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Influence of the homogenization temperature on the microstructure and properties of AlSi10CuNiMn alloy

Cais J., Kraus P., Lysoňková I.

Advances in Science and Technology. Research Journal

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2017

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Vol. 11, no 1

104--110

EN

The article examines the impact of changes in homogenization temperature in the hardening process on the microstructure of aluminum alloys. The research samples were cast from AlSi10CuNiMn alloy produced by gravity casting technology in metal mold. Subsequently, the castings were subjected to a heat treatment. In an experiment with changing temperature and staying time in the process of homogenization. The microstructure of the alloy was investigated by methods of light and electron microscopy. Examination of the microstructure has focused on changing the morphology of separated particles of eutectic silicon and intermetallic phases. The analysis of intermetallic phases was supplemented by an analysis of the chemical composition – EDS analysis. Effect of heat treatment on the properties investigated alloy was further complemented by Vickers microhardness. Investigated alloy is the result of longtime research conducted at the Faculty of Production Technology and Management.

2

Application of chemical pre-treatment on the polished surface of aluminium alloys

Kraus P., Svobodova J., Cais J., Lattner R.

Advances in Science and Technology. Research Journal

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2016

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Vol. 10, nr 32

17--23

EN

This paper reports the preparation and characterization of thin transparent nanolayers with phase composition ZrF4 and different modification of SiO2 with special focus on affecting the surface roughness of the material and the way of exclusion of the thin nanolayer on the surface of the polished aluminium material. The thin nanolayer was prepared by the sol-gel method. The final treatment based on PTFE was applied on the surface of some samples. This treatment is suitable for increasing wear resistance. The films were characterized with help of SEM microscopy and EDS analysis. The surface roughness was measured with classical surface roughness tester. The results on this theme have already published but not on the polished surface of the aluminium material. The results from the experiment show the problems with application of these nanolayers because a cracks were found on the surface of the material and deformations of the layer after application of the PTFE final layer. The surface layer formation is discussed.

3

Nearest neighbor search by using Partial KD-tree method

Kraus P., Dzwinel W.

Theoretical and Applied Informatics

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2008

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Vol. 20, No. 3

149-165

EN

We present a new nearest neighbor (NN) search algorithm, the Partial KD-Tree Search (PKD), which couples the Friedman’s algorithm and the Partial Distance Search (PDS ) technique. Its efficiency was tested using a wide spectrum of input datasets of various sizes and dimensions. The test datasets were both generated artificially and selected from the UCI repository. It appears that our hybrid algorithm is very efficient in comparison to its components and to other popular NN search technique – the Slicing Search algorithm. The results of tests show that PKD outperforms up to 100 times the brute force method and is substantially faster than other techniques. We can conclude that the Partial KD-Tree is a universal and effcient nearest neighbor search scheme.

PL

W pracy prezentujemy rezultaty poprawy efektywności poszukiwania najbliższego sąsiada poprzez hybrydyzację dwóch najczęściej używanych algorytmów: algorytmu Friedman’a opartego o tzw. K-D drzewa oraz prostej techniki liczenia odległości fragmentami (Partial Distance Search (PDS)). Efektywność powstałego algorytmu przetestowano na danych wygenerowanych w sposób sztuczny oraz na popularnym repozytorium danych UCI. Badano efektywność w zależności od wymiaru przestrzeni oraz strukturalnej złożoności testowanych danych. Okazuje sią że nasz hybrydowy algorytm jest wyraźnie efektywniejszy niż jego części składowe oraz inny popularny algorytmy znajdowania najbliższego sąsiada jak poszukiwanie plasterkowe (Slicing Search (SS)). Rezultaty testów pokazują, że na wybranych danych algorytm jest nawet parą rzędów szybszy niż metoda typu Exhaustive Search i kilka razy szybsza niż inne konkurencyjne wyspecjalizowane algorytmy.