A Numerical Study of Vibration-Induced Instrument Reading Capability Degradation in Helicopter Pilots

Rotorcraft suffer from relatively high vibratory levels, due to exposure to significant vibratory load levels originating from rotors. As a result, pilots are typically exposed to vibrations, which have non-negligible consequences. Among those, one important issue is the degradation of instrument reading, which is a result of complex human-machine interaction. Both involuntary acceleration of the eyes as a result of biodynamics and vibration of the instrument panel contribute to a likely reduction in instrument reading capability, affecting flight safety. Therefore, being able to estimate the expected level of degradation in visual performance may give substantial benefits during vehicle design, allowing to make necessary adjustments while there is room for design changes or when retrofitting an existing aircraft to ensure the modifications do not adversely affect visual acuity and instrument reading ability. For this purpose, simulation is a very valuable tool as a proper model helps to understand the aircraft characteristics before conducting flight tests. This work presents the assessment of vibration-induced visual degradation of helicopter pilots under vibration exposure using a modular analysis environment. Core elements of the suggested analysis framework are an aeroelastic model of the helicopter, a model of the seat-cushion subsystem, a detailed multibody model of the human biodynamics, and a simplified model of ocular dynamics. These elements are combined into a comprehensive, fully coupled model. The contribution of each element to instrument reading degradation is examined, after defining an appropriate figure of merit that includes both eye and instrument panel vibration, in application to a numerical model representative of a medium-weight helicopter

A global search inversion for earthquake kinematic rupture history: Application to the 2000 western Tottori, Japan earthquake

We present a two-stage nonlinear technique to invert strong motions records and geodetic data to retrieve the rupture history of an earthquake on a finite fault. To account for the actual rupture complexity, the fault parameters are spatially variable peak slip velocity, slip direction, rupture time and risetime. The unknown parameters are given at the nodes of the subfaults, whereas the parameters within a subfault are allowed to vary through a bilinear interpolation of the nodal values. The forward modeling is performed with a discrete wave number technique, whose Green’s functions include the complete response of the vertically varying Earth structure. During the first stage, an algorithm based on the heat-bath simulated annealing generates an ensemble of models that efficiently sample the good data-fitting regions of parameter space. In the second stage (appraisal), the algorithm performs a statistical analysis of the model ensemble and computes a weighted mean model and its standard deviation. This technique, rather than simply looking at the best model, extracts the most stable features of the earthquake rupture that are consistent with the data and gives an estimate of the variability of each model parameter. We present some synthetic tests to show the effectiveness of the method and its robustness to uncertainty of the adopted crustal model. Finally, we apply this inverse technique to the well recorded 2000 western Tottori, Japan, earthquake (Mw 6.6); we confirm that the rupture process is characterized by large slip (3-4 m) at very shallow depths but, differently from previous studies, we imaged a new slip patch (2-2.5 m) located deeper, between 14 and 18 km depth

Boosting search by rare events

Randomized search algorithms for hard combinatorial problems exhibit a large variability of performances. We study the different types of rare events which occur in such out-of-equilibrium stochastic processes and we show how they cooperate in determining the final distribution of running times. As a byproduct of our analysis we show how search algorithms are optimized by random restarts.Comment: 4 pages, 3 eps figures. References update

Schrödinger’s worker: Are they positive or negative for SARS-CoV-2?

In these days of 2020, tests for the diagnosis of SARS-CoV-2, and their use in the context of health surveillance of workers, are becoming popular. Nevertheless, their sensitivity and specificity could vary on the basis of the type of test used and on the moment of infection of the subject tested. The aim of this viewpoint paper is to make employers, workers, occupational physicians, and public health specialists think about the limits of diagnostic tests currently available, and the possible implication related to the erroneous and incautious assignment of “immunity passports” or “risk-free certificates” to workers during screening campaigns in workplaces

Inferring DNA sequences from mechanical unzipping data: the large-bandwidth case

The complementary strands of DNA molecules can be separated when stretched apart by a force; the unzipping signal is correlated to the base content of the sequence but is affected by thermal and instrumental noise. We consider here the ideal case where opening events are known to a very good time resolution (very large bandwidth), and study how the sequence can be reconstructed from the unzipping data. Our approach relies on the use of statistical Bayesian inference and of Viterbi decoding algorithm. Performances are studied numerically on Monte Carlo generated data, and analytically. We show how multiple unzippings of the same molecule may be exploited to improve the quality of the prediction, and calculate analytically the number of required unzippings as a function of the bandwidth, the sequence content, the elasticity parameters of the unzipped strands

Biomimetic sulfide oxidation by the means of immobilized Fe(III)-5,10,15,20-tetrakis(pentafluorophenyl)porphin under mild experimental conditions

This paper describes the oxidation of inorganic sulfide to sulfate, minimizing the formation of elemental sulfur. The described catalytic reaction uses dilute hydrogen peroxide at nearly neutral pH values in the presence of a bioinspired, heterogenized, and commercial ferriporphin. A substantial increase of the percentage of sulfide converted to sulfate is obtained in comparison with the yields obtained when working with hydrogen peroxide alone. The biomimetic catalyst also proved to be a much more efficient catalyst than horseradish peroxidase. Accordingly, it could be suitable for large-scale applications. Further studies are in progress to drive sulfate yields up to nearly quantitative