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Multidimensional tensor strategy for the inverse analysis of in-service bridge based on SHM data
The inverse analysis and evaluation of in-service bridges by considering structural health monitoring (SHM) data, which is something of a black box...
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Pore Tensor-Based Constitutive Model of Deep Coral Reef Limestone at High Loading Rates
The buried diagenesis and dolomitization in the deep stratum of coral reef island enable the Coral reef limestone (CRL) to exhibit a significant...
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Randomized Tensor Decomposition for Large-Scale Data Assimilation Problems for Carbon Dioxide Sequestration
Data assimilation methods are commonly used to predict petrophysical properties of deep saline aquifers for carbon dioxide sequestration studies....
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A fast imaging method for airborne gravity gradient data based on tensor invariants
Airborne gravity gradient data contain additional short-wavelength information about the buried geological bodies. This study develops a fast...
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Experimental Permeability Tensor for Fractured Porous Rocks
This chapter presents a novel petrophysical experiment for measuring the 3D permeability tensor at reservoir conditions in a fractured porous rock....
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A Non-linear Three-Dimensional Failure Criterion Based on Stress Tensor Distance
The basis of engineering stability evaluation lies in the study of the relationship between rock stress and strength. However, there is no unified...
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An intelligent optimized cyclone intensity prediction framework using satellite images
Weather prediction is the hottest topic in remote sensing to understand natural disasters and their intensity in an early stage. But in many cases,...
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A new approach for calculating the apparent resistivity tensor
The apparent resistivity tensor ρ B is an electromagnetic transfer function, which can be used to analyze and explain the underground electrical...
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Empirical prediction of hydraulic aperture of 2D rough fractures: a systematic numerical study
This study aims to propose an empirical prediction model of hydraulic aperture of 2D rough fractures through numerical simulations by considering the...
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Sea Surface Height Anomaly Prediction Based on Artificial Intelligence
Sea surface height anomaly (SSHA) refers to an essential parameter that can be used to monitor the oceans. Because of global warming and glacial...
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Fracture prediction method for narrow-azimuth seismic data of offshore streamer acquisition
Considering the constraints in the costs and efficiency of seismic exploration acquisition, marine hydrocarbon exploration mainly relies on...
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A Physics-informed Deep-learning Intensity Prediction Scheme for Tropical Cyclones over the Western North Pacific
Accurate prediction of tropical cyclone (TC) intensity is challenging due to the complex physical processes involved. Here, we introduce a new TC...
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Graph Convolutional Neural Network for Pressure Prediction in Water Distribution Network Sites
The safe operation of water distribution networks (WDNs) is crucial for ensuring the city dwellers’ living standards. Accurate and multi-step...
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Development of a Long-Range Hydrological Drought Prediction Framework Using Deep Learning
Long-range (1 to 6 months in advance) prediction of droughts is challenging due to its inherent complexity. In this study, we developed a Long-Range...
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Cluster Analysis of Moment Tensor Solutions and its Application to Rockburst Risk Assessment in Underground Coal Mines
High-magnitude events (HMEs) are commonly observed in underground mines, and they can lead to violent rock failures, such as rockbursts. While moment...
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Strength prediction model for water-bearing sandstone based on near-infrared spectroscopy
The strength of water-bearing rock cannot be obtained in real time and by nondestructive experiments, which is an issue at cultural relics protection...
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Coastal tsunami prediction in Tohoku region, Japan, based on S-net observations using artificial neural network
We present a novel method for coastal tsunami prediction utilizing a denoising autoencoder (DAE) model, one of the deep learning algorithms. Our...
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Prediction of ground-borne vibration induced by impact pile driving: numerical approach and experimental validation
Deep foundations are currently used in engineering practice to solve problems caused by weak geotechnical characteristics of the ground. Impact pile...
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Ultra-short-term prediction of LOD using LSTM neural networks
Earth orientation parameters (EOPs) are essential in geodesy, linking the terrestrial and celestial reference frames. Due to the time needed for data...
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Speeding up the reservoir simulation by real time prediction of the initial guess for the Newton-Raphson’s iterations
We study linear models for the prediction of the initial guess for the nonlinear Newton-Raphson solver. These models use one or more of the previous...