94 research outputs found

    Teaching Modeling to Engineers in an Undergraduate Simulation Course

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    A significant challenge in teaching simulation to undergraduate students is to find a way to allow them to model a real world referent system within time and student skill constraints. Several research sources highlight not only the important challenge of model development (Garcia and Ceneno, 2009, Tako, 2011) but also the increased need for model development instruction among engineers (Grasas et. al., 2013, Saltzman and Roeder, 2013). One approach to this challenge is to use a general purpose discrete event simulation software package within the course, but this presents two challenges. Teaching the package to the students takes significant time, and the package introduces limitations which may restrict their ability to model certain real-world referents, particularly in the engineering domain. A conceptual approach to solving this problem is to use a model development paradigm that abstracts away the interface to the simulation infrastructure while still allowing the students to use the full expressive nature of a programming language. Two undergraduate courses at the United States Military Academy employed this strategy via the Discrete Events Specification System – Distributed Modeling Framework (DEVS-DMF) (Kewley et. al, 2016). The DEVS abstraction allowed students to think about their model as a simple state change function with defined inputs and outputs, and DMF allowed them to program in a cloud-based Jupyter Notebook using the Python language. Students in a combat modeling course employed a variety of models to understand drone jamming, and students in an engineering capstone project employed models to account for human factors in rifle marksmanship. The effectiveness of this approach was assessed through student grades, exit-interviews, and course-end surveys. These assessments showed an increased understanding of the model development process, and students also reported greater ownership of their models. However, this experiment also highlighted some weaknesses in their understanding of underlying methodologies and programming skills

    Adding Executable Context to Executable Architectures: Enabling an Executable Context Simulation Framework (ECSF)

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    A system that does not stand alone is represented by a complex entity of component combinations that interact with each other to execute a function. In today\u27s interconnected world, systems integrate with other systems - called a system-of-systems infrastructure: a network of interrelated systems that can often exhibit both predictable and unpredictable behavior. The current state-of-the-art evaluation process of these system-of-systems and their community of practitioners in the academic community are limited to static methods focused on defining who is doing what and where. However, to answer the questions of why and how a system operates within complex systems-of-systems interrelationships, a system\u27s architecture and context must be observed over time, its executable architecture, to discern effective predictable and unpredictable behavior. The objective of this research is to determine a method for evaluating a system\u27s executable architecture and assess the contribution and efficiency of the specified system before it is built. This research led to the development of concrete steps that synthesize the observance of the executable architecture, assessment recommendations provided by the North Atlantic Treaty Organization (NATO) Code of Best Practice for Command and Control (C2) Assessment, and the metrics for operational efficiency provided by the Military Missions and Means Framework. Based on the research herein, this synthesis is designed to evaluate and assess system-of-systems architectures in their operational context to provide quantitative results

    The Effect of Modeling Simultaneous Events on Simulation Results

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    This thesis explores the method that governs the prioritizing process for simultaneous events in relation to simulation results for discrete-event simulations. Specifically, it contrasts typical discrete-event simulation (DES) execution algorithms with how events are selected and ordered by the discrete-event system specification (DEVS) formalism. The motivation for this research stems from a desire to understand how the selection of events affects simulation output (i.e., response). As a particular use case, we briefly investigate the processing of simultaneous events by the Advanced Framework for Simulation, Integration and Modeling (AFSIM), a military discrete-event combat modeling and simulation package. To facilitate the building of classic DEVS-based models, the python software package PythonPDEVS is used. Initial results indicate that the explicit modeling of how simultaneous events are selected as promoted by the DEVS formalism plays a significant role on simulation results

    Quantifying the Effects of Weapon Weight on Lethality through Holistic Modeling

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    Though it is widely known that weapon weight affects shooter stability, the quantitative effects on lethality and survivability are not well known. This issue stems from weapon lethality primarily being captured by equipment properties. A more holistic analysis can be performed by treating the soldier as a system by incorporating human factors with equipment performance specifications. This analysis requires the building of human factor models to appropriately capture lethality. The model development effort started with the collecting of data from experiments where the shot group accuracy was measured for weighted rifles. The resulting data was used to generate a mathematical model. This model, along with other human factor models, was integrated into the Weapon Lethality Service (WLS), a cloud-based simulation. The WLS was then set up to represent possible combat situations; the results were used to quantify the change in soldier lethality and survivability from changing the weapon weight

    Modelling and Simulation of a River-Crossing Operation via Discrete Event Simulation with Engineering Details

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    From a military standpoint, a river is an area that should be avoided in a potential engagement because of lack of cover and the necessity of dividing the unit while crossing. Thus, a key point of a river-crossing operation is speed. Many efforts have been made to enable faster river crossing by improvement of tactics, techniques, and procedures (TTP). However, improvements in TTP are evaluated by modelling and simulation much less frequently than are the toe-to-toe engagements between two opposing forces, and to our knowledge, this is the first simulation model of brigade-level river crossing with engineering details. This study presents a simulation model of the river-crossing operation, applies real world parameters, and evaluates which tactics are preferable in a particular operational environments. This analysis has led to new operational methods of river crossing that have been suggested by experienced subject-matter experts. For instance, the current Republic of Korea Army Field Manual dictates to rotate river-crossing rafts in all situations, but our experiment suggests that no rotation is preferable when the width of river is less than 400 m based on the statistical analyses, which includes the regression-based meta-modelling and the ANOVA, of our simulation model that embodies the engineering details of river-crossing equipment.Defence Science Journal, Vol. 65, No. 2, March 2015, pp.135-143, DOI:http://dx.doi.org/10.14429/dsj.65.814

    Network-based Metric for Measuring Combat Effectiveness

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    A conceptual definition of combat effectiveness is the overall capability of a force to produce a desiredoutcome from combat against an enemy force. An ability to measure combat effectiveness is critical to strategic andtactical decision making; however, it is a challenging task to develop an operational metric for combat effectivenessdue to the large complexity presented by the rich context of a combat environment. The present paper contendsthat, under a direct fire engagement, combat effectiveness can be reasonably assessed by the prevalence of attack opportunities a given force creates in a combat environment. The paper proposes a method to quantitatively measurecombat effectiveness of a military force in a direct fire engagement environment. The proposed metric is basedon a meta-network representation that captures various aspects of a combat environment. Using a meta-networkrepresentation, two types of basic unit structures of attack opportunity – isolated and networked – are identified,which are then used as a basic element for measuring combat effectiveness. Prevalence of network motifs in anetworked combat environment and availability of attack opportunities are computed as a measure of a militaryforce’s combat effectiveness.Defence Science Journal, 2014, 64(2), pp. 115-122. DOI: http://dx.doi.org/10.14429/dsj.64.553

    Model Driven Combat Effectiveness Simulation Systems Engineering

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    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

    Emergent Behavior Development and Control in Multi-Agent Systems

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    Emergence in natural systems is the development of complex behaviors that result from the aggregation of simple agent-to-agent and agent-to-environment interactions. Emergence research intersects with many disciplines such as physics, biology, and ecology and provides a theoretical framework for investigating how order appears to spontaneously arise in complex adaptive systems. In biological systems, emergent behaviors allow simple agents to collectively accomplish multiple tasks in highly dynamic environments; ensuring system survival. These systems all display similar properties: self-organized hierarchies, robustness, adaptability, and decentralized task execution. However, current algorithmic approaches merely present theoretical models without showing how these models actually create hierarchical, emergent systems. To fill this research gap, this dissertation presents an algorithm based on entropy and speciation - defined as morphological or physiological differences in a population - that results in hierarchical emergent phenomena in multi-agent systems. Results show that speciation creates system hierarchies composed of goal-aligned entities, i.e. niches. As niche actions aggregate into more complex behaviors, more levels emerge within the system hierarchy, eventually resulting in a system that can meet multiple tasks and is robust to environmental changes. Speciation provides a powerful tool for creating goal-aligned, decentralized systems that are inherently robust and adaptable, meeting the scalability demands of current, multi-agent system design. Results in base defense, k-n assignment, division of labor and resource competition experiments, show that speciated populations create hierarchical self-organized systems, meet multiple tasks and are more robust to environmental change than non-speciated populations

    Exploring the Components of Dynamic Modeling Techniques

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    Upon defining the terms modeling and simulation, it becomes apparent that there is a wide variety of different models, using different techniques, appropriate for different levels of representation for any one system to be modeled. Selecting an appropriate conceptual modeling technique from those available is an open question for the practitioner. Existing methods for describing techniques do not capture enough information about the expressive potential of those techniques such that an appropriate selection decision can be made. A formal method to describe conceptual modeling techniques that captures enough about the technique to distinguish it from others is identified as a way to address this gap in the body of knowledge. Such a formal method is derived, and is given additional expressive strength in the special area of dynamic components of conceptual modeling techniques. Application of the formal method to actual conceptual modeling techniques is exhibited, and the capacity of the method to also identify the potential for extension of an existing method is also exhibited. Measures of merit, designed to evaluate the derived method, are tested and shown to be satisfied

    Software Frameworks for Model Composition

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    A software framework is an architecture or infrastructure intended to enable the integration and interoperation of software components. Specialized types of software frameworks are those specifically intended to support the composition of models or other components within a simulation system. Such frameworks are intended to simplify the process of assembling a complex model or simulation system from simpler component models as well as to promote the reuse of the component models. Several different types of software frameworks for model composition have been designed and implemented; those types include common library, product line architecture, interoperability protocol, object model, formal, and integrative environment. The various framework types have different components, processes for composing models, and intended applications. In this survey the fundamental terms and concepts of software frameworks for model composition are presented, the different types of such frameworks are explained and compared, and important examples of each type are described
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