Model Driven Combat Effectiveness Simulation Systems Engineering

Model-driven engineering has become popular in the combat effectiveness simulation systems engineering during these last years. It allows to systematically develop a simulation model in a composable way. However, implementing a conceptual model is really a complex and costly job if this is not guided under a well-established framework. Hence this study attempts to explore methodologies for engineering the development of simulation models. For this purpose, we define an ontological metamodelling framework. This framework starts with ontology-aware system conceptual descriptions, and then refines and transforms them toward system models until they reach final executable implementations. As a proof of concept, we identify a set of ontology-aware modelling frameworks in combat systems specification, then an underwater targets search scenario is presented as a motivating example for running simulations and results can be used as a reference for decision-making behaviors

STEM COIL MODEL VERIFICATION: A PILOT STUDY IN LATVIA

STEM COIL (Science, Technology, Engineering, and Mathematics Collaborative Online International Learning) is an emerging research and education area. This research was enabled by the research question: Is the STEM COIL model designed right? The work aim is to verify the STEM COIL model underpinning the evaluation of the pilot study carried out in Latvia. Descriptive study was deployed. Observational method of the descriptive study was carried out in Latvia in April 2024. Collected data were processed via content analysis. The obtained results were interpreted. The novelty of this research is represented by the STEM COIL model verification based on results of the pilot study carried out in Latvia. The findings of the descriptive study reveal that the STEM COIL implementation coincide with the STEM COIL theoretical model. In other words, the elements of the STEM COIL performed their function in the intended way. The analysis of the pilot study carried out in this work allows concluding that the STEM COIL model has been verified as the STEM COIL elements performed the intended function in the course of the implementation of the pilot study carried out in Latvia in April 2024. Consequently, STEM COIL provides opportunities for STEM learners who wish to improve their STEM knowledge, increase their inclusiveness and equity in society in general and STEM education specifically

Развитие методологии и технологии имитационных исследований сложных систем

In this paper we propose an improved methodology and technology of simulation studies of complex systems as a result of development and improvement of the traditional methodology. The main difference is the improved methodology consistent automation of the process of research and the integration of all programs in a single complex. Software systems that are created on the basis of this methodology allowed an average cut several times during the study of complex systems and significantly increase the number of potential users of simulationВ данной статье предлагается усовершенствованная методология и технология  имитационных исследований сложных систем, как результат развития и совершенствования традиционной методологии. Основным отличием усовершенствованной методологии является последовательная автоматизация процесса исследования и интеграция всех программ в единый комплекс. Программные комплексы, создаваемые на основе данной методологии, позволили  в среднем сократить в несколько раз время проведения исследования сложных систем и значительно увеличить круг потенциальных пользователей имитационного моделировани

Engaging Stakeholders To Extend The Lifecycle Of Hybrid Simulation Models

Developing a simulation model of a complex system requires a significant investment of time, expertise and expense. In order to realize the greatest return on such an investment, it is desirable to extend the lifecycle of the simulation model as much as possible. Existing studies typically end after the `first loop' of the lifecycle, with the computer model suitable for addressing the initial requirements of the stakeholders. We explore extending the modeling lifecycle to a `second loop' by introducing an existing hybrid simulation model to a new group of stakeholders and further developing it to capture new requirements. With the aid of an example application, we explain how the hybrid model facilitated stakeholder engagement by closely reflecting the real world and how the model lifecycle has been successfully extended to maximize the benefit to Eurostar International Limited

Exploring the model development process in discrete-event simulation: insights from six expert modellers

This paper explores the model development process in discrete-event simulation (DES) by reporting on an empirical study that follows six expert modellers while building simulation models. DES is a widely used modelling approach, however little is known about the modelling processes and methodology adopted by modellers in practice. Verbal Protocol Analysis is used to collect data, where the participants are asked to speak aloud while modelling. The results show that the expert modellers spend a significant amount of time on model coding, verification & validation and data inputs. The modellers iterate often between modelling activities. Patterns of modelling behaviour are identified, suggesting that the modellers adopt distinct modelling styles. This study is useful in that it provides an empirical view of existing DES modelling practice, which in turn can inform existing research and simulation practice as well as teaching of DES modelling to novices

Using LIWC to choose simulation approaches: A feasibility study

Can language usage help determine which model approach is best suited to provide decision makers with desired insights? This research addresses that question through an investigation of Linguistic Inquiry and Word Count (LIWC), which calculates the presence of more than 80 language dimensions in text samples, and permits construction of custom dictionaries. This article demonstrates use of LIWC to ensure better problem/model fit within the context of selecting a decision support tool. We selected two simulation tools as research instruments to investigate a broader question on the usefulness of LIWC to guide choice of DSS tool. The tools selected were System Dynamics (SD) and Discrete Event Simulation (DES). First, we tested LIWC to analyze practitioners’ language use when developing models. LIWC pointed out significant linguistic differences consistent with prior theoretical work, based on model development approach in a number of dimensions. These differences provided a basis for developing a custom dictionary for use on the second part of our study. The second part of the study focused on language used by decision makers in problem statements and used the linguistic clues identified in the first part of the study to ensure problem/model fit. Results indicated problem statements contained linguistic clues related to the type of information desired by problem solvers. The article concludes with a discussion about how LIWC and similar tools can help determine which DSS tools are suited to particular applications

Model Continuity in Discrete Event Simulation: A Framework for Model-Driven Development of Simulation Models.

Most of the well known modeling and simulation methodologies state the importance of conceptual modeling in simulation studies and they suggest the use of conceptual models during the simulation model development process. However, only a limited number of methodologies refers to howto move from a conceptual model to an executable simulation model. Besides, existing modeling and simulation methodologies do not typically provide a formal method for model transformations between the models in different stages of the development process. Hence, in the current M&S practice, model continuity is usually not fulfilled. In this article, a model driven development framework for modeling and simulation is in order to bridge the gap between different stages of a simulation study and to obtain model continuity. The applicability of the framework is illustrated with a prototype modeling environment and a case study in the discrete event simulation domain

Model Verification and Validation Strategies and Methods: An Application Case Study

Model verification and validation is an essential part of any modeling and simulation process. Many literatures report model verification and validation strategies and methods in a theoretical framework, but there is limited literature on the application of such strategies and methods to real-world simulation problems such as manufacturing operation system simulation. This research aimed to bridge the gap for a simulation case study from a large UK-based manufacturing company. This paper demonstrates model design and validation processes using a manufacturing case study, explains model verification and validation concepts, and demonstrates the application of a model verification and validation architecture. The emphasis of this paper is on model verification and validation strategies and methods. An example application of such strategies and methods to the verification and validation of a manufacturing operation system simulation case study is presented

Introduction to Modeling and Simulation Techniques

Modeling and simulation techniques are becoming an important research method for investigating operational and organizational systems. Many literatures report different aspects and views of modeling and simulation but there is little literature that covers a full cycle of modeling and simulation, including both model design & development and model verification & validation, for use in industrial product development systems. This paper introduces modeling and simulation concepts, methods and tools, and discusses approaches that can be used for model verification and validation. A modeling and simulation procedure, designed for use in understanding industrial product development systems, is introduced that accommodates both model creation and verification & validation. The overall goal of the research is to bridge the gap between model design & development and model verification & validation in a modeling and simulation procedure which, as a whole, is essential for the application of modeling and simulation techniques to understand any real-world system