Design and Manufacturing of Smart Braking System

Now a days, vehicles have been developed a lot and reach its new margin; but yet accidents are mostly occurred by retard of the driver to stomp the brake or by the sloppiness of the driver or over speed or due to unpleasant weather. So our project points to emerge a system which can actuate the braking system automatically with the aid of high profile sensors with relay circuit and some more changes in conventional braking system which can actuate the brake automatically in emergency state. The brain of this entire set-up is Arduino microcontroller. The ultrasonic sensors are the vision of this system and stepper motor utilised for actuation. This system has been composed to depict the technological improvement in further. In future the actual model may be evolved based on its viability

Exploring the Possibilities of Producing Pulp and Paper from Discarded Lignocellulosic Fibers

The main objective of this work was to explore the prospects of producing pulp and paper from leftover lignocellulosic fibers. In this study discarded Cocos nucifera fibers were collected from an abandoned site and were washed thoroughly. FTIR analysis, chemical composition and fiber morphology studies were conducted. FTIR showed the presence of holocellulose and lignin in the fibers. Chemical analysis showed the holocellulose content as 37.8 wt%. Fiber length, fiber diameter, lumen diameter and cell wall thickness were observed using microscope and derived fiber indices that determine the possibility of producing paper were evaluated. The derived indices such as Runkel index, slenderness ratio, co-efficient of rigidity, flexibility co-efficient, Luce’s shape factor and Solids factor of the fibers were evaluated as 67.9%, 44.11, 58.83%, 0.199, 0.49 and 278.53x103 respectively. All these indices are in good agreement with fibers recommended and used for pulp and paper production. High lignin content present in the fibers is a limitation and it can be removed through appropriate delignification techniques. Thus the study showed that discarded fibers can be used for producing pulp, paper and allied products

Wear behaviour of aluminium alloy 5083/SiC/fly ash inoculants based functional composites – optimization studies

The wear characteristics of Aluminium AA 5083/SiC/Fly Ash functional composites under different load conditions are an important aspect to assess the inoculation of Fly Ash for enhancing the functionality of the aluminium composites with respect to its tribological behaviour and its influence on wear properties. The present work is majorly aimed at the development of AA 5083/SiC functional composites inoculated with Fly Ash using stir casting method for different blends of the reinforcements (2.5, 5 & 7.5 wt%). The novelty of this research is majorly attributed to the incorporation of functional inoculants in the form of Fly Ash, which along with the SiC is bound to influence the tribological characteristics of the composites. The wear characteristics of these fabricated composites have been investigated considering various process parameters viz., the load, sliding distance, sliding velocity, wt% of SiC and wt% of Fly Ash, based on the operational requirements of the composites in real time considered from the earlier research studies and the influence of each parameter on the wear rate is discussed. Based on the different wear regimes obtained after characterization of the samples at different load conditions, Analysis of Variance (ANOVA) is carried out for each blend of the samples to statistically validate the experimental outcomes. The results have given sufficient substantiation to the fact that wear rate decreases with the inoculation. The wear rate and coefficient of friction (COF) is minimum viz., 0.00095 mm ^3 /m, and 0.301 respectively for L9 experimental trial, i.e., for the composite specimens synthesized by reinforcing 7.5 wt% SiC, and 7.5 wt% Fly Ash for a load of 20 N, sliding velocity of 6 m s ^−1 , and a sliding distance of 3000 m. The results have conferred that micro segregation (coring) of SiC and uniform dispersion of Fly Ash in the matrix enhances its tribological characteristics

Short-Term Power Prediction of Building Integrated Photovoltaic (BIPV) System Based on Machine Learning Algorithms

One of the biggest challenges is towards ensuring large-scale integration of photovoltaic systems into buildings. This work is aimed at presenting a building integrated photovoltaic system power prediction concerning the building’s various orientations based on the machine learning data science tools. The proposed prediction methodology comprises a data quality stage, machine learning algorithm, weather clustering assessment, and an accuracy assessment. The results showed that the application of linear regression coefficients to the forecast outputs of the developed photovoltaic power generation neural network improved the PV power generation’s forecast output. The final model resulted from accurate forecasts, exhibiting a root mean square error of 4.42% in NN, 16.86% in QSVM, and 8.76% in TREE. The results are presented with the building facade and roof application such as flat roof, south façade, east façade, and west façade

Large-Scale Non-Targeted Metabolomics Reveals Antioxidant, Nutraceutical and Therapeutic Potentials of Sorghum

Sorghum is one of the most important food and feed cereal crops and has been gaining industrial importance in recent years for its biofuel, nutraceutical and antioxidant values. A genetic profile variation study was undertaken for the accumulation of phytochemicals in 61 diverse sorghum accessions differing in their growth habitat and grain color through non-targeted Gas Chromatography–Mass Spectrometry (GC-MS/MS) analysis. Mass Spectrometry–Data Independent AnaLysis (MS-DIAL) and MetaboAnalyst identified 221 metabolites belonging to 27 different phytochemicals. Tropical and temperate sorghums were distinct in their metabolic profiles with minimum overlaps, and 51 different metabolites were crucial in differentiating the two groups. Temperate sorghums had the ability to accumulate more of phenolic acids, phytosterols, flavonoids, carotenoids, and tropical sorghums for stress-related amino acids, sugars and fatty acids. Grain-color-based Partial Least Square–Discriminant Analysis (PLS-DA) analysis identified 94 Variable Importance in Projections (VIP) metabolites containing majority of flavonoids, phenylpropanoids and phytosterols. This study identified two sorghum lines (IS 7748 and IS 14861) with rich amounts of antioxidants (catechins and epicatechins) belonging to the group of condensed tannins that otherwise do not accumulate commonly in sorghum. Out of 13 metabolic pathways identified, flavonoid biosynthesis showed the highest expression. This study provided new opportunities for developing biofortified sorghum with enhanced nutraceutical and therapeutics through molecular breeding and metabolic engineering