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Projektowanie materiałowe kompozytu z odpadami poliestrowo-szklanymi

100%

Jastrzębska M. , Blokus-Roszkowska A.

2015

tom T. 94, nr 6

1003-1007

Przedstawiono model materiałowy kompozytu poliestrowego z odpadami poliestrowoszklanymi oraz mączką dolomitową. Model został zbudowany na podstawie wyników doświadczeń i ich statystycznej analizy. Jakość dopasowania modelu oceniono przez wyznaczenie współczynników determinacji. Oceniono wpływ składników na wybrane właściwości kompozytu i zaproponowano funkcję optymalizacji pozwalającą na dobór optymalnego składu kompozytu.

Polyester matrix composite was modified by addn. of glass fiber-reinforced polyester composite waste (grain size below 7.0 mm) and dolomite powder, cured and studied for compressive and flexural strengths and water absorption. Synergy between the polyester resin and the recyclate resulted in a decrease in mech. properties and increase in H₂O absorption. The recyclate content optimization functions were derived.

Methodology of high-speed steels design using the artificial intelligence tools

100%

Sitek W.

Journal of Achievements in Materials and Manufacturing Engineering

2010

tom Vol. 39, nr 2

115-160

Purpose: The main goal of the research carried out was developing the design methodology for the new high-speed steels with the required properties, including hardness and fracture toughness, as the main properties guaranteeing the high durability and quality of tools made from them. It was decided that hardness and fracture toughness KIc are the criteria used during the high-speed steels design. Design/methodology/approach: In case of hardness, the statistical and neural network models were developed making computation possible of the high-speed steel hardness based solely on the steel chemical composition and its heat treatment parameters, i.e., austenitizing- and tempering temperatures. In this case results of own work on the effect of alloy elements on the secondary hardness effect were used, as well as data contained in catalogues and pertinent standards regarding the high-speed steels. In the second case - high-speed steels fracture toughness, the neural network model was developed, making it possible to compute the KIc factor based on the steel chemical composition and its heat treatment parameters. The developed material models were used for designing the chemical compositions if the new high-speed steel, demonstrating the desired properties, i.e., hardness and fracture toughness. Methodology was developed to this end, employing the evolutionary algorithms, multicriteria optimisation of the high-speed steels chemical composition. Findings: Results of the research carried out confirmed the assumption that using the data from catalogues and from standards is possible, which - would supplement the set of data indispensable to develop the assumed model - improving in this way its adequacy and versatility. Practical implications: Solutions presented in the work, based on using the adequate material models may feature an interesting alternative in designing of the new materials with the required properties. The practical aspect has to be noted, resulting form the developed models, which may successfully replace the above mentioned technological investigations, consisting in one time selection of the chemical composition and heat treatment parameters and experimental verification of the newly developed materials to check of its properties meet the requirements. Originality/value: The presented approach to new materials design, being the new materials design philosophy, assumes the maximum possible limitation of carrying out the indispensable experiments, to take advantage of the existing experimental knowledge resources in the form of databases and most effective computer science tools, including neural networks and evolutionary algorithms. It should be indicated that the materials science knowledge, pertaining oftentimes to the multi-aspect classic problems and described, or - rather - saved in the existing, broadly speaking, databases, features the invaluable source of information which may be used for discovery of the unknown so far relationships describing the material structure - properties relations.