Estimation of the polishing time for different metallic alloys in surface texture removal

The aim of this work is to propose a novel analytical model for predicting the polishing time and behavior of the surface texture removal in different metal alloys. The surface texture, resulting from a previous milling process, is characterized and investigated by the Abbott–Firestone curve, the relative speed of the abrasive material, the applied force, the type of material and the size of the abrasive grains. Consequently, a model that predicts the surface texture evolution based on the mechanism of abrasion is proposed, in which a constant of the wear model is found to behave linearly with the size of the abrasive grain for each metal alloy. Based on the good agreement between the experimental and the estimated values (R² equal to 0.993), operational parameters are recommended to predict the required surface texture for AlCu4PbMg, 30CrNiMo8, C45E and X6CrNiMo8 when using abrasive grade between P180 and P1200.     

Inventing the Rural: A Brief History of Modern Architecture in the Countryside

The rural has long occupied a valuable, if under-theorised position in modern architectural history. Here, Cole Roskam , Assistant Professor of Architectural History at the University of Hong Kong, highlights key moments in this history and, in doing so, illuminates a central paradox at the heart of architecture's various turns to the countryside; namely, can architects maintain the physical and social integrity of the rural when they are themselves a fundamental vector of its changing character?     

Evaluation of image based Abbott–Firestone curve parameters using machine vision for the characterization of cylinder liner surface topography

In this paper, a method is proposed for the evaluation of image based Abbott–Firestone curve parameters aiming to characterize the cylinder bore surface topography using machine vision. Plateau honing experiments are performed to generate sixteen cylinder liners with different surface topographies and the 2-D and 3-D Abbott–Firestone parameters are measured using a stylus instrument and Coherence Scanning Interferometer (CSI), respectively. The images are captured from the corresponding portions of the cylinder liner surfaces using a Charge Coupled Device (CCD) camera connected with different microscopic attachments. The captured images are filtered using a Butterworth high pass filter followed by the adaptation of the double step Gaussian filtering procedure specified by the ISO 13565-1. An Abbott–Firestone curve is constructed by finding the cumulative of the intensity histogram of the filtered images. Five image based parameters are evaluated from the constructed Abbott curve by adapting the procedures presented in ISO 13565-2. The computed image based Abbott–Firestone curve parameters are observed to bear a statistically significant correlation with the measured 2-D and 3-D Abbott–Firestone curve parameters. An artificial neural network (ANN) is trained and tested to arrive at the actual values of the Abbott–Firestone curve parameters using the computed image based feature parameters. The results indicate that the multiple surface topography parameters of the cylinder bore surface could be estimated/predicted with a reasonable accuracy using machine vision technique coupled with ANN.