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  • Disputas: 2018-12-14 13:00 Delta, Västerås
    Hosain, Md Lokman
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Fluid Flow and Heat Transfer Simulations for Complex Industrial Applications: From Reynolds Averaged Navier-Stokes towards Smoothed Particle Hydrodynamics2018Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Optimal process control can significantly enhance energy efficiency of heating and cooling processes in many industries. Process control systems typically rely on measurements and so called grey or black box models that are based mainly on empirical correlations, in which the transient characteristics and their influence on the control parameters are often ignored. A robust and reliable numerical technique, to solve fluid flow and heat transfer problems, such as computational fluid dynamics (CFD), which is capable of providing a detailed understanding of the multiple underlying physical phenomena, is a necessity for optimization, decision support and diagnostics of complex industrial systems. The thesis focuses on performing high-fidelity CFD simulations of a wide range of industrial applications to highlight and understand the complex nonlinear coupling between the fluid flow and heat transfer. The industrial applications studied in this thesis include cooling and heating processes in a hot rolling steel plant, electric motors, heat exchangers and sloshing inside a ship carrying liquefied natural gas. The goal is to identify the difficulties and challenges to be met when simulating these applications using different CFD tools and methods and to discuss the strengths and limitations of the different tools.

    The mesh-based finite volume CFD solver ANSYS Fluent is employed to acquire detailed and accurate solutions of each application and to highlight challenges and limitations. The limitations of conventional mesh-based CFD tools are exposed when attempting to resolve the multiple space and time scales involved in large industrial processes. Therefore, a mesh-free particle method, smoothed particle hydrodynamics (SPH) is identified in this thesis as an alternative to overcome some of the observed limitations of the mesh-based solvers. SPH is introduced to simulate some of the selected cases to understand the challenges and highlight the limitations. The thesis also contributes to the development of SPH by implementing the energy equation into an open-source SPH flow solver to solve thermal problems. The thesis highlights the current state of different CFD approaches towards complex industrial applications and discusses the future development possibilities.

    The overall observations, based on the industrial problems addressed in this thesis, can serve as decision tool for industries to select an appropriate numerical method or tool for solving problems within the presented context. The analysis and discussions also serve as a basis for further development and research to shed light on the use of CFD simulations for improved process control, optimization and diagnostics.

  • Disputas: 2018-12-21 13:15 Lambda, Västerås
    Tahvili, Sahar
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. RISE SICS Västerås.
    Multi-Criteria Optimization of System Integration Testing2018Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Optimizing software testing process has received much attention over the last few decades. Test optimization is typically seen as a multi-criteria decision making problem. One aspect of test optimization involves test selection, prioritization and execution scheduling. Having an efficient test process can result in the satisfaction of many objectives such as cost and time minimization. It can also lead to on-time delivery and a better quality of the final software product. To achieve the goal of test efficiency, a set of criteria, having an impact on the test cases, need to be identified. The analysis of several industrial case studies and also state of the art in this thesis, indicate that the dependency between integration test cases is one such criterion, with a direct impact on the test execution results. Other criteria of interest include requirement coverage and test execution time. In this doctoral thesis, we introduce, apply and evaluate a set of approaches and tools for test execution optimization at industrial integration testing level in embedded software development. Furthermore, ESPRET (Estimation and Prediction of Execution Time) and sOrTES (Stochastic Optimizing of Test Case Scheduling) are our proposed supportive tools for predicting the execution time and the scheduling of manual integration test cases, respectively. All proposed methods and tools in this thesis, have been evaluated at industrial testing projects at Bombardier Transportation (BT) in Sweden. As a result of the scientific contributions made in this doctoral thesis, employing the proposed approaches has led to an improvement in terms of reducing redundant test execution failures of up to 40% with respect to the current test execution approach at BT. Moreover, an increase in the requirements coverage of up to 9.6% is observed at BT. In summary, the application of the proposed approaches in this doctoral thesis has shown to give considerable gains by optimizing test schedules in system integration testing of embedded software development.