High-Temperature Friction and Wear of Boron Steel and Tool Steel in Open and Closed Tribosystems

More and more components in automotive, material processing, and mining industries are operating under harsh conditions involving high temperatures and high contact pressures. Tribotesting for such applications is done using both open (one surface meeting a fresh countersurface) and closed (one surface follows the same track on the countersurface) test configurations. In order to enable development of new materials and processes intended for such conditions, there is a need for better understanding pertaining to tribological phenomena occurring under these different test configurations.

In this work, friction and wear characteristics of quenched and tempered tool steel sliding against boron steel (22MnB5) have been studied. The experiments were conducted using a specially designed hot strip tribometer (HST) under dry conditions at room temperature and 400°C in open as well as closed configurations. Scanning electron microscopy/energy-dispersive spectroscopy, and X-ray techniques were carried out to analyze the worn surfaces. Additionally, the results from the closed test configuration were compared to previous tests carried out with the same materials and parameters using a pin-on-disk (POD) test rig. The results have shown that wear was reduced at higher temperatures as well as with repeated sliding on the same contacting surfaces (i.e., closed configuration) compared to those with an open configuration. A good correlation of wear mechanisms and coefficient of friction between closed configuration tests and those carried out with the POD test rig were observed especially at 400°C.     

Theoretical Analysis of Thermal Stresses in Electro-discharge Diamond Grinding

Excessive heat generated at the machining zone, during Electro-discharge diamond grinding (EDDG), is the major cause of thermal stresses, untempered martensite, overtempered martensite, and cracks. Therefore, the key to achieve good surface integrity in a machined part is to prevent excessive temperature and thermal stresses generated during machining process. A finite element model has been developed to estimate thermal stresses during EDDG when the current is switched-off. First, the developed code calculates the temperature in the workpiece and then the thermal stress field is estimated using this temperature field. Computations were carried out in plane strain condition for different down feeds of the grinding wheel. The effects of time of grinding and feed on thermal stress distribution have been reported. The thermal stresses are found to be higher near top surface at initial time of grinding but shifted away towards bottom after some grinding time.     

Quadratic Discriminant Analysis Based Ensemble Machine Learning Models for Groundwater Potential Modeling and Mapping

In this study, the AdaBoost, MultiBoost and RealAdaBoost methods were combined with the Quadratic Discriminant Analysis method to develop three new GIS-based Machine Learning ensemble models, i.e., ABQDA, MBQDA, and RABQDA for groundwater potential mapping in the Dak Nong Province, Vietnam. In total, 227 groundwater wells and 12 conditioning factors (infiltration, rainfall, river density, topographic wetness index, sediment transport index, stream power index, elevation, aspect, curvature, slope, soil, and land use) were used for this study. Performance of the models was evaluated using the Area Under the Receiver Operating Characteristics Curve AUC (AUC) and several other performance metrics. The results showed that the ABQDA model that achieved AUC?=?0.741 was superior to the other models in producing an accurate map of groundwater potential for the Dak Nong Province. The models and potential maps produced here can help policymakers and water resources managers to preserve an optimal exploit from these vital resources.

     

Benevolent behavior ofKleinia grandifloraleaf extract as a green corrosion inhibitor for mild steel in sulfuric acid solution

The ethanolic extract of Kleinia grandiflora leaves was characterized and tested for its potential anticorrosion properties on mild steel in 1 M H2SO4 medium using mass-loss analysis, potentiodynamic polarization measurements, electrochemical impedance spectroscopy, Fourier-transform infrared spectroscopy, scanning electron microscopy, UV–visible spectroscopy, and X-ray diffraction analysis. The effect of temperature on the corrosion behavior of mild steel was studied in the range of 308 to 328 K. The inhibition efficiency was observed to increase with increasing concentration of the extract. Polarization curves revealed that the Kleinia grandiflora leaf extract is a mixed inhibitor. Impedance diagrams revealed that an increase of Kleinia grandiflora leaf extract concentration increased the charge transfer resistance and decreased the double-layer capacitance. The adsorption process obeys Langmuir＇s model, with a standard free energy of adsorption（ΔGads） of-18.62 k J/mol. The obtained results indicate that the Kleinia grandiflora leaf extract can serve as an effective inhibitor for the corrosion of mild steel in a sulfuric acid medium.     

Minimum assured fidelity and minimum average fidelity in quantum teleportation of single qubit using non-maximally entangled states

We study use of non-maximally entangled states (NME) in quantum teleportation (QT) of single qubit. We find that if NME states are written in the form ${| E \rangle =\sum_{j,k} {E_{jk} | j \rangle | k \rangle}}$ , where (j, k) = 0 and 1, and maximally entangled Bell-basis is used in measurement by the sender, the ??Minimum Assured Fidelity?? (the minimum value of fidelity for all possible information states) for QT is 2C/(1?+?C), where C is the concurrence of ${| E \rangle }$ given by C?=?2|det (E)| and E is the matrix defined by the coefficients E _jk . We also find the average of fidelity over various results of Bell-state measurement and its minimum value over all possible information states and discuss it for some special cases. We also show that, to evaluate quality of imperfect QT, minimum assured fidelity is a better measure than concurrence or minimum average fidelity.     

Robust Model Reference Adaptive Intelligent Control

In this paper a Neural Network based Model Reference Adaptive Control scheme (NNMRAC) is proposed. In this scheme, the controller is designed by using parallel combination of the conventional Model Reference Adaptive Control (MRAC) scheme and Neural Network (NN) controller. In the conventional MRAC scheme, the controller is designed to realize plant output converging to reference model output based on the plant which is linear. This scheme is used to control linear plant effectively with unknown parameters. However, it is difficult for a nonlinear system to control the plant output in real time applications. In order to overcome the above limitations, the NN-MRAC scheme is proposed to improve the system performances. The control input of the plant is given by the sum of the MRAC output and NN controller output. The NN controller is used to compensate the nonlinearities and disturbances of the plant that are not taken into consideration in the conventional MRAC. The simulation results clearly show that the proposed NN-MRAC scheme have better steady state and transient performances than those of the current adaptive control schemes. Thus, the proposed NN-MRAC scheme named as Robust Model Reference Adaptive Intelligent Control (RMRAIC) is found to be extremely effective, efficient and useful in the field of control system.     

An outcome of quaternary fuel blended Fe3O4-doped reduced graphene oxide nanocomposite on the diesel engine

The study includes the use of alcohols in conjunction with diesel as a binary fuel and biodiesel. In addition, this study was conducted on quaternary fuels (premium diesel, waste cooking biodiesel, n-butanol, and bioethanol), including Fe₃O₄ (iron(III) oxide)-doped reduced graphene oxide (rGO) nanocomposite to reduce the use of fossil fuels, their cost, and energy demand. It includes 10% bioethanol, 5%–20% n-butanol, 25 ppm Fe₃O₄-doped rGO nanocomposite, and 20% and 100% waste cooking biodiesel, all of which have been tested in a diesel engine to ensure that they are suitable for use. The findings were compared to those obtained with premium diesel, ranging from 50% to 100% at full engine load conditions. In comparison to 100% premium diesel fuel, the fuel blend (Blend G) had 37.50% brake thermal efficiency and 0.46% (brake-specific energy consumption), as well as lower rates of 316.2% carbon monoxide, 198.80% hydrocarbon, and 80.01% smoke with 28.10% higher oxides of nitrogen (NOx). Adding 20% n-butanol to premium diesel, as well as waste cooking biodiesel, bioethanol, and Fe₃O₄-doped rGO nanocomposite fuel blends, was used in this study to improve the performance of the diesel engine and reduce some of the NOx emissions. In the near future, these fuel blends may be a viable alternative combination for the diesel engine.     

Study of a nonuniform heat source over a Riga plate using nth-order chemical reaction on Oldroyd-B nanofluid flow for two-dimensional motion

A variety of fluid models are proposed, due to the uncertain flow diversity and rheological features of non-Newtonian fluids, out of which, viscoelastic Oldroyd-B nanofluid is considered here with a nonuniform heat source over a Riga plate using an nth-order chemical reaction. The ever increasing demand for chemical reactions in hydrometallurgical, chemical, and biomedical industries necessitates studying the behavior of heat and mass transfer in the presence of chemical reaction; a few of its applications are manufacturing of glassware or ceramics, food processing, polymer production, particulate water inflows, dehydration and drying operations in the chemical industry, and numerous applications in agricultural fields and many branches of engineering and sciences. To solve the set of nonlinear DEs, which are found after applying a suitable transformation on the governing nonlinear PDEs, a robust numerical technique, such as the fourth-order Runge–Kutta method, is employed in the current motion problem. Also, the influences of all substantial thermophysical parameters are discussed graphically and analytically. Furthermore, the major outcomes of the results are: attenuation in the relaxation time leads to a rise in the fluid momentum significantly near the wall and the solutal profile retards with an enhanced Brownian motion that results in the retardation in the bounding surface thickness of the profile.