coast of tropical peninsular Malaysia. Considering the non-linear relationship between inputs and output, a recursive elimination filter based on support vector machine (SVM-RFE) was employed for the selection of the best combination of inputs from antecedent WL and rainfall data for the prediction of WL one hour ahead. The performance of IGOA was compared with classical GOA and particle swarm optimization (PSO) algorithms. Besides, the performance of the hybrid RVM model was compared with the artificial neural network (ANN) models hybridized with the same optimization algorithms. The SVM-RFE selected 1-, 12- and 24-lags WL data and 1-lag rainfall data as the most potential inputs. The relative performance of the models revealed the reliability of RVM-IGOA in WL prediction of a coastal catchment. Significant improvement of model performance was noticed after optimization using IGOA with Nash-Sutcliff Efficiency (NSE) of 0.986 and 0.981, and Kling-Gupta Efficient (KGE) of 0.981 and 0.974 for RVM-IGOA and ANN-IGOA respectively, compared to the models hybridized using other optimization algorithms with NSE between 0.969 and 0.971, and KGE between 0.890 and 0.908. The study indicates the selection of predictors based on their non-linear relations with WL and better optimization of model parameters can improve model performance in simulation of highly complex hydrological phenomena like tidal river WL in a tropical coastal catchment.

关键词： Flood prediction Tropical coastal catchment Relevance vector machine Non-linear input selection technique optimization algorithms

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A discussion about the Douglas-Reid model updating method and its prospective application to continuous vibration-based SHM of a historical building

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ENGINEERING STRUCTURES 2022年 273卷

作者： Rosati, I. Fabbrocino, G. Rainieri, C. Univ Molise Di BT Dept Via F de Sanctis I-86100 Campobasso Italy Natl Res Council Italy Construct Technol Inst Via Carducci I-67100 Laquila Italy Natl Res Council Italy Construct Technol Inst Corso N Protopisani I-80146 Naples Italy

The opportunities of Operational Modal Analysis and Finite Element model updating for non-destructive structural assessment have attracted significant research interest in recent years. In order to keep the computational efforts associated with model updating as low as possible, different strategies have been proposed over the years to approximate the model response. Among them, response surface models and the Douglas-Reid method are the most popular. However, systematic investigations about the factors affecting their model updating performance in view of Structural Health Monitoring applications are currently very limited. The present paper focuses the attention on the Douglas-Reid method, and analyzes the influence of different factors on the accuracy and reliability of model updating results. Comparisons with different updating approaches, such as grid search and the Inverse Eigensensitivity method, are also reported. The final objective is assessing the performance of the Douglas-Reid method for indirect monitoring of selected updating variables in the context of Structural Health Monitoring applications. Robustness and accuracy of model updating results under varying environmental conditions are evaluated to this aim, highlighting the interesting applicative perspectives of the method in the context of vibration-based Structural Health Monitoring, in spite of the very limited number of similar applications reported in the literature.

关键词： Finite Element model updating Douglas -Reid method Historical structure Structural Health Monitoring Objective function optimization algorithms Inverse Eigensensitivity

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