This study employs finite element analysis (FEA) to address the challenge of motion reconstruction in three-dimensional (3D) human body modeling, specifically focusing on joint movement. High-resolution CT and MRI sca...
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This study employs finite element analysis (FEA) to address the challenge of motion reconstruction in three-dimensional (3D) human body modeling, specifically focusing on joint movement. High-resolution CT and MRI scans of the knee joint were utilized to construct an accurate 3D reconstruction model, while the particle swarm algorithm was implemented to optimize joint positioning. Experimental evaluations were conducted to assess the influence of varying unit numbers and joint rotation angles on reconstruction accuracy. The results demonstrate that increasing the number of units significantly improves the model's continuity and precision. Notably, with 64 units, the discontinuities in the knee region were nearly eliminated, and the entire reconstruction process was completed in just 6.69 milliseconds. Moreover, adjustments in joint rotation angles effectively reduced reconstruction errors, bringing them down to 1.317 cm at a sampling frequency of 1/60. Additionally, iterative reconstruction decreased the error in the knee region by approximately 30% compared to non-iterative methods. The optimization process facilitated by the particle swarm algorithm revealed that most particles achieved high fitness levels after the initial iteration, and a considerable proportion shifted to the foreground region during the second iteration once fitness values dropped below 0.2. Ultimately, the study substantiates the accuracy and reliability of the proposed method for joint area reconstruction. These findings indicate that the FEA-based 3D reconstruction framework is highly effective in capturing complex joint movements and deformations, providing valuable insights for both biomechanical research and clinical applications.
Fuel consumption prediction plays an irreplaceable role in the assessment of ship emissions and energy efficiency optimization. However, in practical and diverse situations with different ship types, routes, and opera...
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Fuel consumption prediction plays an irreplaceable role in the assessment of ship emissions and energy efficiency optimization. However, in practical and diverse situations with different ship types, routes, and operating conditions, single-algorithm-based fuel consumption prediction models fail to operate effectively. Additionally, conventional fusion models that lack construction and optimization mechanisms also lack adaptability. To tackle this issue, this paper proposes a dual-adaptive prediction method. Initially, the particleswarm Optimization (PSO) algorithm is utilized to initialize each base-model. Next, the Binary particleswarm Optimization (BPSO) algorithm is employed to construct an adaptive Blending architecture. Finally, the Phasor particleswarm Optimization (PPSO) algorithm is used for adaptive cascaded optimization of the fusion model. Based on the aforementioned approach, the BPSO-Blending-PPSO model, which consistently maintains optimal performance, is constructed and validated using operational data from two ships. The results demonstrate that the BPSOBlending-PPSO model reduces the RMSE value by 5.2886-46.7492 % compared to single-algorithm models, effectively adapting to various sailing conditions of different ships. This method not only provides a new perspective to improve the predictive accuracy and robustness of ship fuel consumption models but also exhibits good scalability by incorporating various novel prediction algorithms into the base-model pool.
The energy group structure significantly affects the accuracy and efficiency of cross-section and transport calculations. Plate-type reactors have significant differences in neutron dynamics compared to traditional ro...
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The energy group structure significantly affects the accuracy and efficiency of cross-section and transport calculations. Plate-type reactors have significant differences in neutron dynamics compared to traditional rod reactors, which means that traditional energy group structures are not suitable for plate-type reactors. Therefore, it is necessary to explore new energy group structures to adapt to the complex structure of plate-type reactor cores. The paper proposes an optimization method suitable for the energy group structure of plate-type fuel based on the particle swarm algorithm. To ensure the universality of the obtained multi group structure in the plate-type fuel structure, the sensitivity of the plate elements parameters has been analyzed. Multiple examples are set up for optimization, with the average difference in k infinity between multi-group and coarse-group transport calculations as the objective function, and the optimal energy group boundary position is sought by updating generation by generation. Based on the above method, the 15-group, 29-group, 37-group, and 45-group structures suitable for multi-group transport calculations of pressurized water reactor plate-type cores are optimized. Numerical verification shows that the group structure proposed in this paper has high computational accuracy for various operating conditions of pressurized water reactor plate-type cores, and significantly improves computational efficiency compared to the traditional 361-group structure.
With the development of microelectronics and micro-electromechanical systems, the performance requirements for microchannels are becoming increasingly higher and more complex. This study aims to improve the overall pe...
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With the development of microelectronics and micro-electromechanical systems, the performance requirements for microchannels are becoming increasingly higher and more complex. This study aims to improve the overall performance of rectangular microchannels using the multi-objective particleswarm optimization algorithm (MOPSOA). First, the response surface methodology (RSM) was adopted to fit the thermal resistance function. Three-dimensional contour plots and response surface plots were created to analyze the interaction between fin thickness, channel width, and channel depth, aiming to understand their impact on thermal resistance values. Second, a mathematical model for the MOPSOA was developed with the objective functions being thermal resistance and pressure drop. Next, the Pareto optimal solution set for thermal resistance and pressure drop was determined by conducting simulations, and the K-mean clustering method was employed to identifying the four representative solutions. The results indicate a high level of accuracy in the thermal resistance function fitted by the RSM, with correlation coefficients R2= 0.9981 and adjusted correlation coefficient adj R2= 0.9961 respectively. Finally, the performance of a microchannel heat sink was assessed using the computational fluid dynamics method, and the optimized heating surface has a maximum temperature of 11 °C and a maximum pressure drop of 5.292 kPa lower than the non-optimized one. Additionally, the temperature distribution on the substrate is more uniform. This revealed a superior heat transfer capability and lower pressure drop, resulting in a more comprehensive and efficient performance.
The UAV (Unmanned Aerial Vehicle) task allocation problem in power inspection is a complex optimization problem aimed at improving inspection efficiency, reducing costs, and ensuring the safety and reliability of powe...
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Maximum power point tracking (MPPT) control techniques are commonly employed to maximize the benefits and enhance the operational efficiency of photovoltaic systems in challenging outdoor environments. However, when t...
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Maximum power point tracking (MPPT) control techniques are commonly employed to maximize the benefits and enhance the operational efficiency of photovoltaic systems in challenging outdoor environments. However, when the photovoltaic array is subjected to partial shading conditions, the conventional MPPT methods exhibit inadequate global maximum power point (GMPP) tracking performance. To this end, in this study, an effective MPPT control method for photovoltaic systems is proposed based on a hybrid improved whale particleswarm optimization algorithm (IWPOA). The control method integrates the advantages of the Improved Whale Optimization algorithm (IWOA) and the particle swarm algorithm (PSO) with additional control and stochastic elements. Validation analysis under a variety of conditions reveals that IWPOA significantly improves MPPT, achieving a tracking speed of approximately 0.13 s, which represents a 18.75-53.57% enhancement over other comparative algorithms. The mean tracking accuracy of IWPOA is 99.21%, and it offers superior tracking stability, making it suitable for diverse applications in MPPT.
The damage-mitigating control is a novel technique to ameliorate the reliability and safety of liquid-propellant rocket engines by achieving an optimized trade-off level between overall dynamic performance of the liqu...
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The damage-mitigating control is a novel technique to ameliorate the reliability and safety of liquid-propellant rocket engines by achieving an optimized trade-off level between overall dynamic performance of the liquid-propellant rocket engine and structural durability of some selected critical damageable components under the condition of no impact on the achievement of the launch and flight mission. Thus, it is needed to be solved for the damage-mitigating control that the global optimization of the best trade-off between the damage of the critical damageable components and the performance of rocket engine. The major challenge should focus on: (i) to construct model of a certain rocket engine system dynamics, critical components structural dynamics, and damage dynamics;(ii) to optimize open loop feed-forward control law based on liquid-propellant rocket engine system dynamic model, structural and damage dynamics model, by using particleswarm optimization algorithm;(iii) to synthesize an intelligent damage-mitigating control system using the optimized open loop control law. In this paper, synthesis procedure of damage mitigation is introduced;structure and damage dynamic model of damageable components are formulated. The results of the simulation computation show that the synthesized control laws are implemented and achieve the effect of damage mitigating for the liquid-propellant rocket engine. It can provide important theoretical and practical value not only for improving the safety and reliability of the liquid-propellant rocket engine, but also for the complex thermo-flow-mechanical systems such as airplane engines, automobile engines, and fossil-fueled power plant because their service life is very critical too.
Discretization of attributes with real values is an important problem in data mining. From the viewpoint of discernibility, consistency needs to be satisfied and cuts set for discretization is expected to be as small ...
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ISBN:
(纸本)9783037855744
Discretization of attributes with real values is an important problem in data mining. From the viewpoint of discernibility, consistency needs to be satisfied and cuts set for discretization is expected to be as small as possible. Consistent and minimal discretization problem is NP-complete. A particle swarm algorithm for discretization of decision tables is proposed.
Components on console are usually arranged by manual layout according to ergonomics standards and experiences in nuclear power plant. It is hard to balance many criterions, for it depends much on designer's judgme...
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ISBN:
(纸本)9781424458479
Components on console are usually arranged by manual layout according to ergonomics standards and experiences in nuclear power plant. It is hard to balance many criterions, for it depends much on designer's judgments and preferences. This method leads to a random layout results. particleswarm optimization is a solution to complex optimization problems with constraints, and has been applied successfully in layout and optimization fields. Fitness function was structured according to the evaluating indicators which include operation frequency and order and relationships between individuals. The optimization objective was evaluated by the hand moving distance. This method could be adopted to optimize the layout of components on human-machine interface in order to ensure safety and efficiency of the system. The troubles of subjective feelings and randomness are avoided. An example of 13 components is implemented to show the layout procedure.
With the rapid development of modern society, enterprises have also stepped into an era in which the modernization process is accelerating. There are more and more enterprise groups participating in market competition...
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