A Method for the Combination of Stochastic Time Varying Load Effects

The problem of evaluating the probability that a structure becomes unsafe under a combination of loads, over a given time period, is addressed. The loads and load effects are modeled as either pulse (static problem) processes with random occurrence time, intensity and a specified shape or intermittent continuous (dynamic problem) processes which are zero mean Gaussian processes superimposed 'on a pulse process. The load coincidence method is extended to problems with both nonlinear limit states and dynamic responses, including the case of correlated dynamic responses. The technique of linearization of a nonlinear limit state commonly used in a time-invariant problem is investigated for timevarying combination problems, with emphasis on selecting the linearization point. Results are compared with other methods, namely the method based on upcrossing rate, simpler combination rules such as Square Root of Sum of Squares and Turkstra's rule. Correlated effects among dynamic loads are examined to see how results differ from correlated static loads and to demonstrate which types of load dependencies are most important, i.e., affect' the exceedance probabilities the most. Application of the load coincidence method to code development is briefly discussed.National Science Foundation Grants CME 79-18053 and CEE 82-0759

Aeronautical Engineering: A special bibliography, supplement 60

This bibliography lists 284 reports, articles, and other documents introduced into the NASA scientific and technical information system in July 1975

An adaptive sampling method for global sensitivity analysis based on least-squares support vector regression

In the field of engineering, surrogate models are commonly used for approximating the behavior of a physical phenomenon in order to reduce the computational costs. Generally, a surrogate model is created based on a set of training data, where a typical method for the statistical design is the Latin hypercube sampling (LHS). Even though a space filling distribution of the training data is reached, the sampling process takes no information on the underlying behavior of the physical phenomenon into account and new data cannot be sampled in the same distribution if the approximation quality is not sufficient. Therefore, in this study we present a novel adaptive sampling method based on a specific surrogate model, the least-squares support vector regresson. The adaptive sampling method generates training data based on the uncertainty in local prognosis capabilities of the surrogate model - areas of higher uncertainty require more sample data. The approach offers a cost efficient calculation due to the properties of the least-squares support vector regression. The opportunities of the adaptive sampling method are proven in comparison with the LHS on different analytical examples. Furthermore, the adaptive sampling method is applied to the calculation of global sensitivity values according to Sobol, where it shows faster convergence than the LHS method. With the applications in this paper it is shown that the presented adaptive sampling method improves the estimation of global sensitivity values, hence reducing the overall computational costs visibly

Increased burn healing time is associated with higher Vancouver Scar Scale score

Increased burn wound healing time has been shown to influence abnormal scarring. This study hypothesized that scar severity increases commensurate to the increase in time to healing (TTH) of the wound. Wound healing and scar data from burn patients treated by the Burn Service of Western Australia at Royal Perth Hospital were examined. The relationship between TTH and scar severity, as assessed by the modified Vancouver Scar Scale (mVSS), was modelled using regression analysis. Interaction terms evaluated the effect of surgery and total body surface area – burn (TBSA) on the main relationship. Maximum likelihood estimation was used to account for potential bias from missing independent variable data. The sample had a median age of 34 years, TTH of 24 days, TBSA of 3% and length of stay of five days, 70% were men and 71% had burn surgery. For each additional day of TTH, the mVSS score increased by 0.11 points (P ⩽ 0.001) per day in the first 21 days and 0.02 points per day thereafter (P = 0.004). The relationship remained stable in spite of TBSA or surgical intervention. Investigation of the effect of missing data revealed the primary model underestimated the strength of the association. An increase in TTH within 21 days of injury is associated with an increase in mVSS or reduced scar quality. The results confirm that efforts should be directed toward healing burn wounds as early as possible

Neural mechanisms of resistance to peer influence in early adolescence

During the shift from a parent-dependent child to a fully autonomous adult, peers take on a significant role in shaping the adolescent’s behaviour. Peer-derived influences are not always positive, however. Here we explore neural correlates of inter-individual differences in the probability of resisting peer influence in early adolescence. Using functional magnetic-resonance imaging (fMRI), we found striking differences between 10-year old children with high and low resistance to peer influence in their brain activity during observation of angry hand-movements and angry facial expressions: compared with subjects with low resistance to peer influence, individuals with high resistance showed a highly coordinated brain activity in neural systems underlying perception of action and decision making. These findings suggest that the probability of resisting peer influence depends on neural interactions during observation of emotion-laden actions