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Drilling operation of fiber reinforced polymeric (FRP) composites is significantly dissimilar from conventional drilling operation of metals; hence, identification of optimum drilling process param...

This work presents the feasibility study of utilizing neat plastic oil TiO $$_2$$ nanoparticle is added as additive in the proportion of 100, 150, and 200 ppm fuelled in a stationary single cylinder diesel engine to asses the performance, emission and combustion characteristics. From the local municipality, the waste plastic bottles are collected and it it fed into the pyrolysis reactor to convert into pyrolysis oil. The results from performance analysis revealed that the enrichment of neat plastic with TiO $$_2$$ nanoparticle enhanced the brake thermal efficiency than without any additives in the raw oil (plastic oil). Similarly, the results of emission revealed that smoke, and hydrocarbon are considerably reduced with increased proportion of nano additive. Results also revealed that the formation of NOx is higher with POAL200 than plastic oil and other concentration of TiO $$_2$$ nanoparticle and diesel fuel. This is due to the higher availability of oxygen content in the fuel, higher quality of fuel and reduced ignition delay.

The demand for precision machining process and sophisticated fabrication methods is increased due to the wide application of glass fiber reinforced polymer (GFRP) composites in various industries such as aerospace, defense, automobile, construction and railways etc. Identification of optimum drilling process parameters for GFRP composites has become mandatory because drilling operation of GFRP composites is significantly dissimilar from conventional drilling operation of metals. In this present work, three drilling parameters such as drill bit point angle, feed rate, and spindle speed were optimized using teaching learning based optimization (TLBO) algorithm for GFRP composite with 30% fiber volume fraction. The optimization study was carried out based on four output responses namely, thrust force, torque, delamination factor, and surface roughness of drilled surface and reported in this article. TLBO results were validated with experimental results.

Alkali treatment of natural fibers will improve the mechanical, chemical, and thermal characteristics of natural fiber reinforced epoxy composites. The influence of alkali treatment on the improvem...

COVID-19 is an epidemic that has been multiplying rapidly across the globe To order to regulate its growth, several nations have implemented home-stay or lockout policies Prolonged domestic residency, though, can cause worse effects such as economic instability, homelessness, food shortages and individuals' mental health issues This article presents an intelligent consumer electronics solution for secure & gradual launch after residence restrictions have been lifted Completely automatic hand sanitizer supplier to prevent quickly spreading novel corona virus It is implemented to restrict the development of new positive cases through auto touch tracking and by promoting critical social distancing

This paper presents a pioneer study of identifying the wind turbine blade condition based on its vibration pattern. The study used variational mode decomposition (VMD) for signal pre-processing. VMD is an adaptive signal decomposition technique, which can non-recursively decompose a multi-component signal into a number of quasi-orthogonal intrinsic mode functions. This new tool is based on a solid mathematical foundation and can obtain a well-defined time–frequency representation. The main advantage of VMD is, there is no residual noise in the modes and it can avoid redundant modes. Thus, VMD provides a noise-free fault signal for classification. Initially, the obtained vibration data are pre-processed using VMD and then the descriptive statistical features like mean, standard deviation, sample variance, and kurtosis were extracted. After the feature extraction, the dominant features were selected using the C4.5 decision tree algorithm. In this study, multilayer perceptron (MLP) was used for fault classification (blade bend, blade crack, erosion, hub-blade loose connection, and pitch angle twist). Then a comparative study was made with MLP without VMD and MLP with VMD to suggest a better model. From the results, the maximum classification accuracy of 87% was obtained for MLP with VMD when compared to MLP without VMD (76.83%).

Energy modeling in Smart Buildings (SB) and planning and operating the generation of power based on the information extracted are key components of the Smart Grid’s (SG’s) energy management system. In the world, buildings use a significant amount of energy that contributes to energy efficiency programs. Additionally, excessive utilization power generation appliance also including air conditioners and heater, breathing, and climate control (HVAC) units, improper microclimate control, and inappropriate start-up and ordering of power equipment waste a lot of heat pumps. The utility can mitigate energy generation costs when it anticipates electrical loads and schedules generation resources in accordance with the demand. To estimate electricity usage at varying tiers of utility grid systems, a range of techniques have already been used. The goal of this study will be to create a hybrid deep learning model can predict resource utilization in infrastructures. Model building and data cleaning are the two stages of the proposed framework. Data cleaning involves pre-processing techniques and adding additional lag values to raw data. This hybrid deep learning (DL) approach is made up of a series of completely connected layered and linear Long Short-Term Memory (LSTM) sections layered over bi-directional Long Short-Term Memory (LSTM) components and is based also on collected information. You could incorporate the dependence structure of electricity usage on regressors and increase computation efficiency, training time, as well as computational complexity by using the results obtained.

A micromechanically motivated uniaxial model with least number of state variables is presented in this paper to capture nonlinear hysteresis behavior of polycrystalline magnetostrictive materials, in particular Galfenol, with rate effects. This model is formulated based on the classical thermodynamic framework and relies on the domain rotation phenomenon occurring at the microscopic level. The macroscopically averaged domain rotation events are considered as the material state variables. The driving force required for the transformation of one state variable into another is extracted from the derived dissipation inequality equations. A special case, wherein two transformation systems activated simultaneously, is also taken into consideration in the model development. Back fields, accounting in a way the averaged inter-domain and inter-grain effects, are introduced in the proposed model. Rate-dependent effects are also set into the model in a straightforward way without compromising the core idea of this model development, i.e., a simplified approach, yet capturing most of the material responses. Finally, the proposed model, despite the reduced number of state variables, demonstrates its ability to collaborate well with many complex experimental observations of Galfenol reported in the literature.

It is indispensable to enhance the performance of a conventional solar still in order to increase its productivity. It has been effectively done by adding fins and thermal energy storage media to it. In the present work, the performance of a conventional single slope solar still is compared with an identical solar still with square pipes as fins attached to its basin liner. A thin layer of paraffin wax was stored beneath the basin liner as well as in the hollow space present in the square pipe fins as energy storage media. Experiments have been conducted on the conventional still for three different water depths, i.e. for 2, 3 and 4 cms. The masses for the corresponding water depths are 10 kg, 15 kg and 20 kg, respectively. The same water masses were maintained in the modified still, and experiments were conducted for the following cases: with mere fins and with fins cum energy storage media. The percentage increase in the efficiencies of the modified still with mere fins and with fins cum energy storage are observed as 64% and 95%, respectively.

The work analyzes the performance of a solar tunnel dryer for drying four different products (mango slice, citrus, beef, fish) under forced convection by using a DC blower run by a photovoltaic panel (200 w). An experimental setup of solar tunnel dryer has been designed and fabricated. Experiments have been performed during summer season. The system is operated between 30 and 69 °C. The dryer is simple in construction, at a low cost, with locally available materials. The performance of the designed drier is evaluated by carrying drying experiments at Nagercoil, Tamil Nadu, India (8.1700 °N, 77.4300 °E). RSM software was used to investigate estimation of capacity optimization and acceptability using desirability for four different products. The independent variables or responses were time, air temperature, and solar radiation. These researches are applicable to various process industries to analyze the probable utilization in various forms.

The decline in the availability of fossil fuel, increase in cost and the stringent emission norms are the main concerns identified in the automotive sector during the recent years. Biodiesel is one of the hopeful alternate resources for the mineral diesel to address the above-listed problems. In the present investigation, waste chicken fat biodiesel has been prepared and used to investigate the performance features of single cylinder naturally aspired direct injection diesel engine. The waste chicken fat biodiesel is prepared using transesterification process, and the yield is found to be 94.8%. The physicochemical characteristics of the waste chicken fat methyl ester have been tested and found in line with ASTM standards. The blends of waste chicken fat biodiesel with mineral diesel have been prepared and experimented in a single cylinder standard compression ignition diesel engine without any modifications. The combustion, performance and emission characteristics have been studied, and it is found that the blend B20 resulted in higher performance and lesser emissions among the other test fuels.

This investigation deals with an innovative method to improve the efficiency by reducing the fuel consumption and improving the combustion using nano particles and lime steam distilled oil. Lime steam distilled oil is obtained from the peel of Citrus aurantifolia. The characteristics of diesel engine using diesel as a fuel is taken as a benchmark reading and the nanoparticle cerium oxide mix with diesel along with lime steam distilled oil and performance will be compared with varying injection pressures. Grey relational Analysis mainly deals with the objective to "optimize a response which is influenced by several independent variables." Homogeneous combustion catalysts are those additives which are dissolved into diesel fuels homogeneously to play a catalytic role during the combustion process of the engine. Taguchi method is used for the selection of orthogonal array and number of experiments. GRA coefficient is being used to calculate rank and is calculated on the basis of the value of GRA grade. Analysis for variance is used to calculate the percentage of contribution for grey relational analysis

As the fossil fuels reserves are reducing at a faster rate as a result of the population growth and the ensuing energy utilization, in recent years, an urgent need to find renewable alternative fuels has emerged. The danger of global warming and the stringent government regulations have attracted the engine manufacturers and the consumers in improving combustion of fuels and following safer emission norms to save the environment from pollutions and also save fossil fuels for coming population. These limitations have led researchers towards finding alternative sources of energy and ways to improve their combustion for producing energy.in this investigation the experiment was carried out using camelina biodiesel (5%,10%,20%,25%,30%) with addition of silicon oxide as a nano catalyst. camelina biodiesel prepared by transesterification process. Addition of additives lowered the harmful emissions significantly with a trivial increase in NOx emissions to the sample 1 compare with other samples blends.

In-vitro dose response curves were built with 6 MV X-ray for a dose range of 0.1–6 Gy, at a dose rate of 300 cGy/min, using Linear Accelerator (LINAC, SIMENS PRIMUS) for Cytokinesis-Block Micronucleus (CBMN) and Dicentric Chromosome Aberration assay (DCA). The dose response curves constructed up to 6 Gy and also up to 4 Gy using the manual method were compared to those curves obtained with the software program such as CABAS (V.2) and Dose Estimate software (V.5.2). The alpha and beta coefficients for MN and CA obtained for the curves constructed up to 6 Gy showed variation compared to those obtained in dose response curve constructed up to 4 Gy. However, the doses estimated based on these coefficients did not show much variation. The results are discussed in this paper.

This research article highlights the results of analyses conducted to examine the combustion, performance and exhaust emission characteristics of an unmodified diesel engine fueled with a new third generation biodiesel derived from Manilkara zapota seed oil (MZO) and its blends with fossil diesel. Biodiesel was produced by the alkaline catalyst transesterification process using methanol along with KOH as catalyst. Five different test fuels were prepared and tested in a single cylinder direct injection compression ignition engine at a rated speed of 1500 rpm. Test fuel B50 (50% biodiesel + 50% diesel) produced 17% higher brake thermal efficiency and 14.34% reduced brake specific fuel consumption along with a reduction of 34.21% and 4.32% in CO and unburnt hydrocarbon emission respectively as compared to fossil diesel. Although B50 produced 38.91% higher CO2 emission than that of diesel, equivalent amount of CO2 would have been sequestered during the growth of biodiesel plants, keeping the environment balance of CO2 level.

Web query classification, the task of inferring topical categories from a web search query is a non-trivial problem in Information Retrieval domain. The topic categories inferred by a Web query classification system may provide a rich set of features for improving query expansion and web advertising. Conventional methods for Web query classification derive corpus statistics from the web and employ machine-learning techniques to infer Open Directory Project categories. But they suffer from two major drawbacks, the computational overhead to derive corpus statistics and inferring topic categories that are too abstract for semantic discrimination due to polysemy. Concepts too shallow or too deep in the semantic gradient are produced due to the wrong senses of the query terms coalescing with the correct senses. This paper proposes and demonstrates a succinct solution to these problems through a method based on the Tree cut model and Wordnet Thesarus to infer fine-grained topic categories for Web query classification, and also suggests an enhancement to the Tree Cut Model to resolve sense ambiguities.

The people in our society are highly depended on petroleum for their activities. The petroleum is a finite source and it produce several problems such as rising carbon dioxide level in the atmosphere. Around 75% of fuel produced is used for as an energy source for transportation, heat and electricity generation. This study was carried out to understand the effect of fuel injection pressure on the CRDI engine for the performance, combustion and emissions. This work has been done out on a four stroke, single cylinder diesel engine. The fuel injection pressure was varied from 400 bar, 500 bar and 600 bar by having the fuel injection angle as 20°bTDC. The collected data were analysed for various parameters such as brake specific fuel consumption (BSFC), brake thermal efficiency (BTE), CO, CO2, HC, NOxand Smoke emissions for diesel fuel. CO, HC and smoke emissions were reduced by increasing the fuel injection pressure. NO and CO2emissions were increasing by increasing the fuel injection pressure. This is due to injected fuel droplets find smaller as the injection pressure increase, which leads to improve atomization of the fuel. The BTE and SFC were not much varying.

Low productivity is a major issue to be addressed in solar still which is considered to be an economical and viable gadget used to convert brackish water into potable water in remote and rural regions of developing countries. In the present work, an attempt has been made to improve the productivity of solar still by incorporating fins and energy storage materials. Two identical single slope single basin solar stills were fabricated with an effective basin area of 0.5 m2 (1000 mm x 500 mm) and glazing inclination of 120 with the horizontal. Experiments were conducted to compare the performance of conventional solar still with finned solar still attached with paraffin wax as phase change material (PCM). Two different materials; Galvanized iron and Aluminium were used to fabricate the basin and tubular fins. The experimental results showed that the productivity and the daily efficiency of the solar still with fins and energy storage were higher compared to solar still with mere fins and solar still with mere energy storage. Further, solar still with Aluminium fins exhibited superior performance compared to the solar still with galvanized iron fins.

Solar still is a cheap and portable solar distillation system that can purify brackish water into potable water and is ideal for domestics use. Low productivity is a major issue that needs to be addressed in solar stills. In the present work, the efficiency of the fabricated single slope single basin solar still was enhanced by the incorporation of plate fins over the basin liner of the still. The daily productivity was further increased by attaching a latent heat energy storage unit to the still. Paraffin wax was used as phase change material (PCM) in the energy storage unit. Experiments were conducted on modified solar still for the following two cases (i) with mere plate fins and (ii) with plate fins and PCM. A 40.6% increase in productivity was observed for the solar still with mere fins and the productivity is increased by 94.51% for the solar still incorporated with both fins and PCM when compared with that of conventional still.

In this current work, we examine the Hyers-Ulam(H-U) stability results for a finite variable additive functional equation (Ref.[6]) in Intuitionistic Fuzzy Normed space(IFN-space) is discussed by means of direct and fixed point methods.