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Anisotropic characteristics of granular soil consolidated to various initial stress states were evaluated under generalized strain paths using hollow cylinder torsional shear tests. Fraser River sand samples prepared by water pluviation were subjected to isotropic and anisotropic consolidation stresses, and sheared undrained along strain paths with constant intermediate principal strain parameter and various principal strain directions. Anisotropic stress response and stress-strain trends were examined by controlling the orientation of principal strains (αε) with respect to the depositional axis. A decrease in strain hardening tendency is observed as the major principal strain rotates towards the bedding plane. Considering different levels of anisotropic consolidation stresses also allowed a detailed examination of how initial static shear affects the responses. In particular, generated principal stresses and their directions, as well as the pore pressure responses, were closely examined. Novel findings are presented on the range of intermediate principal stress parameters (bσ) associated with the undrained plane strain condition where a value of bσ in the range of 0.2–0.4 was found to correspond to plane strain conditions. [ABSTRACT FROM AUTHOR]

In the present study, performance of the fabricated evacuated U-tube solar collector integrated parabolic reflector (EUSCIPR) and conventional evacuated U-tube solar collector (CEUSC) are analysed experimentally. With reference to humid climatic conditions, a 3D model is developed for comparing the thermal performance of EUSCIPR with a CEUSC. Developed model is validated with field test data and found in good agreement among them. Heat transfer fluid (HTF) temperature difference, energy intake/heat gain and thermal efficiency of the solar collectors are investigated experimentally at various ambient temperatures and solar intensities. From the experimental investigations, it was observed that, in a sunny day, the energy losses incurred across the solar collectors was high during peak hour (1: 20 PM). From the numerical studies, it is found that within the given operating range, the thermal efficiency of the EUSCIPR is 14.1% higher than CEUSC. Further, for a given inlet condition, the contour plots for variation of HTF temperature along the U-tube of EUSCIPR and CEUSC are predicted numerically, and the obtained results are discussed in detail. [ABSTRACT FROM AUTHOR]

In single stage operation, high quality separation of similar size proteins was performed via batch ultrafiltration. Two permeable proteins, hemoglobin and ovalbumin, were separated using a 100 kDa polyethersulfone membrane for a volume concentration factor of 3.5. At low ionic strength, hemoglobin and ovalbumin showed their enhanced reverse selectivity of 11 and selectivity of 14 at pH 9 and 3.5, respectively. Protein adsorption on the membrane during ultrafiltration was carefully controlled by fine adjustment of pH and ionic strength of feed. The high separation factor was achieved as a result of pore constriction by protein adsorption and the electrostatic interaction between proteins and the membrane. [ABSTRACT FROM PUBLISHER]

The objective of this research work is to optimise the injection parameters for a diesel engine in the modified re-entrant chamber and the conventional chamber using jatropha methyl ester blends by incorporating the optimisation techniques through the statistical analysis methods. In this work, a re-entrant combustion chamber and the conventional combustion chamber, with fuel injection timings of 19, 23, and 27 degrees before top dead centre, and the fuel injection pressures of 200, 220 and 240 bars have been used for J20 and J30. At the different injection conditions, eighteen experiments were conducted for two different chambers for J20 well as J30. To find the best operating conditions (better performance and lower emissions) and reduce the time, it is decided to incorporate multiobjective optimisation techniques by implementing the grade analysis and the analysis of variance (ANOVA). The optimised working condition was found and the confirmation experiment was done for the tested fuels. [ABSTRACT FROM AUTHOR]

The increasing demand for energy efficiency and environmental sustainability has driven extensive research into alternative fuels and emission reduction strategies for internal combustion engines. The use of fuel additives, such as hydrogen peroxide and ethanol blends, has emerged as a promising approach to enhance combustion and mitigate harmful emissions. This study investigates the effects of gasoline, ethanol-gasoline, and hydrogen peroxide-ethanol fuel blends on the performance and emissions of a spark-ignition engine across varying engine loads. By exploring the synergistic effects of fuel additives and optimizing engine operating parameters, this research aims to pave the way for reduced emissions, improved fuel efficiency, and a cleaner automotive industry, aligning with global efforts to mitigate the environmental impact of transportation. The results show that both ethanol and hydrogen peroxide significantly improve thermal efficiency, with the combination of both additives providing the highest efficiency gains. Fuel consumption is reduced with the introduction of these additives, particularly with the combined use of E10 and H₂O₂. Emission analysis reveals substantial reductions in carbon monoxide and hydrocarbon emissions, highlighting the environmental benefits of these additives. Contour plots are utilized to visualize and interpret the relationships between engine load, fuel composition, and emissions profiles. [ABSTRACT FROM AUTHOR]

Skin cancer is the irregular growth of skin cells, which is most often termed as cancer, developed by exposure of ultraviolet rays from sun. In this research paper, deep learning enabled hybrid optimization is followed for skin cancer detection and lesion segmentation. Two optimization algorithms are followed for skin lesion segmentation and cancer detection. Here, pre-processing is done by anisotropic diffusion followed by skin lesion segmentation. Here, Multi-Scale Residual Fusion Network (MSRFNet) is utilized for skin lesion segmentation, which is trained by proposed Average Subtraction Student Psychology Based Optimization (ASSPBO). After skin lesion segmentation, necessary features are extracted, followed by skin cancer detection. Skin cancer is detected by Deep Residual Network (DRN) trained by proposed Fractional ASSPBO (FrASSPBO). Moreover, performance of proposed FrASSPBO-DRN is analysed by three performance metrics like testing accuracy, True Positive Rate (TPR), and False Positive Rate (FPR) with values of 93.4%, 94%, and 8.2%. [ABSTRACT FROM AUTHOR]