scholarly journals Musical variations from a chaotic mapping

1996 ◽  
Vol 6 (2) ◽  
pp. 95-107 ◽  
Author(s):  
Diana S. Dabby
Keyword(s):  
Chaotic Mapping ◽  
Musical Variations

scholarly journals Optimal design to control rotor shaft vibrations and thermal management on a supercritical CO2 microturbine

2021 ◽  
Vol 22 ◽  
pp. 22
Author(s):  
Jun Li ◽  
Hal Gurgenci ◽  
Jishun Li ◽  
Lun Li ◽  
Zhiqiang Guan ◽  
...  
Keyword(s):  
Boundary Condition ◽  
Mass Flow Rate ◽  
Mass Flow ◽  
Flow Rate ◽  
Jet Impingement ◽  
Brayton Cycle ◽  
Cooling Device ◽  
Resonance Amplitude ◽  
Chaotic Mapping ◽  
The Given

Supercritical carbon dioxide (SCO2) Brayton cycle microturbine can be used for the next generation of solar power. In order to comprehensively optimize the supporting system and cooling device parameters of Brayton cycle shafting, the concept of chaos interval is introduced by chaotic mapping, and the CIMPSO algorithm is proposed to optimize the multi-objective rotor system model with nonlinear variables.The results show that the resonance amplitude of the optimized model is effectively attenuated, and the critical speed point is far away from the working speed, which shows the robustness of the optimization algorithm. Finally, based on arbitrary several sets of optimization solutions and empirical parameters, the finite element model of shafting is established for simulation, and the results show that the optimized solution has certain guiding significance for the design of the rotor system.The cooling device is designed and simulated by CFD method based on the optimal solution set. Both the inlet boundary conditions of given pressure (1 MPα) and given mass flow rate (0.1 kg/s) numerical calculations were carried out to characterize the cooling performance, for different jet impingement configurations (Hr/din = 0.0125 ∼ 5).Several sets of analyses show the strong effects of the jet-to-target spacing (Hr/din) on the rotor thermal performance at a given diameter (din) of the nozzle. Average temperature (Tc) at the free end of the rotor show that, as jet-to-target distance decreases (0.0125 ≤ Hr/din ≤ 0.33), the heat dissipation efficiency of the cooling device with the given pressure boundary condition tends to decrease, while the conclusion is opposite when the inlet boundary condition is set to the given mass flow rate. And there is an interval for the optimal combination (Hr/din) to promote the cooling efficiency.

scholarly journals A Power Load Forecasting Model Based on FA-CSSA-ELM

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zuoxun Wang ◽  
Xinheng Wang ◽  
Chunrui Ma ◽  
Zengxu Song
Keyword(s):  
Search Algorithm ◽  
Load Forecasting ◽  
Local Optimum ◽  
Chaotic Mapping ◽  
Forecasting Models ◽  
Power Resources ◽  
Power Load ◽  
Power Load Forecasting ◽  
Learning Machine ◽  
Grid Operation

Accurate and stable power load forecasting methods are essential for the rational allocation of power resources and grid operation. Due to the nonlinear nature of power loads, it is difficult for a single forecasting method to complete the forecasting task accurately and quickly. In this study, a new combined model for power loads forecasting is proposed. The initial weights and thresholds of the extreme learning machine (ELM) optimized by the chaotic sparrow search algorithm (CSSA) and improved by the firefly algorithm (FA) are used to improve the forecasting performance and achieve accurate forecasting. The early local optimum that exists in the sparrow algorithm is overcome by Tent chaotic mapping. A firefly perturbation strategy is used to improve the global optimization capability of the model. Real values from a power grid in Shandong are used to validate the prediction performance of the proposed FA-CSSA-ELM model. Experiments show that the proposed model produces more accurate forecasting results than other single forecasting models or combined forecasting models.

scholarly journals Early bearing fault diagnosis based on improved SFLA and ELM network

2018 ◽  
Vol 42 (2) ◽  
pp. 187-193 ◽  
Author(s):  
Jingwen Xu ◽  
Yunxuan Zhang ◽  
Ziqi Yin
Keyword(s):  
Neural Networks ◽  
Fault Diagnosis ◽  
Single Layer ◽  
Shuffled Frog Leaping Algorithm ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Chaotic Mapping ◽  
New Type ◽  
Shuffled Frog Leaping ◽  
Learning Machine

In this paper, an extreme learning machine (ELM) network based on an improved shuffled frog leaping algorithm (CCSFLA) is applied in early bearing fault diagnosis. ELM is a new type of single layer forward network. Although the generalization is stronger compared with traditional neural networks, a random setup of initial parameters increases instability of the network. An improved SFLA based on sinusoidal chaotic mapping with infinite collapses and constriction factors (CCSFLA) is proposed in this paper to optimize the ELM and obtain a CCSFLA–ELM model. Results show that the CCSFLA–ELM model can be used for optimization and that it improved the recognition of early bearing fault diagnosis.

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