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Number of results: 10
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Abstract

Secondary or multiple remelted alloys are common materials used in foundries. For secondary (recycled) Al-Si-Cu alloys, the major problem is the increased iron presence. Iron is the most common impurity and with presence of other elements in alloy creates the intermetallic compounds, which may negatively affect the structure. The paper deals with effect of multiple remelting on the microstructure of the AlS9iCu3 alloy with increased iron content to about 1.4 wt. %. The evaluation of the microstructure is focused on the morphology of iron-base intermetallic phases in caste state, after the heat treatment (T5) and after natural aging. The occurrence of the sludge phases was also observed. From the obtained results can be concluded that the multiple remelting leads to change of chemical composition, changes in the final microstructure and also increases sludge phases formation. The use of heat treatment T5 led to a positive change of microstructure, while the effect of natural aging is beneficial only to the 3rd remelting.

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Authors and Affiliations

M. Matejka
D. Bolibruchová
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Abstract

The paper deals with influence of multiple remelting on AlSi9Cu3 alloy with higher iron content on chosen mechanical properties. Multiple remelting may in various ways influence mechanical, foundry properties, gas saturation, shrinkage cavity, fluidity etc. of alloy. Higher presence of iron in Al-Si cast alloys is common problem mainly in secondary (recycled) aluminium alloys. In Al-Si alloy the iron is the most common impurity and with presence of other elements in alloy creates the intermetallic compounds, which decreases mechanical properties. Iron in the used alloy was increased to about 1.4 wt. %, so that the influence of increased iron content can be investigated. In the paper, the effect of multiple remelting is evaluated with respect to the resulting mechanical properties in cast state, after the heat treatment (T5) and after natural aging. From the obtained results it can be concluded that the multiple remelting leads to change of chemical composition and affect the mechanical properties.
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Authors and Affiliations

M. Matejka
D. Bolibruchová
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Abstract

In the present paper .nite-dimensional, stationary dynamical control systems described by semilinear ordinary di.erential state equations with multiple point delays in control are considered. In.nite-dimensional semilinear stationary dynamical control systems with single point delay in the control are also discussed. Using a generalized open mapping theorem, su.cient conditions for constrained local relative controllability are formulated and proved. It is generally assumed, that the values of admissible controls are in a convex and closed cone with vertex at zero. Some remarks and comments on the existing results for controllability of nonlinear dynamical systems are also presented.

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Authors and Affiliations

J. Klamka
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Abstract

Vapors of benzene and its derivatives are harmful and toxic for human beings and natural environment. Their detection has fundamental importance. For this purpose authors propose surface acoustic wave (SAW) sensor with skeletonized layer deposited by Langmuir-Blodgett (L-B) method. This layer was obtained by depositing a binary equimolar mixture of 5-[[1,3-dioxo-3-[4-(1-oxooctadecyl) phenyl]propyl]amino]–1,3–benzenedicarboxylic acid with cetylamine. The skeletonized sensor layer has been obtained by removing cetylamine. Response of this sensor depends mainly of the electrical dipole momentum of molecule. Among the tested compounds, benzene has a zero dipole moment and gives the smallest sensor response, and nitrobenzene has the largest dipole moment and the sensor reacts most strongly to its vapor.
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Authors and Affiliations

Andrzej Balcerzak
1
Piotr Kiełczyński
1
Marek Szalewski
1
Krzysztof Wieja
1

  1. Institute of Fundamental Technological Research Polish Academy of Sciences Warsaw, Poland
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Abstract

The Convolutional Neural Network (CNN) model is one of the most effective models for load forecasting with hyperparameters which can be used not only to determine the CNN structure and but also to train the CNN model. This paper proposes a framework for Grid Search hyperparameters of the CNN model. In a training process, the optimal models will specify conditions that satisfy requirement for minimum of accuracy scores of Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE). In the testing process, these optimal models will be used to evaluate the results along with all other ones. The results indicated that the optimal models have accuracy scores near the minimum values. Load demand data of Queensland (Australia) and Ho Chi Minh City (Vietnam) were utilized to verify the accuracy and reliability of the Grid Search framework.
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Bibliography

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[3] Raza M.Q., Khosravi A., A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings, Renew. Sustain. Energy Rev., vol. 50, pp. 1352–1372 (2015).
[4] Walther J., Spanier D., Panten N., Abele E., Very short-term load forecasting on factory level – A machine learning approach, Procedia CIRP, vol. 80, pp. 705–710 (2019).
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Authors and Affiliations

Thanh Ngoc Tran
1

  1. Faculty of Electrical Engineering Technology, Industrial University of Ho Chi Minh City, 12 Nguyen Van Bao, Ward 4, Go Vap District, Ho Chi Minh City, Vietnam
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Abstract

A machine learning model was developed to support irrigation decisions. The field research was conducted on ‘Gala’ apple trees. For each week during the growing seasons (2009–2013), the following parameters were determined: precipitation, evapotranspiration (Penman–Monteith formula), crop (apple) evapotranspiration, climatic water balance, crop (apple) water balance (AWB), cumulative climatic water balance (determined weekly, ΣCWB), cumulative apple water balance (ΣAWB), week number from full bloom, and nominal classification variable: irrigation, no irrigation. Statistical analyses were performed with the use of the WEKA 3.9 application software. The attribute evaluator was performed using Correlation Attribute Eval with the Ranker Search Method. Due to its highest accuracy, the final analyses were performed using the WEKA classifier package with the J48graft algorithm. For each of the analysed growing seasons, different correlations were found between the water balance determined for apple trees and the actual water balance of the soil layer (10–30 cm). The model made correct decisions in 76.7% of the instances when watering was needed and in 87.7% of the instances when watering was not needed. The root of the classification tree was the AWB determined for individual weeks of the growing season. The high places in the tree hierarchy were occupied by the nodes defining the elapsed time of the growing season, the values of ΣCWB and ΣAWB.
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Authors and Affiliations

Waldemar Treder
1
ORCID: ORCID
Krzysztof Klamkowski
1
ORCID: ORCID
Katarzyna Wójcik
1
ORCID: ORCID
Anna Tryngiel-Gać
1
ORCID: ORCID

  1. National Institute of Horticultural Research, Konstytucji 3 Maja St, 1/3, 96-100 Skierniewice, Poland
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Abstract

The paper presents the results of research on the production and application of sintered copper matrix composite reinforced with titaniumcopper intermetallic phases. Cu- Ti composites were fabricated by powder metallurgy. The starting materials for obtaining the sintered composites were commercial powders of copper and titanium. Experiments were carried out on specimens containing 2.5, 5, 7.5 and 10 % of titanium by weight. Finished powders mixtures containing appropriate quantities of titanium were subjected to single pressing with a hydraulic press at a compaction pressure of 620 MPa. Obtained samples were subjected to sintering process at 880 °C in an atmosphere of dissociated ammonia. The sintering time was 6 hours. The introduction of titanium into copper resulted in the formation of many particles containing intermetallic phases. The obtained sinters were subjected to hardness, density and electrical conductivity measurements. Observations of the microstructure on metallographic specimens made from the sintered compacts were also performed using a optical microscope. An analysis of the chemical composition (EDS) of the obtained composites was also performed using a scanning electron microscope. Microstructural investigations by scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) showed that after 6 hours of sintering at 880°C intermetallic compounds: TiCu, TiCu2, TiCu4, Ti2Cu3, Ti3Cu4 were formed. The hardness increased in comparison with a sample made of pure copper whereas density and electrical conductivity decreased. The aim of this work was to fabricate copper matrix composites reinforced with titanium particles containing copper- titanium intermetallic phases using powder metallurgy technology and determine the influence of the titanium particles on the properties of the sintered compacts and, finally, analyse the potentials application for friction materials or electric motors brushes.

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Authors and Affiliations

M. Kargul
ORCID: ORCID
M. Konieczny
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Abstract

The goal of this article is to application of non-silica sands based on alumininosilicates as an alternative of traditionally used chromite sand for alloyed steel and iron castings. Basic parameters as bulk density, pH value of water suspension, refractoriness, grain shape of the testing sands were evaluated. Also mechanical properties of furan no-bake moulding mixtures with testing sand were determined. Finally, the influence of non-silica sand on casting quality was evaluated via semi-scale under normal casting production for sand characterization Optimization of production process and production costs were described.

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Authors and Affiliations

J. Beňo
M. Poręba
ORCID: ORCID
T. Bajer

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