Gobinath R
@sru.edu.in
Professor and Head-Department of Civil Engineering
SR University, Telangana, India
is presently serving as Professor and Head of the Department, Civil Engineering of SR University, Telangana, India and also a member of Center for Construction Materials and Methods division. He completed his PhD in the field of Environmental Geotechnology and Disaster Management from Center for Disaster Management and Mitigation, VIT, Vellore, M.E in Environmental Management from College of Engineering, Guindy, Anna University and BE in Civil engineering from Bharathiar University. He had handled several under graduate course in Civil and Environmental engineering including Project management, smart materials and structures, Geosynthetics, Engineering Mechanics etc and also presently handling elective courses related to Disaster Management and Intellectual Property rights in various Universities.
His research interests includes Sustainable materials, Construction Materials, Landslide mitigation and Management, Soil Bioengineering, Engineering Education, Geotechnology, Environmental Geotechnology, Sustainable Development, Sustainable construction technologies, he had handled several projects related to this domains in various levels. He also had executed good number of consultancy projects related to Geotechnical and environmental engineering for various organisations.
EDUCATION
B.E- Civil Engineering (2001), Bharathiar University
M.E- Environmental Management (2007), College of Engineering, Guindy, Anna University
PhD ( Environmental Geotechnology), VIT University, Vellore, India
RESEARCH INTERESTS
Sustainable materials, Construction Materials, Landslide mitigation and Management, Soil Bioengineering, Engineering Education, Geotechnology, Environmental Geotechnology, Sustainable Development, Sustainable construction technologies, Image processing, Machine Learning applications in Civil Enginee
FUTURE PROJECTS
Sustainable Construction material development
This project work involves obtaining sustainable construction materials without depleting the natural resources and by using non convetional material development techniques. It involves lot of analysis, simulation based works and the work is initiated under the aegies of Center for Construction Methdos and Materials of SR University
Applications Invited
Research Scholars and collaborators
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
R. J. Jerin Joe, V. Stephen Pitchaimani, R. Gobinath, and G. Shyamala
Springer Science and Business Media LLC
G. Shyamala, R. Gobinath, B. Hemalatha, DivyaSri Akkalla, S. Shenbaga Ezhil, and V. Sathya
Springer Science and Business Media LLC
AbstractClimate change is a significant threat to ecosystems and communities, and challenges global sustainability; therefore, more research on climate change adaptations should be conducted. This scientometric study presents databases on global trends in academic research, specific contributions, and thematic evolution of environmental adaptations to climate change. Using the Scopus database of publications, this study focuses on publications between 2009 (January) and 2024 (August), with an emphasis on the interpretation of primary research interests, authors, contributions from countries, and collaborative networks. According to the findings, there has been a shift in focus to more adaptive management in agricultural and biological diversity practices, with more emphasis on the integration of ecological, technological, and social science disciplines. This work also reveals that countries have gaps in regional research, especially in developing countries, and highlights the need to work collectively across the globe. Through citation analysis, thematic evolution, and future research recommendations, this study enriches the knowledge of the line of research on environmental adaptation and underlines its significance in addressing climate change effects.
Devika Banothu, Pankaj Kumar, Rajasri Reddy, Sukumar Dhanapalan, and R Gobinath
IOP Publishing
Abstract This investigation examined the mechanical strength and failure behaviour of various 3D printed lattices for implantation in bones, consisting of octahedral, double pyramid, diamond and cubic lattices. The combination of this research methodology includes a finite element analysis and fatigue testing. Low-cycle compressive fatigue tests were performed using specialized equipment, in addition to the employment of a scanning electron microscope for the properties of the surface and failure modes. The results of this study show that the octahedral lattice provides improved structural performance, a small amount of deformation, uniform stress distribution, and the greatest levels of fatigue resistance. Both diamond and double pyramid lattices indicate moderate deformation and fatigue strength; therefore, they are recommended where flexibility, together with high performance, is a concern. However, the cubic lattice was the worst case, resulting in the highest localized stress and poor ductility. Based on this extensive comparison of identifiers when using fused lattices configured for PLA materials, further studies must introduce physiological stimuli and use versatile biomaterials such as PEEK and titanium. The findings around lattice structure re-emphasize the criticality of lattice choice in the overall improvement of implant outcomes, with the octahedral lattice identified to have impressive fatigue properties that will work well in weight-bearing implants. This study furthers the field of biomedical implant science which could help improve the prognosis of patients through the use of robust bone implants.
Bhagyashree Khartode, Manisha Shewale, and R. Gobinath
EDP Sciences
The construction industries are, to a great extent subordinate to variables such as the human workforce, which are incapable of being replaced with machines, therefore it may be a challenge within the range of the development segment to supply suitable labour contractor according to their determinations for creating effectiveness within the development venture. Multi Criteria Decision-Making (MCDM) system that helps to make decisions in situations where you need to consider multiple factors. This work is based on the critical issue of how to allocate labour contractors effectively in industries where labour deployment is critical. Web based solution using MCDM techniques includes an easy-to-use interface that provides stakeholders with a simple and transparent process for selecting labour contractors. Criteria include skills competency, availability schedules, track record, cost-efficiency and geographic location. Using a cross reference of different Hierarchy Process (AHP) approaches to determine which approach is best suited to the labour allocation scenario. Simulations and case studies are also used to test the system effectiveness and efficiency in real life situations. Web based solution enable timely and effective decision making, and also allows for continuous performance tracking and feedback loops. This research contributes to the advancement of labour allocation practices by introducing a robust web-based solution empowered by MCDM techniques. The proposed system offers a practical and innovative approach to address the complexities associated with labour contractor selection, ultimately leading to optimized resource utilization and enhanced project outcomes.
Rajesh Kumar K, Lakshmi Prasanna K, Gobinath R, and Divyasri
EDP Sciences
Energy from Waste (EFW) addresses waste management and energy supply issues. This study aims to identify research trends, challenges, and the current status of EFW using scientometric analysis. Objectives include understanding the field's evolution, assessing global contributions, and identifying future research gaps. Bibliometric methods measured trends in publications, citations, and country participation. Innovations in the EFW sector were evaluated based on current research and challenges. Data was sourced from indexed databases like Scopus, covering publication frequency, citation distribution, author collaboration, and geographical distribution over the past decade. Findings indicate a rise in EFW publications and citations in the last five years, but further research is needed on cost-effectiveness, energy recovery optimization, and waste-to-energy conversion technologies. These insights are beneficial for researchers, policymakers, and investors focused on EFW sector expansion.
Pingili Vydehi, Gobinath Ravindran, G. Shyamala, and S. Ramesh
Elsevier BV
Rachoru Himani Srihita, Gurunadham Goli, Rajyalaxmi M, and R Gobinath
SAGE Publications
Digital platforms play a vital role in shaping today’s labour market, enabling temporary hires and freelance employment in the gig economy. This on-demand, digital economy spans various professions and remote work opportunities. Technological advancements have significantly evolved gig work since the industrial age, improving work-life balance and psychological well-being. Using the Scopus database, a literature analysis on the gig economy was conducted with 1624 documents narrowed to 549 documents based on subject area, document type, publication stage, keywords, and language and examining social, economic and technological factors. This study highlights the evolving nature of non-traditional, online-platform- driven employment through which author’s explored the gig economy, its challenges, ethical issues, and career development and workers experiences. The analysis used R Studio Software to visualize keyword themes using a strategic thematic map, which signifies the structure and development of themes within the gig economy. This study used Origin Pro for author analysis which found GRAHAM as the top author. VOS Viewer for bibliographic coupling which identified USA and UK as top collaborating countries and also highlight the eight clusters of keyword analysis. For sustainable growth, further research should explore the platform economy, gig employment, and worker well-being, assessing technological innovations to create adaptable job opportunities. This will help the gig economy to accommodate market dynamics and ensure diverse and stable employment across various sectors.
Vamsi Nagaraju Thotakura, G. Sri Bala, Ch. Durga Prasad, Gobinath Ravindran, and Monalisa Biswal
Springer Science and Business Media LLC
Prahalad N Tengli, Muntather M. Hassan, R. Gobinath, P. Saravanamoorthi, and Vinod Veeramachaneni
IEEE
Concrete is a building material that is heavily used in construction sector, a significant portion of concrete is composite of aggregate. However, continuous extraction of granite rock for coarse aggregate, raises need for natural resources for upcoming generations. In this work lightweight concrete made of coconut shell is created by substituting convolutional aggregate by coconut shell which is an agricultural waste in used concrete. To improve lightweight concrete's poor mechanical properties, the volume fractions at which a variety of jute fiber components was included like 0%, 0.25%, and 0.50%. The behavior of reinforced concrete using jute fiber was also examined in relation to platiciser (JFRC). Examined were mechanical attributes such impact resistance, elastic modulus, split tensile strength, flexural strength, and compressive strength. Jute fiber has been discovered to be an environmentally friendly biomaterial that can be used to make concrete structures in arid area. Thus, coconut shell combined with jute fiber is appropriate and environmentally responsible substitute for traditional construction material in the industry of construction. Then a test is performed after 28 days based on the mechanical properties and mixing proportion with fiber and coconut shell, according to the test results the strength of the concrete is analyzed by a proposed evaluation model. To evaluate the strength of concrete a Luongo attention based Recurrent Neural Network (L-RNN) is proposed in this research which achieved 0.133 of Root Mean Squared Error (RMSE) which is less than existing methods such as ANN.
Vijay G, R. Gobinath, and Herda Yati Binti Katman
Wiley
The global manufacturing of concrete, which is a highly utilized construction material, is increasingly adopting sustainable construction materials to reduce the carbon footprint. Extensive research is underway to understand this mechanism and to discover alternative materials to meet the demand, bountiful research work is being undertaken and there arises a need to examine the research progress of this domain. Keeping this in mind, this scientometric study examines research trends by analyzing keywords, authorship, cooperation, bibliographic coupling, and production patterns in the field of sustainable concrete development (SCD). From 2018 to 2024, 2051 articles were extracted from the Scopus database and scientometric analysis was performed. From 2009 to 2023, there was a significant increase in publications on SCD, with 2023 having the highest annual publication count (N = 635). The first publication on this topic was published in 1994. 2021 also had the highest number of citations (n = 341), averaging 18.79 per document. The top 3 countries in terms of publishing output were China (1704), India (1391), and Australia (467). The results showed that material science accounted for almost 53.1% of the domain studied, and most of the research on the specified topic came from industrialized nations. This study will help researchers understand the progress of research on SCD and support the development of cooperation among various authors working in this domain.
R. Vandhiyan, K. Rajesh Kumar, and R. Gobinath
Elsevier BV
V. Stephen Pitchaimani, R. J. Jerin Joe, G. Shyamala, G. Manjula, B. Hemalatha, M. Dinesh Babu, S. Shenbaga Ezhil, and Gobinath Ravindran
Springer Science and Business Media LLC
AbstractThis study attempts a detailed assessment of the quality of groundwater in the coastal region of Trivandrum District, Kerala where groundwater is the main source of drinking water. Forty groundwater samples were collected during the pre-monsoon and post-monsoon periods. The collected samples were analyzed for physical properties such as electrical conductivity (EC), pH, total dissolved solids (TDS), and total hardness, along with chemical properties, including major cations (Ca2⁺, Mg2⁺, Na⁺, K⁺) and anions (Cl⁻, SO₄2⁻, HCO₃⁻, NO₃⁻). The analysis of groundwater quality reveals significant spatial and seasonal variations caused by both natural and manmade influences. Water Quality Index (WQI), hydrogeochemical plots, and Principal Component Analysis (PCA) were used to analyses the data. The results show that Vakkom, Kazhakottam, Veli-Attipara, and Pozhiyoor show significant deterioration, and areas such as Varkala, Ayroor, and Edava generally maintain good water quality. The Water Quality Index (WQI) assessment indicates that approximately 22.5% of the studied area falls under excellent quality, while 17.5% is classified as poor. The WHO standard and BSI standards were used to derive the WQI. Principal Component Analysis (PCA) identified electrical conductivity, total dissolved solids, and total hardness as the primary factors affecting groundwater quality, explaining 65.17% and 61.03% of the total variance in the pre-monsoon and post-monsoon periods, respectively. Hydrochemical plots collaborate these results, emphasize the influence of rock-water interactions as the main geochemical process, further compounded by pollution from agricultural runoff and urban development. These findings highlight the need for sustainable groundwater management strategies in coastal communities. Effective measures, including pollution mitigation, sustainable agricultural practice, proper waste management, and preservation of freshwater ecosystems, are essential for ensuring the sustainability of groundwater resources.
Bh Revathi, R. Gobinath, G Sri Bala, T Vamsi Nagaraju, and Sridevi Bonthu
Elsevier BV
T. Vamsi Nagaraju, B.M. Sunil, Babloo Chaudhary, R. Gobinath, and G. Sri Bala
Elsevier BV
Preethi Vijayarengan, Sri Chandana Panchangam, Ananth Stephen, Gokulanandhan Bernatsha, Gokul Krishnan Murali, Subramanyam Sarma Loka, Sathish Kumar Manoharan, Venkatramu Vemula, Rama Rao Karri, and Gobinath Ravindran
Springer Science and Business Media LLC
Pingili Vydehi, Gobinath Ravindran, G. Shyamala, Sri Bala G, Vamsi Nagaraju T, Mallaiah Mekala, and Rama Rao Karri
Elsevier BV
R Gobinath, G.P. Ganapathy, E. Gayathiri, Mehmet Serkan Kırgız, Nihan Naiboğlu, André Gustavo de Sousa Galdino, and Jamal Khatib
CRC Press
E. Gayathiri, R Gobinath, J. Jayanthij, Paniswamy Prakash, and M.G. Ragunathan
CRC Press
R Gobinath, Gayathiri Ekambaram, Paniswamy Prakash, Kumaravel Priya, and Venkata SSR Marella
CRC Press
Thotakura Vamsi Nagaraju, Sunil B. Malegole, Babloo Chaudhary, Gobinath Ravindran, Phanindra Chitturi, and Durga Prasad Chinta
Springer Science and Business Media LLC
Megha Kulkarni, Mohammed H. Fallah, R. Gobinath, Nijaguna G S, and Manohar M
IEEE
Concrete is the most used human-made material that has been utilized in the construction industry. Mix design optimization is difficult due to properties of concrete based on chemical and physical properties of the components as well as their relative proportions. Since number of parameters are comprised in a concrete mix design, identifying an optimal mixing design has always been a challenge for concrete engineers. Hence, this research proposes the Dynamic Adaptive Weighting Sparrow Search Algorithm (DAWSSA) approach for the High Strength Self-Consolidating Concrete mixt design (HSCC). This proposed methodology utilizes the data normalization and data partitioning techniques to normalize the data for enhancing the performance. Then, Best-Worst Method (BWM) approach is accomplished for pairwise comparisons of the quality criteria. The effectiveness of the proposed DAWSSA is estimated by utilizing various error metrices like R-Square (R2), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) of values about 0.86, 1.57 and 2.29 respectively when compared to the previous works such as Multi-objective Salp Swarm Algorithm (MOSSA) and SSA-Extreme Gradient Boosting (SSA-XGB).
Manisha Shewale, P. Murthi, R. Siva Chidambaram, and R. Gobinath
Wiley
The need to improve existing structures has led to extensive research on strengthening techniques. Textile‐reinforced mortar (TRM) systems, which involve the integration of high‐strength fibers with inorganic matrix, have emerged as a highly promising and viable alternative. The objective of this research is to investigate the mechanical characteristics of inorganic mortar by examining different compositions involving sand, fibers, and cementitious materials. Various combinations were tested to evaluate their compressive strength, split tensile strength, and flexural strength. The findings indicated that a composite mixture (sample 12) comprising microsilica, silica sand, and optimized fibers demonstrated enhanced strength in all three assessments. Research highlights the significance of accurate mixing, additional components, and appropriate fibers to achieve intended performance of the mortar. The compatibility of the mortar is checked with substrate surface and textile sheet. Mortar is evaluated for splitting bond strength, slant shear test, direct pull‐off bond strength, and pull‐out strength. These results provide information about the strength and bonding characteristics of the mortar in different test scenarios. Values indicate how well the mortar performs with the substrate surface and the textile sheet under various types of stresses and loading conditions.
S. Padmakala and Gobinath Ravindran
Springer Nature Singapore
Kumar Shubham, Subhadeep Metya, Abdhesh Kumar Sinha, and Ravindran Gobinath
Wiley
This paper presents a thorough reliability assessment of cavity foundation systems involving the generation of 272 datasets using Plaxis 2D automation. The parameters were systematically varied across feasible ranges, and Sobol‐based sensitivity analysis identified the negligible influence of the soil modulus of elasticity (E) on subsequent reliability analyses. A robust 1D‐CNN surrogate model was developed to predict the critical foundation responses by integrating Gaussian white noise to simulate real‐world uncertainties. A log transformation with 1,000 bootstrap samples was chosen for resampling non‐normally distributed data. This study employed a novel approach utilising 1D‐CNN regressor models for bearing capacity (BC) prediction, achieving promising results with R2 values of 0.953 and 0.945 for BC in the training and testing phases, respectively. Bootstrapping resampling facilitates reliability analysis preparation and ensures robustness in handling complex data. Simulated noise varied with specific variance (p) from 0.01 to 0.5, allowing the examination of model efficacy under varying noise levels. Both the Monte Carlo Simulation (MCS) and first‐order reliability method (FORM) were employed, revealing a reliability index (β) of 2.046 for FORM and 2.066 for MCS. This indicates a 0.976% increase in β and a 75% increase in the probability of failure transitioning from FORM to MCS, underscoring the model’s sensitivity to analytical methods.
Sriansh Raj Pradhan, Sushruta Mishra, Hrudaya Kumar Tripathy, Biswajit Brahma, R. Gobinath, and Rajeev Sobti
Springer Nature Singapore
RECENT SCHOLAR PUBLICATIONS
MOST CITED SCHOLAR PUBLICATIONS
RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)
A NOVEL METHOD OF ENHANCE FREEZE-THAW RESISTANCE OF SOIL - Patent application no: 202041005809
A NOVEL METHOD TO PREPARE SELF-COMPACTING CONCRETE USING SINGLE ALKALI ACTIVATED ASH BASED CONCRETE - Patent application no: 202041004257
A NOVEL STRENGTH ENHANCEMENT PROCEDURE FOR NATURAL CURED BINDERLESS CONCRETE- Patent application no:201941042302
A NOVEL METHOD OF WATER CONTENT IDENTIFICATION USING IMAGE PROCESSING FOR LAND SLIDE PRE CURSOR - Patent application no:201941042299
SILICA BASED BINDER COMPOSITION FOR SOIL STABILIZATION AND ENHANCING PAVEMENT LOAD BEARING CAPACITY OF ROADS - Patent application no:201941012760
Industry, Institute, or Organisation Collaboration
Covenant University, Otta, Nigeria
VIT University, Vellore
Anna University, Chennai
Windsor University, Canada