The effect of generalized force correlations on the response statistics of a harmonically driven random system

If the physical properties of a structural component are sufficiently random then the statistical distribution of the natural frequencies and mode shapes tends to a universal distribution associated with the Gaussian Orthogonal Ensemble (GOE) of random matrices. Previous work has exploited this result to yield expressions for the relative variance of the energy of the response of a random system to harmonic excitation. The derivation of these expressions employed random point process theory, and in the theoretical development it was assumed that the modal generalised forces were uncorrelated. Although this assumption is often valid, there are cases in which correlations between the generalised forces can significantly affect the response variance, and in the present work the existing theory is extended to include correlations of this type. The extended theory is applicable to both single frequency responses and to band average responses, and the developed closed form expressions are validated by comparison with direct simulations for a random plate structure.Elke Deckers contribution was funded through The Research Fund KU Leuve

Curved track sprint characteristics in elementary school children

The management strategies of patients who underwent Mustard repair for transposition (of the great arteries were changed in the 1970s: infants became eligible for direct surgical repair, so Blalock-Hanlon atrioseptostomy could be avoided, and cold cardioplegia was introduced for myocardial preservation. Data are lacking, however, regarding whether these changes have had positive effects on the long-term outcome. We therefore conducted a follow-up study on all 91 patients who underwent a Mustard repair for transposition of the great arteries in our institution between 1973 and 1980 to assess the incidence and clinical importance of sequelae as well as health-related quality of life for these patients. Patients who were alive and could be traced through local registrar's offices received an invitation to participate in the follow-up study, which consisted of an interview, physical examination, echocardiography, exercise testing, and standard 12-lead and 24-hour electrocardiography. Patients operated on in the first 4 years had a significantly higher mortality rate and higher incidence of sinus node dysfunction than did patients operated on in the subsequent 4 years (25% vs 2% and 41% vs 3%, respectively). In contrast, the incidence of baffle obstruction necessitating reoperation was significantly higher in the second group. There were no significant differences in echocardiographic findings and exercise capacity between patients operated on in the first 4 years and in the subsequent 4 years. None of the patients had right ventricular failure; a mild degree of baffle leakage or obstruction was seen in 22% of the patients, and the mean exercise capacity was decreased to 84% +/- 16% of normal. The changes introduced between 1973 and 1980 have resulted in a considerable reduction of mortality and incidence of sinus node dysfunction but have also resulted in a more frequent need for reoperatio

Automatic and Sampling-Free Parametric Model Order Reduction of Vibro-Acoustic Systems

Recently, a novel parametric model order reduction formulation has been derived for vibroacoustic systems that allows for the reduction of systems with low-rank parametric changes [1]. This scheme does not require sampling of the parameter space, in contrast to conventional parametric model reduction techniques. This means that a single reduction basis, obtained with conventional non-parametric model order reduction schemes, can be used for a wide range of parameter values. This is done by rewriting the system in a non-parametric form, in which the low-rank contributions act as inputs. A disadvantage of this scheme is that the size of the input matrix scales with the amount of chosen parameters, leading to a potentially large reduced basis when many parameters are considered. Therefore, in [2] an automatic Krylov reduction scheme has been proposed that utilizes the similarity in the reduced bases for inputs which are spaced closely together to still get a small reduced basis with a large number of inputs. This is done by using a combination of block second order Arnoldi with a singular value decomposition acting on the resulting basis. The algorithm includes an error estimator that uses a complementary approximation to calculate the error. The main advantages of this algorithm as compared to the commonly used iterative rational Krylov approach [3] are that only a small amount of system inversions are required and that the final reduced order model has the desired predefined relative error in the specified frequency band. In this paper the automatic Krylov reduction scheme and low-rank parametric model order reduction approach are combined and a suitable error estimator is derived, to arrive at compact but accurate parametric reduced order models. The effectiveness is shown with several examples