Intelligent prediction of ground vibration in coal formations using ANN

The present paper details the prediction of blast induced ground vibration, using artificial neural network. The data was generated from five different coal mines. Twenty one different parameters involving rock mass parameters, explosive parameters and blast design parameters, were used to develop the one comprehensive ANN model for five different coal bearing formations. A total of 131 datasets was used to develop the ANN model and 44 datasets was used to test the model. The developed ANN model was compared with the USBM model. The prediction capability to predict blast induced ground vibration, of the comprehensive ANN model was found to be superior.

Uplift Resistance of Long Pipelines in the Presence of Seismic Forces

The vertical uplift resistance of long pipes buried in sands and subjected to pseudostatic seismic forces has been computed by using the lower-bound theorem of the limit analysis in conjunction with finite elements and nonlinear optimization. The soil mass is assumed to follow the Mohr-Coulomb failure criterion and an associated flow rule. The failure load is expressed in the form of a nondimensional uplift factor F-gamma. The variation of F-gamma is plotted as a function of the embedment ratio of the pipe, horizontal seismic acceleration coefficient (k(h)), and soil friction angle (phi). The magnitude of F-gamma is found to decrease continuously with an increase in the horizontal seismic acceleration coefficient. The reduction in the uplift resistance becomes quite significant, especially for greater values of embedment ratios and lower values of friction angle. The predicted uplift resistance was found to compare well with the existing results reported from the literature. (C) 2014 American Society of Civil Engineers.

Effect of Groundwater Seepage on Uplift Resistance of Buried Pipelines

The uplift resistance of pipelines buried in sands, in the presence of inclined groundwater flow, considering both upward and downward flow directions, has been determined by using the lower bound finite elements limit analysis in conjunction with nonlinear optimization. A correction factor (f (gamma) ), which needs to be multiplied with the uplift factor (F (gamma) ), has been computed to account for groundwater seepage. The variation of f (gamma) has been obtained as a function of i(gamma (w) /gamma (sub) ) for different horizontal inclinations (theta) of groundwater flow; where i = absolute magnitude of hydraulic gradient along the direction of flow, gamma (w) is the unit weight of water and gamma (sub) is the submerged unit weight of soil mass. For a given magnitude of i, there exists a certain critical value of theta for which the magnitude of f (gamma) becomes the minimum. An example has also been presented to illustrate the application of the results obtained for designing pipelines in presence of groundwater seepage.

Experimental and numerical studies on protection of buried pipelines and underground utilities using geocells

This paper presents the results of the laboratory model tests and the numerical studies conducted on small diameter PVC pipes, buried in geocell reinforced sand beds. The aim of the study was to evaluate the suitability of the geocell reinforcement in protecting the underground utilities and buried pipelines. In addition to geocells, the efficacy of only geogrid and geocell with additional basal geogrid cases were also studied. A PVC (Poly Vinyl Chloride) pipe with external diameter 75 mm and thickness 1.4 mm was used in the experiments. The vehicle tire contact pressure was simulated by applying the pressure on the top of the bed with the help of a steel plate. Results suggest that the use of geocells with additional basal geogrid considerably reduces the deformation of the pipe as compared to other types of reinforcements. Further, the depth of placement of pipe was also varied between 1B to 2B (B is the width of loading plate) below the plate in the presence of geocell with additional basal geogrid. More than 50% reduction in the pressure and more than 40% reduction in the strain values were observed in the presence of reinforcements at different depths as compared to the unreinforced beds. Conversely, the performance of the subgrade soil was also found to be marginally influenced by the position of the pipe, even in the presence of the relatively stiff reinforcement system. Further, experimental results were validated with 3-dimensional numerical studies using FLAC(3D) (Fast Lagrangian Analysis of Continua in 3D). A good agreement in the measured pipe stain values were observed between the experimental and numerical studies. Numerical studies revealed that the geocells distribute the stresses in the lateral direction and thus reduce the pressure on the pipe. In addition, the results of the 1-g model tests were scaled up to the prototype case of the shallow buried pipeline below the pavement using the appropriate scaling laws. (C) 2015 Elsevier Ltd. All rights reserved.

Die Filling Behaviour of Semi Solid A356 Al Alloy Slurry During Rheo Pressure Die Casting

The present work discusses the findings obtained from simulations of semi solid die filling of a steering knuckle, prior to actual component development using in-house developed rheo pressure die casting system. Die filling capability of A356 Al alloy at semi-solid state has been investigated using commercial software Flow-3Dcast to optimise the pouring temperature of semi-solid slurry into the die cavity, while all other variables such as gating design, die preheat temperature and injection velocity are kept constant based on the prior knowledge obtained from trial numerical simulations and experimentation. Efforts have been made to nullify the essence of costly, time consuming experiments towards obtaining high-quality castings out of the findings obtained from numerical simulations. The optimum pouring temperature identified in the present study is 610 A degrees C, which facilitates smoother slurry flow, minimum surface defect concentration, uniform temperature field and solid fraction distribution within the component cavity.

Uplift Resistance of Interfering Pipelines Buried in Sand

The vertical uplift resistance of interfering pipelines buried in sands has been computed using the lower-bound limit analysis in conjunction with finite elements and nonlinear optimization. The soil mass is assumed to follow the Mohr-Coulomb failure criterion and an associated flow rule. It is specified that all the pipes fail simultaneously at the same magnitude of the failure load. For different clear spacing (S) between the pipes, the magnitude of the efficiency factor (xi(gamma)) is determined. Because of pipes' interference, with a reduction in the spacing between the pipelines, the magnitude of xi(gamma) is found to decrease continuously. The results were found to compare quite well with the available data from literature for horizontal strip anchors. (C) 2015 American Society of Civil Engineers.

PolyMage: Automatic Optimization for Image Processing Pipelines

This paper presents the design and implementation of PolyMage, a domain-specific language and compiler for image processing pipelines. An image processing pipeline can be viewed as a graph of interconnected stages which process images successively. Each stage typically performs one of point-wise, stencil, reduction or data-dependent operations on image pixels. Individual stages in a pipeline typically exhibit abundant data parallelism that can be exploited with relative ease. However, the stages also require high memory bandwidth preventing effective utilization of parallelism available on modern architectures. For applications that demand high performance, the traditional options are to use optimized libraries like OpenCV or to optimize manually. While using libraries precludes optimization across library routines, manual optimization accounting for both parallelism and locality is very tedious. The focus of our system, PolyMage, is on automatically generating high-performance implementations of image processing pipelines expressed in a high-level declarative language. Our optimization approach primarily relies on the transformation and code generation capabilities of the polyhedral compiler framework. To the best of our knowledge, this is the first model-driven compiler for image processing pipelines that performs complex fusion, tiling, and storage optimization automatically. Experimental results on a modern multicore system show that the performance achieved by our automatic approach is up to 1.81x better than that achieved through manual tuning in Halide, a state-of-the-art language and compiler for image processing pipelines. For a camera raw image processing pipeline, our performance is comparable to that of a hand-tuned implementation.