Rheological characterization of styrene-butadiene based medium and its finishing performance using rotational abrasive flow finishing process

Finishing of complex shaped components needs advanced finishing processes to produce nano level surface finish. Abrasive flow finishing (AFF) process uses abrasive mixed polymer as a medium to finish complex shapes. The medium should possess three basic properties i.e., better flow ability, self deformability and abrading ability to finish the given surface to nano scale. Various flow and deformation properties of the medium can be investigated by rheological characterization. In the present work, different media are made using specially co-polymered soft styrene butadiene based polymer, plasticizer and abrasives. Static and dynamic rheological properties of these in-house prepared media are evaluated, and it is found that these media follow viscoelastic behavior with shear thinning nature. For a small rise in temperature, the medium starts losing its original properties.In the present work, static (flow test, creep compliance test, stress relaxation test) and dynamic (amplitude sweep and frequency sweep) rheological properties are measured. Finishing experiments are carried out on Al alloy as well as its metal matrix composites using rotational abrasive flow finishing (R-AFF) process. Later, the effect of each rheological parameter such as shear stress, % viscous component, stress relaxation modulus and storage modulus on the change in average surface roughness (ΔR_a) and material removal rate during R-AFF is found.     

Comparing regional stove-usage patterns and using those patterns to model indoor air quality impacts

Monitoring improved cookstove adoption and usage in developing countries can help anticipate potential health and environmental benefits that may result from household energy interventions. This study explores stove-usage monitor (SUM)-derived usage data from field studies in China (52 stoves, 1422 monitoring days), Honduras (270 stoves, 630 monitoring days), India (19 stoves, 565 monitoring days), and Uganda (38 stoves, 1007 monitoring days). Traditional stove usage was found to be generally similar among four seemingly disparate countries in terms of cooking habits, with average usage of between 171 and 257 minutes per day for the most-used stoves. In Honduras, where survey-based usage data were also collected, there was only modest agreement between sensor data and self-reported user data. For Indian homes, we combined stove-usage data with a single-zone Monte Carlo box model to estimate kitchen-level PM_2.5 and CO concentrations under various scenarios of cleaner cookstove adoption. We defined clean cookstove performance based on the International Standards Organization (ISO) voluntary guidelines. Model results showed that even with 75% displacement of traditional stoves with the cleanest available stove (ISO tier-5), World Health Organization 24 hours PM_2.5 standards were exceeded in 96.4% of model runs, underscoring the importance of full displacement.     

Characterizing and modelling popularity of user-generated videos

This paper develops a framework for studying the popularity dynamics of user-generated videos, presents a characterization of the popularity dynamics, and proposes a model that captures the key properties of these dynamics. We illustrate the biases that may be introduced in the analysis for some choices of the sampling technique used for collecting data; however, sampling from recently-uploaded videos provides a dataset that is seemingly unbiased. Using a dataset that tracks the views to a sample of recently-uploaded YouTube videos over the first eight months of their lifetime, we study the popularity dynamics. We find that the relative popularities of the videos within our dataset are highly non-stationary, owing primarily to large differences in the required time since upload until peak popularity is finally achieved, and secondly to popularity oscillation. We propose a model that can accurately capture the popularity dynamics of collections of recently-uploaded videos as they age, including key measures such as hot set churn statistics, and the evolution of the viewing rate and total views distributions over time.     

Effect of magnetic field on the heat and mass transfer in a vertical annulus

This paper reports the effect of axial or radial magnetic field on the double-diffusive natural convection in a vertical cylindrical annular cavity. The boundary conditions at the side walls are imposed in such a way that the thermal and solutal buoyancy effects are either cooperating or opposing, resulting in a cooperating gradients or opposing gradients flow configuration. The top and bottom walls are insulated and impermeable. The governing equations of this fluid system are solved by the Alternating Direction Implicit and the Successive Line Over Relaxation methods. Total heat and mass transfer rates across the cavity are calculated by evaluating the average Nusselt and Sherwood numbers. The main objective of the present numerical study is to understand the effect of magnetic field on the double-diffusive convection in the annular cavity. From the numerical results, it is found that the magnetic field suppresses the double-diffusive convection only for small buoyancy ratios. But, for larger buoyancy ratio, the magnetic field is effective in suppressing the thermal convective flow. Further, the magnetic field is effective when it is applied perpendicular to the main flow.     

Dynamics of nonuniform viscosity of unsteady CuO–H2O nanofluid flow from a spinning body

This paper studies an unsteady rotating flow over a sphere. The substantial effect of nonuniform viscosity is accounted in the extant study. nanofluid is used in adopted nanofluid model. A comparative study among the upshot of nonuniform viscosity and uniform viscosity on present nanofluid model is established here. Primary equations of adopted model have been standardized through similarity methodology and the subsequent equations have been resolved numerically by expending an RK‐4 shooting exercise. The stimulus of encouraging flow parameters on the flow specific is made accurately through diagrams and charts. We witnessed that the heat transmission rate is intensified for unsteadiness factor of the present flow, which suggests that the rate of cooling improves. The unsteadiness factor supports the flow to upsurge in and the reverse consequence originates in the spinning direction. The heat transmission rate is higher in case of nonuniform viscosity than uniform viscosity.     

Robust formulations for clustering-based large-scale classification

Chebyshev-inequality-based convex relaxations of Chance-Constrained Programs (CCPs) are shown to be useful for learning classifiers on massive datasets. In particular, an algorithm that integrates efficient clustering procedures and CCP approaches for computing classifiers on large datasets is proposed. The key idea is to identify high density regions or clusters from individual class conditional densities and then use a CCP formulation to learn a classifier on the clusters. The CCP formulation ensures that most of the data points in a cluster are correctly classified by employing a Chebyshev-inequality-based convex relaxation. This relaxation is heavily dependent on the second-order statistics. However, this formulation and in general such relaxations that depend on the second-order moments are susceptible to moment estimation errors. One of the contributions of the paper is to propose several formulations that are robust to such errors. In particular a generic way of making such formulations robust to moment estimation errors is illustrated using two novel confidence sets. An important contribution is to show that when either of the confidence sets is employed, for the special case of a spherical normal distribution of clusters, the robust variant of the formulation can be posed as a second-order cone program. Empirical results show that the robust formulations achieve accuracies comparable to that with true moments, even when moment estimates are erroneous. Results also illustrate the benefits of employing the proposed methodology for robust classification of large-scale datasets.     

A study of correlation technique on pyramid processed images

The pyramid algorithm is potentially a powerful tool for advanced television image processing and for pattern recognition. An attempt is made to design and develop both hardware and software for a system which performs decomposition and reconstruction of digitized images by implementing the Burt pyramid algorithm. In this work, an attempt is also made to study correlation performance on reconstructed images. That is, the reference image is taken from the original image and correlation is performed on expanded images of the same size. Similarly, correlation performance study is carried out on different pyramid-processed levels. In this paper results are presented in terms of RMS error between original and expanded images. Only still images are considered, and the hardware is designed around an i486 processor and software is developed in PL/M 86.     

The effects of process faults and misalignments on the cutting force system and hole quality in reaming

A chip thickness and cutting force model that considers the deflection of the tool and the regenerative effect resulting from the presence of process faults and misalignments has been developed for the reaming process. Through a series of experiments, the model has been calibrated and validated. The model predicts tool displacement, torque, thrust, X and Y forces, and the average radius of the reamed hole. The developed model is also shown to be capable of being used as a basis for the on-line detection of process faults present in the system.