Reuse Of Model Components Research Articles

Approaches for Simulation Model Reuse in Systems Design — A Review

<div class="section abstract"><div class="htmlview paragraph">In this paper, we review the literature related to the reuse of computer-based simulation models in the context of systems design.</div><div class="htmlview paragraph">Models are used to capture aspects of existing or envisioned systems and are simulated to predict the behavior of these systems. However, developing such models from scratch requires significant time and effort. Researchers have recognized that the time and effort can be reduced if existing models or model components are reused, leading to the study of model reusability. In this paper, we review the tasks necessary to retrieve and reuse model components from repositories, and to prepare new models and model components such that they are more amenable for future reuse.</div><div class="htmlview paragraph">Model reuse can be significantly enhanced by carefully characterizing the model, and capturing its meaning and intent so that potential users can determine whether the model meets their needs. Traditionally, the meaning and intent of models has been captured in textual documentation, but more recently, semantically rich, axiomatized approaches using model characteristics based on ontologies have been introduced that enable algorithmic support for the identification, discovery, and reuse of models. Researchers have also recognized that the opportunity for reuse significantly increases when models are modularized into composable model components. While many repositories and frameworks for modular modeling have been recently developed, it is important to recognize that without considerable forethought in terms of model architecture, model composability often remains elusive.</div><div class="htmlview paragraph">Even when models are well-characterized and organized in a repository, model users need to perform several tasks before they can successfully reuse these models and components for a specific analysis scenario. These tasks include searching, optionally adapting, composing, integrating and validating models and model components. We will review the literature on each of these tasks and focus on identifying opportunities for further improvement of model reuse support frameworks.</div></div>

Distributed Co-simulation of Maritime Systems and Operations

Here, we present the concept of an open virtual prototyping framework (VPF) for maritime systems and operations that enables its users to develop reusable component or subsystem models, and combine them in full-system simulations for prototyping, verification, training, and performance studies. This framework consists of a set of guidelines for model coupling, high-level and low-level coupling interfaces to guarantee interoperability, a full-system simulation software, and example models and demonstrators. We discuss the requirements for such a framework, address the challenges and the possibilities in fulfilling them, and aim to give a list of best practices for modular and efficient virtual prototyping and full-system simulation. The context of our work is within maritime systems and operations, but the issues and solutions we present here are general enough to be of interest to a much broader audience, both industrial and scientific.

Using simulation in layout verification of solar module assembly workshop

Facility layout problem (FLP) contemplates the optimization of space utilization, costs, and material flow. Commercial simulation softwares are commonly used to validate layouts by simulating the real world material flow and production process. To validate a layout scenario of a solar module assembly workshop, a 3D simulation model is presented which was designed on VisualComponents software. To begin with, we introduce the layout characteristics and use the systematic layout planning (SLP) method to design the block layout of workshop. Then, we built components library which contains all the facilities needed in the production line, specifically conveyors, processing equipments, robots, buffers. Finally, we have established a simulation layout model using the components in the customized library according to the block layout, and configured the components which were allocated in the layout by setting the parameters and building the connection between components via signal. To improve the performance of the workshop, we have found the best work-in-process (WIP) value for the workshop and the optimal number of workers. Additionally, the layout model was used to test collision and reachability. It demonstrated the production process in a realistic simulation environment which helped in the sales process as well. The reusable component models we have built make it easy to build a layout within a short time and validate the effectiveness of the layout scenarios for any other projects.

Towards a new generation of agricultural system data, models and knowledge products: Information and communication technology

Agricultural modeling has long suffered from fragmentation in model implementation. Many models are developed, there is much redundancy, models are often poorly coupled, model component re-use is rare, and it is frequently difficult to apply models to generate real solutions for the agricultural sector. To improve this situation, we argue that an open, self-sustained, and committed community is required to co-develop agricultural models and associated data and tools as a common resource. Such a community can benefit from recent developments in information and communications technology (ICT). We examine how such developments can be leveraged to design and implement the next generation of data, models, and decision support tools for agricultural production systems. Our objective is to assess relevant technologies for their maturity, expected development, and potential to benefit the agricultural modeling community. The technologies considered encompass methods for collaborative development and for involving stakeholders and users in development in a transdisciplinary manner.Our qualitative evaluation suggests that as an overall research challenge, the interoperability of data sources, modular granular open models, reference data sets for applications and specific user requirements analysis methodologies need to be addressed to allow agricultural modeling to enter in the big data era. This will enable much higher analytical capacities and the integrated use of new data sources. Overall agricultural systems modeling needs to rapidly adopt and absorb state-of-the-art data and ICT technologies with a focus on the needs of beneficiaries and on facilitating those who develop applications of their models. This adoption requires the widespread uptake of a set of best practices as standard operating procedures.

1 - CHIC – A Multi-scale Modelling Platform for in-silico Oncology

Models of normal physiology and disease are necessary in cancer research and clinical practice to optimally exploit the available (pre)clinical multi-scale and multi-modality data. Relevant models often cover multiple spatio-temporal scales and require automated access to heterogeneous and confidential data, making their development, validation and deployment challenging. The CHIC (Computational Horizons in Cancer) [1] project develops computational models for the cancer domain, as well as tools, services and a secure infrastructure for model and data access, and reuse. The architecture is designed to support the creation of complex disease models (hypermodels) by composition of reusable component models (hypomodels). It aims to provide individualized answers to concrete clinical questions by patient-specific parametrization of disease-specific hyper-models. We introduce the CHIC project and illustrate its approach to multi-scale cancer modelling by coupled execution of two component models operating on distinct spatial scales: OncoSimulator (OS): a spatially discrete model of cancer cell proliferation and treatment effect in function of tumour, treatment and patient-specific parameters [2], implemented as cellular automaton model, Bio-mechanical Simulator (BMS): a macroscopic continuum model of mechanical effects caused by tumour expansion in patient-specific anatomy, implemented as finite element model, based on [3]. Both component models exchange information about the spatial distribution of cancer cells and mechanical pressure in order to simulate the evolution of tumour volume and shape. Latter is achieved by correcting simple spherical growth (OS) by mechanically induced growth anisotropy (BMS). Results are demonstrated on the clinical example of Glioblastoma Multiforme. CHIC is working towards an extensible platform for in-silico oncology with a set of reusable component models at its core, covering sub-cellular, cellular and super-cellular scales. Viability of infrastructure and composite hyper-models is being evaluated against clinical questions in the treatment of Nephroblastoma, Glioblastoma and Non-small Cell Lung Cancer.

SBML Level 3 package: Hierarchical Model Composition, Version 1 Release 3

SummaryConstructing a model in a hierarchical fashion is a natural approach to managing model complexity, and offers additional opportunities such as the potential to re-use model components. The SBML Level 3 Version 1 Core specification does not directly provide a mechanism for defining hierarchical models, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactical constructs. The SBML Hierarchical Model Composition package for SBML Level 3 adds the necessary features to SBML to support hierarchical modeling. The package enables a modeler to include submodels within an enclosing SBML model, delete unneeded or redundant elements of that submodel, replace elements of that submodel with element of the containing model, and replace elements of the containing model with elements of the submodel. In addition, the package defines an optional “port” construct, allowing a model to be defined with suggested interfaces between hierarchical components; modelers can chose to use these interfaces, but they are not required to do so and can still interact directly with model elements if they so chose. Finally, the SBML Hierarchical Model Composition package is defined in such a way that a hierarchical model can be “flattened” to an equivalent, non-hierarchical version that uses only plain SBML constructs, thus enabling software tools that do not yet support hierarchy to nevertheless work with SBML hierarchical models.

Applying Component‐Based Technologies to Model‐Driven Software Development

SUMMARYImproving the reusability of models and increasing automatic code generation efficiency are problems in model‐driven development. In order to solve these problems, we apply component‐based development technologies that have mainly been developed at the software implementation level to the modeling level. In the proposed approach, functionally relevant model elements are packaged as a component, and the modeling of software is performed by associating them with the model components. The role of a model becomes clear by introducing the concept of a component, and the reusability of model components is improved by externalizing the dependencies between the components. In addition, flexible model transformation rules united with the roles of models can be designed. As a result, the proposed method is able to generate more source code automatically. The validity of the proposed approach is verified through application experiments.

SBML Level 3 package: Hierarchical Model Composition, Version 1 Release 3

Summary Constructing a model in a hierarchical fashion is a natural approach to managing model complexity, and offers additional opportunities such as the potential to re-use model components. The SBML Level 3 Version 1 Core specification does not directly provide a mechanism for defining hierarchical models, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactical constructs. The SBML Hierarchical Model Composition package for SBML Level 3 adds the necessary features to SBML to support hierarchical modeling. The package enables a modeler to include submodels within an enclosing SBML model, delete unneeded or redundant elements of that submodel, replace elements of that submodel with element of the containing model, and replace elements of the containing model with elements of the submodel. In addition, the package defines an optional “port” construct, allowing a model to be defined with suggested interfaces between hierarchical components; modelers can chose to use these interfaces, but they are not required to do so and can still interact directly with model elements if they so chose. Finally, the SBML Hierarchical Model Composition package is defined in such a way that a hierarchical model can be “flattened” to an equivalent, non-hierarchical version that uses only plain SBML constructs, thus enabling software tools that do not yet support hierarchy to nevertheless work with SBML hierarchical models.

Reusability of model components for environmental simulation – Case studies for integrated coastal zone management

Model constructs in environmental models are seldom reused beyond the project lifetime or in other modelling studies. A library of reusable model components could facilitate the maintenance of existing models and make the design of new models more efficient. Although component-based design is the common standard in software engineering and manufacturing few examples are yet found in environmental science. The multi-disciplinary project SPICOSA used a common, component-based simulation framework for environmental modelling, based on 18 case studies through Europe. The development of high-quality model components with potential for reuse turned out to be a challenge despite of the guidelines and tutorial examples provided. Well-designed components are of appropriate granularity, encapsulated, with a limited use of connectors and proper data handling. Ultimately, the success of a model library depends on a sufficient set of quality components with complementary functionalities, a framework for quality control, and support of the environmental modelling community.

Research on the Development Approach for Reusable Model in Parallel Discrete Event Simulation

Model reuse is an essential means to meet the demand of model development in complex simulation. An effective approach to realize the model reusability is to establish standard model specification including interface specification and representation specification. By standardizing model’s external interfaces, Reusable Component Model Framework (RCMF) achieves the model reusability acting as an interface specification. However, the RCMF model is presently developed just through manual programing. Besides implementing model’s business logic, modeler should also ensure the model strictly following the reusable framework, which is very distracting. And there lacks model description information for instructing model reuse or integration. To address these issues, we first explored an XML-based model description file which completed RCMF as the model representation and then proposed a RCMF model development tool—SuKit. Model description file describes a RCMF model and can be used for regenerating a model and instructing model integration. SuKit can generate a skeleton RCMF model together with a model-customized description file with the configured information. Modeler then just needs to concentrate on the model processing logic. The case study indicates that SuKit has good capability of developing RCMF models and the well-formed description file can be used for model reuse and integration.

Model-driven agent-based simulation: Procedural semantics of a MAIA model

Agent-based modelling and simulation (ABMS) is highly instrumental for studying socio-technical systems. MAIA – Modelling Agents using Institutional Analysis – is an ABMS modelling framework that formalises social sciences knowledge. It enables handling the complexity of large complex systems, allows collaborative model development and the reuse of model components when building simulations. We detail the procedural semantics for transforming a MAIA model into an executable simulation. Its evaluation through various case studies of model development and simulation is described. The MAIA meta-model is a declarative language to conceptualise an ABM. A model description in MAIA thus provides sufficient information to translate it into a simulation model – it defines the agents, their decision-making process and their actions, all within an institutional and physical context, to affect system states that are defined in the MAIA model. A modeller can use MAIA to specify and document her model and to build her simulation by using MAIA’s semi-automatic code generation option.

Reusable component model development approach for parallel and distributed simulation.

Model reuse is a key issue to be resolved in parallel and distributed simulation at present. However, component models built by different domain experts usually have diversiform interfaces, couple tightly, and bind with simulation platforms closely. As a result, they are difficult to be reused across different simulation platforms and applications. To address the problem, this paper first proposed a reusable component model framework. Based on this framework, then our reusable model development approach is elaborated, which contains two phases: (1) domain experts create simulation computational modules observing three principles to achieve their independence; (2) model developer encapsulates these simulation computational modules with six standard service interfaces to improve their reusability. The case study of a radar model indicates that the model developed using our approach has good reusability and it is easy to be used in different simulation platforms and applications.

해군무기체계 수중교전 모델 라이브러리 개발

국방과학연구소는 해군 전투실험을 위한 시뮬레이션 통합개발환경(QUEST)을 개발하였으며 본 논문은 QUEST의 수중교전 시뮬레이션을 응용을 위한 해군무기체계 모델 라이브러리 개발에 대하여 기술한다. 모델은 기본적으로 함정 및 무장체계 간의 수중교전 효과도 및 전술 개발 목적으로 개발되었다. 수중교전 임무공간과 기존 운용모델 기능 분석을 통하여 표준 모델구조를 정립하고 구성 컴포넌트를 개발하였다. 각각의 컴포넌트는 무기체계 구성부의 기능을 잘 정의한 표준화된 체계, 부체계, 알고리듬 모델이며 모델간 표준 인터페이스를 정의하였다. 모델 라이브러리를 이용하여 사용자는 최소한의 도메인지식으로 기존 모델을 재사용하고 새로운 모델을 효율적으로 조립가능하며 사용자간에 모델을 공유하고 협업할 수 있다. ADD (Agency for Defense Development) has developed the naval warfare simulation environment (QUEST), this paper describes the model library of naval weapon systems for the application of underwater warfare simulation included in the QUEST. Models are basically developed in order to measure the effectiveness and tactical development of underwater engagement between ships and weapons. Analyzing the mission space of underwater engagement and the functionality of the legacy models, we define standards of the model structure and developed the model components. Each components are the well-defined environment, system, subsystem, algorithm models, and the interfaces are defined between them. Users can construct a model in an efficient way to various warfare scenarios using the re-usable model components and co-work with the common model library.

Applying Component-Based Technologies to Model Driven Software Development

Improving the reusability of models and automatic code generation efficiency are problems of model driven development. In order to solve these problems, we apply component-based development technologies which have been mainly developed on software implementing level to modeling level. In the proposed approach, functionally relevant model elements are packed as a component, and modeling software is carried out associating with the model components. The role of a model becomes clear by introducing the concept of component, and the reusability of model components is raised by externalizing the dependency between components. In addition, flexible model transformation rules united with the roles of models can be designed. As a result, it is able to generate more source codes automatically. The validity of the proposed approach has been checked by application experiments.

Reusing model components in logistics simulation and device emulation in container terminal operation with open-source framework DESMO-J

With this applied research study, we are demonstrating how an open-source Java simulation framework can be extended beyond standard logistic studies as the main application domain so far to evaluate and test container terminal control systems. We are investigating whether implementing model components of container terminals in such a flexible way that they can be applied in logistics simulation as well as in device emulation test beds is feasible. This paper outlines our experience in extending DESMO-J for a broader range of applications in the context of container terminals and in developing reusable model components for simulation and emulation.

From types to type requirements: genericity for model-driven engineering

Model-driven engineering (MDE) is a software engineering paradigm that proposes an active use of models during the development process. This paradigm is inherently type-centric, in the sense that models and their manipulation are defined over the types of specific meta-models. This fact hinders the reuse of existing MDE artefacts with other meta-models in new contexts, even if all these meta-models share common characteristics. To increase the reuse opportunities of MDE artefacts, we propose a paradigm shift from type-centric to requirement-centric specifications by bringing genericity into models, meta-models and model management operations. For this purpose, we introduce so-called concepts gathering structural and behavioural requirements for models and meta-models. In this way, model management operations are defined over concepts, enabling the application of the operations to any meta-model satisfying the requirements imposed by the concept. Model templates rely on concepts to define suitable interfaces, hence enabling the definition of reusable model components. Finally, similar to mixin layers, templates can be defined at the meta-model level as well, to define languages in a modular way, as well as layers of functionality to be plugged-in into other meta-models. These ideas have been implemented in MetaDepth, a multi-level meta-modelling tool that integrates action languages from the Epsilon family for model management and code generation.

AIBench: A rapid application development framework for translational research in biomedicine

Applied research in both biomedical discovery and translational medicine today often requires the rapid development of fully featured applications containing both advanced and specific functionalities, for real use in practice. In this context, new tools are demanded that allow for efficient generation, deployment and reutilization of such biomedical applications as well as their associated functionalities. In this context this paper presents AIBench, an open-source Java desktop application framework for scientific software development with the goal of providing support to both fundamental and applied research in the domain of translational biomedicine. AIBench incorporates a powerful plug-in engine, a flexible scripting platform and takes advantage of Java annotations, reflection and various design principles in order to make it easy to use, lightweight and non-intrusive. By following a basic input–processing–output life cycle, it is possible to fully develop multiplatform applications using only three types of concepts: operations, data-types and views. The framework automatically provides functionalities that are present in a typical scientific application including user parameter definition, logging facilities, multi-threading execution, experiment repeatability and user interface workflow management, among others. The proposed framework architecture defines a reusable component model which also allows assembling new applications by the reuse of libraries from past projects or third-party software.

Simulation Model Quality Issues in Product Engineering: A Review

Dynamic models are of central importance in engineering design for many fields of application but, within some areas, surprisingly little attention is given to the confidence that can be placed on predictions from such models and the implications of model quality, or the lack of it, for design. In recent years the growth of interest in the possible benefits that generic models and model component re-use provide has stimulated new interest in questions of model quality and in the closely associated issues of model testing, verification and validation. This paper considers the link between model quality and the quantitative testing of continuous system simulation models in product engineering and reviews techniques available for the verification and validation of such models. Recent developments and current trends in this field are emphasised, with particular reference to generic models and the re-use of model components. The paper also considers some of the problems inherent in applying rigorous testing and validation procedures. Implications for the education and training of engineering students in the areas of modelling and simulation are considered.

Critical evaluation of paradigms for modelling integrated supply chains

Contemporary problems in process systems engineering often require model-based decision support tool. Among the various modelling paradigms, equation-based models and agent-based models are widely used to develop dynamic models of systems. Which is the most appropriate modelling paradigm for a supply chain? In this paper, we seek to address this important question through a well-structured benchmarking process. First, we demonstrate that in the space of models, ‘equations’ and ‘agents’ are concepts of a different order, the former referring to the system description elements in the model while the latter emphasises the model elements. Thus conceptually, the two paradigms are not mutually exclusive. Next, in a case study different dynamic models of an oil refinery supply chain are developed, using different tools and approaches. By performing detailed experiments with two different models, it is demonstrated that the models are equivalent when compared using model definition, numerical results and recommended decisions. However, the modelling process itself is different and results in different model structures. By analysing the effort required to expand the models, allowing new scenarios to be tested, and re-use of model components, we identify the strengths of the two paradigms in the context of supply chain modelling.

A methodology for enhanced flexibility of integrated assessment in agriculture

Agriculture is interrelated with the socio-economic and natural environment and faces increasingly the problem of managing its multiple functions in a sustainable way. Growing emphasis is on adequate policies that can support both agriculture and sustainable development. Integrated Assessment and Modelling (IAM) can provide insight into the potential impacts of policy changes. An increasing number of Integrated Assessment (IA) models are being developed, but these are mainly monolithic and are targeted to answer specific problems. Approaches that allow flexible IA for a range of issues and functions are scarce. Recently, a methodology for policy support in agriculture has been developed that attempts to overcome some of the limitations of earlier IA models. The proposed framework (SEAMLESS-IF) integrates relationships and processes across disciplines and scales and combines quantitative analysis with qualitative judgments and experiences. It builds on the concept of systems analysis and attempts to enable flexible coupling of models and tools. The present paper aims to describe progress in improving flexibility of IAM achieved with the methodology developed for SEAMLESS-IF. A brief literature review identifying limitations in the flexibility of IAM is followed by a description of the progress achieved with SEAMLESS-IF. Two example applications are used to illustrate relevant capabilities of SEAMLESS-IF. The examples refer to (i) the impacts on European agriculture of changes in world trade regulations and (ii) regional impacts of the EU Nitrates Directive in combination with agro-management changes. We show that improving the flexibility of IAM requires flexibility in model linking but also a generic set up of all IA steps. This includes problem and scenario definition, the selection and specification of indicators and the indicator framework, the structuring of the database, and the visualization of results. Very important is the flexibility to integrate, select and link models, data and indicators depending on the application. Technical coupling and reusability of model components is greatly improved through adequate software architecture (SEAMLESS-IF uses OpenMI). The use of ontology strongly supports conceptual consistency of model linkages. However, the scientific basis for linking models across disciplines and scales is still weak and requires specific attention in future research. We conclude that the proposed framework significantly advances flexibility in IAM and that it is a good basis to further improve integrated modelling for policy impact assessment in agriculture.