Optimization methods for a direct current electric motor design : magistrsko deloVid Černec
, 2022, master's thesis
Abstract: In the modern world, the need for planning in advance has become increasingly important. The companies want to know the cost, the dimensions of the elements, and the properties of the final product in advance. Therefore, we can find teams working on the analysis and development of new and different products in larger companies. More experienced workers can determine the given results and see what would be acceptable by simply looking at the situation. Although, the help of technology makes the process easier and faster, and even provides the same result. When creating a specific model, we must focus on the equations describing our result. Then we begin with optimization, which means we define the variables, which will be our subject of research in the project, and define some fixed parameters until the desired goals are reached.
Keywords: design, DC electric motor, optimization, optimization algorithms, genetic algorithms
Published in DKUM: 21.10.2022; Views: 40; Downloads: 7
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Optimization methods for charging an electric vehicle : magistrsko deloLara Borovnik
, 2022, master's thesis
Abstract: This thesis contains the comparison of different optimization methods that were implemented on a mathematical model of battery charging for electric vehicles. The goal was to compare how the total price of charging changes with different methods and what happens to other variables in equations with different types of optimizations. We tested what happens if the battery only works in charging mode and what happens if we add a possibility of discharging the battery meaning that the electricity goes from the battery back to the grid (vehicle to grid mode). The mathematical model was implemented in Python and optimized using various methods that are from Python libraries SciPy and Pymoo.
Keywords: optimization, battery charging, Python, SciPy, Pymoo
Published in DKUM: 21.10.2022; Views: 33; Downloads: 9
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Measurements of material heat transfer propertiesMiha Donša
, 2022, master's thesis
Abstract: An experimental setup was created to observe temperature change at two points inside the experimental body. Such an experimental setup created data that was used as an anchor point of optimization that was coupled with numerical models to find unknown variables of heat conductivity and specific heat of the materials. Two numerical models were created. A 1D numerical model was created for possibilities of fast optimization ignoring the insulation and heat transfer through it. Such a model did not manage to describe the experimental setup accurately. Therefore, a 3D numerical model was created simulating the whole experimental setup and yielded much more promising results. Problems with the model were soon seen when experimental data was compared to the numerical solution where variables that were initially not taken into the account showed a much greater effect than first anticipated. Therefore, the 3D numerical model was adjusted to describe the experimental setup as accurately as possible. The experiment was done with two different materials. The materials were picked based on their heat conductivity (high and low). High heat conductivity material was easy to understand and to find a solution to it. With low conductivity material, some problems were quickly observed and as such created a lot of questions as to why and how to find the unknown variables of the material. It was then shown that the masses of the materials in the experiment and the length of the experiment played the most important role in the experiment and quickly explained why and how the experimental setup should be modified to obtain better results.
Keywords: heat transfer, material heat transfer properties, specific heat, heat conductivity, optimization, numerical simulation of heat transfer
Published in DKUM: 07.07.2022; Views: 151; Downloads: 18
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uARMSolver: a framework for association rule miningIztok Fister
, Iztok Fister
, 2020, treatise, preliminary study, study
Keywords: association rule mining, categorical attributes, numerical attributes, software framework, optimization
Published in DKUM: 17.03.2021; Views: 665; Downloads: 24
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An analysis of exploration and exploitation using attraction basins on 2D and 3D continuous functions : master's thesisMihael Baketarić
, 2020, master's thesis
Abstract: In this thesis we were discussing an analysis of numerical optimization algorithms from the most important aspect, that is exploration and exploitation. We focused on 2-dimensional and 3-dimensional unconstrained continuous functions, which were used to test the recently proposed metric based on attraction basins. The metric does not need any user-defined parameters. Attraction basins were expounded more profoundly and extensively. Our algorithm to calculate them consists of three steps such as making potential boundaries, filling, and then removing false boundaries from attraction basins. Results show that our algorithm is barely satisfying, depends on a particular problem function used. For example, attraction basins from Rastrigin, Schwefel, Ackley and similar functions (including all unimodal ones) were calculated accurately, while more special functions like Michalewicz, Shubert and Branin were proved to be not so easy. Further, we arbitrarly selected two algorithms, Particle Swarm Optimization and Self-adapting Differential Evolution, not for comparative study, rather to test the metric based on attraction basins. Results implied the relevance of recently proposed metric, and opened us a fruitful field for further investigation.
Keywords: exploration, exploitation, attraction basins, optimization, metaheuristic
Published in DKUM: 04.11.2020; Views: 393; Downloads: 63
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Optimization of the distribution network operation by integration of distributed energy resources and participation of active elements : doctoral thesisNevena Srećković
, 2020, doctoral dissertation
Abstract: Distribution Networks (DNs) are evolving from a once passive to an active part of the electricity network. This evolution is driven by the current political and environmental decisions, Directives and Incentives, as well as the technological development, observed in the everincreasing integration of renewable energy resources, advanced network control and measurement devices, the upcoming energy exibility market, etc. This Doctoral Thesis deals with the problem of optimization of the technical aspects of a DN operation, enabled by the proliferated integration of the photovoltaic systems (PV) and other active devices. The main objective of the Thesis is the optimization of a DN operation in terms of minimization of electrical energy losses while ensuring the proper voltage profiles and preventing thermal overloadingof lines. Therefore, three Differential Evolution-based optimization procedures were developed and tested on real medium and low voltage DNs. The first methodology determines the optimal rooftop surfaces for the installation of PV systems, yielding minimum annual energy losses. It is based on the simultaneous consideration of high-resolution spatio-temporal solar and PV potential data, as well as long-term measured profiles of consumption and generation of electrical energy within the network of a given configuration. The second algorithm minimizes network losses in a time-discrete operation point, by determining the optimal operation of the following active elements: PV systems capable of cooperation in reactive power provision, On-Load Tap Changer equipped transformer substations and remotely controlled switches for network reconfiguration. The final algorithm was developed by a proper consolidation of the first two approaches, yielding the synergistic effects expressed as the increase of loss reduction and network exibility. The results of the performed case studies show that the locations of the highest suitability for PV installation with respect to the solar energy availability, are not necessarily the best choice from the network operation standpoint. Therefore, both standpoints should be considered simultaneously when choosing the rooftop surfaces for PV installation. Furthermore, by determining optimal hourly operation of the considered active elements, not only the additional reduction of annual network losses was achieved, but also increased accommodation of the PV systems that doesn't violate operation constraints.
Keywords: distribution network, optimization of operation, active network elements, PV system placement, minimization of losses
Published in DKUM: 11.06.2020; Views: 1231; Downloads: 254
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Influence of Heat Treatments on Microstructure of Electron Beam Additive Manufactured Ti-6Al-4V Alloy : magistrsko deloDamir Skuhala
, 2020, master's thesis
Abstract: Additive manufacturing of metallic parts is increasing in popularity and starting to emerge as a new competitive manufacturing process. Printed structures from Ti-6Al-4V titanium alloy, produced by electron beam additive manufacturing (EBAM), possess columnar prior β grains and layer bands, alongside an ultrafine lamellar microstructure, which is prone to low ductility and thus requiring thermal post-processing. Several heat treatments were performed in α + β and β field, in one or multiple stages. The results showed that bi-lamellar microstructure can be obtained, and that selection of annealing temperature and cooling rate determines the morphology, thickness, and distribution of both primary and secondary α features. Mechanical properties were evaluated on three selected heat treatments. Annealing of the As-built condition was performed at 710°C (HT1) and 870°C (HT2), resulting in lamellar microstructure with basketweave morphology. In two-stage heat treatment (HT3), the temperature in the first stage has exceeded β transus, while in the second, annealing was performed again at 870°C. The microstructure was characterized as a mixture of lamellar and bi-lamellar with large α colonies inside the rearranged prior β grains. Air cooling was performed in all HT from the final annealing stage. Strength and hardness have decreased with increasingly coarser microstructural features, while fracture toughness was improved, except in HT1, where the decrease in the fracture toughness was mainly attributed to reduced intrinsic toughening. As-built and HT1 conditions were eﬀected by microstructural texture, causing inconsistent fracture morphology, reduced crack roughness and scattering in results. The influence of texture was decreased by coarser microstructure in HT2, while crack tortuosity was increased. Very unpredictable fracture behaviour was observed in HT3 due to large α colonies, as their orientation determines the areas of ductile or cleavage crack propagation.
Keywords: Titanium alloys, Ti-6Al-4V, additive manufacturing, EBAM, heat treatments, microstructural optimization, mechanical properties, fracture toughness
Published in DKUM: 11.05.2020; Views: 910; Downloads: 164
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INJECTION MOULDING PROCESS OPTIMIZATION OF CITRUS FIBER BIOCOMPOSITES BY SIMULATIONS AND TAGUCHI EXPERIMENTAL DESIGN : magistrsko deloPeter Fajs
, 2019, master's thesis
Abstract: The objective of the master thesis is to determine the filling properties of injection moulding process for newly created material, and to understand how the variation of processing parameters affects the flow possibilities. In thesis two materials were analysed, i.e. neat PLA material, which was used as a benchmark material and newly created composite CitrusPLA that is based on biodegradable PLA matrix and reinforced with citrus fibres. To fulfil the aim, the virtual and experimental design of experiment with the Taguchi methodology was conducted with use of spiral flow test, where the flow length of material through mould cavity was observed. The experimental results were the basis for the accuracy validation of numerical results and also to determine the optimum process parameters for injection moulding products with best flow conditions through statistical evaluation.
It has been concluded that the newly created composite has lower viscosity compared to benchmark virgin PLA which results in better flow conditions in spiral flow test analysis. Both materials have the same optimal conditions in terms of flow conditions. The contribution of mould temperature is in both cases negligible. However, other two variated parameters i.e. melt temperature and injection speed have higher influence on filling characteristics for both materials.
Keywords: injection moulding optimization, material characterization, Moldflow, injection moulding simulations, Taguchi DOE, bio-composites, citrus waste fibres, PLA
Published in DKUM: 07.06.2019; Views: 1111; Downloads: 9
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FORMULATION, PREPARATION AND CHARACTERIZATION OF NANOEMULSIONS FOR PARENTERAL NUTRITION : doctoral disertationDušica Mirković
, 2019, doctoral dissertation
Abstract: The aim of this doctoral research was to develop and optimize parenteral nanoemulsions as well as the total parenteral nutrition (TPN) admixture containing a nanoemulsion obtained in the course of the optimization process (hereinafter referred to as optimal nanoemulsion), and to examine their physicochemical and biological quality as well. In addition, the quality of the prepared nanoemulsions was compared with the quality of the industrial nanoemulsion (Lipofundin® MCT/LCT 20%), and, in the end, the TPN admixture initially prepared was also compared with the admixture into which the industrial emulsion was incorporated.
Parenteral nanoemulsions that were considered in this dissertation were prepared by the high-pressure homogenization method. This method is the most widely applied method for the production of nanoemulsions due to the shortest length of homogenization time, the best-obtained homogeneity of the product and the smallest droplet diameter.
For the nanoemulsion formulation, preparation and optimization purposes, by using, firstly, the concept of the computer-generated fractional design, and, after that, the full experimental design, the assessment of both direct effects of different formulation and process parameters (the oil phase type, the emulsifier type and concentration, a number of homogenization cycles and the pressure under which homogenization was carried out) as well as the effects of their interactions on the characteristics of prepared nanoemulsions was performed.
Monitoring the nanoemulsion physical and chemical stability parameters was carried out immediately after their preparation, and then after 10, 30 and 60 days. It included the visual inspection, the measurement of the droplet diameter (the mean and volume droplet diameter), the polydispersity index, the ζ-potential, the pH value, the electrical conductivity, and the peroxide number. After the preparation and after 60 days, the biological evaluation (the sterility test and the endotoxic test) of the prepared nanoemulsions was carried out. As far as the characterization of the TPN admixture is concerned, it included practically the same parameters. The dynamics of monitoring the characteristics of the TPN admixture was determined on the basis of practical needs of hospitalized patients (0h, 24h and 72h).
The scope and comprehensiveness of this issue indicated the need to divide the doctoral dissertation into three basic stages. The first stage was preliminary. Using the 24-1 fractional factorial design, nanoemulsions for the parenteral nutrition were prepared. They contained either a combination of soybean and fish oil, or a combination of medium chain triglycerides and fish oil. In addition, the type and the amount of an emulsifier used, a number of high-pressure homogenization cycles, and the homogenization pressure, were also varied. The measurement of the above-mentioned parameters for the industrial nanoemulsion was parallely carried out (Lipofundin® MCT/LCT 20%). The objective of this part of the research was to identify critical numerical factors having the most significant effect on the characteristics that define the prepared parenteral nanoemulsions. Parameters that were singled out as the result of this stage of the research (the emulsifier concentration and a number of homogenization cycles) were used as independent variables in the second stage of the research.
Keywords: nanoemulsions, total parenteral nutrition admixtures, high pressure homogenization, design of experiments, optimization, analysis of variance, artificial neural networks
Published in DKUM: 07.06.2019; Views: 11328; Downloads: 8
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