Faculty Publications

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Author: search.filters.author.Kamath, N.Subject: search.filters.subject.Performance

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    Experimental investigation and optimization of performance, emission, and vibro-acoustic parameters of SI engine fueled with n-propanol and gasoline blends using ANN-GA coupled with NSGA3-modified TOPSIS hybrid approach
    (Elsevier Ltd, 2024) Kirankumar, K.R.; Kumar, G.N.; Kamath, N.; Gangadharan, K.V.
    In the present study, performance, emission, and vibro-acoustic studies were conducted on a spark ignition (SI) engine fueled with gasoline and an n-propanol blend at variable compression ratio (CR), speed, and propanol blend fraction (PBF). Experimental data were used to model an artificial neural network (ANN) trained with a genetic algorithm (GA). ANN predictive responses were employed to establish regression relationships between brake power (BP), brake specific fuel consumption (BSFC), brake thermal efficiency (BTE), oxides of nitrogen (NOx), carbon monoxide (CO), hydrocarbon (HC), resultant vibration acceleration (RVA), and sound pressure level (SPL) with operating parameters using response surface methodology (RSM). These models served as objective functions in the non-dominated sorting genetic algorithm-3 (NSGA3), a multi-objective optimization (MOO) technique, to optimize responses and obtain non-dominated solutions. These solutions were filtered using a modified technique for order preference by similarity to the ideal solution (TOPSIS) to obtain a compromised optimal solution. ANN-GA model outcomes showed high accuracy, with coefficient of determination (R2) and root mean square error (RMSE) values ranging from 0.979 to 0.993 and 0.0381 to 0.0643, respectively. NSGA3 coupled with modified TOPSIS identified optimal operating conditions at 1271.77 RPM, a CR of 11.96, and a PBF of 33.26 %. © 2024 Elsevier Ltd
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    Implementation of model free fuzzy control on a novel magnetorheological elastomer-based handle for a rotary hammer
    (Institute of Physics, 2025) Kamath, N.; Shenoy, K.; Susheelkumar, G.N.; Gangadharan, K.V.
    This study presents a novel application of a Magnetorheological Elastomer-based handle (MREH) designed to improve the user’s comfort, specifically by reducing hand-arm vibrations. Various control logics were used on the MREH system attached to a rotary hammer to fully utilize the ability to adapt to various operating conditions, and each logic’s performance was evaluated. On/Off, PID, and fuzzy methods have been implemented in real-time. A case-based control logic where the frequency of the rotary hammer is given as an input to the control logic is developed to reduce the decision time as the events occur at a higher rate for on/off and fuzzy. PID gains are obtained directly from the experimental setup through PID autotuning. The performance of these logics is evaluated by performing a drilling operation on a M45 concrete block. Further, the fuzzy logic is investigated by operating at different locations on the same block. Based on the present research, fuzzy logic has demonstrated superior performance in aligning with the system by exhibiting a maximum 3 Hz increase from the natural frequency © 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.