scholarly journals Application of parametric modelling methods for estimating the parameters of damped sinusoidal signals

2017 ◽  
Vol 66 (4) ◽  
pp. 193-208
Author(s):  
Piotr Figoń
Keyword(s):  
Linear Prediction ◽  
Analytical Signal ◽  
Parametric Modelling ◽  
Deterministic Component ◽  
Sinusoidal Waveform ◽  
Sinusoidal Signals ◽  
Modelling Methods

The paper describes the results of analyses aimed at obtaining information on selected parameters of the deterministic component of a signal being the sum of two waveforms, an exponentially damped sinusoidal waveform and a stochastic waveform. Keywords: linear prediction, optimisation, analytical signal

scholarly journals A survey of parametric modelling methods for designing the head of a high-speed train

2018 ◽  
Vol 232 (7) ◽  
pp. 1965-1983 ◽  
Author(s):  
Ruibin Wang ◽  
Jianjun Zhang ◽  
Shaojun Bian ◽  
Lihuan You
Keyword(s):  
High Speed ◽  
Aerodynamic Performance ◽  
Parametric Modelling ◽  
High Speed Train ◽  
Head Shape ◽  
Local Shape ◽  
Advantages And Disadvantages ◽  
Design Variables ◽  
Simulation Results ◽  
Modelling Methods

With the continuous increase of the running speed, the head shape of a high-speed train turns out to be the critical factor to boost the speed further. In order to reduce the time required to design the head of a high-speed train and to improve the modelling efficiency, various parametric modelling methods have been widely applied in the optimization design of the head of a high-speed train to obtain an optimal head shape so that the aerodynamic effect acting on the head of a high-speed train can be reduced and more energy can be saved. This paper reviews these parametric modelling methods and classifies them into four categories: two-dimensional, three-dimensional, CATIA-based, and mesh deformation-based parametric modelling methods. Each of the methods is introduced, and the advantages and disadvantages of these methods are identified. The simulation results are presented to demonstrate that the aerodynamic performance of the optimal models constructed by these parametric modelling methods has been improved when compared with the numerical calculation results of the original models or the prototype models of running trains. Since different parametric modelling methods used different original models and optimization methods, few publications could be found which compare the simulation results of the aerodynamic performance among different parametric modelling methods. In spite of this, these parametric modelling methods indicate that more local shape details will lead to more accurate simulation results, and fewer design variables will result in higher computational efficiency. Therefore, the ability of describing more local shape details with fewer design variables could serve as a main specification to assess the performance of various parametric modelling methods. The future research directions may concentrate on how to improve such ability.

Non-linear modelling of a novel gas strut

2005 ◽  
Vol 219 (10) ◽  
pp. 1153-1164 ◽  
Author(s):  
B Gao ◽  
J Darling ◽  
D G Tilley ◽  
R A Williams ◽  
A Bean ◽  
...  
Keyword(s):  
Vehicle Suspension ◽  
Polytropic Index ◽  
Parametric Modelling ◽  
Nonlinear Characteristics ◽  
Highly Nonlinear ◽  
Linear Modelling ◽  
Non Linear ◽  
Vehicle Suspension System ◽  
Modelling Methods ◽  
Good Agreement

The strut is one of the most important components in a vehicle suspension system; however, it is also one of the most difficult elements to model owing to its highly nonlinear characteristics. In this paper a non-linear gas strut model built in the software package Bath fp is presented. Both analytical and parametric modelling methods were used in the representation of different components in the strut. Simulations at various frequencies showed good agreement with experimental results. A sensitivity analysis of strut performance is presented at the end of the paper. It was found that the damper valve characteristics, the rod diameter, the temperature, and the user-defined polytropic index significantly affect the strut performance.

Economic benefit of shale gas exploitation based on back propagation neural network

2020 ◽  
Vol 39 (6) ◽  
pp. 8823-8830
Author(s):  
Jiafeng Li ◽  
Hui Hu ◽  
Xiang Li ◽  
Qian Jin ◽  
Tianhao Huang
Keyword(s):  
Neural Network ◽  
Shale Gas ◽  
Bp Neural Network ◽  
Large Scale ◽  
Linear Prediction ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Economic Benefits ◽  
Gas Well ◽  
Well Production

Under the influence of COVID-19, the economic benefits of shale gas development are greatly affected. With the large-scale development and utilization of shale gas in China, it is increasingly important to assess the economic impact of shale gas development. Therefore, this paper proposes a method for predicting the production of shale gas reservoirs, and uses back propagation (BP) neural network to nonlinearly fit reservoir reconstruction data to obtain shale gas well production forecasting models. Experiments show that compared with the traditional BP neural network, the proposed method can effectively improve the accuracy and stability of the prediction. There is a nonlinear correlation between reservoir reconstruction data and gas well production, which does not apply to traditional linear prediction methods

Dc arc emission analysis of rare earth metals and their oxides with sorption preconcentration of impurities

2018 ◽  
Vol 84 (11) ◽  
pp. 9-14
Author(s):  
E. S. Koshel ◽  
V. B. Baranovskaya ◽  
M. S. Doronina
Keyword(s):  
Rare Earth ◽  
Rare Earth Metals ◽  
Analytical Signal ◽  
Graphite Powder ◽  
Atomic Emission ◽  
Standard Samples ◽  
Emission Analysis ◽  
Sorption Preconcentration ◽  
Sample Shape

The analytical capabilities of arc atomic emission determination of As, Bi, Sb, Cu, Te in rare earth metals (REM) and their oxides after preparatory group concentration using S,N-containing heterochain polymer sorbent are studied on a high-resolution spectrometer “Grand- Extra” (“WMC-Optoelectron-ics” company, Russia). Sorption kinetics and dependence of the degree of the impurity extraction on the solution acidity are analyzed to specify conditions of sorption concentration. To optimize the procedure of arc atomic emission determination of As, Bi, Sb, Cu, and Te various schemes of their sorption preconcentration and subsequent processing of the resulted concentrate with the addition of a collector at different stages of the sorption process have been considered. Graphite powder is used as a collector in analysis of rare earth oxides due to universality and relative simplicity of the emission spectrum. Conditions of analysis and parameters of the spectrometer that affect the analytical signal (mass and composition of the sample, shape and size of the electrodes, current intensity and generator operation mode, interelectrode spacing, wavelengths of the analytical lines) are chosen. The evaporation curves of the determinable impurities were studied and the exposure time of As, Bi, Sb, Cu, and Te in the resulted sorption concentrate was determined. Correctness of the obtained results was evaluated using standard samples of the composition and in comparisons between methods. The results of the study are used to develop a method of arc chemical-atomic emission analysis of yttrium, gadolinium, neodymium, europium, scandium and their oxides in a concentration range of n x (10-2 - 10-5) wt.%.

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