Transmission line condition assessment technology based on multi-source Parameter Fusion

Aiming at the shortcomings of current transmission line state evaluation, which refers to the isolation of scalars and the low accuracy of evaluation methods, a transmission line state evaluation technology based on multi-source parameter fusion is proposed. This paper collects and selects characteristic data such as line test inspection information, operation and maintenance records, and power grid operating parameters as indicator quantities. The membership function is used to express the distribution state of the index quantity, and the distribution state is used as the data to establish a comprehensive evaluation model of the line operation state based on the long- and short-term memory network. The data tag is used to train the deep network to establish the mapping relationship between index parameters and operation state. Experiments show that the evaluation accuracy of the proposed method is significantly higher than that of the traditional shallow method, which can provide theoretical guidance for the operation and maintenance of overhead transmission lines.

Parallel Dislocation Model Implementation for Earthquake Source Parameter Estimation on Multi-Threaded GPU

Graphics processing units (GPUs) have been in the spotlight in various fields because they can process a massive amount of computation at a relatively low price. This research proposes a performance acceleration framework applied to Monte Carlo method-based earthquake source parameter estimation using multi-threaded compute unified device architecture (CUDA) GPU. The Monte Carlo method takes an exhaustive computational burden because iterative nonlinear optimization is performed more than 1000 times. To alleviate this problem, we parallelize the rectangular dislocation model, i.e., the Okada model, since the model consists of independent point-wise computations and takes up most of the time in the nonlinear optimization. Adjusting the degree of common subexpression elimination, thread block size, and constant caching, we obtained the best CUDA optimization configuration that achieves 134.94×, 14.00×, and 2.99× speedups over sequential CPU, 16-threads CPU, and baseline CUDA GPU implementation from the 1000×1000 mesh size, respectively. Then, we evaluated the performance and correctness of four different line search algorithms for the limited memory Broyden–Fletcher–Goldfarb–Shanno with boundaries (L-BFGS-B) optimization in the real earthquake dataset. The results demonstrated Armijo line search to be the most efficient one among the algorithms. The visualization results with the best-fit parameters finally derived by the proposed framework confirm that our framework also approximates the earthquake source parameters with an excellent agreement with the geodetic data, i.e., at most 0.5 cm root-mean-square-error (RMSE) of residual displacement.

The intelligent networks for double-diffusion and MHD analysis of thin film flow over a stretched surface

This study presents a novel application of soft-computing through intelligent, neural networks backpropagated by Levenberg–Marquardt scheme (NNs-BLMS) to solve the mathematical model of unsteady thin film flow of magnetized Maxwell fluid with thermo-diffusion effects and chemical reaction (TFFMFTDECR) over a horizontal rotating disk. The expression for thermophoretic velocity is accounted. Energy expression is deliberated with the addition of non-uniform heat source. The PDEs of mathematical model of TFFMFTDECR are transformed to ODEs by the application of similarity transformations. A dataset is generated through Adams method for the proposed NNs-BLMS in case of various scenarios of TFFMFTDECR model by variation of rotation parameter, magnetic parameter, space dependent heat sink/source parameter, temperature dependent heat sink/source parameter and chemical reaction controlling parameter. The designed computational solver NNs-BLMS is implemented by performing training, testing and validation for the solution of TFFMFTDECR system for different variants. Variation of various physical parameters are designed via plots and explain in details. It is depicted that thin film thickness increases for higher values of disk rotation parameter, while it diminishes for higher magnetic parameter. Furthermore, higher values of Dufour number and the corresponding diminishing values of Soret number causes enhancement in fluid temperature profile. Further the effectiveness of NNs-BLMS is validated by comparing the results of the proposed solver and the standard solution of TFFMFTDECR model through error analyses, histogram representations and regression analyses.

Implication of Bio-convective Marangoni flow of non-Newtonian material towards an infinite disk subject to exponential space-based heat source

In recent years, the research for enhanced thermal transportation is centered around the utilization of nanostructures to avail the prospective benefits in areas of biomedical, metallurgy, polymer processing, mechanical and electrical engineering applications, food processing, ventilation, heat storage devices, nuclear systems cooling, electronic devices, solar preoccupation, magnetic sticking, bioengineering applications, etc. The thermal aspects of nanoliquids and associated dynamics properties are still necessary to be explored. In this thermal contribution, the flow of Casson nanofluid configured by an infinite disk is analyzed. The significance of Marangoni flow with activation energy, thermal and exponential space-dependent heat source, nonlinear thermal radiation and Joule heating impacts is also incorporated. Similarly, variables are affianced to recast the governing flow expressions into highly coupled nonlinear ODEs. The numerical simulation for the prevailing model is elucidated by applying the bvp4cbuilt-in function of computational commercial software MATLAB. Consequences of sundry parameters, namely, magnetic parameter, Prandtl number, radiation parameter, exponential space-dependent heat source parameter, thermal-dependent heat source parameter, Eckert number, Dufour parameter, Soret number, Schmidt number, Marangoni number and Marangoni ratio parameter, mixed convection parameter, buoyancy ratio parameter, bioconvection Rayleigh number, activation energy parameter, thermophoresis parameter, Brownian motion parameter, bioconvection Lewis number, Peclet number microorganisms difference variable versus involved flow profiles like velocity, temperature, concentration of nanoparticles and microorganism field are obtained and displayed through graphs and tabular data.