K14
System Level Simulation 2

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17:35
conference time (CEST, Berlin)
Managing Distributed Model-Based Design Projects
27/10/2021 17:35 conference time (CEST, Berlin)
Room: K
C. Rygaard (Blend Dynamics, USA)
C. Rygaard (Blend Dynamics, USA)
Increasingly, multidisciplinary simulations are being built with contributions from multiple groups, or even from multiple companies. In my career, I’ve worked on several MBD projects that were distributed across multiple groups. Each of these projects proceeded in very different ways, but they all had some commonality in the types of problems encountered during the lifecycle of the project. Managing projects that are distributed this way presents unique challenges that are not encountered on projects developed within one organization, including: - Developing a consistent, unambiguous system-level design. This is more critical and more difficult in a Distributed MBD project. The participants are not co-located so collaboration is more difficult. - Communicating the design to the participating groups. Ensuring each group has a clear and precise understanding takes on added importance in a distributed project. Textual requirements are often imprecise and misinterpreted. - Ensuring the groups accurately implement the design. Because the groups are not working side-by-side, each group must deliver a component that precisely implements the design, both in intent and in details. A group that does not properly implement the component will cause problems downstream for the group that is integrating it. - Integrating the components from the different groups. When integrating components, the developers might not be present, so iterating on the details during integration is unacceptable. Because the groups are physically separated, refining the details at this stage can result in time-consuming phone calls and may even necessitate travel while the team wait for the integrated simulation. - Managing the project as it evolves and grows. All of the above topics are revisited each time the team updates the simulation. This presentation will discuss: - Some of the lessons I have learned from my experience with Distributed MBD Projects - Why the traditional techniques, ICDs and perhaps some packaging technology, do not adequately address the challenges faced by a project lead who is managing a Distributed MBD project. - A new approach to managing Distribute MBD projects, as embodied in the SystemBlend- tool suite.
MBSE, Systems Engineering, Distributed Development, Project Management
17:55
conference time (CEST, Berlin)
How Multi-Fidelity Analytical Modeling Can Reduce Risk at All Levels of System Development
27/10/2021 17:55 conference time (CEST, Berlin)
Room: K
G. Garstecki (Garstecki Modeling Solutions, LLC, USA)
G. Garstecki (Garstecki Modeling Solutions, LLC, USA)
Analytical modeling and simulation of systems are traditionally done at the component or module levels and usually involve complex 3-D simulations. These types of simulations take a long time to solve but give detailed design direction. In addition, these types of simulations are typically conducted after the project gets into the development life cycle phase. Within a Systems Engineering strategy, modeling and simulation of systems are starting to be done at the product level and usually involve simplified 0-D or 1-D models. These types of simulations run very fast but only give general design direction. In addition, these types of simulations are typically needed during the planning or conceptual phase of the project’s life cycle. If we were to couple the 0-D, 1-D and 3-D models in such a way that they would give consistent output, then the knowledge gained during the 3-D simulations would be captured within the 0-D or 1-D models. Coupling these models also becomes a key enabler for robust execution of the Systems Engineering technical processes. Imagine providing the initial verification for a set of requirements at each subsystem and component earlier than ever done before. An additional benefit to implementing this model coupling strategy over the entire design process is that this “family of models” becomes the company’s Intellectual Capital. The success of this model coupling strategy is predicated on the fact that products are being improved through next-generation development. For example, a project to develop a new truck is using previous models of that truck as the knowledge foundation. In this presentation, I will outline the benefits of incorporating such a multi-fidelity strategy for your company. I will describe what I mean by multi-fidelity, how analytical modeling connects with Model-based Systems Engineering, and how this family of models are used and updated throughout the design process. I will do this through an example of what this would look like within product development using a fictitious company that supplies suspension systems to various industries.
System-level Simulation, MBSE, Multi-fidelity modeling, product development
18:15
conference time (CEST, Berlin)
Towards a VR-Based Early Design Interaction for Electric Vertical Take-Off & Landing (eVTOL) Cyber-Physical Models
27/10/2021 18:15 conference time (CEST, Berlin)
Room: K
M. Podlaski, L. Vanfretti, A. Khare, J. Montenieri, J. Lewin, E. Segall (Rensselaer Polytechnic Institute, USA)
M. Podlaski, L. Vanfretti, A. Khare, J. Montenieri, J. Lewin, E. Segall (Rensselaer Polytechnic Institute, USA)
In the development of eVTOL systems, simulation-based studies using well-understood physics-based models are extremely valuable to determine which designs best comply with specifications and requirements before manufacturing them. It’s difficult to integrate human interaction in early design stages into the engineering design process, for both designer and end-user, because typical engineering requirements don’t depend on human factors. This opens the research questions: (1)can the design improve if designers interact with the virtual prototype during early design phases?, and (2)can the end-user interaction at early phases fulfill unperceived end-user needs and requirements w.r.t. existing approaches? To address such questions, a “virtual design” environment is needed allowing for designers/end-users to interact with the “virtual prototypes”. This paper discusses preliminary work to address how virtual reality-based technologies can enable interaction with eVTOL models early in the design process, providing more flexibility to study models with additional human feedback. The proposed systems engineering method can also provide a basis for a eVTOL virtual reality-based flight training simulator. The proposed method is implemented for a multi-domain drone model created using the open access standardized modeling language, Modelica. This paper builds off the model described in [1] to show methods to simulate and interact with the drone using virtual reality. The drone model is instrumented with additional functionalities from a visualization library [2], coupled to a generic gaming flight controller, and interfaced with a custom off-the-shelf headset. The model is exported to a gaming environment using the Functional Mock-up Interface (FMI) open access standard. The FMI allows exporting models as functional mock-up units (FMUs) [3] to use them in other environments through a standardized software interface. This allows us to deploy the models to take advantage of the VR ecosystem provided by game engines. The results aim to highlight the importance of the use of open access and open source model exchange standards, specifically FMI, for model portability into new interaction environments that weren’t initially conceived for simulation purposes. [1] Vanfretti, L., Nademi, H., Podlaski, M., and Chang, H., “UAV Dynamics and Electric Power System Modeling and Visualization using Modelica and FMI,” , 10 2020. [2] Hellerer, M., Bellmann, T., and Schlegel, F., “The DLR Visualization Library - Recent development and applications,”Link̈oping Electronic Conference Proceedings, The 10th International Modelica Conference 2014, March 2014 [3] “FMI Standard,” https://fmi-standard.org/, March 2021.
eVTOL modeling and simulation, drone modeling, Modelica, FMI, virtual reality
18:35
conference time (CEST, Berlin)
Quality Assurance of Engineering Simulations: a Review of Concepts, Methods, and Standards
27/10/2021 18:35 conference time (CEST, Berlin)
Room: K
F. Santandrea, RISE Research Institutes of Sweden; M. Eriksson, Validus Engineering, SWE
F. Santandrea, RISE Research Institutes of Sweden; M. Eriksson, Validus Engineering, SWE
Numerical simulations play a pivotal role in the development and testing of novel technologies, enabling the improvement of product quality whilst reducing costs and shortening time to market. Increasing reliance on numerical simulations in product development and verification demands for robust simulation governance, i.e. procedures to ensure the reliability of the predictions based on numerical simulations.
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