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The combined use of anticorrosive and load carrying additives in industrial and automotive lubricants has been well known for many years. In some cases, the same additive has been claimed to act both for load carrying and anticorrosive properties. The synergistic and antagonistic effects of various chemicals involved in lubricant system employing both these two types of additives are the subjects of present interest.

The purpose of this paper is to evaluate various reliability measures like reliability, expected lifetime (mean time to failure), signature reliability and compare networks based on the different flows.

The reliability characteristics of complex bridge networks have been evaluated using different algorithms with the help of universal generating function (UGF). Further, the signature reliability of the considered networks has been determined using Owen’s method.

The present paper proposes an efficient algorithm to compute the reliability indices of complex bridge networks having i.i.d. lifetime components (nodes, edges) with the help of UGF and Owen’s method. This study reveals that a slight change in the complex bridge network affects the reliability significantly. Finally, by the reliability structure function, proposed algorithms are used to find the signature and MTTF. From signature, we have determined the different failure probabilities corresponding to edges of the network.

In this work, we have evaluated reliability characteristics and signature reliability of the complex bridge networks using UGF method and Owen’s method respectively unlike done in the past.

The main purpose of this study is to present a non-similar analysis of two-dimensional boundary layer flow of non-Newtonian nanofluid over a vertical stretching sheet with variable thermal conductivity. The Sisko fluid model is used for non-Newtonian fluid with an exponent (n* > 1), that is, shear thickening fluid. Buongiorno model for nanofluid accounting Brownian diffusion and thermophoresis effects is used to model the governing differential equations.

The governing boundary layer equations are converted into nondimensional coupled nonlinear partial differential equations using appropriate transformations. The resultant differential equations are solved numerically using implicit finite difference scheme in association with the quasilinearization technique.

This analysis shows that the temperature raises for thermal conductivity parameter and velocity ratio parameter while decreases for the thermal buoyancy parameter. The thermophoresis and Brownian diffusion parameter that characterizes the nanofluid flow enhances the temperature and reduces the heat transfer rate. Skin friction drag can be effectively reduced by proper control of the values of thermal buoyancy and velocity ratio parameter.

The wall heating and cooling investigation result in the analysis of the control parameters that are related to the designing and manufacturing of thermal systems for cooling applications and energy harvesting. These control parameters have practical significance in the designing of heat exchangers and solar thermal collectors, in glass and polymer industries, in the extrusion of plastic sheets, the process of cooling of the metallic plate, etc.

To the best of authors’ knowledge, it is found from the literature survey that no similar work has been published which investigates the non-similar solution of Sisko nanofluid with variable thermal conductivity using finite difference method and quasilinearization technique.

The purpose of this study is to provide a numerical investigation of Casson nanofluid along a vertical nonlinear stretching sheet with variable thermal conductivity and viscosity.

The boundary-layer equations are presented in the dimensionless form using proper non-similar transformations. The subsequent non-dimensional nonlinear partial differential equations are solved using the implicit finite difference technique. To linearize the nonlinear terms present in these equations, the quasilinearization technique is used.

The investigation showed graphically the temperature, velocity and nanoparticle volume fraction for particular included physical parameters. It is observed that the velocity profile decreases with an increase in the values of Casson fluid parameter while increases with an increase in the viscosity variation parameter. The temperature profile enhances for large values of velocity variation parameter and thermal conductivity parameter while it reduces for large values of thermal buoyancy parameter. Further, the Nusselt number and skin-friction coefficient are introduced which are helpful in determining the physical aspects of Casson nanofluid flow.

The immediate control of heat transfer in the industrial system is crucial because of increasing energy prices. Recently, nanotechnology is proposed to control the heat transfer phenomenon. Ongoing research in complex nanofluid has been fruitful in various applications such as solar thermal collectors, nuclear reactors, electronic equipment and diesel–electric conductor. A reasonable amount of nanoparticle when added to the base fluid in solar thermal collectors serves to deeper absorption of incident radiation, and hence it upgrades the efficiency of the solar thermal collectors.

The non-similar solution of Casson nanofluid due to a vertical nonlinear stretching sheet with variable viscosity and thermal conductivity is discussed in this work.

To find the reliability characteristics of repairable weighted (u, v)- out-of-(x, y) system using the interval valued universal generating function (IUGF).

In this paper (u, v)-out-of-(x, y) system is an extension of the k-out-of-n system. Here, the interval valued universal generating function (UGF) is present and the corresponding operators are defined.

The present paper proposes a interval valued universal generating function (IUGF) to compute the reliability indices of the considered system. The current study investigates the reliability and sensitivity of the proposed system with respect to system parameters by applying Markov process with the help of the interval valued UGF approach.

In this work, the considered system, i.e. repairable weighted (u, v)-of-the- (x, y) is the extension of k-out-of-n system for the assessment of reliability characteristics using the interval valued UGF.

This paper aims to achieve accurate maximum power from solar photovoltaic (PV), its five parameters need to be estimated. This study proposes a novel optimization technique for parameter estimation of solar PV.

To extract optimal parameters of solar PV new optimization technique based on the Jellyfish search optimizer (JSO). The objective function is defined based on two unknown variables and the proposed technique is used to estimate the two unknown variables and the rest three unknown variables are estimated analytically.

In this paper, JSO is used to estimate the parameters of a single diode PV model. In this study, eight different PV panels are considered. In addition, various performance indices, such as PV characteristics, such as power-voltage and current-voltage curves, relative error (RE), root mean square error (RMSE), mean absolute error (MAE) and normalized mean absolute error (NMAE) are determined using the proposed algorithm and existing algorithms. The results for different solar panels have been obtained under varying environmental conditions such as changing temperature and constant irradiance or changing irradiance and constant temperature.

The proposed technique is new and provides better results with minimum RE, RMSE, NMAE, MAE and converges fast, as depicted by the fitness graph presented in this paper.

The purpose of this paper is to study the antirust, tribological performance and anti-wear (AW) mechanism of the of soybean lecithin (SL) as a kind of multifunctional lubricant additive.

As a kind of multifunctional lubricant additive, the antirust performance of SL was tested according to ASTM D 665, and meanwhile, its tribological performances were also evaluated by Optimol SRV-I oscillating reciprocating friction and wear tester and four ball tester. The worn steel surfaces were investigated by scanning electron microscope (SEM) and X-ray photoelectron spectroscopy (XPS).

The results showed that the SL exhibited excellent antirust properties in different base stock, and could effectively improve the AW and extreme pressure (EP) performances. The results of SEM and XPS indicated that a protective film was formed between steel-steel friction pair during the tribological test.

This paper first investigated the antirust properties and the tribological mechanism of the SL as a kind of multifunctional lubricant additive, which can be very useful and will promote the application of SL in lubricant industry.

A significant increase in the number of private sector banks has intensified the level of competition in the Indian banking industry (IBI). This increase in the number of banks has a considerable impact on the existing players, which calls for prioritizing customer satisfaction (CS) and enhancing bank reputation (BR). Our study seeks to investigate the enablers of CS and BR in the IBI.

The study adopted a cross-sectional design for gathering responses from retail bank customers across the selected banks through a structured questionnaire. Structural equation modeling (SEM) was utilized to evaluate direct and indirect linkages among the identified constructs by examining mediating and moderating effects.

The study puts forward crucial antecedents of CS and BR. The findings exhibit that perceived trust (PT) and relationship commitment (RC) magnify CS and BR, respectively, while CS amplifies repurchase intention (RI). The study advances that BR and CS partially mediate between the underlying constructs. In addition, fairness and risk exhibit moderating effects between CS and customer repurchase intention (CRI) and BR and CRI.

The study illustrates the crucial enablers of BR, CS and CRI that may assist banking professionals in enriching customer experience and holding on to their customers.

There is a shortage of research on RC, service innovation (SI) and BR in the IBI. Accordingly, our study builds on the prior studies by considering these constructs using a comprehensive conceptual framework by extending the application of signaling theory (ST) in the banking domain and scrutinizing the dual moderating effects of fairness and risk.

The present paper focuses on the evaluation of reliability and its characteristics (Mean time to failure and Sensitivity) of a k-out-of-n network.

The minimal cuts of the network have been evaluated for different nodes in this paper, using an algorithm. With the help of these cuts, reliability and its characteristics are obtained using Gumbel–Hougaard family of the copula.

The present paper proposes to compute the reliability and its measures of the k-out-of-n network using the minimal cuts and copula methodology. The completely failed nodes of the network have been repaired using Gumbel–Hougaard family of the copula.

In this paper, the reliability of a k-out-of-n network has been evaluated by first calculating k-out-of-n minimal cuts, and the failed nodes have also been repaired using Gumbel–Hougaard family of the copula, unlike as done in the past.

The purpose of this paper is to provide a better method for quality management to maintain an essential level of quality in different fields like product quality, service quality, air quality, etc.

In this paper, a hybrid adaptive time-variant fuzzy time series (FTS) model with genetic algorithm (GA) has been applied to predict the air pollution index. Fuzzification of data is optimized by GAs. Heuristic value selection algorithm is used for selecting the window size. Two algorithms are proposed for forecasting. First algorithm is used in training phase to compute forecasted values according to the heuristic value selection algorithm. Thus, obtained sequence of heuristics is used for second algorithm in which forecasted values are selected with the help of defined rules.

The proposed model is able to predict AQI more accurately when an appropriate heuristic value is chosen for the FTS model. It is tested and evaluated on real time air pollution data of two popular tourism cities of India. In the experimental results, it is observed that the proposed model performs better than the existing models.

The management and prediction of air quality have become essential in our day-to-day life because air quality affects not only the health of human beings but also the health of monuments. This research predicts the air quality index (AQI) of a place.

The proposed method is an improved version of the adaptive time-variant FTS model. Further, a nature-inspired algorithm has been integrated for the selection and optimization of fuzzy intervals.