Transonic Aeroelastic Stability Predictions Under the Influence of Structural Variability

Flutter prediction as currently practiced is almost always deterministic in nature, based on a single structural model that is assumed to represent a fleet of aircraft. However, it is also recognized that there can be significant structural variability, even for different flights of the same aircraft. The safety factor used for flutter clearance is in part meant to account for this variability. Simulation tools can, however, represent the consequences of structural variability in the flutter predictions, providing extra information that could be useful in planning physical tests and assessing risk. The main problem arising for this type of calculation when using high-fidelity tools based on computational fluid dynamics is the computational cost. The current paper uses an eigenvalue-based stability method together with Euler-level aerodynamics and different methods for propagating structural variability to stability predictions. The propagation methods are Monte Carlo, perturbation, and interval analysis. The feasibility of this type of analysis is demonstrated. Results are presented for the Goland wing and a generic fighter configuration.

Predictions of large events on a spring-block model

We study the predictability of a theoretical model for earthquakes, using a pattern recognition algorithm similar to the CN and M8 algorithms known in seismology. The model, which is a stochastic spring-block model with both global correlation and local interaction, becomes more predictable as the strength of the global correlation or the local interaction is increased.

The Influence of Friction Stir Welding Process Idealization on Residual Stress and Distortion Predictions for Future Airframe Assembly Simulations

The ability to accurately predict residual stresses and resultant distortions is a key product from process assembly simulations. Assembly processes necessarily consider large structural components potentially making simulations computationally expensive. The objective herein is to develop greater understanding of the influence of friction stir welding process idealization on the prediction of residual stress and distortion and thus determine the minimum required modeling fidelity for future airframe assembly simulations. The combined computational and experimental results highlight the importance of accurately representing the welding forging force and process speed. In addition, the results emphasize that increased CPU simulation times are associated with representing the tool torque, while there is potentially only local increase in prediction fidelity.

An effective method for comparing the turbulence intensity from LDA measurements and CFD predictions within a ship propeller jet

The mean velocity and turbulence intensity are the two main inputs to investigate the ship propeller induced seabed scouring resulting from a vessel is manoeuvring within a port where the underkeel clearances are low. More accurate data including the turbulence intensity is now available by using the laser doppler anemometry (LDA) measurement system and computational fluid dynamics (CFD) approach. Turbulence intensity has a loose definition, which is the velocity fluctuation as the root mean square (RMS) referenced to a mean flow velocity. However, the velocity fluctuation and mean velocity can be the overall value includingx, y and z directions or the value of a single component. LDA and CFD results were obtained from two different acquisition systems (Dantec LDA system and Fluent CFD package) and therefore the outputs cannot be compared directly. An effective method is proposed for comparing the turbulence intensity between the experimental measurements and the computational predictions within a ship propeller jet. The flow patterns of turbulence intensity within a ship propeller jet are presented by using the LDA measurements and CFD results from turbulence models of standard k-e, RNG k-e, realizable k–e, standard k–?, SST k–?and Reynolds stresses.

Predictions of survival up to 10 years after diagnosis for European women with breast cancer in 2000-2002

Few studies have addressed longer-term survival for breast cancer in European women. We have made predictions of 10-year survival for European women diagnosed with breast cancer in 2000-2002. Data for 114,312 adult women (15-99 years) diagnosed with a first primary malignant cancer of the breast during 2000-2002 were collected in the EUROCARE-4 study from 24 population-based cancer registries in 14 European countries. We estimated relative survival at 1, 5, and 10 years after diagnosis for women who were alive at some point during 2000-2002, using the period approach. We also estimated 10-year survival conditional on survival to 1 and 5 years after diagnosis. Ten-year survival exceeded 70% in most regions, but was only 54% in Eastern Europe, with the highest value in Northern Europe (about 75%). Ten-year survival conditional on survival for 1 year was 2-6% higher than 10-year survival in all European regions, and geographic differences were smaller. Ten-year survival for women who survived at least 5 years was 88% overall, with the lowest figure in Eastern Europe (79%) and the highest in the UK (91%). Women aged 50-69 years had higher overall survival than older and younger women (79%). Six cancer registries had adequate information on stage at diagnosis; in these jurisdictions, 10-year survival was 89% for local, 62% for regional and 10% for metastatic disease. Data on stage are not collected routinely or consistently, yet these data are essential for meaningful comparison of population-based survival, which provides vital information for improving breast cancer control. What's new? Policy-makers and health-care planners need accurate data on long-term survival to improve cancer control. This Europe-wide study of 10-year survival identified low survival in Eastern Europe for women with breast cancer in 2000-2002, and wide variation by age at diagnosis. Data on stage at diagnosis are crucial for meaningful comparison of population-based survival, and fundamental for improving breast cancer control, but our analyses confirmed that stage data are not collected routinely or consistently Copyright © 2012 UICC.