School of Mechanical Engineering (September 2021)


Journal Papers

1. Nayak, K. K., Singhal, D. and Tripathy, S. (2021), Determination of Challenges and Driving Forces of Green Supply Chain Management in Indian Manufacturing Industries: a Critical Review,International Journal of Logistics Systems and Management, Vol. 40, No. 1, pp. 28-51.


Primary objective of this research is to carry out a literature review on the field of GSCM in Indian manufacturing industries. Further, this research focuses on the illustration of the common challenges and driving forces of GSCM along with the status of GSCM in Indian manufacturing industries. A systematic analysis has been performed then open-ended questionnaire survey has been carried out to find the common challenges and driving forces of GSCM. The questionnaire was sent to 45 respondents, and in return, 24 responses were received which shows a response of 53.33%. This research investigates the challenges and driving forces of GSCM in various Indian manufacturing industries and discovered 22 common challenges and 15 common driving forces of GSCM. Classification of the critical challenges and critical driving forces may turn out to be an extremely valuable wellspring of data to the decision makers and researchers in their green practice usage programs..

2. Aich, S., Thakur, A., Nanda, D., Tripathy, S. and Kim, H. C. (2021), Factors Affecting ESG towards Impact on Investment: A Structural Approach,Sustainability, Vol. 13, No. 19, 10868.


The research gap extracted from the previous studies is to determine the relationship among the influencing factors of environmental, social, and governance (ESG) and its priority with their driving and dependence capabilities. An ISM Approach was used to uncover the interrelationships and influencing behavior among the elements for considering ESG in investment after conducting a thorough literature research and consulting with experts. Here interpretive structural modeling (ISM) was used to explore the links among such extracted factors and its interdependencies. There was also focus on the short-term and long-term factors to achieve our desired objective. Our research will assist businesses in attracting and obtaining finance. The results of this analysis will be helpful for leaders to understand the impact of ESG on the investment aspects of an organization.

3. Saha, R., Aich, S., Tripathy, S. and Kim, H. C. (2021), Artificial Intelligence Is Reshaping Healthcare amid COVID-19: A Review in the Context of Diagnosis & Prognosis,Diagnostics, Vol. 11, No. 9, 1604.


This paper seeks to pick out the crucial fulfillment of factors for AI with inside the healthcare sector in the Indian context. Using critical literature review and experts’ opinion, a total of 11 factors affecting COVID-19 diagnosis and prognosis were detected, and we eventually used an interpretive structural model (ISM) to build a framework of interrelationships among the identified factors. Finally, the matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis resulted the driving and dependence powers of these identified factors. Our analysis will help healthcare stakeholders to realize the requirements for successful implementation of AI.

4. Aich, S., Tripathy, S., Joo, M. I. and Kim, H. C. (2021), Critical Dimensions of Blockchain Technology Implementation in the Healthcare Industry: An Integrated Systems Management Approach,Sustainability, Vol. 13, No. 9, 5269.


The authors defined the critical factors that affect blockchain implementation in the healthcare industry. We extracted such factors from the literature and from experts, then used interpretive structural modeling to define the interrelationships among these factors and classify them according to driving and dependence forces. This identified key drivers of the desired objectives. Regulatory clarity and governance (F2), immature technology (F3), high investment cost (F6), blockchain developers (F9), and trust among stakeholders (F12) are key factors to consider when seeking to implement blockchain technology in healthcare. Our analysis will allow managers to understand the requirements for successful implementation.

5. Mukherjee, S., Ali, N., Aljuwayhel, N. F., Mishra, P. C., Sen, S. and Chaudhuri, P. (2021), Pool Boiling Amelioration by Aqueous Dispersion of Silica Nanoparticles,Nanomaterials, Vol. 11, No. 8, 2138.


The present study reports an investigation on the PBHT characteristics and performance of water-based silica nanofluids in the nucleate boiling region. Sonication-aided stable silica nanofluids with 0.0001, 0.001, 0.01, and 0.1 particle concentrations were prepared. The stability of nanofluids was detected and confirmed via visible light absorbance and zeta potential analyses. The PBHT performance of nanofluids was examined in a customized boiling pool with a flat heating surface. The boiling characteristics, pool boiling heat transfer coefficient (PBHTC), and critical heat flux (CHF) were analyzed. The effects of surface wettability, contact angle, and surface roughness on heat transfer performance were investigated. Bubble diameter and bubble departure frequency were estimated using experimental results. PBHTC and CHF of water have shown an increase due to the nanoparticle inclusion, where they have reached a maximum improvement of ≈1.33 times over that of the base fluid. The surface wettability of nanofluids was also enhanced due to a decrease in boiling surface contact angle from 74.1° to 48.5°. The roughness of the boiling surface was reduced up to 1.5 times compared to the base fluid, which was due to the nanoparticle deposition on the boiling surface. Such deposition reduces the active nucleation sites and increases the thermal resistance between the boiling surface and bulk fluid layer. The presence of the dispersed nanoparticles caused a lower bubble departure frequency by 2.17% and an increase in bubble diameter by 4.48%, which vigorously affects the pool boiling performance.

6. Mukherjee, S., Panda, S. R., Mishra, P. C. and Chaudhuri, P. (2021), Convective Flow Boiling Heat Transfer Enhancement with Aqueous Al2O3 and TiO2 Nanofluids: Experimental Investigation, International Journal of Thermophysics, Vol. 42, No. 6, pp. 1-26.


The convective flow boiling characteristics of aqueous Al2O3 and TiO2 nanofluids are presented in this paper. Stable suspensions of aqueous Al2O3 and TiO2 nanofluids at two different concentrations of 0.01 and 0.1 wt% were prepared and allowed to flow through a horizontal annulus under varying heat flux from 26,140.132 to 53,573.503 W/m2 and varying flow rates from 3 to 6 L/min. Parametric effects of nanoparticle concentration, heat flux, and flow rate on the heat transfer coefficient (HTC) were studied. Variation in pressure drop and pumping power at studied concentration and flow rates was estimated. In addition to that, bubble growth and nucleation site were analyzed using flow visualization technique. Enhancement in the HTC was obtained with increasing concentration and flow rate. A maximum of 2.4 times enhancement in HTC relative to water was observed. Bubble growth and nucleation site density increased with increasing heat flux and nanofluid concentration. Pressure drop and pumping power increased with nanoparticle addition and even at such a low-flow condition. Highest pressure drop of 33.33 % was registered with nanofluids at 0.1 wt%. The change in heating surface roughness due to particle deposition affects heat transfer performance. Finally, figure of merit showed that nanofluids are better alternatives to their basefluids for superior heat transfer.

7. Muduli, S. K., Mishra, R. K. and Mishra, P. C. (2021), Computational Assessment of Performance Parameters of an Aero Gas Turbine Combustor for Full Flight Envelope Operation,International Journal of Turbo & Jet-Engines. DOI: 10.1515/tjj-2021-0034


This paper presents the computational study carried out on an aero gas turbine combustor to assess important performance parameters. The CFD results are compared with experimental data obtained from the full scale combustor tested at ground test stand simulating various operational conditions. The CFD predictions have agreed very well with the experimental data. The model is then extended to predict combustor exit temperature pattern factors, pressure loss, and combustion efficiency and exhaust gas constituents over a wide range of operating pressure and temperature conditions. The paper also presents the studies carried out on the effect of atomizer spray cone angle, particle size and fuel flow variations expected due to manufacturing tolerances in various flow passages as well as due to operational degradations on temperature pattern factors. The pattern factors are also analyzed on cold and hot day environment. The radial pattern factor (RPF) at mid height is found to increase as altitude increases from sea level to 12 km. Spray cone angle is found to have a predominant effect on temperature non-uniformity at exit, lower cone angle increasing both radial and circumferential pattern factors. The findings of this study are valuable inputs for engine performance estimation.

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