Relevant bibliographies by topics / Rayleigh Model; Genetic Algorithm; SPRT

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Academic literature on the topic 'Rayleigh Model; Genetic Algorithm; SPRT'

Author: Grafiati
Published: 3 June 2025
Last updated: 6 July 2025

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Journal articles on the topic "Rayleigh Model; Genetic Algorithm; SPRT"

1

Dr., R.Satyaprasad1, Kiran2 Ch.Surya, and G.Krishna Mohan3 Dr. "MODIFIED GENETIC ALGORITHM BASED SOFTWARE RELIABILITY USING SPRT: RAYLEIGH MODEL." International Journal of Engineering Technologies and Management Research 5, no. 4 (2018): 17–25. https://doi.org/10.5281/zenodo.1244675.

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In Classical Hypothesis testing volumes of data is to be collected and then the conclusions are drawn, which may need more time. But, Sequential Analysis of Statistical science could be adopted in order to decide upon the reliability or unreliability of the developed software very quickly. The procedure adopted for this is, Sequential Probability Ratio Test (SPRT). It is designed for continuous monitoring. The likelihood based SPRT proposed by Wald is very general and it can be used for many different probability distributions. In the present paper we propose the performance of SPRT on 6 data sets of Time domain data using Rayleigh model and analyzed the results. The parameters are estimated using Modified Genetic Algorithm.
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Satyaprasad, R., Surya Kiran, and G. Krishna Mohan. "MODIFIED GENETIC ALGORITHM BASED SOFTWARE RELIABILITY USING SPRT: RAYLEIGH MODEL." International Journal of Engineering Technologies and Management Research 5, no. 4 (2020): 17–25. http://dx.doi.org/10.29121/ijetmr.v5.i4.2018.204.

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In Classical Hypothesis testing volumes of data is to be collected and then the conclusions are drawn, which may need more time. But, Sequential Analysis of Statistical science could be adopted in order to decide upon the reliability or unreliability of the developed software very quickly. The procedure adopted for this is, Sequential Probability Ratio Test (SPRT). It is designed for continuous monitoring. The likelihood based SPRT proposed by Wald is very general and it can be used for many different probability distributions. In the present paper we propose the performance of SPRT on 6 data sets of Time domain data using Rayleigh model and analyzed the results. The parameters are estimated using Modified Genetic Algorithm.
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K, Joseph Shibu, K. Shankar, Ch Kanna Babu, and Girish K. Degaonkar. "Multi-objective optimisation of a small aircraft turbine engine rotor system with self-updating Rayleigh damping model and frequency-dependent bearing-pedestal model." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, no. 16 (2019): 5710–23. http://dx.doi.org/10.1177/0954406219851531.

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A self-updating Rayleigh damping model and frequency-dependent bearing-pedestal model for multi-objective optimisation is presented through this paper and is applied for a small turbine engine rotor system for aircraft application. This engine is used as an auxiliary power unit on aircraft. The Rayleigh damping model and frequency-dependent bearing pedestal model are verified by carrying out experiments on this auxiliary power unit rotor system. The novel self-updating feature calculates the Rayleigh damping coefficients and frequency-dependent bearing-pedestal stiffness for each chromosome and modifies rotor system equation of motion for computing the objectives during multi-objective optimisation for each chromosome. This novel model is used for multi-objective optimisation of auxiliary power unit rotor system. The unbalance response and weight are minimised subjected to critical speed constraint. Controlled elitist genetic algorithm is used for the optimisation resulting in Pareto optimal solutions and the acceptable solution is identified as the solution close to Utopia point. The results are compared with the constant Rayleigh damping model. The new model has produced an accurate optimum solution superior to constant Rayleigh damping model.
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Xing, Zhen, and Alfredo Mazzotti. "Two-grid full-waveform Rayleigh-wave inversion via a genetic algorithm — Part 1: Method and synthetic examples." GEOPHYSICS 84, no. 5 (2019): R805—R814. http://dx.doi.org/10.1190/geo2018-0799.1.

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When reliable a priori information is not available, it is difficult to correctly predict near-surface S-wave velocity models from Rayleigh waves through existing techniques, especially in the case of complex geology. To tackle this issue, we have developed a new method: two-grid genetic-algorithm Rayleigh-wave full-waveform inversion (FWI). Adopting a two-grid parameterization of the model, the genetic algorithm inverts for unknown velocities and densities at the nodes of a coarse grid, whereas the forward modeling is performed on a fine grid to avoid numerical dispersion. A bilinear interpolation brings the coarse-grid results into the fine-grid models. The coarse inversion grid allows for a significant reduction in the computing time required by the genetic algorithm to converge. With a coarser grid, there are fewer unknowns and less required computing time, at the expense of the model resolution. To further increase efficiency, our inversion code can perform the optimization using an offset-marching strategy and/or a frequency-marching strategy that can make use of different kinds of objective functions and allows for parallel computing. We illustrate the effect of our inversion method using three synthetic examples with rather complex near-surface models. Although no a priori information was used in all three tests, the long-wavelength structures of the reference models were fairly predicted, and satisfactory matches between “observed” and predicted data were achieved. The fair predictions of the reference models suggest that the final models estimated by our genetic-algorithm FWI, which we call macromodels, would be suitable inputs to gradient-based Rayleigh-wave FWI for further refinement. We also explored other issues related to the practical use of the method in different work and explored applications of the method to field data.
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Nagai, K., A. O'Neill, Y. Sanada, and Y. Ashida. "Genetic Algorithm Inversion of Rayleigh Wave Dispersion from CMPCC Gathers Over a Shallow Fault Model." Journal of Environmental & Engineering Geophysics 10, no. 3 (2005): 275–86. http://dx.doi.org/10.2113/jeeg10.3.275.

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Wirawan, Rezki, Jamhir Safani, and Al Rubaiyn. "Multiple inversions of Rayleigh wave dispersion curve for geotechnical site characterization using particle swarm optimization dan genetic algorithm." Journal of Physics: Theories and Applications 7, no. 2 (2023): 201. http://dx.doi.org/10.20961/jphystheor-appl.v7i2.79065.

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The inversion of the Rayleigh wave dispersion curve is a crucial step in the multi-channel analysis of surface waves (MASW) method, used to obtain the shear wave velocity (<em>Vs</em>) profile. The nonlinear and multimodal nature of the dispersion curve makes a global optimization approach, such as particle swarm optimization (PSO) and genetic algorithm (GA), the optimal choice for inversion. This study aims to compare the performance of multiple inversions of PSO (MI-PSO) and multiple inversions of GA (MI-GA) in solving the inversion problem of the Rayleigh wave dispersion curve. The test results indicate that the utilized MI-PSO outperforms MI-GA in terms of computational time and accuracy of the obtained model
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Zhang, Jian Lin, Zhi Hong, Qian Lin, and Jie Sheng Jiang. "A Mixed Control System of 3D High Rise Benchmark Building Model Based on Genetic Algorithm." Advanced Materials Research 163-167 (December 2010): 2862–67. http://dx.doi.org/10.4028/www.scientific.net/amr.163-167.2862.

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In the former research, the Damper control system, TMD control system and the Mixed Control of the active control and passive control were all optimized alone. It is found that less research of the optimization is on the Mixed Control of the Damper system and TMD system. In order to achieve better control effect, we venture to propose a Mixed Control system of third-generation three-dimensional 20-storey Benchmark model under the multi-directional earthquake in this paper. By means of Rayleigh damping and D-value, dynamic equations including the damping matrixes, stiffness matrixes of the structure are obtained. Then in the process of the optimization, the displacement reducing coefficient (DRF) is used as the objective function to optimize the placement of damping devices and control parameters based on Genetic Algorithm (GA). Numerical results in this paper show that the optimal design method proposed in this paper is effective and flexible. It can obviously reduce the seismic responses of building structure.
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Łabędzki, Paweł. "Fractional Kelvin–Voigt Model for Beam Vibrations: Numerical Simulations and Approximation Using a Classical Model." Electronics 14, no. 10 (2025): 1918. https://doi.org/10.3390/electronics14101918.

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In this study, a cantilever beam with a tip mass under base excitation was analyzed, with system damping modeled using a fractional derivative approach. By applying the Rayleigh–Ritz method, the governing equation was decomposed into spatial and temporal components. Analytical solutions for the temporal equation were derived; however, their complexity posed challenges for practical application. To address this, convergence acceleration techniques were employed to efficiently evaluate slowly converging series representations. Additionally, two methods for identifying the parameters of a classical model approximating the fractional system were investigated: a geometric approach based on waveform shape analysis and an optimization procedure utilizing a genetic algorithm. The identified harmonic oscillator reproduced the dynamic response of the fractional model with an average relative error typically below 5% for off-resonance excitation. Overall, the study presents a robust analytical framework for solving fractional-order vibration problems and demonstrates effective strategies for their approximation using classical harmonic models.
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Song, Zhenghong, Xiangfang Zeng, and Clifford H. Thurber. "Surface-wave dispersion spectrum inversion method applied to Love and Rayleigh waves recorded by distributed acoustic sensing." GEOPHYSICS 86, no. 1 (2021): EN1—EN12. http://dx.doi.org/10.1190/geo2019-0691.1.

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Recently, distributed acoustic sensing (DAS) has been applied to shallow seismic structure imaging providing dense spatial sampling at a relatively low cost. DAS on a standard straight fiber-optic cable mostly records axial dynamic strain, which makes it difficult to separate the Rayleigh and Love wavefields. As a result, the mixed Rayleigh and Love wave signals cannot be used in the conventional surface-wave dispersion inversion method. Therefore, it is often ensured that the source and the cable are in the same line and only Rayleigh wave dispersion is used, which limits the constraints on structure and model resolution. We have inverted surface-wave dispersion spectra instead of dispersion curves. This inversion method can use mixed Rayleigh and Love waves recorded when the source and receiver array are not aligned. The multiple-channel records are transformed to the frequency domain, and a slant stack method is used to construct the dispersion spectra. The genetic algorithm method is used to obtain an optimal S-wave velocity model that minimizes the difference between theoretical and observed dispersion spectra. A series of synthetic tests are conducted to validate our method. The results suggest that our method not only improves the flexibility of the acquisition system design, but the Love wave data also provide additional constraints on the structure. Our method is applied to the active source and ambient noise data sets acquired at a geothermal site and provides consistent results for different data sets and acquisition geometries. The sensitivity of the dispersion spectra to layer thickness, density, and P-wave velocity is also discussed. With our method, the amount of usable data can be increased, helping deliver better subsurface images.
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Xing, Zhen, and Alfredo Mazzotti. "Two-grid full-waveform Rayleigh-wave inversion via a genetic algorithm — Part 2: Application to two actual data sets." GEOPHYSICS 84, no. 5 (2019): R815—R825. http://dx.doi.org/10.1190/geo2018-0800.1.

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We have applied our two-grid genetic-algorithm Rayleigh-wave full-waveform inversion (FWI) to two actual data sets acquired in Luni (Italy) and Grenoble (France), respectively. Because our technique used 2D elastic finite-difference modeling for solving the forward problem, the observed data were 3D to 2D corrected prior to the inversion. To limit the computing time, both inversions focused on predicting low-resolution, smooth models by using quite coarse inversion grids. The wavelets for FWI were estimated directly from the observed data by using the Wiener method. In the Luni case, due to the strong dispersion effects on the data, to strengthen the inversion, envelopes and waveforms were considered in the objective function and an offset-marching strategy was applied. Though no a priori information was exploited, the outcomes of the Luni and Grenoble data inversion were fair. The predicted Luni [Formula: see text] model indicates a strong velocity increase from approximately 3 to 6 m, and velocity inversions have been detected at approximately 2 and 9 m depths. Analyzing the dispersion spectra, it results that the predicted Luni data reasonably reproduced the waveforms related to the fundamental mode and, likely, a small part of those related to the first higher mode. Concerning the Grenoble example, the predicted [Formula: see text] model coincides reasonably well with the long-wavelength structures presented in the [Formula: see text] profiles obtained from nearby boreholes. The data reconstruction is generally satisfactory, and when mismatches occur between the predicted and observed traces, the phase differences are always within half-periods. The fair inversion outcomes suggest that the predicted Luni and Grenoble models would likely be adequate initial models for local FWI, which could further increase the resolution and the details of the estimated [Formula: see text] models.
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Conference papers on the topic "Rayleigh Model; Genetic Algorithm; SPRT"

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Shibu Kalloor, Joseph, Ch Kanna Babu, Girish K. Degaonkar, and K. Shankar. "Multi Objective Optimisation of an Aero Engine Rotor System Using Nondominated Sorting Genetic Algorithm (NSGA)." In ASME 2017 Gas Turbine India Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gtindia2017-4681.

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A comprehensive multi-objective optimisation methodology is presented and applied to a practical aero engine rotor system. A variant of Nondominated Sorting Genetic Algorithm (NSGA) is employed to simultaneously minimise the weight and unbalance response of the rotor system with restriction imposed on critical speed. Rayleigh beam is used in Finite Element Method (FEM) implemented in-house developed MATLAB code for analysis. The results of practical interest are achieved through bearing-pedestal model and eigenvalue based Rayleigh damping model. Pareto optimal solutions generated and best solution selected with the help of response surface approximation of the Pareto optimal front. The outcome of the paper is a minimum weight and minimum unbalance response rotor system which satisfied the critical speed constraints.
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Arif, Tariq M., and Zhiming Ji. "A Fast Estimation Model for Angular Spectrum Based Focused Ultrasound Wave Simulation in Layered Tissue Media." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11088.

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Abstract High-Intensity Focused Ultrasound (HIFU) is a popular non-invasive therapeutic tool and widely used in many clinical settings. The simulation models used for HIFU responses are computationally expensive and time-consuming. Among many numerical HIFU simulation methods, the Rayleigh-Sommerfeld approach is considered to be a reliable one. However, Rayleigh-Sommerfeld is suitable for homogeneous medium, and for a heterogeneous media, many approximations should be made in order to reduce the calculation time. In this study, we propose a fast methodology for estimating focused ultrasound pressure-temperature field responses through layered tissue media. A computationally efficient nonlinear angular spectrum-based method that can address the effects of varying attenuations, reflections and refractions from tissue layers is implemented to calculate reference datasets. From the simulation datasets, a profile function coupled with a GUI code is constructed for estimating the pressure-temperature response by using a Gaussian function and a Genetic Algorithm. The HIFU response model illustrated in this study can be advantageous and time-effective when multiple simulations are required on a similar complex patient model, and it can be used to guide and reduce the sets of simulations required for planning HIFU treatment.
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De Giorgi, Maria Grazia, Pietro Marco Congedo, Maria Giovanna Rodio, and Antonio Ficarella. "Shape Optimization for Cryogenic Cavitating Flows Past an Isolated Hydrofoil." In ASME 2008 Fluids Engineering Division Summer Meeting collocated with the Heat Transfer, Energy Sustainability, and 3rd Energy Nanotechnology Conferences. ASMEDC, 2008. http://dx.doi.org/10.1115/fedsm2008-55119.

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The aim of this paper is shape optimization of a cryogenic flow past an isolated hydrofoil in order to reduce the cavitation. The numerical simulation of cavitating flows has been performed by way of the commercially available code Fluent (release 6.3), implementing a cavitation model by using external routines. The model is based on a simplified Rayleigh-Plesset equation, and takes into account both nucleation and thermal effects. This study has been divided in two parts. Firstly the cavitation model has been validated by comparison with experimental data, in particular, water cavitation on a NACA0015 airfoil and hydrogen cavitating flow over an external profile. Secondly, Fluent has been coupled with a multi-objective genetic algorithm (MOGA). Genetic algorithms have proved their interest with respect to gradient-based methods because of their high flexibility, and also because of their ability to find global optima of multi-modal problem. The representation of the design space has been previously investigated through a Design of Experiment (DOE) procedure. A shape optimization of an hydrofoil has been computed in order to minimize the vapor volume in different operating conditions.
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Huang, Renfang, Xianwu Luo, Zhihong Zhai, and Jiajian Zhou. "Design Optimization of a Mixed Flow Waterjet Pump for Performance Improvement Involving Cavitation." In ASME/JSME/KSME 2015 Joint Fluids Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/ajkfluids2015-02115.

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A mixed-flow waterjet pump with a vaneless diffuser is treated to improve its hydraulic efficiency as well as cavitation performance. In order to conduct the design optimization, the authors apply a multiobjective strategy combined with design of experiments (DOE), computational fluid dynamics (CFD), inverse design method, surface response method (RSM) and non-dominated sorting genetic algorithm-II (NSGA-II). The hydraulic efficiency and the total vapor volume are selected as the optimization targets, and nine parameters are used to describe the blade shape with the same meridional section. For numerical simulation, RANS method is applied with SST k-ω turbulence model and a mass transfer cavitation model based on the Rayleigh-Plesset equation. Optimal Latin hypercube design method is used in the design of experiments to uniformly sample in variation ranges and global optimization is then conducted by using non-dominated sorting genetic algorithm-II (NSGA-II) based on the input-target approximation functions built by the response surface model (RSM). The optimization results demonstrate that both hydraulic efficiency and cavitation performance are improved at the design point through this multiobjective strategy. Based on analysis of the internal flows, secondary flows would be important contributor to the hydraulic loss as well as the nonuniform flow at impeller exit, and can be suppressed by adjusting the blade load along the hub or shroud by using the inverse design method.
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