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This paper seeks to investigate the effect of a heat conducting vertical partition in an enclosure on natural convection heat transfer and fluid flow using the polynomial‐based differential quadrature (PDQ) method.

The PDQ method with the non‐uniform Chebyshev‐Gauss‐Lobatto grid point distribution given below is used to transform the governing equations into a set of algebraic equations. After numerical discretization, the resulting algebraic equations are solved by the successive over‐relaxation iteration method.

It is found that the average Nusselt number decreases towards a constant value as the partition is distanced from the hot wall towards the middle of the enclosure. Furthermore, with decreasing thermal conductivity ratio, the average Nusselt number first increases and passes a peak point and then begins to decrease. The average heat transfer rate exhibits little dependence on the width of the partition in the range taken into consideration in this study for the thickness of the partition.

This study offers more knowledge on natural convection in partitioned enclosures.

The purpose of this paper is to optimize the heat transfer rate in square cavity by attaching fin at the bottom wall.

The problem is formulated and solved using finite element method. Accuracy of the method is validated by comparisons with previously published work.

It was found that attaching fin reduces heat transfer rate in the cavity.

Although the problem is not very original it is important in that many applications have heating on adjacent walls.

The purpose of this paper is to present a methodology of hybrid parallelization applied to the discrete element method that combines message-passing interface and OpenMP to improve computational performance. The scheme is based on mapping procedures based on Hilbert space-filling curves (HSFC).

The methodology uses domain decomposition strategies to distribute the computation of large-scale models in a cluster. It also partitions the workload of each subdomain among threads. This additional procedure aims to reach higher computational performance by adjusting the usage of message-passing artefacts and threads. The main objective is to reduce the communication among processes. The work division by threads employs HSFC in order to improve data locality and to avoid related overheads. Numerical simulations presented in this work permit to evaluate the proposed method in terms of parallel performance for models that contain up to 3.2 million particles.

Distinct partitioning algorithms were used in order to evaluate the local decomposition scheme, including the recursive coordinate bisection method and a topological scheme based on METIS. The results show that the hybrid implementations reach better computational performance than those based on message passing only, including a good control of load balancing among threads. Case studies present good scalability and parallel efficiencies.

The proposed approach defines a configurable execution environment for numerical models and introduces a combined scheme that improves data locality and iterative workload balancing.

The purpose of this paper is to propose general parallelism techniques for holistic twig join algorithms to process queries against Extensible Markup Language (XML) databases on a multi‐core system.

The parallelism techniques comprised data and task parallelism. As for data parallelism, the paper adopted the stream‐based partitioning for XML to partition XML data as the basis of parallelism on multiple CPU cores. The XML data partitioning was performed in two levels. The first level was to create buckets for creating data independence and balancing loads among CPU cores; each bucket was assigned onto a CPU core. Within each bucket, the second level of XML data partitioning was performed to create finer partitions for providing finer parallelism. Each CPU core performed the holistic twig join algorithm on each finer partition of its own in parallel with other CPU cores. In task parallelism, the holistic twig join algorithm was decomposed into two main tasks, which were pipelined to create parallelism. The first task adopted the data parallelism technique and their outputs were transferred to the second task periodically. Since data transfers incurred overheads, the size of each data transfer needed to be estimated cautiously for achieving optimal performance.

The data and task parallelism techniques contribute to good performance especially for queries having complex structures and/or higher values of query selectivity. The performance of data parallelism can be further improved by task parallelism. Significant performance improvement is attained by queries having higher selectivity because more outputs computed by the second task is performed in parallel with the first task.

The proposed parallelism techniques primarily deals with executing a single long‐running query for intra‐query parallelism, partitioning XML data on‐the‐fly, and allocating partitions on CPU cores statically. During the parallel execution, presumably there are no such dynamic XML data updates.

The effectiveness of the proposed parallel holistic twig joins relies fundamentally on some system parameter values that can be obtained from a benchmark of the system platform.

The paper proposes novel techniques to increase parallelism by combining techniques of data and task parallelism for achieving high performance. To the best of the author's knowledge, this is the first paper of parallelizing the holistic twig join algorithms on a multi‐core system.

The purpose of this paper is to propose Extensible Markup Language (XML) data partitioning schemes that can cope with static and dynamic allocation for parallel holistic twig joins: grid metadata model for XML (GMX) and streams‐based partitioning method for XML (SPX).

GMX exploits the relationships between XML documents and query patterns to perform workload‐aware partitioning of XML data. Specifically, the paper constructs a two‐dimensional model with a document dimension and a query dimension in which each object in a dimension is composed from XML metadata related to the dimension. GMX provides a set of XML data partitioning methods that include document clustering, query clustering, document‐based refinement, query‐based refinement, and query‐path refinement, thereby enabling XML data partitioning based on the static information of XML metadata. In contrast, SPX explores the structural relationships of query elements and a range‐containment property of XML streams to generate partitions and allocate them to cluster nodes on‐the‐fly.

GMX provides several salient features: a set of partition granularities that balance workloads of query processing costs among cluster nodes statically; inter‐query parallelism as well as intra‐query parallelism at multiple extents; and better parallel query performance when all estimated queries are executed simultaneously to meet their probability of query occurrences in the system. SPX also offers the following features: minimal computation time to generate partitions; balancing skewed workloads dynamically on the system; producing higher intra‐query parallelism; and gaining better parallel query performance.

The current status of the proposed XML data partitioning schemes does not take into account XML data updates, e.g. new XML documents and query pattern changes submitted by users on the system.

Note that effectiveness of the XML data partitioning schemes mainly relies on the accuracy of the cost model to estimate query processing costs. The cost model must be adjusted to reflect characteristics of a system platform used in the implementation.

This paper proposes novel schemes of conducting XML data partitioning to achieve both static and dynamic workload balance.

The progress of parallel computing in Information Retrieval (IR) is reviewed. In particular we stress the importance of the motivation in using parallel computing for text retrieval. We analyse parallel IR systems using a classification defined by Rasmussen and describe some parallel IR systems. We give a description of the retrieval models used in parallel information processing. We describe areas of research which we believe are needed.

The purpose of this paper is to describe the development and employment of an hp‐adaptive finite element method (FEM) algorithm for solving heat transfer problems in partitioned enclosures, which has attracted the attention of both experimental and theoretical researchers in recent years.

In the hp‐adaptive FEM algorithm presented here, both the element size and the shape function order are dynamically controlled by an a posteriori error estimator based on the L₂ norm; a three‐step adaptation strategy is used with a projection algorithm for the flow solver.

Simulation results are obtained for 2D and 3D natural convection within partitioned enclosures. Results show refined and enriched elements that develop near the partition edges and side walls of the enclosure, as expected. The heat transfer between the heated and cooled side walls is reduced in the presence of a partial partition.

The Rayleigh numbers were set to 10⁵ in the 2D case and 10³ in the 3D case. Efforts are underway to apply the hp‐adaptive algorithm to partitioned enclosures at much higher Rayleigh numbers, including comparison with available experimental data.

Heat transfer within partitioned enclosures occurs in many engineering situations: heat transfer across thermo pane windows, solar collectors, fire spread and energy transfer in rooms and buildings, cooling of nuclear reactors and heat exchanger design.

The hp‐adaptive FEM algorithm is one of the best mesh‐based algorithms for improving solution quality, whilst maintaining computational efficiency. The method shows considerable promise in solving a wide range of heat transfer problems including fluid flow.

The purpose of this paper is to propose a method to determine the optimal number of operators to be assigned to a given number of machines, as well as the number of machines that will be run by each operator (a numerical partition). This determination should be made with the objective of minimizing production costs or maximizing profits.

The method calculates the machines interference rate via the binomial distribution function. The optimal assignment is calculated by transformation of a partition problem into a problem of finding the shortest path on a directed acyclic graph.

The method enables the authors to calculate the adjusted cycle time, the workload of the operators, and the utility of the machines, as well as the production yield, the total cost per unit, and the hourly profit for each potential assignment of operators to machines. In a case study, the deviation of the output per hour of the proposed method from the actual value was about 2 percent.

The paper provides formulas and tables that give machine interference rates through the application of binomial distribution. The practicability of the proposed method is demonstrated by a real-life case study.

The method can be applied in a wide variety of manufacturing systems that use many identical machines. This includes tire presses in tire manufacturing operations, ovens in pastry manufacturing systems, textile machines, and so on.

The growing need for cellularisation presents the facilities manager with an array of partitioning options that can be daunting. Patrick Manwell, of Phippen, Randall and Parkes, looks at proprietary products available and at the principles that underpin their construction.

The design of a cellular manufacturing system requires that a machine population be partitioned into machine groups called manufacturing cells. A new graph partitioning heuristic is proposed to solve the manufacturing cell formation problem (MCFP). In the proposed heuristic, The MCFP is represented by a graph whose node set represents the machine cluster and edge set represents the machine‐pair association weights. A graph partitioning approach is used to form the manufacturing cells. This approach offers improved design flexibility by allowing a variety of design parameters to be controlled during cell formation. The effectiveness of the heuristic is demonstrated by comparing it to two MCFP published solution methods using several problems from the literature.