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ASME International Mechanical Engineering Congress and Exposition (IMECE)

作者： Altammar, Hussain Kaul, Sudhir Dhingra, Anoop Univ Jamestown Jamestown ND 58405 USA Western Carolina Univ Cullowhee NC USA Univ Wisconsin Milwaukee WI USA

ISBN: (纸本)9780791885697

This paper presents a novel probabilistic optimization approach to identify damage characteristics by using the frequency response function (FRF). The proposed approach has been developed to predict the probability of damage existence and to further identify salient details about damage location and damage severity in a probabilistic manner. The optimization problem has been developed as a function of measured and simulated frequency responses and is formulated in a multi-stage sequence to detect the probability of damage parameters including crack depth and crack location while minimizing uncertainties in the analysis outcomes. To demonstrate the proposed approach, a simply supported beam has been modeled with an open edge crack and characterized by using Linear Elastic Fracture Mechanics (LEFM). Several frequency responses obtained from the structure have been incorporated with different levels of noise to evaluate the robustness of the proposed algorithm. The algorithm has been tested through multiple simulations with various damage characteristics and different levels of noise. In all cases, the proposed algorithm has successfully predicted the presence of damage with a relatively high probability. Evaluation of the results demonstrates that the probabilistic optimization approach provides significant advantages over conventional deterministic methods for damage detection in structural health monitoring.

关键词： damage detection optimization algorithm probabilistic structural health monitoring structural integrity

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Complex hilly terrain agricultural UAV trajectory planning driven by Grey Wolf Optimizer with interference model

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APPLIED SOFT COMPUTING 2024年 160卷

作者： Liu, Xinyu Shao, Peng Li, Guangquan Ye, Liuxi Yang, Haoyuan Jiangxi Agr Univ Sch Comp & Informat Engn Nanchang 330045 Peoples R China Jiangxi Agr Univ Coll Land Resources & Environm Nanchang 330045 Peoples R China

To address the limitations of agricultural UAV in performing trajectory planning in complex hilly terrain, a trajectory planning model based on hilly characteristic terrain and agricultural scheduling requirements is proposed. For obtaining an efficient and stable flight operations solution, a multi mechanism grey wolf algorithm based on the interferometric image enhancement model (IIE-GWO) is proposed to improve the population diversity and balance the algorithm's ability of exploration and exploitation. By comparing the IIE-GWO with twelve significant meta-heuristic algorithms on the CEC2017 functions in a comparative experiment, the results show that the IIE-GWO possesses excellent optimization seeking ability and search stability. Meanwhile, in the trajectory planning part, the effectiveness of the model and algorithms was tested by eight flight tasks with different scales and challenges. The experimental results show that IIE-GWO is able to generate effective trajectory paths, and the flight cost of the agricultural operations performed in the hilly terrain is low, and the trajectory planning capability is more adaptable and effective.

关键词： Unmanned aerial vehicle Trajectory planning optimization algorithm Interferometric image Hilly terrain

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Revolutionizing Demand Response Management: Empowering Consumers through Power Aggregator and Right of Flexibility

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ENERGIES 2024年第6期17卷 1419页

作者： Alhussein, Sadeq Neamah Bazoon Barzamini, Roohollah Ebrahimi, Mohammad Reza Farahani, Shoorangiz Shams Shamsabad Arabian, Mohammad Aliyu, Aliyu M. Sohani, Behnaz Islamic Azad Univ Dept Elect Engn Sci & Res Branch Tehran *** Iran Islamic Azad Univ Dept Elect Engn Cent Tehran Branch Tehran *** Iran Islamic Azad Univ Islamshahr Branch Dept Elect Engn Islamshahr *** Iran Univ Lincoln Coll Hlth & Sci Sch Engn Lincoln LN6 7TS England

This paper introduces a groundbreaking approach to demand response management, aiming to empower consumers through innovative strategies. The key contribution is the concept of "acquiring flexibility rights", wherein consumers engage with power aggregators to curtail energy usage during peak-load periods, receiving incentives in return. A flexibility right coefficient is introduced, allowing consumers to tailor their participation in demand response programs, ensuring their well-being. Additionally, a lighting intensity control system is developed to enhance residential lighting network efficiency. The study demonstrates that high-energy consumers, adopting a satisfaction factor of 10, can achieve over 61% in electricity cost savings by combining the lighting control system and active participation in demand response programs. This not only reduces expenses but also generates income through the sale of flexibility rights. Conversely, low-energy consumers can fully offset their expenses and accumulate over USD 33 in earnings through the installation of solar panels. This paper formulates an optimization problem considering flexibility rights, lighting control, and time-of-use tariff rates. An algorithm is proposed for a distributed solution, and a sensitivity analysis is conducted for evaluation. The proposed method showcases significant benefits, including cost savings and income generation for consumers, while contributing to grid stability and reduced blackout occurrences. Real data from a residential district in Tehran validates the method's effectiveness. This study concludes that this approach holds promise for demand response management in smart grids, emphasizing the importance of consumer empowerment and sustainable energy practices.

关键词： demand response management flexibility rights lighting intensity control energy cost savings optimization algorithm

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Application and effect evaluation of BIM technology in seismic design of high-rise buildings

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INFRASTRUCTURE ASSET MANAGEMENT 2025年

作者： Hu, Yunpeng Henan Univ Urban Construct Sch Management Pingdingshan Peoples R China

This paper discusses the application of Building Information Modelling (BIM) technology in the seismic design of high-rise buildings, focusing on digital modelling based on BIM, seismic performance optimisation algorithm, structural analysis and seismic load simulation, and data-driven performance evaluation methods. Through the construction and optimisation of the BIM model, not only is the design accuracy improved, but the intelligent and dynamic optimisation of the design process is also realized, especially in the application of seismic performance prediction and structural optimisation. The material utilisation rate of 23.5% shows a high resource utilisation efficiency, while 87% of the building structures meet the design seismic standards. When considering different optimisation schemes, a 54.8% improvement in seismic performance was recorded. However, a 12.9% increase in cost affected the final decision. The optimized scheme exhibited a 68.4% improvement in seismic stability, while a 91% shortened construction period, indicating that the optimized design improved performance and significantly improved in time. A good balance is achieved between the 34.7% increase in seismic effect and the 77.2% cost saving, indicating the critical role of BIM technology in optimisation design.

关键词： BIM technologies high-rise buildings optimization algorithm seismic design

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Two-level Weight optimization of Composite Laminates using Integer Programming

Two-level Weight Optimization of Composite Laminates using I...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Borwankar, Pranav Zhao, Wei Kapania, Rakesh K. Bansal, Manish Virginia Polytech Inst & State Univ Kevin T Crofton Dept Aerosp & Ocean Engn Blacksburg VA 24060 USA Virginia Polytech Inst & State Univ Dept Ind & Syst Engn Blacksburg VA 24060 USA

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

Composite laminate optimization requires the satisfaction of various constraints wherein the various design parameters such as the ply thicknesses and orientations can only take discrete values prescribed by the manufacturer. Different heuristics, such as particle swarm or genetic algorithms, are inefficient in such cases primarily because they provide sub-optimal solutions and are computationally expensive. In contrast, with the help of binary decision variables, Mixed Integer Programming (MIP) can be adapted to efficiently optimize such laminates. Using a commercially available MIP solver Gurobi [1], this paper presents an approach using integer programming that can be used in the optimization of composite laminates subjected to failure constraints that are non-linear in terms of design variables. Initially, buckling load maximization for a simply-supported laminated plate is demonstrated using integer linear programming. The formulation is then modified to minimize the laminate weight for a given external bi-axial compressive load and subjected to buckling and material failure constraints. The modified problem is optimized with a nested bi-level approach using a combination of integer programming and a gradient-based optimizer (GBO). Finally, a two-level, sequential method is demonstrated which can be used for GBO-MIP or MIP-MIP combinations to optimize laminates subjected to constraints of polynomial order higher than two.

关键词： Composite Laminates optimization algorithm Genetic algorithm Finite Element Modeling Evolutionary algorithm Mixed Integer Linear Programming Aspect Ratio Annealing Techniques Composite Structures Transverse Shear

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IEAWind Energy Task 37 System Engineering Aerodynamic optimization Case Study

IEAWind Energy Task 37 System Engineering Aerodynamic Optimi...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： McWilliam, Michael K. Dykes, Katherine Zahle, Frederik Bortolotti, Pietro Ning, Andrew Gaertner, Evan Macquart, Terence Merz, Karl Ruiz, Ainara Irisarri Tech Univ Denmark Wind Energy Dept Frederiksborgvej 399 DK-4000 Roskilde Denmark Natl Renewable Energy Lab Natl Wind Technol Ctr 18200 CO-128 Boulder CO 80303 USA Brigham Young Univ Provo UT 84602 USA Univ Massachusetts Amherst Amherst MA 01003 USA Univ Bristol Senate HouseTyndall Ave Bristol BS8 1TH Avon England SINTEF POB 4760 NO-7465 Trondheim Norway CENER Natl Renewable Energy Ctr Av Ciudad Innovac 7 Sarriguren 31621 Navarra Spain

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

This paper presents the results from the first IEA Wind Task 37 aerodynamic optimization case study. Eight participants applied their optimization tools to a purely aerodynamic problem and the results were compared. Overall, the different tools produced widely different designs, while there was better agreement in the improvement achieved. This highlights the fact that further investigation is needed to try to understand these differences and develop best practices. There were too many differences between the different analysis and optimization codes to determine the sources of these differences. However, several potential sources of discrepancy were identified for further investigation. One hypothesis is that one potential source of discrepancy is that the design problem itself is relatively flat in design directions of constant loading. This flatness would impact the convergence in the optimization, and at the same time mean that discrepancies in the design itself would be less severe.

关键词： Systems Engineering Wind Energy Bending Moment Wind Turbine Design optimization algorithm Aerodynamic Efficiency Aerodynamic Design MATLAB Lift to Drag Ratio Genetic algorithm

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Single and multi-objective optimization of steel moment-resisting frame buildings under vehicle impact using evolutionary algorithms

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Journal of Building Pathology and Rehabilitation 2021年第1期6卷 1-13页

作者： Sadeghi, Abbasali Kazemi, Hamid Samadi, Maysam Department of Civil Engineering Mashhad Branch Islamic Azad University Mashhad Iran

The evaluation of optimization approaches such as single and multi-objective optimization is important for determining the optimal design of structures against abnormal loadings. In this study, the optimal design of steel moment-resisting frames (SMRFs) with 5 and 12-story is investigated and compared by using the mentioned optimization approaches under light vehicle impact loading. Then, the single and multi-objective optimization methodologies are discussed. Next, for single-objective optimization approach, three evolutionary algorithms such as a particle swarm optimization (PSO), a genetic algorithm (GA) and a whale optimization algorithm (WOA) are considered and then for another approach, a multi-objective optimization cuckoo search algorithm (MOCSA) is noticed by linking the nonlinear dynamic analysis responses of OpenSees software to MATLAB software for weight optimization of SMRFs. Finally, the effectiveness and efficiency of these optimization algorithms are evaluated and compared with each other. The results indicated that in comparison to single-objective method, the MOCSA was able to present a solution leading to a more practical and economic selection of minimum total weights and drift. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Light vehicle impact Multi-objective optimization algorithm Single-objective Steel moment-resisting frame

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Path Synthesis optimization Model of Planar Five-Bar Metamorphic Mechanism 14th

Path Synthesis Optimization Model of Planar Five-Bar Metamor...

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14th International Conference on Intelligent Robotics and Applications (ICIRA)

作者： Yao, Xinyuan Wang, Xingdong Sun, Wei Bai, Haoke Wuhan Univ Sci & Technol Sch Mech Automat Wuhan Peoples R China

ISBN: (纸本)9783030890926;9783030890919

The path synthesis of metamorphic mechanism is an essential problem in kinematics. This paper develops a new optimization model for planar five-bar metamorphic mechanism with two sub-configurations. As different configurations may produce large differences in the target points, the utilization of two configurations can help to preserve good results and avoid bad results. Comparative study between metamorphic mechanism and the models using one sub-configuration shows that trajectory of metamorphic mechanism by the proposed model is closer to the target point. In addition, an example demonstrates the comprehensive capabilities of metamorphic mechanisms in the face of trajectories with change mutation points. This optimization model has potential reference value for the optimization of other metamorphic mechanisms.

关键词： Metamorphic mechanism Path synthesis optimization algorithm Kinematics Five-bar mechanism

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Enhanced Flexible algorithm for the optimization of Slot Filling Factors in Electrical Machines

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ENERGIES 2020年第5期13卷 1041-1041页

作者： Dietz, Armin Di Tommaso, Antonino Oscar Marignetti, Fabrizio Miceli, Rosario Nevoloso, Claudio Tech Hsch Nurnberg Inst ELSYS D-90489 Nurnberg Germany Univ Palermo Dipartimento Ingn Viale Sci I-90128 Palermo Italy Univ Cassino & South Lazio Dept Elect & Informat Engn DIEI Via G Di Biasio 43 I-03043 Cassino Italy

The continuous development in the field of industrial automation and electric mobility has led to the need for more efficient electrical machines with a high power density. The improvement of electrical machines' slot filling factors is one of the measures to satisfy these requirements. In recent years, this topic has aroused greater interest in the industrial sector, since the evolution of the winding technological manufacturing processes allows an economically sustainable realization of ordered winding arrangements, rather than random ones. Moreover, the manufacture of electrical machines' windings must be preceded by an accurate design phase in which it is possible to evaluate the maximum slot filling factor obtainable for a given wire shape and for its dimensions. For this purpose, this paper presents an algorithmic approach for the evaluation of maximum slot filling factors in electrical machines under an ideal geometric premise. In particular, this algorithm has a greater degree of flexibility with respect to the algorithm approaches found in the literature, since the study has been extended to round, rectangular and hexagonal wire sections. Furthermore, the slot filling factor calculation was carried out both for standard and non-standard slots. The algorithmic approach proposed can be considered as an additional useful tool for the fast design of electrical machine windings.

关键词： electrical motors sot filling factor optimization algorithm windings magnetic wire filling factor optimization

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Estimating an optimal macroeconomic uncertainty index for Australia

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APPLIED ECONOMICS 2022年第38期54卷 4374-4383页

作者： Kaya, Havvanur Feyza Tawadros, George B. Samsun Univ Fac Econ Adm & Social Sci Dept Int Commerce & Business Samsun Turkey Winona State Univ Dept Econ Coll Business Winona MN 55987 USA

In this article, an optimal macroeconomic uncertainty index is constructed for the Australian economy. This index is derived from a small structural macroeconomic model. The structural model is first estimated using GMM to extract the parameter estimates, which are then used to initialize maximum likelihood techniques in order to obtain the optimal coefficient values for the relevant variables. The relevant variables are then weighted by the obtained optimal coefficients and, finally, are aggregated to produce the optimal macroeconomic uncertainty index for Australian economy. The empirical results show that the uncertainty index constructed is a good indicator of the optimal economic conditions in Australia, providing a useful tool to assist the Reserve Bank of Australia in its decision-making process.

关键词： Optimal uncertatiny index central bank GMM optimization algorithm

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