Static fatigue of Hi-Nicalon™-S fiber at elevated temperature in air,steam, and silicic acid-saturated steam

A facility for testing SiC fiber tows in static fatigue and creep at elevated temperatures in air and steam was developed. Static fatigue of Hi-Nicalon™-S fibers was investigated at 800°C-1100°C at applied stresses between 115 and 1250 MPa in air, in Si(OH)₄(g)-saturated steam, and in unsaturated steam. Fibers tested in Si(OH)₄(g)-saturated steam and in air had silica scales throughout the test sections, but those tested in unsaturated steam did not develop scales near the steam injection point. Fiber lifetimes in static fatigue were shortest in unsaturated steam, intermediate in Si(OH)₄(g)-saturated steam, and longest in air. Failure strains did not exceed 0.3%. Steady-state strain rates and static fatigue lifetimes are modelled empirically by the Monkman-Grant relationship. Failure mechanisms are discussed.     

Chemical Ecology of the host searching behavior in an Egg Parasitoid: are Common Chemical Cues exploited to locate hosts in Taxonomically Distant Plant Species?

Parasitoids are known to exploit volatile cues emitted by plants after herbivore attack to locate their hosts. Feeding and oviposition of a polyphagous herbivore can induce the emission of odor blends that differ among distant plant species, and parasitoids have evolved an incredible ability to discriminate them and locate their hosts relying on olfactive cues. We evaluated the host searching behavior of the egg parasitoid Cosmocomoidea annulicornis (Ogloblin) (Hymenoptera: Mymaridae) in response to odors emitted by two taxonomically distant host plants, citrus and Johnson grass, after infestation by the sharpshooter Tapajosa rubromarginata (Signoret) (Hemiptera: Cicadellidae), vector of Citrus Variegated Chlorosis. Olfactory response of female parasitoids toward plants with no herbivore damage and plants with feeding damage, oviposition damage, and parasitized eggs was tested in a Y-tube olfactometer. In addition, volatiles released by the two host plant species constitutively and under herbivore attack were characterized. Females of C. annulicornis were able to detect and significantly preferred plants with host eggs, irrespectively of plant species. However, wasps were unable to discriminate between plants with healthy eggs and those with eggs previously parasitized by conspecifics. Analysis of plant volatiles induced after sharpshooter attack showed only two common volatiles between the two plant species, indole and β-caryophyllene. Our results suggest that this parasitoid wasp uses common chemical cues released by many different plants after herbivory at long range and, once on the plant, other more specific chemical cues could trigger the final decision to oviposit.

     

Continuous prediction of manufacturing performance throughout the production lifecycle

We describe methods for continual prediction of manufactured product quality prior to final testing. In our most expansive modeling approach, an estimated final characteristic of a product is updated after each manufacturing operation. Our initial application is for the manufacture of microprocessors, and we predict final microprocessor speed. Using these predictions, early corrective manufacturing actions may be taken to increase the speed of expected slow wafers (a collection of microprocessors) or reduce the speed of fast wafers. Such predictions may also be used to initiate corrective supply chain management actions. Developing statistical learning models for this task has many complicating factors: (a) a temporally unstable population (b) missing data that is a result of sparsely sampled measurements and (c) relatively few available measurements prior to corrective action opportunities. In a real manufacturing pilot application, our automated models selected 125 fast wafers in real-time. As predicted, those wafers were significantly faster than average. During manufacture, downstream corrective processing restored 25 nominally unacceptable wafers to normal operation.     

Copper anode corrosion affects power generation in microbial fuel cells

Non‐corrosive, carbon‐based materials are usually used as anodes in microbial fuel cells (MFCs). In some cases, however, metals have been used that can corrode (e.g. copper) or that are corrosion resistant (e.g. stainless steel, SS). Corrosion could increase current through galvanic (abiotic) current production or by increasing exposed surface area, or decrease current due to generation of toxic products from corrosion. In order to directly examine the effects of using corrodible metal anodes, MFCs with Cu were compared with reactors using SS and carbon cloth anodes. MFCs with Cu anodes initially showed high current generation similar to abiotic controls, but subsequently they produced little power (2 mW m^‐2). Higher power was produced with microbes using SS (12 mW m^‐2) or carbon cloth (880 mW m^‐2) anodes, with no power generated by abiotic controls. These results demonstrate that copper is an unsuitable anode material, due to corrosion and likely copper toxicity to microorganisms. © 2013 Society of Chemical Industry     

Task-switching performance with 1:1 and 2:1 cue–task mappings: Not so different after all.

When task-switching studies use the task-cuing procedure with a 1:1 cue–task mapping, task switching and cue switching are confounded, which is problematic for interpreting switch costs. The use of a 2:1 cue–task mapping is a potential solution to this problem, but it is possible that introducing more cues may also introduce marked changes in task-switching performance. In 5 experiments involving 160 subjects, the authors compared performance with 1:1 and 2:1 mappings across several methodological changes. Differences in switch costs between mappings were small and, in most analyses, nonsignificant. In all experiments, both mappings yielded significant reductions in switch cost across cue–target interval, and there were significant cue-switching effects with the 2:1 mapping. A model of cue encoding fit the data from both mappings about equally well. Overall, task-switching performance was more similar than it was different between mappings, leading the authors to suggest that the use of a 2:1 mapping is a viable solution to the problem associated with a 1:1 mapping. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Efficient recovery of nano-sized iron oxide particles from synthetic acid-mine drainage (AMD) water using fuel cell technologies

Acid mine drainage (AMD) is an important contributor to surface water pollution due to the release of acid and metals. Fe(II) in AMD reacts with dissolved oxygen to produce iron oxide precipitates, resulting in further acidification, discoloration of stream beds, and sludge deposits in receiving waters. It has recently been shown that new fuel cell technologies, based on microbial fuel cells, can be used to treat AMD and generate electricity. Here we show that this approach can also be used as a technique to generate spherical nano-particles of iron oxide that, upon drying, are transformed to goethite (α-FeOOH). This approach therefore provides a relatively straightforward way to generate a product that has commercial value. Particle diameters ranged from 120 to 700 nm, with sizes that could be controlled by varying the conditions in the fuel cell, especially current density (0.04-0.12 mA/cm²), pH (4-7.5), and initial Fe(II) concentration (50-1000 mg/L). The most efficient production of goethite and power occurred with pH = 6.3 and Fe(II) concentrations above 200 mg/L. These results show that fuel cell technologies can not only be used for simultaneous AMD treatment and power generation, but that they can generate useful products such as iron oxide particles having sizes appropriate for used as pigments and other applications.     

Optimal gate sizing using a self-tuning multi-objective framework

In this paper, we present a self-tuning multi-objective framework for geometric programming that provides a fine trade-off between the competing objectives. The significance of this framework is that the designer does not need to perform any tuning of weights of objectives. The proposed framework is applied to gate sizing and clock network buffer sizing problems. In gate sizing application, power consumption is reduced on average by 86% while delay sees only an increase of 34 ns. In clock network butter sizing application, our framework results in a significant reduction in power, 57%, and an improvement of 31 ps in skew.     

Injury prediction in a side impact crash using human body model simulation

Background

Improved understanding of the occupant loading conditions in real world crashes is critical for injury prevention and new vehicle design. The purpose of this study was to develop a robust methodology to reconstruct injuries sustained in real world crashes using vehicle and human body finite element models.

Methods

A real world near-side impact crash was selected from the Crash Injury Research and Engineering Network (CIREN) database. An average sedan was struck at approximately the B-pillar with a 290 degree principal direction of force by a lightweight pickup truck, resulting in a maximum crush of 45 cm and a crash reconstruction derived Delta-V of 28 kph. The belted 73-year-old midsized female driver sustained severe thoracic injuries, serious brain injuries, moderate abdominal injuries, and no pelvic injury. Vehicle finite element models were selected to reconstruct the crash. The bullet vehicle parameters were heuristically optimized to match the crush profile of the simulated struck vehicle and the case vehicle. The Total Human Model for Safety (THUMS) midsized male finite element model of the human body was used to represent the case occupant and reconstruct her injuries using the head injury criterion (HIC), half deflection, thoracic trauma index (TTI), and pelvic force to predict injury risk. A variation study was conducted to evaluate the robustness of the injury predictions by varying the bullet vehicle parameters.

Results

The THUMS thoracic injury metrics resulted in a calculated risk exceeding 90% for AIS3+ injuries and 70% risk of AIS4+ injuries, consistent with her thoracic injury outcome. The THUMS model predicted seven rib fractures compared to the case occupant's 11 rib fractures, which are both AIS3 injuries. The pelvic injury risk for AIS2+ and AIS3+ injuries were 37% and 2.6%, respectively, consistent with the absence of pelvic injury. The THUMS injury prediction metrics were most sensitive to bullet vehicle location. The maximum 95% confidence interval width for the mean injury metrics was only 5% demonstrating high confidence in the THUMS injury prediction.

Conclusions

This study demonstrates a variation study methodology in which human body models can be reliably used to robustly predict injury probability consistent with real world crash injury outcome.