Prediction of bulk modulus and volumetric expansion coefficient of water for leak tightness test of pipelines

To determine whether any pressure variation in pipeline hydrostatic test is a result of temperature changes or the presence of leaks, the calculation of pressure/temperature changes is required for test sections. In these calculations, bulk modulus and volumetric expansion coefficient of fresh or sea water must be taken into account. In this study, a simple-to-use correlation is developed to predict the bulk modulus and volumetric expansion coefficient of both fresh and sea water as a function of temperature and pressure. The proposed correlation helps to cover the bulk modulus and volumetric expansion coefficient of both fresh and sea water for temperatures less than 50 °C (40 °C for sea water) as well as pressures up to 55,000 kPa (550 bar). The results can be used in follow-up calculations to determine whether any pressure variation in pipeline hydrostatic test is a result of temperature changes or the presence of leaks. The proposed correlation showed promising results with average absolute deviations for volumetric expansion coefficient and bulk modulus of water being around 0.58% and 0.08% respectively. The novel correlation is easy to use and will prove to be of immense value for project engineers to test the critical limits accurately.     

Optimization of Water Distribution Networks Using Integer Linear Programming

In this study optimum design of municipal water distribution networks for a single loading condition is determined by the branch and bound integer linear programming technique. The hydraulic and optimization analyses are linked through an iterative procedure. This procedure enables us to design a water distribution system that satisfies all required constraints with a minimum total cost. The constraints include pipe sizes, which are limited to the commercially available sizes, reservoir levels, pipe flow velocities, and nodal pressures. Accuracy of the developed model has been assessed using a network with limited solution alternatives, the optimal solution of which can be determined without employing optimization techniques. The proposed model has also been applied to a network solved by others. Comparison of the results indicates that the accuracy and convergence of the proposed method is quite satisfactory.     

Modeling Multithreaded Applications Using Petri Nets

Since most modern computing systems contain multiple processing elements, applications are relying on multithreaded programming techniques that allow a program to execute multiple tasks concurrently to take advantage of the processing capabilities. Multithreaded programs are more difficult to design and test because of the nondeterministic execution orders and synchronization among the threads. Different approaches can be used to test Multithreaded Applications. In our approach we use Petri nets to represent the key elements of interactions among threads to identify potential problems such as race conditions, lost signals, and deadlocks. A tool called C2Petri has been developed which converts C-Pthreads programs to the equivalent Petri net model. This tool helps verification of Pthread-based programs. At present the tool has limited capabilities and we hope to expand the capabilities of our tool in the near future.     

Multireference object pose retrieval with volume feedback

Pose retrieval of a rigid object from monocular video sequences or images is addressed. Initially, the object pose is estimated in each image assuming flat depth maps. Shape-from-silhouette is then applied to make a 3-D model (volume), which is used for a new round of pose estimations, this time by a model-based method that gives better estimates. Before repeating this process by building a new volume, pose estimates are adjusted to reduce error by maximizing a novel quality factor for shape-from-silhouette volume reconstruction. The feedback loop is terminated when pose estimates do not change much, as compared with those produced by the previous iteration. Based on a theoretical study of the proposed system, a test of convergence to a given set of poses is devised. Reliable performance of the system is also proved by several experiments on both synthetic and real image sequences. No model is assumed for the object and no feature point is detected or tracked as there is no problematic feature matching or correspondence. Our method can be used for 3-D object tracking in video, 3-D modeling, and volume reconstruction from video.     

A hybrid multi-objective shuffled frog-leaping algorithm for a mixed-model assembly line sequencing problem

In this paper, a mixed-model assembly line (MMAL) sequencing problem is studied. This type of production system is used to manufacture multiple products along a single assembly line while maintaining the least possible inventories. With the growth in customers’ demand diversification, mixed-model assembly lines have gained increasing importance in the field of management. Among the available criteria used to judge a sequence in MMAL, the following three are taken into account: the minimization of total utility work, total production rate variation, and total setup cost. Due to the complexity of the problem, it is very difficult to obtain optimum solution for this kind of problems by means of traditional approaches. Therefore, a hybrid multi-objective algorithm based on shuffled frog-leaping algorithm (SFLA) and bacteria optimization (BO) are deployed. The performance of the proposed hybrid algorithm is then compared with three well-known genetic algorithms, i.e. PS-NC GA, NSGA-II, and SPEA-II. The computational results show that the proposed hybrid algorithm outperforms the existing genetic algorithms, significantly in large-sized problems.     

Comparison of deposition models for a TEOS LPCVD process

We present a comparison of models describing the pyrolytic deposition of SiO₂ with a low pressure chemical vapor deposition process. In order to meet industrial simulation requirements, e.g. accuracy and fast delivery of results, we present an overview of established and new models, their use within TCAD applications, and their best results which have been obtained by calibrations according to SEM measurements.     

Nanoelectromechanical Chip (NELMEC) Combination of Nanoelectronics and Microfluidics to Diagnose Epithelial and Mesenchymal Circulating Tumor Cells from Leukocytes

An integrated nano‐electromechanical chip (NELMEC) has been developed for the label‐free distinguishing of both epithelial and mesenchymal circulating tumor cells (ECTCs and MCTCs, respectively) from white blood cells (WBCs). This nanoelectronic microfluidic chip fabricated by silicon micromachining can trap large single cells (>12 µm) at the opening of the analysis microchannel arrays. The nature of the captured cells is detected using silicon nanograss (SiNG) electrodes patterned at the entrance of the channels. There is an observable difference between the membrane capacitance of the ECTCs and MCTCs and that of WBCs (measured using SiNG electrodes), which is the key indication for our diagnosis. The NELMEC chip not only solves the problem of the size overlap between CTCs and WBCs but also detects MCTCs without the need for any markers or tagging processes, which has been an important problem in previously reported CTC detection systems. The great conductivity of the gold‐coated SiNG nanocontacts as well as their safe penetration into the membrane of captured cells, facilitate a precise and direct signal extraction to distinguish the type of captured cell. The results achieved from epithelial (MCF‐7) and mesenchymal (MDA‐MB231) breast cancer cells circulated in unprocessed blood suggest the significant applications for these diagnostic abilities of NELMEC.     

THE EFFICIENCY CHALLENGES OF RESOURCE DISCOVERY IN GRID ENVIRONMENTS

Resource discovery is one of the most important services that significantly affects the efficiency of grid computing systems. The inherent dynamic and large-scale characteristics of grid environments make their resource discovery a challenging task. In recent years, different approaches have been proposed for resource discovery, attempting to tackle the challenges of grid environments and improve the efficiency. Being aware of these challenges and approaches is worthwhile in order to choose an appropriate approach according to the application in different organizations. This study reviews the most important factors that should be considered and challenges to be tackled in order to develop an efficient grid resource discovery system.     

An efficient parallel algorithm for the longest path problem in meshes

The longest path problem is the problem of finding a simple path with the maximum number of vertices in a given graph, and so far it has been solved polynomially only for a few classes of graphs. This problem generalizes the well-known Hamiltonian path problem, hence it is NP-hard in general graphs. In this paper, first we give a sequential linear-time algorithm for the longest path problem in meshes. Then based on this algorithm, we present a constant-time parallel algorithm for the problem, which can be run on every parallel machine.