Numerical Analysis of Bird Impact on Glass-Reinforced Leading Edge of an Aircraft Wing

The paper describes the methodology of modeling and simulation of bird impact mechanism of GLARE laminate structures. The bird is modeled using Lagrangian concept. Explicit finite element techniques have been developed to simulate the impact mechanics. The study involves deeper understanding of impact dynamics and contact mechanics. The bird impact analysis has been carried out on typical configuration of GLARE 3/2, 4/3, 5/4, 6/5, 7/6 and 8/7. The results of stress propagation and material deformation at high strain rate have been obtained. Results from the numerical analysis are compared with experimental results, and the material is found to be capable of absorbing the impact energy. The results also show that the bird material model chosen to simulate for carrying out impact mechanics analysis is found to be capable of capturing most of the complex behavior exhibited by functional structural material GLARE.     

Corrosion inhibition behaviour of thiourea derivatives in acid media against mild steel deterioration: An overview

This paper summarizes the inhibitor activity of various reported thiourea derivatives in acid media used against the deterioration of mild steel. Acid solutions have been extensively employed in manufacturing and many industrial processes for pickling and removal of undesirable scale. Mild steel is highly susceptible to corrosion in such aggressive acid media. The additives such as inhibitors are widely employed in those cases to reduce the extent of corrosion as much as possible. The survey of literature on organic inhibitors clearly indicates the potential usage of thiourea derivatives as inhibitors of mild steel corrosion. The influence of physical-chemical properties on the inhibition activity of thiourea derivatives has been discussed. This information is highly useful for different industrial applications where good performing inhibitors are being required for protecting mild steel from aggressive acid media.     

An efficient algorithm for mass detection and shape analysis of different masses present in digital mammograms

The present study introduces an efficient algorithm for automatic segmentation and detection of mass present in the mammograms. The problem of over and under-segmentation of low-contrast mammographic images has been solved by applying preprocessing on original mammograms. Subtraction operation performed between enhanced and enhanced inverted mammogram significantly highlights the suspicious mass region in mammograms. The segmentation accuracy of suspicious region has been improved by combining wavelet transform and fast fuzzy c-means clustering algorithm. The accuracy of mass segmentation has been quantified by means of Jaccard coefficients. Better sensitivity, specificity, accuracy, and area under the curve (AUC) are observed with support vector machine using radial basis kernel function. The proposed algorithm is validated on Mini-Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammography (DDSM) datasets. Highest 91.76% sensitivity, 96.26% specificity, 95.46% accuracy, and 96.29% AUC on DDSM dataset and 94.63% sensitivity, 92.74% specificity, 92.02% accuracy, and 95.33% AUC on MIAS dataset are observed. Also, shape analysis of mass is performed by using moment invariant and Radon transform based features. The best results are obtained with Radon based features and achieved accuracies for round, oval, lobulated, and irregular shape of mass are 100%, 70%, 64%, and 96%, respectively.     

3D multi-material and multi-joint topology optimization with tooling accessibility constraints

Structural and Multidisciplinary Optimization - This paper proposes a method for performing both multi-material topology optimization and multi-joint topology optimization. The algorithm can...     

Linked Simulation-Optimization based Dedicated Monitoring Network Design for Unknown Pollutant Source Identification using Dynamic Time Warping Distance

Implementation of monitoring strategy for increasing the efficiency of groundwater pollutant source characterization is often necessary, especially when only inadequate and arbitrary concentration measurement data are initially available. Two main parameters that need to be estimated for efficient and accurate characterization of groundwater pollution sources are: location of the source and the time when the source became active. Complexities involved with the explicit estimation of the time of start and source activity have not been addressed so far in previous studies. The main complexity arises due to the fact that the spatial location and time of activity are inter-related. Therefore, specifying one and solving for the other simplifies the source characterization problem. Hence, in this study, both the source location and time of initiation are treated as unknowns. The developed methodology uses dynamic time warping distance in the linked simulation-optimization model to address some complex issues in designing a monitoring network to efficiently estimate source characteristics including the time of first activity of unknown groundwater source. Performance of the developed methodology is evaluated on illustrative contaminated aquifer. These evaluation results demonstrate the potential use of the developed methodology.     

Addressing spatiotemporal and computational heterogeneity in structured adaptive mesh refinement

Structured adaptive mesh refinement (SAMR) techniques can provide accurate and cost- effective solutions to realistic scientific and engineering simulations modeling complex physical phenomena. However, the adaptive nature and inherent space–time heterogeneity of SAMR applications result in significant runtime management challenges. Moreover, certain SAMR applications involving reactive flows exhibit pointwise varying workloads and cannot be addressed by traditional parallelization approaches, which assume homogeneous loads. This paper presents hierarchical partitioning, bin-packing based load balancing, and Dispatch structured partitioning strategies to manage the spatiotemporal and computational heterogeneity in SAMR applications. Experimental evaluation of these schemes using 3-D Richtmyer–Meshkov compressible turbulence and 2-D reactive-diffusion kernels demonstrates the improvement in overall performance.     

Socket Buffer Auto-Sizing for High-Performance Data Transfers

It is often claimed that TCP is not a suitable transport protocol for data intensive Grid applications in high-performance networks. We argue that this is not necessarily the case. Without changing the TCP protocol, congestion control, or implementation, we show that an appropriately tuned TCP bulk transfer can saturate the available bandwidth of a network path. The proposed technique, called SOBAS, is based on automatic socket buffer sizing at the application layer. In non-congested paths, SOBAS limits the socket buffer size based on direct measurements of the received throughput and of the corresponding round-trip time. The key idea is that the send window should be limited, after the transfer has saturated the available bandwidth in the path, so that the transfer does not cause buffer overflows (self-induced losses). A difference with other socket buffer sizing schemes is that SOBAS does not require prior knowledge of the path characteristics, and it can be performed while the transfer is in progress. Experimental results in several high bandwidth-delay product paths show that SOBAS provides consistently a significant throughput increase (20% to 80%) compared to TCP transfers that use the maximum possible socket buffer size. We expect that SOBAS will be mostly useful for applications such as GridFTP in non-congested wide-area networks.     

Production of Two‐Dimensional Nanomaterials via Liquid‐Based Direct Exfoliation

Tremendous efforts have been devoted to the synthesis and application of two‐dimensional (2D) nanomaterials due to their extraordinary and unique properties in electronics, photonics, catalysis, etc., upon exfoliation from their bulk counterparts. One of the greatest challenges that scientists are confronted with is how to produce large quantities of 2D nanomaterials of high quality in a commercially viable way. This review summarizes the state‐of‐the‐art of the production of 2D nanomaterials using liquid‐based direct exfoliation (LBE), a very promising and highly scalable wet approach for synthesizing high quality 2D nanomaterials in mild conditions. LBE is a collection of methods that directly exfoliates bulk layered materials into thin flakes of 2D nanomaterials in liquid media without any, or with a minimum degree of, chemical reactions, so as to maintain the high crystallinity of 2D nanomaterials. Different synthetic methods are categorized in the following, in which material characteristics including dispersion concentration, flake thickness, flake size and some applications are discussed in detail. At the end, we provide an overview of the advantages and disadvantages of such synthetic methods of LBE and propose future perspectives.