Rapid advances of computer modeling and simulation tools and computing hardware have turned Model Based Design (MBD) a more viable technology. However, using a computationally intensive, “black-box” form MBD software tool to carry out design optimization leads to a number of key challenges. The non-unimodal objective function and/or non-convex feasible search region of the implicit numerical simulations in the optimization problems are beyond the capability of conventional optimization algorithms. In addition, the computationally intensive simulations used to evaluate the objective and/or constraint functions during the MBD process also make conventional stochastic global optimization algorithms unusable due to their requirement of a huge number of objective and constraint function evaluations. Surrogate model, or metamodeling-based global optimization techniques have been introduced to address these issues. Various surrogate models, including kriging, radial basis functions (RBF), multivariate adaptive regression splines (MARS), and polynomial regression (PR), are built using limited samplings on the original objective/constraint functions to reduce needed computation in the search of global optimum. In many real-world design optimization applications, computationally expensive numerical simulation models are used as objective and/or constraint functions. To solve these problems, enormous fitness function evaluations are required during the evolution based search process when advanced Global Optimization algorithms, such as DIRECT search, Differential Evolution (DE), and Bat Algorithm (BA) are used. In this work, improvements have been made to three widely used global optimization algorithms, Divided Rectangles (DIRECT), Differential Evolution (DE), and Bat Algorithm (BA) by integrating appropriate surrogate modeling methods to increase the computation efficiency of these algorithms to support MBD. The superior performance of these new algorithms in comparison with their original counterparts are shown using commonly used optimization algorithm testing benchmark problems. Integration of the surrogate modeling methods have considerably improved the search efficiency of the DIRECT, DE, and BA algorithms with significant reduction on the Number of Function Evaluations (NFEs). The newly introduced algorithms are then applied to a complex engineering design optimization problem, the design optimization of floating wind turbine platform, to test its effectiveness in real-world applications. These newly improved algorithms were able to identify better design solutions using considerably lower NFEs on the computationally expensive performance simulation model of the design. The methods of integrating surrogate modeling to improve DIRECT, DE and BA global optimization searches and the resulting algorithms proved to be effective for solving complex and computationally intensive global optimization problems, and formed a foundation for future research in this area. / Graduate

Transportation is a primary pollution source contributing to 14 percent of global greenhouse gas emissions, and 12 percent of transportation emissions came from maritime activities. Emissions from the ferry industry, which carries roughly 2.1 billion passengers and 250 million vehicles annually, is a major concern for the general public due to their near-shore operations. Compared to the rapidly advancing clean automotive propulsion, fuel efficiency and emissions improvements for marine vessels are more urgent and beneficial due to the significantly higher petroleum fuel consumption and heavy pollutants and the relatively slow adoption of clean propulsion technology by the marine industry. Hybrid electric propulsion, proven to be effective for ground vehicles, presents a promising solution for more efficient clean marine transportation. Due to the diversified hull/propulsor design and operation cycle, the development of a hybrid electric marine propulsion system demands model-based design and control optimization for each unique and small batch production vessel. The integrated design and control optimization further require accurate and computation efficient hull resistance and propulsor thrust calculation methods that can be used to predict needed propulsion power and gauge vessel performance, energy efficiency, and emissions. This research focuses on improving the low-order empirical hull resistance and propulsor thrust models in the longitudinal direction by extracting model parameters from one-pass computational fluid dynamics (CFD) simulation and testing the acquired models in integrated design optimization of the marine propulsion system. The model is implemented in MATLAB/Simulink and ANSYS Aqwa and validated using operation data from BC Ferries’ ship Tachek. The modified low-order model (M-LOM) is then used in the integrated optimizations of propulsion system component sizes and operation control strategies for another BC Ferries’ ship, Skeena Queen. The performance, energy efficiency, and emissions of various propulsion options, including nature gas-mechanical and natural gas-electric benchmarks, and hybrid electric alternatives of series hybrid, parallel hybrid, and battery/pure electric are compared to demonstrate the benefits of the new method in completing these complex tasks and hybrid electric marine propulsion. The research forms the foundation for further studies to achieve more accurate propulsion demand prediction and a more comprehensive lifecycle cost assessment of clean marine propulsion solutions. / Graduate

The automotive industry is experiencing a rapid increase in software complexity due to various functionalities introduced into modern vehicles. Companies use software development standards like AUTOSAR to develop the application layer software independent from the hardware. Development methodologies such as Model-Based Design are used to increase the efficiency of the development process and decrease the time to market. However, to ensure high-quality software standards such as A-SPICE are imposed on the companies. Conforming to A-SPICE requires having certain traceability between work artifacts. Thus, manual and inefficient development, testing, and requirement management processes lead to higher time to market. This thesis will introduce the concept of virtual validation using VEOS virtual platform from dSPACE. The new toolchain will focus on automatizing the testing process, requirement management, and report generation. To highlight the benefits of the virtual validation concept this new approach will be compared to the existing one, which includes a lot of manual development steps. Besides the application of the virtual validation with AUTOSAR and non-AUTOSAR software architectures will be discussed.

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<p>Model based design has had a large impact on the process of software development in many different industries. A lack of formality in these environments can lead to incorrect software and does not facilitate the formal analysis of created models. A formal tool known as tabular expressions have been successfully used in developing safety critical systems, however insufficient tool support has hampered their wider adoption. To address this shortfall we have developed the Tabular Expression Toolbox for Matlab/Simulink.</p> <p>We have developed an intuitive user interface that allows users to easily create, modify and check the completeness and disjointness of tabular expressions using the theorem prover PVS or SMT solver CVC3. The tabular expressions are translated to m-functions allowing their seamless use with Matlab's simulation and code generation. We present a method of generating counter examples for incorrect tables and a means of effectively displaying this information to the user. We provide support for modelling inputs as floating point numbers, through subtyping a user can show the properness of a table using a more concrete representation of data. The developed tools and processes have been used in the modelling of a nuclear shutdown system as a case study of the practicality and usefulness of the tools.</p> / Master of Applied Science (MASc)

Formally-based design and implementation techniques for complex safety-critical embedded systems are required not only to handle the complexity, but also to provide correctness guarantees. Traditional design approaches struggle to cope with complexity, and they generally require extensive testing to guarantee correctness. As the designs get larger and more complex, traditional approaches face many limitations. An alternate design approach is to adopt a "correct-by-construction" paradigm and synthesize the desired hardware and software from the high-level descriptions expressed using one of the many formal modeling languages. Since these languages are equipped with formal semantics, formally-based tools can be employed for various analysis. In this dissertation, we adopt one such formal modeling language - MRICDF (Multi-Rate Instantaneous Channel-connected Data Flow). MRICDF is a graphical, declarative, polychronous modeling language, with a formalism that allows the modeler to easily describe multi-clocked systems without the necessity of global clock. Unnecessary synchronizations among concurrent computation entities can be avoided using a polychronous language such as MRICDF. We have explored a Boolean theory-based techniques for synthesizing multi-threaded/concurrent code and extended the technique to improve the performance of synthesized multi-threaded code. We also explored synthesizing ASIPs (Application Specific Instruction Set Processors) from MRICDF models. Further, we have developed formal techniques to identify constructive causality in polychronous models. We have also developed SMT (Satisfiablity Modulo Theory)-based techniques to identify dimensional inconsistencies and to perform value-range analysis of polychronous models. / Ph. D.

Formula SAE (FSAE) vehicle systems are very complex. Understanding how subsystems effect the overall vehicle is essential for making design trade-offs. FSAE is a competitive environment. Teams need to have reliable and high performing vehicles to do well in competition. The Virginia Tech (VT) FSAE team has produced a prototype electric powertrain (EPT) vehicle, VTM16e, and will take their first EPT vehicle, VTM17e, to competition in 2017. The use of model-based design (MBD) for an EPT FSAE vehicle is investigated through this thesis. The goal of the research is to build the framework of a full vehicle simulation to take knowledge gained from the VTM16e prototype vehicle, and apply it to the VTM17e competition vehicle. A top-down, bottom-up approach is taken to build a full vehicle model of an EPT FSAE vehicle. A full vehicle simulation is built with subsystems to establish an overall structure and subsystem interactions. Individual subsystems are then focused on for testing and validation. Breaking the vehicle down into subsystems allows the overall model to be incrementally improved. The battery subsystem is focused on in this thesis. Extensive testing is performed on the batteries to characterize their performance. Computer models are generated from empirical data through parameter estimation techniques. Validation of the battery models is performed and the resulting model is incorporated into the overall vehicle model. Performance limits of the vehicle are determined through model exploration, and design modifications to increase the reliability and performance for the VTM17e vehicle are proposed. / Master of Science

This thesis explains the model-based design of a fork control system in a turret head operated Very Narrow Aisle forklift in order to evaluate and push the limits of the current hardware architecture. The turret head movement consists of two separate motions, traversing and rotation, which both are hydraulically actuated. The plant is thoroughly modeled in the Mathworks softwares Simulink/Simscape to assist in the design of the control system. The control system is designed in Simulink/Stateflow and code-generated to be evaluated in the actual forklift. Optimal control theory is used to generate a minimum-jerk trajectory for auto-rotation, that is simultaneous traversing and rotation with the load kept in centre. The new control system is able to control the system within the positioning requirements of +/- 10 mm and +/- 9 mrad for traversing and rotation, respectively. It also shows good overall performance in terms of robustness since it has been tested and validated with different loads and on different versions of the forklift. However, the study also shows that the non-linearities of the system, especially in the hydraulic proportional valves, causes problems in a closed-loop control system. The work serves as a proof of concept for model-based development at the company since the development time of the new control system was significantly lower than for the original control system.

Development of embedded systems poses an increasing challenge fordevelopers largely due to increasing complexity. Several factors contribute tothe complexity challenge: • the number of extra-functional properties applying to embedded systems,such as resource usage, timing effects, safety. • the functionality of embedded systems, to a larger extent than for othersoftware, involves engineers from multiple different disciplines, such asmechanical, control, software, safety, systems and electrical engineers.Themulti-disciplinarity causes the development environments to consistof separate data, models and tools. Several engineering paradigms to handle this complexity increase havebeen suggested, including methodologies focused on architecture, models andcomponents. In systems engineering, a long-standing approach has been todescribe the system in several views, each according to a certain viewpoint.By doing so, a divide-and-conquer strategy is applied to system concerns.Unfortunately, it is hard to always find completely independent concerns:there is always some semantic overlap between the different views. Modelbaseddesign (MBD) deals with building sound abstractions that can representa system under design and be used for analysis. Component-based design(CBD) focuses on how to build reusable component models with well-definedcomposition models. In this thesis, a concept of formalized multi-viewed component models (MVCM) is proposed, which integrates the three above mentioned paradigms.Principles and guidelines for MV CMs are developed. One of the main challengesfor the proposition is to provide MV CMs that produce composabilityboth along component boundaries and viewpoint boundaries. To accomplishthis, the relations between viewpoints need to be explicitly taken into account.Further, the semantic relations between these viewpoints need to be explicitlymodeled in order to efficiently ensure that the views are kept consistent. Asa main contribution, this thesis presents the formalization of the conceptsneeded to build such component models. A proper formalization of multiviewedconcerns provides several opportunities. Given suitable tool support, itwill be feasible to automate architecture analysis and architecture exploration. The thesis includes a number of case studies that provide insight andfeedback to the problem formulation and validating the results. The casestudies include a resource-aware reconfigurable middleware, a design of anarchitecture exploration methodology, and a windshield wiper system. / <p>QC 20130527</p>