Preprints

Filtering by Subject: Computational Engineering

Challenges of applying an embedded domain specific language for performance portability to Earth system models

Yen-Sen Lu, Daniel Caviedes-Voullième, Olaf Stein, et al.

Published: 2024-02-26
Subjects: Computational Engineering, Earth Sciences

Weather and climate modeling, reliant on substantial computational resources, faces challenges of escalating resource demands and energy consumption as problem sizes and model complexity increase. Leveraging Graphics Processing Units (GPUs) for accelerated simulations demands performance portability across diverse High Performance Computing (HPC) architectures. The concept of embedded Domain [...]

On the economic feasibility of tidal range power plants

Konstantinos Pappas, Nguyen Quang Chien, Ilias Zilakos, et al.

Published: 2023-12-17
Subjects: Civil and Environmental Engineering, Computational Engineering, Engineering, Environmental Engineering, Hydraulic Engineering

The wave potential energy associated with tides presents a promising sustainable energy resource. Uncertainties on the economic case of tidal range power plants are a known bottleneck hindering the development of the industry. Significant costs depend on each design's general arrangement, which includes both mechanical components and the associated civil works. Research on tidal range structures [...]

Graphics Processing Unit Assisted Computation for a Gas-Phase Chemical Solver in a Regulatory Chemical Transport Model

Khanh Do, George Delic, Jose Rodríguez Borbón, et al.

Published: 2023-11-28
Subjects: Civil and Environmental Engineering, Computational Engineering

The Earth’s atmosphere is extremely complex due to the presence of several dynamic processes, such as dispersion, diffusion, deposition, and chemical reactions. There is a pressing need to improve the predictability of air quality models by integrating more of these scientific processes with an increasing number of chemical species into the mechanisms. These enhancements degrade the computational [...]

Physics-Informed Neural Networks Applied to Catastrophic Creeping Landslides

Ahmad Moeineddin, Carolina Segui, Stephan Dueber, et al.

Published: 2023-02-13
Subjects: Computational Engineering, Geotechnical Engineering

In this study, a new paradigm compared to traditional numerical approaches to solve the partial differential equation (PDE) that governs the thermo-poro-mechanical behavior of the shear band of deep-seated landslides, is presented. In particular, we show projections of the temperature inside the shear band as a proxy to estimate catastrophic failure of deep-seated landslides. A deep neural [...]

GANSim-surrogate: An integrated framework for conditional geomodelling and uncertainty analysis

Suihong Song, Dongxiao Zhang, Tapan Mukerji, et al.

Published: 2022-10-24
Subjects: Computational Engineering, Earth Sciences, Environmental Engineering, Fluid Dynamics, Geology, Geophysics and Seismology, Hydrology, Sedimentology

We propose a deep-learning framework (GANSim-surrogate) for conditioning subsurface geomodel realizations to static data and dynamic flow data. The static data includes well facies data, interpreted facies probability maps, and non-spatial global features, while dynamic data can include well data such as pressures and flow rates. The framework consists of a Convolutional Neural Network (CNN) [...]

Client-side Web-based Model Coupling using Basic Model Interface for Hydrology and Water Resources

Gregory James Ewing, Carlos Erazo Ramirez, Ashani Vaidya, et al.

Published: 2022-10-06
Subjects: Civil and Environmental Engineering, Computational Engineering, Other Engineering

A recent trend in hydroinformatics has been the growing number of data, models, and cyber tools which are web accessible, each aiming to improve common research tasks in hydrology through web technologies. Coupling web-based models and tools holds great promise for an integrated environment that can facilitate community participation, collaboration, and scientific replication. There are many [...]

HydroLang Markup Language: Community-Driven Web Components for Hydrological Analyses

Carlos Erazo Ramirez, Muhammed Yusuf Sermet, Ibrahim Demir

Published: 2022-08-25
Subjects: Civil and Environmental Engineering, Computational Engineering, Environmental Engineering, Science and Mathematics Education

We introduce HydroLang Markup Language (HL-ML), a programming interface that uses markup language to perform environmental analyses using the hydrological and environmental framework HydroLang. The software acts as a self-contained interface that uses HTML tags powered by the web components specification to generate simple hydrological computations that enable data analysis, visualization and [...]

Automated detection of microfossil fish teeth from slide images using combined deep learning models

Kazuhide Mimura, Shugo Minabe, Kentaro Nakamura, et al.

Published: 2022-04-20
Subjects: Computational Engineering, Sedimentology

Microfossil fish teeth, known as ichthyoliths, provide a key constraint on the depositional age and environment of deep-sea sediments, especially pelagic clays where siliceous and calcareous microfossils are rarely observed. However, traditional methods for the observation of ichthyoliths require considerable time and manual labor, which can hinder their wider application. In this study, we [...]

LSTM with forget gates optimized by Optuna for lithofacies prediction

Yohei Nishitsuji, Jalil Nasseri

Published: 2022-03-15
Subjects: Computational Engineering

One of major technical competitions in energy industry relates to how optimally deep-learning architectures we can design. Optimization of hyperparameters is treated as labor-intensive. However, it is important to tune the parameters especially when we deal with relatively small targets, yet high-impact consequences can be resulted. In this study, we adapt Optuna, the global optimizer, for tuning [...]

GANSim-3D for conditional geomodelling: theory and field application

Suihong Song, Tapan Mukerji, Jiagen Hou, et al.

Published: 2021-12-22
Subjects: Artificial Intelligence and Robotics, Computational Engineering, Geology, Hydrology, Numerical Analysis and Scientific Computing, Oil, Gas, and Energy, Theory and Algorithms, Water Resource Management

Geomodelling of subsurface reservoirs is important for water resources, hydrocarbon exploitation, and Carbon Capture and Storage (CCS). Traditional geostatistics-based approaches cannot abstract complex geological patterns and are thus not able to simulate very realistic earth models. We present a Generative Adversarial Networks (GANs)-based 3D reservoir simulation framework, GANSim-3D, which can [...]

Adaptive Mesh Refinement Strategies for a Novel Modelof Immiscible Fluid Flow in Fractures

Sobhan Hatami, Stuart Duncan Christopher Walsh

Published: 2021-12-13
Subjects: Civil and Environmental Engineering, Computational Engineering, Engineering

In this paper, we consider two Adaptive Mesh Refinement (AMR) methods to simulate flow through fractures using a novel multiphase model. The approach represents the fluid using a two-dimensional parallel-plate model that employs techniques adapted from lattice-Boltzmann simulations to track the fluid interface. Here, we discuss different mesh refinement strategies for the model and compare [...]

Optimizing nature-based solutions by combining social equity, hydro-environmental performance, and economic costs through a novel Gini coefficient

Cyndi V. Castro

Published: 2021-11-15
Subjects: Civil and Environmental Engineering, Civil Engineering, Computational Engineering, Engineering, Environmental Studies, Geographic Information Sciences, Geography, Nature and Society Relations, Operations Research, Systems Engineering and Industrial Engineering, Physical and Environmental Geography, Social and Behavioral Sciences, Systems Engineering

A robust multi-functional framework for widespread planning of nature-based solutions (NBS) must incorporate components of social equity and hydro-environmental performance in a cost-effective manner. NBS systems address stormwater mitigation by increasing on-site infiltration and evaporation through enhanced greenspace while also improving various components of societal well-being, such as [...]

Evaluating Short-Term Spatio-Temporal Tropospheric Variability in Multi-Temporal SAR Interferograms Using LES Models

Fengming Hu, Ramon Hanssen, Pier Siebesma, et al.

Published: 2021-07-13
Subjects: Aerospace Engineering, Atmospheric Sciences, Computational Engineering, Earth Sciences, Fluid Dynamics, Longitudinal Data Analysis and Time Series, Meteorology, Multivariate Analysis, Signal Processing

Atmospheric delay has a significant impact on synthetic aperture radar (SAR) interferometry, inducing spatial phase errors and decorrelation in extreme weather condition. For Low Earth Orbit (LEO) SAR missions, the atmosphere can be considered as being spatio-temporally frozen due to the short integration time. Geosynchronous (GEO) SAR missions, however, have short revisit times and extensive [...]

A damage model for the frictional shear failure of brittle materials in compression

Simon Philip Gill

Published: 2021-05-13
Subjects: Applied Mathematics, Computational Engineering, Earth Sciences, Engineering, Geology, Materials Science and Engineering, Physical Sciences and Mathematics

Damage models have been successfully employed for many decades in the modelling of tensile failure, where the crack surfaces separate as a crack grows. The advantage of this approach is that crack trajectories can be computed simply and efficiently on a fixed finite element mesh without explicit tracking. The development of damage models for shear failure in compression, where the crack faces [...]

Real-time Flood Mapping on Client-side Web Systems using HAND model

Anson Hu, Ibrahim Demir

Published: 2021-02-19
Subjects: Civil and Environmental Engineering, Computational Engineering, Engineering

The height above nearest drainage (HAND) model is frequently used to calculate properties of the soil as well as predict flood inundation extents. HAND is extremely useful due to its lack of reliance on prior data, as only the digital elevation model (DEM) is needed. It is close to optimal, running in linear or linearithmic time in the number of cells depending on the values of the heights. It [...]

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