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Relevant bibliographies by topics / INVERSION-COMPRESSION METHOD

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Journal articles

Academic literature on the topic 'INVERSION-COMPRESSION METHOD'

Author: Grafiati

Published: 11 September 2023

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Journal articles on the topic "INVERSION-COMPRESSION METHOD"

1

Li, Shouju, De Li, Lijuan Cao, and Zichang Shangguan. "Parameter estimation approach for particle flow model of rockfill materials using response surface method." International Journal of Computational Materials Science and Engineering 04, no. 01 (2015): 1550003. http://dx.doi.org/10.1142/s2047684115500037.

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Particle flow code (PFC) is widely used to model deformation and stress states of rockfill materials. The accuracy of numerical modeling with PFC is dependent upon the model parameter values. How to accurately determine model parameters remains one of the main challenges. In order to determine model parameters of particle flow model of rockfill materials, some triaxial compression experiments are performed, and the inversion procedure of model parameters based on response surface method is proposed. Parameters of particle flow model of rockfill materials are determined according to the observe

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2

Chen, Dai Heng, and Lu Yang. "Inversion Behavior for Cylindrical Tubes under Axial Compression." Advanced Materials Research 430-432 (January 2012): 512–16. http://dx.doi.org/10.4028/www.scientific.net/amr.430-432.512.

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This paper presents an analysis of tube inversion under axial compression by a finite element method with the aim of expressing and calculating the axial stress from the stress equilibrium equation. The state of a cylinder under internal stress and the inversion transformation mechanism are then clarified, and verification of the proposed theoretical model is examined.

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3

Habashy, T. M., A. Abubakar, G. Pan, and A. Belani. "Source-receiver compression scheme for full-waveform seismic inversion." GEOPHYSICS 76, no. 4 (2011): R95—R108. http://dx.doi.org/10.1190/1.3590213.

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We have developed a source-receiver compression approach for reducing the computational time and memory usage of the acoustic and elastic full-waveform inversions. By detecting and quantifying the extent of redundancy in the data, we assembled a reduced set of simultaneous sources and receivers that are weighted sums of the physical sources and receivers used in the survey. Because the numbers of these simultaneous sources and receivers could be significantly less than those of the physical sources and receivers, the computational time and memory usage of any gradient-type inversion method suc

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4

Foks, Nathan Leon, Richard Krahenbuhl, and Yaoguo Li. "Adaptive sampling of potential-field data: A direct approach to compressive inversion." GEOPHYSICS 79, no. 1 (2014): IM1—IM9. http://dx.doi.org/10.1190/geo2013-0087.1.

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Compressive inversion uses computational algorithms that decrease the time and storage needs of a traditional inverse problem. Most compression approaches focus on the model domain, and very few, other than traditional downsampling focus on the data domain for potential-field applications. To further the compression in the data domain, a direct and practical approach to the adaptive downsampling of potential-field data for large inversion problems has been developed. The approach is formulated to significantly reduce the quantity of data in relatively smooth or quiet regions of the data set, w

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5

Portniaguine, Oleg, and Michael S. Zhdanov. "3‐D magnetic inversion with data compression and image focusing." GEOPHYSICS 67, no. 5 (2002): 1532–41. http://dx.doi.org/10.1190/1.1512749.

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We develop a method of 3‐D magnetic anomaly inversion based on traditional Tikhonov regularization theory. We use a minimum support stabilizing functional to generate a sharp, focused inverse image. An iterative inversion process is constructed in the space of weighted model parameters that accelerates the convergence and robustness of the method. The weighting functions are selected based on sensitivity analysis. To speed up the computations and to decrease the size of memory required, we use a compression technique based on cubic interpolation. Our method is designed for inversion of total m

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6

Pan, Shiyang, Tongchun Li, Guicai Shi, Zhen Cui, Hanjing Zhang, and Li Yuan. "The Inversion Analysis and Material Parameter Optimization of a High Earth-Rockfill Dam during Construction Periods." Applied Sciences 12, no. 10 (2022): 4991. http://dx.doi.org/10.3390/app12104991.

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Inversion analysis is usually an efficient solution to process the monitoring data of earth-rockfill dams. However, it is still difficult to obtain calculation results that are consistent with monitoring data due to different construction statuses. To deal with this situation and to introduce a new solution to improve calculation accuracy, the general method of inversion analysis based on back-propagation neural networks and the original step-by-step inversion method assuming that the parameters of the constitutive model vary with construction periods are introduced and verified in this work.

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7

Lin, Cherng-Yuan, and Keng-Hung Lin. "Comparison of the Engine Performance of Soybean Oil Biodiesel Emulsions Prepared by Phase Inversion Temperature and Mechanical Homogenization Methods." Processes 11, no. 3 (2023): 907. http://dx.doi.org/10.3390/pr11030907.

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The engine performance and emission characteristics of burning emulsions of soybean oil biodiesel in a compression-ignition diesel engine prepared through the phase inversion temperature method were compared with those of neat soybean oil biodiesel and the emulsion prepared by the mechanical homogenization method. The engine torque was set constantly at 98 N·m with varying engine speeds. The experimental results show that the emulsion prepared by the method of phase inversion temperature had higher O2 and NOx emissions, a higher excess air ratio, a higher exhaust gas temperature, and a higher

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8

Jiang, Dandan, Zhaofa Zeng, Shuai Zhou, Yanwu Guan, Tao Lin, and Pengyu Lu. "Three-Dimensional Magnetic Inversion Based on an Adaptive Quadtree Data Compression." Applied Sciences 10, no. 21 (2020): 7636. http://dx.doi.org/10.3390/app10217636.

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Three-dimensional magnetic inversion allows the distribution of magnetic parameters to be obtained, and it is an important tool for geological exploration and interpretation. However, because of the redundancy of the data obtained from large-scale investigations or high-density sampling, it is very computationally intensive to use these data for iterative inversion calculations. In this paper, we propose a method for compressing magnetic data by using an adaptive quadtree decomposition method, which divides the two-dimensional data region into four quadrants and progressively subdivides them b

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9

Liu, Weiqiang, and Liangyong Yang. "A New Method for Geophysical Induced Polarization Inversion Based on Stochastic Medium Model and Sample-Compressed Artificial Neural Network." Journal of Physics: Conference Series 2025, no. 1 (2021): 012010. http://dx.doi.org/10.1088/1742-6596/2025/1/012010.

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Abstract Induced polarization (IP) is a near-surface geophysical exploration method. Inverting the electrical properties of the underground medium from surface apparent IP parameters is a highly nonlinear problem. To further improve the accuracy, the artificial neural network (ANN) algorithm is applied to the two-dimensional (2D) IP data inversion for the first time. We firstly produced smooth geo-electric models based on the stochastic medium theory, and obtained the corresponding theoretical responses through forward modelling. Then, we compressed the responses and models through image compr

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10

Abubakar, A., T. M. Habashy, Y. Lin, and M. Li. "A model-compression scheme for nonlinear electromagnetic inversions." GEOPHYSICS 77, no. 5 (2012): E379—E389. http://dx.doi.org/10.1190/geo2011-0494.1.

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We have developed a model-compression scheme for improving the efficiency of the regularized Gauss-Newton inversion algorithm for marine controlled-source electromagnetic applications. In this scheme, the unknown model parameters (the conductivity/resistivity distribution) are represented in terms of a basis such as Fourier and wavelet (Haar and Daubechies). By applying a truncation criterion, the model may then be approximated by a reduced number of basis functions, which is usually much less than the number of the model parameters. Further, because the controlled-source electromagnetic measu

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