Classification of Simulation Models for the Model-based Design of Plastic-Metal Hybrid Joints

Spütz, Kathrin; Berges, Julius Moritz; Jacobs, Georg; Berroth, Joerg; Konrad, Christian

doi:10.1016/j.procir.2022.05.211

Cited by 17 publications

(38 citation statements)

References 11 publications

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“…at a parameter level as well as the integration of domain models (such as FE-simulation models) to seamlessly verify the requirements [6,7,13,25,30,31].…”

Section: Motego Methodsmentioning

confidence: 99%

“…In the literature, two current approaches aim to systematize and methodically support the selection and combination of models. The approaches of [7,25] propose the classification of models according to their scope (Which system element is represented? ), purpose (Which physical quantities are calculated?)…”

Section: State Of the Artmentioning

confidence: 99%

“…The method specifies the systematic structure of system models and, in particular, the relationships between system elements and subsystems. Several function-oriented, model-based development methods exist, such as SYSMOD [28], FAS4M [29] and motego [6,7,13,25,30,31]. In particular, the MBSE motego method is suitable for the verification of battery systems in different scenarios because it allows for the description of the physical and chemical properties at a parameter level as well as the integration of domain models (such as FE-simulation models) to seamlessly verify the requirements [6,7,13,25,30,31].…”

Section: State Of the Artmentioning

confidence: 99%

“…A major problem in the integration of multiple domain models for each purpose into the SolutionElements and SystemSolutions is the complexity that arises from the necessary interconnections. In [25], a SysML model structure is presented that clearly defines how domain models can be integrated into SolutionElements so that the interconnection is well structured and it is easy to switch between models of the same purpose.…”

Section: Integration Of Domain Models Into the System Model Based On ...mentioning

confidence: 99%

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Automated Identification of Valid Model Networks Using Model-Based Systems Engineering

Berges

Spütz

Jacobs

et al. 2022

Systems

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To handle increasing complexity in product development, model-based systems engineering (MBSE) approaches are well suited, in which the technical system is represented in a system model. To efficiently test requirements, domain models are integrated into the system model. For each purpose (e.g., battery lifetime calculation), there are typically several models at several fidelity levels. Since the model signatures (i.e., necessary inputs for the models and their outputs) differ depending on the fidelity level, not all models can be used in any development phase. In addition, due to the different model signatures, not all models can be combined arbitrarily to model networks. Currently, valid model networks in system models must be determined in a time-consuming, manual process. Therefore, this paper presents an approach that automates this task via the implementation of an algorithm that analyzes a system model and the model signatures and automatically returns all valid model networks. When input parameters, models or their signatures change, the algorithm updates automatically, and the user receives the valid model network without any manual effort. The approach is demonstrated with the running example of battery system development.

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“…at a parameter level as well as the integration of domain models (such as FE-simulation models) to seamlessly verify the requirements [6,7,13,25,30,31].…”

Section: Motego Methodsmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Section: Integration Of Domain Models Into the System Model Based On ...mentioning

confidence: 99%

See 2 more Smart Citations

Automated Identification of Valid Model Networks Using Model-Based Systems Engineering

Berges

Spütz

Jacobs

et al. 2022

Systems

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“…The solution elements include a functional description via principle solutions (incl. physical effect and active surfaces) following a formal SysML profile [5], corresponding models [16], and workflows. The defined structure of a solution element (Figure 1) is considered as the foundation for the presented research.…”

Section: State Of Researchmentioning

confidence: 99%

A Classification Method for the Systematic Identification of Models and Workflows in MBSE

Höpfner¹,

Kowalski²,

Faustmann³

et al. 2022

DS 119: Proceedings of the 33rd Symposium Design for X (DFX2022)

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Modern engineering uses models for virtual verification of systems. Such models are usually combined in workflows, where the results of models are linked to verify system requirements. Model-Based Systems Engineering (MBSE) has evolved as an approach to ease the usage of models and workflows. One goal in MBSE is to reuse models and workflows from libraries. However, the step of identifying and classifying both models and workflows for such a library is not yet systematized. We propose a method on how to identify models and workflows for an MBSE model library. Possible purposes of models are identified and afterwards models satisfying that purpose are retrieved. The identified models are systematically combined to workflows. Thereby a systematic approach to create a model library is given.

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Combining and evaluating function-oriented solutions in model-based systems engineering

Irnich

Jacobs

Zerwas

et al. 2023

Forsch Ingenieurwes

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Increasing complexity and shorter innovation cycles require a rethink in the development of mechatronic products. A function-oriented development process using model-based systems engineering (MBSE) methods promises to identify technical solutions via solution-neutral functional architectures. Since each function can typically be realized by multiple, alternative solutions the combinatorial number of overall system solutions explodes. Existing MBSE approaches enable to establish functional architectures as well as support the verification of solutions. However, evaluating different solution combinations with the current state of research involves repetitive and time-consuming modeling which leads to a heuristic selection of potentially suboptimal solutions. In this paper, we present a method for the systematic and function-oriented composition and model-based evaluation of solution combinations. Alternative solutions are structured based on a functional architecture, so that each possible solution combination can be composed and simulated with a minimum of effort, considering physical interactions and the efficiency. Based on simulation results, solution combinations can be verified against requirements and evaluated striving for the best solution combination. The elaborated method extends an existing MBSE approach and is illustrated by the running example of an electrical coolant pump of a passenger vehicle.

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Classification of Simulation Models for the Model-based Design of Plastic-Metal Hybrid Joints

Cited by 17 publications

References 11 publications

Automated Identification of Valid Model Networks Using Model-Based Systems Engineering

Automated Identification of Valid Model Networks Using Model-Based Systems Engineering

A Classification Method for the Systematic Identification of Models and Workflows in MBSE

Combining and evaluating function-oriented solutions in model-based systems engineering

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