- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
[IEEE 2019 International Conference on Optical MEMS and Nanophotonics (OMN) - Daejeon, Korea (South) (2019.7.28-2019.8.1)] 2019 International Conference on Optical MEMS and Nanophotonics (OMN) - Electromagnetic FPCB micromirror scanning laser rangefinder
摘要： Since several years, the number of total hip arthroplasty revision surgeries is substantially growing. One of the main reasons for this procedure to become necessary is the loosening or damage of the prothesis, which is facilitated by bone necrosis at the implant–bone interface. Electrostimulation is one promising technique, which can accelerate the growth of bone cells and, therefore, enhance the anchorage of the implant to the bone. We present computational models of an electrostimulative total hip revision system to enhance bone regeneration. In this study, the influence of uncertainty in the conductivity of bone tissue on the electric field strength and the beneficial stimulation volume for an optimized electrode geometry and arrangement is investigated. The generalized polynomial chaos technique is used to quantify the uncertainty in the stimulation volumes with respect to the uncertain conductivity of cancellous bone, bone marrow, and bone substitute, which is used to fill defective areas. The results suggest that the overall beneficial stimulation areas are only slightly sensitive to the uncertainty in conductivity of bone tissue. However, in the proximity of tissue boundaries, larger uncertainties, especially in the transition between beneficial and understimulation areas, can be expected.
关键词： Electrical stimulation,finite-element method,multiobjective optimization,uncertainty quantification,total hip arthroplasty (THA) revision
更新于2025-09-19 17:13:59
-
[IEEE IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society - Lisbon, Portugal (2019.10.14-2019.10.17)] IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society - Techno-Economic Analysis of Building Integrated Photovoltaics Electrical Installations
摘要： Insulated-gate bipolar transistor (IGBT) power modules find widespread use in numerous power conversion applications where their reliability is of significant concern. Standard IGBT modules are fabricated for general-purpose applications while little has been designed for bespoke applications. However, conventional design of IGBTs can be improved by the multiobjective optimization technique. This paper proposes a novel design method to consider die-attachment solder failures induced by short power cycling and baseplate solder fatigue induced by the thermal cycling which are among major failure mechanisms of IGBTs. Thermal resistance is calculated analytically and the plastic work design is obtained with a high-fidelity finite-element model, which has been validated experimentally. The objective of minimizing the plastic work and constrain functions is formulated by the surrogate model. The nondominated sorting genetic algorithm-II is used to search for the Pareto-optimal solutions and the best design. The result of this combination generates an effective approach to optimize the physical structure of power electronic modules, taking account of historical environmental and operational conditions in the field.
关键词： power cycling (PC),Aging,fatigue,insulated-gate bipolar transistors (IGBTs),thermal cycling (TC),multiobjective,optimization methods,reliability,finite-element (FE) methods
更新于2025-09-19 17:13:59
-
[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Investigations of Site-Specific, Long Term Average Albedo Determination for Accurate Bifacial System Energy Modeling
摘要： It is known that Pareto dominance has its own weaknesses as the selection criterion in evolutionary multiobjective optimization. Algorithms based on Pareto criterion (PC) can suffer from problems such as slow convergence to the optimal front and inferior performance on problems with many objectives. Non-Pareto criterion (NPC), such as decomposition-based criterion and indicator-based criterion, has already shown promising results in this regard, but its high selection pressure may lead to the algorithm to prefer some specific areas of the problem’s Pareto front, especially when the front is highly irregular. In this paper, we propose a bi-criterion evolution (BCE) framework of the PC and NPC, which attempts to make use of their strengths and compensates for each other’s weaknesses. The proposed framework consists of two parts: PC evolution and NPC evolution. The two parts work collaboratively, with an abundant exchange of information to facilitate each other’s evolution. Specifically, the NPC evolution leads the PC evolution forward and the PC evolution compensates the possible diversity loss of the NPC evolution. The proposed framework keeps the freedom on the implementation of the NPC evolution part, thus making it applicable for any non-Pareto-based algorithm. In the PC evolution, two operations, population maintenance and individual exploration, are presented. The former is to maintain a set of representative nondominated individuals and the latter is to explore some promising areas that are undeveloped (or not well-developed) in the NPC evolution. Experimental results have shown the effectiveness of the proposed framework. The BCE works well on seven groups of 42 test problems with various characteristics, including those in which Pareto-based algorithms or non-Pareto-based algorithms struggle.
关键词： Pareto criterion (PC),Bi-criterion evolution (BCE),non-Pareto criterion (NPC),evolutionary multiobjective optimization (EMO)
更新于2025-09-19 17:13:59
-
[IEEE 2019 21st International Middle East Power Systems Conference (MEPCON) - Cairo, Egypt (2019.12.17-2019.12.19)] 2019 21st International Middle East Power Systems Conference (MEPCON) - Optimal Allocation of Reactive Power Compensation in a Distribution Network with Photovoltaic System Integration
摘要： Since several years, the number of total hip arthroplasty revision surgeries is substantially growing. One of the main reasons for this procedure to become necessary is the loosening or damage of the prothesis, which is facilitated by bone necrosis at the implant–bone interface. Electrostimulation is one promising technique, which can accelerate the growth of bone cells and, therefore, enhance the anchorage of the implant to the bone. We present computational models of an electrostimulative total hip revision system to enhance bone regeneration. In this study, the influence of uncertainty in the conductivity of bone tissue on the electric field strength and the beneficial stimulation volume for an optimized electrode geometry and arrangement is investigated. The generalized polynomial chaos technique is used to quantify the uncertainty in the stimulation volumes with respect to the uncertain conductivity of cancellous bone, bone marrow, and bone substitute, which is used to fill defective areas. The results suggest that the overall beneficial stimulation areas are only slightly sensitive to the uncertainty in conductivity of bone tissue. However, in the proximity of tissue boundaries, larger uncertainties, especially in the transition between beneficial and understimulation areas, can be expected.
关键词： Electrical stimulation,finite-element method,multiobjective optimization,uncertainty quantification,total hip arthroplasty (THA) revision
更新于2025-09-19 17:13:59
-
[IEEE 2019 International Conference on Advanced Electrical Engineering (ICAEE) - Algiers, Algeria (2019.11.19-2019.11.21)] 2019 International Conference on Advanced Electrical Engineering (ICAEE) - Photovoltaic module parameters extraction using best-so-far ABC algorithm
摘要： Existing multiobjective evolutionary algorithms (MOEAs) tackle a multiobjective problem either as a whole or as several decomposed single-objective sub-problems. Though the problem decomposition approach generally converges faster through optimizing all the sub-problems simultaneously, there are two issues not fully addressed, i.e., distribution of solutions often depends on a priori problem decomposition, and the lack of population diversity among sub-problems. In this paper, a MOEA with double-level archives is developed. The algorithm takes advantages of both the multiobjective-problem-level and the sub-problem-level approaches by introducing two types of archives, i.e., the global archive and the sub-archive. In each generation, self-reproduction with the global archive and cross-reproduction between the global archive and sub-archives both breed new individuals. The global archive and sub-archives communicate through cross-reproduction, and are updated using the reproduced individuals. Such a framework thus retains fast convergence, and at the same time handles solution distribution along Pareto front (PF) with scalability. To test the performance of the proposed algorithm, experiments are conducted on both the widely used benchmarks and a set of truly disconnected problems. The results verify that, compared with state-of-the-art MOEAs, the proposed algorithm offers competitive advantages in distance to the PF, solution coverage, and search speed.
关键词： multiobjective optimization,Evolutionary algorithm (EA),global optimization
更新于2025-09-16 10:30:52
-
A Priority-Based Multiobjective Design for Routing, Spectrum, and Network Coding Assignment Problem in Network-Coding-Enabled Elastic Optical Networks
摘要： In elastic optical networks, the use of network coding (NC) represents a new dimension to further optimize spectrum efficiency, and indeed, combining NC and dedicated path protection has paved the way for achieving greater capacity efficiency, while retaining the merit of near-instantaneous recovery. In order to harness the NC benefits, a more complicated problem called routing, spectrum, and network coding assignment (RSNCA) has to be solved, and in this article, we propose a priority-based multiobjective design for the RSNCA problem aiming at maximizing the network throughput in the constrained bandwidth capacity and simultaneously minimizing the spectrum link usage for accepted demands. The multiobjective design is based on the weighting method, and we present a rigorous analysis on the impact of weight coefficients to the priority of constituent objectives. The efficacy of our design proposal is benchmarked with reference ones based on the traditional single-objective model and for both coding and non-coding approaches on various realistic topologies. It is highlighted that the application of NC brings about considerable throughput enhancement, and furthermore, the multiobjective RSNCA design is highly more efficient than the single-objective RSNCA, as up to more than 50% saving on spectrum link usage could be attained.
关键词： routing and spectrum assignment (RSA),elastic optical networks,network coding (NC),intelligent optical networks,integer linear programming,multiobjective optimization,Dedicated protection
更新于2025-09-16 10:30:52
-
[IEEE 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) - Valparaiso, Chile (2019.11.13-2019.11.27)] 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) - A simple validation methodology for Photovoltaic Systems efficacy in Agriculture applications
摘要： This paper addresses the integrated volt-var control for distribution network operation via multiobjective optimization. This paper seeks to explore the problem of energy savings and peak demand relief through the voltage reduction procedure. Currently, due to the emergence of the distribution smart grids, these procedures are gaining renewed interest and attention. The proposal presented here is for the operation phase, with a strategy based on an hourly load forecast for the next day/week, taking into account the active power intake reduction, and the voltage deviation. Therefore, the result is a set of nondominated optimal solutions, and then one may decide when, where, and how to apply them to meet different goals. The obtained solutions, for two typical distribution networks, describe relevant economic and technical bene?ts.
关键词： multiobjective optimization,Distribution systems,voltage reduction,integrated volt-var control
更新于2025-09-16 10:30:52
-
Large-Temporal-Numerical-Aperture Parametric Spectro-Temporal Analyzer Based on Silicon Waveguide
摘要： In the distributed integrated modular avionics (DIMA), it is desirable to assign the DIMA devices to the installation locations of the aircraft for obtaining the optimal quality and cost, subject to the resource and safety constraints. Currently the routine device assignments in DIMA are conducted manually or by experience, which becomes more and more dif?cult with the increasing number of devices. Especially in the face of large-scale device assignment problems (DAPs), manual allocation will become an almost impossible task. In this paper, a bi-objective safety-constraint device assignment model in DIMA is formulated with the integer encoding for better scalability. A two-Phase multiobjective local search (2PMOLS) is proposed for addressing it. In the ?rst phase of 2PMOLS, the fast convergence of the population towards the Pareto front (PF) is achieved by the weighted sum approach. In the second phase, Pareto local search is conducted on the solutions delivered in the ?rst phase for the extension of the PF approximation. 2PMOLS is compared with three decomposition-based approaches and one domination-based approach on DAPs of different sizes in the experimental studies. The experimental results show that 2PMOLS outperforms all the compared algorithms, in terms of both the convergence and diversity. It has also been demonstrated that the solution obtained by 2PMOLS is better in terms of both objectives (mass and ship set costs), compared with the solution designed by the domain expert. The experimental results show that 2PMOLS performs increasingly better with the increase of the problem size, compared with other algorithms, which indicates it has better scalability.
关键词： device assignment,Distributed Integrated Modular Avionics,multiobjective optimization,Pareto local search
更新于2025-09-11 14:15:04
-
A multiobjective approach for design of an off-grid PV/Diesel system considering reliability and cost
摘要： The aim of the present study is to solve multiobjective optimization (MO) of an off-grid hybrid power generation system including photovoltaic (PV) and diesel generator by multiobjective version of a recently developed metaheuristic approach named crow search algorithm (CSA). For this goal, the objective functions are regarded as net present cost (NPC) and system reliability defined by loss of power supply probability (LPSP) index. In the optimization problem, operating limitations of diesel generator and uncertainties of solar radiation and load demand are considered. To solve this problem, a multiobjective CSA (MO-CSA) is developed and the obtained results are compared with the results of nondominated sorting genetic algorithm II (NSGA-II). On the case study, simulation results reveals that when diesel generator ramp rate is 100%, at LPSP = 0, MO-CSA reaches to 54.8 kW and 172.8 m2 for rated power of diesel generator and PV surface area (corresponding cost is 3.7219 × 105 $), while the values found by NSGA-II are 55 kW and 86.04 m2 (corresponding cost is 3.7345 × 105 $). Based on the results, it can be drawn that (1) MO-CSA finds more promising results than NSGA-II, (2) Combination of PV and diesel generator leads to having a cost-effective and reliable power generation system, and (3) by considering the solar radiation and load uncertainties, the system cost increases.
关键词： crow search algorithm,hybrid photovoltaic/diesel system,multiobjective optimization
更新于2025-09-10 09:29:36
-
Robust Optimization of Nanoslit Array Sensor Based on Extraordinary Optical Transmission
摘要： A robust optimization approach for plasmonic periodic array sensor based on extraordinary optical transmission is proposed using Kriging surrogate models to reduce the effects of uncertainty in various manufacturing processes while maintaining sensor performance. For systematic design with reasonable computation cost, the author adopt the universal Kriging models whose regression function is a polynomial. The gradient index and the multiobjective genetic algorithm are chosen as a robustness measure and a global optimization tool, respectively. The figure of merit and the gradient index are set as two objective functions, and the design variables are the slit width and height, respectively. The optical properties of interest are investigated using the finite-element method. The numerical optimization results show the proposed scheme to be powerful and efficient in designing nanoslity array sensors based on extraordinary optical transmission with fabrication uncertainty.
关键词： gradient index,robust optimization,Plasmonics,surface plasmon polariton,multiobjective optimization,Kriging model
更新于2025-09-09 09:28:46