A Hybrid Dung Beetle Optimization Algorithm with Simulated Annealing for the Numerical Modeling of Asymmetric Wave Equations

IF 0.7 4区 地球科学 Q4 GEOCHEMISTRY & GEOPHYSICS Applied Geophysics Pub Date : 2023-12-14 DOI:10.1007/s11770-024-1039-1
Xu-ruo Wei, Wen-lei Bai, Lu Liu, You-ming Li, Zhi-yang Wang
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Abstract

In the generalized continuum mechanics (GCM) theory framework, asymmetric wave equations encompass the characteristic scale parameters of the medium, accounting for microstructure interactions. This study integrates two theoretical branches of the GCM, the modified couple stress theory (M-CST) and the one-parameter second-strain-gradient theory, to form a novel asymmetric wave equation in a unified framework. Numerical modeling of the asymmetric wave equation in a unified framework accurately describes subsurface structures with vital implications for subsequent seismic wave inversion and imaging endeavors. However, employing finite-difference (FD) methods for numerical modeling may introduce numerical dispersion, adversely affecting the accuracy of numerical modeling. The design of an optimal FD operator is crucial for enhancing the accuracy of numerical modeling and emphasizing the scale effects. Therefore, this study devises a hybrid scheme called the dung beetle optimization (DBO) algorithm with a simulated annealing (SA) algorithm, denoted as the SA-based hybrid DBO (SDBO) algorithm. An FD operator optimization method under the SDBO algorithm was developed and applied to the numerical modeling of asymmetric wave equations in a unified framework. Integrating the DBO and SA algorithms mitigates the risk of convergence to a local extreme. The numerical dispersion outcomes underscore that the proposed SDBO algorithm yields FD operators with precision errors constrained to 0.5‱ while encompassing a broader spectrum coverage. This result confirms the efficacy of the SDBO algorithm. Ultimately, the numerical modeling results demonstrate that the new FD method based on the SDBO algorithm effectively suppresses numerical dispersion and enhances the accuracy of elastic wave numerical modeling, thereby accentuating scale effects. This result is significant for extracting wavefield perturbations induced by complex microstructures in the medium and the analysis of scale effects.

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用于非对称波方程数值建模的蜣螂优化算法与模拟退火混合算法
在广义连续介质力学(GCM)理论框架中,非对称波方程包含介质的特征尺度参数,考虑了微观结构的相互作用。本研究整合了广义连续介质力学(GCM)的两个理论分支:修正耦合应力理论(M-CST)和一参数二次应变梯度理论,在统一框架下形成了一个新的非对称波方程。在统一框架下对非对称波方程进行数值建模,可准确描述地下结构,对后续地震波反演和成像工作具有重要意义。然而,采用有限差分(FD)方法进行数值建模可能会引入数值色散,从而对数值建模的精度产生不利影响。设计最佳的有限差分算子对于提高数值建模的精度和强调尺度效应至关重要。因此,本研究设计了一种蜣螂优化(DBO)算法与模拟退火(SA)算法的混合方案,称为基于模拟退火的混合 DBO(SDBO)算法。在 SDBO 算法下开发了一种 FD 算子优化方法,并在统一框架下应用于非对称波方程的数值建模。将 DBO 算法与 SA 算法相结合,降低了收敛到局部极值的风险。数值离散结果表明,所提出的 SDBO 算法产生的 FD 算子精度误差限制在 0.5‱,同时涵盖了更广的频谱范围。这一结果证实了 SDBO 算法的有效性。最终,数值建模结果表明,基于 SDBO 算法的新 FD 方法有效地抑制了数值色散,提高了弹性波数值建模的精度,从而突出了尺度效应。这一结果对于提取介质中复杂微结构引起的波场扰动和分析尺度效应具有重要意义。
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来源期刊
Applied Geophysics
Applied Geophysics 地学-地球化学与地球物理
CiteScore
1.50
自引率
14.30%
发文量
912
审稿时长
2 months
期刊介绍: The journal is designed to provide an academic realm for a broad blend of academic and industry papers to promote rapid communication and exchange of ideas between Chinese and world-wide geophysicists. The publication covers the applications of geoscience, geophysics, and related disciplines in the fields of energy, resources, environment, disaster, engineering, information, military, and surveying.
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