Browsing SINTEF Open by Author "Rasheed, Adil"
Now showing items 1-20 of 56
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A Comprehensive Simulation Methodology for Fluid-Structure Interaction of Offshore Wind Turbines
Rasheed, Adil; Holdahl, Runar; Kvamsdal, Trond; Åkervik, Espen (Journal article; Peer reviewed, 2014)This paper gives an overview of a comprehensive simulation methodology for fluid-structure interaction (FSI) of offshore wind turbines that is being developed at the Applied Mathematics Department of SINTEF ICT. The ... -
A COMPUTATIONAL FRAMEWORK INVOLVING CFD AND DATA MINING TOOLS FOR ANALYZING DISEASE IN CAROTID ARTERY BIFURCATION
Tabib, Mandar; Rasheed, Adil; Fonn, Eivind (Chapter, 2017)Cardiovascular diseases, like Carotid Artery Disease and Coronary Artery Disease (CAD) are associated with the narrowing of artery due to build-up of fatty substances and cholesterol deposits (called plaque). Carotid Artery ... -
A full-scale 3D Vs 2.5D Vs 2D analysis of flow pattern and forces for an industrial-scale 5MW NREL reference wind-turbine
Tabib, Mandar; Rasheed, Adil; Siddiqui, Muhammad Salman; Kvamsdal, Trond (Journal article; Peer reviewed, 2017)NREL 5MW reference turbine, which is a popular, realistic and standardized industrial scale offshore turbine model, is used in this work for understanding the associated flow-complexities and for testing models. For such ... -
A Hybrid Analytics Paradigm Combining Physics-Based Modeling and Data-Driven Modeling to Accelerate Incompressible Flow Solvers
Rahman, Sk. Mashfiqur; San, Omer; Rasheed, Adil (Journal article; Peer reviewed, 2018)Numerical solution of the incompressible Navier–Stokes equations poses a significant computational challenge due to the solenoidal velocity field constraint. In most computational modeling frameworks, this divergence-free ... -
A Hybrid Approach for Model Order Reduction of Barotropic Quasi-Geostrophic Turbulence
Rahman, Sk. Mashfiqur; San, Omer; Rasheed, Adil (Journal article; Peer reviewed, 2018)We put forth a robust reduced-order modeling approach for near real-time prediction of mesoscale flows. In our hybrid-modeling framework, we combine physics-based projection Methods with neural network closures to account ... -
A step towards reduced order modelling of flow characterized by wakes using Proper Orthogonal Decomposition
Fonn, Eivind; Tabib, Mandar; Siddiqui, Muhammad Salman; Rasheed, Adil; Kvamsdal, Trond (Journal article; Peer reviewed, 2017)High fidelity simulations of flow can be quite demanding, involving up to O(106) to O(109) degrees of freedom, and several hours or days of computational time, even on powerful parllel architectures. These techniques become ... -
Analysis of Turbulent Wakes Behind Helicopter Hangars at Sola Airport
Sørli, Karstein; Tabib, Mandar; Rasheed, Adil (SINTEF Rapport;, Research report, 2015)Turbulence in the wake generated by airflow over buildings may produce complex airflow patterns in the downwind region. Examples include the recirculating flow and wind deficit areas behind airport buildings and their ... -
Anomaly detection in multivariate time series of drilling data
Altindal, Mehmet Cagri; Nivlet, Philippe; Tabib, Mandar Vasudeo; Rasheed, Adil; Kristiansen, Tron Golder; Khosravanian, Rasool (Peer reviewed; Journal article, 2024)Different clusters of abnormal activities often arise within same temporal domain of drilling operations. This contrasts with employing simplified scenarios, such as anomaly detection models for specific issues like stuck ... -
Applying Object Detection to Marine Data and Exploring Explainability of a Fully Convolutional Neural Network Using Principal Component Analysis
Stavelin, Peter Herman; Rasheed, Adil; San, Omer; Hestnes, Arne Johan (Peer reviewed; Journal article, 2021)With the rise of focus on man made changes to our planet and wildlife therein, more and more emphasis is put on sustainable and responsible gathering of resources. In an effort to preserve maritime wildlife the Norwegian ... -
Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach
Blakseth, Sindre Stenen; Rasheed, Adil; Kvamsdal, Trond; San, Omer (Peer reviewed; Journal article, 2022)Upcoming technologies like digital twins, autonomous, and artificial intelligent systems involving safety–critical applications require accurate, interpretable, computationally efficient, and generalizable models. ... -
Comparing Deep Reinforcement Learning Algorithms’ Ability to Safely Navigate Challenging Waters
Larsen, Thomas Nakken; Teigen, Halvor Ødegård; Laache, Torkel; Varagnolo, Damiano; Rasheed, Adil (Peer reviewed; Journal article, 2021)Reinforcement Learning (RL) controllers have proved to effectively tackle the dual objectives of path following and collision avoidance. However, finding which RL algorithm setup optimally trades off these two tasks is not ... -
Data-driven deconvolution for large eddy simulations of Kraichnan turbulence
Maulik, Romit; San, Omer; Rasheed, Adil; Vedula, Prakash (Journal article; Peer reviewed, 2018)In this article, we demonstrate the use of artificial neural networks as optimal maps which are utilized for convolution and deconvolution of coarse-grained fields to account for sub-grid scale turbulence effects. We ... -
Deep neural network enabled corrective source term approach to hybrid analysis and modeling
Blakseth, Sindre Stenen; Rasheed, Adil; Kvamsdal, Trond; San, Omer (Peer reviewed; Journal article, 2022)In this work, we introduce, justify and demonstrate the Corrective Source Term Approach (CoSTA)—a novel approach to Hybrid Analysis and Modeling (HAM). The objective of HAM is to combine physics-based modeling (PBM) and ... -
Demonstrating the impact of bidirectional coupling on the performance of an ocean-met model
Rasheed, Adil; Süld, Jakob Kristoffer; Tabib, Mandar; Kvamsdal, Trond; Kristiansen, Jørn (Journal article; Peer reviewed, 2017)The mass, momentum and energy fluxes between the atmosphere and ocean surface depend on the state of the ocean surface. The fluxes in turn can significantly alter the nature of the marine boundary layer and the state of ... -
Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions
Stadtmann, Florian; Rasheed, Adil; Kvamsdal, Trond; Johannessen, Kjetil Andre; San, Omer; Kölle, Konstanze; Tande, John Olav Giæver; Barstad, Idar; Benhamou, Alexis; Brathaug, Thomas; Christiansen, Tore; Firle, Anouk-Letizia; Fjeldly, Alexander; Frøyd, Lars; Gleim, Alexander; Høiberget, Alexander; Meissner, Catherine; Nygård, Guttorm; Olsen, Jørgen; Paulshus, Håvard; Rasmussen, Tore; Rishoff, Elling; Scibilia, Francesco; Skogås, John Olav (Peer reviewed; Journal article, 2023) -
Discovering Thermoelectric Materials Using Machine Learning: Insights and Challenges
Tabib, Mandar; Løvvik, Ole Martin; Johannessen, Kjetil Andre; Rasheed, Adil; Sagvolden, Espen; Rustad, Anne Marthine (Journal article; Peer reviewed, 2018)This work involves the use of combined forces of data-driven machine learning models and high fidelity density functional theory for the identification of new potential thermoelectric materials. The traditional method of ... -
Effect of turbulence intensity on the performance of an offshore vertical axis wind turbine
Siddiqui, Muhammad Salman; Rasheed, Adil; Kvamsdal, Trond; Tabib, Mandar (Journal article; Peer reviewed, 2015)Offshore wind energy is one of the most competitive renewable energy resources available to us, which until now been under- exploited. Most of the problems associated with wind farm installation like land acquisition, low ... -
Enhancing elasticity models with deep learning: A novel corrective source term approach for accurate predictions
Sørbø, Sondre; Blakseth, Sindre Stenen; Rasheed, Adil; Kvamsdal, Trond; San, Omer (Peer reviewed; Journal article, 2024) -
An environmental disturbance observer framework for autonomous surface vessels
Menges, Daniel; Rasheed, Adil (Peer reviewed; Journal article, 2023)This paper proposes a robust disturbance observer framework for maritime autonomous surface vessels considering model and measurement uncertainties. The core contribution lies in a nonlinear disturbance observer, reconstructing ... -
Fast divergence-conforming reduced basis methods for stationary and transient flow problems
Fonn, Eivind; van Brummelen, Harald; Kvamsdal, Trond; Rasheed, Adil (Peer reviewed; Journal article, 2020)Reduced basis methods (RB methods or RBMs) form one of the most promising techniques to deliver numerical solutions of parametrized PDEs in real-time with reasonable accuracy [1]. For the Navier-Stokes equation, RBMs based ...