Hardness of porous nanocrystalline Co-Ni electrodeposits

The Hall-Petch relationship can fail when the grain size is below a critical value of tens of nanometres. This occurs particularly for coatings having porous surfaces. In this study, electrodeposited nanostructured Co-Ni coatings from four different nickel electroplating baths having grain sizes in the range of 11-23 nm have been investigated. The finest grain size, approximately 11 nm, was obtained from a coating developed from the nickel sulphate bath. The Co-Ni coatings have a mixed face centred cubic and hexagonal close-packed structures with varying surface morphologies and different porosities. A cluster-pore mixture model has been proposed by considering no contribution from pores to the hardness. As the porosity effect was taken into consideration, the calculated pore-free hardness is in agreement with the ordinary Hall-Petch relationship even when the grain size is reduced to 11 nm for the Co-Ni coatings with 77±2 at% cobalt. The present model was applied to other porous nanocrystalline coatings, and the Hall-Petch relationship was maintained. © 2013 The Korean Institute of Metals and Materials and Springer Science+Business Media Dordrecht. © KIM and Springer

New Measurements of Nucleon Structure Functions from the CCFR/NuTeV Collaboration

We report on the extraction of the structure functions F_2 and Delta xF_3 = xF_3nu-xF_3nubar from CCFR neutrino-Fe and antineutrino-Fe differential cross sections. The extraction is performed in a physics model independent (PMI) way. This first measurement for Delta xF_3, which is useful in testing models of heavy charm production, is higher than current theoretical predictions. The F_2 (PMI) values measured in neutrino and muon scattering are in good agreement with the predictions of Next to Leading Order PDFs (using massive charm production schemes), thus resolving the long-standing discrepancy between the two sets of data.Comment: 5 pages. Presented by Arie Bodek at the CIPNAP2000 Conference, Quebec City, May 200

Choice of activity-intensity classification thresholds impacts upon accelerometer-assessed physical activity-health relationships in children

It is unknown whether using different published thresholds (PTs) for classifying physical activity (PA) impacts upon activity-health relationships. This study explored whether relationships between PA (sedentary [SED], light PA [LPA], moderate PA [MPA], moderate-to-vigorous PA, vigorous PA [VPA]) and health markers differed in children when classified using three different PTs

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP

Shape modeling technique KOALA validated by ESA Rosetta at (21) Lutetia

We present a comparison of our results from ground-based observations of asteroid (21) Lutetia with imaging data acquired during the flyby of the asteroid by the ESA Rosetta mission. This flyby provided a unique opportunity to evaluate and calibrate our method of determination of size, 3-D shape, and spin of an asteroid from ground-based observations. We present our 3-D shape-modeling technique KOALA which is based on multi-dataset inversion. We compare the results we obtained with KOALA, prior to the flyby, on asteroid (21) Lutetia with the high-spatial resolution images of the asteroid taken with the OSIRIS camera on-board the ESA Rosetta spacecraft, during its encounter with Lutetia. The spin axis determined with KOALA was found to be accurate to within two degrees, while the KOALA diameter determinations were within 2% of the Rosetta-derived values. The 3-D shape of the KOALA model is also confirmed by the spectacular visual agreement between both 3-D shape models (KOALA pre- and OSIRIS post-flyby). We found a typical deviation of only 2 km at local scales between the profiles from KOALA predictions and OSIRIS images, resulting in a volume uncertainty provided by KOALA better than 10%. Radiometric techniques for the interpretation of thermal infrared data also benefit greatly from the KOALA shape model: the absolute size and geometric albedo can be derived with high accuracy, and thermal properties, for example the thermal inertia, can be determined unambiguously. We consider this to be a validation of the KOALA method. Because space exploration will remain limited to only a few objects, KOALA stands as a powerful technique to study a much larger set of small bodies using Earth-based observations.Comment: 15 pages, 8 figures, 2 tables, accepted for publication in P&S