Journal Articles

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    Review of thermo-physical properties, wetting and heat transfer characteristics of nanofluids and their applicability in industrial quench heat treatment
    (2011) Ramesh, G.; Prabhu, K.N.
    The success of quenching process during industrial heat treatment mainly depends on the heat transfer characteristics of the quenching medium. In the case of quenching, the scope for redesigning the system or operational parameters for enhancing the heat transfer is very much limited and the emphasis should be on designing quench media with enhanced heat transfer characteristics. Recent studies on nanofluids have shown that these fluids offer improved wetting and heat transfer characteristics. Further water-based nanofluids are environment friendly as compared to mineral oil quench media. These potential advantages have led to the development of nanofluid-based quench media for heat treatment practices. In this article, thermo-physical properties, wetting and boiling heat transfer characteristics of nanofluids are reviewed and discussed. The unique thermal and heat transfer characteristics of nanofluids would be extremely useful for exploiting them as quench media for industrial heat treatment. © 2011 Ramesh and Prabhu.
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    A Comprehensive Review on Scaling Machine Learning Workflows Using Cloud Technologies and DevOps
    (Institute of Electrical and Electronics Engineers Inc., 2025) Ramesh, G.; Vaikunta Pai, T.; Birǎu, R.; Poojary, K.K.; Abhay; Shingad, A.R.; Sowjanya, N.; Popescu, V.; Mitroi, A.T.; Nioata, R.M.; Kiran Raj, K.M.
    Scaling Machine Learning (ML) workflows in cloud environments presents critical challenges in ensuring reproducibility, low-latency inference, infrastructure reliability, and regulatory compliance. This review addresses the lack of a comprehensive synthesis of how integrated DevOps practices and cloud-native technologies enable scalable, production-grade ML systems. We analyze the convergence of MLOps with tools such as Kubernetes, Jenkins, and Terraform, detailing their role in automating CI/CD pipelines, infrastructure provisioning, and model lifecycle management. The main highlights strategies for optimizing resource utilization, minimizing inference latency, and managing data versioning across hybrid and multi-cloud architectures (AWS, Azure, GCP). We also examine serverless computing, container orchestration, and monitoring practices to enhance scalability and governance. By categorizing challenges chronologically and evaluating emerging practices such as federated learning and security-by-design, this work bridges a key gap in existing literature. It offers a unified perspective on building reliable, reproducible, and compliant ML workflows, thereby advancing the state of scalable AI system engineering. © IEEE. 2013 IEEE.
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    A review on NLP zero-shot and few-shot learning: methods and applications
    (Springer Nature, 2025) Ramesh, G.; Sahil, M.; Palan, S.A.; Bhandary, D.; Ashok, T.A.; J, J.; Sowjanya, N.
    Zero-shot and few-shot learning techniques in natural language processing (NLP), this comprehensive review traces their evolution from traditional methods to cutting-edge approaches like transfer learning and pre-trained language models, semantic embedding, attribute-based approaches, generative models for data augmentation in zero-shot learning, and meta-learning, model-agnostic meta-learning, relationship networks, model-agnostic meta-learning (MAML), prototypical networks in few-shot learning. Real-world applications underscore the adaptability and efficacy of these techniques across various NLP tasks in both industry and academia. Acknowledging challenges inherent in zero-shot and few-shot learning, this review identifies limitations and suggests avenues for improvement. It emphasizes theoretical foundations alongside practical considerations such as accuracy and generalization across diverse NLP tasks. By consolidating key insights, this review provides researchers and practitioners with valuable guidance on the current state and future potential of zero-shot and few-shot learning techniques in addressing real-world NLP challenges. Looking ahead, this review aims to stimulate further research, fostering a deeper understanding of the complexities and applicability of zero-shot and few-shot learning techniques in NLP. By offering a roadmap for future exploration, it seeks to contribute to the ongoing advancement and practical implementation of NLP technologies across various domains. © The Author(s) 2025.
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    Heat flux transients and casting surface macro-profile during downward solidification of Al-12% Si alloy against chills
    (American Foundry Society, 2011) Prabhu, K.N.; Sharath, K.; Ramesh, G.
    Heat flux transients were estimated during downward solidificationofAl- 12%Sialloy(A413)againstaluminumand graphite chills. The thermal plot of graphite chill indicated one-dimensional heat flow in the initial stages which then changes to two-dimensional heat transfer. The heat transfer becomes one-dimensional again during the final stages of solidification. In aluminum chill, heat flow was nearly one- dimensional. Experiments were designed to verify whether the peak heat flux is an artifact of the experiment. The results clearly showed that the occurrence of the peak in the heat flux transients is not an artifact of the inverse model or the experimental technique. The macro-profile of the casting surface in contact with the chill revealed the occurrence of crests and troughs. A mechanism based on the convection within the liquid metal below the solid shell was proposed to account for the formation of wavy casting surface. Copyright © 2011 American Foundry Society.
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    Characterisation of water base copper nanoquenchants by standard cooling curve analysis
    (2011) Ramesh, G.; Prabhu, K.N.
    Water base copper nanofluids having concentrations varying from 0?001 to 0?1 vol.-% were prepared and used as quench media for immersion quenching. Cooling curve analyses were carried out by using a standard ISO/DIS 9950 quench probe. An inverse heat conduction model is employed to estimate the metal/nanoquenchant interfacial heat flux transients from the measured temperature field and thermophysical properties of the quench probe material. The addition of copper nanoparticles had a significant effect on the occurrence of the vapour blanket stage and nucleate boiling stage. Furthermore, all six cooling curve parameters were found to be altered by adding nanoparticles to water. The contact angle of water decreased from 67 to 39° by adding 0?1 vol.-% of copper nanoparticles indicating the improved wettability of nanofluids. The heat flux curve shows a maximum initially then drops rapidly during quenching. The peak cooling rate and heat flux of water increased by adding copper nanoparticles up to 0?01 vol.-%. Both parameters decreased with further increase in concentration of nanoparticles. The results suggest that the quench severity of water could be altered by adding copper nanoparticles. © 2011 IHTSE Partnership.
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    Effect of addition of aluminum nanoparticles on cooling performance and quench severity of water during immersion quenching
    (ASTM International, 2012) Ramesh, G.; Prabhu, K.N.
    In the present work, the effect of the addition of aluminum nanoparticles in concentrations varying from 0.001 to 0.5 vol. % on the cooling performance and quench severity of water during immersion quenching is investigated. The results of cooling curve analyses show that an increase in nanoparticle concentration increased the cooling rates at critical temperatures up to 0.05 vol. % and decreased them thereafter. The transition from the vapor blanket stage to the nucleate boiling stage was also altered by quenching in nanofluids. A finite difference heat transfer program was employed to generate cooling curves at different values of heat transfer coefficient from thermo-physical properties of the quench probe material. A Grossmann H quench severity versus cooling rate curve was established, and from this curve, the H factors of prepared nanofluids were estimated. An increase in nanoparticle concentration up to 0.05 vol. % resulted in an increase of the H value of water from 63 m -1 to 93 m-1, and any further increase in the concentration of nanoparticles resulted in a decrease in H. The results suggest both the enhancement and the deterioration of the cooling performance of water by the addition of aluminum nanoparticles. Copyright © 2012 by ASTM International.
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    Effect of addition of aluminum nanoparticles on cooling performance and quench severity of water during immersion quenching
    (2012) Ramesh, G.; Prabhu, K.N.
    In the present work, the effect of the addition of aluminum nanoparticles in concentrations varying from 0.001 to 0.5 vol. % on the cooling performance and quench severity of water during immersion quenching is investigated. The results of cooling curve analyses show that an increase in nanoparticle concentration increased the cooling rates at critical temperatures up to 0.05 vol. % and decreased them thereafter. The transition from the vapor blanket stage to the nucleate boiling stage was also altered by quenching in nanofluids. A finite difference heat transfer program was employed to generate cooling curves at different values of heat transfer coefficient from thermo-physical properties of the quench probe material. A Grossmann H quench severity versus cooling rate curve was established, and from this curve, the H factors of prepared nanofluids were estimated. An increase in nanoparticle concentration up to 0.05 vol. %resulted in an increase of the H value of water from 63 m 1 to 93 m 1, and any further increase in the concentration of nanoparticles resulted in a decrease in H. The results suggest both the enhancement and the deterioration of the cooling performance of water by the addition of aluminum nanoparticles. Copyright © 2012 by ASTM International.
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    Heat transfer at the casting/chill interface during solidification of commercially pure Zn and Zn base alloy (ZA8)
    (2012) Ramesh, G.; Prabhu, K.N.
    Casting/chill interfacial heat transfer during solidification of commercially pure zinc and ZA8 alloy against copper, hot die steel, stainless steel and aluminiuminstrumented chills was investigated. The peak heat flux strongly depends on the thermophysical properties of chill, chill surface condition and superheat of the castingmaterial. Contact angles of alumina coatingmeasured on various substrates suggested that the adhesion of the coating material on copper chill was significantly better as compared to other chill materials. The heat flux curve in the case of coated chills is characterised by a double peak indicating remelting of the solidified casting shell. The second peak in the HTC curve is lower for high conductivity and higher for low conductivity chills as compared to the first peak. It is possible that solid shell formation and remelting occurred in the case of high thermal conductivity chills, whereas shell remelting did not happen in lower thermal conductivity chills. © 2012 W. S. Maney & Son Ltd.
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    Effect of boundary heat transfer coefficient and probe section size on cooling curves during quenching
    (ASTM International, 2012) Ramesh, G.; Prabhu, K.N.
    In the present work the effect of boundary heat transfer coefficient and section size of quench probe material on cooling curves was investigated by using finite difference heat transfer based SolidCast software. Simulations were carried out at different combinations of heat transfer coefficient and quench probe diameter and thermal history at the geometric center of the probe was estimated to generate cooling curves. Simulation results show that both boundary heat transfer coefficient and quench probe diameter had a significant effect on the average cooling rate. A relationship between Grossmann quench severity (H), thermal conductivity of material, size of the probe, and average cooling rate was established. By using this model, for a known quench medium, probe size, and material it is possible to predict the average cooling rate of the probe. On the other-hand, for a given material and required cooling rate, cooling severity required from the quench media could be predicted and accordingly an appropriate quench medium can be selected. © 2012 by ASTM International.
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    Effect of Mn on cooling behaviour and microstructure of chill cast Zn-Al (ZA8) alloy
    (2012) Ramesh, G.; Vishwanatha, H.M.; Prabhu, K.N.
    In the present work, the effect of manganese addition to ZA8 alloy on thermal analysis parameters, heat transfer and microstructure was investigated. The thermal analysis parameters were found to be significantly affected by chemical modification of ZA8 alloy. Cooling curve and differential scanning calorimetry analyses of modified alloy showed nucleation of new phase other than b dendrites. Chilling of modified alloy resulted in decreased liquidus temperature and enhanced eutectoid transformation. Further, chilling avoids the formation of intermetallic compounds in modified alloy. The heat flux transients were estimated using inverse modelling during solidification of unmodified and modified alloys against different chills. The peak heat flux decreased on addition of Mn to ZA8 alloy. Differential scanning calorimetry analysis indicated that the addition of Mn to ZA8 alloy decreases the heat of solidification. The addition of Mn to ZA8 alloy increased the contact angle, indicating decreased wettability of the modified alloy on the chill surface. The microstructure of ZA8 with Mn showed an increased amount of b phase and a decreased amount of eutectic. X-ray diffraction analysis confirmed the formation of MnAl6 intermetallics in Mn added ZA8 alloy. Chilling with chemical modification resulted in enhanced decomposition of b phase. © 2012 Institute of Materials, Minerals and Mining.