Jingxiao Liu, Haipeng Li, Hae Young Noh, Paolo Santi, Biondo Biondi, Carlo Ratti
The analysis of urban seismic sources offers valuable insights into urban environments, including seismic hazards, infrastructure conditions, human mobility, and cultural life. Yet, accurate detection and localization of seismic sources at the urban scale with conventional seismic sensing networks is unavailable due to the prohibitive costs of ultra-dense seismic arrays required for imaging high-frequency anthropogenic seismic sources. Here, we leverage existing fiber-optic networks as a distributed acoustic sensing system to accurately locate urban seismic sources and estimate how their intensity varies with time. By repurposing a 50-kilometer telecommunication fiber into an ultra-dense seismic array with 50,000 channels, we generate high-resolution spatiotemporal maps of seismic source power (SSP) across San Jose, California. Our approach overcomes the proximity limitations of urban seismic sensing, enabling accurate localization of remote seismic sources generated by urban activities. Examples of detected activities are vehicle movements and operations at construction sites and schools. We also show strong correlations between SSP values and noise level measurements, as well as various persistent urban features, including point of interest density, land use patterns, and demographics. Our study shows how spatiotemporal SSP maps can be turned into novel urban data that effectively captures urban dynamics across multiple features, thus opening the way towards the use of fiber-optic networks as a ubiquitous and general-purpose urban sensing platform, with wide-ranging applications in urban and environmental studies.
{"title":"Urban Sensing Using Existing Fiber-Optic Networks","authors":"Jingxiao Liu, Haipeng Li, Hae Young Noh, Paolo Santi, Biondo Biondi, Carlo Ratti","doi":"arxiv-2409.05820","DOIUrl":"https://doi.org/arxiv-2409.05820","url":null,"abstract":"The analysis of urban seismic sources offers valuable insights into urban\u0000environments, including seismic hazards, infrastructure conditions, human\u0000mobility, and cultural life. Yet, accurate detection and localization of\u0000seismic sources at the urban scale with conventional seismic sensing networks\u0000is unavailable due to the prohibitive costs of ultra-dense seismic arrays\u0000required for imaging high-frequency anthropogenic seismic sources. Here, we\u0000leverage existing fiber-optic networks as a distributed acoustic sensing system\u0000to accurately locate urban seismic sources and estimate how their intensity\u0000varies with time. By repurposing a 50-kilometer telecommunication fiber into an\u0000ultra-dense seismic array with 50,000 channels, we generate high-resolution\u0000spatiotemporal maps of seismic source power (SSP) across San Jose, California.\u0000Our approach overcomes the proximity limitations of urban seismic sensing,\u0000enabling accurate localization of remote seismic sources generated by urban\u0000activities. Examples of detected activities are vehicle movements and\u0000operations at construction sites and schools. We also show strong correlations\u0000between SSP values and noise level measurements, as well as various persistent\u0000urban features, including point of interest density, land use patterns, and\u0000demographics. Our study shows how spatiotemporal SSP maps can be turned into\u0000novel urban data that effectively captures urban dynamics across multiple\u0000features, thus opening the way towards the use of fiber-optic networks as a\u0000ubiquitous and general-purpose urban sensing platform, with wide-ranging\u0000applications in urban and environmental studies.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211787","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}
Jørgen R. Aarnes, Omer Babiker, Anqing Xuan, Lian Shen, Simen Å. Ellingsen
Turbulence beneath a free surface leaves characteristic long-lived signatures on the surface, such as upwelling 'boils', near-circular 'dimples' and elongated 'scars', easily identifiable by eye, e.g., in riverine flows. In this paper, we use Direct Numerical Simulations to explore the connection between these surface signatures and the underlying vortical structures. We investigate dimples, known to be imprints of surface-attached vortices, and scars, which have yet to be extensively studied, by analysing the conditional probabilities that a point beneath a signature is within a vortex core as well as the inclination angles of sub-signature vorticity. The analysis shows that the likelihood of vortex presence beneath a dimple decreases from the surface down through the viscous and blockage layers in a near-Gaussian manner, influenced by the dimple's size and the bulk turbulence. When expressed as a function of depth over the Taylor microscale $lambda_T$, this probability is independent of Reynolds and Weber number. Conversely, the probability of finding a vortex beneath a scar increases sharply from the surface to a peak at the edge of the viscous layer, at a depth of approximately $lambda_T/4$. Distributions of vortical orientation also show a clear pattern: a strong preference for vertical alignment below dimples and an equally strong preference for horizontal alignment below scars. Our findings suggest that scars can be defined as imprints of horizontal vortices approximately a quarter of the Taylor microscale beneath the surface, analogous to how dimples can be defined as imprints of surface-attached vertical vortex tubes.
{"title":"Vortex structures under dimples and scars in turbulent free-surface flows","authors":"Jørgen R. Aarnes, Omer Babiker, Anqing Xuan, Lian Shen, Simen Å. Ellingsen","doi":"arxiv-2409.05409","DOIUrl":"https://doi.org/arxiv-2409.05409","url":null,"abstract":"Turbulence beneath a free surface leaves characteristic long-lived signatures\u0000on the surface, such as upwelling 'boils', near-circular 'dimples' and\u0000elongated 'scars', easily identifiable by eye, e.g., in riverine flows. In this\u0000paper, we use Direct Numerical Simulations to explore the connection between\u0000these surface signatures and the underlying vortical structures. We investigate\u0000dimples, known to be imprints of surface-attached vortices, and scars, which\u0000have yet to be extensively studied, by analysing the conditional probabilities\u0000that a point beneath a signature is within a vortex core as well as the\u0000inclination angles of sub-signature vorticity. The analysis shows that the\u0000likelihood of vortex presence beneath a dimple decreases from the surface down\u0000through the viscous and blockage layers in a near-Gaussian manner, influenced\u0000by the dimple's size and the bulk turbulence. When expressed as a function of\u0000depth over the Taylor microscale $lambda_T$, this probability is independent\u0000of Reynolds and Weber number. Conversely, the probability of finding a vortex\u0000beneath a scar increases sharply from the surface to a peak at the edge of the\u0000viscous layer, at a depth of approximately $lambda_T/4$. Distributions of\u0000vortical orientation also show a clear pattern: a strong preference for\u0000vertical alignment below dimples and an equally strong preference for\u0000horizontal alignment below scars. Our findings suggest that scars can be\u0000defined as imprints of horizontal vortices approximately a quarter of the\u0000Taylor microscale beneath the surface, analogous to how dimples can be defined\u0000as imprints of surface-attached vertical vortex tubes.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226706","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}
Grant Bruer, Abhinav Prakash Gahlot, Edmond Chow, Felix Herrmann
Monitoring carbon dioxide (CO2) injected and stored in subsurface reservoirs is critical for avoiding failure scenarios and enables real-time optimization of CO2 injection rates. Sequential Bayesian data assimilation (DA) is a statistical method for combining information over time from multiple sources to estimate a hidden state, such as the spread of the subsurface CO2 plume. An example of scalable and efficient sequential Bayesian DA is the ensemble Kalman filter (EnKF). We improve upon existing DA literature in the seismic-CO2 monitoring domain by applying this scalable DA algorithm to a high-dimensional CO2 reservoir using two-phase flow dynamics and time-lapse full waveform seismic data with a realistic surface-seismic survey design. We show more accurate estimates of the CO2 saturation field using the EnKF compared to using either the seismic data or the fluid physics alone. Furthermore, we test a range of values for the EnKF hyperparameters and give guidance on their selection for seismic CO2 reservoir monitoring.
对注入和储存在地下储层中的二氧化碳（CO2）进行监测，对于避免出现故障情况和实时优化二氧化碳注入率至关重要。序列贝叶斯数据同化（DA）是一种统计方法，用于结合来自多个来源的长期信息来估计隐藏状态，如地下二氧化碳羽流的扩散。集合卡尔曼滤波器（EnKF）就是可扩展的高效序列贝叶斯数据同化的一个例子。我们将这种可扩展的贝叶斯算法应用于高维 CO2 储层，使用两相流动力学和具有现实地表地震勘测设计的延时全波形地震数据，从而改进了地震-CO2 监测领域现有的贝叶斯算法。与单独使用地震数据或流体物理数据相比，我们使用 EnKF 对二氧化碳饱和度场进行了更精确的估算。此外，我们还测试了一系列 EnKF 超参数值，并为二氧化碳储层地震监测的参数选择提供了指导。
{"title":"Seismic monitoring of CO2 plume dynamics using ensemble Kalman filtering","authors":"Grant Bruer, Abhinav Prakash Gahlot, Edmond Chow, Felix Herrmann","doi":"arxiv-2409.05193","DOIUrl":"https://doi.org/arxiv-2409.05193","url":null,"abstract":"Monitoring carbon dioxide (CO2) injected and stored in subsurface reservoirs\u0000is critical for avoiding failure scenarios and enables real-time optimization\u0000of CO2 injection rates. Sequential Bayesian data assimilation (DA) is a\u0000statistical method for combining information over time from multiple sources to\u0000estimate a hidden state, such as the spread of the subsurface CO2 plume. An\u0000example of scalable and efficient sequential Bayesian DA is the ensemble Kalman\u0000filter (EnKF). We improve upon existing DA literature in the seismic-CO2\u0000monitoring domain by applying this scalable DA algorithm to a high-dimensional\u0000CO2 reservoir using two-phase flow dynamics and time-lapse full waveform\u0000seismic data with a realistic surface-seismic survey design. We show more\u0000accurate estimates of the CO2 saturation field using the EnKF compared to using\u0000either the seismic data or the fluid physics alone. Furthermore, we test a\u0000range of values for the EnKF hyperparameters and give guidance on their\u0000selection for seismic CO2 reservoir monitoring.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"63 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211788","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 interiors of many planets consist mostly of fluid layers. When these layers are subject to superadiabatic temperature or compositional gradients, turbulent convection transports heat and momentum. In addition, planets are fast rotators. Thus, the key process that underpins planetary evolution, the dynamo action, flow patterns and more, is rotating convection. Because planetary interiors are inaccessible to direct observation, experiments offer physically consistent models that are crucial to guide our understanding. If we can fully understand the laboratory model, we may eventually fully understand the original. Experimentally reproducing rotating thermal convection relevant to planetary interiors comes with specific challenges, e.g. modelling the central gravity field of a planet that is parallel to the temperature gradient. Three classes of experiments tackle this challenge. One approach consists of using an alternative central force field, such as the electric force. These are, however, weaker than gravity and require going to space. Another method entails rotating the device fast enough so that the centrifugal force supersedes Earth's gravity. This mimics the equatorial regions of a planet. Lastly, by using the actual lab gravity aligned with the rotation axis, insight into the polar regions is gained. These experiments have been continuously refined during the past seven decades. We review their evolution, from the early days of visualising the onset patterns of convection, over central force field experiments in spacecrafts, liquid metal experiments, to the latest optical velocity mapping of rotating magnetoconvection in sulfuric acid inside high-field magnets. We show how innovative experimental design and emerging experimental techniques advanced our understanding and painted a more realistic picture of planetary interiors, including Earth's liquid metal outer core.
{"title":"Seven decades of exploring planetary interiors with rotating convection experiments","authors":"Alban Pothérat, Susanne Horn","doi":"arxiv-2409.05220","DOIUrl":"https://doi.org/arxiv-2409.05220","url":null,"abstract":"The interiors of many planets consist mostly of fluid layers. When these\u0000layers are subject to superadiabatic temperature or compositional gradients,\u0000turbulent convection transports heat and momentum. In addition, planets are\u0000fast rotators. Thus, the key process that underpins planetary evolution, the\u0000dynamo action, flow patterns and more, is rotating convection. Because\u0000planetary interiors are inaccessible to direct observation, experiments offer\u0000physically consistent models that are crucial to guide our understanding. If we\u0000can fully understand the laboratory model, we may eventually fully understand\u0000the original. Experimentally reproducing rotating thermal convection relevant\u0000to planetary interiors comes with specific challenges, e.g. modelling the\u0000central gravity field of a planet that is parallel to the temperature gradient.\u0000Three classes of experiments tackle this challenge. One approach consists of\u0000using an alternative central force field, such as the electric force. These\u0000are, however, weaker than gravity and require going to space. Another method\u0000entails rotating the device fast enough so that the centrifugal force\u0000supersedes Earth's gravity. This mimics the equatorial regions of a planet.\u0000Lastly, by using the actual lab gravity aligned with the rotation axis, insight\u0000into the polar regions is gained. These experiments have been continuously\u0000refined during the past seven decades. We review their evolution, from the\u0000early days of visualising the onset patterns of convection, over central force\u0000field experiments in spacecrafts, liquid metal experiments, to the latest\u0000optical velocity mapping of rotating magnetoconvection in sulfuric acid inside\u0000high-field magnets. We show how innovative experimental design and emerging\u0000experimental techniques advanced our understanding and painted a more realistic\u0000picture of planetary interiors, including Earth's liquid metal outer core.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211790","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}
Yifei Guan, Pedram Hassanzadeh, Tapio Schneider, Oliver Dunbar, Daniel Zhengyu Huang, Jinlong Wu, Ignacio Lopez-Gomez
Different approaches to using data-driven methods for subgrid-scale closure modeling have emerged recently. Most of these approaches are data-hungry, and lack interpretability and out-of-distribution generalizability. Here, we use {online} learning to address parametric uncertainty of well-known physics-based large-eddy simulation (LES) closures: the Smagorinsky (Smag) and Leith eddy-viscosity models (1 free parameter) and the Jansen-Held (JH) backscattering model (2 free parameters). For 8 cases of 2D geophysical turbulence, optimal parameters are estimated, using ensemble Kalman inversion (EKI), such that for each case, the LES' energy spectrum matches that of direct numerical simulation (DNS). Only a small training dataset is needed to calculate the DNS spectra (i.e., the approach is {data-efficient}). We find the optimized parameter(s) of each closure to be constant across broad flow regimes that differ in dominant length scales, eddy/jet structures, and dynamics, suggesting that these closures are {generalizable}. In a-posteriori tests based on the enstrophy spectra and probability density functions (PDFs) of vorticity, LES with optimized closures outperform the baselines (LES with standard Smag, dynamic Smag or Leith), particularly at the tails of the PDFs (extreme events). In a-priori tests, the optimized JH significantly outperforms the baselines and optimized Smag and Leith in terms of interscale enstrophy and energy transfers (still, optimized Smag noticeably outperforms standard Smag). The results show the promise of combining advances in physics-based modeling (e.g., JH) and data-driven modeling (e.g., {online} learning with EKI) to develop data-efficient frameworks for accurate, interpretable, and generalizable closures.
最近出现了不同的使用数据驱动方法进行亚网格尺度闭合建模的方法。这些方法大多对数据要求较高，缺乏可解释性和分布外概括性。在这里，我们使用在线学习来解决著名的基于物理的大尺度涡旋模拟（LES）闭合模型的参数不确定性问题：Smagorinsky（Smag）和 Leitheddy-粘度模型（1 个自由参数）以及 Jansen-Held （JH）反向散射模型（2 个自由参数）。针对 8 种二维地球物理扰动情况，利用集合卡尔曼反演（EKI）估算出最佳参数，从而使 LES 的能谱与直接数值模拟（DNS）的能谱相匹配。计算 DNS 能谱只需要少量的训练数据集（即该方法{数据效率高}）。我们发现每个闭合的优化参数在不同的流态下都是恒定的，而这些流态在主要长度尺度、涡/射流结构和动力学方面都有所不同，这表明这些闭合是{可通用的}。在基于涡度的熵谱和概率密度函数（PDF）的后验中，采用优化闭合的 LES 优于基线（采用标准 Smag、动态 Smag 或 Leith 的 LES），尤其是在 PDF 的尾部（极端事件）。在先验测试中，优化 JH 在尺度间熵和能量传递方面明显优于基线、优化 Smag 和 Leith（但优化 Smag 仍明显优于标准 Smag）。这些结果表明，将基于物理的建模（如 JH）和数据驱动的建模（如使用 EKI 的{在线}学习）的进步结合起来，为准确、可解释和可推广的信息披露开发数据高效的框架是大有可为的。
{"title":"Online learning of eddy-viscosity and backscattering closures for geophysical turbulence using ensemble Kalman inversion","authors":"Yifei Guan, Pedram Hassanzadeh, Tapio Schneider, Oliver Dunbar, Daniel Zhengyu Huang, Jinlong Wu, Ignacio Lopez-Gomez","doi":"arxiv-2409.04985","DOIUrl":"https://doi.org/arxiv-2409.04985","url":null,"abstract":"Different approaches to using data-driven methods for subgrid-scale closure\u0000modeling have emerged recently. Most of these approaches are data-hungry, and\u0000lack interpretability and out-of-distribution generalizability. Here, we use\u0000{online} learning to address parametric uncertainty of well-known physics-based\u0000large-eddy simulation (LES) closures: the Smagorinsky (Smag) and Leith\u0000eddy-viscosity models (1 free parameter) and the Jansen-Held (JH)\u0000backscattering model (2 free parameters). For 8 cases of 2D geophysical\u0000turbulence, optimal parameters are estimated, using ensemble Kalman inversion\u0000(EKI), such that for each case, the LES' energy spectrum matches that of direct\u0000numerical simulation (DNS). Only a small training dataset is needed to\u0000calculate the DNS spectra (i.e., the approach is {data-efficient}). We find the\u0000optimized parameter(s) of each closure to be constant across broad flow regimes\u0000that differ in dominant length scales, eddy/jet structures, and dynamics,\u0000suggesting that these closures are {generalizable}. In a-posteriori tests based\u0000on the enstrophy spectra and probability density functions (PDFs) of vorticity,\u0000LES with optimized closures outperform the baselines (LES with standard Smag,\u0000dynamic Smag or Leith), particularly at the tails of the PDFs (extreme events).\u0000In a-priori tests, the optimized JH significantly outperforms the baselines and\u0000optimized Smag and Leith in terms of interscale enstrophy and energy transfers\u0000(still, optimized Smag noticeably outperforms standard Smag). The results show\u0000the promise of combining advances in physics-based modeling (e.g., JH) and\u0000data-driven modeling (e.g., {online} learning with EKI) to develop\u0000data-efficient frameworks for accurate, interpretable, and generalizable\u0000closures.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211792","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}
Hang Gao, Xinming Wu, Luming Liang, Hanlin Sheng, Xu Si, Gao Hui, Yaxing Li
Seismic geobody interpretation is crucial for structural geology studies and various engineering applications. Existing deep learning methods show promise but lack support for multi-modal inputs and struggle to generalize to different geobody types or surveys. We introduce a promptable foundation model for interpreting any geobodies across seismic surveys. This model integrates a pre-trained vision foundation model (VFM) with a sophisticated multi-modal prompt engine. The VFM, pre-trained on massive natural images and fine-tuned on seismic data, provides robust feature extraction for cross-survey generalization. The prompt engine incorporates multi-modal prior information to iteratively refine geobody delineation. Extensive experiments demonstrate the model's superior accuracy, scalability from 2D to 3D, and generalizability to various geobody types, including those unseen during training. To our knowledge, this is the first highly scalable and versatile multi-modal foundation model capable of interpreting any geobodies across surveys while supporting real-time interactions. Our approach establishes a new paradigm for geoscientific data interpretation, with broad potential for transfer to other tasks.
{"title":"A foundation model enpowered by a multi-modal prompt engine for universal seismic geobody interpretation across surveys","authors":"Hang Gao, Xinming Wu, Luming Liang, Hanlin Sheng, Xu Si, Gao Hui, Yaxing Li","doi":"arxiv-2409.04962","DOIUrl":"https://doi.org/arxiv-2409.04962","url":null,"abstract":"Seismic geobody interpretation is crucial for structural geology studies and\u0000various engineering applications. Existing deep learning methods show promise\u0000but lack support for multi-modal inputs and struggle to generalize to different\u0000geobody types or surveys. We introduce a promptable foundation model for\u0000interpreting any geobodies across seismic surveys. This model integrates a\u0000pre-trained vision foundation model (VFM) with a sophisticated multi-modal\u0000prompt engine. The VFM, pre-trained on massive natural images and fine-tuned on\u0000seismic data, provides robust feature extraction for cross-survey\u0000generalization. The prompt engine incorporates multi-modal prior information to\u0000iteratively refine geobody delineation. Extensive experiments demonstrate the\u0000model's superior accuracy, scalability from 2D to 3D, and generalizability to\u0000various geobody types, including those unseen during training. To our\u0000knowledge, this is the first highly scalable and versatile multi-modal\u0000foundation model capable of interpreting any geobodies across surveys while\u0000supporting real-time interactions. Our approach establishes a new paradigm for\u0000geoscientific data interpretation, with broad potential for transfer to other\u0000tasks.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211789","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}
Samaneh Ansari, Edwin S. Kite, Ramses Ramirez, Liam J. Steele, Hooman Mohseni
One-third of Mars' surface has shallow-buried H$_2$O, but it is currently too cold for use by life. Proposals to warm Mars using greenhouse gases require a large mass of ingredients that are rare on Mars' surface. However, we show here that artificial aerosols made from materials that are readily available at Mars-for example, conductive nanorods that are ~9 $mu$m long-could warm Mars >5 $times$ 10$^3$ times more effectively than the best gases. Such nanoparticles forward-scatter sunlight and efficiently block upwelling thermal infrared. Similar to the natural dust of Mars, they are swept high into Mars' atmosphere, allowing delivery from the near-surface. For a particle lifetime of 10 years, two climate models indicate that sustained release at 30 liters/sec would globally warm Mars by $gtrsim$30 K and start to melt the ice. Therefore, if nanoparticles can be made at scale on (or delivered to) Mars, then the barrier to warming of Mars appears to not be as high as previously thought.
{"title":"Feasibility of keeping Mars warm with nanoparticles","authors":"Samaneh Ansari, Edwin S. Kite, Ramses Ramirez, Liam J. Steele, Hooman Mohseni","doi":"arxiv-2409.03925","DOIUrl":"https://doi.org/arxiv-2409.03925","url":null,"abstract":"One-third of Mars' surface has shallow-buried H$_2$O, but it is currently too\u0000cold for use by life. Proposals to warm Mars using greenhouse gases require a\u0000large mass of ingredients that are rare on Mars' surface. However, we show here\u0000that artificial aerosols made from materials that are readily available at\u0000Mars-for example, conductive nanorods that are ~9 $mu$m long-could warm Mars\u0000>5 $times$ 10$^3$ times more effectively than the best gases. Such\u0000nanoparticles forward-scatter sunlight and efficiently block upwelling thermal\u0000infrared. Similar to the natural dust of Mars, they are swept high into Mars'\u0000atmosphere, allowing delivery from the near-surface. For a particle lifetime of\u000010 years, two climate models indicate that sustained release at 30 liters/sec\u0000would globally warm Mars by $gtrsim$30 K and start to melt the ice. Therefore,\u0000if nanoparticles can be made at scale on (or delivered to) Mars, then the\u0000barrier to warming of Mars appears to not be as high as previously thought.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226707","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}
Physics-informed neural networks (PINNs) have great potential for flexibility and effectiveness in forward modeling and inversion of seismic waves. However, coordinate-based neural networks (NNs) commonly suffer from the "spectral bias" pathology, which greatly limits their ability to model high-frequency wave propagation in sharp and complex media. We propose a unified framework of Fourier feature physics-informed neural networks (FF-PINNs) for solving the time-domain wave equations. The proposed framework combines the stochastic gradient descent (SGD) strategy with a pre-trained wave velocity surrogate model to mitigate the singularity at the point source. The performance of the activation functions and gradient descent strategies are discussed through ablation experiments. In addition, we evaluate the accuracy comparison of Fourier feature mappings sampled from different families of distributions (Gaussian, Laplace, and uniform). The second-order paraxial approximation-based boundary conditions are incorporated into the loss function as a soft regularizer to eliminate spurious boundary reflections. Through the non-smooth Marmousi and Overthrust model cases, we emphasized the necessity of the absorbing boundary conditions (ABCs) constraints. The results of a series of numerical experiments demonstrate the accuracy and effectiveness of the proposed method for modeling high-frequency wave propagation in sharp and complex media.
{"title":"Physics-informed Neural Networks with Fourier Features for Seismic Wavefield Simulation in Time-Domain Nonsmooth Complex Media","authors":"Yi Ding, Su Chen, Hiroe Miyake, Xiaojun Li","doi":"arxiv-2409.03536","DOIUrl":"https://doi.org/arxiv-2409.03536","url":null,"abstract":"Physics-informed neural networks (PINNs) have great potential for flexibility\u0000and effectiveness in forward modeling and inversion of seismic waves. However,\u0000coordinate-based neural networks (NNs) commonly suffer from the \"spectral bias\"\u0000pathology, which greatly limits their ability to model high-frequency wave\u0000propagation in sharp and complex media. We propose a unified framework of\u0000Fourier feature physics-informed neural networks (FF-PINNs) for solving the\u0000time-domain wave equations. The proposed framework combines the stochastic\u0000gradient descent (SGD) strategy with a pre-trained wave velocity surrogate\u0000model to mitigate the singularity at the point source. The performance of the\u0000activation functions and gradient descent strategies are discussed through\u0000ablation experiments. In addition, we evaluate the accuracy comparison of\u0000Fourier feature mappings sampled from different families of distributions\u0000(Gaussian, Laplace, and uniform). The second-order paraxial approximation-based\u0000boundary conditions are incorporated into the loss function as a soft\u0000regularizer to eliminate spurious boundary reflections. Through the non-smooth\u0000Marmousi and Overthrust model cases, we emphasized the necessity of the\u0000absorbing boundary conditions (ABCs) constraints. The results of a series of\u0000numerical experiments demonstrate the accuracy and effectiveness of the\u0000proposed method for modeling high-frequency wave propagation in sharp and\u0000complex media.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226708","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}
Fluid injections can induce aseismic slip, resulting in stress changes that may propagate faster than pore pressure diffusion, potentially triggering seismicity at significant distances from injection wells. Constraining the maximum extent of these aseismic ruptures is thus important for better delineating the influence zone of injections concerning their seismic hazard. Here we derive a scaling relation based on rupture physics for the maximum size of aseismic ruptures, accounting for fluid injections with arbitrary flow rate histories. Moreover, based on mounting evidence that the moment release during these operations is often predominantly aseismic, we derive a scaling relation for the maximum magnitude of aseismic slip events. Our theoretical predictions are consistent with observations over a broad spectrum of event sizes, from laboratory to real-world cases, indicating that fault-zone storativity, background stress state, and injected fluid volume are key determinants of the maximum size and magnitude of injection-induced slow slip events.
{"title":"Maximum size and magnitude of injection-induced slow slip events","authors":"Alexis Sáez, François Passelègue, Brice Lecampion","doi":"arxiv-2409.03330","DOIUrl":"https://doi.org/arxiv-2409.03330","url":null,"abstract":"Fluid injections can induce aseismic slip, resulting in stress changes that\u0000may propagate faster than pore pressure diffusion, potentially triggering\u0000seismicity at significant distances from injection wells. Constraining the\u0000maximum extent of these aseismic ruptures is thus important for better\u0000delineating the influence zone of injections concerning their seismic hazard.\u0000Here we derive a scaling relation based on rupture physics for the maximum size\u0000of aseismic ruptures, accounting for fluid injections with arbitrary flow rate\u0000histories. Moreover, based on mounting evidence that the moment release during\u0000these operations is often predominantly aseismic, we derive a scaling relation\u0000for the maximum magnitude of aseismic slip events. Our theoretical predictions\u0000are consistent with observations over a broad spectrum of event sizes, from\u0000laboratory to real-world cases, indicating that fault-zone storativity,\u0000background stress state, and injected fluid volume are key determinants of the\u0000maximum size and magnitude of injection-induced slow slip events.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211793","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}
Manousos Valyrakis, Xiao Zhao, Thomas Pähtz, Zhen Li
Recently, significant progress has been made in conceptually describing the dynamic aspects of coarse particle entrainment, which has been explored experimentally for open channel flows. The aim of this study is to extend the application of energy criterion to the low mobility aeolian transport of solids (including both natural sediment and anthropogenic debris such as plastics), ranging from incomplete (rocking) to full (rolling) entrainments. This is achieved by linking particle movements to energetic flow events, which are defined as flow structures with the ability to work on particles, setting them into motion. It is hypothesized that such events should impart sufficient energy to the particles, above a certain threshold value. The concept's validity is demonstrated experimentally, using a wind tunnel and laser distance sensor (LDS) to capture the dynamics of an individual target particle, exposed on a rough bed surface. Measurements are acquired at a high spatiotemporal resolution, and synchronously with the instantaneous air velocity at an appropriate distance upwind of the target particle, using a hot film anemometer. This enables the association of flow events with rocking and rolling entrainments. Furthermore, it is shown that rocking and rolling may have distinct energy thresholds. Estimates of the energy transfer efficiency, normalized by the drag coefficient, range over an order of magnitude (from about 0.001 to 0.0048 for rocking, up to about 0.01, for incipient rolling). The proposed event-based theoretical framework is a novel approach to characterizing the energy imparted from the wind to the soil surface and could have potential implications for modelling intermittent creep transport of coarse particles and related aeolian bedforms.
{"title":"The role of energetic flow structures on the aeolian transport of sediment and plastic debris","authors":"Manousos Valyrakis, Xiao Zhao, Thomas Pähtz, Zhen Li","doi":"arxiv-2409.03494","DOIUrl":"https://doi.org/arxiv-2409.03494","url":null,"abstract":"Recently, significant progress has been made in conceptually describing the\u0000dynamic aspects of coarse particle entrainment, which has been explored\u0000experimentally for open channel flows. The aim of this study is to extend the\u0000application of energy criterion to the low mobility aeolian transport of solids\u0000(including both natural sediment and anthropogenic debris such as plastics),\u0000ranging from incomplete (rocking) to full (rolling) entrainments. This is\u0000achieved by linking particle movements to energetic flow events, which are\u0000defined as flow structures with the ability to work on particles, setting them\u0000into motion. It is hypothesized that such events should impart sufficient\u0000energy to the particles, above a certain threshold value. The concept's\u0000validity is demonstrated experimentally, using a wind tunnel and laser distance\u0000sensor (LDS) to capture the dynamics of an individual target particle, exposed\u0000on a rough bed surface. Measurements are acquired at a high spatiotemporal\u0000resolution, and synchronously with the instantaneous air velocity at an\u0000appropriate distance upwind of the target particle, using a hot film\u0000anemometer. This enables the association of flow events with rocking and\u0000rolling entrainments. Furthermore, it is shown that rocking and rolling may\u0000have distinct energy thresholds. Estimates of the energy transfer efficiency,\u0000normalized by the drag coefficient, range over an order of magnitude (from\u0000about 0.001 to 0.0048 for rocking, up to about 0.01, for incipient rolling).\u0000The proposed event-based theoretical framework is a novel approach to\u0000characterizing the energy imparted from the wind to the soil surface and could\u0000have potential implications for modelling intermittent creep transport of\u0000coarse particles and related aeolian bedforms.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211794","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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