2021
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| Waldmann, Moritz; Grosch, Alice; Witzler, Christian; Lehner, Matthias; Benda, Odo; Koch, Walter; Vogt, Klaus; Kohn, Christopher; Schröder, Wolfgang; Göbbert, Jens Henrik; Lintermann, Andreas An effective simulation- and measurement-based workflow for enhanced diagnostics in rhinology Artikel In: Medical & Biological Engineering & Computing , 2021. @article{Waldmann2021,
title = {An effective simulation- and measurement-based workflow for enhanced diagnostics in rhinology},
author = {Waldmann, Moritz and Grosch, Alice and Witzler, Christian and Lehner, Matthias and Benda, Odo and Koch, Walter and
Vogt, Klaus and Kohn, Christopher and Schröder, Wolfgang and Göbbert, Jens Henrik and Lintermann, Andreas },
editor = {Springer },
url = {https://link.springer.com/content/pdf/10.1007/s11517-021-02446-3.pdf},
doi = {10.1007/s11517-021-02446-3},
year = {2021},
date = {2021-12-23},
urldate = {2021-12-23},
journal = {Medical & Biological Engineering & Computing },
abstract = {Physics-based analyses have the potential to consolidate and substantiate medical diagnoses in rhinology. Such methods are frequently subject to intense investigations in research. However, they are not used in clinical applications, yet. One issue preventing their direct integration is that these methods are commonly developed as isolated solutions which do not consider the whole chain of data processing from initial medical to higher valued data. This manuscript presents a workflow that incorporates the whole data processing pipeline based on a Jupyter environment. Therefore, medical image data are fully automatically pre-processed by machine learning algorithms. The resulting geometries employed for the simulations on high-performance computing systems reach an accuracy of up to 99.5% compared to manually segmented geometries. Additionally, the user is enabled to upload and visualize 4-phase rhinomanometry data. Subsequent analysis and visualization of the simulation outcome extend the results of standardized diagnostic methods by a physically sound interpretation. Along with a detailed presentation of the methodologies, the capabilities of the workflow are demonstrated by evaluating an exemplary medical case. The pipeline output is compared to 4-phase rhinomanometry data. The comparison underlines the functionality of the pipeline. However, it also illustrates the influence of mucosa swelling on the simulation.},
keywords = {Computational Fluid Dynamics, High performance computing, Machine Learning, Rhinology},
pubstate = {published},
tppubtype = {article}
}
Physics-based analyses have the potential to consolidate and substantiate medical diagnoses in rhinology. Such methods are frequently subject to intense investigations in research. However, they are not used in clinical applications, yet. One issue preventing their direct integration is that these methods are commonly developed as isolated solutions which do not consider the whole chain of data processing from initial medical to higher valued data. This manuscript presents a workflow that incorporates the whole data processing pipeline based on a Jupyter environment. Therefore, medical image data are fully automatically pre-processed by machine learning algorithms. The resulting geometries employed for the simulations on high-performance computing systems reach an accuracy of up to 99.5% compared to manually segmented geometries. Additionally, the user is enabled to upload and visualize 4-phase rhinomanometry data. Subsequent analysis and visualization of the simulation outcome extend the results of standardized diagnostic methods by a physically sound interpretation. Along with a detailed presentation of the methodologies, the capabilities of the workflow are demonstrated by evaluating an exemplary medical case. The pipeline output is compared to 4-phase rhinomanometry data. The comparison underlines the functionality of the pipeline. However, it also illustrates the influence of mucosa swelling on the simulation. |
| Inthavong, Kiao; Wong, Eugene; Tu, Jiyuan; Singh, Narinder (Hrsg.) Clinical and Biomedical Engineering in the Human Nose Buch Springer, 2021, ISBN: 978-981-15-6716-2. @book{inthavong2021clinicalb,
title = {Clinical and Biomedical Engineering in the Human Nose},
editor = {Inthavong, Kiao and Wong, Eugene and Tu, Jiyuan and Singh, Narinder},
url = {https://link.springer.com/book/10.1007/978-981-15-6716-2#toc},
isbn = {978-981-15-6716-2},
year = {2021},
date = {2021-01-01},
publisher = {Springer},
abstract = {This book explores computational fluid dynamics in the context of the human nose, allowing readers to gain a better understanding of its anatomy and physiology and integrates recent advances in clinical rhinology, otolaryngology and respiratory physiology research. It focuses on advanced research topics, such as virtual surgery, AI-assisted clinical applications and therapy, as well as the latest computational modeling techniques, controversies, challenges and future directions in simulation using CFD software. Presenting perspectives and insights from computational experts and clinical specialists (ENT) combined with technical details of the computational modeling techniques from engineers, this unique reference book will give direction to and inspire future research in this emerging field.},
keywords = {Computational Fluid Dynamics, Convolutional Neural Networks, Nasal cavity flows, Respiratory Flow Computation},
pubstate = {published},
tppubtype = {book}
}
This book explores computational fluid dynamics in the context of the human nose, allowing readers to gain a better understanding of its anatomy and physiology and integrates recent advances in clinical rhinology, otolaryngology and respiratory physiology research. It focuses on advanced research topics, such as virtual surgery, AI-assisted clinical applications and therapy, as well as the latest computational modeling techniques, controversies, challenges and future directions in simulation using CFD software. Presenting perspectives and insights from computational experts and clinical specialists (ENT) combined with technical details of the computational modeling techniques from engineers, this unique reference book will give direction to and inspire future research in this emerging field. |
2020
|
| Grosch, Alice; Waldmann, Moritz; Göbbert, Jens Henrik; Lintermann, Andreas A Web-Based Service Portal to Steer Numerical Simulations on High-Performance Computers Proceedings Article In: Samo Mahnič-Kalamiza Tomaž Jarm, Aleksandra Cvetkoska (Hrsg.): 8th European Medical and Biological Engineering Conference (=
EMBEC 2020), IFMBE Proceedings, S. 57-65, Ljubljana, 2020. @inproceedings{Grosch2021,
title = {A Web-Based Service Portal to Steer Numerical Simulations on High-Performance Computers},
author = {Grosch, Alice and Waldmann, Moritz and Göbbert, Jens Henrik and Lintermann, Andreas},
editor = {Tomaž Jarm, Samo Mahnič-Kalamiza, Aleksandra Cvetkoska, Damijan Miklavčič},
url = {https://link.springer.com/chapter/10.1007%2F978-3-030-64610-3_8},
doi = {10.1007/978-3-030-64610-3_8},
year = {2020},
date = {2020-11-30},
booktitle = {8th European Medical and Biological Engineering Conference (=
EMBEC 2020), IFMBE Proceedings},
pages = {57-65},
address = {Ljubljana},
abstract = {Benefiting and accessing high-performance computing resources can be quite difficult. Unlike domain scientists with a background in computational science, non-experts coming from, e.g., various medical fields, have almost no chance to run numerical simulations on large-scale systems. To provide easy access and a user-friendly interface to supercomputers, a web-based service portal, which under the hood takes care of authentication, authorization, job submission, and interaction with a simulation framework is presented. The service is exemplary developed around a simulation framework capable of efficiently running computational fluid dynamics simulations on high-performance computers. The framework uses a lattice-Boltzmann method to simulate and analyze respiratory flows. The implementation of such a web-portal allows to steer the simulation and represents a new diagnostic tool in the field of ear, nose, and throat treatment.},
keywords = {Computational Fluid Dynamics, High-performance computing, Lattice-Boltzmann method, Respiratory flows, Service portal},
pubstate = {published},
tppubtype = {inproceedings}
}
Benefiting and accessing high-performance computing resources can be quite difficult. Unlike domain scientists with a background in computational science, non-experts coming from, e.g., various medical fields, have almost no chance to run numerical simulations on large-scale systems. To provide easy access and a user-friendly interface to supercomputers, a web-based service portal, which under the hood takes care of authentication, authorization, job submission, and interaction with a simulation framework is presented. The service is exemplary developed around a simulation framework capable of efficiently running computational fluid dynamics simulations on high-performance computers. The framework uses a lattice-Boltzmann method to simulate and analyze respiratory flows. The implementation of such a web-portal allows to steer the simulation and represents a new diagnostic tool in the field of ear, nose, and throat treatment. |
| Koch, Walter The Rhinodiagnost Project - Concept and Implementation of a Nasal Airflow Simulator Sonstige EMBEC Abstract Book Contribution, 2020, ISBN: 978-961-243-411-3. @misc{WKo20,
title = {The Rhinodiagnost Project - Concept and Implementation of a Nasal Airflow Simulator},
author = {Koch, Walter},
editor = {Tomaž Jarm, Samo Mahnič-Kalamiza, Aleksandra Cvetkoska, Damijan Miklavčič},
url = {https://www.embec2020.org/wp-content/uploads/2020/11/EMBEC2020_Book_of_Abstracts.pdf},
isbn = {978-961-243-411-3},
year = {2020},
date = {2020-11-30},
abstract = {The RHINODIAGNOST services shall be organized in a rapid network providing new, additional decision aids, such as 3D models and flow simulations, for ENT physicians and radiologists” (taken from: http://www.rhinodiagnost.eu ). The Austrian coordinator of the Rhinodiagnost Project, AIT – Applied Information Technique Research Inc., developed an experimental station which allows the simulation of airflow in the nasal cavities using a 3D printed model. The system was designed as low cost system which doesn’t need great financial efforts and fits on a DIN-A-4 sized area of a desk},
howpublished = {EMBEC Abstract Book Contribution},
keywords = {Airflow Simulator, Computational Fluid Dynamics, Experimental Station, Validation},
pubstate = {published},
tppubtype = {misc}
}
The RHINODIAGNOST services shall be organized in a rapid network providing new, additional decision aids, such as 3D models and flow simulations, for ENT physicians and radiologists” (taken from: http://www.rhinodiagnost.eu ). The Austrian coordinator of the Rhinodiagnost Project, AIT – Applied Information Technique Research Inc., developed an experimental station which allows the simulation of airflow in the nasal cavities using a 3D printed model. The system was designed as low cost system which doesn’t need great financial efforts and fits on a DIN-A-4 sized area of a desk |
| Lintermann, Andreas Computational Meshing for CFD Simulations Buchkapitel In: Ithavong, Kiao; Singh, Narinder; Wong, Eurgene; Tu, Jiyuang (Hrsg.): Clinical and Biomedical Engineering in the Human Nose - A Computational Fluid Dynamics Approach, Kapitel 6, S. 85-115, Springer Nature Singapore Pte Ltd. 2021, 2020, ISBN: 978-981-15-6715-5. @inbook{Lintermann2020d,
title = {Computational Meshing for CFD Simulations},
author = {Lintermann, Andreas},
editor = {Ithavong, Kiao and Singh, Narinder and Wong, Eurgene and Tu, Jiyuang},
url = {https://link.springer.com/chapter/10.1007%2F978-981-15-6716-2_6},
doi = {10.1007/978-981-15-6716-2_6},
isbn = {978-981-15-6715-5},
year = {2020},
date = {2020-10-17},
booktitle = {Clinical and Biomedical Engineering in the Human Nose - A Computational Fluid Dynamics Approach},
pages = {85-115},
publisher = {Springer Nature Singapore Pte Ltd. 2021},
chapter = {6},
abstract = {In CFD modelling, small cells or elements are created to fill this volume. They constitute a mesh where each cell represents a discrete space that represents the flow locally. Mathematical equations that represent the flow physics are then applied to each cell of the mesh. Generating a high quality mesh is extremely important to obtain reliable solutions and to guarantee numerical stability. This chapter begins with a basic introduction to a typical workflow and guidelines for generating high quality meshes, and concludes with some more advanced topics, i.e., how to generate meshes in parallel, a discussion on mesh quality, and examples on the application of lattice-Boltzmann methods to simulate flow without any turbulence modelling on highly-resolved meshes.},
keywords = {Computational Fluid Dynamics, Mesh Generation, Nasal cavity flows, Nasal respiration, Strömungssimulation},
pubstate = {published},
tppubtype = {inbook}
}
In CFD modelling, small cells or elements are created to fill this volume. They constitute a mesh where each cell represents a discrete space that represents the flow locally. Mathematical equations that represent the flow physics are then applied to each cell of the mesh. Generating a high quality mesh is extremely important to obtain reliable solutions and to guarantee numerical stability. This chapter begins with a basic introduction to a typical workflow and guidelines for generating high quality meshes, and concludes with some more advanced topics, i.e., how to generate meshes in parallel, a discussion on mesh quality, and examples on the application of lattice-Boltzmann methods to simulate flow without any turbulence modelling on highly-resolved meshes. |
| Lintermann, Andreas; Schröder, Wolfgang Lattice–Boltzmann simulations for complex geometries on high-performance computers Artikel In: CEAS Aeronautical Journal, 2020, ISBN: 1869-5582. @article{Lintermann2020c,
title = {Lattice–Boltzmann simulations for complex geometries on high-performance computers},
author = {Lintermann, Andreas and Schröder, Wolfgang },
url = {http://link.springer.com/10.1007/s13272-020-00450-1},
doi = {10.1007/s13272-020-00450-1},
isbn = {1869-5582},
year = {2020},
date = {2020-05-13},
journal = {CEAS Aeronautical Journal},
abstract = {Complex geometries pose multiple challenges to the field of computational fluid dynamics. Grid generation for intricate objects is often difficult and requires accurate and scalable geometrical methods to generate meshes for large-scale computations. Such simulations, furthermore, presume optimized scalability on high-performance computers to solve high-dimensional physical problems in an adequate time. Accurate boundary treatment for complex shapes is another issue and influences parallel load-balance. In addition, large serial geometries prevent efficient computations due to their increased memory footprint, which leads to reduced memory availability for computations. In this paper, a framework is presented that is able to address the aforementioned problems. Hierarchical Cartesian boundary-refined meshes for complex geometries are obtained by a massively parallel grid generator. In this process, the geometry is parallelized for efficient computation. Simulations on large-scale meshes are performed by a high-scaling lattice–Boltzmann method using the second-order accurate interpolated bounce-back boundary conditions for no-slip walls. The method employs Hilbert decompositioning for parallel distribution and is hybrid MPI/OpenMP parallelized. The parallel geometry allows to speed up the pre-processing of the solver and massively reduces the local memory footprint. The efficiency of the computational framework, the application of which to, e.g., subsonic aerodynamic problems is straightforward, is shown by simulating clearly different flow problems such as the flow in the human airways, in gas diffusion layers of fuel cells, and around an airplane landing gear configuration},
keywords = {Airway, Computational Fluid Dynamics, High performance computing, Large-Scale Simulation Data, Lattice-Boltzmann method},
pubstate = {published},
tppubtype = {article}
}
Complex geometries pose multiple challenges to the field of computational fluid dynamics. Grid generation for intricate objects is often difficult and requires accurate and scalable geometrical methods to generate meshes for large-scale computations. Such simulations, furthermore, presume optimized scalability on high-performance computers to solve high-dimensional physical problems in an adequate time. Accurate boundary treatment for complex shapes is another issue and influences parallel load-balance. In addition, large serial geometries prevent efficient computations due to their increased memory footprint, which leads to reduced memory availability for computations. In this paper, a framework is presented that is able to address the aforementioned problems. Hierarchical Cartesian boundary-refined meshes for complex geometries are obtained by a massively parallel grid generator. In this process, the geometry is parallelized for efficient computation. Simulations on large-scale meshes are performed by a high-scaling lattice–Boltzmann method using the second-order accurate interpolated bounce-back boundary conditions for no-slip walls. The method employs Hilbert decompositioning for parallel distribution and is hybrid MPI/OpenMP parallelized. The parallel geometry allows to speed up the pre-processing of the solver and massively reduces the local memory footprint. The efficiency of the computational framework, the application of which to, e.g., subsonic aerodynamic problems is straightforward, is shown by simulating clearly different flow problems such as the flow in the human airways, in gas diffusion layers of fuel cells, and around an airplane landing gear configuration |
2017
|
| Göbbert, Jens Henrik Flow predictions for your nose Artikel In: Exascale-Newsletter, Bd. 3, S. 3, 2017. @article{Göbbert2017exa,
title = {Flow predictions for your nose},
author = {Göbbert, Jens Henrik},
editor = {Forschungszentrum Jülich GmbH},
url = {http://exascale-news.de/en/2017/index/#!/Flow-Predictions-for-Your-Nose, Flow predictions for your nose (Englische Version online)
http://rhinodiagnost.eu/wp-content/uploads/2017/11/exascale_nl_03_2017.pdf, Strömungsvorhersage für die Nase (Deutsche Version)
},
year = {2017},
date = {2017-11-09},
urldate = {2017-11-09},
journal = {Exascale-Newsletter},
volume = {3},
pages = {3},
institution = {Forschungszentrum Jülich GmbH},
keywords = {Computational Fluid Dynamics, High performance computing, Höchstleistungsrechner, Medizin, Nasal respiration, Strömungssimulation},
pubstate = {published},
tppubtype = {article}
}
|
| Lintermann, Andreas; Göbbert, Jens Henrik; Vogt, Klaus; Koch, Walter; Hetzel, Alexander Rhinodiagnost - Morphological and functional precision diagnostics of nasal cavities Artikel In: InSiDE, Innovatives Supercomputing in Deutschland, Bd. 15, Nr. 2, S. 106-109, 2017. @article{RhinoAll,
title = {Rhinodiagnost - Morphological and functional precision diagnostics of nasal cavities},
author = {Lintermann, Andreas and Göbbert, Jens Henrik and Vogt, Klaus and Koch, Walter and Hetzel, Alexander},
editor = {Gauss Center for Supercomputing (GCS), High-Perfomance Computing Center Stuttart (HLRS)},
url = {http://rhinodiagnost.eu/wp-content/uploads/2017/11/InSiDE-Innovatives-Supercomputing-in-Deutschland-2017-Rhinodiagnost-Morphological-and-functional-precision-diagnostics-of-nasal-c.pdf, Rhinodiagnost - Morphological and functional precision diagnostics of nasal cavities},
year = {2017},
date = {2017-08-31},
journal = {InSiDE, Innovatives Supercomputing in Deutschland},
volume = {15},
number = {2},
pages = {106-109},
keywords = {Computational Fluid Dynamics, Diagnostics, In-situ computational steering, Nasal respiration, Rhinology, Rhinomanometry},
pubstate = {published},
tppubtype = {article}
}
|