Acrylonitrile–butadiene–styrene (ABS) is a very significant and widely used amorphous thermoplastic which, on account of its importance in industry, multiplied billions of dollars are spent yearly in the United States alone, not to talk of the rest of the world. It is primarily utilized in industry and domestic situations due to its high damage resistance properties. This fact makes it a required exercise for serious and thorough research in this area to go ahead. In this article, the tension, compression, and bending response behavior of ABS material under various strain rate levels tests were investigated. Its characterization under tensile, compression, and other mechanical testing is thus quite important, to elicit ways of enhancing properties that would make the material or structures made from it, better in service. In the current phase, tension, compression, shear, and flexural samples were tested, because it is of interest to know how the longitudinal and shear loading damages propagate through the specimen length and thickness, and how the microstructure is affected from point to point, both laterally and depth-wise. The issues of energy transfer and dissipation are significant in terms of the effectiveness of this material as a damage retarder. Mat_187 nonlinear material model in Ls-Dyna was utilized to numerically evaluate the behavior of ABS under tension, compression, and three-point bending. The experimental results compared favorably to the numerical results.

In this paper, the impact of different input variables on the performance and emission features of a pongamia pinnata and rapeseed oil biodiesel with n-Butanol additive were investigated, statistically analyzed, and optimized by employing the powerful response surface methodology (RSM) based design of experiment (DOE) techniques. The vegetable oils (pongamia pinnata and rapeseed oils) were transesterified and their corresponding methyl esters were blended with diesel and n-Butanol at blend ratios 10:84:6, 10:78:12, 20:74:6 and 20:68:12. The samples were tested on a direct injection CI engine at a rated speed of 1500 rpm and standard CR of 17.5:1 at different loads. In each test, performance and emission parameters were measured. Expert machine learning (ML) methods were used to forecast these features. In addition, polynomial equations were developed for each blend using regression techniques and compared with an artificial intelligence technique. It was observed that the engine performance increased as biodiesel and additive weight percentage increased. Regardless of the loads placed on the engine and the blend ratios, the use of PPME and RSME combined with n-Butanol blends demonstrated a clear decrease in NOx compared to diesel (7.07% for P20B12 and 6.58% for R20B12). As per the trend, it is seen that the percentage reduction in CO₂ emissions is greater with high percentage increase of n-Butanol in the tested sample irrespective of loads applied on the engine (2.95% more P20B12 for as compared to P20B6). For the emission characteristics, ANN demonstrated a range of 87.92% to 98.83% prediction accuracy while that of regression varies from 81.4% to 98.8% for all the samples of PPME blended biodiesel.

Nowadays the trend toward the use of transportation technologies which are clean and less dependent on fossil fuel is highly increased. That is because of the fast depletion of oil reserves in the world, on the other hand the growth of developing nations into industrialized one’s will increase...

Nematicons upgrade the recognition of light localization in the reorientation of non-local media. the current research employs a powerful integral scheme using a different procedure, namely, the modified simple equation method (MSEM), to analyze nematicons in liquid crystals from the controlling model. The expanded MSEM is investigated to enlarge the applicability of the standard one. The suggested expansion depends on merging the MSEM and the ansatz method. The new generalized nonlinear n-times quadruple power law is included. With the aid of the symbolic computational package Mathematica, new explicit complex hyperbolic, periodic, and more exact spatial soliton solutions are derived. Moreover, the related existence constraints are obtained. To show the dynamical properties of some of the obtained nematicons, three-dimensional profiles with corresponding contours are depicted with the choice of appropriate values of arbitrary parameters. The fractional impacts in various applicable senses are analyzed to investigate the generality of the considered model.

This manuscript presents a fault detection method for a SI engine at variable speeds using acoustic signal technique. Two faults were addressed: misfire and the malfunction of manifold absolute pressure (MAP) sensor. The main objective is to detect these two faults by measuring the sound pressure level (SPL) in decibels (dBA) at different engine speeds and one octave frequency bands in the audible human range, and then compare the results to the normal operating SPL engine. The experiments were conducted using a four cylinder, four stroke spark ignition Mitsubishi Lancer sedan engine (1.6 L) model 2006. The experimental results showed that: 1) the SPL due to misfire malfunction increases as the engine speed decreases; 2) at low frequencies the difference between the two values of SPL is very small compared at high frequencies; 3) the curve shape for SPL follows the shape of the power produced from the engine.