34 research outputs found
A close neighbor mobility method using particle swarm optimizer for solving multimodal optimization problems
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Niching is an important technique for multimodal optimization. Most existing niching methods require specification of certain niching parameters in order to perform well. But these parameters are usually difficult to set because they depend on the problem. The particle swarm optimization algorithm using the ring neighborhood topology does not require any niche parameters, but the determination of the particle neighborhood in this method is based on the subscript of the particle, and the result fails to achieve the best performance. For better performance, in this paper, a particle swarm optimization algorithm based on the ring neighborhood topology of Euclidean distance between particles is proposed, which is called the close neighbor mobility optimization algorithm. The algorithm mainly includes the following three strategies: elite selection mechanism, close neighbor mobility strategy and modified DE strategy. It mainly uses the Euclidean distance between particles. Each particle forms its own
unique niche, evolves in a local scope, and finally locates multiple global optimal solutions with high precision. The algorithm greatly improves the accuracy of the particle. The experimental results show that the close neighbor mobility optimization algorithm has better performance than most single-objective multi-modal algorithms
Period Cycle Optimization of Integrated Energy Systems with Long-Term Scheduling Consideration
The economy and energy saving effects of integrated energy system dispatch plans are influenced by the coupling of different energy devices. In order to consider the impact of changes in equipment load rates on the optimization and scheduling of the system under long-term operation, a method for energy and component cycle optimization considering energy device capacity and load has been proposed. By improving the initial parameters of the components, energy economic parameters, and operational optimization parameters, the system is subjected to long-term scheduling and multi-cycle operational optimization analysis to evaluate the energy saving and emission reduction potential as well as the economic feasibility of the system. Finally, through numerical analysis, the effectiveness of this optimization approach in achieving energy savings, emission reductions, and cost benefits for the system is validated. Furthermore, compared to existing optimization methods, this approach also assesses the economic feasibility of the system. The case study resulted in a pre-tax IRR of 23.14% and a pre-tax NPV of 66.38 million. It is inferred that the system could generate profits over a 10-year operation period, thereby offering a more rational and cost-effective scheduling scheme for the integrated energy system
Intelligent control strategy for industrial furnaces based on yield classification prediction using a gray relative correlation-convolutional neural network-multilayer perceptron (GCM) machine learning model
Industrial furnaces still play an important role in national economic growth. Owing to the complexity of the production process, the product yield fluctuates, and cannot be executed in real time, which has not kept pace with the development of the intelligent technologies in Industry 4.0. In this study, based on the deep learning theory and operational data collected from more than one year of actual production of a lime kiln, we proposed a hybrid deep network model combining a gray relative correlation, a convolutional neural network and a multilayer perceptron model (GCM) to categorize production processes and predict yield classifications. The results show that the loss and calculation time of the model based on the screened set of variables are significantly reduced, and the accuracy is almost unaffected; the GCM model has the best performance in predicting the yield classification of lime kilns. The intelligent control strategy for non-fault state is then set according to the predicted yield classification. Operating parameters are adjusted in a timely manner according to different priority control sequences to achieve higher yield, ensure high production efficiency, reduce unnecessary waste, and save energy
Numerical Investigation of Periodic Fluctuations in Energy Efficiency in Centrifugal Pumps at Different Working Points
In order to simulate the energy efficiency fluctuation behavior of an industrial centrifugal pump with a six-blade impeller, a full-scale three-dimensional (3D) an unsteady state computational fluid dynamics (CFD) model was used. Five operational points with different flow fluxes were numerically investigated by using the Navier–Stokes code with shear-stress transport (SST) k-ω turbulence model. The predicted performance curves agreed well with the test data. A sine function was fitted to the transient calculation results and the results show that the efficiency fluctuates mainly on the blade passing frequency, while the fluctuation level varies with flow rate. Furthermore, high efficiency is not necessarily associated with low fluctuation level. The efficiency fluctuation level is high at part-load points, and becomes relatively low when flow rate exceeds the design value. The effect of change in torque is greater than that of the head lift with respect to fluctuations of efficiency. Based upon the analysis of velocity vector distribution of different impeller phase positions, a hypothesis which considers both the effect of pump’s structural shape and flow fluxes was proposed to explain the above behavior by analyzing the impeller–tongue interaction. This work enriches the theoretical system of flow parameters fluctuation of centrifugal pump, and provides useful insight for the optimal design of centrifugal pumps
Effect of temperature on dielectric response in X-band of silicon nitride ceramics prepared by gelcasting
Due to the drastic aerodynamic heating effect in supersonic aircrafts, the operational performance of wave-transmitting dielectric ceramics functionalized radomes strongly depends on the temperature and oxidation. In this paper, the evolution of microwave dielectric responses in Si3N4 ceramics via gelcasting over a wide temperature range (25°C∼800°C) is investigated experimentally and theoretically. Specifically, the relative increment rate of real permittivity over evaluated temperature range is 4.46% at 8.2GHz and 8.67% at 12.4GHz, while the imaginary permittivity remains less than 0.06. Taking temperature-dependent polarized bound charge and damping coefficient into consideration, a revised dielectric relaxation model with Lorentz correction for Si3N4 ceramics has been established, which agrees well with evolution of experimental results. Furthermore, the best fitting results indicate that the activation energy of electrons Ea (15.46 ∼17.49 KJ/mol) is less than that of lattice Eb (33.29∼40.40 KJ/mol), which could be ascribed to the binding force between the electrons and nucleus is lower than covalent bonding force of lattice. Besides, excellent restorable feature of permittivity after heat-treatment lays a solid foundation for radome materials serviced in high temperature circumstances
OMNIDIRECTIONAL WIRELESS POWER TRANSFER SYSTEM WITH MULTIPLE RECEIVERS AND A SINGLE WIRE WOUND SPIRAL TRANSMITTER
Microwave Wireless Power Transfer System Based on a Frequency Reconfigurable Microstrip Patch Antenna Array
The microwave wireless power transfer (MWPT) technology has found a variety of applications in consumer electronics, medical implants and sensor networks. Here, instead of a magnetic resonant coupling wireless power transfer (MRCWPT) system, a novel MWPT system based on a frequency reconfigurable (covering the S-band and C-band) microstrip patch antenna array is proposed for the first time. By switching the bias voltage-dependent capacitance value of the varactor diode between the larger main microstrip patch and the smaller side microstrip patch, the working frequency band of the MWPT system can be switched between the S-band and the C-band. Specifically, the operated frequencies of the antenna array vary continuously within a wide range from 3.41 to 3.96 GHz and 5.7 to 6.3 GHz. For the adjustable range of frequencies, the return loss of the antenna array is less than −15 dB at the resonant frequency. The gain of the frequency reconfigurable antenna array is above 6 dBi at different working frequencies. Simulation results verified by experimental results have shown that power transfer efficiency (PTE) of the MWPT system stays above 20% at different frequencies. Also, when the antenna array works at the resonant frequency of 3.64 GHz, the PTE of the MWPT system is 25%, 20.5%, and 10.3% at the distances of 20 mm, 40 mm, and 80 mm, respectively. The MWPT system can be used to power the receiver at different frequencies, which has great application prospects and market demand opportunities
Microwave Wireless Power Transfer System Based on a Frequency Reconfigurable Microstrip Patch Antenna Array
The microwave wireless power transfer (MWPT) technology has found a variety of applications in consumer electronics, medical implants and sensor networks. Here, instead of a magnetic resonant coupling wireless power transfer (MRCWPT) system, a novel MWPT system based on a frequency reconfigurable (covering the S-band and C-band) microstrip patch antenna array is proposed for the first time. By switching the bias voltage-dependent capacitance value of the varactor diode between the larger main microstrip patch and the smaller side microstrip patch, the working frequency band of the MWPT system can be switched between the S-band and the C-band. Specifically, the operated frequencies of the antenna array vary continuously within a wide range from 3.41 to 3.96 GHz and 5.7 to 6.3 GHz. For the adjustable range of frequencies, the return loss of the antenna array is less than −15 dB at the resonant frequency. The gain of the frequency reconfigurable antenna array is above 6 dBi at different working frequencies. Simulation results verified by experimental results have shown that power transfer efficiency (PTE) of the MWPT system stays above 20% at different frequencies. Also, when the antenna array works at the resonant frequency of 3.64 GHz, the PTE of the MWPT system is 25%, 20.5%, and 10.3% at the distances of 20 mm, 40 mm, and 80 mm, respectively. The MWPT system can be used to power the receiver at different frequencies, which has great application prospects and market demand opportunities
Investigation and Practical Application of Silica Nanoparticles Composite Underwater Repairing Materials
Repairing materials are well-known to play an important role in rehabilitating and extending the service life for hydraulic concrete structures. However, current underwater repairing materials possess several problems, including insufficient bond tensile strength, inconsistency with the deformation of the old substrate, and insufficient underwater self-sealing ability. In the present paper, an experimental study was carried out to evaluate the influence of silica nanoparticles (SNs) on the properties of underwater composite-repairing materials. The underwater deformation, impermeability, bond tensile strength, and compressive strength of the SN-modified underwater composite-repairing materials were used as the properties’ evaluation indices. The results show that, within a certain range, the performance of the repairing material increase with increased SN percent. The deformability, impermeability grade, underwater bond tensile strength, and compressive strength of the SN-modified composite underwater repairing materials are 2.2%, 8, 2.91 MPa, and 115.87 MPa, respectively, when the mass ratio of the mortar, the curing agent and the SNs is 8:1:0.002. The proposed material is employed to repair the dam for a hydropower station in Guizhou province, China. Results show the seepage discharge is reduced by 8.6% when the dam is repaired. The annual average generating capacity is increased by 1.104 × 105 kWh. Meanwhile, CO2 and NOx emissions are reduced by 1.049 × 105 and 220.8 kg annually, respectively