Validation of an Open Source Framework for the Simulation of Blood Flow

By setting contact sets, achieved overall analysis results of the mechanical properties with omni-direction side-loading forklift truck lifting system based on COSMOSWorks. And made an experimental measurements to omni-direction side-loading forklift truck lifting system by electrometric methods. There was a good relevance between experimental data and calculation values, and the deviation was basically within the 10 percent allowed. Finally, in this way it verified the correctness and reliability of the finite element analysis by experimental measurements. Ensured the omni-direction side-loading forklift truck lifting system could be safe and efficient to work. And also it laid a foundation for subsequent structural optimization.

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Implicit Partitioned Fluid-Structure Interaction Coupling

Volume 4: Fluid Structure Interaction, Parts A and B ◽

10.1115/pvp2006-icpvt-11-93184 ◽

2006 ◽

Cited By ~ 5

Author(s):

Michael Scha¨fer ◽

Saim Yigit ◽

Marcus Heck

Keyword(s):

Experimental Data ◽

Numerical Simulation ◽

Finite Element ◽

Fluid Structure Interaction ◽

Solution Procedure ◽

Volume Flow ◽

Fluid Structure ◽

Flow Solver ◽

Solution Approach ◽

Structure Interaction

The paper deals with an implicit partitioned solution approach for the numerical simulation of fluid-structure interaction problems. The solution procedure involves the finite-volume flow solver FASTEST, the finite-element structural solver FEAP, and the coupling interface MpCCI. The method is verified and validated by comparisons with benchmark results and experimental data. Investigations concerning the influence of the grid movement technique and an underrelaxation on the performance of the method are presented.

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Summit: Benchmarking Machine Learning Methods for Reaction Optimisation

10.26434/chemrxiv.12939806.v1 ◽

2020 ◽

Author(s):

Kobi Felton ◽

Jan Rittig ◽

Alexei Lapkin

Keyword(s):

Machine Learning ◽

Experimental Data ◽

Open Source ◽

Chemical Reaction ◽

Learning Strategy ◽

New Products ◽

Fine Chemicals ◽

Optimal Solutions ◽

Machine Learning Methods ◽

Open Source Framework

In the fine chemicals industry, reaction screening and optimisation are essential to development of new products. However, this screening can be extremely time and labor intensive, especially when intuition is used. Machine learning offers a solution through iterative suggestions of new experiments based on past experimental data, but knowing which machine learning strategy to apply in a particular case is still difficult. Here, we develop chemically-motivated virtual benchmarks for reaction optimisation and compare several strategies on these benchmarks. The benchmarks and strategies are encompassed in an open source framework named Summit. The results of our tests show that Bayesian optimisation strategies perform very well across the types of problems faced in chemical reaction optimisation, while many strategies commonly used in reaction optimisation fail to find optimal solutions.

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Analysis of finite element and finite volume methods for fluid-structure interaction simulation of blood flow in a real stenosed artery

International Journal of Mechanical Sciences ◽

10.1016/j.ijmecsci.2021.106650 ◽

2021 ◽

pp. 106650

Author(s):

D. Lopes ◽

R. Agujetas ◽

H. Puga ◽

J. Teixeira ◽

R. Lima ◽

...

Keyword(s):

Finite Element ◽

Blood Flow ◽

Finite Volume ◽

Fluid Structure Interaction ◽

Finite Volume Methods ◽

Fluid Structure ◽

Structure Interaction ◽

Stenosed Artery ◽

Interaction Simulation

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Validation of an Open Source Framework for the Simulation of Blood Flow in Rigid and Deformable Vessels

Volume 1A: Abdominal Aortic Aneurysms; Active and Reactive Soft Matter; Atherosclerosis; BioFluid Mechanics; Education; Biotransport Phenomena; Bone, Joint and Spine Mechanics; Brain Injury; Cardiac Mechanics; Cardiovascular Devices, Fluids and Imaging; Cartilage and Disc Mechanics; Cell and Tissue Engineering; Cerebral Aneurysms; Computational Biofluid Dynamics; Device Design, Human Dynamics, and Rehabilitation; Drug Delivery and Disease Treatment; Engineered Cellular Environments ◽

10.1115/sbc2013-14791 ◽

2013 ◽

Author(s):

T. Passerini ◽

A. Quaini ◽

U. Villa ◽

A. Veneziani ◽

S. Canic

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Blood Flow ◽

Numerical Methods ◽

Open Source ◽

Open Source Framework ◽

Computational Fluid Dynamics Cfd ◽

Scientific Endeavor ◽

The Right ◽

Computational Analyses

Computational methods are the tool of choice for the study of physics phenomena in many fields of scientific endeavor. To guarantee the reliability of the results of computational analyses, it is crucial that mathematical models are validated and numerical methods are verified. A verified method is capable of correctly solving the problem equations, while a valid model is able to correctly describe the features of the problem (i.e. it uses the right equations). In this paper we: (i) verify and validate an open source computational fluid dynamics (CFD) framework for the solution of problems of interest in hemodynamics and (ii) provide a report on the methodology that we use, to make our experiences reproducible.

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Summit: Benchmarking Machine Learning Methods for Reaction Optimisation

10.26434/chemrxiv.12939806.v2 ◽

2020 ◽

Author(s):

Kobi Felton ◽

Jan Rittig ◽

Alexei Lapkin

Keyword(s):

Machine Learning ◽

Experimental Data ◽

Open Source ◽

Chemical Reaction ◽

Learning Strategy ◽

New Products ◽

Fine Chemicals ◽

Optimal Solutions ◽

Machine Learning Methods ◽

Open Source Framework

In the fine chemicals industry, reaction screening and optimisation are essential to development of new products. However, this screening can be extremely time and labor intensive, especially when intuition is used. Machine learning offers a solution through iterative suggestions of new experiments based on past experimental data, but knowing which machine learning strategy to apply in a particular case is still difficult. Here, we develop chemically-motivated virtual benchmarks for reaction optimisation and compare several strategies on these benchmarks. The benchmarks and strategies are encompassed in an open source framework named Summit. The results of our tests show that Bayesian optimisation strategies perform very well across the types of problems faced in chemical reaction optimisation, while many strategies commonly used in reaction optimisation fail to find optimal solutions.

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A Boundary-Element Method for Slamming Analysis

Journal of Ship Research ◽

10.5957/jsr.1982.26.2.117 ◽

1982 ◽

Vol 26 (02) ◽

pp. 117-124

Author(s):

Thomas L. Geers

Keyword(s):

Experimental Data ◽

Finite Element Analysis ◽

Finite Element ◽

Boundary Element Method ◽

Boundary Element ◽

Element Analysis ◽

Structure Interaction ◽

The Finite Element Analysis ◽

Computational Resources ◽

Element Method

A boundary-element method for treatment of the fluid-structure interaction in slamming analysis is described. The method emphasizes simplicity and efficiency, so that the analyst may devote most of his computational resources to the analysis of the structure. Numerical results for a number of rigid-impactor problems are compared with analytical solutions and experimental data, and procedures for the finite-element analysis of flexible impactors are discussed.

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A novel framework for fluid/structure interaction in rapid subject specific simulations of blood flow in coronary artery bifurcations

Vojnosanitetski pregled ◽

10.2298/vsp1403285b ◽

2014 ◽

Vol 71 (3) ◽

pp. 285-292 ◽

Cited By ~ 3

Author(s):

Milan Blagojevic ◽

Aleksandar Nikolic ◽

Miroslav Zivkovic ◽

Milorad Zivkovic ◽

Goran Stankovic

Keyword(s):

Finite Element ◽

Blood Flow ◽

Shear Stress ◽

Coronary Artery ◽

Oscillatory Shear ◽

Patient Specific ◽

Oscillatory Shear Index ◽

Structure Interaction ◽

Endothelial Shear Stress ◽

Lateral Walls

Background/Aim. Practical difficulties, particularly long model development time, have limited the types and applicability of computational fluid dynamics simulations in numerical modeling of blood flow in serial manner. In these simulations, the most revealing flow parameters are the endothelial shear stress distribution and oscillatory shear index. The aim of this study was analyze their role in the diagnosis of the occurrence and prognosis of plaque development in coronary artery bifurcations. Methods. We developed a novel modeling technique for rapid cardiovascular hemodynamic simulations taking into account interactions between fluid domain (blood) and solid domain (artery wall). Two numerical models that represent the observed subdomains of an arbitrary patient-specific coronary artery bifurcation were created using multi-slice computed tomography (MSCT) coronagraphy and ultrasound measurements of blood velocity. Coronary flow using an in-house finite element solver PAK-FS was solved. Results. Overall behavior of coronary artery bifurcation during one cardiac cycle is described by: velocity, pressure, endothelial shear stress, oscillatory shear index, stress in arterial wall and nodal displacements. The places where (a) endothelial shear stress is less than 1.5, and (b) oscillatory shear index is very small (close or equal to 0) are prone to plaque genesis. Conclusion. Finite element simulation of fluid-structure interaction was used to investigate patient-specific flow dynamics and wall mechanics at coronary artery bifurcations. Simulation model revealed that lateral walls of the main branch and lateral walls distal to the carina are exposed to low endothelial shear stress which is a predilection site for development of atherosclerosis. This conclusion is confirmed by the low values ??of oscillatory shear index in those places.

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