A weakly nonlinear study is numerically conducted to determine the behaviour near the onset of convection in rotating spherical shells. The mathematical and numerical procedure is described in generality, with the results presented for an Earth-like radius ratio. Through the weakly nonlinear analysis a Stuart--Landau equation is obtained for the amplitude of the convective instability, valid in the vicinity of its onset. Using this amplitude equation we derive a reduced order model for the saturation of the instability via nonlinear effects and can completely describe the resultant limit cycle without the need to solve initial value problems. In particular the weakly nonlinear analysis is able to determine whether convection onsets as a supercritical or subcritical Hopf bifurcation through solving only linear 2D problems, specifically one eigenvalue and two linear boundary value problems. Using this, we efficiently determine that convection can onset subcritically in a spherical shell for a range of Prandtl numbers if the shell is heated internally, confirming previous predictions. Furthermore, by examining the weakly nonlinear coefficients we show that it is the strong zonal flow created through Reynolds and thermal stresses that determines whether convection is supercritical or subcritical.
{"title":"Weakly nonlinear analysis of the onset of convection in rotating spherical shells","authors":"Calum S. Skene, Steven M. Tobias","doi":"arxiv-2408.15603","DOIUrl":"https://doi.org/arxiv-2408.15603","url":null,"abstract":"A weakly nonlinear study is numerically conducted to determine the behaviour\u0000near the onset of convection in rotating spherical shells. The mathematical and\u0000numerical procedure is described in generality, with the results presented for\u0000an Earth-like radius ratio. Through the weakly nonlinear analysis a\u0000Stuart--Landau equation is obtained for the amplitude of the convective\u0000instability, valid in the vicinity of its onset. Using this amplitude equation\u0000we derive a reduced order model for the saturation of the instability via\u0000nonlinear effects and can completely describe the resultant limit cycle without\u0000the need to solve initial value problems. In particular the weakly nonlinear\u0000analysis is able to determine whether convection onsets as a supercritical or\u0000subcritical Hopf bifurcation through solving only linear 2D problems,\u0000specifically one eigenvalue and two linear boundary value problems. Using this,\u0000we efficiently determine that convection can onset subcritically in a spherical\u0000shell for a range of Prandtl numbers if the shell is heated internally,\u0000confirming previous predictions. Furthermore, by examining the weakly nonlinear\u0000coefficients we show that it is the strong zonal flow created through Reynolds\u0000and thermal stresses that determines whether convection is supercritical or\u0000subcritical.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aggregates consisting of submicron-sized cohesive dust grains are ubiquitous, and understanding the collisional behavior of dust aggregates is essential. It is known that low-speed collisions of dust aggregates result in either sticking or bouncing, and local and permanent compaction occurs near the contact area upon collision. In this study, we perform numerical simulations of collisions between two aggregates and investigate their compressive behavior. We find that the maximum compression length is proportional to the radius of aggregates and increases with the collision velocity. We also reveal that a theoretical model of contact between two elastoplastic spheres successfully reproduces the size- and velocity-dependence of the maximum compression length observed in our numerical simulations. Our findings on the plastic deformation of aggregates during collisional compression provide a clue to understanding the collisional growth process of aggregates.
{"title":"On the elastoplastic behavior in collisional compression of spherical dust aggregates","authors":"Sota Arakawa, Hidekazu Tanaka, Eiichiro Kokubo, Satoshi Okuzumi, Misako Tatsuuma, Daisuke Nishiura, Mikito Furuichi","doi":"arxiv-2408.15573","DOIUrl":"https://doi.org/arxiv-2408.15573","url":null,"abstract":"Aggregates consisting of submicron-sized cohesive dust grains are ubiquitous,\u0000and understanding the collisional behavior of dust aggregates is essential. It\u0000is known that low-speed collisions of dust aggregates result in either sticking\u0000or bouncing, and local and permanent compaction occurs near the contact area\u0000upon collision. In this study, we perform numerical simulations of collisions\u0000between two aggregates and investigate their compressive behavior. We find that\u0000the maximum compression length is proportional to the radius of aggregates and\u0000increases with the collision velocity. We also reveal that a theoretical model\u0000of contact between two elastoplastic spheres successfully reproduces the size-\u0000and velocity-dependence of the maximum compression length observed in our\u0000numerical simulations. Our findings on the plastic deformation of aggregates\u0000during collisional compression provide a clue to understanding the collisional\u0000growth process of aggregates.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"407 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The adjoint method is a popular method used for seismic (full-waveform) inversion today. The method is considered to give more realistic and detailed images of the interior of the Earth by the use of more realistic physics. It relies on the definition of an adjoint wavefield (hence its name) that is the time reversed synthetics that satisfy the original equations of motion. The physical justification of the nature of the adjoint wavefield is, however, commonly done by brute force with ad hoc assumptions and/or relying on the existence of Green's functions, the representation theorem and/or the Born approximation. Using variational principles only, and without these mentioned assumptions and/or additional mathematical tools, we show that the time reversed adjoint wavefield should be defined as a premise that leads to the correct adjoint equations. This allows us to clarify mathematical inconsistencies found in previous seminal works when dealing with visco-elastic attenuation and/or odd-order derivative terms in the equation of motion. We then discuss some methodologies for the numerical implementation of the method in the time domain and to present a variational formulation for the construction of different misfit functions. We here define a new misfit travel-time function that allows us to find consensus for the long-standing debate on the zero sensitivity along the ray path that cross-correlation travel-time measurements show. In fact, we prove that the zero sensitivity along the ray-path appears as a consequence of the assumption on the similarity between data and synthetics required to perform cross-correlation travel-time measurements. When no assumption between data and synthetics is preconceived, travel-time Frechet kernels show an extremum along the ray path as one intuitively would expect.
{"title":"Understanding the Adjoint Method in Seismology: Theory and Implementation in the Time Domain","authors":"Rafael Abreu","doi":"arxiv-2408.15060","DOIUrl":"https://doi.org/arxiv-2408.15060","url":null,"abstract":"The adjoint method is a popular method used for seismic (full-waveform)\u0000inversion today. The method is considered to give more realistic and detailed\u0000images of the interior of the Earth by the use of more realistic physics. It\u0000relies on the definition of an adjoint wavefield (hence its name) that is the\u0000time reversed synthetics that satisfy the original equations of motion. The\u0000physical justification of the nature of the adjoint wavefield is, however,\u0000commonly done by brute force with ad hoc assumptions and/or relying on the\u0000existence of Green's functions, the representation theorem and/or the Born\u0000approximation. Using variational principles only, and without these mentioned\u0000assumptions and/or additional mathematical tools, we show that the time\u0000reversed adjoint wavefield should be defined as a premise that leads to the\u0000correct adjoint equations. This allows us to clarify mathematical\u0000inconsistencies found in previous seminal works when dealing with visco-elastic\u0000attenuation and/or odd-order derivative terms in the equation of motion. We\u0000then discuss some methodologies for the numerical implementation of the method\u0000in the time domain and to present a variational formulation for the\u0000construction of different misfit functions. We here define a new misfit\u0000travel-time function that allows us to find consensus for the long-standing\u0000debate on the zero sensitivity along the ray path that cross-correlation\u0000travel-time measurements show. In fact, we prove that the zero sensitivity\u0000along the ray-path appears as a consequence of the assumption on the similarity\u0000between data and synthetics required to perform cross-correlation travel-time\u0000measurements. When no assumption between data and synthetics is preconceived,\u0000travel-time Frechet kernels show an extremum along the ray path as one\u0000intuitively would expect.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jingxiao Liu, Haipeng Li, Siyuan Yuan, Hae Young Noh, Biondo Biondi
Continuous seismic monitoring of the near-surface structure is crucial for urban infrastructure safety, aiding in the detection of sinkholes, subsidence, and other seismic hazards. Utilizing existing telecommunication optical fibers as Distributed Acoustic Sensing (DAS) systems offers a cost-effective method for creating dense seismic arrays in urban areas. DAS leverages roadside fiber-optic cables to record vehicle-induced surface waves for near-surface imaging. However, the influence of roadway vehicle characteristics on their induced surface waves and the resulting imaging of near-surface structures is poorly understood. We investigate surface waves generated by vehicles of varying weights and speeds to provide insights into accurate and efficient near-surface characterization. We first classify vehicles into light, mid-weight, and heavy based on the maximum amplitudes of quasi-static DAS records. Vehicles are also classified by their traveling speed using their arrival times at DAS channels. To investigate how vehicle characteristics influence the induced surface waves, we extract phase velocity dispersion and invert the subsurface structure for each vehicle class by retrieving virtual shot gathers (VSGs). Our results reveal that heavy vehicles produce higher signal-to-noise ratio surface waves, and a sevenfold increase in vehicle weight can reduce uncertainties in phase velocity measurements from dispersion spectra by up to 3X. Thus, data from heavy vehicles better constrain structures at greater depths. Additionally, with driving speeds ranging from 5 to 30 meters per second in our study, differences in the dispersion curves due to vehicle speed are less pronounced than those due to vehicle weight. Our results suggest judiciously selecting and processing surface wave signals from certain vehicle types can improve the quality of near-surface imaging in urban environments.
对近地表结构进行连续地震监测对城市基础设施安全至关重要，有助于检测沉井、沉降和其他地震危险。利用现有的电信光纤作为分布式声学传感（DAS）系统，为在城市地区建立密集的地震阵列提供了一种具有成本效益的方法。DAS 利用路边光纤电缆记录车辆引起的表面波，用于近地表成像。然而，人们对道路车辆特性对其诱导面波以及由此产生的近地表结构成像的影响知之甚少。我们对不同重量和速度的车辆产生的表面波进行了研究，以便为准确、高效的近地表特征描述提供见解。我们首先根据准静态 DAS 记录的最大振幅将车辆分为轻型、中型和重型车辆。此外，我们还根据车辆到达 DAS 信道的时间，按其行驶速度对车辆进行分类。为了研究车辆特征如何影响诱导面波，我们提取了相位速度频散，并通过检索虚拟拍摄集合（VSGs）反演了每类车辆的次表层结构。我们的研究结果表明，重型车辆产生的表面波信噪比较高，车辆重量增加七倍可将频散谱相速度测量的不确定性降低 3 倍。因此，来自重型车辆的数据可以更好地约束更深的结构。此外，在我们的研究中，车辆的行驶速度从每秒 5 米到每秒 30 米不等，车辆速度造成的频散曲线差异没有车辆重量造成的差异那么明显。我们的研究结果表明，明智地选择和处理某些类型车辆的表面波信号，可以提高城市环境中近地表成像的质量。
{"title":"Characterizing Vehicle-Induced Distributed Acoustic Sensing Signals for Accurate Urban Near-Surface Imaging","authors":"Jingxiao Liu, Haipeng Li, Siyuan Yuan, Hae Young Noh, Biondo Biondi","doi":"arxiv-2408.14320","DOIUrl":"https://doi.org/arxiv-2408.14320","url":null,"abstract":"Continuous seismic monitoring of the near-surface structure is crucial for\u0000urban infrastructure safety, aiding in the detection of sinkholes, subsidence,\u0000and other seismic hazards. Utilizing existing telecommunication optical fibers\u0000as Distributed Acoustic Sensing (DAS) systems offers a cost-effective method\u0000for creating dense seismic arrays in urban areas. DAS leverages roadside\u0000fiber-optic cables to record vehicle-induced surface waves for near-surface\u0000imaging. However, the influence of roadway vehicle characteristics on their\u0000induced surface waves and the resulting imaging of near-surface structures is\u0000poorly understood. We investigate surface waves generated by vehicles of\u0000varying weights and speeds to provide insights into accurate and efficient\u0000near-surface characterization. We first classify vehicles into light,\u0000mid-weight, and heavy based on the maximum amplitudes of quasi-static DAS\u0000records. Vehicles are also classified by their traveling speed using their\u0000arrival times at DAS channels. To investigate how vehicle characteristics\u0000influence the induced surface waves, we extract phase velocity dispersion and\u0000invert the subsurface structure for each vehicle class by retrieving virtual\u0000shot gathers (VSGs). Our results reveal that heavy vehicles produce higher\u0000signal-to-noise ratio surface waves, and a sevenfold increase in vehicle weight\u0000can reduce uncertainties in phase velocity measurements from dispersion spectra\u0000by up to 3X. Thus, data from heavy vehicles better constrain structures at\u0000greater depths. Additionally, with driving speeds ranging from 5 to 30 meters\u0000per second in our study, differences in the dispersion curves due to vehicle\u0000speed are less pronounced than those due to vehicle weight. Our results suggest\u0000judiciously selecting and processing surface wave signals from certain vehicle\u0000types can improve the quality of near-surface imaging in urban environments.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhuan Ge, Teng Man, Kimberly M. Hill, Yujie Wang, Sergio Andres Galindo-Torres
Jamming transitions and the rheology of granular avalanches in fluids are investigated using experiments and numerical simulations. Simulations use the lattice-Boltzmann method coupled with the discrete element method, providing detailed stress and deformation data. Both simulations and experiments present a perfect match with each other in carefully conducted deposition experiments, validating the simulation method. We analyze transient rheological laws and jamming transitions using our recently introduced length-scale ratio $G$. $G$ serves as a unified metric for the pressure and shear rate capturing the dynamics of sheared fluid-granular systems. Two key transition points, $G_{Y}$ and $G_{0}$, categorize the material's state into solid-like, creeping, and fluid-like states. Yielding at $G_{Y}$ marks the transition from solid-like to creeping, while $G_{0}$ signifies the shift to the fluid-like state. The $mu-G$ relationship converges towards the equilibrium $mu_{eq}(G)$ after $G>G_0$ showing the critical point where the established rheological laws for steady states apply during transient conditions.
{"title":"Jamming, Yielding, and Rheology during Submerged Granular Avalanche","authors":"Zhuan Ge, Teng Man, Kimberly M. Hill, Yujie Wang, Sergio Andres Galindo-Torres","doi":"arxiv-2408.13730","DOIUrl":"https://doi.org/arxiv-2408.13730","url":null,"abstract":"Jamming transitions and the rheology of granular avalanches in fluids are\u0000investigated using experiments and numerical simulations. Simulations use the\u0000lattice-Boltzmann method coupled with the discrete element method, providing\u0000detailed stress and deformation data. Both simulations and experiments present\u0000a perfect match with each other in carefully conducted deposition experiments,\u0000validating the simulation method. We analyze transient rheological laws and\u0000jamming transitions using our recently introduced length-scale ratio $G$. $G$\u0000serves as a unified metric for the pressure and shear rate capturing the\u0000dynamics of sheared fluid-granular systems. Two key transition points, $G_{Y}$\u0000and $G_{0}$, categorize the material's state into solid-like, creeping, and\u0000fluid-like states. Yielding at $G_{Y}$ marks the transition from solid-like to\u0000creeping, while $G_{0}$ signifies the shift to the fluid-like state. The\u0000$mu-G$ relationship converges towards the equilibrium $mu_{eq}(G)$ after\u0000$G>G_0$ showing the critical point where the established rheological laws for\u0000steady states apply during transient conditions.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seismic data denoising is an important part of seismic data processing, which directly relate to the follow-up processing of seismic data. In terms of this issue, many authors proposed many methods based on rank reduction, sparse transformation, domain transformation, and deep learning. However, when the seismic data is noisy, complex and uneven, these methods often lead to over-denoising or under-denoising. To solve this problems, we proposed a novel method called noise level estimation and similarity segmentation for graded denoising. Specifically, we first assessed the average noise level of the entire seismic data and denoised it using block matching and three-dimensional filtering (BM3D) methods. Then, the denoised data is contrasted with the residual using local similarity, pinpointing regions where noise levels deviate significantly from the average. The remaining data is retained intact. These areas are then re-evaluated and denoised. Finally, we integrated the data retained after the first denoising with the re-denoising data to get a complete and cleaner data. This method is verified on theoretical model and actual seismic data. The experimental results show that this method has a good effect on seismic data with uneven noise.
{"title":"Adaptive Graded Denoising of Seismic Data Based on Noise Estimation and Local Similarity","authors":"Xueting Yang, Yong Li, Zhangquan Liao, Yingtian Liu, Junheng Peng","doi":"arxiv-2408.13578","DOIUrl":"https://doi.org/arxiv-2408.13578","url":null,"abstract":"Seismic data denoising is an important part of seismic data processing, which\u0000directly relate to the follow-up processing of seismic data. In terms of this\u0000issue, many authors proposed many methods based on rank reduction, sparse\u0000transformation, domain transformation, and deep learning. However, when the\u0000seismic data is noisy, complex and uneven, these methods often lead to\u0000over-denoising or under-denoising. To solve this problems, we proposed a novel\u0000method called noise level estimation and similarity segmentation for graded\u0000denoising. Specifically, we first assessed the average noise level of the\u0000entire seismic data and denoised it using block matching and three-dimensional\u0000filtering (BM3D) methods. Then, the denoised data is contrasted with the\u0000residual using local similarity, pinpointing regions where noise levels deviate\u0000significantly from the average. The remaining data is retained intact. These\u0000areas are then re-evaluated and denoised. Finally, we integrated the data\u0000retained after the first denoising with the re-denoising data to get a complete\u0000and cleaner data. This method is verified on theoretical model and actual\u0000seismic data. The experimental results show that this method has a good effect\u0000on seismic data with uneven noise.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ziheng Yu, David Al-Attar, Frank Syvret, Andrew J. Lloyd
This paper revisits and extends the adjoint theory for glacial isostatic adjustment (GIA) of Crawford et al. (2018). Rotational feedbacks are now incorporated, and the application of the second-order adjoint method is described for the first time. The first-order adjoint method provides an efficient means for computing sensitivity kernels for a chosen objective functional, while the second-order adjoint method provides second-derivative information in the form of Hessian kernels. These latter kernels are required by efficient Newton-type optimisation schemes and within methods for quantifying uncertainty for non-linear inverse problems. Most importantly, the entire theory has been reformulated so as to simplify its implementation by others within the GIA community. In particular, the rate-formulation for the GIA forward problem introduced by Crawford et al. (2018) has been replaced with the conventional equations for modelling GIA in laterally heterogeneous earth models. The implementation of the first- and second-order adjoint problems should be relatively easy within both existing and new GIA codes, with only the inclusions of more general force terms being required.
本文重温并扩展了 Crawford 等人（2018 年）的冰川等静力调整（GIA）邻接理论。现在纳入了旋转反馈，并首次描述了二阶积分法的应用。一阶积分法为计算选定目标函数的灵敏度核提供了一种高效方法，而二阶积分法则以黑森核的形式提供了二阶衍生信息。高效的牛顿优化方案和非线性逆问题的不确定性量化方法都需要后一种核。最重要的是，对整个理论进行了重新表述，以简化 GIA 社区其他成员的实施。特别是，Crawford 等人（2018 年）提出的 GIA 前向问题的速率公式已被用于模拟横向异质地球模型中 GIA 的常规方程所取代。在现有和新的 GIA 代码中，一阶和二阶邻接问题的实现相对容易，只需包含更多的一般力项。
{"title":"Application of first- and second-order adjoint methods to glacial isostatic adjustment incorporating rotational feedbacks","authors":"Ziheng Yu, David Al-Attar, Frank Syvret, Andrew J. Lloyd","doi":"arxiv-2408.13564","DOIUrl":"https://doi.org/arxiv-2408.13564","url":null,"abstract":"This paper revisits and extends the adjoint theory for glacial isostatic\u0000adjustment (GIA) of Crawford et al. (2018). Rotational feedbacks are now\u0000incorporated, and the application of the second-order adjoint method is\u0000described for the first time. The first-order adjoint method provides an\u0000efficient means for computing sensitivity kernels for a chosen objective\u0000functional, while the second-order adjoint method provides second-derivative\u0000information in the form of Hessian kernels. These latter kernels are required\u0000by efficient Newton-type optimisation schemes and within methods for\u0000quantifying uncertainty for non-linear inverse problems. Most importantly, the\u0000entire theory has been reformulated so as to simplify its implementation by\u0000others within the GIA community. In particular, the rate-formulation for the\u0000GIA forward problem introduced by Crawford et al. (2018) has been replaced with\u0000the conventional equations for modelling GIA in laterally heterogeneous earth\u0000models. The implementation of the first- and second-order adjoint problems\u0000should be relatively easy within both existing and new GIA codes, with only the\u0000inclusions of more general force terms being required.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stefania Gentili, Giuseppe Davide Chiappetta, Giuseppe Petrillo, Piero Brondi, Jiancang Zhuang
The advanced machine learning algorithm NESTORE (Next STrOng Related Earthquake) was developed to forecast strong aftershocks in earthquake sequences and has been successfully tested in Italy, western Slovenia, Greece, and California. NESTORE calculates the probability of aftershocks reaching or exceeding the magnitude of the main earthquake minus one and classifies clusters as type A or B based on a 0.5 probability threshold. In this study, NESTORE was applied to Japan using data from the Japan Meteorological Agency catalog (1973-2024). Due to Japan's high seismic activity and class imbalance, new algorithms were developed to complement NESTORE. The first is a hybrid cluster identification method using ETAS-based stochastic declustering and deterministic graph-based selection. The second, REPENESE (RElevant features, class imbalance PErcentage, NEighbour detection, SElection), is optimized for detecting outliers in skewed class distributions. A new seismicity feature was proposed, showing good results in forecasting cluster classes in Japan. Trained with data from 1973 to 2004 and tested from 2005 to 2023, the method correctly forecasted 75% of A clusters and 96% of B clusters, achieving a precision of 0.75 and an accuracy of 0.94 six hours after the mainshock. It accurately classified the 2011 T=ohoku event cluster. Near-real-time forecasting was applied to the sequence after the April 17, 2024 M6.6 earthquake in Shikoku, classifying it as a "Type B cluster," with validation expected on October 31, 2024.
{"title":"Forecasting Strong Subsequent Earthquakes in Japan using an improved version of NESTORE Machine Learning Algorithm","authors":"Stefania Gentili, Giuseppe Davide Chiappetta, Giuseppe Petrillo, Piero Brondi, Jiancang Zhuang","doi":"arxiv-2408.12956","DOIUrl":"https://doi.org/arxiv-2408.12956","url":null,"abstract":"The advanced machine learning algorithm NESTORE (Next STrOng Related\u0000Earthquake) was developed to forecast strong aftershocks in earthquake\u0000sequences and has been successfully tested in Italy, western Slovenia, Greece,\u0000and California. NESTORE calculates the probability of aftershocks reaching or\u0000exceeding the magnitude of the main earthquake minus one and classifies\u0000clusters as type A or B based on a 0.5 probability threshold. In this study,\u0000NESTORE was applied to Japan using data from the Japan Meteorological Agency\u0000catalog (1973-2024). Due to Japan's high seismic activity and class imbalance,\u0000new algorithms were developed to complement NESTORE. The first is a hybrid\u0000cluster identification method using ETAS-based stochastic declustering and\u0000deterministic graph-based selection. The second, REPENESE (RElevant features,\u0000class imbalance PErcentage, NEighbour detection, SElection), is optimized for\u0000detecting outliers in skewed class distributions. A new seismicity feature was\u0000proposed, showing good results in forecasting cluster classes in Japan. Trained\u0000with data from 1973 to 2004 and tested from 2005 to 2023, the method correctly\u0000forecasted 75% of A clusters and 96% of B clusters, achieving a precision of\u00000.75 and an accuracy of 0.94 six hours after the mainshock. It accurately\u0000classified the 2011 T=ohoku event cluster. Near-real-time forecasting was\u0000applied to the sequence after the April 17, 2024 M6.6 earthquake in Shikoku,\u0000classifying it as a \"Type B cluster,\" with validation expected on October 31,\u00002024.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pavol Matlovič, Adriana Pisarčíková, Veronika Pazderová, Stefan Loehle, Juraj Tóth, Ludovic Ferrière, Peter Čermák, David Leiser, Jérémie Vaubaillon, Ranjith Ravichandran
Emission spectra and diagnostic spectral features of a diverse range of ablated meteorite samples with a known composition are presented. We aim to provide a reference spectral dataset to improve our abilities to classify meteoroid composition types from meteor spectra observations. The data were obtained by ablating meteorite samples in high-enthalpy plasma wind tunnel facilities recreating conditions characteristic of low-speed meteors. Near-UV to visible-range (320 - 800 nm) emission spectra of 22 diverse meteorites captured by a high-resolution Echelle spectrometer were analyzed to identify the characteristic spectral features of individual meteorite groups. The same dataset captured by a lower-resolution meteor spectrograph was applied to compare the meteorite data with meteor spectra observations. Spectral modeling revealed that the emitting meteorite plasma was characterized by temperatures of 3700 - 4800 K, similar to the main temperature component of meteors. The studied line intensity variations were found to trace the differences in the original meteorite composition and thus can be used to constrain the individual meteorite classes. We demonstrate that meteorite composition types, including ordinary chondrites, carbonaceous chondrites, various achondrites, stony-iron and iron meteorites, can be spectrally distinguished by measuring relative line intensities of Mg I, Fe I, Na I, Cr I, Mn I, Si I, H I, CN, Ni I, and Li I. Additionally, we confirm the effect of the incomplete evaporation of refractory elements Al, Ti, and Ca, and the presence of minor species Co I, Cu I, and V I.
本文介绍了各种已知成分的已辐射陨石样本的发射光谱和诊断光谱特征。我们的目的是提供一个参考光谱数据集，以提高我们从流星光谱观测中对陨石成分类型进行分类的能力。这些数据是通过在高焓等离子风隧道设施中烧蚀陨石样本获得的，再现了低速流星的特征条件。对高分辨率埃歇尔光谱仪捕获的 22 种不同陨石的近紫外至可见光范围（320 - 800 nm）发射光谱进行了分析，以确定各个陨石群的光谱特征。应用低分辨率流星光谱仪捕获的同类数据集将陨石数据与流星光谱观测数据进行比较。光谱建模显示，发射陨石的等离子体的温度为 3700 - 4800 K，与流星的主要温度成分相似。研究发现，所研究的线强度变化可追溯到陨石原始成分的差异，因此可用于约束各个陨石类别。我们证明，通过测量 Mg I、Fe I、Na I、Cr I、Mn I、Si I、H I、CN、Ni I 和 Li I 的相对线强度，可以从光谱上区分陨石的成分类型，包括普通软玉、碳质软玉、各种隐长岩、石铁陨石和铁陨石。
{"title":"Spectral properties of ablating meteorite samples for improved meteoroid composition diagnostics","authors":"Pavol Matlovič, Adriana Pisarčíková, Veronika Pazderová, Stefan Loehle, Juraj Tóth, Ludovic Ferrière, Peter Čermák, David Leiser, Jérémie Vaubaillon, Ranjith Ravichandran","doi":"arxiv-2408.12276","DOIUrl":"https://doi.org/arxiv-2408.12276","url":null,"abstract":"Emission spectra and diagnostic spectral features of a diverse range of\u0000ablated meteorite samples with a known composition are presented. We aim to\u0000provide a reference spectral dataset to improve our abilities to classify\u0000meteoroid composition types from meteor spectra observations. The data were\u0000obtained by ablating meteorite samples in high-enthalpy plasma wind tunnel\u0000facilities recreating conditions characteristic of low-speed meteors. Near-UV\u0000to visible-range (320 - 800 nm) emission spectra of 22 diverse meteorites\u0000captured by a high-resolution Echelle spectrometer were analyzed to identify\u0000the characteristic spectral features of individual meteorite groups. The same\u0000dataset captured by a lower-resolution meteor spectrograph was applied to\u0000compare the meteorite data with meteor spectra observations. Spectral modeling\u0000revealed that the emitting meteorite plasma was characterized by temperatures\u0000of 3700 - 4800 K, similar to the main temperature component of meteors. The\u0000studied line intensity variations were found to trace the differences in the\u0000original meteorite composition and thus can be used to constrain the individual\u0000meteorite classes. We demonstrate that meteorite composition types, including\u0000ordinary chondrites, carbonaceous chondrites, various achondrites, stony-iron\u0000and iron meteorites, can be spectrally distinguished by measuring relative line\u0000intensities of Mg I, Fe I, Na I, Cr I, Mn I, Si I, H I, CN, Ni I, and Li I.\u0000Additionally, we confirm the effect of the incomplete evaporation of refractory\u0000elements Al, Ti, and Ca, and the presence of minor species Co I, Cu I, and V I.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhixiang Guo, Xinming Wu, Luming Liang, Hanlin Sheng, Nuo Chen, Zhengfa Bi
We explore adapting foundation models (FMs) from the computer vision domain to geoscience. FMs, large neural networks trained on massive datasets, excel in diverse tasks with remarkable adaptability and generality. However, geoscience faces challenges like lacking curated training datasets and high computational costs for developing specialized FMs. This study considers adapting FMs from computer vision to geoscience, analyzing their scale, adaptability, and generality for geoscientific data analysis. We introduce a workflow that leverages existing computer vision FMs, fine-tuning them for geoscientific tasks, reducing development costs while enhancing accuracy. Through experiments, we demonstrate this workflow's effectiveness in broad applications to process and interpret geoscientific data of lunar images, seismic data, DAS arrays and so on. Our findings introduce advanced ML techniques to geoscience, proving the feasibility and advantages of cross-domain FMs adaptation, driving further advancements in geoscientific data analysis and offering valuable insights for FMs applications in other scientific domains.
我们探讨了如何将计算机视觉领域的基础模型（FMs）应用到地球科学领域。基础模型是在海量数据集上训练的大型神经网络，在各种任务中表现出色，具有显著的适应性和通用性。然而，地球科学面临着各种挑战，如缺乏经过精心策划的训练数据集，以及开发专用基础模型的计算成本高昂。本研究考虑将计算机视觉中的调频技术应用到地球科学中，分析它们在地球科学数据分析中的规模、适应性和通用性。我们介绍了一种工作流程，该流程利用现有的计算机视觉调频技术，针对地球科学任务对其进行微调，在提高准确性的同时降低开发成本。通过实验，我们证明了这一工作流程在处理和解释月球图像、地震数据、DAS 阵列等地球科学数据的广泛应用中的有效性。我们的研究成果将先进的 ML 技术引入了地球科学，证明了跨领域调频适应的可行性和优势，推动了地球科学数据分析的进一步发展，并为调频在其他科学领域的应用提供了宝贵的启示。
{"title":"Cross-Domain Foundation Model Adaptation: Pioneering Computer Vision Models for Geophysical Data Analysis","authors":"Zhixiang Guo, Xinming Wu, Luming Liang, Hanlin Sheng, Nuo Chen, Zhengfa Bi","doi":"arxiv-2408.12396","DOIUrl":"https://doi.org/arxiv-2408.12396","url":null,"abstract":"We explore adapting foundation models (FMs) from the computer vision domain\u0000to geoscience. FMs, large neural networks trained on massive datasets, excel in\u0000diverse tasks with remarkable adaptability and generality. However, geoscience\u0000faces challenges like lacking curated training datasets and high computational\u0000costs for developing specialized FMs. This study considers adapting FMs from\u0000computer vision to geoscience, analyzing their scale, adaptability, and\u0000generality for geoscientific data analysis. We introduce a workflow that\u0000leverages existing computer vision FMs, fine-tuning them for geoscientific\u0000tasks, reducing development costs while enhancing accuracy. Through\u0000experiments, we demonstrate this workflow's effectiveness in broad applications\u0000to process and interpret geoscientific data of lunar images, seismic data, DAS\u0000arrays and so on. Our findings introduce advanced ML techniques to geoscience,\u0000proving the feasibility and advantages of cross-domain FMs adaptation, driving\u0000further advancements in geoscientific data analysis and offering valuable\u0000insights for FMs applications in other scientific domains.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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