Research Publications

@article{452,

title = {RESILIENCE-ORIENTED DECISION SUPPORT SYSTEM FOR ECOSYSTEM MANAGEMENT: INTEGRATING MACHINE LEARNING AND PARTICIPATORY MODELLING},

author = {S. Rajan and A. Madhukumar and A. Anthonisamy and R. Reenadevi and R. Sridivya and T. Muruganantham and J. M. Philip and A. Rajaram},

url = {hhttps://scibulcom.net/en/article/klnA14eZe6RmBYawrTvB},

isbn = {13115065 (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {Journal of Environmental Protection and Ecology},

volume = {26},

pages = {1001-1010,},

abstract = {Ecosystem management requires adaptive method which handles the complexity and uncertainty, especially the habitat degradation, biodiversity loss, and climate change. The existing methods of managing ecosystems often lack in the adaptability and necessary to precisely addresses the dynamic circumstances. To enhance the decision-making in ecosystem management, this study offers a Resilience-Oriented Decision Support System (RODSS) that integrates the Participatory Modelling (PM) and Machine Learning (ML) methods. Initially, the data are collected from the environmental sensors, satellite imagery, and stakeholder. Then, Bayesian Network (BN) algorithms are used for analysis and the System Dynamics (SD) modelling involves stakeholders in defining scenarios, assessing trade-offs, and co-developing strategies to improve the ecosystem resilience that determines the anomalies, and patterns in ecosystem health. The RODSS employs a Reinforcement Learning (RL) model for predicting the potential results and recommends the adaptive management techniques. The proposed system simulations are evaluated using the real-world case studies showcases the RODSS significantly enhances the accuracy and robustness of ecosystem manage ment techniques. The combinations of Machine Learning (ML) provide a processing of complex, high-dimensional data, while PM guarantees a contextual relevance and stakeholder engagement of the techniques, made possible for attaining more sustainable and effective.},

note = {0},

keywords = {CIVIL},

pubstate = {published},

tppubtype = {article}

}

@article{625,

title = {Mapping Nitrate Distribution And Non-Carcinogenic Health Risk Assessment Via Hazard Index For Infants},

author = {B. S. Shankar and R. S. Sreevidya and M. Raju and L. Sanjeev},

url = {https://theaspd.com/index.php/ijes/article/view/612/449},

year  = {2025},

date = {2025-01-01},

journal = {International Journal of Environmental Sciences},

volume = {11},

pages = {645-652,},

publisher = {Academic Science Publications and Distributions},

abstract = {Nitrate contamination in drinking water has become a major public health concern, as high nitrate levels have been linked to various health issues. This study was conducted to assess nitrate concentrations in the groundwater of Bellandur by collecting and analyzing thirty groundwater samples during the pre-and postmonsoon seasons. Analysis results showed that 53.33% and 56.67 % of samples exceeded the BIS limit for nitrate in drinking water (45 mg/L) during pre-and post-monsoon seasons respectively. Health risks related to non-carcinogenic effects from nitrate exposure through drinking water were evaluated, focusing on infants who are particularly vulnerable to nitrate-induced methemoglobinemia. The Health Risk Index, HI was calculated based on Chronic Daily Intake (CDI), with findings indicating that 76.67% and 83.33% of the samples in the pre-and post-monsoon respectively, had HI values above 1, suggesting a significant risk of nitrate exposure, posing a health threat to the residents. This underscores the need for effective strategies to control and manage nitrate contamination sources, safeguarding groundwater quality in the area. © 2025, Academic Science Publications and Distributions. All rights reserved.},

note = {1},

keywords = {CIVIL},

pubstate = {published},

tppubtype = {article}

}

@article{675,

title = {INFLUENCE OF COBALT CONTENT ON THE MECHANICAL AND EROSION PERFORMANCE OF HVOF-SPRAYED WC-Co COATINGS ON INCONEL 718 SUPERALLOY},

author = {U. Harish and M. V. Kumar and M. Mruthunjaya and M. V. Mohan and C. Chitrada and B. S. Bindhushree and P. K. Soni and C. H. Kumar and H. Soni and C. D. Prasad},

url = {https://www.worldscientific.com/doi/10.1142/S0218625X26500125},

doi = {10.1142/S0218625X26500125},

isbn = {17936667 (ISSN); 0218625X (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {Surface Review and Letters},

publisher = {World Scientific},

abstract = {This study presents a detailed analysis of the microstructure and erosion behavior of WC-Co composite coatings with different cobalt levels: WC-10Co, WC-13Co, and WC-16Co, applied on nickel-based Inconel 718 steel superalloy using the HVOF spray process. The research shows that the coatings’ hardness increases with cobalt content, with WC-16Co reaching the highest microhardness of 825 Hv. XRD analysis indicates that the WC-16Co coating displays notably sharper cobalt peaks as the cobalt content increases, indicating improved phase visibility. This correlates with a distinct layered structure exhibiting minimal porosity of 1.1±0.15%, compared to 1.4±0.20% for WC-10Co and 1.3±0.15% for WC-13Co. The increased hardness and lower porosity of WC-16Co suggest better wear and erosion resistance relative to the other coatings. Overall, this study emphasizes the impact of cobalt content on the microstructural and mechanical properties of WC-Co coatings, identifying WC-16Co as the most durable option for applications demanding superior erosion resistance.},

note = {0},

keywords = {CIVIL},

pubstate = {published},

tppubtype = {article}

}

@article{691,

title = {Electromagnetic Analysis and Machine Learning-Driven Optimization of a Graphene-Based Metasurface Sensor for Waterborne Pathogen Detection},

author = {V. Kalaipoonguzhali and R. Vijayakumar and A. Madhukumar and U. Arunkumar},

url = {https://link.springer.com/article/10.1007/s11220-025-00675-6},

doi = {10.1007/s11220-025-00675-6},

isbn = {15572064 (ISSN); 15572072 (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {Sensing and Imaging},

volume = {26},

publisher = {Springer},

abstract = {Waterborne bacterial contamination represents a critical global health challenge, with traditional detection methods suffering from lengthy processing times, complex sample preparation, and limited real-time monitoring capabilities. This research develops a metasurface biosensor incorporating graphene-enhanced multilayer resonators for rapid, label-free detection of waterborne bacteria such as Escherichia coli, Vibrio cholerae, and Salmonella species. Electromagnetic analysis employing Maxwell’s equations, Kubo formalism for graphene conductivity, and coupled-mode theory provides comprehensive theoretical foundation for the sensor’s operation. Using COMSOL Multiphysics for numerical simulations, the sensor achieves a maximum sensitivity of 487.805 GHz/RIU and a figure of merit of 19.5122 RIU⁻¹ over the operating frequency range of 0.168–0.176 THz, demonstrating remarkable performance characteristics. As the sensitivity to changes in the refractive index increases, the detection limit drops substantially from 0.548421 RIU to 0.064244 RIU. Machine learning integration using polynomial regression algorithms achieves R² scores of 86% and 89% for predicting absorption characteristics based on graphene chemical potential and incident angle parameters. The proposed design establishes a scalable pathway toward real-time terahertz biosensing for next-generation water quality monitoring and microbial diagnostics.},

note = {0},

keywords = {CIVIL},

pubstate = {published},

tppubtype = {article}

}

@article{706,

title = {Integrated experimental-modeling study on strength and durability in fiber-reinforced geopolymer concrete},

author = {A. K. Manahala and C. Wollur and A. Ranjith and M. S. Shobha and E. Hanumappa and S. Kavith},

url = {https://onlinelibrary.wiley.com/doi/10.1002/suco.70345},

doi = {10.1002/suco.70345},

isbn = {14644177 (ISSN); 17517648 (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {Structural Concrete},

publisher = {John Wiley and Sons Inc},

abstract = {The newest innovation in the building industry is alkaline activated concrete. Additionally, the demand for river sand has increased significantly and is now more expensive. Utilizing locally accessible supplies improves both the environmental and economic aspects. Manufactured sand (MS) is a substitute for stream sand in this situation. Using the right reinforcing components, namely “Fibers,” can increase the ductility of these quasi-brittle inorganic composites. The paper's focus is polymer–concrete optimization, highlighting the impact of fiber and molar concentration. To make GPC mixtures, a solution-to-binder ratio of 0.45 was maintained. An addition of 1% of fibers was made to the matrix. The samples were considered for molarities of 12 and 14. Samples were cast and exposed to ambient curing. In addition to fibers with increasing molarities, the slump values have decreased by 41%, compressive and flexural strength results are improved by 11% and 19% respectively, and the modulus of elasticity (Ec) is compared with the analytical equation where the coefficient is within 10%. Sorptivity outcomes prove a noteworthy decline in capillary rise up to 24.7% compared to traditional concrete; penetration of chloride has reduced by 39%.},

note = {0},

keywords = {CIVIL},

pubstate = {published},

tppubtype = {article}

}

@article{721,

title = {Decentralized Urban Groundwater Nitrate Remediation Using Low-Cost ZVI Reactors: Laboratory Validation, Colony-Scale Simulation, Techno-Economic Assessment, and Deployment Feasibility},

author = {SHANKAR .S},

url = {https://onlinelibrary.wiley.com/doi/10.1002/rem.70051},

doi = {10.1002/rem.70051},

isbn = {10515658 (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {Remediation},

volume = {36},

publisher = {John Wiley and Sons Inc},

abstract = {Elevated nitrate levels in groundwater across India's urban peripheries present a pressing public health challenge, especially in unplanned settlements where formal remediation infrastructure is lacking. This study proposes a scientifically validated, cost-effective nitrate mitigation approach based on modular zero-valent iron (ZVI) reactors designed for decentralized installation and passive operation. Using detailed laboratory experimentation and field sampling across 30 stations in Bellandur (Bengaluru, India), a deployment simulation was created to model the reactor's real-world scalability. The gravity-fed column reactor constructed using locally available media—sand, charcoal, brickbats, and red soil, which contain ZVI capable of absorbing nitrate—demonstrated 85%–90% nitrate removal efficiency across varied synthetic influent levels, achieving compliance with the Bureau of Indian Standards (BIS) nitrate permissible standard of 45 mg/L. The deployment simulated reactor incorporating field data, population exposure indexing, and reactor allocation was developed, achieving an average nitrate removal efficiency of 82.4% across high-risk zones, with post-treatment concentrations reduced below the BIS permissible standard. Based on the above functions, the simulation recommended the installation of 3335 ZVI reactors across 17 high-risk colonies, directly serving over 28,500 households and addressing a cumulative nitrate load of 2984 mg/L. Comparative cost analysis revealed that this system reaches breakeven against reverse osmosis (RO) within 4 years and against ion exchange (IX) in 7 years, offering a practical alternative for corporate social responsibility-aligned groundwater rehabilitation programs. This is one of the first studies to integrate laboratory validation, colony-scale deployment simulation, and techno-economic assessment into a single nitrate remediation framework for peri-urban India and similar underserved regions, providing both technical validation and a replicable policy blueprint, providing a validated deployment framework rooted in field data, cost realism, and performance metrics.},

note = {0},

keywords = {CIVIL},

pubstate = {published},

tppubtype = {article}

}

@article{725,

title = {Identification, Source Forensics, and Risk Assessment of Heavy Metals in the Groundwater of Tannery Area in Bangalore, India},

author = {S. Raman},

url = {https://www.tandfonline.com/doi/full/10.1080/15275922.2025.2594978},

doi = {10.1080/15275922.2025.2594978},

isbn = {15275922 (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {Environmental Forensics},

publisher = {Taylor and Francis Ltd.},

abstract = {This study involves the identification and risk assessment of heavy metals in groundwater of tannery area in Bangalore, India, where leather and a few allied industries are responsible for severe contamination. Groundwater-dependent residents report health disorders, underlining the need for planned studies and mitigation measures. Groundwater samples were collected from 30 locations during the pre-(dry) and post-monsoon (wet) seasons of 2024 and analyzed for chromium, copper, lead, cadmium, and iron. Risk indices such as contamination factor (CF), degree of contamination (CD), pollution load index (PLI), index of geo-accumulation (Igeo), enrichment factor (EF), quantification of contamination (QoC), and ecological risk index (ERI) were evaluated. Forensic and source identification confirms anthropogenic origin linked to tanning, metal processing, and associated industrial activities. During pre-monsoon, 70%, 36.67%, 33.33%, 53.33%, and 56.67% of samples exceeded BIS limits for Cd, Fe, Cu, Pb, and Cr, respectively, while in post-monsoon, 60%, 33.37%, 33.33%, 53.33%, and 46.67% exceeded limits in the same order. Pre-monsoonal metal concentrations were marginally higher, though variations were negligible. Based on CF, 53.33%, 33.33%, 30%, and 26.67% of samples were in very high contamination zone for Fe, Cd, Cr, and Pb; 6.66%, 23.33%, 13.33%, and 3.33% were in considerable contamination zone for Fe, Cr, Cu, and Pb. CD index shows 43.33% and 13% of samples under high and considerable contamination range. PLI indicated extremely heavy contamination in 40% and heavy contamination in 13.33% of samples. EF showed most samples in background rank and minimal enrichment; only one sample each showed very high enrichment for Pb and Cd, and extremely high enrichment for Cu, Cr, and Cd. Igeo values revealed 10, 6, 5, 6, and 10 samples fell under the heavily to extremely contaminated category. ERI indicated Cd contributed to 30% of samples under very high ecological risk, along with 3 due to Pb, 2 due to Cu, and one each due to Pb and Cd, showing high ecological risk. Overall, ERI showed low to moderate risk. QoC revealed human activities as the primary contamination source. These findings provide a critical foundation for policymakers to reduce contamination, mitigate risks, and ensure sustainable groundwater management.},

note = {0},

keywords = {CIVIL},

pubstate = {published},

tppubtype = {article}

}