| 1. |
- Hosain, Md Lokman, 1984-
(författare)
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Fluid Flow and Heat Transfer Simulations for Complex Industrial Applications : From Reynolds Averaged Navier-Stokes towards Smoothed Particle Hydrodynamics
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 2. |
- Kyprianidis, Konstantinos
(författare)
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On Gas Turbine Conceptual Design
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The thesis begins with a review of the evolution of the industry's vision for the aero-engine design of the future. Appropriate research questions are set that can influence how this vision may further evolve in the years to come. Design constraints, material technology, customer requirements, noise and emissions legislation, technology risk and economic considerations and their effect on optimal concept selection are discussed in detail. Different aspects of the pedagogy of gas turbine conceptual design as well as information on the Swedish and Brazilian educational systems are also presented.A multi-disciplinary aero-engine conceptual design tool is utilised for assessing engine/aircraft environmental performance. The tool considers a variety of disciplines that span conceptual design including: engine performance, engine aerodynamic and mechanical design, aircraft design and performance, emissions prediction and environmental impact, engine and airframe noise, and production, maintenance and direct operating costs.With respect to addressing the research questions set, several novel engine cycles and technologies - currently under research - are identified. It is shown that there is great potential to reduce fuel consumption for the different concepts identified, and consequently decrease the CO2 emissions. Furthermore, this can be achieved with sufficient margin from the NOx certification limits set by International Civil Aviation Organisation, and in line with the medium-term and long-term goals set through it's Committee on Aviation Environmental Protection.The option of an intercooled-core geared-fan aero-engine for long-haul applications is assessed by means of a detailed design space exploration. An attempt is made to identify the fuel burn optimal values for a set of engine design parameters by varying them all simultaneously, as well as in isolation. Different fuel optimal designs are developed based on different sets of assumptions. Evidence is provided that higher overall pressure ratio intercooled engine cycles become more attractive in aircraft applications that require larger engine sizes.The trade-off between the ever-increasing energy efficiency of modern aero-engines and their NOx performance is assessed. Improving engine thermal efficiency has a detrimental effect on NOx emissions for traditional combustors, both at high altitude and particularly at sea-level conditions. Lean-combustion technology does not demonstrate such behaviour and can therefore help decouple NOx emissions performance from engine thermal efficiency. If we are to reduce the contribution of aviation to global warming, however, future certification legislation may need to become more stringent and comprehensive, i.e., cover high altitude conditions. By doing so we can help unlock the competitive advantage of lean burn technology in relation to cruise NOx and mission performance.Finally, some insight is provided on the potential benefits to be tapped from a transition from the traditional deterministic approach for system analysis to a stochastic (robust design) approach for economic decision-making under uncertainty. A basic methodology is outlined and applied on a specific conceptual design case for a conventional turbofan engine. The sensitivity of an optimal engine design obtained deterministically to real-life uncertainties is found to be far from negligible. The considerable impact of production scatter, measurement uncertainties as well as component performance deterioration, on engine performance must be catered for; this includes taking into consideration control system design aspects. A fast analytical approach is shown to be sufficiently accurate for the conceptual design process, particularly for estimating key performance parameters. These relate to type-test certication and performance retention guarantees including preliminary estimates of engine production margins.Lessons learned are presented from: (i) the integration of different elements of conceptual design in a new BSc course and an existing traditional MSc course on gas turbine technology, (ii) the development of an intensive course on gas turbine multi-disciplinary conceptual design. The results from the use of problem-based learning are very encouraging, in terms of enhancing student learning and developing engineering skills.
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| 3. |
- Skvaril, Jan, 1982-
(författare)
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Near-Infrared Spectroscopy and Extractive Probe Sampling for Biomass and Combustion Characterization
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Biomass is characterized by highly variable properties. It can be converted to more valuable energy forms and products through a variety of conversion processes. This thesis focuses on addressing several important issues related to combustion and pulping.Experimental investigations were carried out on a biomass-fired industrial fluidized-bed boiler. The observed combustion asymmetry was explained by an imbalance in the fuel feed. Increased levels of carbon monoxide were detected close to boiler walls which contribute significantly to the risk of wall corrosion.Moreover, extensive literature analysis showed that near-infrared spectroscopy (NIRS) has a great potential to provide property information for heterogeneous feedstocks or products, and to directly monitor processes producing/processing biofuels in real-time. The developed NIRS-based models were able to predict characteristics such as heating value, ash content and glass content. A study focusing on the influence of different spectra acquisition parameters on lignin quantification was carried out. Spectral data acquired on moving woodchips were found to increase the representativeness of the spectral measurements leading to improvements in model performance.The present thesis demonstrates the potential of developing NIRS-based soft-sensors for characterization of biomass properties. The on-line installation of such sensors in an industrial setting can enable feed-forward process control, diagnostics and optimization.
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| 4. |
- Aichmayer, Lukas
(författare)
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Solar receiver development for gas-turbine based solar dish systems
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Small-scale concentrating solar power plants such as micro gas-turbine based solar dish systems have the potential to harness solar energy in an effective way and supply electricity to customers in remote areas. In such systems, the solar receiver transfers the power of concentrated solar radiation to the working fluid of the power conversion cycle. It is one of the key components as it needs to operate at high temperatures to ensure a high power cycle efficiency and under high flux densities to ensure a high receiver efficiency. In order to address these challenges and to ensure efficient and reliable operation innovative designs are needed.This research work focuses on the complete development of a novel solar receiver applying a new systematic design and analysis methodology. Therefore, a comprehensive receiver design and experimental evaluation process were developed and implemented. The design process includes the identification of technical specifications and requirements, the development of receiver design tools of different investigation levels coupled with multi-objective optimization tools, the evaluation of scaling effects between tests in the KTH high-flux solar simulator and the full-scale solar dish system. As a result of the design process a representative final receiver was established with material temperatures and stresses below critical limits while respecting the design specification.The experimental evaluation includes the enhancement of the KTH high-flux solar simulator to provide stable and reliable operating conditions, the precise characterization of the radiative boundary conditions, the design of a receiver test bed recreating the operating behavior of a gas-turbine, and the final receiver testing for multiple operating points. It was shown that the prototype reaches an efficiency of 69.3% for an air outlet temperature of 800°C and a mass flow of 29.5 g/s. For a larger mass flow of 38.4 g/s a receiver efficiency of 84.8% was achieved with an air outlet temperature of 749°C.The measurement results obtained were then used for a multi-point validation of the receiver design tools, resulting in a high level of confidence in the accuracy of the tools. The validated models were then harnessed to calculate the performance of a full-scale solar receiver integrated into the OMSoP solar dish system. It was shown that a solar receiver can be designed, which delivers air at 800°C with a receiver efficiency of 82.2%.Finally, the economic potential of micro gas-turbine based solar systems was investigated and it was shown that they are ideally suited for small-scale stand-alone and off-grid applications.The results of the receiver development highlight the feasibility of using volumetric solar receivers to provide heat input to micro gas-turbine based solar dish systems and no major hurdles were found.
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| 5. |
- Rahman, Moksadur, 1989-
(författare)
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Towards a learning system for process and energy industry : Enabling optimal control, diagnostics and decision support
- 2019
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Driven by intense competition, increasing operational cost and strict environmental regulations, the modern process and energy industry needs to find the best possible way to adapt to maintain profitability. Optimization of control and operation of the industrial systems is essential to satisfy the contradicting objectives of improving product quality and process efficiency while reducing production cost and plant downtime. Use of optimization not only improves the control and monitoring of assets but also offers better coordination among different assets. Thus, it can lead to considerable savings in energy and resource consumption, and consequently offer a reduction in operational costs, by offering better control, diagnostics and decision support. This is one of the main driving forces behind developing new methods, tools and frameworks that can be integrated with the existing industrial automation platforms to benefit from optimal control and operation. The main focus of this dissertation is the use of different process models, soft sensors and optimization techniques to improve the control, diagnostics and decision support for the process and energy industry. A generic architecture for an optimal control, diagnostics and decision support system, referred to here as a learning system, is proposed. The research is centred around an investigation of different components of the proposed learning system. Two very different case studies within the energy-intensive pulp and paper industry and the promising micro-combined heat and power (CHP) industry are selected to demonstrate the learning system. One of the main challenges in this research arises from the marked differences between the case studies in terms of size, functions, quantity and structure of the existing automation systems. Typically, only a few pulp digesters are found in a Kraft pulping mill, but there may be hundreds of units in a micro-CHP fleet. The main argument behind the selection of these two case studies is that if the proposed learning system architecture can be adapted for these significantly different cases, it can be adapted for many other energy and process industrial cases. Within the scope of this thesis, mathematical modelling, model adaptation, model predictive control and diagnostics methods are studied for continuous pulp digesters, whereas mathematical modelling, model adaptation and diagnostics techniques are explored for the micro-CHP fleet.
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