The free piston engine linear generator (FPELG) is a simple engine structure with few components, making it a promising power generation system. However, because the engine works without a crankshaft, the handling of the piston motion control (PMC) is the main challenge influencing the stability and performance of FPELGs. In this article, the optimal operating parameters of FPELG for maximising engine performance and reducing exhaust gas emissions were studied. Moreover, the influence of adding hydrogen (H2) to compressed natural gas (CNG) fuel on FPELG performance was investigated. The influence of operating parameters on in-cylinder pressure was also analysed. The single-piston FPELG fuelled by CNG blended with H2 was used to run the experiments. The response surface methodology (RSM), including the central composite design (CCD), was used. Then, adequacy models were developed and verified by ANOVA. Three independent factors on seven responses were utilised for optimisation. Results showed that the optimal operating conditions of lambda, ignition velocity, and injection position were 0.96, 0.53 m/s, and 14.9 mm, respectively. The best-predicted values were as follows: indicated mean effective pressure (IMEP) of 7.6 bar, in-cylinder pressure of 27.87 bar, combustion efficiency of 39.64%, CO of 9531.41 ppm, CO2 of 2.4%, HC of 551.75 ppm, and NOX of 113.737 ppm. Furthermore, results showed that the experimental data could be fitted well with the predicted quadratic model.
The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
... Show MoreIn this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method
Eight different Dichloro(bis{2-[1-(4-R-phenyl)-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})iron(II) compounds, 2–9, have been synthesised and characterised, where group R=CH3 (L2), OCH3 (L3), COOH (L4), F (L5), Cl (L6), CN (L7), H (L8) and CF3 (L9). The single crystal X-ray structure was determined for the L3 which was complemented with Density Functional Theory calculations for all complexes. The structure exhibits a distorted octahedral geometry, with the two triazole ligands coordinated to the iron centre positioned in the equatorial plane and the two chloro atoms in the axial positions. The values of the FeII/III redox couple, observed at ca. −0.3 V versus Fc/ Fc+ for complexes 2–9, varied over a very small potential range of 0.05 V.
... Show MoreAbstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.
The game of basketball (orange ball) is considered one of the fast and exciting games in the world. It is played by both sexes and different ages. It has Olympic and international championships and has various performance skills, including defensive ones. This game requires physical abilities that players must have for duties during matches, including special endurance that is compatible with... The peculiarity of the game is the changing rhythm and positions on the field. The importance of the research lies in the importance of special exercises to develop special endurance and its role in influencing the defensive skill performance of the players throughout the duration of the match.The problem of the research appeared in the decline in i
... Show MoreThe eaction of 2 4 .6-trihydroxyactophenonemonohydra1e with
l hydr.azine monohydrate was realized ti·nder reflu.(( in methanol and i:l.
Jew drops of glacial acetic acid we.re added to give lhe'(int rmediate)
2-(1hydr pno-ctbyt)-benzcne-·1.3.5-r:Qql, which reacted wittl
saEcy.laldehyde. jn methm)ql to gjy;e 'a new :tyRe CNzOi) Ligand (H:flL]
f(2-{1-[(2-=bydroxy-bertzylide·ne)-bydrazqoo,J-e·thy.1}bcnze·neJ ;3·,5
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New Schiff base [3-(3-acetylthioureido)pyrazine-2-carboxylic acid][L] has been prepared through 2 stages, the chloro acetyl chloride has been reacting with the ammonium thiocyanate in the initial phase for producing precursor [A], after that [A] has been reacting with the 3-amino pyrazine-2-carboxilic acid to provide a novel bidentate ligand [L], such ligand [L] has been reacting with certain metal ions in the Mn(II), VO(II), Ni(II), Co(II), Zn(II), Cu(II), Hg(II), and Cd(II) for providing series of new metal complexes regarding general molecular formula [M(L)2XY], in which; VO(II); X=SO4,Y=0, Co(II), Mn(II), Cu(II), Ni(II), Cd(II), Zn(II), and Hg(II); Y=Cl, X=Cl. Also, all the compounds were characterized through spectroscopic techniques [
... Show MoreSchiff base (methyl 6-(2- (4-hydroxyphenyl) -2- (1-phenyl ethyl ideneamino) acetamido) -3, 3-dimethyl-7-oxo-4-thia-1-azabicyclo[3.2.0] heptane-2-carboxylate)Co(II), Ni(II), Cu (II), Zn (II), and Hg(II)] ions were employed to make certain complexes. Metal analysis M percent, elemental chemical analysis (C.H.N.S), and other standard physico-chemical methods were used. Magnetic susceptibility, conductometric measurements, FT-IR and UV-visible Spectra were used to identified. Theoretical treatment of the generated complexes in the gas phase was performed using the (hyperchem-8.07) program for molecular mechanics and semi-empirical computations. The (PM3) approach was used to determine the heat of formation (ΔH˚f), binding energy (ΔEb), an
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