High-speed,two-dimensional digital image correlation algorithm using heterogeneous (CPU-GPU) framework

Two-dimensional digital image correlation (2D-DIC) is an experimental technique used to measure in-plane displacement of a test specimen. Real-time measurement of full-field displacement data is challenging due to enormous computational load of the algorithm. In order to improve the computational speed, the focus of recent research works has been on the approach of parallelization across subsets within image pairs using graphics processing unit (GPU). But alternate GPU-based parallelization approaches to improve the performance of this algorithm as per the order of data processing have not been explored. To address this research gap, our method utilizes parallelism within a subset as well as across subsets for each computation step in an iteration cycle. A heterogeneous (CPU-GPU) framework in combination with a pyramid-based initial values estimation for subsets (in parallel) is proposed in this work. The precompute steps of the proposed framework are implemented using CPU, whereas the main iterative steps are realized using GPU. It is demonstrated that the overall computational speed of the proposed heterogeneous framework improves by compared to a sequential CPU-based implementation for a pair of gray-scale images with a resolution of pixels. As an important milestone, feasibility to measure deformations in real time ( 1 s) is manifested in this study.     

A grounded theory model for analysis of marine accidents

The purpose of this paper was to design a conceptual model for analysis of marine accidents. The model is grounded on large amounts of empirical data, i.e. the Swedish Maritime Administration database, which was thoroughly studied. This database contains marine accidents organized by ship and variable. The majority of variables are non-metric and some have never been analyzed because of the large number of values. Summary statistics were employed in the data analysis. In order to develop a conceptual model, the database variables were clustered into eleven main categories or constructs, which were organized according to their properties and connected with the path diagram of relationships. For demonstration purposes, one non-metric and five metric variables were selected, namely fatality, ship's properties (i.e. age, gross register tonnage, and length), number of people on board, and marine accidents. These were analyzed using the structural equation modeling (SEM) approach. The combined prediction power of the ‘ship's properties’ and ‘number of people on board’ independent variables accounted for 65% of the variance of the fatality. The model development was largely based on the data contained in the Swedish database. However, as this database shares a number of variables in common with other databases in the region and the world, the model presented in this paper could be applied to other datasets. The model has both theoretical and practical values. Recommendations for improvements in the database are also suggested.     

Experimental and Numerical Study of Serpentine Flow Fields for Improving Direct Methanol Fuel Cell Performance

Methanol crossover is an important issue as it affects direct methanol fuel cell (DMFC) performance. But it may be controlled by selecting a proper flow field design. Experiments were carried out to investigate the effect of single, double and triple serpentine flow field configurations on a DMFC with a 25 cm² membrane electrode assembly (MEA) with a constant open ratio. A three dimensional model was also developed for the anode of the DMFC to predict methanol concentration and cell current density distributions. Experimental and model results show that at lower methanol concentrations (0.25–0.5M), single serpentine flow field (SSFF) provides high peak power density, while a double serpentine flow field (DSFF) gives high peak power density at a high methanol concentration (1–2M). Single and double serpentine flow fields exhibit the same peak power density (33 mW cm⁻²) at 1M. But the cell efficiency of double serpentine flow field is 12.5% which is 3.5% point greater than single serpentine flow field. This is attributed to reduced mixed potential. triple serpentine flow field (TSFF) shows the lowest peak power density and cell efficiency, which is attributed to high mass transfer resistance.     

Existence of Solutions and Approximate Controllability of Fractional Nonlocal Neutral Impulsive Stochastic Differential Equations of Order 1 &lt; <Emphasis Type="Italic">q</Emphasis> &lt; 2 with Infinite Delay and Poisson Jumps

In this paper, we study the existence of mild solutions and the approximate controllability of nonlinear fractional nonlocal neutral impulsive stochastic differential equations of order 1 < q < 2 with infinite delay and Poisson jumps in which the initial value belong to the abstract phase space C _h . The existence of mild solutions is derived with the help of Sadovskii’s fixed point theorem. The approximate controllability of the nonlinear fractional nonlocal neutral impulsive stochastic differential systems of order 1 < q < 2 with infinite delay and Poisson jumps is discussed under the assumption that the corresponding linear system is approximately controllable. Moreover, the approximate controllability of the above control system is established by using Lebesgue dominated convergence theorem. An example is provided to illustrate the theory.