An experimental study on the load carrying capacity of cold-formed steel studs and panels

A full-scale experimental study on the structural performance of load-bearing wall panels made of cold-formed steel frames and boards is presented. Six different types of C-channel stud, a total of 20 panels with one middle stud and 10 panels with two middle studs were tested under vertical compression until failure. For panels, the main variables considered are screw spacing (300 mm, 400 mm, or 600 mm) in the middle stud, board type (oriented strand board - OSB, cement particle board - CPB, or calcium silicate board - CSB), board number (no sheathing, one-side sheathing, or two-side sheathing), and loading type (1, 3, or 4-point loading). The measured load capacity of studs and panels agrees well with analytical prediction. Due to the restraint by rivet connections between stud and track, the effective length factor for the middle stud and the side stud in a frame (unsheathed panel) is reduced to 0.90 and 0.84, respectively. The load carrying capacity of a stud increases significantly whenever one- or two-side sheathing is used, although the latter is significantly more effective. It is also dependent upon the type of board used. Whereas panels with either OSB or CPB boards have nearly identical load carrying capacity, panels with CSB boards are considerably weaker. Screw spacing affects the load carrying capacity of a stud. When the screw spacing on the middle stud in panels with one-side sheathing is reduced from 600 mm to 300 mm, its load carrying capacity increases by 14.5 %, 20.6% and 94.2% for OSB, CPB and CSB, respectively.

Design, construction and evaluation of systems to predict risk in obstetrics.

We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.

Transient growth and triggering in the horizontal Rijke tube Matthew

This theoretical paper examines a non-normal and non-linear model of a horizontal Rijke tube. Linear and non-linear optimal initial states, which maximize acoustic energy growth over a given time from a given energy, are calculated. It is found that non-linearity and non-normality both contribute to transient growth and that, for this model, linear optimal states are only a good predictor of non-linear optimal states for low initial energies. Two types of non-linear optimal initial state are found. The first has strong energy growth during the first period of the fundamental mode but loses energy thereafter. The second has weaker energy growth during the first period but retains high energy for longer. The second type causes triggering to self-sustained oscillations from lower energy than the first and has higher energy in the fundamental mode. This suggests, for instance, that low frequency noise will be more effective at causing triggering than high frequency noise.

A simple prediction model for asphalt surface texture incorporating mix gradation and air voids

This paper presents the results of a preliminary study that seeks to show how asphalt grading and air voids are related to the texture depth of asphalt. The fiftieth percentile particle size (D50) is shown to be a good predictor of texture depth measurements from a collected database of field and laboratory studies. The D50 is used to normalise collected texture data and this 'relative texture' is shown to correlate with air voids. Regression analyses confirm that air voids should be included along with a measure of gradation in the interpretation of asphalt surface texture.The derived formulae are used to develop correlation charts.

Phase synchronization between stratospheric and tropospheric quasi-biennial and semi-annual oscillations

A combination of singular systems analysis and analytic phase techniques are used to investigate the possible occurrence in observations of coherent synchronization between quasi-biennial and semi-annual oscillations (QBOs; SAOs) in the stratosphere and troposphere. Time series of zonal mean zonal winds near the Equator are analysed from the ERA-40 and ERA-interim reanalysis datasets over a ∼ 50-year period. In the stratosphere, the QBO is found to synchronize with the SAO almost all the time, but with a frequency ratio that changes erratically between 4:1, 5:1 and 6:1. A similar variable synchronization is also evident in the tropical troposphere between semi-annual and quasi-biennial cycles (known as TBOs). Mean zonal winds from ERA-40 and ERA-interim, and also time series of indices for the Indian and West Pacific monsoons, are commonly found to exhibit synchronization, with SAO/TBO ratios that vary between 4:1 and 7:1. Coherent synchronization between the QBO and tropical TBO does not appear to persist for long intervals, however. This suggests that both the QBO and tropical TBOs may be separately synchronized to SAOs that are themselves enslaved to the seasonal cycle, or to the annual cycle itself. However, the QBO and TBOs are evidently only weakly coupled between themselves and are frequently found to lose mutual coherence when each changes its frequency ratio to its respective SAO. This suggests a need to revise a commonly cited paradigm that advocates the use of stratospheric QBO indices as a predictor for tropospheric phenomena such as monsoons and hurricanes. © 2012 Royal Meteorological Society.

On the use of predictor-corrector method for coupled Monte Carlo burnup codes

This paper investigates the effect of the burnup coupling scheme on the numerical stability and accuracy of coupled Monte-Carlo depletion calculations. We show that in some cases, even the Predictor Corrector method with relatively short time steps can be numerically unstable. In addition, we present two possible extensions to the Euler predictor-corrector (PC) method, which is typically used in coupled burnup calculations. These modifications allow using longer time steps, while maintaining numerical stability and accuracy. © 2013 Elsevier Ltd. All rights reserved.

Numerical stability of the predictor-corrector method in Monte Carlo burnup calculations of critical reactors

Monte Carlo burnup codes use various schemes to solve the coupled criticality and burnup equations. Previous studies have shown that the simplest methods, such as the beginning-of-step and middle-of-step constant flux approximations, are numerically unstable in fuel cycle calculations of critical reactors. Here we show that even the predictor-corrector methods that are implemented in established Monte Carlo burnup codes can be numerically unstable in cycle calculations of large systems. © 2013 Elsevier Ltd. All rights reserved.

Statistics anxiety, trait anxiety, learning behavior, and academic performance

The present study investigated the relationship between statistics anxiety, individual characteristics (e.g., trait anxiety and learning strategies), and academic performance. Students enrolled in a statistics course in psychology (N=147) filled in a questionnaire on statistics anxiety, trait anxiety, interest in statistics, mathematical selfconcept, learning strategies, and procrastination. Additionally, their performance in the examination was recorded. The structural equation model showed that statistics anxiety held a crucial role as the strongest direct predictor of performance. Students with higher statistics anxiety achieved less in the examination and showed higher procrastination scores. Statistics anxiety was related indirectly to spending less effort and time on learning. Trait anxiety was related positively to statistics anxiety and, counterintuitively, to academic performance. This result can be explained by the heterogeneity of the measure of trait anxiety. The part of trait anxiety that is unrelated to the specific part of statistics anxiety correlated positively with performance.