Performing detailed power system studies for designing and analyzing electrical distribution systems - Power system studies for cement plants

The power system studies for designing and analyzing the electrical distribution system for cement plants is detailed. The analysis consists of a short circuit, load flow, motor starting over-current coordination, and arc flash hazard study. There are several load flow solution algorithms used in industry such as Gauss-Seidel, Newton-Raphson, and current injection. It is good engineering practice to have an up-to-date load flow study for every installation.     

Optimization of relative tool position in accumulative double sided incremental forming using finite element analysis and model bias correction

Double-Sided Incremental Forming (DSIF) uses two small, independently moving, hemispherical tools on either side of the sheet to form a desired shape by following a predefined tool path. This study was motivated by the observation that the relative tool position of the tools, specified in the tool path generation algorithm, affects the formed geometric accuracy. A methodology for defining the relative tool positioning in the tool path generation algorithm based on local part geometry is proposed using simplified Finite Element Analysis (FEA) and sample physical experiments combined with Gaussian Process modeling techniques. This approach can take into account the mechanics of deformation in DSIF explicitly and physical compliance of the DSIF machine implicitly. Physical experiments were performed to demonstrate the effectiveness of the proposed framework.     

A POPULATION MONTE CARLO METHOD FOR GENERATING RANDOM MATRICES WITH KNOWN CHARACTERISTICS

An algorithm which provides approximate solutions to a certain matrix inverse problem is presented. In this inverse problem, we usually assume that the distribution of a functional of a random matrix is known. For example, we may know the distribution of the determinant or trace of the matrix. The algorithm attempts to find the mean and covariance structure of a random Gaussian matrix which yields the correct distribution for the functional. The algorithm is based on population Monte Carlo (PMC). Density estimation and importance sampling are used to converge toward a Gaussian matrix solution space described by the means and covariances. We also apply the algorithm to a machine learning problem without a known distribution and show the algorithm can find solutions maximizing an objective function. Results of the algorithm can give insights into the nature of random matrices with certain properties and allow statistical machine learning to create hypotheses about matrix structures from limited measurements. Furthermore, there are applications in testing and communications theory.     

Multi-Fault Tolerance for Cartesian Data Distributions

Faults are expected to play an increasingly important role in how algorithms and applications are designed to run on future extreme-scale systems. Algorithm-based fault tolerance is a promising approach that involves modifications to the algorithm to recover from faults with lower overheads than replicated storage and a significant reduction in lost work compared to checkpoint-restart techniques. Fault-tolerant linear algebra algorithms employ additional processors that store parities along the dimensions of a matrix to tolerate multiple, simultaneous faults. Existing approaches assume regular data distributions (blocked or block-cyclic) with the failures of each data block being independent. To match the characteristics of failures on parallel computers, we extend these approaches to mapping parity blocks in several important ways. First, we handle parity computation for generalized Cartesian data distributions with each processor holding arbitrary subsets of blocks in a Cartesian-distributed array. Second, techniques to handle correlated failures, i.e., multiple processors that can be expected to fail together, are presented. Third, we handle the colocation of parity blocks with the data blocks and do not require them to be on additional processors. Several alternative approaches, based on graph matching, are presented that attempt to balance the memory overhead on processors while guaranteeing the same fault tolerance properties as existing approaches that assume independent failures on regular blocked data distributions. Evaluation of these algorithms demonstrates that the additional desirable properties are provided by the proposed approach with minimal overhead.     

Response Surface Estimates of the Cross-Sectionally Augmented IPS Tests for Panel Unit Roots

This paper estimates response surface coefficients for a large range of quantiles of the cross-sectionally augmented IPS (CIPS) test of Pesaran (2007), for different specifications of the deterministic components. An Excel programme is available to calculate the P value associated with a CIPS test statistic.     

On the role of search for learning from examples

Gold (1967) discovered a fundamental enumeration technique, the socalled identification-by-enumeration, a simple but powerful class of algorithms for learning from examples (inductive inference). We introduce a variety of more sophisticated (and more powerful) enumeration techniques and characterize their power. We conclude with the thesis that enumeration techniques are even universal in that each solvable learning problem in inductive inference can be solved by an adequate enumeration technique. This thesis is technically motivated and discussed.     

Mass customization in the product life cycle

This study presents an introduction to mass customization in the product life cycle—the goal of mass customization, mass customization configurations, and new customer integration techniques, modular design techniques, flexible manufacturing systems (FMSs), and supply chain management methods. The study reviews three selected books and twenty-one selected papers—early papers that describe the goal of mass customization, early papers that describe mass customization configurations, and recent papers that describe new customer integration techniques, modular design techniques, FMSs, and supply chain management methods. The study shows that the goal of mass customization is to create individually customized products, with mass production volume, cost, and efficiency, that most companies use ‘assemble-to-order’ configurations to create standardized products, and that more work is needed on interactive customer integration techniques, collaborative modular design techniques, reconfigurable manufacturing systems, and integrated supply chain management methods to achieve the goal of mass customization.     

USE OF NATIVE AND NONNATIVE NEST PLANTS BY RIPARIAN‐NESTING BIRDS ALONG TWO STREAMS IN NEW MEXICO

Nonnative plant invasions are a management concern, particularly in riparian forests, but little is known about mechanisms through which they influence vertebrate communities. In the American Southwest, native trees such as cottonwood (Populus spp.) are thought to provide better habitat for breeding birds than nonnative plants, which are more tolerant of human‐altered conditions. To evaluate effects of riparian forest composition on riparian‐nesting birds, we examined nest plant use along two rivers in New Mexico that differed in abundance of nonnative vegetation. Of the nests we observed, 49% along the Middle Rio Grande were constructed in nonnative plants, compared with 4% along the Gila River. Birds in the canopy and cavity‐nesting guilds constructed less than 5% of their nests in nonnative plants along either river. At the Middle Rio Grande, birds in the subcanopy/shrub guild constructed 67% of their nests in nonnative plants. Despite the relatively low availability of cottonwoods, they were used by greater numbers of species than any other woody plant at either river. Riparian obligates and species of conservation concern in the canopy and cavity guilds were especially dependent on cottonwood and Arizona sycamore (Platanus wrightii). Our results show that, although nonnative trees and shrubs support large numbers of nests for certain birds, cottonwoods and other large native trees are disproportionately important to riparian bird communities. Copyright © 2013 John Wiley & Sons, Ltd.     

A geometrical approach to the motion planning problem for a submerged rigid body

The main focus of this article is the motion planning problem for a deeply submerged rigid body. The equations of motion are formulated and presented by use of the framework of differential geometry and these equations incorporate external dissipative and restoring forces. We consider a kinematic reduction of the affine connection control system for the rigid body submerged in an ideal fluid, and present an extension of this reduction to the forced affine connection control system for the rigid body submerged in a viscous fluid. The motion planning strategy is based on kinematic motions; the integral curves of rank one kinematic reductions. This method is of particular interest to autonomous underwater vehicles which cannot directly control all six degrees of freedom (such as torpedo-shaped autonomous underwater vehicles) or in case of actuator failure (i.e. under-actuated scenario). A practical example is included to illustrate our technique.     

Stem volume estimation in boreal forests using ERS-1/2 coherence and SPOT XS optical data

The use of spaceborne synthetic aperture radar (SAR) systems to estimate stem volume and biomass in boreal forests has shown some promising results, but with saturation of the radar backscatter at relatively low stem volumes and limited accuracy of stem volume estimation. These limitations have motivated evaluation of more advanced methods, such as interferometry. The results presented in this study show that ERS interferometry, under favourable conditions, may be used to estimate stem volume at stand level with saturation level and accuracy useful for operational forestry management planning in boreal forests. Five interferograms were analysed, covering a test site located in the central part of Sweden with stem volume in the range of 0-305 m³ ha^-1. The best interferogram showed a linear relationship between stem volume and coherence with a root mean square error (RMSE) of approximately 26 m³ ha^-1, corresponding to 20% of the average stem volume, throughout the range of stem volume. No saturation was observed up to the maximum stem volume. However, the sensitivity of coherence to stem volume varied considerably between the interferograms. Finally, four SPOT XS images were evaluated and compared with the stem volume estimations obtained from the interferograms, resulting in a relative RMSE of about 24% of the stem volume, for the best case. The estimation of stem volume using coherence data was found to be better than optical data for stem volumes exceeding about 110 m³ ha^-1. The statistical analysis was performed using linear regression models with cross-validation.