BITS Faculty Publications

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    Electroosmotic microchannel flow of blood conveying copper and cupric nanoparticles: Ciliary motion experiencing entropy generation using backpropagated networks
    (Wiley, 2024-03) Sharma, Bhupendra Kumar
    A novel mathematical model for a hybrid (Cu–CuO/blood) Jeffrey nanofluid passing a vertical symmetric microchannel along with an electroosmosis pump is presented. The focuses on the advancement of mathematical modeling techniques, its comprehensive analysis of microfluidic system dynamics, and its potential to inform the optimal design of devices using nanofluids with broad applications in various fields. Arrhenius's law is used to analyze endothermic–exothermic reactions and activation energy. The governing partial differential equations of the fixed frame are transformed into ordinary differential equations of the wave frame using self-similarity transformations. Low Reynolds number and long-wavelength approximations helped to find solutions of the equations by applying a suitable BVP solver in MATLAB. The fluid's velocity, temperature, concentration, and electroosmosis properties are studied graphically. Two-dimensional contour plots of fluid velocity and three-dimensional surface plots of fluid properties are discussed. Physically significant quantities of mass transfer rate, skin friction coefficient, entropy generation, and heat transfer rate are studied using contour plots. Artificial neural network simulation using Bayesian regularization backpropagation algorithms is analyzed for training state, error histogram, fit, performance, and regression plots. Conclusively, the comprehensive analysis of the fluid dynamics, entropy generation, mass and heat transfer, and in the microchannel, coupled with the successful implementation of artificial neural network simulation, contributes to an improved understanding of the system's behavior. Entropy generation was raised for enhanced Brownian motion number and reduced values of thermophoresis, activation energy, and endothermic–exothermic reaction parameters. This study's results can be used to improve the efficiency and effectiveness of microfluidic devices used in fields as diverse as electrical cooling and medicine delivery.
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    Computational analysis of entropy generation optimization for Cu–Al2O3 water-based chemically reactive magnetized radiative hybrid nanofluid flow
    (AIP, 2024-07) Sharma, Bhupendra Kumar
    This study aims to analyze the mass transfer and entropy generation in the flow system of chemically reactive, thermal radiative hybrid nanofluids (Al2O3/Cu with H2O as base fluid) flow across flat stretching porous surfaces in the presence of viscous dissipation and transverse magnetic field. The governing partial differential equations are converted into a set of ordinary differential equations by applying a group of self-similarity transformations. The resulting differential equations are solved using the Bvp4c technique in MATLAB. The impact of several physical parameters has been examined the velocity, heat, and mass transfer components of the fluid. To optimize the complete heat transfer process, the consequences of all physical parameters are discussed on entropy generation and Bejan number and presented graphically. It is observed that velocity increases with the increase in magnetic parameter M because pressure force dominates over Lorentz force, temperature increases with the rise of Ec, concertation reduces with the enhancement of chemical reaction parameter delta, and the Bejan number decreases with the increase in Br; however, reverse phenomena are observed with increasing the value of the magnetic number and entropy increases with the rise of magnetic parameter M. Due to the increase in magnetic parameter M, drag force is accelerated, which leads to increase in entropy, With an increment in Pr and Ec, the heat exchange rate declines although the skin friction coefficient and mass transfer remain constant. There are several significant applications of the study of thermal analysis of hybrid nanofluid flows in numerous mechanical processes, such as extrusion or metal manufacturing processes, heat transportation in biological tissues, cooling of electric devices, high-size refrigeration, hydroelectric dams, and fuel systems.
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    Detection of Distributed Denial of Service Attacks Using Entropy on Sliding Window with Dynamic Threshold
    (Springer, 2022-03) Gupta, Vishal
    The Internet has become an integral part of our day-to-day lives, from remaining connected to accessing information from any part of the world. Distributed Denial of service (DDoS) attacks disrupts the normal functioning of the Internet. Because of DDoS attacks, services over the Internet become inaccessible; regular hosts lose connectivity, etc. DDoS attacks are more dangerous because it is not always possible to differentiate whether an organization is under attack or its’ just normal traffic. Therefore, an effective detection mechanism is needed that is computationally less expensive and can detect different types of attacks with good accuracy. Hence, in this paper, we propose Entropy with Dynamic Thresholds to detect DDoS attacks. A dynamic threshold helps us accurately detect an attack in different rates of traffic. To validate our approach, we have used the CICDDoS-2019 attack dataset.
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    Entropy based fuzzy least squares twin support vector machine for class imbalance learning
    (Springer, 2018-06) Richhariya, Bharat
    In classification problems, the data samples belonging to different classes have different number of samples. Sometimes, the imbalance in the number of samples of each class is very high and the interest is to classify the samples belonging to the minority class. Support vector machine (SVM) is one of the widely used techniques for classification problems which have been applied for solving this problem by using fuzzy based approach. In this paper, motivated by the work of Fan et al. (Knowledge-Based Systems 115: 87–99 2017), we have proposed two efficient variants of entropy based fuzzy SVM (EFSVM). By considering the fuzzy membership value for each sample, we have proposed an entropy based fuzzy least squares support vector machine (EFLSSVM-CIL) and entropy based fuzzy least squares twin support vector machine (EFLSTWSVM-CIL) for class imbalanced datasets where fuzzy membership values are assigned based on entropy values of samples. It solves a system of linear equations as compared to the quadratic programming problem (QPP) as in EFSVM. The least square versions of the entropy based SVM are faster than EFSVM and give higher generalization performance which shows its applicability and efficiency. Experiments are performed on various real world class imbalanced datasets and compared the results of proposed methods with new fuzzy twin support vector machine for pattern classification (NFTWSVM), entropy based fuzzy support vector machine (EFSVM), fuzzy twin support vector machine (FTWSVM) and twin support vector machine (TWSVM) which clearly illustrate the superiority of the proposed EFLSTWSVM-CIL
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    Entropy production in active Rouse polymers
    (IOP, 2023-03) Dutta, Sandipan
    Active polymers are the archetype of nonequilibrium viscoelastic systems that constantly consume energy to produce motion. The activity of many biopolymers is essential to many life processes. The entropy production rate quantifies their non-equilibrium nature through the breaking of the time reversal symmetry. In this work we build an analytical model of active polymers as active Rouse polymers where the beads are active OrnsteinUhlenbeck particles (AOUP) and calculate their entropy production. The interactions between the beads are decoupled through the normal mode analysis and the entropy production can be solved analytically. We obtain the contribution of each Rouse mode in the entropy production and the dependence of the entropy production on the polymer properties like length. We find that the entropy production is zero for a passive Rouse polymer in the presence of thermal bath as well as for an active Rouse polymer in the absence of thermal bath. For an active chain in the presence of a thermal bath the entropy production is non-zero. In this case we find that the local temporal entropy production dominates the non-local entropy production.
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    Colossal Power Extraction from Active Cyclic Brownian Information Engines
    (ACS, 2022-07) Dutta, Sandipan
    Brownian information engines can extract work from thermal fluctuations by utilizing information. To date, the studies on Brownian information engines consider the system in a thermal bath; however, many processes in nature occur in a nonequilibrium setting, such as the suspensions of self-propelled microorganisms or cellular environments called an active bath. Here, we introduce an archetypal model for a Maxwell-demon type cyclic Brownian information engine operating in a Gaussian correlated active bath capable of extracting more work than its thermal counterpart. We obtain a general integral fluctuation theorem for the active engine that includes additional mutual information gained from the active bath with a unique effective temperature. This effective description modifies the generalized second law and provides a new upper bound for the extracted work. Unlike the passive information engine operating in a thermal bath, the active information engine extracts colossal power that peaks at the finite cycle period. Our study provides fundamental insights into the design and functioning of synthetic and biological submicrometer motors in active baths under measurement and feedback control.
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    The probability analysis of opening of DNA
    (AIP, 2011-03) Singh, Navin
    We have studied the separation of a double stranded DNA (dsDNA), which is driven by either the temperature or force. By monitoring the probability of opening of entire base pairs along the chain, we show that the opening of a dsDNA depends not only on the sequence but also on the constraints on the chain in the experimental setups. Our results clearly demonstrate that the force-induced melting of dsDNA, whose one of the ends is constrained, is significantly different from the thermal melting, when both ends are free.
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    The effect of circular hole spring tape on the turbulent heat transfer and entropy analysis in a heat exchanger tube: an experimental study
    (Taylor & Francis, 2020-07) Bhattacharyya, Suvanjan
    The current paper is focused on the experimental investigation of the turbulent forced convection with circular-hole spring tape (CHST) inserts in a circular tube. The CHST inserts with different hole and spring ratios, are investigated for a wide ranges of Reynolds number (10,000–50,000). Results show that use of CHST provides an increase in heat transfer by 35% and 51% when assessed with other inserts and plain tube, respectively. Furthermore, an entropy generation study shows that the irreversibility rises significantly with the increase of diameter ratio and Reynolds number. The overall enhancement ratio has been evaluated to study the effect of the CHST. The thermo-hydraulic performance are approximately more than unity for all the cases which indicates that the consequence of HT augmentation due to the augmenting apparatus is more governing than the consequence of the growing friction penalty. Thermo-hydraulic performance of c = 0, y = 1.5 (maximum value) is 25% higher than c = 0.6, y = 3.0 (minimum value). A predictive Nusselt number and friction factor correlations are also developed.
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    Entropy Analysis for MHD Flow Subject to Temperature-Dependent Viscosity and Thermal Conductivity
    (Springer, 2022-10) Sharma, Bhupendra Kumar
    This research aimed to figure out how to optimise the entropy of MHD flow past a continuously stretching surface. The effect of temperature-dependent variables viscosity and electric conductivity has been taken into account. The fluid region is subjected to a uniform magnetic field. By using similarity analysis, the governing coupled partial differential equations (PDEs) that describe the model are turned into non-linear ordinary differential equations and then computed by employing “BVP4C” in MATLAB software. The effect of various pertinent parameters like Magnetic field parameter M, radiation parameter R, Grashof number Gr, Brinkman number Br, Reynold number Re, and a variation of variables viscosity ϵ1 and electric conductivity ϵ2 is analysed and presented graphically on velocity, temperature, entropy, and concentration profile. The comparison is based on previously published studies, and there is a considerable deal of agreement.