1. |
2. Optimizacija Chaboche materialnih parametrov z genetskim algoritmom : magistrsko deloNejc Dvoršek, 2022, master's thesis Abstract: The basis of this thesis is research and development of a genetic algorithm for material parameters optimization. It is written in collaboration with AVL, which already has a solution for this problem, but is looking into better alternatives. Chaboche material model is a nonlinear isotropic and kinematic hardening model which can describe elasto-viscoplastic constitutive relations. Parameters of such complex nature do not have a physical interpretation in the real-world and must be defined with inverse analysis. Genetic algorithms (GA) are a promising tool to help with such tasks. They have been widely used and recognized for various optimization problems. Material data available are low cycle fatigue (LCF), creep, and tensile experiments. For each experiment a corresponding finite element model in Abaqus is prepared. Comparing experimental and simulation data is the objective function GA will try to minimize. For this reason, a corresponding fitness function was developed to score each individual. It makes use of similarity measure algorithm proposed in this paper [10]. GA was implemented in Python with Pygad library. Instead of bits, genes are represented with real-valued numbers with defined limits. Performance of developed GA was tested based on various population sizes, mutation probabilities, and crossover operators. The main parameter that impacts algorithms performance is population size. Paired with right mutation probability the algorithm can find a global minimum of described optimization problem. Making it a viable alternative to existing approach used at AVL.
Keywords: Chaboche material model, parameter optimization, genetic algorithm, finite element method
Published in DKUM: 16.12.2022; Views: 872; Downloads: 0
 Full text (1,90 MB) |
3. Measurements of material heat transfer properties : master study programmeMiha 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: 834; Downloads: 47
Full text (6,54 MB) |
4. 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: 1665; Downloads: 35
Full text (3,19 MB) |
5. Development of analytical methods for simultaneous identification and determination of phenolic compoundsMilena Ivanović, 2018, doctoral dissertation Abstract: The objective of this doctoral dissertation was to develop different analytical approaches for the extraction, separation, identification and quantitative determination of various phenolic compounds from different plants and their products. This dissertation is divided into the following four major segments, which, to some extent, can stand alone, but when it comes to the research, they are mutually very related:
- Segment 1: Short-term (up to 24 h) and long-term (up to 1 month) stability studies of trans-caffeic acid (trans-CA) and trans-ferulic acid (trans-FA) dissolved in two organic solvents (methanol and tetrahydrofuran) and exposed to a range of storage conditions (temperature, organic solvents used, influence of daylight and UV irradiation) were performed for the first time. Gas chromatography with mass spectrometry (GC-MS) was used to study the degradation of the samples and structural identification of the degradation products.
- Segment 2: The research within this segment focused on the optimization of a simple, fast and quantitative extraction method for the isolation of phenolic acids (PAs) from Slovenian red wine samples. Different extraction techniques were tested, and solid phase extraction (SPE) using HLB cartridges was selected as the optimal technique. For the identification and quantification of extracted analytes, the GC-MS method was optimized and validated. Different statistical and chemometrical tools were applied, and the wines were classified according to the Slovenian wine-growing regions and vine varieties.
- Segment 3: The main goal within this research segment was the development of an ultrasound-assisted extraction (UAE) method for the isolation of different polyphenol classes from coriander fruits. Additionally, for the isolation of total PAs (free and bound), two analytical steps were applied: UAE alkaline hydrolysis and clean-up using SPE HLB cartridges. The response surface methodology (RSM) combined with a Box-Behnken experimental design (BBD) were used for the optimization of the alkaline hydrolysis and for increasing the extraction yields of the PAs. In this way, most influencing factors (temperature, sonication time and NaOH concentration) were studied as independent variables. Extracted PAs were determined using the previously optimized GC-MS method.
- Segment 4: The main goal of this segment of the dissertation was to show the application of deep eutectic solvents (DESs) as a ‘green’ alternative to the conventional organic solvents for the isolation of phenolic compounds from plants such as Aronia melanocarpa (dried chokeberry) and Olea europaea (olive leaves). Different extraction techniques and instrumental methods were applied for the determination of phenolic profiles. Phenols from chokeberries were obtained through UAE. Furthermore, for the simultaneous identification and quantitative determination of 21 different phenolic compounds from Aronia melanocarpa, the HPLC-UV method was optimized and validated. On the other hand, microwave-assisted extraction (MAE) was used to improve the extraction yields of phenolic compounds from olive leave samples, which were subsequently determined by using validated HPLC-DAD-ESI-TOF-MS method.
Keywords: phenolic compounds, phenolic acids, extraction, GC-MS, HPLC, method optimization, deep eutectic solvents, plant material
Published in DKUM: 11.04.2018; Views: 2385; Downloads: 173
Full text (5,10 MB) |
6. A multi-objective optimization approach for designing automated warehousesTone Lerher, Matej Borovinšek, Iztok Potrč, Matjaž Šraml, 2012, published scientific conference contribution Abstract: A multi objective optimization of automated warehouses is discussed and evaluated in present paper. Since most of researchers in material handling community had performed optimization of decision variables with single objective function only (usually named with minimum travel time, maximum throughput capacity, minimum cost, etc.), the multi objective optimization (travel time - cost - quality) will be presented. For the optimization of decision variables in objective functions, the method with genetic algorithms is used. To find the Pareto optimal solutions, the NSGA II genetic algorithm was used. The main objective of our contribution is to determine the performance of the system according to the multi objective optimization technique. The results of the proposed model could be useful tool for the warehouse designer in the early stage of warehouse design.
Keywords: automated warehouses, material handling, multi objective optimization
Published in DKUM: 10.07.2015; Views: 1331; Downloads: 34
 Link to full text |
7. The multilevel MINLP optimization approach to structural synthesis: the simultaneous topology, material, standard and rounded dimension optimizationStojan Kravanja, Simon Šilih, Zdravko Kravanja, 2005, original scientific article Abstract: The paper describes the simultaneous topology, material, standard and rounded dimension optimization of mechanical structures, performed by the Mixed-Integer Non-linear Programming (MINLP) approach. Beside the generation of an MINLP mechanical superstructure, the development of a general multilevel MINLP formulation for a mechanical superstructure is presented. The consideration of the discrete materials as well as standard and particularly rounded dimensions in structural synthesis significantly increases the combinatorics of the discrete optimization, which as a result may become too difficult to solve. A Linked Multilevel Hierarchical Strategy (LMHS) has been introduced for the solving of such large combinatorial problems. In order to decrease the effect of non-convexities, the Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm has been applied. Four numerical examples of different complexities are presented to illustrate the proposed multilevel MINLP optimization approach: the optimization of two steel trusses, a composite I beam and a hydraulic steel roller gate Intake gate, erected in Aswan II, Egypt.
Keywords: structural optimization, structural synthesis, MINLP, topology opitmization, material optimization, discrete variable optimization, multilevel MINLP strategy, truss, composite beam, roller gate
Published in DKUM: 01.06.2012; Views: 2803; Downloads: 107
Link to full text |
