An efficient method for solving the Signorini problem in the simulation of free-form surfaces produced by belt grinding

Industrial robots are recently introduced to the belt grinding of free-form surfaces to obtain high productive efficiency and constant surface quality. The simulation of belt grinding process can facilitate planning grinding paths and writing robotic programs before manufacturing. In simulation, it is crucial to get the force distribution in the contact area between the workpiece and the elastic contact wheel because the uneven distributed local forces are the main reason to the unequal local removals on the grated surface. The traditional way is to simplify this contact problem as a Signorini contact problem and use the finite element method (FEM) to calculate the force distribution. However, the FEM model is too computationally expensive to meet the real-time requirement. A new model based on support vector regression (SVR) technique is developed in this paper to calculate the force distribution instead of the FEM model. The new model approximates the FEM model with an error smaller than 5%, but executes much faster (1 s vs 15 min by FEM). With this new model, the real-time simulation and even the on-line robot control of grinding processes can be further conducted.     

Ongoing verification of a multiphysics community code: FLASH

When developing a complex, multi‐authored code, daily testing on multiple platforms and under a variety of conditions is essential. It is therefore necessary to have a regression test suite that is easily administered and configured, as well as a way to easily view and interpret the test suite results. We describe the methodology for verification of FLASH, a highly capable multiphysics scientific application code with a wide user base. The methodology uses a combination of unit and regression tests and an in‐house testing software that is optimized for operation under limited resources. Although our practical implementations do not always comply with theoretical regression‐testing research, our methodology provides a comprehensive verification of a large scientific code under resource constraints.Copyright © 2013 John Wiley & Sons, Ltd.     

A greedy gradient-simulated annealing selection hyper-heuristic

Educational timetabling problem is a challenging real world problem which has been of interest to many researchers and practitioners. There are many variants of this problem which mainly require scheduling of events and resources under various constraints. In this study, a curriculum based course timetabling problem at Yeditepe University is described and an iterative selection hyper-heuristic is presented as a solution method. A selection hyper-heuristic as a high level methodology operates on the space formed by a fixed set of low level heuristics which operate directly on the space of solutions. The move acceptance and heuristic selection methods are the main components of a selection hyper-heuristic. The proposed hyper-heuristic in this study combines a simulated annealing move acceptance method with a learning heuristic selection method and manages a set of low level constraint oriented heuristics. A key goal in hyper-heuristic research is to build low cost methods which are general and can be reused on unseen problem instances as well as other problem domains desirably with no additional human expert intervention. Hence, the proposed method is additionally applied to a high school timetabling problem, as well as six other problem domains from a hyper-heuristic benchmark to test its level of generality. The empirical results show that our easy-to-implement hyper-heuristic is effective in solving the Yeditepe course timetabling problem. Moreover, being sufficiently general, it delivers a reasonable performance across different problem domains.     

VISIM: Sequential simulation for linear inverse problems

Linear inverse Gaussian problems are traditionally solved using least squares-based inversion. The center of the posterior Gaussian probability distribution is often chosen as the solution to such problems, while the solution is in fact the posterior Gaussian probability distribution itself. We present an algorithm, based on direct sequential simulation, which can be used to efficiently draw samples of the posterior probability distribution for linear inverse problems. There is no Gaussian restriction on the distribution in the model parameter space, as inherent in traditional least squares-based algorithms.As data for linear inverse problems can be seen as weighed linear averages over some volume, block kriging can be used to perform both estimation (i.e. finding the center of the posterior Gaussian pdf) and simulation (drawing samples of the posterior Gaussian pdf). We present the kriging system which we use to implement a flexible GSLIB-based algorithm for solving linear inverse problems.We show how we implement such a simulation program conditioned to linear average data. The program is called VISIM as an acronym for Volume average Integration SIMulation. An effort has been made to make the program efficient, even for larger scale problems, and the computational efficiency and accuracy of the code is investigated.Using a synthetic cross-borehole tomography case study, we show how the program can be used to generate realizations of the a posteriori distributions (i.e. solutions) from a linear tomography problem. Both Gaussian and non-Gaussian a priori model parameter distributions are considered.     

Grouping Techniques for Scheduling Problems: Simpler and Faster

In this paper we describe a general grouping technique to devise faster and simpler approximation schemes for several scheduling problems. We illustrate the technique on two different scheduling problems: scheduling on unrelated parallel machines with costs and the job shop scheduling problem. The time complexity of the resulting approximation schemes is always linear in the number n of jobs, and the multiplicative constant hidden in the O(n) running time is reasonably small and independent of the error ε. Supported by Swiss National Science Foundation project 200020-109854, “Approximation Algorithms for Machine scheduling Through Theory and Experiments II”. A preliminary version of this paper appeared in the Proceedings of ESA’01.     

Directed model checking with distance-preserving abstractions

In directed model checking, the traversal of the state space is guided by an estimate of the distance from the current state to the nearest error state. This paper presents a distance-preserving abstraction for concurrent systems that allows one to compute an interesting estimate of the error distance without hitting the state explosion problem. Our experiments show a dramatic reduction both in the number of states explored by the model checker and in the total runtime.     

Computing presentations for subgroups of polycyclic groups and of context-free groups

Algorithms for solving uniform decision problems for algebraic structures crucially depend on the chosen finite presentations for the structures under consideration. Rewriting techniques have been used very successfully to solve uniform decision problems, when the presentations considered involve finite, noetherian, and ()-confluent rewriting systems. Whenever the class of algebraic structures considered is closed under the operation of taking finitely generated substructures, then the algorithms for solving the uniform decision problems can be applied to the substructures as well. However, since these algorithms depend on the form of the presentations, this involves the task of constructing a presentation of a certain form for a substructure given a presentation of this form for the structure itself and a finite set of generating elements for the substructure.This problem, which has received a lot of attention in algebra, is here investigated from an algorithmic point of view. The structures considered are the following two classes of groups, which have been studied extensively before: the polycyclic groups and the context-free groups.Finitely generated context-free groups can be presented by finite, monadic, and -confluent string-rewriting systems. Due to their nice algorithmic properties these systems provide a way to effectively solve many decision problems for context-free groups. Since finitely generated subgroups of context-free groups are again contextfree, they can be presented in the same way. Here we describe a process that, from a finite, monadic, and -confluent string-rewriting system presenting a context-free groupG and a finite subsetU ofG, determines a presentation of this form for the subgroup U ofG that is generated byU. For finitely presented polycyclic groups we obtain an analogous result, when we use finite confluent PCP2-presentations to describe these groups.This work was performed while this author was visiting at the Fachbereich Informatik, Universität Kaiserslautern, during his sabbatical 1991/92     

Effects of exogenous porcine somatotropin on the development of fat cells and fatty acid composition in backfat of live finishing pigs

The effects of long-term application of recombinant porcine somatotropin (pST) to Landrace pigs on the development of backfat thickness, fat cells and fatty acid composition were investigated from about the 116th to the 186th day of life. Biopsy samples from the backfat of 56 castrates were taken at the beginning of treatment and after 5 and 10 weeks. The daily injection of 2 or 4 mg of pST induced a considerable decrease in backfat growth compared to untreated controls. This was attributed to a decreased size (about 18–20%) and number (about 13–25%) of fat cells. The higher dose of 4 mg pST/day induced a greater restriction of fat growth. This was obviously based on differences in fat cell number. Furthermore, pST treatment delayed the normal decrease of unsaturated fatty acids (C 18:2; C 18:3) during the period of growth examined. Therefore, the percentages of unsaturated fatty acids increased, indicating changes in fat cell metabolism of pST treated pigs.