Investigation of a Novel Thermoelectric Cooler for Building/Infrastructure Application

With the enormous building/infrastructure construction in advanced and emerging economies, the energy demand and carbon emissions from building/infrasturcture continues to rise. Buildings/infrastructure construction sectors contributed to 30% of global energy consumption and 27% of total energy emissions. To align with the carbon net zero scenario, carbon footprint from building need to more than halve by 2030, which requiring significant efforts on adopting clean and efficient technologies applicable to all end-uses. For energy consumption of modern building, heating, ventilation, and air-conditioning (HVAC) system play a critical role, which accounts for 40% of total building consumption and 70% of landlord consumption.Thermoelectric coolers (TECs) are highly dependable, scalable, and noiseless devices. Beyond their conventional use, TECs have been investigated for a wide range of applications, including waste heat energy harvesting, electronics cooling, wearable device technology, power generation, and more. Numerous researches have unveiled their substantial potential in both domestic and industrial sectors, particularly in distributed building air conditioning. However, the cooling/energy performance of the TECs faces challenges in terms of building structures embedding, which limits its application. In particular, the integrated structure of TEC makes it difficult to dissipate heat to outside of building.To overcome these challenges, the proposed research aims to investigate a novel TEC air cooler which has a number of distinguished innovations: (1) First-of-its-kind trial in separating hot and cold ends enabling placement of one side of TEC to outside of the building and another side of TEC to inside of building, thus creating an increased temperature gradient between the ends and increased cooling capacity. Furthermore, separated TEC makes it possible to be integrated with the building façade. (2) Initiative optimization of the TEC geometries enables the enhanced energy performance and cooling capacity that makes the TEC more building applicable; (3) Pioneering full-day case studies of TEC performance illustrates the applicability and adaptation of the coolers across different climatic conditions of the world.This thesis employs a fundamental approach that integrates both theoretical and experimental analyses. The methodology comprises an exhaustive literature review, a conceptual design phase, mathematical analysis, model development, validation, and an in-depth examination of performance and thermal characteristics for thermoelectric geometry optimization. Furthermore, the thesis includes a conceptual design phase, mathematical analysis, model development, experimental testing, model validation, performance analysis, and real-climatic condition case studies.Trials on the separated configuration TEC indicate that the specialist TEC, when applying 10 K temperature difference and 5A of current, led to reduction in cooling capacity by 5.6% compared to the integrated TEC, varying from 7.13 W to 6.76 W. However, the TEC device height will be doubled. While sacrificing a small portion of cooling capacity, the TEC’s application scenarios have been significantly broadened. It is noteworthy that separated-TEC configuration exhibits excellent cooling power density. The cooling capacity per unit area could exceed 15 kW/m2 under high current (I=5A), even at low current (I=0.5A), it is up to 500 W/m2.Geometry optimization of the TEC reveals that the proposed design excels in both cooling performance and thermal-mechanical characteristics. The study demonstrates that under specified conditions, the truncated cone-shaped module (g) exhibits a noteworthy improvement in cooling capacity. In comparison to a traditional TEC, the cooling capacity from 0.1429 W increases to 0.1557 W, when operating at a temperature difference of 50 K, marking an 8.9% enhancement. This translates to a rise in the overall TEC device's cooling capacity from 18.15 W to 19.78 W. Additionally, the 'g' module, characterized by its absence of corners or edges, effectively reduces the peak von Mises stress.A number of case studies were undertaken. The results show that, by introducing the separated-configuration structure, the unit cooling capacity of TEC system increases from 16.66 W/m2 to 18.82 W/m2 by 13%, while the cooling surface temperature is reduced by 0.2 °C.This research shows that the TEC geometry optimization and separated TEC configuration create an opportunity to allow the TEC to be well integrated into a building. The cooling performance of the TEC could be improved by establishing the optimal geometry and its proper connection and configuration

Performance assessment and optimisation of a novel guideless irregular dew point cooler using artificial intelligence

Air Conditioners (ACs) are a vital need in modern buildings to provide comfortable indoor air for the occupants. Several alternatives for the traditional coolers are introduced to improve the cooling efficiency but among them, Evaporative Coolers (ECs) absorbed more attention owing to their intelligible structure and high efficiency. ECs are categorized into two types, i.e., Direct Evaporative Coolers (DECs) and Indirect Evaporative Coolers (IECs). Continuous endeavours in the improvement of the ECs resulted in development of Dew Point Coolers (DPCs) which enable the supply air to reach the dew point temperature. The main innovation of DPCs relies on invention of a M-cycle Heat and Mass Exchanger (HMX) which contributes towards improvement of the ECs’ efficiency by up to 30%. A state-of-the-art counter flow DPC in which the flat plates in traditional HMXs are replaced by the corrugated plates is called Guideless Irregular DPC (GIDPC). This technology has 30-60% more cooling efficiency compared to the flat plate HMX in traditional DPCs.Owing to the empirical success of the Artificial Intelligence (AI) in different fields and enhanced importance of Machine Learning (ML) models, this study pioneers in developing two ML models using Multiple Polynomial Regression (MPR), and Deep Neural Network (DNN) methods, and three Multi Objective Evolutionary Optimisation (MOEO) models using Genetic Algorithms (GA), Particle Swarm Optimisation (PSO), and a novel bio-inspired algorithm, i.e., Slime Mould Algorithm (SMA), for the performance prediction and optimisation of the GIDPC in all possible operating climates. Furthermore, this study pioneers in developing an explainable and interpretable DNN model for the GIDPC. To this end, a game theory-based SHapley Additive exPlanations (SHAP) method is used to interpret contribution of the operating conditions on performance parameters.The ML models, take the intake air characteristic as well as main operating and design parameters of the HMX as inputs of the ML models to predict the GIDPC’s performance parameters, e.g., cooling capacity, coefficient of performance (COP), thermal efficiencies. The results revealed that both models have high prediction accuracies where MPR performs with a maximum average error of 1.22%. In addition, the Mean Square Error (MSE) of the selected DNN model is only 0.04. The objectives of the MOEO models are to simultaneously maximise the cooling efficiency and minimise the construction cost of the GIDPC by determining the optimum values of the selected decision variables.The performance of the optimised GIDPCs is compared in a deterministic way in which the comparisons are carried out in diverse climates in 2020 and 2050 in which the hourly future weather data are projected using a high-emission scenario defined by Intergovernmental Panel for Climate Change (IPCC). The results revealed that the hourly COP of the optimised systems outperforms the base design. Moreover, although power consumption of all systems increases from 2020 to 2050, owing to more operating hours as a result of global warming, but power savings of up to 72%, 69.49%, 63.24%, and 69.21% in hot summer continental, arid, tropical rainforest and Mediterranean hot summer climates respectively, can be achieved compared to the base system when the systems run optimally

First Principles Modelling of Thermoelectric Materials

Thermoelectric semiconductor materials possess the unique ability to convert temperature differential into electricity or vice versa. This presents excellent opportunities for harvesting waste heat or cooling. Thermoelectric applications are found in many different areas ranging from medicine to space programs. The quality of the materials is determined by their thermoelectric properties like the Seebeck coefficient, electrical and thermal conductivity. In this thesis we model the thermoelectric properties from first principles. The materials of interest include Fe2VAl, NbFeSb, TaFeSb and Bi2Te3. The thermoelectric properties are analysed by considering the effects of doping, point defects, grain boundaries and size reduction. A number of key results are found. We show that the experimentally observed behaviour of the Seebeck coefficient in Fe2VAl can be theoretically modelled by enhancing the localisation of V electrons with the Hubbard model. We establish TaFeSb as a new thermoelectric material which exhibits 50 % better p-type thermoelectric properties than NbFeSb due to an increased scattering strength between Ta and potential dopants. We also note that mixing NbFeSb and TaFeSb does not have a negative impact on the electronic properties and could potentially lead to further improvements in the thermoelectric performance. We investigate the electronic thermoelectric properties of Bi2Te3 thin films. We find that the Seebeck coefficient increases dramatically when the film thickness is reduced to 1-2 nm. This leads to an overall increase in the power factor of the material and enhanced p-type thermoelectric performance. The successful calculation of the properties for a wide range of materials also shows that the developed in this project computational framework can be reliably used for further research on thermoelectrics

Optimisation of thermal output for an SMA-based heat pump

As countries transition to a low carbon economy, there are sizable environmental and economic benefits from developing and using efficient, innovative, low carbon heating and cooling technologies that have the potential to reduce energy use and carbon emissions. This thesis focuses on elastocaloric refrigeration technology and ways of enhancing the thermal outputs of Shape Memory Alloys (SMA), which are the core material of the technology. The thesis includes an up-to-date and comprehensive critical review and evaluation of recent advances in emerging alternative heating and cooling technologies that have the potential to reduce the environmental impacts of the refrigeration, air-conditioning and heat-pumps (RACHP) sector. The literature review on elastocaloric refrigeration showed that all the designed and manufactured prototypes to date either work under tension or under compression for pipes. The experiments also showed that using tension loading for a heat pump device is not practical despite its excellent heat transfer potential, as the material under tension tends to deform permanently much quicker, since the cracks on the surface of the material tend to grow and propagate and thus leading to failure; moreover, tension loading is limited to stress between 100 MPa to 200 MPa. On the other hand, although compressive loading requires specific geometric configurations to avoid failuressuch as buckling, it has a longer fatigue life, because the impurities and cracks do not grow and propagate; moreover, compression loading can exceed stresses of 1000 MPa allowing for better material performance. To overcome the challenges as identified and stated in the literature, it was necessary to establish a thorough understanding of the designated material properties with the aid of COMSOL MULTIPHYSICS modelling. This included looking at methods of altering the material's characteristics by means of heat-treatment, as well as using material characterization equipment to achieve improved thermal outputs. Moreover, the research focused on proposing and studying a range of novel geometric designs and configurations for the material. The best performing configuration was established, and this led to designing the SMA-heat-pump stack and the fluid flow paths. Also, the research focused on modelling the working fluids in COMSOL MULTIPHYSICS to establish the most appropriate means of enhancing their thermal properties. The first base-fluid to be tested was water, of which was followed by adding 1%, 2% and then 3% concentrations of Graphene Oxide nanoparticles to compose new nanofluids that had improved thermal properties. The research included a study of the relationship between the stress and strain, the temperature lift, and the available latent heat. Since the potential design was to stack the plates and compress them, the results showed that applying a compressive loading of 500 MPa on an SMA specimen resulted in a 1.63% of material’s deformation, a 10K temperature lift, and 1.46 \u1d43d. \u1d454−1 of latent heat. When the applied compressive loading was increased to 900 MPa, the material deformed by 5.4% and in so doing achieved a 19K temperature lift and 19 \u1d43d. \u1d454−1 of latent heat. On the plate design front, the results showed that the rectangular shape channels/fluid-path provided the highest Reynolds number which led to higher heat transfer coefficient; and as a result, it was possible to extract 98% of the available heat within the plate. On the fluids front, the results showed that the channel/ flow-path has different temperatures at different heights, and it was found that there is a lag between the increase of the material’s temperature and that of the fluid. It was also found that water achieved a temperature span of 2.8K; however, when 1%, 2% and 3% concentrations of the nanoparticles were added to water, the newly formed nanofluids had better thermal properties, as their thermal conductivity increased by 52%, 59% and 65% respectively, and because of that the temperature lift increased by 25.9% and the loading cycle was shortened by 24% with the third nanofluid (water plus 3% of Graphene Oxide), which will have a positive impact on the compactness and the cost of the SMA core. This research has contributed to knowledge through the following: ✓ Providing a roadmap for SMA modelling in CFD (COMSOL MULTIPHYSICS) and how SMA is susceptible to different applied stresses and cycle times. ✓ Providing a roadmap of how to design different SMA geometries that can withstand high stresses and thus could potentially be used as the core material for an SMA-based heat pump device without encountering material failure due to high stresses. ✓ Developing an innovative approach to enhance the heat transfer from SMA through using enhanced nanofluids

Optimisation of welding parameters to mitigate the effect of residual stress on the fatigue life of nozzle–shell welded joints in cylindrical pressure vessels.

Doctoral Degree. University of KwaZulu-Natal, Durban.The process of welding steel structures inadvertently causes residual stress as a result of thermal cycles that the material is subjected to. These welding-induced residual stresses have been shown to be responsible for a number of catastrophic failures in critical infrastructure installations such as pressure vessels, ship’s hulls, steel roof structures, and others. The present study examines the relationship between welding input parameters and the resultant residual stress, fatigue properties, weld bead geometry and mechanical properties of welded carbon steel pressure vessels. The study focuses on circumferential nozzle-to-shell welds, which have not been studied to this extent until now. A hybrid methodology including experimentation, numerical analysis, and mathematical modelling is employed to map out the relationship between welding input parameters and the output weld characteristics in order to further optimize the input parameters to produce an optimal welded joint whose stress and fatigue characteristics enhance service life of the welded structure. The results of a series of experiments performed show that the mechanical properties such as hardness are significantly affected by the welding process parameters and thereby affect the service life of a welded pressure vessel. The weld geometry is also affected by the input parameters of the welding process such that bead width and bead depth will vary depending on the parametric combination of input variables. The fatigue properties of a welded pressure vessel structure are affected by the residual stress conditions of the structure. The fractional factorial design technique shows that the welding current (I) and voltage (V) are statistically significant controlling parameters in the welding process. The results of the neutron diffraction (ND) tests reveal that there is a high concentration of residual stresses close to the weld centre-line. These stresses subside with increasing distance from the centre-line. The resultant hoop residual stress distribution shows that the hoop stresses are highly tensile close to the weld centre-line, decrease in magnitude as the distance from the weld centre-line increases, then decrease back to zero before changing direction to compressive further away from the weld centre-line. The hoop stress distribution profile on the flange side is similar to that of the pipe side around the circumferential weld, and the residual stress peak values are equal to or higher than the yield strength of the filler material. The weld specimens failed at the weld toe where the hoop stress was generally highly tensile in most of the welded specimens. The multiobjective genetic algorithm is successfully used to produce a set of optimal solutions that are in agreement with values obtained during experiments. The 3D finite element model produced using MSC Marc software is generally comparable to physical experimentation. The results obtained in the present study are in agreement with similar studies reported in the literature

Simulation-based process design and integration for retrofit

This research proposes a novel Retrofit Design Approach based on process simulation and the Response Surface Methodology (RSM).Retrofit Design Approach comprises: 1) a diagnosis stage in which the variables are screened and promising variables to improve system performance are identified through a sensitivity analysis, 2) an evaluation stage in which RSM is applied to assess the impact of those promising variables and the most important factors are determined by building a reduced model from the process response behaviour, and 3) an optimisation stage to identify optimal conditions and performance of the system, subject to objective function and model constraints. All these stages are simulation-supported. The main advantages of the proposed Retrofit Design Approach using RSM are that the design method is able to handle a large industrial-scale design problem within a reasonable computational effort, to obtain valuable conceptual insights of design interactions and economic trade-off existed in the system, as well as to systematically identify cost-effective solutions by optimizing the reduced model based on the most important factors. This simplifies the pathway to achieve pseudo-optimal solutions, and simultaneously to understand techno-economic and system-wide impacts of key design variables and parameters. In order to demonstrate the applicability and robustness of the proposed design method, the proposed Retrofit Design Approach has been applied to two case studies which are based on existing gas processing processes. Steady-state process simulation using Aspen Plus TM® has been carried out and the simulation results agree well with the plant data. Reduced models for both cases studies have been obtained to represent the techno-economic behaviour of plants. Both the continuous and discrete design options are considered in the retrofitting of the plant, and the results showed that the Retrofit Design Approach is effective to provide reliable, cost-effective retrofit solutions which yield to improvements in the studied processes, not only economically (i.e. cost and product recovery), but also environmentally linked (i.e. CO₂ emissions and energy efficiency). The main retrofitting solutions identified are, for the first case, column pressure change, pump-around arrangement and additional turbo-expansion capacity, while for the second case, columns pressure change, trays efficiency, HEN retrofit arrangements (re-piping) and onsite utility generation schemes are considered. These promising sets of retrofit design options were further investigated to reflect implications of capital investment for the retrofit scenarios, and this portfolio of opportunities can be very useful for supporting decision-making procedure in practice. It is important to note that in some cases a cost-effective retrofit does not always require structural modifications. In conclusion, the proposed Retrofit Design Approach has been found to be a reliable approach to address the retrofit problem in the context of industrial applications.EThOS - Electronic Theses Online ServiceConsejo Nacional de Ciencia y Tecnología de Mexico (CONACYT)GBUnited Kingdo