5,306 research outputs found

    CFD Modelling of the Mixture Preparation in a Modern Gasoline Direct Injection Engine and Correlations with Experimental PN Emissions

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    A detailed 3D CFD analysis of a modern gasoline direct injection (GDI) engine is carried out to reveal the connections between pre-combustion mixture indicators and PN emissions. Firstly, a novel calibration methodology is introduced to accurately predict the widely used characteristics of the high-pressure fuel spray. The methodology utilised the Siemens STAR-CD 3D CFD software environment and employed a combination of statistical and optimization methods supported by experimental data. The calibration process identified dominant factors influencing spray properties and established their optimal levels. The two most used models for fuel atomisation were investigated. The Kelvin–Helmholtz/Rayleigh–Taylor (KH–RT) and Reitz–Diwakar (RD) break-up models were calibrated in conjunction with the Rosin–Rammler (RR) mono-modal droplet size distribution. RD outperformed KH–RT in terms of prediction when comparing numerical spray tip penetration and droplet size characteristics to the experimental counterparts. Then, the modelling protocol incorporated droplet-wall interaction models and a multi-component surrogate fuel blend model. The comprehensive digital model was validated using published data and applied to a modern small-capacity GDI engine. The study explored various engine operating conditions and highlights the contribution of fuel mal-distribution and liquid film retention at spark timing to Particle Number (PN) emissions. Finally, a novel surrogate model was developed to predict the engine-out PN. An extensive CFD analysis was conducted considering part-load operating conditions and variations of engine control variables. The PN surrogate model was developed using an Elastic Net (EN) regression technique, establishing relationships between experimental PN emission levels and modelled, pre-combustion, air-fuel mixture quality indicators. The approach enabled the reliable prediction of engine sooting tendencies without relying on complex measurements of combustion characteristics. These research efforts aim to enhance engine efficiency, reduce emissions, and contribute to the development of a reliable and cost-effective digital toolset for engine development and diagnostics

    Reacting Flow Prediction of the Low-Swirl Lifted Flame in an Aeronautical Combustor With Angular Air Supply

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    The development of lean-burn combustion systems is of paramount importance for reducing the pollutant emissions of future aero engine generations. By tilting the burners of an annular combustor in circumferential direction relative to the rotational axis of the engine, the potential of increased combustion stability is opened up due to an enhanced exhaust gas recirculation between adjacent flames. The innovative gas turbine combustor concept, called the short helical combustor (SHC), allows the main reaction zone to be operated at low equivalence ratios. To exploit the higher stability of the fuel-lean combustion, a low-swirl lifted flame is implemented in the staggered SHC burner arrangement. The objective is to reach ultralow NOx emissions by complete evaporation and extensive premixing of fuel and air upstream of the lean reaction zone. In this work, a modeling approach is developed to investigate the characteristics of the lifted flame in an enclosed single-burner configuration, using the gaseous fuel methane. It is demonstrated that by using the large eddy simulation method, the shape and liftoff height of the flame are adequately reproduced by means of the finite-rate chemistry approach. For the numerical prediction of the lean lifted flame in the SHC arrangement, the focus is on the interaction of adjacent burners. It is shown that the swirling jet flow is deflected toward the sidewall of the staggered combustor dome, which is attributed to the asymmetrical confinement. Since the stabilization mechanism of the low-swirl flame relies on outer recirculation zones, the upstream transport of hot combustion products back to the flame base is studied by the variation of the combustor confinement ratio. It turns out that increasing the combustor size amplifies the exhaust gas recirculation along the sidewall, and increases the temperature of recirculating burned gases. This study emphasizes the capability of the proposed lean-burn combustor concept for future aero engine applications

    Dynamic analysis and energy management strategies of micro gas turbine systems integrated with mechanical, electrochemical and thermal energy storage devices

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    The growing concern related to the rise of greenhouse gases in the atmosphere has led to an increase of share of renewable energy sources. Due to their unpredictability and intermittency, new flexible and efficient power systems need to be developed to compensate for this fluctuating power production. In this context, micro gas turbines have high potential for small-scale combined heat and power (CHP) applications considering their fuel flexibility, quick load changes, low maintenance, low vibrations, and high overall efficiency. Furthermore, the combination of micro gas turbines with energy storage systems can further increase the overall system flexibility and the response to rapid load changes. This thesis aims to analyse the integration of micro gas turbines with the following energy storage systems: compressed air energy storage (CAES), chemical energy storage (using hydrogen and ammonia), battery storage, and thermal energy storage. In particular, micro gas turbines integrated with CAES systems and alternative fuels operate in different working conditions compared to their standard conditions. Applications requiring increased mass flow rate at the expander, such as CAES and the use of fuels with low LHV, such as ammonia, can potentially reduce the compressor surge margin. Conversely, sudden composition changes of high LHV fuels, such as hydrogen, can cause temperature peaks, detrimental for the turbine and recuperator life. A validated model of a T100 micro gas turbine is used to analyse transitions between different conditions, identify operational limits and test the control system. Starting from the dynamic constraints defined in the related chapters, in the final part, an optimisation tool for energy management is developed to couple the micro gas turbine with energy storage systems, maximizing the plant profitability and satisfying the local electrical and thermal demands. For the modelling of the CAES system and alternative fuels, the operating constraints obtained from the initial analyses are implemented in the optimisation tool. In addition, a battery and thermal energy storage system are also considered. In the first part, a comprehensive analysis of the T100 combined with a second-generation CAES system showed enhanced efficiency, reduced fuel consumption, reduced thermal power output and increased maximum electrical power output due to the reduction of the rotational speed. The study identified optimal air injection constraints, demonstrating a +3.23% efficiency increase at 80 kW net power with a maximum mass flow rate of 50 g/s. The dynamic analysis exposed potential instabilities issues during air step injections, mitigated by using ramps at a rate of +0.5 (g/s)/s for safe and rapid dynamic mode operation. The second part explored the effects of varying H2-NG and NH3-NG blends on the T100 mGT. Steady-state results showed increased power output with hydrogen or ammonia, notably +6.1 kW for 100% H2 and up to +11.3 kW for 100% NH3. Transient power steps simulations showed surge margin reductions, especially at lower power levels with high concentrations of ammonia, highlighting the need for controlled transitions. Controlled ramps were effective in preventing extreme temperature peaks during fuel composition changes. The final chapter focused on developing an energy scheduler for different plant setups, evaluating four configurations. For a typical day of the month of April of the Savona Campus, the integration of the CAES lead to relative savings of +8.1% and power-to-H2 of +5.3% when surplus electricity was not sold to the grid. Conversely, with the ability to sell excess electricity, CAES and battery energy storage (BES) systems exhibit modest savings of +1.2% and +2.4%, respectively, while the power-to-H2 system failed to provide economic advantages

    Metal foam recuperators on micro gas turbines: Multi-objective optimisation of efficiency, power and weight

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    Small size and high efficiency of micro gas turbines require a higher surface-to-volume ratio of recuperators. Conventional recuperators can achieve a range of 250–3600 m2/m3. Advances in materials and manufacturing, such as metal foams, can increase significantly the exchange surface and improve compactness ranging approximately from 500 to over 10,000 m2/m3, due to their exceptional micro geometry. The main advantage is that the increase of surface area does not impact the cost of the heat exchanger as much as conventional recuperators due to their easy manufacturing. This work addresses the optimisation of the recuperator using multiple objectives satisfying efficiency, power output and weight criteria, offering a holistic approach that takes into account the entire system rather than individual components or channels. A model is developed to represent the performance of a compact heat exchanger in micro gas turbines. The recuperator is an annular heat exchanger with involute profile filled with porous media in a counterflow arrangement on the hot and cold sides. The model allows the evaluation of the effect of the recuperator geometry features on the electrical efficiency, power output and weight savings in a micro gas turbine. Existing models for the global heat transfer coefficient, effective thermal conductivity, surface area and pressure drop of porous media are selected and implemented. The design variables of multi-objective are the pore density, porosity and number of channels, whilst the objectives are the overall electrical efficiency, power output and recuperator weight. The problem is solved using the Non-Dominated Sorting Genetic Algorithm (NSGA-II) to determine an approximation of the Pareto front, whilst the accuracy of the approximation is assessed against the solution obtained by an exhaustive search. The comparison shows that NSGA-II outperforms an exhaustive search by at least 90 % in terms of computational efficiency. These results allow the quantification of the impact of metal foam technology on performance metrics of the recuperator as well as the entire system. This quantitative analysis provides valuable insights into the behaviour of metal foam recuperators in micro gas turbines. An optimal design with 30 % efficiency and 28 kW power output appears in pore densities of approximately 10 and 20 pores per inch (PPI) for the air and gas side respectively, and a porosity of 85 %, which leads to a state-of-the-art recuperator weight of 48 kg. The efficiency improvement over the industry standard is 15 %, with only a 2.5 % reduction in power output

    Exploiting the potential of chemical looping processes for industrial decarbonization and waste to energy conversion. Process design and experimental evaluations

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    The impact of anthropogenic activities on the environment is leading to climate changes and exceptional meteorological phenomena all over the world. To address this negative trend, the scientific community agrees that the environmental impact from fossil fuels-based power production must be mitigated by the integration with alternative and sustainable technologies, such as renewable energy. However, the time required for the complete development and diffusion of such technology poses the urgency of finding a midterm solution to significantly reduce CO2 emissions. Carbon capture, utilization, and storage (CCUS) technologies represent an interesting option to mitigate CO2 emissions. CCUS involves (among other possible applications) the separation of the CO2 content from industrial off-gases, its transport and storage or its reconversion to a chemical/fuel. Chemical looping can be considered as an oxyfuel combustion where the oxygen supply comes from the lattice oxygen atoms of a solid. It is based on gas-solid reactions where a solid also known as oxygen carrier, generally a metal oxide, undergoes successive reduction and oxidation steps. In the reduction step, normally occurring at high temperatures (700-1000 °C), the oxygen carrier interacts with a reducing agent, such as coal, natural gas, syngas etc. and loses part of its oxygen atoms. By controlling the degree of reduction of the oxygen carrier is thus possible to achieve a complete oxidation of the reducing agent (the fuel) to CO2 and H2O (chemical looping combustion) or a partial oxidation to a syngas (chemical looping reforming and gasification). In these latter case, the introduction of external CO2 and H2O can be of help to support the reforming or gasification processes. The oxygen carrier in the reduced phase is then sent to an air reactor, where it reacquires the oxygen atoms by an exothermic reaction with air. This process presents several advantages according to the specific application. In chemical looping combustion, intrinsic separation of N2 and CO2 is achieved, because the two streams are involved in two different reaction steps. This largely simplifies the CO2 separation effort for storage or utilization purposes. On the other hand, in chemical looping reforming it is possible to achieve autothermal operation thanks to the exothermicity of the oxidation step in the air reactor, as well as high reforming efficiencies. Similarly, in chemical looping gasification the resulting syngas is characterized by no N2 dilution, lower tar release and possibility of autothermal operation. These benefits enhance the energy efficiency of the process, leading to a better energy utilisation. In this work, strategies for the decarbonisation and circularity of the industrial and power sector are proposed based on the synthesis of hydrogen and hydrogen-derived fuels. In particular, the potential of chemical looping technology is deeply studied aiming at exploiting its ability to reconvert or valorise CO2 or waste streams to a syngas and then to a liquid fuel/chemical, such as methanol or ammonia. This task is carried out through modelling and experimental evaluations. The modelling activities mainly concern design of process schemes involving the chemical looping section for waste or CO2 reconversion and the liquid fuel synthesis section. The experimental evaluations are focused on two crucial that have been limitedly discussed in the literature: the thermochemical syngas production step by oxidation with CO2 and H2O streams, the effect of high-pressure operation on the redox abilities of a typical iron and nickel-based oxygen carrier. In Chapter 1, a general overview on the main research developments on chemical looping technology is provided. A section is reserved for each chemical looping variant, i.e. combustion, reforming and gasification, and a general description of each process is provided along with the summary of the main research achievements. Subsequently, the technology is divided by application in power production and chemicals production. Main findings from techno-economic assessment and process designs are discussed in comparison with benchmark technologies and other clean pathways. In Chapter 2 steel mills are taken as an example of the hard-to-abate industry. A H2-based decarbonization strategy is proposed and assessed by Aspen Plus simulation. The strategy starts from an initial configuration that is characterized by a typical blast furnace-basic oxygen furnace steel mill and consider the introduction of direct reduction – electric arc furnace lines, that are more efficient and involve natural gas as reducing agent rather than coke. Sensitivity analyses are carried out to assess the effect of the introduction of H2/CH4 blendings in the direct reduction plant and of the utilization of scrap material in the electric arc furnace. The impact of each configuration on the CO2 emissions and the energy flows of the plant is assessed by mass and energy balances. The results indicate a promising decarbonization potential of the introduced technologies but require large investments to increase the renewable sources penetration in the energy mix and large availability of H2. Therefore, alternative pathways for an earlier decarbonization of hard-to-abate industries and for large scale syngas/H2 production need to be considered. In Chapter 3, a novel process scheme is proposed involving chemical looping for syngas production. The CO2 content in blast furnace gases is separated with a calcium looping cycle and subsequently injected with H2O into the oxidation reactor of a chemical looping cycle. Assuming an inlet stream of pure CO2, mass balances on the chemical looping plant are carried out to compare the performance of nickel ferrites and iron oxides in terms of required oxygen carrier flow rate to process 1 t/h of CO2. Computational fluid dynamics simulations with integrated reaction kinetics are then carried out to validate the assumptions on the oxygen carrier conversion and syngas compositions. In Chapter 4 and 5, experimental evaluations are carried out on two crucial aspects for the successful operation of a chemical looping plant aiming at syngas production. In Chapter 4, the syngas productivity by CO2 and H2O splitting over a Fe bed is investigated. This is a very important step, and the effect of various parameters was considered. Firstly, the CO2 splitting is analysed for different temperatures with an inlet flow rate of 1 NL/min to ensure a substantial dissociation of the CO2. Subsequently, combined streams of CO2 and H2O are evolved in the reactor. The effect of the total flow rate, reactants molar ratio and bed height is investigated and from the results, the optimal syngas composition is identified. SEM and XRD are used to assess the morphological evolution and the phase changes of the material during the test. On the contrary, in Chapter 5 the effect of high-pressure operation on the redox abilities of two NiFe aluminates is assessed. The aluminates present similar Fe loadings, but different Ni loadings. High pressure operation is crucial for the development of this technology because it facilitates downstream processing of the syngas to liquid fuels. For a comparative analysis, preliminary tests at low pressure are carried out at three temperatures. Subsequently, the effect of reactants flow rate, temperature, total pressure, gas composition is analysed at high pressure conditions. Finally, long term tests are performed both at ambient and high-pressure conditions. Material characterization by SEM, XRD and H2-TPR is used to support the comparative analysis. In Chapter 6, a techno-economic analysis on a process scheme encompassing methanol and ammonia production from chemical looping gases is carried out. Chemical looping hydrogen production is a very versatile technology and allows for the combined production of power and H2 or syngas. With proper calibration of the flow rates, a stream of high purity N2 can also be obtained at the air reactor outlet and used for ammonia synthesis. Back up with an alkaline electrolyser is considered for the supply of the required amount of hydrogen. Sensitivity analyses are carried out on the chemical looping plant to evaluate the effect of fuel flow rate, steam flow rate, and oxygen carrier inlet temperature to the fuel reactor. Subsequently, a techno-economic analysis is carried out evaluating several parameters among which: the specific CO2 emissions, the energy intensity, and the levelized cost of methanol and ammonia. Finally, a comparison with benchmark technologies and other clean alternatives is presented. In this way, the benefits as well as the drawbacks of chemical looping in terms of environmental and economic parameters are assessed and the missing elements to reach industrial competitivity are clarified

    A decision-making approach for the health-aware energy management of ship hybrid power plants

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    Although autonomous shipping has attracted increasing interest, its further develop-ment requires innovative solutions to operate autonomous ships without the direct in-tervention of human operators. This study aims to develop a health-aware energy management (HAEM) approach for ship hybrid power plants, integrating the health monitoring information from reliability tools with the energy management tools. This approach employs the equivalent consumption minimisation strategy (ECMS) along with a Dynamic Bayesian network (DBN), as well as the utopia decision-making meth-od and a model for the ship hybrid power plant. The HAEM approach is demonstrated for a parallel hybrid power plant of a pilot boat considering realistic operating profiles. The results demonstrate that by employing HAEM approach for the investigated ship power plant operating for 300 hours reduces its failure rate almost fourfold at the cost of fuel consumption increase of around 1.5 %, compared to the respective operation with the ECMS. This study is expected to contribute towards the development of su-pervisory control of autonomous power plants

    Contactless excitation for electric machines: high temperature superconducting flux pumps

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    With the intensification of global warming and climate change, the pace of transformation to a neutral-emission society is accelerating. In various sectors, electrification has become the absolute tendency to promote such a movement, where electric machines play an important role in the current power generation system. It is widely convinced that electric machines with very high power density are essential for future applications, which, however, can be hardly achieved by conventional technologies. Owing to the maturation of the second generation (2G) high temperature superconducting (HTS) technologies, it has been recognized that superconducting machine could be a competitive candidate to realize the vision. One significant obstacle that hinders the implementation of superconducting machines is how to provide the required magnetic fields, or in other words, how to energise them appropriately. Conventional direct injection is not suitable for HTS machines, because the current leads would bridge ambident temperature to the cryogenic environment, which can impose considerable heat load on the system and increase the operational cost. Thus, an efficient energisation method is demanded by HTS machines. As an emerging technology that can accumulate substantial flux in a closed loop without any physical contact, HTS flux pumps have been proposed as a promising solution. Among the existing developed HTS flux pumps, rotary HTS flux pumps, or so-called HTS dynamo, can output non-zero time-averaged DC voltage and charge the rest of the circuit if a closed loop has been formed. This type of flux pump is often employed together with HTS coils, where the HTS coils can potentially work in the persistent current mode, and act like electromagnets with a considerable magnetic field, having a wide range of applications in industry. The output characteristics of rotary HTS flux pumps have been extensively explored through experiments and finite element method (FEM) simulations, yet the work on constructing statistical models as an alternative approach to capture key characteristics has not been studied. In this thesis, a 2D FEM program has been developed to model the operation of rotary HTS flux pumps and evaluate the effects of different factors on the output voltage through parameter sweeping and analysis of variance. Typical design considerations, including the operating frequency, air gap, HTS tape width, and remanent flux density have been investigated, in particular, the bilateral effect of HTS tape width has been discovered and explained by looking at the averaged integration of the electric field over the HTS tape. Based on the data obtained from various simulations, regression analysis has been conducted through a collection of machine learning methods. It has been demonstrated that the output voltage of a rotary HTS flux pump can be obtained promptly with satisfactory accuracy via Gaussian process regression, aiming to provide a novel approach for future research and a powerful design tool for industrial applications using rotary HTS flux pumps. To enhance the applicability of the proposed statistical models, an updated FEM program has been built to take more parameters into account. The newly added parameters, namely the rotor radius and the width of permanent magnet, together with formerly included ones, should have covered all the key design parameters for a rotary HTS flux pump. Based on data collected from the FEM model, a well-trained semi-deep neural network (DNN) model with a back-propagation algorithm has been put forward and validated. The proposed DNN model is capable of quantifying the output voltage of a rotary HTS flux pump instantly with an overall accuracy of 98% with respect to the simulated values with all design parameters explicitly specified. The model possesses a powerful ability to characterize the output behaviour of rotary HTS flux pumps by integrating all design parameters, and the output characteristics of rotary HTS flux pumps have been successfully demonstrated and visualized using this model. Compared to conventional time-consuming FEM-based numerical models, the proposed DNN model has the advantages of fast learning, accurate computation, as well as strong programmability. Therefore, the DNN model can greatly facilitate the design and optimization process for rotary HTS flux pumps. An executable application has been developed accordingly based on the DNN model, which is believed to provide a useful tool for learners and designers of rotary HTS flux pumps. A new variant inspired by the working principles of rotary HTS flux pumps has been proposed and termed as stationary wave HTS flux pumps. The superiority of this type is that it has a simple structure without any moving components, and it utilises a controllable current-driven electromagnet to provide the required magnetic field. It has been demonstrated that the origin of the output voltage is determined by the asymmetric distribution of the dynamic resistance in the HTS tape, for which the electromagnet must be placed at such a position that its central line is not aligned with that of the HTS tape. A numerical model has been built to simulate the operation of a stationary wave HTS flux pump, based on which the output characteristics and dynamic resistance against various parameters have been investigated. Besides, accurate and reliable statistical models have been proposed to predict the open circuit voltage and effective dynamic resistance by adapting the previously developed machine learning techniques. The work presented in this PhD thesis can bring more insight into HTS flux pumps as an emerging promising contactless energisation technology, and the proposed statistical models can be particularly useful for the design and optimization of such devices

    Evaluating the sustainability and resiliency of local food systems

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    With an ever-rising global population and looming environmental challenges such as climate change and soil degradation, it is imperative to increase the sustainability of food production. The drastic rise in food insecurity during the COVID-19 pandemic has further shown a pressing need to increase the resiliency of food systems. One strategy to reduce the dependence on complex, vulnerable global supply chains is to strengthen local food systems, such as by producing more food in cities. This thesis uses an interdisciplinary, food systems approach to explore aspects of sustainability and resiliency within local food systems. Lifecycle assessment (LCA) was used to evaluate how farm scale, distance to consumer, and management practices influence environmental impacts for different local agriculture models in two case study locations: Georgia, USA and England, UK. Farms were grouped based on urbanisation level and management practices, including: urban organic, peri-urban organic, rural organic, and rural conventional. A total of 25 farms and 40 crop lifecycles were evaluated, focusing on two crops (kale and tomatoes) and including impacts from seedling production through final distribution to the point of sale. Results were extremely sensitive to the allocation of composting burdens (decomposition emissions), with impact variation between organic farms driven mainly by levels of compost use. When composting burdens were attributed to compost inputs, the rural conventional category in the U.S. and the rural organic category in the UK had the lowest average impacts per kg sellable crop produced, including the lowest global warming potential (GWP). However, when subtracting avoided burdens from the municipal waste stream from compost inputs, trends reversed entirely, with urban or peri-urban farm categories having the lowest impacts (often negative) for GWP and marine eutrophication. Overall, farm management practices were the most important factor driving environmental impacts from local food supply chains. A soil health assessment was then performed on a subset of the UK farms to provide insight to ecosystem services that are not captured within LCA frameworks. Better soil health was observed in organically-farmed and uncultivated soils compared to conventionally farmed soils, suggesting higher ecosystem service provisioning as related to improved soil structure, flood mitigation, erosion control, and carbon storage. However, relatively high heavy metal concentrations were seen on urban and peri-urban farms, as well as those located in areas with previous mining activity. This implies that there are important services and disservices on farms that are not captured by LCAs. Zooming out from a focus on food production, a qualitative methodology was used to explore experiences of food insecurity and related health and social challenges during the COVID-19 pandemic. Fourteen individuals receiving emergency food parcels from a community food project in Sheffield, UK were interviewed. Results showed that maintaining food security in times of crisis requires a diverse set of individual, household, social, and place-based resources, which were largely diminished or strained during the pandemic. Drawing upon social capital and community support was essential to cope with a multiplicity of hardship, highlighting a need to develop community food infrastructure that supports ideals of mutual aid and builds connections throughout the food supply chain. Overall, this thesis shows that a range of context-specific solutions are required to build sustainable and resilient food systems. This can be supported by increasing local control of food systems and designing strategies to meet specific community needs, whilst still acknowledging a shared global responsibility to protect ecosystem, human, and planetary health
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