Research on AI- and Simulation-Based Engineering at Exascale

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Visual identity (2)

Visual identity website social media accounts video etc created

Visual identity (1)

Visual identity website social media accounts video etc created

Communication and dissemination plan (1)

Dissemination and communication and standardization report

Educational portfolio document (1)

Periodically updated document describing the change of education portfolio in accordance to RAISEs developments and industrialacademic needs

Report on outcomes of WP3 use-cases (3)

Report on outcomes of WP3 use-cases

Report on porting & performance engineering (1)

Report on porting and performance engineering activities

Report on porting & performance engineering (2)

Report on porting and performance engineering activities

Communication and dissemination plan (3)

Dissemination and communication and standardization report

Communication and dissemination plan (2)

Dissemination and communication and standardization report

Report on novel AI technologies (3)

Report on novel use-case-overarching AI technologies

Benchmarking & support report (1)

Report on benchmarking AI technologies (QA) and on support activities

Benchmarking & support report (2)

Report on benchmarking AI technologies (QA) and on support activities

Support report (2)

Report on support activities

Report on porting & performance engineering (3)

Report on porting and performance engineering activities

Educational portfolio document (3)

Periodically updated document describing the change of education portfolio in accordance to RAISE’s developments and industrial/academic needs

Best practice guidelines/tutorials prototype

Best practice guidelines and tutorials for prototype systems are available

Network evaluation document (1)

Periodically updated documents i listing RAISEs connected networks their user groups contact persons and entry points ii evaluating the potential to include new communities iii describing information and service request transfer in RAISEs network

Report on outcomes of WP4 use-cases (3)

Report on outcomes of WP4 use-cases

Best practice guidelines/tutorials for MSA/heterogenous systems

Best practice guidelines and tutorials for the various HPC systems are available

Network evaluation document (3)

Periodically updated documents: (i) listing RAISE’s connected networks, their user groups, contact persons and entry points; (ii) evaluating the potential to include new communities; (iii) describing information and (service) request transfer in RAISE’s network

Support report (1)

Report on support activities

Network evaluation document (2)

Educational portfolio document (2)

Periodically updated document describing the change of education portfolio in accordance to RAISE’s developments and industrial/academic needs

Educational services platform

Accessible and extendible online educational services platform including webinars e learning MOOCs etc

Software framework layout plan (1)

Software layout plan for a unique AI framework

Software framework layout plan (2)

Software layout plan for a unique AI framework

Pubblicazioni

Practice and Experience in using Parallel and Scalable Machine Learning with Heterogenous Modular Supercomputing Architectures

Autori: Morris Riedel, Rocco Sedona, Chadi Barakat, Petur Einarsson, Reza Hassanian, Gabriele Cavallaro, Matthias Book, Helmut Neukirchen and Andreas Lintermann
Pubblicato in: 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2021
Editore: IEEE
DOI: 10.1109/ipdpsw52791.2021.00019

Challenges and Opportunities in the Adoption of High Performance Computing for Earth Observation in the Exascale Era

Autori: G. Cavallaro, R. Sedona, M. Riedel, A. Lintermann, K. Michielsen
Pubblicato in: Proceedings of the 2023 Conference on Big Data from Space (BiDS’23) - From foresight to impact, 2023, Pagina/e 25-28
Editore: Publications Office of the European Union
DOI: 10.2760/46796

Lagrangian Particle Tracking Data of a Straining Turbulent Flow Assessed Using Machine Learning and Parallel Computing

Autori: Hassanian, Reza; Riedel, Morris; Helgadottir, Asdis; Costa, Pedro; Bouhlali, Lahcen
Pubblicato in: Numero 3, 2022
Editore: ParCFD

Enabling Hyperparameter-Tuning of AI Models for Healthcare using the CoE RAISE Unique AI Framework for HPC

Autori: M. Riedel, C. Barakat, S. Fritsch, M. Aach, J. Busch, A. Lintermann, A. Schuppert, S. Brynjólfsson, H. Neukirchen, M. Book
Pubblicato in: 2023 46th MIPRO ICT and Electronics Convention (MIPRO), 2023, Pagina/e 435-440
Editore: IEEE
DOI: 10.23919/mipro57284.2023.10159755

Optimal Resource Allocation for Early Stopping-based Neural Architecture Search Methods

Autori: M. Aach, E. Inanc, R. Sarma, M. Riedel, A. Lintermann
Pubblicato in: Proceedings of the Second International Conference on Automated Machine Learning (AutoML), Numero Vol. 228, 2023, Pagina/e 12/1—-17
Editore: Proceedings of Machine Learning Research (PMLR)

Turbulent flow prediction: Lagrangian Particle Tracking-Deep Learning (LPT-DL) based models

Autori: R. Hassanian, A. Helgadottir, C. Velte, M. Riedel
Pubblicato in: APS 76th Annual Meeting of the Division of Fluid Dynamics, Bulletin of the American Physical Society, 2023
Editore: American Physical Society

Deep learning model capable of simulating the inertial particle path in particle-laden turbulent flow

Autori: R. Hassanian, P. Costa, A. Helgadottir, M. Riedel
Pubblicato in: 5th International Conference on Numerical Methods in Multiphase Flows (ICNMMF-5), 2024
Editore: University of Iceland

Parallel and Scalable Deep Learning to Reconstruct Actuated Turbulent Boundary Layer Flows. Part I: Investigation of Autoencoder-Based Trainings

Autori: R. Sarma, M. Albers, E. Inanc, M. Aach, W. Schröder, A. Lintermann
Pubblicato in: ParCFD2022 33rd International Conference on Parallel Computational Fluid Dynamics, 2022
Editore: Forschungszentrum Jülich GmbH

Educational Service Platform for Artificial Intelligence Resources

Autori: Ilmars Slaidins,Ieva Timrote,Viktors Zagorskis and Lauris Cikovskis
Pubblicato in: 2022 31st Annual Conference of the European Association for Education in Electrical and Information Engineering (EAEEIE), 2022
Editore: IEEE
DOI: 10.1109/eaeeie54893.2022.9820214

Quantum Support Vector Machine Algorithms for Remote Sensing Data Classification

Autori: Amer Delilbasic; Gabriele Cavallaro; Madita Willsch; Farid Melgani; Morris Riedel; Kristel Michielsen
Pubblicato in: IEEE 2608-2611 (2021). doi:10.1109/IGARSS47720.2021.9554802, Numero 1, 2021
Editore: IEEE
DOI: 10.1109/igarss47720.2021.9554802

Speed-Up of Machine Learning for Sound Localization via High-Performance Computing

Autori: Eric Michael Sumner, Marcel Aach, Andreas Lintermann, Runar Unnthorsson, Morris Riedel
Pubblicato in: 2022 26th International Conference on Information Technology (IT), Numero 585, 2022, Pagina/e 1-4, ISBN 978-1-6654-2127-0
Editore: IEEE
DOI: 10.1109/it54280.2022.9743519

A proposed hybrid two-stage DL-HPC method for wind speed forecasting: using the first average forecast output for long-term forecasting

Autori: Hassanian, R. ; Helgadottir, A. ; Aach, M. ; Lintermann, A. ; Riedel, M.
Pubblicato in: 2023
Editore: IACM Computational Fluids Conference (CFC2023)

Short Paper: Accelerating Hyperparameter Optimization Algorithms with Mixed Precision

Autori: Marcel Aach, Rakesh Sarma, Eray Inanc, Morris Riedel, Andreas Lintermann
Pubblicato in: Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, 2024, Pagina/e 1776-1779
Editore: ACM
DOI: 10.1145/3624062.3624259

Replicating Human Sound Localization with a Multi-Layer Perceptron

Autori: E. M. Sumner, R. Unnthorsson, M. Riedel
Pubblicato in: Proceedings of the 19th Sound and Music Computing Conference, 2022
Editore: Zenodo
DOI: 10.5281/zenodo.6797854

Accelerating Hyperparameter Tuning of a Deep Learning Model for Remote Sensing Image Classification

Autori: Aach, Marcel; Sedona, Rocco; Lintermann, Andreas; Cavallaro, Gabriele; Neukirchen, Helmut; Riedel, Morris
Pubblicato in: 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022, Kuala Lumpur, Malaysia, 2022-07-17 - 2022-07-22, Numero 2, 2022, ISSN 2022-03638
Editore: 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022
DOI: 10.1109/igarss46834.2022.9883257

The Capability of Recurrent Neural Networks to Predict Turbulence Flow via Spatiotemporal Features

Autori: Reza Hassanian, Morris Riedel, Lahcen Bouhlali
Pubblicato in: 2022 IEEE 10th Jubilee International Conference on Computational Cybernetics and Cyber-Medical Systems (ICCC), 2022, ISBN 978-1-6654-8177-9
Editore: IEEE
DOI: 10.1109/iccc202255925.2022.9922754

AI4HPC: Library to Train AI Models on HPC Systems Using CFD Datasets

Autori: E. Inanc, R. Sarma, M. Aach, R. Sedona, A. Lintermann
Pubblicato in: Workshop on Advancing Neural Network Training at 37th Conference on Neural Information Processing Systems (WANT@NeurIPS 2023), 2023
Editore: OpenReview

A Hybrid Quantum-Classical Workflow for Hyperparameter Optimization of Neural Net-works

Autori: M. Aach, E. Wulff, E. Pasetto, A. Delilbasic, R. Sarma, E. Inanc, M. Girone, M. Riedel, A. Linter- mann
Pubblicato in: ISC High Performance 2023, ISC’23, 2023
Editore: Forschungszentrum Jülich GmbH

An Automatic Approach for the Production of a Time Series of Consistent Land-Cover Maps Based on Long-Short Term Memory

Autori: Rocco Sedona, Claudia Paris, Liang Tian, Morris Riedel, Gabriele Cavallaro
Pubblicato in: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, 2022, Pagina/e 203-206
Editore: IEEE
DOI: 10.1109/igarss46834.2022.9883655

Practice and Experience in Using Parallel and Scalable Machine Learning in Remote Sensing from HPC Over Cloud to Quantum Computing

Autori: Morris Riedel, Gabriele Cavallaro, Jon Atli Benediktsson
Pubblicato in: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Numero 11, 2022, Pagina/e 1571-1574, ISSN 2153-7003
Editore: IEEE
DOI: 10.1109/igarss47720.2021.9554656

A Case Study on Coupling OpenFOAM with Different Machine Learning Frameworks

Autori: Fabian Orland, Kim Sebastian Brose, Julian Bissantz, Federica Ferraro, Christian Terboven, Christian Hasse
Pubblicato in: 2022 IEEE/ACM International Workshop on Artificial Intelligence and Machine Learning for Scientific Applications (AI4S), Numero 52, 2023, Pagina/e 7-12
Editore: IEEE
DOI: 10.1109/ai4s56813.2022.00007

Mechanical Elements Analysis of Stewart Platform: Computational Approach

Autori: Reza Hassanian and Morris Riedel
Pubblicato in: International Journal of Science and Research, 2022, ISSN 2319-7064
Editore: International Journal of Science and Research

Hyperparameter optimization of data-driven AI models on HPC systems

Autori: Eric Wulff, Maria Girone, Joosep Pata
Pubblicato in: Journal of Physics: Conference Series, Numero 2438, 2023, Pagina/e 012092, ISSN 1742-6588
Editore: Institute of Physics
DOI: 10.1088/1742-6596/2438/1/012092

Wind Velocity and Forced Heat Transfer Model for Photovoltaic Module

Autori: Reza Hassanian, Nashmin Yeganeh, Morris Riedel
Pubblicato in: Fluids, Numero 9, 2024, Pagina/e 17, ISSN 2311-5521
Editore: MDPI
DOI: 10.3390/fluids9010017

Deep Learning Forecasts a Strained Turbulent Flow Velocity Field in Temporal Lagrangian Framework: Comparison of LSTM and GRU

Autori: Reza Hassanian, Ásdís Helgadóttir, Morris Riedel
Pubblicato in: Fluids, Numero 7, 2024, Pagina/e 344, ISSN 2311-5521
Editore: MDPI
DOI: 10.3390/fluids7110344

Modeling the wall shear stress in large-eddy simulation using graph neural networks

Autori: Dorian Dupuy, Nicolas Odier, Corentin Lapeyre, Dimitrios Papadogiannis
Pubblicato in: Data-Centric Engineering, Numero 4, 2023, ISSN 2632-6736
Editore: Cambridge Core
DOI: 10.1017/dce.2023.2

AI-assisted modeling of capillary-driven droplet dynamics

Autori: Andreas D. Demou, Nikos Savva
Pubblicato in: Data-Centric Engineering, Numero 4, 2023, Pagina/e e24, ISSN 2632-6736
Editore: Cambridge University Press
DOI: 10.1017/dce.2023.19

A Single-Step Multiclass SVM Based on Quantum Annealing for Remote Sensing Data Classification

Autori: Amer Delilbasic, Bertrand Le Saux, Morris Riedel, Kristel Michielsen, Gabriele Cavallaro
Pubblicato in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Numero 17, 2024, Pagina/e 1434-1445, ISSN 1939-1404
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/jstars.2023.3336926

Buckling Assessment in the Dynamics Mechanisms, Stewart Platform Case Study: In the Context of Loads and Joints, Deflection Positions Gradient

Autori: Reza Hassanian, Morris Riedel
Pubblicato in: Computation, Numero 11, 2023, Pagina/e 227, ISSN 2079-3197
Editore: MDPI
DOI: 10.3390/computation11110227

HPC-enabling technologies for high-fidelity combustion simulations

Autori: Daniel Mira, Eduardo J. Pérez-Sánchez, Ricard Borrell, Guillaume Houzeaux
Pubblicato in: Proceedings of the Combustion Institute, Numero 39, 2024, Pagina/e 5091-5125, ISSN 1540-7489
Editore: Combustion Institute
DOI: 10.1016/j.proci.2022.07.222

Deciphering the dynamics of distorted turbulent flows: Lagrangian particle tracking and chaos prediction through transformer-based deep learning models

Autori: R. Hassanian, H. Myneni, Á. Helgadóttir, M. Riedel
Pubblicato in: Physics of Fluids, Numero 35, 2023, Pagina/e 075118, ISSN 1070-6631
Editore: American Institute of Physics
DOI: 10.1063/5.0157897

Direct numerical simulations of methane, ammonia-hydrogen and hydrogen turbulent premixed flames

Autori: Victor Coulon, Jessica Gaucherand, Victor Xing, Davide Laera, Corentin Lapeyre, Thierry Poinsot
Pubblicato in: Combustion and Flame, Numero Volume 256, 2023, ISSN 0010-2180
Editore: Elsevier BV
DOI: 10.1016/j.combustflame.2023.112933

Developing an Artificial Intelligence-Based Representation of a Virtual Patient Model for Real-Time Diagnosis of Acute Respiratory Distress Syndrome

Autori: Chadi S. Barakat, Konstantin Sharafutdinov, Josefine Busch, Sina Saffaran, Declan G. Bates, Jonathan G. Hardman, Andreas Schuppert, Sigurður Brynjólfsson, Sebastian Fritsch, Morris Riedel
Pubblicato in: Diagnostics, Numero 13, 2023, Pagina/e 2098, ISSN 2075-4418
Editore: MDPI
DOI: 10.3390/diagnostics13122098

Machine Learning for Particle Flow Reconstruction at CMS

Autori: Joosep Pata, Javier Duarte, Farouk Mokhtar, Eric Wulff, Jieun Yoo, Jean-Roch Vlimant, Maurizio Pierini, Maria Girone
Pubblicato in: Journal of Physics: Conference Series, Numero 2438, 2023, Pagina/e 012100, ISSN 1742-6588
Editore: Institute of Physics
DOI: 10.1088/1742-6596/2438/1/012100

A High-Performance Multispectral Adaptation GAN for Harmonizing Dense Time Series of Landsat-8 and Sentinel-2 Images

Autori: Rocco Sedona, Claudia Paris, Gabriele Cavallaro, Lorenzo Bruzzone and Morris Riedel
Pubblicato in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, ISSN 1939-1404
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/jstars.2021.3115604

Surrogate‐based optimization for active drag reduction of turbulent boundary layer flows

Autori: Fabian Hübenthal, Marian Albers, Matthias Meinke, Wolfgang Schröder
Pubblicato in: PAMM, Numero 23, 2024, ISSN 1617-7061
Editore: Wiley
DOI: 10.1002/pamm.202300190

Analysis of Chest X-ray for COVID-19 Diagnosis as a Use Case for an HPC-Enabled Data Analysis and Machine Learning Platform for Medical Diagnosis Support

Autori: Chadi Barakat; Marcel Aach; Andreas Schuppert; Sigurður Brynjólfsson; Sebastian Fritsch; Morris Riedel
Pubblicato in: Diagnostics, Numero Volume 13, Numero 3, March 2023, 2023, Pagina/e Basel, Switzerland, ISSN 2075-4418
Editore: MDPI
DOI: 10.3390/diagnostics13030391

Implicit Equation for Photovoltaic Module Temperature and Efficiency via Heat Transfer Computational Model

Autori: Reza Hassanian, Morris Riedel, Asdis Helgadottir, Nashmin Yeganeh and Runar Unnthorsson
Pubblicato in: Thermo, 2022, ISSN 2673-7264
Editore: MDPI
DOI: 10.3390/thermo2010004

An experiment generates a specified mean strained rate turbulent flow: Dynamics of particles

Autori: R. Hassanian, Á. Helgadóttir, L. Bouhlali, M. Riedel
Pubblicato in: Physics of Fluids, Numero 35, 2023, Pagina/e 015124, ISSN 1070-6631
Editore: American Institute of Physics
DOI: 10.1063/5.0134306

A Review in Context to Wind Effect on NOCT Model for Photovoltaic Panel

Autori: Reza Hassanian, Morris Riedel and Nashmin Yeganeh
Pubblicato in: Journal of Solar and Photoenergy Systems, 2022, ISSN 2577-8374
Editore: Crimson Publishers

Kernel Approximation on a Quantum Annealer for Remote Sensing Regression Tasks

Autori: Edoardo Pasetto, Morris Riedel, Kristel Michielsen, Gabriele Cavallaro
Pubblicato in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Numero 17, 2024, Pagina/e 3262-3269, ISSN 1939-1404
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/jstars.2024.3350385

Optimizing Wind Energy Production: Leveraging Deep Learning Models Informed with On-Site Data and Assessing Scalability through HPC

Autori: Reza Hassanian, Abdollah Shahinfar, Ásdís Helgadóttir, Morris Riedel
Pubblicato in: Acta Polytechnica Hungarica, Numero 21, 2024, Pagina/e 45-56, ISSN 1785-8860
Editore: Obuda University
DOI: 10.12700/aph.21.9.2024.9.4

Model Performance Prediction for Hyperparameter Optimization of Deep Learning Models Using High Performance Computing and Quantum Annealing

Autori: Juan Pablo García Amboage, Eric Wulff, Maria Girone, Tomás F. Pena
Pubblicato in: EPJ Web of Conferences, Numero 295, 2024, Pagina/e 12005, ISSN 2100-014X
Editore: EDP science
DOI: 10.1051/epjconf/202429512005

Toward the Production of Spatiotemporally Consistent Annual Land Cover Maps Using Sentinel-2 Time Series

Autori: Rocco Sedona, Claudia Paris, Jan Ebert, Morris Riedel, Gabriele Cavallaro
Pubblicato in: IEEE Geoscience and Remote Sensing Letters, Numero 20, 2024, Pagina/e 1-5, ISSN 1545-598X
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/lgrs.2023.3329428

Automated surgery planning for an obstructed nose by combining computational fluid dynamics with reinforcement learning

Autori: Mario Rüttgers, Moritz Waldmann, Klaus Vogt, Justus Ilgner, Wolfgang Schröder, Andreas Lintermann
Pubblicato in: Computers in Biology and Medicine, Numero 173, 2024, Pagina/e 108383, ISSN 0010-4825
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.compbiomed.2024.108383

Robustness evaluation of large-scale machine learning-based reduced order models for reproducing flow fields

Autori: Aito Higashida, Kazuto Ando, Mario Rüttgers, Andreas Lintermann, Makoto Tsubokura
Pubblicato in: Future Generation Computer Systems, Numero 159, 2024, Pagina/e 243-254, ISSN 0167-739X
Editore: Elsevier BV
DOI: 10.1016/j.future.2024.05.005

Reference dataset and benchmark for reconstructing laser parameters from on-axis video in powder bed fusion of bulk stainless steel

Autori: Cyril Blanc, Ayyoub Ahar, Kurt De Grave
Pubblicato in: Additive Manufacturing Letters, Numero 7, 2023, Pagina/e 100161, ISSN 2772-3690
Editore: Elsevier
DOI: 10.1016/j.addlet.2023.100161

A Practical Approach for Estimating the Optimum Tilt Angle of a Photovoltaic Panel for a Long Period—Experimental Recorded Data

Autori: Reza Hassanian, Morris Riedel, Nashmin Yeganeh and Runar Unnthorsson
Pubblicato in: Solar, 2021, ISSN 2673-9941
Editore: MDPI
DOI: 10.3390/solar1010005

Leading-Edge Erosion and Floating Particles: Stagnation Point Simulation in Particle-Laden Turbulent Flow via Lagrangian Particle Tracking

Autori: Reza Hassanian, Morris Riedel
Pubblicato in: Machines, Numero 11, 2023, Pagina/e 566, ISSN 2075-1702
Editore: MDPI
DOI: 10.3390/machines11050566

Distributed hybrid quantum-classical performance prediction for hyperparameter optimization

Autori: Eric Wulff, Juan Pablo Garcia Amboage, Marcel Aach, Thorsteinn Eli Gislason, Thorsteinn Kristinn Ingolfsson, Tomas Kristinn Ingolfsson, Edoardo Pasetto, Amer Delilbasic, Morris Riedel, Rakesh Sarma, Maria Girone, Andreas Lintermann
Pubblicato in: Quantum Machine Intelligence, Numero 6, 2024, ISSN 2524-4906
Editore: Springer
DOI: 10.1007/s42484-024-00198-5

Hybrid AI-Analytical Modeling of Droplet Dynamics on Inclined Heterogeneous Surfaces

Autori: Andreas D. Demou, Nikos Savva
Pubblicato in: Mathematics, Numero 12, 2024, Pagina/e 1188, ISSN 2227-7390
Editore: MDPI
DOI: 10.3390/math12081188

Turbulent Flow Prediction-Simulation: Strained Flow with Initial Isotropic Condition Using a GRU Model Trained by an Experimental Lagrangian Framework, with Emphasis on Hyperparameter Optimization

Autori: Reza Hassanian, Marcel Aach, Andreas Lintermann, Ásdís Helgadóttir, Morris Riedel
Pubblicato in: Fluids, Numero 9, 2024, Pagina/e 84, ISSN 2311-5521
Editore: MDPI
DOI: 10.3390/fluids9040084

Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors

Autori: Pata, Joosep; Wulff, Eric; Mokhtar, Farouk; Southwick, David; Zhang, Mengke; Girone, Maria; Duarte, Javier
Pubblicato in: Communications Physics, Numero 124, 2024, ISSN 2399-3650
Editore: Communications Physics
DOI: 10.1038/s42005-024-01599-5

Large scale performance analysis of distributed deep learning frameworks for convolutional neural networks

Autori: Marcel Aach, Eray Inanc, Rakesh Sarma, Morris Riedel & Andreas Lintermann
Pubblicato in: Journal of Big Data, 2023, ISSN 2196-1115
Editore: Springer
DOI: 10.1186/s40537-023-00765-w

Iceland wind farm assessment case study and development: An empirical data from wind and wind turbine

Autori: Reza Hassanian, Ásdís Helgadóttir, Morris Riedel
Pubblicato in: Cleaner Energy Systems, Numero 4, 2023, Pagina/e 100058, ISSN 2772-7831
Editore: Elsevier
DOI: 10.1016/j.cles.2023.100058

Refining computer tomography data with super-resolution networks to increase the accuracy of respiratory flow simulations

Autori: Xin Liu, Mario Rüttgers, Alessio Quercia, Romain Egele, Elisabeth Pfaehler, Rushikesh Shende, Marcel Aach, Wolfgang Schröder, Prasanna Balaprakash, Andreas Lintermann
Pubblicato in: Future Generation Computer Systems, Numero 159, 2024, Pagina/e 474-488, ISSN 0167-739X
Editore: Elsevier BV
DOI: 10.1016/j.future.2024.05.020

A Level Set-Based Actuator Disc Model for Turbine Realignment in Wind Farm Simulation: Meshing, Convergence and Applications

Autori: Abel Gargallo-Peiró, Gonzalo Revilla, Matias Avila, Guillaume Houzeaux
Pubblicato in: Energies, Numero 15, 2024, Pagina/e 8877, ISSN 1996-1073
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/en15238877

Numerical Investigation on the Acceleration Vibration Response of Linear Actuator

Autori: Reza Hassanian, Morris Riedel and Nashmin Yeganeh
Pubblicato in: Open Access Library Journal, 2022, ISSN 2333-9705
Editore: Scientific Research Publishing

CoE RAISE - data for actuated turbulent boundary layer flows

Autori: M. Albers, P. S. Meysonnat, D. Fernex, R. Seemaan, B. Noack, W. Schröder, A. Lintermann
Pubblicato in: 2023
Editore: EUDAT / Forschungszentrum Jülich GmbH
DOI: 10.34730/5dbc8e35f21241d0889906136cf28d26

AI4HPC

Autori: E. Inanc, R. Sarma, M. Aach, A. Lintermann
Pubblicato in: 2023
Editore: Zenodo
DOI: 10.5281/zenodo.7705417

Simulated datasets for detector and particle flow reconstruction: CLIC detector

Autori: J. Pata, E. Wulff, J. Duarte, F. Mokhtar, M. Zhang, M. Girone, D. Southwick
Pubblicato in: 2023
Editore: CERN
DOI: 10.5281/zenodo.8260741

Parallel Computing Accelerates Sequential Deep Networks Model in Turbulent Flow Forecasting

Autori: R. Hassanian, A. Helgadottir, M. Riedel
Pubblicato in: The International Conference for High Performance Computing, Networking, Storage, and Analysis, SC22, 2022
Editore: SC 2022

Correction to: Machine-Learning-Based Control of Perturbed and Heated Channel Flows

Autori: Mario Rüttgers, Moritz Waldmann, Wolfgang Schröder, Andreas Lintermann
Pubblicato in: Lecture Notes in Computer Science, High Performance Computing, 2022, Pagina/e C2-C2
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-90539-2_37

Design and Evaluation of Parallel and Scalable Machine Learning Research in Biomedical Modelling Applications

Autori: Barakat, Chadi
Pubblicato in: 2023, ISBN 978-9935-9697-9-8
Editore: University of Iceland
DOI: 10.34734/fzj-2023-02488

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