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

<p>Developments in the technology are followed by the methods and frameworks in industry to intensify the production of information, tools, goods, and services. This trend has been followed by the pharmaceutical industry which is highly regulated by administrations to meet the quality requirements of the drugs and produce more for cheaper in a shorter time. As the knowledge and understanding of crystallization systems have been increasing with the development of process analytical technology (PAT) tools, it is inevitable to use the experience and data coming with it to develop data-driven, better processes. In the light of these developments, Industry 4.0 has started becoming the new paradigm in pharmaceutical industry pushing the data-driven design of pharmaceutical processes. This thesis demonstrates the development and usage of a framework for data-driven, model-based design of pharmaceutical processes that fall in line with this latest paradigm shift. The proposed framework can be summarized in four levels showing the benefits of the collected data and model development. These levels are data collection from specially designed experiments, model writing, using the data collected from the first step to train the model, validation of the model to call it ‘Digital Twin’ of the process, using the digital twin for process design via in-silico design of experiments (DoE) or process optimization. The chapters in this thesis are different case studies that follow these steps for model-based process design. The systems studied are batch cooling crystallization with temperature cycling to produce a drug compound, batch cooling crystallization with integrated milling and temperature cycling for the shape optimization of the same drug compound from previous step, and hot melt extrusion for amorphization of another drug compound. In addition to demonstrating the development of the whole framework and its possible benefits in each chapter, Chapter 4 is the solely experimental proof of concept of a previous, more general model-based design of a mill integrated crystallization work.</p>

Reliable access to power is essential for modern society’s fundamental functions. It is necessary that faults and abnormalities in low-voltage grids can easily be detected and diagnosed. A fault in a grid can be a consequence of several causes, including internal damage, technical errors, malfunctioning electricity meters and electricity theft. This thesis investigates the possibilities with model-based approaches for fault diagnosis and monitoring of low-voltage grids. Data and properties from a real low-voltage grid is utilised in this thesis. Furthermore, hypothetical sensors are introduced in the model equations and simulations. To delimit and make the results easier to understand, three different clusters, made up from a few households and intermediate cables, from the grid are analysed. The methods used includes modelling of the real low-voltage grid, structural analysis of the isolability performance of faults, and simulation of faulty scenarios in MATLAB. The investigation of the isolability performance uses isolability matrices and Dulmage Mendelsohn decomposition. The results from the structural analysis show that it is hard to design residuals that are only sensible to certain faults and draw conclusions on where a particular fault takes place. Many times, it shows that several faults cannot be isolable from each other. The redundancy has to be increased in the equations with even more sensors. By using the simulated model directly for residual generation, clearer and more determined results can be seen. Because it does take quantities into account, it is easier to analyse and look after changes in the grid. A few introduced sensors can often tell where a current through a cable must have been increased. An injected fault will more or less always affect residuals indirect proximity. However, because faults can occur in both sensors and cables, itis often hard to specify exactly why and where the fault takes place.

Graphical user interfaces represent significant part of computer systems. This causes an increase of demands for their proper behavior, which can be achieved by a proper testing during development. This thesis describes the principles of model based testing for automated generation of test cases. In this way, the productivity of test teams can increase. The thesis defines model for modeling the most common GUI elements, algorithm for obtaining such a model from the GUI, and a tool for definition of coverage criteria.

Traceability in the software industry is a topic which has been studied for a long time, but there still remain questions to be answered. This thesis looks into the state of software traceability in the software industry is today. It is also a case study in implementing traceability in a model-based testing process at a large automotive company. The thesis finds that while progress has been made in identifying the important aspects of traceability, there does not yet exist a clear consensus on general traceability models which can be used to implement traceability in an arbitrary company or project. Through a case study in implementing traceability in a model-based testing process, the thesis gives one example of how this could potentially be done.

Background &amp; Purpose: The current standard dosimetry in brachytherapy treatment planning, the TG-43 formalism, ignore the presence of non-water media and finite patient dimensions. This can cause clinically relevant errors in dose estimates. To over- come the limitations of the TG-43 formalism, Model-Based Dose Calculation Algorithms (MBDCAs) have evolved. One of the commercial available MBDCAs is the Advanced Collapsed cone Engine (ACE) by Elekta. In ACE, the total dose is divided into three components, the primary, the first-scattered and the multiple-scattered dose, where the two last mentioned are calculated by the means of the Collapsed Cone Algorithm. In this study the performance of ACE has been investigated. The study has been di- vided into 2 parts, where the aim of part 1 was to analyze the relationship between the so called discretization artifacts, caused by the collapsed cone approximation, and the number of dwell positions. The severeness of the artifact is thought to decrease as the number of dwell positions are increased. The second part focus on ACE’s behavior in cortical bone, with the aim to form a hypothesis (explanation and solution) to the previously observed dose underestimation of the dose to bone made by ACE. Materials and Methods: The generic 192Ir source, the Oncentra Brachy (OcB) treatment planning system (TPS) and the Monte Carlo (MC) platform ALGEBRA have been utilized. In the first part of the study, six source configurations, all with a different number of dwell positions, were created and placed in the center of large water phantoms, i.e. under TG-43 conditions in which the TG-43 formalism can be assumed to yield a high accuracy of the estimated dose. The accuracy of ACE has been judged by its’ deviation from TG-43. In the second part of the study, a cubic source configuration, of 27 dwell positions, was positioned at the center of a cubic water phantom. Three cases where constructed, with a small cortical bone heterogeneity positioned at different distances from the source configu- ration. The ACE calculated dose distribution has been divided into its’ three constituents. The accuracy of ACE and TG-43 has been judged by its’ deviation from MC. Results: Part 1 showed that increasing the number of dwell positions does not guar- antee an improved accuracy of ACE. Local dose difference ratios of &gt; 2%, caused by the artifacts, were mainly located outside the 5% isodose line. A general dose underestima- tion was observed in ACE, with an increased magnitude as the dose level decreased. The majority of local dose difference ratios below -4% were found where the multi-resolution voxelization grid of ACE has a voxel size of ≥23 mm3, that is at a distance of ≥8 cm from the closest dwell position when using the ACE standard accuracy level. In part 2, ACE underestimated the dose to cortical bone, with an increased magnitude as the bone was positioned farther away from the source configuration. The TG-43 formalism gave slightly better estimates of the mean dose to bone than ACE, especially at higher dose levels. For a mean dose to the cortical bone heterogeneity equal to 45% of the prescribed dose, TG-43 and ACE underestimated the mean dose with 1% and 4%, respectively. The estimated mean dose to a volume located directly behind the heterogeneity agreed within 1% between ACE and MC. However, an increased amount of positive local dose difference ratios were observed in this volume. Conclusions: Increasing the number of dwell positions cause a ”blurring” effect of the artifact, but may also increase the fluence gradient. In such situations the severeness of the artifact may not be improved. In patient cases the dwell positions are usually added in a more random manner which may favor the ”blurring effect”. The underestimations observed in ACE are thought to be caused by both the multiple- resolution voxelization grid of ACE and the relationship between the dimensions of the phantom in which the multiple-scattered kernel has been generated and the current calcu- lation volume. ACE was unsuccessful to predict the dose to cortical bone, and should hence be used with caution when cortical bone is an organ at risk, as long as the problem remains. The results indicates that the error in ACE is located in the scatter dose calculations and that the heterogeneity cause ACE to displace the dose. The error is thought to be located in the multiple-scattered dose component, which was also shown by Terribilni et al.. A hypothesis is that the problem is caused by the neglected effect of media dependent absorption coefficients in the multiple-scattered dose calculation. A suggested solution, left to be proven, is to use effective attenuation scaling factors.

Model-based testing (MBT) is using a model of expected behavior of the system to automatically generate a set of tests. It aims at reducing the testing cost when compared to the traditional testing techniques. This work focuses on testing a real-world software system using the selected MBT tool OSMO. The tested system is responsible for compiling business rules and it is one of the main components of the Drools platform, developed by Red Hat. The work describes the introduction of MBT considering the good reception from the community of developers, then the creation of compiler input models and evaluation of the newly created test suite. The usage of the MBT resulted in detection of five reported and three potential issues in the tested code. Using the Drools compiler example, the work summarizes the main strengths and also weaknesses of practical use of MBT techniques.

Retrofits of hydraulic and mechanical deep drawing presses often stop with the exchange of the electrical and the hydraulic parts. But that is only half the job. The use of high definition control electronics, faster CPUs and more dynamic hydraulic actuators, offers the opportunity of redesigning the already existing control concepts of the press. In this paper we present how the performance of the press, i.e. the control quality, can be increased for hydraulic ram and cushion axes. The improvement in control quality is achieved through the use of intelligent closed-loop and open-loopcontrol algorithms. Therefore, creasing and crack formation can be reduced, since enhancements in control quality have direct influence on the quality of the forming process. Results will be shown for hydraulic drawing cushion control, i.e. pressure control, as well as for hydraulic ram control, i.e. position, velocity and parallelism control. We present findings for hydraulic cushion control of a mechanical press type Arisa S-4-1600-470-230-LDE (link-drive press with 10 hydraulic cushions) and for ram- / cushion-control of hydraulic press type Müller-Weingarten ZE2100 (multi-curve press with 8-point cushion).

An efficient system development needs reuse, traceability and understanding. Today, specifications are usually written in text documents. Reuse means a copy and paste of suitable specifications. Traceability is the textual note that references to affected requirements. Achieving a full context understanding requires reading hundreds of pages in a variety of documents. Changing one textual requirement in complex systems can be very time-consuming. Model-based systems engineering (MBSE) addresses these issues. There, an integrated system model is used for the design, analysis, communication and system specification and shall contribute to handling the system complexity. This paper shows aspects of this approach in the development of a wheel loader\'s attachment system. Customer requirements will be used to derive a specification model. Based on this, the author introduces the system and software architecture. The connection between requirement and architecture leads to a traceable system design and produces the huge advantage of MBSE.

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.