Search

Evolutionary parametric shape optimization relies on generic shape models which provide sufficient 3D geometric modeling freedom while being modest in terms of the number of shape variables and hence dimensionality of search space. The number of shape parameters needs to be reduced towards computational efficiency in shape optimization. However, this may imply loss of generality or local modeling capacity, potentially also bias towards unintentionally predefined 3D shape templates, all of which may result in sub-optimal shapes. This paper develops a novel approach in the form of a conceptual intelligent system based on integral parametric surfaces representing objects. The computational efficiency of the models is established by engaging a sparing multitude of shape parameters in evolutionary optimization. Sufficiently generic and unbiased modeling capacity is obtained by the adaptability of the approach, as it can adapt to the features of the current state in optimization iterations. Decomposition of the integral surfaces into shape partitions is implemented based on 3D pattern recognition (edges, peaks, etc).

The positioning of PV panels for maximum energy extraction is a well-known problem. This problem is particularly important within an islanded microgrid system since the change of the PV panel positioning directly influenced the remaining microgrid system components. This problem can also be coupled with the microgrid sizing problem. Different optimization approaches exist in the literature. In this paper, we investigate the effect of different optimization approaches in a microgrid system in the case when a simple battery degradation model is used. It was shown that the battery degradation model significantly influences the optimal parameters of the system and investment cost savings up to 4.3% can be achieved, compared to the selection of convectional optimum PV positioning values.

Vertical axis wind-turbines (VAWT) can be divided in Darrieus and Savonius designs. The advantage of the Darrieus design is higher energy conversion efficiency. The advantage of the Savonius design is the self-starting ability and lower tip-speed ration (TSR). By combining both designs (Figure 1a) into a hybrid design might offer a combination of the mentioned advantages of both designs [1-2]. This research considers the possibility of numerical simulation and optimization of the hybrid VAWT design. An initial optimization using only the maximum power coefficient as a criterion has shown that the optimized design does not have the desirable self-starting ability (Figure 2). Thereby the both aspects of the design should be considered (Figure 1b). In the simplest optimization, only two shape variables can be used by only scaling a fixed-shape Darrieus and Savonius components. In more complex optimization, the number of variables can rise to 10-20 [3]. The prerequisite to any optimization is the selection of appropriate numerical simulation parameters. The number of required timesteps for the convergence of 2D CFD simulation for a Darrieus design alone was shown to be about 105 which about 103 core-hours [4]. This means that only a relatively small number of simulations can be conducted in a realistic time- scales thereby reducing the possible number of variables in optimization. This research discusses the possibilities of reduction of simulation time by adaptive time-step control. The reduction of the optimization time is considered by adaptively increasing the CFD fidelity for potentially good design.

The paper deals with a passive air based cooling technique of photovoltaic (PV) panels in operating conditions. Cooling technique is done by specific type of using aluminium fins, and its main purpose is to increase the electrical efficiency of the PV panel. An increase in electrical efficiency can be achieved because of temperature degradation effect, where the PV panel yields less power at higher operating temperatures (the PV panel’s efficiency can drop by up to 0.5%/°C). To confirm a cooling technique, a medium-sized PV system was used in a two-month experiment. The experiment was done in realistic operating conditions, and all working parameters were thoroughly measured. After the analysis of the data, no significant raise in electrical efficiency was recorded throughout the experiment. A numerical approach was conducted, based on gained experimental data. Developed numerical model gave explanations of experimental results, and provided an insight in heat flow through the PV cell. Later on, developed numerical model was used to propose new cooling variations of the fin based technique , and to further examine the overall potential of air based passive cooling techniques. It was shown that cooling effect by up to 5°C is a realistic expectation for this technique in described operating conditions.

Results shown in this paper were acquired by the prototype laboratory die casting testing equipment. This paper is a part of experimental research in area of high pressure die casting (HPDC) mould wear (H11). The laboratory equipment was designed to achieve similar conditions to die casting process. The main goal was to analyze tribological wear mechanisms of a die casting mould such as: thermal fatigue, erosion and adhesion wear. Testing parameters were set to simulate con-ditions in HPDC of aluminium alloy. Results for thermal fatigue wear of the mould material are presented for three samples. Samples were tested under same parameters for 10000 testing cycles, except with significantly different preheating temperature. Results are shown graphically by 3D scan before and after the ex-periment. The wear was also determined by mass loss of the tested samples.

Centrifugal roof fans are traditionally considered as ‘small’ machines and as such did not attract much attention. They can be categorized as low power fans as their installed power is usually bellow 2kW. Nevertheless, they make approximately 30% of fans used in non-residential ventilation, which when considered on mass-scale makes them large energy consumers. Since they have relatively low efficiency (ranging between 0.3-0.5), considerable space for improvement exists. This resulted in various studies which include optimization coupled with CFD flow models. The most often used criterion was fan efficiency at single flow regime. Recent studies have shown that this is not a good approach since there can be multiple different solutions with almost the same single-regime efficiency. A better approach is to conduct optimization for multi-regime operating conditions or to use multi-objective optimization with the minimization of noise emission used as the second criterion. The predictions of numerical flow model must be robustly accurate (for various in impeller shapes and flow regimes). In this paper, enhanced CFD models for the prediction of fan energy performance and noise emissions are developed. First, the RANS based models with the frozen-rotor approach and k- epsilon / k-omega turbulence models were reviewed. The application of more advanced models of frozen-rotor RANS, URANS and LES models is investigated. The CFD predictions are compared to our experimental data from a previous study. The results show that improved prediction of energy efficiency is obtained with LES based CFD models for the off-design flow regimes. Meanwhile, the RANS and URANS models can also provide good results when using first-order upwind discretization scheme. The results show that using high-order discretization schemes deteriorates the CFD prediction of the fan performance. The fan noise emission was predicted using LES data and this allowed for the investigation of wide-spectra noise in comparison to simple models used in previous papers. The models developed in this paper can be used as the basis for shape optimization studies which require multi-fidelity simulations.

Engineering shape optimization often involves computationally expensive numerical simulations such as computational fluid dynamics. Furthermore, these technical objects are almost always complex three-dimensional shapes that cannot adequately be described with a small number of shape variables. These problems are usually solved by gradient method starting from an initial solution. This approach is computationally efficient especially when the gradients are calculated by the adjoint method. However, this approach can be used only to obtain a local optimum. To obtain the global optimal solution, different approach is required. A possible approach is to use B-spline surfaces to describe the shape and genetic algorithm for optimization of the B-spline control point coordinates. The problem with this approach is that it requires many computationally expensive numerical simulations. The objective of this paper is the evaluation of different surrogate models on the cases of global shape optimization which involve B-spline shape parameterization and computational fluid dynamics. The first step is solving several selected problems by genetic algorithm starting from a randomly generated population. The optimization variables are only the coordinates of the B-spline control points. After the optimal solution is obtained by genetic algorithm, several surrogate models were tested in various stages of the optimization procedure. The results are used to propose which surrogate models are appropriate for various stages of the global optimization problem at hand. This leads to a surrogate based optimization method developed specifically for global shape optimization based on B-spline shape parameterization.

U radu je razvijen numerički radni tok za reverzno inženjerstvo i optimiranje brodskog vijka sa ili bez sapnice. Prvi korak procedure je 3D skeniranje brodskog vijka čime se dobiva 3D oblak točaka. Zatim se pristupa opisivanju geometrije brodskog vijka i sapnice pomoću generičkih B-spline ploha. Da bi se pristupilo postupku optimiranja, razvijen je CFD model slobodnog strujanja brodskog vijka. Korišteno je višekriterijsko optimiranja gdje je jedna funkcija cilja maksimum efikasnosti, a druga maksimalni poriv. Rezultat je set Pareto optimalnih rješenja. Ograničenja su postavljena na dimenzije, a razmatrala se i kavitacija kao dodatno ograničenje. Provedena je dvo-stupanjska optimizacija oblika. U prvom stupnju se optimirao oblik sapnice za trenutno stanje brodskog vijka. U drugom koraku je optimiran oblik brodskog vijka za fiksni oblik sapnice. Rezultati su pokazali da korištene metode korištenja generičkog opisa geometrije mogu sintetizirati oblik sapnice i brodskog vijka koji povećava učinkovitost. Preliminarna analiza pojave kavitacije pokazala je mogućnosti simulacije bez velikih povećavanja računalnih resursa stoga će se za budući rad ugraditi kao dodatno ograničenje u razvijeni numerički radni tok. Nadalje će se razmatrat tro-stupanjska optimizacija gdje je u trećoj fazi optimizatoru dopušteno istovremeno optimiranje i sapnice i brodskog vijka.

This paper deals with influence of PV panel size on its average working temperature. A numerical model has been established in accordance with experimental results gained in realistic operating conditions. Established model was used to gain information of size influence on average panel temperature. Results show significant difference in average temperature between several distinct panel sizes. Since the dependence between temperature and electrical efficiency of PV panel is already known, provided information can be used in future design of PV systems.