Essays about: "Deep Operator Networks"

Showing result 1 - 5 of 10 essays containing the words Deep Operator Networks.

1. 1. Deep Neural Networks as SurrogateModels for Fuel Performance Codes

   University essay from Uppsala universitet/Tillämpad kärnfysik

   Author : Wenhan Zhou; [2023]
   Keywords : Transuranus; AI; Nuclear Fuel Rods;

   Abstract : The core component of a nuclear power plant is the reactor and the fuel rods that supply it with fission fuel. Efficient and safe energy extraction is thus highly dependent on the reactor design and the conditions of the fuel rods. To anticipate high-quality operation and potential risks in advance, one must perform simulations on the fuel rods. READ MORE

3. 2. Deep learning of nonlinear development of unstable flame fronts

   University essay from Lunds universitet/Institutionen för energivetenskaper

   Author : Ludvig Nobel; [2023]
   Keywords : Technology and Engineering;

   Abstract : The purpose of this study is to investigate Machine Learning methods and their ability to learn the development of nonlinear unstable flame fronts due to diffusive-thermal instabilities. This task is performed by first numerically computing long time-sequences of solutions to the chaotic partial differential equation named Kuramoto-Sivashinsky equation which models such instabilities in a flame front. READ MORE

4. 3. Turbulent Boundary Layers Modelling with Deep Operator Networks

   University essay from KTH/Skolan för teknikvetenskap (SCI)

   Author : Yu-Cheng Lu; [2023]
   Keywords : Turbulent Boundary Layers; Pressure Gradient; Composite Profiles; Deep Operator Networks; Sensitivity Analysis Nyckelord på svenska;

   Abstract : This thesis project aims to advance the modelling of pressure gradient turbulent boundary layers (PG TBLs) and offer new insights into TBLs modelling. Previous analytical studies have explored various mathematical models, but this research introduces an extended unstacked Deep Operator Networks (DeepONets) architecture with double outputs and five branch parameters. READ MORE

5. 4. Solving Partial Differential Equations With Neural Networks

   University essay from Uppsala universitet/Matematiska institutionen

   Author : Håkan Karlsson Faronius; [2023]
   Keywords : Partial differential equations; neural networks; physics-informed neural networks; deep ritz method; fourier neural operator; importance sampling; inverse problems;

   Abstract : In this thesis three different approaches for solving partial differential equa-tions with neural networks will be explored; namely Physics-Informed NeuralNetworks, Fourier Neural Operators and the Deep Ritz method. Physics-Informed Neural Networks and the Deep Ritz Method are unsupervised machine learning methods, while the Fourier Neural Operator is a supervised method. READ MORE

6. 5. Anomalous Behavior Detection in Aircraft based Automatic Dependent Surveillance–Broadcast (ADS-B) system using Deep Graph Convolution and Generative model (GA-GAN)

   University essay from Linköpings universitet/Databas och informationsteknik

   Author : Jayesh Kenaudekar; [2022]
   Keywords : Intrusion detection aircraft aviation security adsb protocol AI deep learning machine learning graph generative model surveillance broadcast;

   Abstract : The Automatic Dependent Surveillance-Broadcast (ADS-B) is a key component of the Next Generation Air Transportation System (Next Gen) that manages the increasingly congested airspace and operation. From Jan 2020, the U.S. Federal Aviation Administration (FAA) mandated the use of (ADS-B) as a key component of Next Gen project. READ MORE