Damage evolution in polymer due to exposure to high-pressure hydrogen gas

The use of hydrogen as a fuel is increasing exponentially, and the most economical way to store and transport hydrogen for fuel use is as a high-pressure gas. Polymers are widely used for hydrogen distribution and storage systems because they are chemically inert towards hydrogen. However, when exposed to high-pressure hydrogen, some hydrogen diffuses through polymers and occupies the preexisting cavities inside the material. Upon depressurization, the hydrogen trapped inside polymer cavities can cause blistering or cracking by expanding these cavities. A continuum mechanics–based deformation model was deployed to predict the stress distribution and damage propagation while the polymer undergoes depressurization after high-pressure hydrogen exposure. The effects of cavity size, cavity location, and pressure inside the cavity on damage initiation and evolution inside the polymer were studied. The stress and damage evolution in the presence of multiple cavities was also studied, because interaction among cavities alters the damage and stress field. It was found that all these factors significantly change the stress state in the polymer, resulting in different paths for damage propagation. The effect of adding carbon black filler particles and plasticizer on the damage was also studied. It was found that damage tolerance of the polymer increases drastically with the addition of carbon black fillers, but decreases with the addition of the plasticizer.     

Fault tolerance in wireless sensor network using hand-off and dynamic power adjustment approach

Wireless Sensor Network (WSN) is deployed to monitor physical conditions in various places such as geographical regions, agriculture lands, office buildings, industrial plants and battlefields. WSNs are prone to different types of failures due to various environmental hazards like interference and internal failures (such as battery failure, processor failure, transceiver failure, etc). In such a situation, the sensed data cannot be transmitted correctly to the data center and the very purpose of deploying WSNs is not effective. Since it is difficult to monitor the network continuously through a manual operator, the nodes in WSN need to be capable of overcoming the failures and transmit the sensed data in proper order to the data center. Sensor network should be designed such that it should be able to identify the faulty nodes, try to rectify the fault and be able to transmit the sensed data to data center under faulty condition of a network and thereby make the network fault-free and thus enhance the fault tolerant capability.In this paper, we propose a novel idea of an Active node based Fault Tolerance using Battery power and Interference model (AFTBI) in WSN to identify the faulty nodes using battery power model and interference model. Fault tolerance against low battery power is designed through hand-off mechanism where in the faulty node selects the neighboring node having highest power and transfers all the services that are to be performed by the faulty node to the selected neighboring node. Fault tolerance against interference is provided by dynamic power level adjustment mechanism by allocating the time slot to all the neighboring nodes. If a particular node wishes to transmit the sensed data, it enters active status and transmits the packet with maximum power; otherwise it enters into sleep status having minimum power that is sufficient to receive hello messages and to maintain the connectivity. The performance evaluation is tested through simulation for packet delivery ratio, control overhead, memory overhead and fault recovery delay. We compared our results with Fault Detection in Wireless Sensor Networks (FDWSNs) for various performance measures and found that AFTBI outperforms compared to the results of FDWSN.     

Not so black and white: Memory for ambiguous group members.

Exponential increases in multiracial identities, expected over the next century, create a conundrum for perceivers accustomed to classifying people as their own- or other-race. The current research examines how perceivers resolve this dilemma with regard to the own-race bias. The authors hypothesized that perceivers are not motivated to include ambiguous-race individuals in the in-group and therefore have some difficulty remembering these individuals. Both racially ambiguous and other-race faces were misremembered more often than own-race faces (Study 1), though memory for ambiguous faces was improved among perceivers motivated to include biracial individuals in the in-group (Study 2). Racial labels assigned to racially ambiguous faces determined memory for these faces, suggesting that uncertainty provides the motivational context for discounting ambiguous faces in memory (Study 3). Finally, an inclusion motivation fostered cognitive associations between racially ambiguous faces and the in-group. Moreover, the extent to which perceivers associated racially ambiguous faces with the in-group predicted memory for ambiguous faces and accounted for the impact of motivation on memory (Study 4). Thus, memory for biracial individuals seems to involve a flexible person construal process shaped by motivational factors. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Impact toughness,viscoelastic behavior,and morphology of polypropylene–jute–viscose hybrid composites

In this investigation, we studied the impact toughness and viscoelastic behavior of polypropylene (PP)–jute composites. In this study, we used viscose fiber as an impact modifier and maleated PP as a compatibilizer. The toughness of the composites was studied with conventional Charpy and instrumental falling‐weight impact tests. The composites’ viscoelastic properties were studied with dynamic mechanical analysis. The results show that the incorporation of viscose fibers improved the impact strength and toughness to 134 and 65% compared to those of the PP–jute composites. The tan δ peak amplitude also increased with the addition of the impact modifier and indicated a greater degree of molecular mobility. The thermal stability of the composites was evaluated with thermogravimetric analysis. The addition of 2 wt % maleated polypropylene (MAPP) to the impact‐modified composite improved the impact strength and toughness to 144 and 93%, respectively. The fiber–matrix morphology of the fracture surface and the Fourier transform infrared spectra were also studied to ascertain the existence of the type of interfacial bonds. Microstructural analysis showed the retention of viscose fibers in the composites compared to the more separated jute fibers. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 42981.     

Coupling fiber optics to a permeation liquid membrane for heavy metal sensor development

We present the first sensing system for metal ions based on the combination of separation/preconcentration by a permeation liquid membrane (PLM) and fluorescence detection with an optical fiber. As a model, a system for the detection of Cu(II) ions was developed. The wall of a polypropylene hollow fiber serves as support for the permeable liquid membrane. The lumen of the fiber contains the strip solution in which Cu(II) is accumulated. Calcein, a fluorochromic dye, acts as stripping agent and at the same time as metal indicator. The quenching of the calcein fluorescence upon metal accumulation in the strip phase is detected with a multimode optical fiber, which is incorporated into the lumen. Fluorescence is excited with a blue LED and detected with a photon counter. Taking advantage of the high selectivity and sensitivity of PLM preconcentration, a detection limit for Cu(II) of approximately 50 nM was achieved. Among five tested heavy metal ions, Pb(II) was the only major interfering species. The incorporation of small silica optical fibers into the polypropylene capillary allows for real-time monitoring of the Cu(II) accumulation process.     

Directory-based composite routing and scheduling policies for dynamic multimedia environments

In this paper we present and evaluate algorithms to address combined path and server selection (CPSS) problems in highly dynamic multimedia environments. Our goal is to ensure effective utilization of network and server resources while tolerating imprecision in system state information. Components within the framework implement the optimized scheduling policies as well as collect/update the network and server parameters using a directory service. We present and analyze multiple policies to solve the CPSS problem. In addition, we study multiple techniques for updating the directory service with system state information. We further evaluate the performance of the CPSS policies under different update mechanisms and study the implications of the CPSS policies on directory service management.     

Selecting exposure measures in crash rate prediction for two-lane highway segments

A critical part of any risk assessment is identifying how to represent exposure to the risk involved. Recent research shows that the relationship between crash count and traffic volume is non-linear; consequently, a simple crash rate computed as the ratio of crash count to volume is not proper for comparing the safety of sites with different traffic volumes. To solve this problem, we describe a new approach for relating traffic volume and crash incidence. Specifically, we disaggregate crashes into four types: (1) single-vehicle, (2) multi-vehicle same direction, (3) multi-vehicle opposite direction, and (4) multi-vehicle intersecting, and define candidate exposure measures for each that we hypothesize will be linear with respect to each crash type. This paper describes initial investigation using crash and physical characteristics data for highway segments in Michigan from the Highway Safety Information System (HSIS). We use zero-inflated-Poisson (ZIP) modeling to estimate models for predicting counts for each of the above crash types as a function of the daily volume, segment length, speed limit and roadway width. We found that the relationship between crashes and the daily volume (AADT) is non-linear and varies by crash type, and is significantly different from the relationship between crashes and segment length for all crash types. Our research will provide information to improve accuracy of crash predictions and, thus, facilitate more meaningful comparison of the safety record of seemingly similar highway locations.