Chapter 1 - Introduction to Modeling and Simulation
This chapter introduces the novice to the main ideas of modeling and simulation for science and engineering along with some basic modeling and simulation vocabulary and terms. The chapter opens with some definitions of modeling and simulation and several examples of how and where it is used. It then introduces the idea of a simulation study, the process used to develop models and simulations for such studies, and what is entailed at each step. The readers are then introduced to modeling and simulation methodologies, including discrete-event simulations, continuous simulations, agent-based modeling, and systems dynamics. This chapter ends with an explanation how Monte Carlo technique is used in science and engineering.
Chapter 2 - Effectively Incorporating Modeling and Simulation into Classroom Instruction
This chapter describes the use of inquiry-based instruction to effectively incorporate modeling and simulation into classroom instruction. Science teachers have always been concerned about engaging students in the content of the subjects they teach. It is very easy for students to see science as a complex, fact-driven field of study in which all of the basics have already been determined. Especially with the great advances in personal computers and technology in general over the past few years, it is all too easy for students to view traditional science courses as not relevant to their everyday life. Teachers are always on the lookout for approaches that make instruction both relevant and enjoyable while at the same time maintaining academic rigor. One approach that is starting to gain traction in education is in the use of models and simulations (MODSIM) in the classroom.
There are three sections in this chapter. The first section discusses inquiry-based instruction and how the use of a guided inquiry model is particularly suitable for using MODSIM as an instructional tool. The second section describes the MODSIM School Demonstration Project undertaken as a collaboration of NASA Langley Research Center, the National Institute of Aerospace (NIA), and the Virginia Beach (Virginia) City Public Schools using inquiry-based instruction with models and simulations. Finally, the third and largest section contains example lessons utilizing this approach.
Chapter 3 - Live, Virtual, and Constructive Models and Simulations for Test and Evaluation
This chapter defines three categories of modeling and simulation and the practice of test and evaluation (T&E) as used throughout industry and government research and development agencies and departments – in this particular chapter, by the Department of Defense. The chapter first describes what Test and Evaluation is and explains why T&E is conducted on a new product. Examples are provided and risk and test planning are defined. Next, live, virtual, and constructive (LVC) simulations in test and evaluation are defined as three basic categories of simulation. Examples are provided as to the strengths and weaknesses of each category. Systems Integration Laboratories are described, as is validation and verification (V&V) for models and simulations. Live, virtual, and constructive simulations are then described in the integration of several LVC components into a distributed test event.
Chapter 4 – Live, Virtual, and Constructive Modeling and Simulation for Training
This chapter provides an introduction to live, virtual, and constructive (LVC) modeling and simulation (M&S) for training. While Chapter 3 discussed bringing a simulation to fruition via T&E, this chapter details one of the uses of the completed simulation: training. LVC simulations are being used by the military, space, safety, transportation, and other organizations to provide effective training for individuals and teams at various levels of fidelity. LVC simulations save time, money, and lives while achieving an improvement in human performance. In this chapter the reader will gain an understanding of LVC modeling and simulation by learning to categorize LVC as it pertains to training applications. The reader will also get an illustrated overview of the history of modeling and simulation for training from very early attempts to the present day and future promises. The chapter concludes with an introduction to LVC architectures and the cultural, technical, and economic challenges and considerations associated with integrating LVC in support of individual, small- to large-scale training exercises.
Chapter 5 – Using Computer Simulation to Make Better Business Decisions
This chapter is an introduction to how computer simulation can be used in business to improve the decisions that business managers make. In the scenarios that this chapter addresses, improved decisions result in increased profit, reduced cost, and better service to customers. The chapter first describes basic business concepts such as profit, customer service, capacity, and demand. Understanding these terms is important because the purpose of simulation is to help managers make decisions about capacity that is used to make goods and provide services in response to customer demand and, as a result, to improve profit and customer service. A familiar setting is used as an example in this chapter, specifically, a fast-food restaurant. The succession of lessons in this chapter ultimately leads to a description of how a computer simulation model might be created to mimic the operations of the restaurant to help a manager understand how different decisions, such as purchasing equipment, augmenting or reducing staff, and re-assigning/cross-training staff, lead to different levels of profit and customer service. Essential background information and skills are provided throughout the chapter, such as the concept of probability distributions and Excel spreadsheet functions that are required to create the simulation model.
Chapter 6 – Agent-based Modeling
The traditional view of modeling and simulation is to model the entire system and the interactions between different entities of the system based on clearly defined and well understood theories. Although we may not be able to identify and describe various system behaviors top down, we may be able to identify the main components, what they do, and how they are related. For example, we cannot describe the traffic in New York City as a function, but we know that cars – in particular yellow taxis – and utility trucks play a major role. The movements of the vehicles are constrained by traffic lights, traffic regulators, sidewalks, and pedestrians. Instead of trying to come up with a complex fluid-mechanic solution, each taxi, car, truck, regulator, and potential pedestrian is modeled as an agent. Instead of describing the system behavior top down in form of functions, we only define the components and their interplay and observe the system behavior that emerges bottom up. An agent-based model consists of a collection of autonomous agents. Each agent is able to make decisions based on a set of software instructions programmed to model its behavior, according to how it interacts with its environment and with other agents. Agent-based modeling provides a powerful method to model behavior of complex system that would otherwise not be possible using traditional approaches.
Flight Fidelity: Engineering with Practical Mathematics
High school college-prep physics students will use the iterative engineering design process to build a model rocket capable of carrying a specific payload. During the test flights, the students will work both to ensure that their designs fly with a minimal amount of horizontal velocity, and that they fly as high as possible. The students will measure and record the maximum height attained by their rockets.
The students will then describe the forces acting on the rockets when they are in flight, including a drag force model that varies with the square of velocity. Using Newton’s laws of motion, the students will develop the equations describing the motion of the rockets. This project is an ideal platform for students to see the practical application of mathematical concepts (such as Riemann sums) to which they have been exposed in their higher-level mathematics courses. Additionally, this project takes advantage of the cognitive maturity of calculus-based physics students, motivating them to use high-level mathematical paradigms (such as the Euler method of integration) to bring relevance to the theory they have learned in their math and science courses.
Stress and Strength Testing
This unit focuses on the concepts of stress, strength, deflection, point of failure, allowable strength, modulus of rupture, and factor of safety. To model these concepts in action and allow the students to conduct their own tests, the experiment tests the strength of popsicle sticks of varying sizes. The strength of a material is defined as the amount of stress that causes failure. Failure occurs when the stress is larger than the strength, causing the popsicle stick to break under the given load (weight). Students collect a range of data that will be compiled by the teacher. The experimenters are asked to organize, display, and analyze that data in different ways. Once these basic concepts are understood, the students are tasked with an engineering project, the design of a bridge that can withstand a maximum amount of stress before failing. The students test their designs using a computer-based bridge building simulation, make any revisions necessary, and then construct the actual bridge using popsicle sticks and glue. The bridges are tested by the teacher to determine their strength.
As a part of a new focus on moving out into our solar system, NASA has increased its emphasis in several areas, including research into xenobiology and the interactions of differing life forms from very disparate environments. This unit will be used as a means to explore the interactions between ourselves and potential alien life forms from beyond our earthly environment in order to determine the potential positive and negative consequences. In particular, this unit will focus on student problem-solving activities in order to develop a plan should one of several scenarios unfold involving the introduction of alien microbial life on Earth.
This unit was designed in order to 1) integrate modeling and simulation into lesson activities as a means to teach the engineering design process to students; and 2) provide students with the opportunity to apply previously-mastered content in biology to real-world scenarios while scaffolding in specific content regarding the characteristics of microorganisms and how they can help/hurt the environment and other organisms. Each lesson can be used as an individual activity in genetics, evolution, classification, or microorganisms, or can be used in tandem to emphasize the ModSim model.
Troubled Waters: Water Quality, Usage, and Reclamation
This unit focuses on water reclamation. It features a simulation that allows students to follow water from pristine and logging forests through residential and commercial areas into wetlands and urban areas. Students have the opportunity to explore a number of water quality issues, including how land use affects water quality, how to collect and analyze data related to water quality, and how water filtration systems work, both in general and in their communities. The lessons culminate in an actual engineering project to design, build, and operate a wastewater filtration system. The unit as a whole contains a number of activities which build upon each other, but each can also be used as a stand-alone activity to teach individual concepts. This lesson is intended for use in high school biology, chemistry, environmental science, Earth science, ecology, urban studies or sustainability classes. Students are expected to have a basic understanding of ecosystems, the water cycle, data collection, percent composition, and graphical analysis.
Exploring Trajectory Optimization Using Simulation
This unit focuses on trajectory optimization, a key tool in engineering design. The unit is framed as an engineering design challenge that requires the students to attempt to design an optimized trajectory for iRobot’s Roomba, an autonomous robotic vacuum cleaner. Students are introduced to how modeling and simulation is used at NASA to optimize the design of helicopters, airplanes, and space vehicles. Through a series of activities, including the use of a Traveling Salesman Problem Computer Simulation and a Roomba Trajectory Simulation that utilizes student data, students gain an understanding of how modeling and simulation can be useful, and are in fact essential, to engineers.