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1

Prediction of flyrock distance induced by blasting using particle swarm optimization and multiple regression analysis: an engineering perspective

Chen Yong, Wang Minghua, Yin Heng, Zhang Tianbao

Acta Geophysica

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2024

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Vol. 72, no. 1

287--301

EN

Flyrock is one of the major safety hazards induced by blasting operations. However, few studies were for predicting blasting-induced flyrock distance from the perspective of engineers. The present paper attempts to provide an engineer-friendly equation predicting blasting-induced flyrock distance. Data used in the present study contains s seven blasting parameters including borehole diameter, blasthole length, powder factor, stemming length, maximum charge per delay, burden, and flyrock distance is obtained. Data is inputted into Random Forest for feature selection. The selected features are formulated as two candidate equations, including Multiple Linear Regression (MLR) equation and Multiple Nonlinear Regression (MNR) equation. Those two candidates are respectively referred by Particle Swarm Optimization for searching optimum values for the coefficients of selected features. It is proved that MLR equation has better accuracy. MLR equation is compared with two empirical equations and the MLR equation based on least squares method. It is found that the coefficient of correlation of the proposed MLR equation reaches 0.918, which is the highest compared with the scores of other three equations. The present study utilizes feature selection process to screen inputs, which effectively excludes irrelevant parameters from being considered. Plus the contribution of Particle Swarm Optimization, the accuracy of the obtained equation can be guaranteed.

2

Analiza statystyczna właściwości mechanicznych mieszanek trójskładnikowych betonów o dużej wytrzymałości

Robinson J., Srisanthi V. G.

Cement Wapno Beton

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2022

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R. 27, nr 6

386--402

PL

Rosnące zapotrzebowanie na beton o dużej wytrzymałości [BDW] w budownictwie zwiększa zużycie cementu, co powoduje problemy środowiskowe. Ostatnie badania wykazują, że wykorzystanie materiałów cementowych w betonie może skutecznie zmniejszyć objętość cementu. W niniejszej pracy przygotowano trójskładnikowe mieszanki cementu, krzemionki i popiołu lotnego w celu uzyskania BDW. W tym przypadku cement został częściowo zastąpiony odpowiednio: pyłem krzemionkowym - 0, 2,5, 5, 7,5 i 10% oraz popiołem lotnym - 0, 5, 10 i 15%. W celu określenia kompatybilności zaczynu cementowego z super-plastyfikatorem opartym na eterze polikarboksylanowym [PCE], przeprowadzono badanie metodą mini stożka opadowego. Obliczono gęstość ziaren kruszyw w celu zmniejszenia porów i poprawy rozmieszczenia cząstek w BDW. Przeprowadzono badania doświadczalne i uzyskano ostateczną wytrzymałość na ściskanie 71,55 MPa, po 28 dniach twardnienia. Badania mikrostruktury przeprowadzono przy użyciu skaningowego mikroskopu elektronowego i spektroskopii rentgenowskiej z dyspersją energii, aby poznać podstawowy mechanizm i udział składników chemicznych wpływających na zmianę właściwości mieszanki w różnych etapach. Przeprowadzono analizę regresji wielokrotnej [ARW] w celu symulacji projektu mieszanki, aby wspomóc przewidywanie wytrzymałości na ściskanie betonu o dużej wytrzymałości.

EN

The growing demand for high strength concrete [HSC] in the construction industry increases the usage of cement, resulting in environmental issues. Recent studies are showing that the utilization of cementitious materials in concrete can effectively reduce the volume of cement. In the present study, ternary blended combinations were prepared using cement, silica fume, and fly ash to attain the HSC. Here, cement was partially replaced by silica fume [2.5, 5, 7.5, and 10%] and fly ash [5, 10, and 15%], respectively. Mini slump cone test was conducted to identify the compatibility of cement paste with polycarboxylate ether [PCE] based superplasticizer. The packing density of aggregates was calculated to reduce the voids and improve the particle distribution in HSC. An experimental investigation was carried out, and the ultimate compressive strength was obtained as 71.55 MPa at 28 days of curing. Multi linear regression analysis was conducted to simulate the mix design for aiding the prediction of compressive strength of the HSC.

3

Multiple regression analysis predicts the dynamic of chondrocytes stimulated by magnetic and electric fields

Vaca-Gonzalez Juan Jairo, Escobar Juan Felipe, Garzon-Alvarado Diego Alexander

Acta of Bioengineering and Biomechanics

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2021

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Vol. 23, no. 3

109--124

EN

Purpose: The aim of this study was to implement a multiple regression analysis to find mathematical models that estimate the proliferative rate and the molecular synthesis of chondrocytes when these cells are stimulated either by magnetic or electric fields. Methods: Data derived from previous studies performed in our laboratory were used for statistical analyses, which consisted of applying magnetic fields (1 and 2 mT) and electric fields (4 and 8 mV/cm) to chondrocytes. Data from cell proliferation and glycosaminoglycan expression were used to adjust and to validate each mathematical model. Results: The root square model efficiently predicted the chondrocyte dynamics, evidencing determination coefficients of R2 = 92.04 for proliferation and R2 = 70.95 for glycosaminoglycans when magnetic fields were applied, and R2 = 88.19 for proliferation and R2 = 74.79 for glycosaminoglycans when electric fields were applied. Conclusions: The reduced, interactive, quadratic and combined models exhibited lower R2 values, nevertheless, they were useful to predict proliferation and glycosaminoglycan synthesis, as the right-skewed distribution, determined by the F parameter, evidenced a Frejected < Fcomputed. The models are efficient since the prediction of chondrocyte dynamics is comparable to the cell growth and to the molecular synthesis observed experimentally. This novel formulation may be dynamic because the variables that fit the models may be modified to improve in vitro procedures focused on cartilage recovery.

4

Badania mikronizacji węgla kamiennego w młynie elektromagnetycznym

Micorek T., Rejdak M., Robak J., Różycki G.

Piece Przemysłowe & Kotły

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2016

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Nr 4

27--33

PL

Energetyczne wykorzystanie odpadów może przynieść wiele korzyści środowiskowych przy dodatnim efekcie finansowym. Głównymi wyzwaniami technologicznymi, związanymi z przeróbką odpadów na paliwo, są: odseparowanie frakcji niepalnych oraz wysoko chlorowanych, rozdrobnienie oraz homogenizacja. Wytworzone paliwo powinno charakteryzować się parametrami spełniającymi kryteria ustanowione przez Europejski Komitet Normalizacyjny (CEN). Technologia energetycznego wykorzystania paliwa typu SRF (Solid Recovered Fuel) determinuje wymogi dotyczące właściwości fizykochemicznych oraz użytkowych paliwa, a tym samym decyduje o wyborze technologii jego przygotowania.

EN

The paper presents the results of the test of wet grinding of coal with use of electromagnetic mill. The tests were carried out in a batch system at different initial grain sizes of raw material, various coal concentrations in the feed and the various milling times. Based on the multiple regression analysis of the obtained data, it can be concluded that the efficiency of coal grinding wit use of electromagnetic mill depends on the residence time of the particles in the mill working chamber and a solid phase concentration in the feed directed to the process.

5

Regressional Estimation of Cotton Sirospun Yarn Properties from Fibre Properties

Bedez Üte T., Kadoğlu H.

Autex Research Journal

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2014

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Vol. 14, no. 3

161--167

EN

In this paper, it is aimed at determining the equations and models for estimating the sirospun yarn quality characteristics from the yarn production parameters and cotton fibre properties, which are focused on fibre bundle measurements represented by HVI (high volume instrument). For this purpose, a total of 270 sirospun yarn samples were produced on the same ring spinning machine under the same conditions at Ege University, by using 11 different cotton blends and three different strand spacing settings, in four different yarn counts and in three different twist coefficients. The sirospun yarn and cotton fibre property interactions were investigated by correlation analysis. For the prediction of yarn quality characteristics, multivariate linear regression methods were performed. As a result of the study, equations were generated for the prediction of yarn tenacity, breaking elongation, unevenness and hairiness by using fibre and yarn properties. After the goodness of fit statistics, very large determination coefficients (R2 and adjusted R2) were observed.

6

Zastosowanie analizy regresji wielokrotnej do oceny rangi ważności parametrów układów maszynowych

Łuszczyna R.

Zeszyty Naukowe. Mechanika / Politechnika Opolska

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2010

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z. 96

61-62

EN

This paper presents new complex method of numerical optimization of mechanical systems. Presented a new approach of application of multiple regression and logical decision trees in investigations of importance rank of constructional and service parameters.

7

Złożone zmienne niezależne w modelach pogoda - plon

Rozbicki T.

Przegląd Naukowy Inżynieria i Kształtowanie Środowiska

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2007

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Vol. 16, No. 2

3--10

EN

The relationships between the yield and meteorological elements have been stated by the use of multiple regression model selection. Winter wheat yield was taken as dependent variable and three groups of meteorological elements were taken as independent variables. Simple meteorological elements belong to the first group of independent variables; their nonlinear combinations (square, square root) belong to the second group. The third group has included complex elements they are functions basing on the relationships between plant growing and environmental conditions among others meteorological conditions. Stations Sulejów has been the source of longterm meteorological, phonological and winter wheat yield data. The station is situated in central part of Poland and winter wheat is grown on medium type of soil. The regression equations including both simple meteorological elements, their nonlinear combinations and complex variables achieves the best statistical characteristics than the equations including simple elements only.