Kilaru Harsha Vardhan
@ssn.edu.in
Associate Professor, Chemical Engineerring Department
Sri Sivasubramaniya Nadar College of Engineering
Dr. Kilaru Harsha Vardhan currently works at the Department of Chemical Engineering, SSN College of Engineering, Chennai and has 25 years of teaching experience at various reputed Engineering Colleges in Tamilnadu. He has completed his Ph.D. in the Chemical Engineering at Anna University, Chennai, M.Tech. in Chemical Engineering from IIT Madras, Chennai and B.Tech. in Chemical Engineering from St. Joseph’s College of Engineering, Chennai. His areas of interest are Environmental Engineering, Process control. He has hands on experience on Chemical Engineering Simulation Softwares like Aspen plus, Hysys, ChemCad and Matlab etc. He has organized a national workshops on Chemcad simulation software and Matlab based Process control. He is a Fellow of The Institution of Engineers ( India) and Life member of ISTE and IIChE.
EDUCATION
Doctor of Philosophy
RESEARCH, TEACHING, or OTHER INTERESTS
Chemical Engineering, Environmental Engineering, Renewable Energy, Sustainability and the Environment, Control and Optimization
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Reshma Bhandari, Kilaru Harsha Vardhan, P. Senthil Kumar, and K. Veena Gayathri
Informa UK Limited
ABSTRACT The marine environment poses a serious threat due to accidental oil spill and industrial discharge specifically from refineries which has become a serious threat to the marine ecosystem. Most of the recalcitrant compounds belong to the group of polyaromatic hydrocarbons. Hence, the present study focuses on biodegradability of simple Polycyclic Aromatic Hydrocarbon (PAH) such as Naphthalene using halotolerant bacterial consortium isolated from oil-spilled environment. Two halotolerant bacterial consortiums were isolated based on the degradation of PAH which measured to be 69.38% by RSKVG1 and 30.61% by RSKVG2 after 96 hours. Naphthalene utilisation was up to 100 mg/L by RSKVG1 and 300 mg/L by RSKVG2. Further, the isolates were optimised for different parameters, optimum NaCl concentration was 30 g/L and 50 g/L by RSKVG1 and RSKVG2, respectively. The functional groups and secondary metabolites produced by the bacterial strains were characterised by FT-IR, HPLC, and GC-MS analysis. Biochemical, morphological and Molecular characterisation, and construction of phylogenetic tree was done which revealed the significant similarity of RSKVG1 and RSKVG2 to Bacillus thuringiensis and Bacillus pacificus respectively. The Naphthalene was also studied for the degradation using the vermiremediation technique.
G. Padmalaya, Kilaru Harsha Vardhan, P. Senthil Kumar, M. Ajmal Ali, and Tse-Wei Chen
Elsevier BV
A. Annam Renita, Kilaru Harsha Vardhan, P. Senthil Kumar, P. Tsopbou Ngueagni, A. Abilarasu, Subi Nath, Pallavi Kumari, and R. Saravanan
Elsevier BV
P. Senthil Kumar, P. Tsopbou Ngueagni, E. Djoufac Woumfo, and Kilaru Harsha Vardhan
Springer Singapore
Kirubanandam Grace Pavithra, P. Senthil Kumar, V. Jaikumar, Kilaru Harsha Vardhan, and PanneerSelvam SundarRajan
Springer Science and Business Media LLC
Rauf Foroutan, Reza Mohammadi, Fariba MousaKhanloo, Soleyman Sahebi, Bahman Ramavandi, Ponnusamy Senthil Kumar, and Kilaru Harsha Vardhan
Elsevier BV
Anbalagan Saravanan, Ponnusamy Senthil Kumar, Kilaru Harsha Vardhan, Sathasivam Jeevanantham, Suresh Babu Karishma, Ponnambalam Ragini Yaashikaa, and Parthasarathy Vellaichamy
Elsevier BV
D. Prabu, P. Senthil Kumar, Kilaru Harsha Vardhan, S. Sathish, Alan Raju, and John Mathew
Desalination Publications
The present research aims to investigate the potential of new biochar prepared from cocoa shell (CS), through the chemical modification method [sulfuric acid-modified CS (SMCS)]. The prepared material was found to possess an excellent adsorption capacity for the elimination of Methylene blue (MB) dye from a polluted environment by experimenting the several operating parameters which include initial dye concentration, contact time, solution pH, temperature and adsorbent dose. SMCS was characterized using scanning electron microscopy-energy dispersive analysis of X-rays, thermo-gravimetric analysis, Fourier transform infrared, and Brunauer–Emmett–Teller analysis. The equilibrium data were best discussed by the Freundlich model. Langmuir model capacity was estimated at 163.5 mg/g for MB dye removal. The feasibility and spontaneous activities of the adsorption process were observed because of the negative values of Gibbs free energy obtained for SMCS-MB dye adsorption system. Pseudo-first-order, pseudo-second-order, and Elovich kinetic models have been tested for kinetic data of SMCS-MB dye system. Pseudo-firstorder model showed good results for SMCS-MB dye system. Through obtained results, it was concluded that the SMCS can act as a potential low cost, environmental friendly, and effective adsorbents and which can be employed as an alternative to various commercial adsorbents.
Kilaru Harsha Vardhan, Ponnusamy Senthil Kumar, and Rames C. Panda
Elsevier BV
K. H. Vardhan, K. H. Vardhan and B. Sarada
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
The main objective of the work is to reduce COD levels of industrial effluents Using Amberlite XAD-1180 in a fluidization reactor. The experiment runs at the flowrates in the range 2 to 8 LPM. The parameters like flow-rate, time & dosage of XAD have been studied and their effect of COD reduction is analysed, for this experiment COD analysis was done for industrial wastewater which is taken from near by industry. The COD reduction increases with increasing flow rate and adsorbent dosage. The maximum percentage COD reduction is found to be 91.56 %. Maximum adsorption occurs at the flow rate of 8 LPM and with 20 gm of XAD adsorbent
Kilaru Harsha Vardhan, Rames C. Panda, and A. Saravanan
Desalination Publications
R. Saravanathamizhan, Kilaru Harsha Vardhan, D. Gnana Prakash, and N. Balasubramanian
Informa UK Limited
AbstractIn this study, response surface methodology (RSM) and artificial neural network (ANN) were employed to develop prediction models for Acid Red 88 dye removal from synthetic wastewater using electro-oxidation. Experiments were carried out in a continuous stirred tank electrochemical reactor (CSTER) in once through approach using Ruthenium oxide-coated Titanium as anode and stainless steel sheet as cathode. The four operational parameters such as, effluent flow rate, initial dye concentration, current density, and pH, on chemical oxygen demand removal has been observed as a response. Experiments were conducted as per RSM of Box–Behnken design. The operating parameters were optimized and the models were developed using RSM and ANN. The ANN model of three hidden layers with two neuron networks, 4-2-2-2-1, matches well with the experimental observation.
C. Sreepradha, A. Krishna Kumari, A. Elaya Perumal, Rames C. Panda, K. Harshabardhan, and M. Aribalagan
Springer Science and Business Media LLC