1,678 research outputs found

    Undergraduate Catalog of Studies, 2023-2024

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    Graduate Catalog of Studies, 2023-2024

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    Data-driven analysis of crustal and subduction seismic environments using interpretation of deep learning-based generalized ground motion models

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    Studies on understanding the regional seismological differences based on the variations in the characteristics of the ground motion waves recorded during seismic events have provided independent insights into the different seismic environments of the world. This study aims to showcase the differences between three of the major seismic environments of the world including Japanese subduction, Chilean subduction, and Californian crustal. The study is based on developing deep learning (DL)-based surrogate generalized ground motion models (GGMMs) and analyzing them to understand the patterns between the earthquake source parameters and the resulting ground motion waveforms’ engineering characteristics. The GGMMs are developed using long short-term memory (LSTM) based recurrent neural networks (RNNs), which are trained using six earthquake source and site parameters as the inputs and a 25 × 1 vector of amplitude-, duration-, and energy-based ground motion intensity measures (IMs). The GGMMs are trained and evaluated using carefully selected large datasets of ground motion records from the Japanese subduction, Chilean subduction, and Californian crustal sources (∼2000 records from each source). The models are developed in two settings: i) three independent GGMMs using the three datasets of each source, ii) one combined GGMM using the combined dataset. While the former provides individual surrogate models of the regional seismic environments and allows relative comparison among the three environments, the latter acts as a global seismic surrogate model and allows comparison in absolute terms. The seismic environments are investigated by analyzing the two types of GGMMs using explainable artificial intelligence (XAI) and game theory based Shapley explanations (SHAP). As the direct physical study of the seismic environments is not generally feasible/practical, the proposed GGMMs surrogating the process becomes a source of knowledge. By interpreting them, inferences about the seismic environments are derived. Results indicate the peculiar nature of the earthquakes arising from the three seismic backgrounds, further emphasizing the importance of conducting independent regional seismic hazard and risk analysis. In particular, the role of magnitude and rupture distance is observed to have a significantly different impact on the different IMs of the three different environments. The study further sets a novel basis to utilize advanced DL and XAI methods in understanding convoluted physics and engineering phenomena.</p

    Undergraduate Catalog of Studies, 2023-2024

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    Graduate Catalog of Studies, 2023-2024

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    Determining the ages of sub-fossil cetacean remains, found in the Carse of Stirling, Scotland

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    During the 19th and early 20th centuries, sub-fossil cetacean remains were often discovered in the Firth of Forth, Central Scotland. These bones and skeletons of "Whales" were excavated from a recent, estuarine deposit (named "carse clay") and, within the biological and geological sciences, were not judged to be important. That palaeontological evidence is re-evaluated in this thesis. These cetacean remains have been preserved in an unusual marine environment and form an exceptional fossil assemblage, with almost no geological precedents. Why is it there? Whatever caused exceptional preservation in the Firth of Forth in the early Holocene (c. 9.5 – 2.5ka cal BP) can be best identified with chronological data. The ages of six sets of cetacean remains are determined in this thesis, by radiocarbon dating and stratigraphic inference. To reconstruct where a bone or skeleton had been found in the "carse" and then to identify any surviving elements in modern museum collections, archaic textual sources had to be thoroughly investigated. Radiocarbon dates from marine organisms require correction for "reservoir effects" and those applicable to mysticete cetaceans require careful consideration. The absolute dating evidence shows that no two "Whales" are the same age and that each died, and was then preserved, over the period 9.5 – 7.0ka cal BP. Therefore, a "disaster" (e.g. tsunami) or mass mortality is unlikely to have caused these remains to accumulate. A combination of physical processes and stable environmental conditions are more likely responsible, and might still permit exceptional preservation in the modern Firth of Forth. Actualistic experiment (observing if, and how, a cetacean carcass is preserved or dispersed on a modern tidal foreshore) would allow further insights into this cryptic palaeontological assemblage

    Natural and Technological Hazards in Urban Areas

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    Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events

    Undergraduate Catalog of Studies, 2022-2023

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    War and Policy: Investor Expectations on the Net-Zero Transition

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    This study employs novel text-based proxies to analyze corporate exposure to regulatory risks in the low-carbon transition. In response to the Russia-Ukraine war, stocks with higher transition risk outperformed, suggesting an expected slowdown in the transition. These effects were far more pronounced in the US than Europe, where renewable energy policy support was anticipated. The US Inflation Reduction Act (IRA) and the REPowerEU plan increased the value of firms with renewable energy opportunities, but the IRA also benefited higher transition risk firms. Overall, the findings highlight an international divergence in the energy transition pace

    Deep Learning for Subtle Volcanic Deformation Detection With InSAR Data in Central Volcanic Zone

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    Subtle volcanic deformations point to volcanic activities, and monitoring them helps predict eruptions. Today, it is possible to remotely detect volcanic deformation in mm/year scale thanks to advances in interferometric synthetic aperture radar (InSAR). This article proposes a framework based on a deep learning model to automatically discriminate subtle volcanic deformations from other deformation types in five-year-long InSAR stacks. Models are trained on a synthetic training set. To better understand and improve the models, explainable artificial intelligence (AI) analyses are performed. In initial models, Gradient-weighted Class Activation Mapping (Grad-CAM) linked new-found patterns of slope processes and salt lake deformations to false-positive detections. The models are then improved by fine-tuning (FT) with a hybrid synthetic-real data, and additional performance is extracted by low-pass spatial filtering (LSF) of the real test set. The t-distributed stochastic neighbor embedding (t-SNE) latent feature visualization confirmed the similarity and shortcomings of the FT set, highlighting the problem of elevation components in residual tropospheric noise. After fine-tuning, all the volcanic deformations are detected, including the smallest one, Lazufre, deforming 5 mm/year. The first time confirmed deformation of Cerro El Condor is observed, deforming 9.9–17.5 mm/year. Finally, sensitivity analysis uncovered the model’s minimal detectable deformation of 2 mm/year
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