Faculty Publications

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    A novel procedure for determination of hydrodynamic pressure along upstream face of dams due to earthquakes
    (2010) Gogoi, I.; Maity, D.
    The estimation of hydrodynamic pressures along the upstream face of the dam is a critical parameter for the accurate analysis and design of a dam. The accurate estimation of the hydrodynamic pressures necessitates the consideration of interaction between the dam, the reservoir and the foundation. The interaction effects of the unbounded domain of the reservoir and the absorptive materials deposited at the reservoir bottom are frequency dependent which can be incorporated in a frequency domain procedure easily. But in a time domain procedure the frequency dependent interaction effects are lost. In a frequency domain solution, the excitation frequencies are extracted from the earthquake signal using a Fourier transformation, but do not give any information about how it varies with time. To overcome this, a short-time Fourier transform based formulation is presented in this paper to evaluate the hydrodynamic pressures in time domain to account for the frequency dependent interaction effects of the dam-reservoir system. Thus, the adequate accuracy in the determination of hydrodynamic pressure under earthquake excitation is ensured with the proposed truncation boundary condition. © 2010 Elsevier Ltd. All rights reserved.
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    Predicting compressive strength of SCC mixtures using artif icial neural network
    (2012) Rame Gowda, M.; Narasimhan, M.C.; Karisiddappa; Kumuda, T.
    Over the last few years, the use of artificial neural networks (ANNs) has increased in many areas of engineering. In particular it is increasingly being used in concrete engineering problems. Since accurate estimation of compressive strength of self-compacting concrete (SCC) is an important issue in concrete engineering this paper describes the development of ANN models based on laboratory SCC mixes. The multilayer feed-forward type network models were trained using the back-propagation method with a momentum factor. The data obtained from the mix design exercises were employed to develop and test the performance of the models. A new concept of using more than one error statistic resulted in efficiently training the models and improving its generalization capability.
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    Estimation of dew point temperature using SVM and ELM for humid and semi-arid regions of India
    (Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2018) Deka, P.C.; Patil, A.P.; Yeswanth Kumar, P.; Naganna, S.R.
    The dew point temperature is the temperature at which the moisture in the air begins to condense into dew or water droplets. The accurate estimation of the dew point temperature is very important as it controls the heat stress on humans, detects fluctuations of evaporation rates, and humidity trends. The dew point temperature is a significant parameter particularly required in various hydrological, climatological and agronomical related researches. This study proposes Support Vector Machine (SVM) and Extreme Learning Machine (ELM) models for the estimation of daily dew point temperature. The daily measured weather data (Wet bulb temperature, relative humidity, vapor pressure and dew point temperature) of humid and semi-arid regions of India were used for model development. The statistical indices, namely Mean Absolute Error, Root Mean Square Error, and Nash Sutcliffe Efficiency were adopted to evaluate the performances of these two models. The merit of the ELM model is evaluated against SVM technique in the estimation of dew point temperature. The proposed ELM models demonstrated much greater capability than the SVM models in the estimation of daily dew point temperature. © 2017 Indian Society for Hydraulics.
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    A combined ANN-GA and experimental based technique for the estimation of the unknown heat flux for a conjugate heat transfer problem
    (Springer Verlag service@springer.de, 2018) Kumar, M.K.; Vishweshwara, P.S.; Gnanasekaran, N.; Balaji, C.
    The major objectives in the design of thermal systems are obtaining the information about thermophysical, transport and boundary properties. The main purpose of this paper is to estimate the unknown heat flux at the surface of a solid body. A constant area mild steel fin is considered and the base is subjected to constant heat flux. During heating, natural convection heat transfer occurs from the fin to ambient. The direct solution, which is the forward problem, is developed as a conjugate heat transfer problem from the fin and the steady state temperature distribution is recorded for any assumed heat flux. In order to model the natural convection heat transfer from the fin, an extended domain is created near the fin geometry and air is specified as a fluid medium and Navier Stokes equation is solved by incorporating the Boussinesq approximation. The computational time involved in executing the forward model is then reduced by developing a neural network (NN) between heat flux values and temperatures based on back propagation algorithm. The conjugate heat transfer NN model is now coupled with Genetic algorithm (GA) for the solution of the inverse problem. Initially, GA is applied to the pure surrogate data, the results are then used as input to the Levenberg- Marquardt method and such hybridization is proven to result in accurate estimation of the unknown heat flux. The hybrid method is then applied for the experimental temperature to estimate the unknown heat flux. A satisfactory agreement between the estimated and actual heat flux is achieved by incorporating the hybrid method. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
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    Accurate estimation of decay coefficients for dynamic range compressors in hearing aids and a hardware level comparison of different architectures
    (Elsevier B.V., 2020) Deepu, S.P.; Ramesh Kini, M.R.; Sumam David, S.S.
    Dynamic Range Compression (DRC) algorithm helps to protect the residual hearing ability of hearing aid users by compressing the signal levels which go above a particular threshold. This paper addresses two different aspects of DRC for hearing aid applications. In the first part, methods to estimate the decay coefficients corresponding to the required time constants for a feed-forward DRC architecture accurately, to meet the hearing aid specifications are proposed. The effect of compression on the attack and release time parameters are compensated with the new formula. The hardware implementation of four different DRC architectures is explained in the second part of the paper. The estimated decay coefficients for a test signal were used for the corresponding hardware implementations and verified the validity of proposed algorithmic modifications. The architectures were implemented using UMC 65 nm standard cell libraries and the power and error results were compared. The proposed methods to estimate the decay coefficients for both attack and release phases show close to 0 dB error from expected output values, while conventional methods are not meeting the specifications. Hardware implementation shows that there is not much improvement in power performance, between a lower resolution Look-Up Table (LUT) based logarithm implementation and a higher resolution one. From the results, we propose using the absolute level detector based DRC with higher resolution logarithm without a gain smoothing stage at the output for lowest power consumption and better approximation error performance. © 2020 Elsevier B.V.
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    Heat Transfer During Solidification of Polyethylene Terephthalate (PET) in Injection Molding
    (Springer, 2024) Kamala Nathan, D.K.; Prabhu, K.N.
    In injection molding, heat transfer at the polymer/mold interface during solidification of the polymer significantly affects the cooling rate, microstructure, and hence the product quality. An accurate estimation of the boundary heat flux transients is essential for the successful simulation of polymer solidification, which can aid in predicting and preventing potential defects that may arise from improper filling and cooling. Simulation studies also help in optimizing the cycle time with different process parameters. In the present work, a pneumatically-operated injection molding machine capable of producing a single component in one cycle was designed and fabricated in-house to estimate the heat flux transients at the polymer/mold interface. The mold used for solidification of the polymer was made from tool steel (P20) with a simple rectangular cavity. The mold was instrumented with thermocouples across the thickness to record its thermal history during injection molding. The polymer/mold interfacial heat flux transients were estimated by solving an inverse heat conduction problem (IHCP). The temperature measured at locations beneath the cavity surface inside the mold was used as an input to the inverse solver. Altering the melt injection and mold temperatures showed negligible effects on heat flux transients at the polymer/mold interface. The estimated solidification time for the polymer sample was about 2 s. © The Indian Institute of Metals - IIM 2024.