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Articles 511 - 540 of 839
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Hydrogen Infrastructure: Resource Evaluation And Capacity Modeling, Kevin B. Martin
Hydrogen Infrastructure: Resource Evaluation And Capacity Modeling, Kevin B. Martin
Doctoral Dissertations
"A hydrogen economy could offer energy stability, economical, and environmental benefits. Several issues are involved in the design and implementation of a hydrogen economy such as the selection of feedstocks, generation and storage technologies, transportation methods, appropriate equipment capacity, codes/standards and public awareness. The design of a hydrogen infrastructure may seem insurmountable; however, as the system is deconstructed a proper design can be achieved. In order to better understand how a hydrogen system for light duty vehicles might operate, both hydrogen resource and capacity analysis and modeling is conducted. Specifically, an evaluation of leading near term production and distribution technologies …
Communication Models For Monitoring And Mobility Verification In Mission Critical Wireless Networks, Maheswaran Thiagarajan
Communication Models For Monitoring And Mobility Verification In Mission Critical Wireless Networks, Maheswaran Thiagarajan
Masters Theses
"Recent technological advances have seen wireless sensor networks emerge as an interesting research topic because of its ability to realize mission critical applications like in military or wildfire detection. The first part of the thesis focuses on the development of a novel communication scheme referred here as a distributed wireless critical information-aware maintenance network (DWCIMN), which is presented for preventive maintenance of network-centric dynamic systems. The proposed communication scheme addresses quality of service (QoS) issues by using a combination of a head-of-the-line queuing scheme, efficient bandwidth allocation, weight-based backoff mechanism, and a distributed power control scheme. A thorough analysis of …
On The Effects Of Small-Scale Fading And Mobility In Mobile Wireless Communication Network, Bandana Paudel
On The Effects Of Small-Scale Fading And Mobility In Mobile Wireless Communication Network, Bandana Paudel
Masters Theses
"In this study, a comprehensive analysis of the impact of mobility on end-to-end performance measures of Mobile Ad Hoc Network is performed by using small-scale fading models. Network simulation is performed in order to study a wide range of phenomena occurring during MANET communication. The effectiveness of three reactive routing protocols against different level of mobility is observed under varying network parameter like the network size, number of nodes and network connectivity. The study reveals that the network sparseness or density favors one or the other routing mechanism under varying mobility. Outcome of the simulation also provides a great deal …
Preventing Chemical Product Failure, Kenneth Ombete
Preventing Chemical Product Failure, Kenneth Ombete
Masters Theses
"The purpose of this thesis is to demonstrate a research methodology to prevent chemical product failures. This methodology extends the risk in early design (RED) method for prevention of failure in electromechanical products to include products with chemical subsystems. Inclusion of this domain is demanded by the ever-growing semiconductor and energy industries. The RED method was extended by first identifying principal chemical failure modes and adding them to the failure mode taxonomy. The RED database was then augmented with historical failures of products that included chemical subsystems. Finally, the extension was validated with a case study of a fuel cell"--Abstract, …
An Analysis Of Lessons Learned And Best Practices From Fuel Cell Applications With An Emphasis On Hydrogen Technology, Clint Alex Cottrell
An Analysis Of Lessons Learned And Best Practices From Fuel Cell Applications With An Emphasis On Hydrogen Technology, Clint Alex Cottrell
Masters Theses
"In its review of the Department of Energy's Research Development and Demonstration (RD&D) plan for hydrogen, the National Academies recommended a study of lessons learned from technologies developed for stationary fuel cell power systems. Thus, the motivation for this thesis is to study and identify the lessons learned and best practices from prior stationary fuel cell power programs. To understand how to prepare for this technology, this study conducted a thorough investigation of past stationary alternative power projects to assess the opportunities for future stationary power efforts, and how this information can be used to meet objectives for future fuel …
Public-Private Partnerships In High Risk Transportation Projects, Kiran Rangarajan
Public-Private Partnerships In High Risk Transportation Projects, Kiran Rangarajan
Masters Theses
"This research examines Public-Private Partnerships (PPPs) between private firms and City of Chamois, Missouri to establish a ferry boat service across the Missouri River. The study illustrates the role of PPPs in managing high risk transportation projects for rural economic development. The research study was designed to accomplish three objectives. First, understand and study the high risk transportation industry which included analyzing other ferry services in and around the region, and identifying potential risks involved in a ferry boat project. Second, study various models of PPPs, identify the attributes of each model and select appropriate models based on local and …
Project Collaboration In A Distributed Environment, Shriroopa Prabhakar Deshpande
Project Collaboration In A Distributed Environment, Shriroopa Prabhakar Deshpande
Masters Theses
"This thesis investigates methods of managing projects in an environment where project team members are in different locations. Today, large scale projects undertaken by firms that have a global presence are successfully developed across time, distance, and geographic boundaries. In order to survive in this environment, firms face many project challenges, including diverse employees, various work practices, and communication issues. Many communication issues can be minimized by the proper use of collaborative tools as well as by sharing expertise, coordinating activities, and managing relationships. Web-enabled project management tools have enhanced efforts to increase the quality, competitiveness, and profitability of these …
Adapting Management Strategies To Enter New Global Markets, Karuna Vineetha Vemulapalli
Adapting Management Strategies To Enter New Global Markets, Karuna Vineetha Vemulapalli
Masters Theses
"With globalization spreading its roots into every country, people from various countries are working together, and will be trying to understand the cultural differences between the organizations in different nations. Effective management of the cultural differences will be an important and competitive advantage. Keeping in mind the different perceptions of the term “Management” by varying cultures, namely United States and India, this research will be focused on understanding and managing these differences.
The proposed research will deal with concepts of cultural diversity, economic differences, intercultural and organizational differences between the two countries. Understanding why some factors like motivation, responsibility, and …
Development And Use Of Computer Aided Tools To Enhance Team Dynamics With Role Play Simulations, Vachaspathy Kuntamukkala
Development And Use Of Computer Aided Tools To Enhance Team Dynamics With Role Play Simulations, Vachaspathy Kuntamukkala
Masters Theses
"This thesis proposes a methodology for the development and use of computer based tools to enhance student team dynamics. Working effectively in groups cannot be taught in class room environment. Students often encounter conflicts during team meetings. Although some conflicts are resolved by the efforts of team members, an unbiased facilitator who is not a member of the team is often needed to help. This work proposes a tool that uses role play simulations to engage students in real-life scenarios so that they gain a practical, as well as a theoretical, understanding of how to work effectively as a team. …
Xftsp: A Tool For Time Series Prediction By Means Of Fuzzy Inference Systems, Federico Montesino, Amaury Lendasse, Ángel Barriga
Xftsp: A Tool For Time Series Prediction By Means Of Fuzzy Inference Systems, Federico Montesino, Amaury Lendasse, Ángel Barriga
Engineering Management and Systems Engineering Faculty Research & Creative Works
A New Software Tool for Time Series Prediction by Means of Fuzzy Inference Systems is Reported. This Tool, Named XFTSP, implements a Novel Methodology for Time Series Prediction based on Methods for Automatic Fuzzy Systems Identification and Supervised Learning Combined with Statistical Methods for Nonparametric Residual Variance Estimation. XFTSP is Designed as a Tool Integrated in the Xfuzzy Development Environment for Fuzzy Systems. Experiments Carried Out on a Number of Time Series Benchmarks Show the Advantages of XFTSP in Terms of Both Accuracy and Computational Requirements as Compared Against Least-Squared Support Vector Machines, an Established Technique in the Field of …
On Step Sizes, Stochastic Shortest Paths, And Survival Probabilities In Reinforcement Learning, Abhijit Gosavi
On Step Sizes, Stochastic Shortest Paths, And Survival Probabilities In Reinforcement Learning, Abhijit Gosavi
Engineering Management and Systems Engineering Faculty Research & Creative Works
Reinforcement learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the problems have a very large number of states. We present an empirical study of (i) the effect of step-sizes (learning rules) in the convergence of RL algorithms, (ii) stochastic shortest paths in solving average reward problems via RL, and (iii) the notion of survival probabilities (downside risk) in RL. We also study the impact of step sizes when function approximation is combined with RL. Our experiments yield some interesting insights that will be useful in practice …
Comparing Component Functional Template Modeling Experimental Results In An Undergraduate Level Engineering Design Course, Daniel Abbott, Katie Grantham Lough
Comparing Component Functional Template Modeling Experimental Results In An Undergraduate Level Engineering Design Course, Daniel Abbott, Katie Grantham Lough
Engineering Management and Systems Engineering Faculty Research & Creative Works
Component functional templates are a foundational tool, for the functional modeling method, that novice users can implement to develop functional modeling skills and produce better results by not requiring the modeler to have extensive background knowledge in the method. the templates provide common function layouts of ordinary electromechanical components that are based on historic data collected from design information on a wide range of consumer products. a previous experiment has been performed on a sophomore level design class to assess the change in quality between functional modeling results with and without the use of component functional templates. to address further …
Design For Manufacturing (Dfm) Methodology To Implement Friction Stir Welding (Fsw) For Automobile Chassis Fabrication, Harish Bagaitkar, Venkat Allada
Design For Manufacturing (Dfm) Methodology To Implement Friction Stir Welding (Fsw) For Automobile Chassis Fabrication, Harish Bagaitkar, Venkat Allada
Engineering Management and Systems Engineering Faculty Research & Creative Works
The manufacturing functional feasibility of implementing Friction Stir Welding (FSW) for automobile chassis fabrication is discussed using a case study. in the case study, the Design for Manufacturing (DFM) principles are applied to manufacture an aluminum automobile chassis. Various DFM issues are addressed while proposing the FSW technique as an alternative to laser welding and metal inert gas welding techniques. DFM guidelines involving joint design change, component geometries, and component elimination are discussed in this paper. by making appropriate changes in the component geometries and joint designs and eliminating some components, more than 50% of the joints in the example …
A Model Based Fault Detection And Prognostic Scheme For Uncertain Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani
A Model Based Fault Detection And Prognostic Scheme For Uncertain Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A new fault detection and prognostics (FDP) framework is introduced for uncertain nonlinear discrete time system by using a discrete-time nonlinear estimator which consists of an online approximator. A fault is detected by monitoring the deviation of the system output with that of the estimator output. Prior to the occurrence of the fault, this online approximator learns the system uncertainty. In the event of a fault, the online approximator learns both the system uncertainty and the fault dynamics. A stable parameter update law in discrete-time is developed to tune the parameters of the online approximator. This update law is also …
Neural Network Output Feedback Control Of A Quadrotor Uav, Jagannathan Sarangapani, Travis Alan Dierks
Neural Network Output Feedback Control Of A Quadrotor Uav, Jagannathan Sarangapani, Travis Alan Dierks
Electrical and Computer Engineering Faculty Research & Creative Works
A neural network (NN) based output feedback controller for a quadrotor unmanned aerial vehicle (UAV) is proposed. The NNs are utilized in the observer and for generating virtual and actual control inputs, respectively, where the NNs learn the nonlinear dynamics of the UAV online including uncertain nonlinear terms like aerodynamic friction and blade flapping. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semi-globally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional …
Neural-Network-Based State Feedback Control Of A Nonlinear Discrete-Time System In Nonstrict Feedback Form, Pingan He, Jagannathan Sarangapani
Neural-Network-Based State Feedback Control Of A Nonlinear Discrete-Time System In Nonstrict Feedback Form, Pingan He, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a suite of adaptive neural network (NN) controllers is designed to deliver a desired tracking performance for the control of an unknown, second-order, nonlinear discrete-time system expressed in nonstrict feedback form. In the first approach, two feedforward NNs are employed in the controller with tracking error as the feedback variable whereas in the adaptive critic NN architecture, three feedforward NNs are used. In the adaptive critic architecture, two action NNs produce virtual and actual control inputs, respectively, whereas the third critic NN approximates certain strategic utility function and its output is employed for tuning action NN weights …
On Nonparametric Residual Variance Estimation, Elia Liitiäinen, Francesco Corona, Amaury Lendasse
On Nonparametric Residual Variance Estimation, Elia Liitiäinen, Francesco Corona, Amaury Lendasse
Engineering Management and Systems Engineering Faculty Research & Creative Works
In This Paper, the Problem of Residual Variance Estimation is Examined. the Problem is Analyzed in a General Setting Which Covers Non-Additive Heteroscedastic Noise under Non-Iid Sampling. to Address the Estimation Problem, We Suggest a Method based on Nearest Neighbor Graphs and We Discuss its Convergence Properties under the Assumption of a Hölder Continuous Regression Function. the Universality of the Estimator Makes It an Ideal Tool in Problems with Only Little Prior Knowledge Available. © 2008 Springer Science business Media, LLC.
Long-Term Prediction Of Time Series Using Nne-Based Projection And Op-Elm, Antti Sorjamaa, Yoan Miche, Robert Weiss, Amaury Lendasse
Long-Term Prediction Of Time Series Using Nne-Based Projection And Op-Elm, Antti Sorjamaa, Yoan Miche, Robert Weiss, Amaury Lendasse
Engineering Management and Systems Engineering Faculty Research & Creative Works
This Paper Proposes a Combination of Methodologies based on a Recent Development -Called Extreme Learning Machine (Elm)- Decreasing Drastically the Training Time of Nonlinear Models. Variable Selection is Beforehand Performed on the Original Dataset, using the Partial Least Squares (Pls) and a Projection based on Nonparametric Noise Estimation (NNE), to Ensure Proper Results by the Elm Method. Then, after the Network is First Created using the Original Elm, the Selection of the Most Relevant Nodes is Performed by using a Least Angle Regression (Lars) Ranking of the Nodes and a Leave-One-Out Estimation of the Performances, Leading to an Optimally Pruned …
Optimal Pruned K-Nearest Neighbors: Op-Knn - Application To Financial Modeling, Q. Yu, A. Sorjamaa, Y. Miche, Amaury Lendasse, Eric Séverin, A. Guillen, F. Mateo
Optimal Pruned K-Nearest Neighbors: Op-Knn - Application To Financial Modeling, Q. Yu, A. Sorjamaa, Y. Miche, Amaury Lendasse, Eric Séverin, A. Guillen, F. Mateo
Engineering Management and Systems Engineering Faculty Research & Creative Works
The Paper Proposes a Methodology Called OO-KNN, Which Builds a One Hidden-Layer Feedforward Neural Network, using Nearest Neighbors Neurons with Extremely Small Computational Time. the Main Strategy is to Select the Most Relevant Variables Beforehand, Then to Build the Model using KNN Kernels. Multi response Sparse Regression (MRSR) is Used as the Second Step in Order to Rank Each Kth Nearest Neighbor and Finally as a Third Step Leave-One-Out Estimation is Used to Select the Number of Neighbors and to Estimate the Generalization Performances. This New Methodology is Tested on a Toy Example and is Applied to Financial Modeling. © …
Fuzzy Inference Based Autoregressors For Time Series Prediction Using Nonparametric Residual Variance Estimation, Federico Montesino Pouzols, Amaury Lendasse, Angel Barriga
Fuzzy Inference Based Autoregressors For Time Series Prediction Using Nonparametric Residual Variance Estimation, Federico Montesino Pouzols, Amaury Lendasse, Angel Barriga
Engineering Management and Systems Engineering Faculty Research & Creative Works
We Apply Fuzzy Techniques for System Identification and Supervised Learning in Order to Develop Fuzzy Inference based Auto regressors for Time Series Prediction. an Automatic Methodology Framework that Combines Fuzzy Techniques and Statistical Techniques for Nonparametric Residual Variance Estimation is Proposed. Identification is Performed through the Learn from Examples Method Introduced by Wang and Mendel, While the Marquard-Levenberg Supervised Learning Algorithm is Then Applied for Tuning. Delta Test Residual Noise Estimation is Used in Order to Select the Best Subset of Inputs as Well as the Number of Linguistic Labels for the Inputs. Experimental Results for Three Time Series Prediction …
Function-Based Failure Propagation For Conceptual Design, Daniel A. Krus, Katie Grantham
Function-Based Failure Propagation For Conceptual Design, Daniel A. Krus, Katie Grantham
Engineering Management and Systems Engineering Faculty Research & Creative Works
When designing a product, the earlier the potential risks can be identified, the more costs can be saved, as it is easier to modify a design in its early stages. Several methods exist to analyze the risk in a system, but all require a mature design. However, by applying the concept of “common interfaces” to a functional model and utilizing a historical knowledge base, it is possible to analyze chains of failures during the conceptual phase of product design. This paper presents a method based on these common interfaces to be used in conjunction with other methods such as risk …
A Model Based Fault Detection Scheme For Nonlinear Multivariable Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani
A Model Based Fault Detection Scheme For Nonlinear Multivariable Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a novel robust scheme is developed for detecting faults in nonlinear discrete time multi-input and multi-output systems in contrast with the available schemes that are developed in continuous-time. Both state and output faults are addressed by considering separate time profiles. The faults, which could be incipient or abrupt, are modeled using input and output signals of the system. By using nonlinear estimation techniques, the discrete-time system is monitored online. Once a fault is detected, its dynamics are characterized using an online approximator. A stable parameter update law is developed for the online approximator scheme in discrete-time. The …
Sr-2: A Hybrid Algorithm For The Capacitated Vehicle Routing Problem, Angel A. Juan, Javier Faulin, Josep Jorba, Barry Barrios, Scott Erwin Grasman
Sr-2: A Hybrid Algorithm For The Capacitated Vehicle Routing Problem, Angel A. Juan, Javier Faulin, Josep Jorba, Barry Barrios, Scott Erwin Grasman
Engineering Management and Systems Engineering Faculty Research & Creative Works
During the last decades a lot of work has been devoted to develop algorithms that can provide near-optimal solutions for the capacitated vehicle routing problem (CVRP). Most of these algorithms are designed to minimize an objective function, subject to a set of constraints, which typically represents aprioristic costs. This approach provides adequate theoretical solutions, but they do not always fit real-life needs since there are some important costs and some routing constraints or desirable properties that cannot be easily modeled. In this paper, we present a new approach which combines the use of Monte Carlo simulation and parallel and grid …
Network-Centric Localization In Manets Based On Particle Swarm Optimization, Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy, Ann K. Miller, Cihan H. Dagli
Network-Centric Localization In Manets Based On Particle Swarm Optimization, Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy, Ann K. Miller, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
There exist several application scenarios of mobile ad hoc networks (MANET) in which the nodes need to locate a target or surround it. Severe resource constraints in MANETs call for energy efficient target localization and collaborative navigation. Centralized control of MANET nodes is not an attractive solution due to its high network utilization that can result in congestions and delays. In nature, many colonies of biological species (such as a flock of birds) can achieve effective collaborative navigation without any centralized control. Particle swarm optimization (PSO), a popular swarm intelligence approach that models social dynamics of a biological swarm is …
Optimal Energy-Delay Routing Protocol With Trust Levels For Wireless Ad Hoc Networks, Eyad Taqieddin, Ann K. Miller, Jagannathan Sarangapani
Optimal Energy-Delay Routing Protocol With Trust Levels For Wireless Ad Hoc Networks, Eyad Taqieddin, Ann K. Miller, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents the Trust Level Routing (TLR) pro- tocol, an extension of the optimized energy-delay rout- ing (OEDR) protocol, focusing on the integrity, reliability and survivability of the wireless network. TLR is similar to OEDR in that they both are link state routing proto- cols that run in a proactive mode and adopt the concept of multi-point relay (MPR) nodes. However, TLR aims at incorporating trust levels into routing by frequently changing the MPR nodes as well as authenticating the source node and contents of control packets. TLR calcu- lates the link costs based on a composite metric (delay …
Reinforcement Learning Based Dual-Control Methodology For Complex Nonlinear Discrete-Time Systems With Application To Spark Engine Egr Operation, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Reinforcement Learning Based Dual-Control Methodology For Complex Nonlinear Discrete-Time Systems With Application To Spark Engine Egr Operation, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement-learning-based dual-control methodology adaptive neural network (NN) controller is developed to deliver a desired tracking performance for a class of complex feedback nonlinear discrete-time systems, which consists of a second-order nonlinear discrete-time system in nonstrict feedback form and an affine nonlinear discrete-time system, in the presence of bounded and unknown disturbances. For example, the exhaust gas recirculation (EGR) operation of a spark ignition (SI) engine is modeled by using such a complex nonlinear discrete-time system. A dual-controller approach is undertaken where primary adaptive critic NN controller is designed for the nonstrict feedback nonlinear discrete-time system whereas the secondary …
Damping Inter-Area Oscillations By Upfcs Based On Selected Global Measurements, Mahyar Zarghami, Yilu Liu, Jagannathan Sarangapani, Mariesa Crow
Damping Inter-Area Oscillations By Upfcs Based On Selected Global Measurements, Mahyar Zarghami, Yilu Liu, Jagannathan Sarangapani, Mariesa Crow
Electrical and Computer Engineering Faculty Research & Creative Works
This paper introduces a method of using a selected set of the global data for controlling inter-area oscillations of the power network using unified power flow controllers. This novel algorithm utilizes reduced order observers for estimating the missing data the purpose of control when all the data is unavailable through frequency measurements in a wide area control approach. The paper will also address the problem of time-delay in data acquisition through examples.
System Of Systems: Power And Paradox, Joseph J. Simpson, Cihan H. Dagli
System Of Systems: Power And Paradox, Joseph J. Simpson, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
Systems concepts and artifacts provide the basis for enumerable sources of power and wealth in our modern world. Culture, art and science all are based on established systems of behavior, values and thought. The current environment is densely populated with physical system artifacts that are used in every aspect of human life. The ubiquitous nature of existing systems has generated a strong interest in using an existing set of systems as the basis for a system of systems. Further interest in the system-of-systems approach is stimulated by rapid development, deployment and expansion of new and existing systems. While successful system …
Public-Private Partnerships For Technology Growth In The Public Sector, F. Lera-Lopez, Scott Erwin Grasman, Javier Faulin
Public-Private Partnerships For Technology Growth In The Public Sector, F. Lera-Lopez, Scott Erwin Grasman, Javier Faulin
Engineering Management and Systems Engineering Faculty Research & Creative Works
Public-private partnerships (PPP) are a mechanism for financing large infrastructure development such as transportation projects, hospitals, schools, and public works facilities. In addition, the benefits of PPP stretch well into the realm of engineering management. Most notably, PPPs provide the opportunity for more efficient project management, proficient risk mitigation, and enhanced technological innovation. This paper provides a general description of the typical PPP process and how this process can be used to improve management of technology in the public sector.
An Executable System Architecture Approach To Discrete Events System Modeling Using Sysml In Conjunction With Colored Petri Net, Renzhong Wang, Cihan H. Dagli
An Executable System Architecture Approach To Discrete Events System Modeling Using Sysml In Conjunction With Colored Petri Net, Renzhong Wang, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
This paper proposes an executable system architecting paradigm for discrete event system modeling and analysis through integration of a set of architecting tools, executable modeling tools, analytical tools, and visualization tools. The essential step is translating SysML-based specifications into colored Petri nets (CPNs) which enables rigorous static and dynamic system analysis as well as formal verification of the behavior and functionality of the SysML-based design. A set of tools have been studied and integrated that enable a structured architecture design process. Some basic principles of executable system architecture for discrete event system modeling that guide the process of executable architecture …