Translator from Extended SysML to Physical Interaction and Signal Flow Simulation Platforms, Version 1.1

The design of complex systems often requires engineers from multiple disciplines (mechanical, electrical, production, and so on) to communicate with each other and exchange system design information. Systems engineering models are a cross-disciplinary foundation for this process, but are not well-integrated with specialized engineering information, leading to redundant and inconsistent system specifications. The software provided here translates system models in the Systems Modeling Language (SysML) to physical interaction and signal flow (also known as lumped-parameter, one-dimensional, or network) models on two simulation platforms used in many engineering domains.

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Translator from Extended SysML to Physical Interaction and Signal Flow Simulation Platforms

Journal of Research of the National Institute of Standards and Technology ◽

10.6028/jres.124.017 ◽

2019 ◽

Vol 124 ◽

Author(s):

Raphael Barbau ◽

Conrad Bock ◽

Mehdi Dadfarnia

Keyword(s):

Systems Engineering ◽

Flow Simulation ◽

Physical Interaction ◽

Exchange System ◽

One Dimensional ◽

Signal Flow ◽

Inconsistent System ◽

Lumped Parameter ◽

Engineering Models ◽

Engineering Information

Designing complex systems often requires engineers from multiple disciplines (mechanical, electrical, production, and so on) to communicate with each other and exchange system design information. Systems engineering models are a cross-disciplinary foundation for this process, but are not well-integrated with specialized engineering information, leading to redundant and inconsistent system specifications. The software provided here translates system models in the Systems Modeling Language (SysML) to physical interaction and signal flow (also known as lumped-parameter, one-dimensional, or network) files on two simulation platforms used in many engineering domains.

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An Extension of the Systems Modeling Language for Physical Interaction and Signal Flow Simulation

Systems Engineering ◽

10.1002/sys.21380 ◽

2017 ◽

Vol 20 (5) ◽

pp. 395-431 ◽

Cited By ~ 4

Author(s):

Conrad Bock ◽

Raphael Barbau ◽

Ion Matei ◽

Mehdi Dadfarnia

Keyword(s):

Flow Simulation ◽

Modeling Language ◽

Physical Interaction ◽

Systems Modeling ◽

Signal Flow

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An Efficient Preconditioner for Linear System Solution in Multi-Domain Modeling of the Circulatory System

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/sbc2013-14392 ◽

2013 ◽

Author(s):

Mahdi Esmaily Moghadam ◽

Yuri Bazilevs ◽

Tain-Yen Hsia ◽

Alison Marsden

Keyword(s):

Strong Coupling ◽

Large Scale ◽

Computational Cost ◽

Circulatory System ◽

Flow Simulation ◽

Global Dynamics ◽

Domain Modeling ◽

Computationally Efficient ◽

Lumped Parameter ◽

System Solution

A closed-loop lumped parameter network (LPN) coupled to a 3D domain is a powerful tool that can be used to model the global dynamics of the circulatory system. Coupling a 0D LPN to a 3D CFD domain is a numerically challenging problem, often associated with instabilities, extra computational cost, and loss of modularity. A computationally efficient finite element framework has been recently proposed that achieves numerical stability without sacrificing modularity [1]. This type of coupling introduces new challenges in the linear algebraic equation solver (LS), producing an strong coupling between flow and pressure that leads to an ill-conditioned tangent matrix. In this paper we exploit this strong coupling to obtain a novel and efficient algorithm for the linear solver (LS). We illustrate the efficiency of this method on several large-scale cardiovascular blood flow simulation problems.

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Systems engineering models of human-machine interaction

Mathematics and Computers in Simulation ◽

10.1016/0378-4754(82)90081-7 ◽

1982 ◽

Vol 24 (4) ◽

pp. 353

Keyword(s):

Systems Engineering ◽

Human Machine Interaction ◽

Engineering Models ◽

Machine Interaction

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Presenting Model-Based Systems Engineering Information to Non-Modelers

2021 IEEE Aerospace Conference (50100) ◽

10.1109/aero50100.2021.9438292 ◽

2021 ◽

Author(s):

Jeffrey R. Cohen ◽

Sarah Arai ◽

Tatyana Rakalina ◽

Emily Griffin ◽

Jared Heiser ◽

...

Keyword(s):

Systems Engineering ◽

Model Based ◽

Engineering Information ◽

Model Based Systems Engineering

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Contractile Filament Stress in the Left Ventricle and its Relationship to Wall Stress

Journal of Biomechanical Engineering ◽

10.1115/1.3426250 ◽

1979 ◽

Vol 101 (4) ◽

pp. 225-231 ◽

Cited By ~ 6

Author(s):

E. S. Grood ◽

C. A. Phillips ◽

R. E. Mates

Keyword(s):

Three Dimensional ◽

Wall Stress ◽

One Dimensional ◽

Muscle Work ◽

Lumped Parameter ◽

Pressure Development ◽

The One ◽

Active Force Generation ◽

Muscle Models ◽

Significant Underestimation

A three-dimensional composite model of heart muscle is proposed, consisting of one-dimensional (uniaxial) active contractile filaments embedded in a passive elastic binder. Equations are developed which relate the force developed by the filaments to the local tissue stress. An approximate analysis is employed to determine the time variation of the contractile filament stress throughout the cardiac cycle from catheterization data. Results from 15 patients with normal left ventricles demonstrate that the stress developed by the contractile filaments is up to 25 percent more tensile than the wall stress, and that the binder stress is compressive during most of systole. In contrast, the one-dimensional lumped parameter muscle models previously employed predict active (CE) stresses less tensile than the wall stress and binder (PE) stresses that are tensile. We conclude that the use of a one-dimensional muscle model results in a significant underestimation of the active force generation required for pressure development and the power requirements for ejection. Prior studies relating muscle work and power to ventricular oxygen consumption should be re-examined in this light.

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