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A system model for assessing water consumption across transportation modes in urban mobility networksYen, Jeffrey Lee 05 April 2011 (has links)
Energy and environmental impacts are two factors that will influence urban region composition in the near future. One emerging issue is the effect on water usage resulting from changes in regional or urban transportation trends. With many regions experiencing stresses on water availability, transportation planners and users need to combine information on transportation-related water consumption for any region and assess potential impacts on local water resources from the expansion of alternative transportation modes. This thesis will focus on use-phase water consumption factors for multiple vehicle modes, energy and fuel pathways, roads, and vehicle infrastructure for a given transportation network.
While there are studies examining life cycle impacts for energy generation and vehicle usage, few repeatable models exist for assessing overall water consumption across several transportation modes within urban regions. As such, the question is: is it possible to develop a traceable decision support model that combines and assesses water consumption from transportation modes and related mobility infrastructure for a given mobility network? Based on this, an object-oriented system model of transportation elements was developed using the Systems Modeling Language (SysML) and Model-Based Systems Engineering principles to compare water consumption across vehicle modes for assessing the resiliency of existing infrastructure and water resources.
To demonstrate the intent of this model, daily network usage water consumption will be analyzed for current and alternative network scenarios projected by policies regarding the expansion of alternative energy. The model is expected to show variations in water consumption due to fluctuations in energy pathways, market shares, and driving conditions, from which the model should help determine the feasibility of expanding alterative vehicles and fuels in these networks. While spatially explicit data is limited compared to the national averages that are used as model inputs, the analytical framework within this model closely follows that of existing assessments and the reusable nature of SysML model elements allows for the future expansion of additional transportation modes and infrastructure as well as other environmental analyses.
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Model-Based Early Validation and Verification of Design Decisions for Cross-Disciplinary StakeholdersStenlund, Alexander January 2024 (has links)
Systems engineering becomes more challenging as system engineers must tackle increasingly growing and complex systems while balancing stakeholder needs, dependability, costs, and much more. Engineering decisions at early stages become important as their impact can affect the product's entire life cycle. Model-Based System Engineering (MBSE) is a way to capture this system complexity and explore how different engineering decisions affect a system. With this in mind, this thesis will explore how MBSE can capture engineering decisions and their impact at early stages of development and what insight can be gained into a system. This is done by exploratively creating a concept, using it on a toy example to get direct feedback on its performance, and refining the concept before evaluating it in a case study. The case study evaluates the concept in an industrial context through a focus group and receives direct industry feedback. The modelling concept is implemented in Papyrus Eclipse as a Unified Modeling Language (UML) profile to capture concept-specific details and an Eclipse plugin. This implementation is to retrieve and process data from the modelled system. This is used to answer impact questions of choices, such as: "How much does this parameter change if component X is exchanged for another?".The evaluation of the concept was generally positive and gave valuable feedback and possible future directions of the concept. This includes the opinion that a spread sheet gives a better overview of the system and ways to expand the tool though parameterised relations and other suggestions. The thesis in the end presents, one way that MBSE can be used to support the analysis of early cross-disciplinary models, and two major insights which could be gained, namely risk and constraints.
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DIGITAL TWIN: FACTORY DISCRETE EVENT SIMULATIONZachary Brooks Smith (7659032) 04 November 2019 (has links)
Industrial revolutions bring dynamic change to industry through major technological advances (Freeman & Louca, 2002). People and companies must take advantage of industrial revolutions in order to reap its benefits (Bruland & Smith, 2013). Currently, the 4th industrial revolution, industry is transforming advanced manufacturing and engineering capabilities through digital transformation. Company X’s production system was investigated in the research. Detailed evaluation the production process revealed bottlenecks and inefficiency (Melton, 2005). Using the Digital Twin and Discrete Event Factory Simulation, the researcher gathered factory and production input data to simulate the process and provide a system level, holistic view of Company X’s production system to show how factory simulation enables process improvement. The National Academy of Engineering supports Discrete Event Factory Simulation as advancing Personalized Learning through its ability to meet the unique problem solving needs of engineering and manufacturing process through advanced simulation technology (National Academy of Engineering, 2018). The directed project applied two process optimization experiments to the production system through the simulation tool, 3DExperience wiht the DELMIA application from Dassualt Systemes (Dassault, 2018). The experiment resulted in a 10% improvement in production time and a 10% reduction in labor costs due to the optimization
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