Towards a semantic representation for multi-scale finite element biosimulation experiments

Freitas, André; Jones, M. Z.; Asooja, Kartik; Bellos, Christos; Elliott, S.J.; Stenfelt, Stefan; Hasapis, Panagiotis; Georgousopoulos, Christos; Marquardt, Torsten; Filipović, Nenad; Decker, Stefan; Sahay, Ratnesh

doi:10.1109/bibe.2013.6701586

Cited by 4 publications

(8 citation statements)

References 10 publications

(14 reference statements)

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“…The SIFEM Conceptual Model is designed to support simulation of hearing processes and the biological system of inner ear [3]. The simulation of any biological system, in our case inner ear, requires two types of models; 1) models for conceptual representation of the studied phenomenon, and 2) mathematical/numerical models for describing the behaviour of the system.…”

Section: Listing 2: Rdfized Output Parametersmentioning

confidence: 99%

“…All the approaches mentioned above focus on ontologising finite element constructs into the various domains such as cardiovascular, product development, and systems biology. Similarly, the SIFEM consortium has developed an ontological multi-scale model of the human cochlea (inner-ear) [3]. However, in order to use above ontologies into a complete finite element biosimulation process, a well-integrated in-frastructure is required to improve automation at all the biosimulation stages starting from the numerical parameter collection to visualising the simulation results.…”

Section: Related Workmentioning

confidence: 99%

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A linked data platform for finite element biosimulations

Mehdi

Khan

Freitas

et al. 2015

Proceedings of the 11th International Conference on Semantic Systems

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Biosimulation models have been recently introduced to understand the exact causative factors that give rise to impairment in human organs. Finite Element Method (FEM) provides a mathematical framework to simulate dynamic biological systems, with applications ranging from human ear, cardiovascular, to neurovascular research. Due to lack of a well-integrated data infrastructure, the steps involved in the execution and comparative evaluation of large Finite Element (FE) simulations are time consuming and are performed in isolated environments. In this paper, we present a Linked Data platform to improve the automation in integration, analysis and visualisation of biosimulation models for the inner-ear (cochlea) mechanics. The proposed platform aims to help domain scientists and clinicians for exploring and analysing Finite Element (FE) numerical data and simulation results obtained from multiple domains such as biological, geometrical, mathematical, physical models. We validate the platform by conducting a qualitative survey and perform quantitative experiments to record overall performance.

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Section: Listing 2: Rdfized Output Parametersmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A linked data platform for finite element biosimulations

Mehdi

Khan

Freitas

et al. 2015

Proceedings of the 11th International Conference on Semantic Systems

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“…Scientific investigation practice is evolving in the direction of the creation of large-scale, highly complex, multi-domain and multi-scale scientific models and theories [1]. The complexity intrinsic to these models, brings barriers for interpreting, reproducing and reusing third-party scientific results.…”

Section: Motivationmentioning

confidence: 99%

“…Figure 2 also depicts the main ontologies which are reused and extended in the SIFEM system. Additional details on the SIFEM conceptual model can be found in [1].…”

Section: Semantic Infrastructurementioning

confidence: 99%

“…Figure 2 shows the high-level components of the SIFEM platform and a typical usage workflow of the platform (represented by the number sequence). The workflow starts with the specification of the simulation parameters and of different simulation scenarios on the Simulation Manager component (1). This specification of the simulation is stored in the RDF triple store using a prospective provenance representation.…”

Section: Semantic Infrastructurementioning

confidence: 99%

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Towards a Semantic Web Platform for Finite Element Simulations

Freitas

Asooja

Soni

et al. 2014

Lecture Notes in Computer Science

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Finite Element (FE) simulations are present in many different branches of science. The growth in the complexity of FE models and their associated costs bring the demand to facilitate the construction , reuse and reproducibility of FE models. This work demonstrates how Semantic Web technologies can be used to represent FE simulation data, improving the reproducibility and automation of FE simulations. 1 Motivation Scientific investigation practice is evolving in the direction of the creation of large-scale, highly complex, multi-domain and multi-scale scientific models and theories [1]. The complexity intrinsic to these models, brings barriers for interpreting , reproducing and reusing third-party scientific results. The lack of repro-ducibility in science and the effort necessary for reusing and adapting existing scientific models are major problems in contemporary scientific praxis. Finite Element (FE) methods are numerical techniques for finding approximate solutions for differential equations, and are examples of computational models which are present in different branches of science, including Biology, Physics and Engineering. The construction of FE models is a high complexity task which depends on multiple steps, including the definition of a discretized geometrical model (a mesh), the definition of a physical model, the selection of numerical methods, the visualization and interpretation of the results and the experimental validation of the model. Building a consistent and realistic FE model is an empirical and time consuming process, depending on the composition and fine-tuning of different parameters. This complexity is expressed in the difficulty of building and validating FE Models and in reproducing and reusing third-party FE models. Previous works in the area have concentrated on the representation of FE elements in the mechanical engineering design domain [2]. This work targets the FE modeling problem from an eScience perspective. This work describes the SIFEMacronym for Semantic Infostructure for Finite Element Methods platform, a semantic infrastructure to support the construction , validation, reproducibility and reuse of Finite Element models. The next sections provide a brief description and demonstration of the SIFEM system.

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Capturing simulation intent in an ontology: CAD and CAE integration application

Boussuge

Tierney

Vilmart

et al. 2019

Journal of Engineering Design

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Computational simulation is critical in the modern engineering design process. Currently, the use of simulation is limited by the time-consuming process of converting CAD assemblies into FEA models which are efficient to run and yet sufficiently accurate. In addition to the geometric representation of components, analysts require additional knowledge to describe the complete 3D simulation model. To speed up the generation of CAE models from CAD assemblies, we propose to capture high-level modelling and idealisation decisions, characterising the simulation intent, into a knowledge-based CAE model. In this framework, a simulation intent ontology formalises and structures the analysis parameters, the modelling and idealisation decisions. The ontological concepts and relations required to incorporate two of the key capabilities, cellular modelling and equivalencing, are described. Cellular modelling introduces the concept of cells, which subdivide the 3D space, and to which simulation attributes can be attached. Equivalencing maintains the link between different representations of the cells required for different analyses throughout the analysis lifecycle. Illustrative examples show how the knowledge-based CAE model is used to manage the idealisation decisions and to apply inference rules replicating current modelling practices.

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Towards a semantic representation for multi-scale finite element biosimulation experiments

Cited by 4 publications

References 10 publications

A linked data platform for finite element biosimulations

A linked data platform for finite element biosimulations

Towards a Semantic Web Platform for Finite Element Simulations

Capturing simulation intent in an ontology: CAD and CAE integration application

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