Neat waste plastic oil (WPO) application as a fuel in engines reduces BTE and increases deleterious emissions of CO, UHC, NOx, and smoke due to the presence of insufficient oxygen and unbreakable hydrocarbon chains in WPO. Present investigation was performed to evaluate the impact of ZnO nanoparticles on the performance and emission characteristics of a diesel engine operated with the waste plastic oil (WPO20) blend. The objective of doping ZnO nanoparticles with WPO20 was to enhance the oxidation reaction and heat transfer rate between fuel droplets during combustion, which aids in completing the combustion. The sol-gel technique was adopted to successfully synthesize the ZnO nanoparticles using zinc acetate (Zn(CH₃CO₂)₂.2H₂O) and sodium hydroxide (NaOH) precursors. The structure and morphology of resulted particles were studied by XRD and FESEM tests. Both results indicate the stable formation of ZnO, and exhibit the crystallinity nature, spherical surface, and size consistency. The synthesized ZnO nanoparticles were infused in WPO20 blend in the amounts of 50, 100, and 150 ppm with the aid of the ultrasonication technique. Engine test was conducted with diesel fuel, WPO20 blend, and nano-infused fuels at a constant speed of 1500 rpm under various loads. The disparities in performance and emission characteristics were examined and compared with pure diesel fuel. The findings demonstrated that adding nanoparticles to WPO20 significantly lowers the smoke, CO, UHC, and NOx emissions and simultaneously improves the BTE and decreases the BSFC of the diesel engine. Optimum results were obtained for 100 ppm concentration of ZnO nanoparticles. Reduction of smoke by 11.86%, CO by 5.7%, UHC by 28%, and NOx by 14.93%, along with the enhancement of BTE by 2.47%, were noticed at maximum load with 100 ppm particles. Based on the test results, it is concluded that ZnO nanoparticles can be used as a suitable additive in WPO blends to improve the overall engine characteristics. Further scope of the present work is to study the effect of organic nanoparticles with WPO on engine behaviour, the detailed combustion of nanoparticles infused WPO, and the nanoparticles doped WPO on engine wear and corrosion.

Due to tamper-resistant sensor nodes and wireless media, Industrial Wireless Sensor Networks (WSNs) are susceptible to various security threats that severely affect industrial/business applications. The survival of sensor networks is highly dependent on the flourishing collaboration of sensor nodes. Trust management schemes seem to be realistic and promising techniques to improve security as well as cooperation (dependability) among sensor nodes by estimating the trust level (score) of individual sensor nodes. This research paper presents a well-organized and motivating secure, dependable trust assessment (SDTS) scheme for industrial WSNs to cope with unexpected behavior such as an on–off attack, bad-mouthing attack, garnished attack, etc., by employing robust trust evaluation components based on success ratio and node misbehaviour. SDTS incorporates an interesting trust evaluation function in which the trust range can be adjusted in accordance with the application requirement. SDTS include direct communication trust, indirect communication trust, data trust, and misbehavior-based trust to defend the multiple internal attacks. SDTS works according to the behavior of nodes, i.e., whether the sensor nodes are interacting frequently or not. Moreover, abnormal attenuation and dynamic slide lengths are incorporated in the proposed model (SDTS) to deal with various natural calamities and internal attacks. SDTS is compared against three recent state-of-the-art methods and found efficient in terms of ease of trust assessment, false-positive rate (2.5%), false-negative rate (2%), attack detection rate (90%), detection accuracy (91%), average energy consumption (0.40 J), and throughput (108 Kbps) under the load of 500 sensor nodes with 50% malicious nodes. Investigational results exhibit the potency of the proposed scheme.

In recent years, industries have been investing to develop a potential alternative fuel to substitute the depleting fossil fuels which emit noxious emissions. Present work investigated the effect of ferrous ferric oxide nano-additive on performance and emission parameters of compression ignition engine fuelled with chicken fat methyl ester blends. The nano-additive was included with various methyl ester blends at different ppm of 50, 100, and 150 through the ultrasonication process. Probe sonicator was utilized for nano-fuel preparation to inhibit the formation of agglomeration of nanoparticles in base fuel. Experimental results revealed that the addition of 100 ppm dosage of ferrous ferric oxide nanoparticles in blends significantly improves the combustion performance and substantially decrease the pernicious emissions of the engine. It is also found from an experimental results analysis that brake thermal efficiency (BTE) improved by 4.84%, a reduction in brake specific fuel consumption (BSFC) by 10.44%, brake specific energy consumption (BSEC) by 9.44%, exhaust gas temperature (EGT) by 19.47%, carbon monoxides (CO) by 53.22%, unburned hydrocarbon (UHC) by 21.73%, nitrogen oxides (NOx) by 15.39%, and smoke by 14.73% for the nano-fuel B20FFO100 blend. By seeing of analysis, it is concluded that the doping of ferrous ferric oxide nano-additive in chicken fat methyl ester blends shows an overall development in engine characteristics.

This paper presents lightning (1.2/50 µs) breakdown voltages of palm oil (PO), coconut oil (CO) and mineral oil (MO) in a quasi-uniform sphere to sphere electric field at two gap distances. The type of PO used in this study is Refined Bleached Deodorized Palm Oil (RBDPO) Olein type. The effect of voltage polarities (positive and negative) and testing methods (rising voltage, up and down and multiple level) on the lightning breakdown performance were investigated. The results indicated that lightning breakdown voltages of CO and RBDPO are comparable to those of MO under various test conditions. The results indicated that there is no polarity effect for lightning impulse breakdown tests in a quasi-uniform field. The testing methods, including rising voltage method, up and down method and multiple level method have a notable influence on the breakdown voltages. The effect of the 50% breakdown voltage on rising voltage method, up and down method and multiple level method for RBDPO and CO is comparable to MO. The withstand voltage at 1% and 50% breakdown probabilities were obtained using the Normal distribution fitting on the cumulative probability plot of impulse shots. Based on a normal distribution fitting, withstand voltages 1% breakdown probability of POA were close to the MO. Finally, based on statistical studies and simulation using ANSYS software, the prediction formulas for breakdown voltage for larger gap distances for all samples were derived.

LoRa is being considered as one of the promising system for Low-Power-Wide-Area-Network (LPWAN) to support the growth of Internet of Things (IoT) applications. Designed to operate in the industrial, scientific and medical (ISM) bands, LoRa had been tested and evaluated mainly in Europe and US in the 868 MHz and 915 MHz modulation bands. Using chirp spread spectrum technology, LoRa is expected to be robust against degredation. This paper provides some early results in the performance of LoRa signal propagation of 433 MHz modulation in tropical foliage environments.