An alternative to the claus process for treating hydrogen sulfide

The thermochemical decomposition of hydrogen sulfide by concentrated sunlight was investigated. Three commercial catalysts were used to improve the kinetics of the reaction. It was shown that a cobalt-molybdenum catalyst has the highest activity. A hydrogen yield of 19% was obtained at a reaction temperature of 770 °C and residence time of 0.3 sec. An activation energy of 13.3 kcal/mol was determined for the catalyzed reaction.     

A computational simulation study for techno-economic comparison of conventional and stripping gas methods for natural gas dehydration

In the present work, the conventional natural gas dehydration method (CDM) and stripping gas method (SGM) are technically and economically analyzed, utilizing Aspen HYSYS and Aspen Process Economic Analyzer (APEA), respectively. To optimize the CDM and SGM, the sensitivities of the water content of dry gas, reboiler duty and raw material loss are analyzed against solvent rate and stripping gas rate. The optimized processes are set to achieve a targeted value of water content in dry gas and analyzed at optimized point. The analysis shows that SGM gives 46% lower TEG feed rate, 42% lower reboiler duty and 99.97% pure regenerated TEG. Moreover, economic analysis reveals that SGM has 38% lower annual operating cost compared to CDM. According to results, from both technical and economic point of view, SGM is more feasible for natural gas dehydration compared to CDM.     

A fuzzy particle swarm optimization algorithm for computer communication network topology design

Particle swarm optimization (PSO) is a powerful optimization technique that has been applied to solve a number of complex optimization problems. One such optimization problem is topology design of distributed local area networks (DLANs). The problem is defined as a multi-objective optimization problem requiring simultaneous optimization of monetary cost, average network delay, hop count between communicating nodes, and reliability under a set of constraints. This paper presents a multi-objective particle swarm optimization algorithm to efficiently solve the DLAN topology design problem. Fuzzy logic is incorporated in the PSO algorithm to handle the multi-objective nature of the problem. Specifically, a recently proposed fuzzy aggregation operator, namely the unified And-Or operator (Khan and Engelbrecht in Inf. Sci. 177: 2692–2711, 2007), is used to aggregate the objectives. The proposed fuzzy PSO (FPSO) algorithm is empirically evaluated through a preliminary sensitivity analysis of the PSO parameters. FPSO is also compared with fuzzy simulated annealing and fuzzy ant colony optimization algorithms. Results suggest that the fuzzy PSO is a suitable algorithm for solving the DLAN topology design problem.     

Formal methods applied to high‐performance computing software design: a case study of MPI one‐sided communication‐based locking

There is a growing need to address the complexity of verifying the numerous concurrent protocols employed in the high‐performance computing software. Today's approaches for verification consist of testing detailed implementations of these protocols. Unfortunately, this approach can seldom show the absence of bugs, and often results in serious bugs escaping into the deployed software. An approach called Model Checking has been demonstrated to be eminently helpful in debugging these protocols early in the software life cycle by offering the ability to represent and exhaustively analyze simplified formal protocol models. The effectiveness of model checking has yet to be adequately demonstrated in high‐performance computing. This paper presents a case study of a concurrent protocol that was thought to be sufficiently well tested, but proved to contain two very non‐obvious deadlocks in them. These bugs were automatically detected through model checking. The protocol models in which these bugs were detected were also easy to create. Recent work in our group demonstrates that even this tedium of model creation can be eliminated by employing dynamic source‐code‐level analysis methods. Our case study comes from the important domain of Message Passing Interface (MPI)‐based programming, which is universally employed for simulating and predicting anything from the structural integrity of combustion chambers to the path of hurricanes. We argue that model checking must be taught as well as used widely within HPC, given this and similar success stories. Copyright © 2009 John Wiley & Sons, Ltd.     

Feature Preserving Mesh Generation from 3D Point Clouds

We address the problem of generating quality surface triangle meshes from 3D point clouds sampled on piecewise smooth surfaces. Using a feature detection process based on the covariance matrices of Voronoi cells, we first extract from the point cloud a set of sharp features. Our algorithm also runs on the input point cloud a reconstruction process, such as Poisson reconstruction, providing an implicit surface. A feature preserving variant of a Delaunay refinement process is then used to generate a mesh approximating the implicit surface and containing a faithful representation of the extracted sharp edges. Such a mesh provides an enhanced trade‐off between accuracy and mesh complexity. The whole process is robust to noise and made versatile through a small set of parameters which govern the mesh sizing, approximation error and shape of the elements. We demonstrate the effectiveness of our method on a variety of models including laser scanned datasets ranging from indoor to outdoor scenes.     

On the iterative refinement of the solution of ill-conditioned linear system of equations

Recently, Salkuyeh and Fahim [A new iterative refinement of the solution of ill-conditioned linear system of equations, Int. Comput. Math. 88(5) (2011), pp. 950–956] have proposed a two-step iterative refinement of the solution of an ill-conditioned linear system of equations. In this paper, we first present a generalized two-step iterative refinement procedure to solve ill-conditioned linear system of equations and study its convergence properties. Afterward, it is shown that the idea of an orthogonal projection technique together with a basic stationary iterative method can be utilized to construct a new efficient and neat hybrid algorithm for solving the mentioned problem. The convergence of the offered hybrid approach is also established. Numerical examples are examined to demonstrate the feasibility of proposed algorithms and their superiority to some of existing approaches for solving ill-conditioned linear system of equations.     

Satellite remote sensing of total ozone column (TOC) over Pakistan and neighbouring regions

Total ozone column (TOC) obtained from the Ozone Monitoring Instrument (OMI) on board the Aura satellite was utilized to examine the spatio-temporal distribution of atmospheric ozone over Pakistan and adjoining regions of Afghanistan, India, and Iran for October 2004 to March 2014. This region has not yet been evaluated in greater detail. A yearly spatial averaged value of 278 ± 2 DU was found over the region. A decadal increase of 1.3% in TOC value over study region was observed for the first time. Large spatial and temporal variability of TOC was found over the study region. Elevated ozone columns were observed over the regions with high NO₂ and CO concentrations. Analysis indicated that Srinagar city has the highest averaged value of 290 ± 3 DU whereas Jodhpur city showed the highest increasing trend of 1.9% per decade. A monthly averaged maximum value of 289 ± 8 DU and a minimum of 264 ± 5 DU were found during April and November, respectively, over the region. January showed a decreasing trend of ?0.8% and February exhibited the highest increasing trend of 5.1% per decade. Forward trajectory analysis showed the possibility of ozone transport from eastern parts of the study region towards the Indian Ocean (Bay of Bengal) through the subtropical jet stream creating low values at higher meridians in October. TOC data deduced from OMI and the Atmospheric Infrared Sounder were compared to check the level of correlation and the results showed significant correlation (r = 0.75) and an acceptable average relative difference of 4.2%.     

Geometry design of herringbone structures for cancer cell capture in a microfluidic device

Cancer cell detection with high capture efficiency is important for its extensive clinical applications. Herringbone structures in microfluidic devices have been widely adopted to increase the cell capture performance due to its chaotic effect. Given the fact of laminar flow in microfluidic devices, geometry-based optimization acting as a design strategy is effective and can help researchers reduce repetitive trial experiments. In this work, we presented a computational model to track the cell motion and used normalized capture efficiency to evaluate the tumor cell capture performance under various geometry settings. Cell adhesion probability was implemented in the model to consider the nature of ligand–receptor formation and breakage during cell–surface interactions. A facile approach was introduced to determine the two lumped coefficients of cell adhesion probability through two microfluidic experiments. A comprehensive geometric study was then performed by using this model, and results were explained from the fluid dynamics. Although most of the geometric guides agree with the general criterion concluded in the literature, we found herringbone structures with symmetric arms rather than a short arm–long arm ratio of 1/3 are optimal. This difference mainly comes from the fact that our model considers the particulate nature of cells while most studies in the literature optimize the geometry merely relying on mixing effects. Thus, our computational model implemented with cell adhesion probability can serve as a more accurate and reliable approach to optimize microfluidic devices for cancer cell capture.