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Carbon Fiber Reinforced Polymer (CFRP) is the most preferred composite material due to its high strength, high modulus, corrosion resistance and rigidity and which has wide applications in aerospace engineering, automobile sector, sports instrumentation, light trucks, airframes. This paper is an attempt to carry out drilling experiments as per Taguchi’s L27 (313) orthogonal array on CFRP under dry condition with three different drill bit type (HSS, TiAlN and TiN). In this research work Response Surface Analysis (RSA) is used to correlate the effect of process parameters (cutting speed and feed rate) on thrust force, torque, vibration and surface roughness. This paper also focuses on determining the optimum combination of input process parameter and the drill bit type that produces quality holes in CFRP composite laminate using Multi-objective Taguchi technique and TOPSIS. The percentage of contribution, influence of process parameters and adequacy of the second order regression model is carried out by analysis of variance (ANOVA). The results of experimental investigation demonstrates that feed rate is the pre-dominate factor which affects the response variables.

The applications of the polymer nanocomposites are increasing to a greater extent in several sectors. In this investigation, the matrix selected was Polypropylene (PP) and reinforcing filler was Cloisite 30B (C3B) with Elvaloy-AC-3427 (EAC) as a compatibilizer. Twin screw extruder was used for manufacturing of PP/C3B/EAC nanocomposites. C3B was added at the range of 1, 2, 3, 5 wt% to PP matrix. The manufactured composites was analysed for mechanical and thermal characterization. The tribological characteristics of manufactured nanocomposites were studied using abrasive wear tests. The input parameters considered for the abrasive wear tests were (i) load, (ii) C3B and (iii) sliding distance. The output parameters for the abrasive wear tests were weight loss, Coefficient of Friction (COF) and Specific Wear Rate (SWR). Grey relational analysis and grey fuzzy were done for the optimisation of abrasive wear characteristics. Analysis of Variance (ANOVA) was used for analysing the effect of input parameters over the output factors. Finally, the abraded wear samples of PP/C3B/EAC nanocomposites samples were examined microscopically.

Petroleum hydrocarbons (PHs) are compounds composed mostly of carbon and hydrogen, originating from crude oil and its derivatives. PHs are primarily released into the environment through the diffusion of oils, resulting from anthropogenic activities like transportation and offshore drilling, and accidental incidents such as oil spills. Once released, these PHs can persist in different ecosystems and cause long-term detrimental ecological impacts. While the hazards associated with such PH contaminations are often assessed by the concentrations of total petroleum hydrocarbons in the environment, studies focusing on the risks associated with individual PHs are limited. In this study, different network-based frameworks were utilized to explore and understand the adverse ecological effects associated with PH exposure. First, a list of 320 PHs was systematically curated from published reports. Next, biological endpoint data from toxicological databases was systematically integrated, and a stressor-centric adverse outcome pathway (AOP) network, linking 75 PHs with 177 ecotoxicologically-relevant high confidence AOPs within AOP-Wiki, was constructed. Further, stressor-species networks, based on reported toxicity concentrations and bioconcentration factors data within ECOTOX, were constructed for 80 PHs and 28 PHs, respectively. It was found that crustaceans are documented to be affected by many of these PHs. Finally, the aquatic toxicity data within ECOTOX was used to construct species sensitivity distributions for PHs, and their corresponding hazard concentrations (HC05), that are harmful to 5% of species in the aquatic ecosystem, were derived. Further, the predicted no-effect concentrations (PNECs) and risk quotients for the US EPA priority polycyclic aromatic hydrocarbons (PAHs) were computed by using their environmental concentration data for Indian coastal and river waters. Overall, this study highlights the importance of using network-based approaches and risk assessment methods to understand the PH-induced toxicities effectively.