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Far-Infrared Properties of Cyclic Olefin Copolymer
Cyclic olefin copolymer (COC) is an amorphous thermoplastic with desirable dielectric and mechanical characteristics for optical applications. In particular, its low refractive index, overall mechanical strength, and absence of strong absorption features make it a promising substrate material for far-infrared applications, which include frequency-selective surfaces, scattering filters, and windows. The dielectric properties of selected COC formulations are surveyed from 10700 per.cm (100014m), and representative usage as a thin film membrane structure in optical filters is presented
The Aerosol, Clouds, Convection, and Precipitation Mission Study: Observing System Simulation Experiments for Multi-angle Polarimeters
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Sensorimotor Predictors of Post-Landing Functional Task Performance
Spaceflight drives adaptive changes in healthy individuals appropriate for sensorimotor function in a microgravity environment. These changes are maladaptive for return to earth's gravity. The inter-individual variability of sensorimotor decrements is striking, although poorly understood. The goal of this study is to identify a set of behavioral, neuroimaging and genetic measures that can potentially be used to predict early performance following G-transitions such as return to Earth on a set of sensorimotor tasks. Astronauts are being recruited who previously participated in sensorimotor field tests and/or dynamic posturography (MedB) within R+1 days following long-duration spaceflight
Mode-Based Sensing and Actuation Techniques for Multi-Objective Flexible Aircraft Control
Intelligent sensing and actuation designs are explored as a means to improve performance of a gust load alleviation control design for a flexible wing aircraft equipped with wing-shaping control surfaces. The proposed techniques rely on identification of the dominant structural modes during specified flight conditions and uses them as a basis for sensor placement and actuator utilization. Specifically, a strategy for sensor placement is discussed that uses target mode shape capture as a mean to improve state estimation quality. A second strategy that reduces the number of wing-shaping control inputs using mode and objective-based shape functions as virtual input channels is also presented. Both techniques are demonstrated in simulation of a flexible wing transport aircraft utilizing a multi-objective control system designed to suppress flexible motion, minimize gust and maneuver load, and reduce drag
Quantification of Ophthalmic Changes After Long-Duration Spaceflight, and Subsequent Recovery
A subset of crewmembers are subjected to ophthalmic structure changes due to long-duration spaceflight (>6 months). Crewmembers who experience these changes are described as having Spaceflight Associated Neuro-Ocular Syndrome (SANS). Characteristics of SANS include optic disk edema, cotton wool spots, choroidal folds, refractive error, and posterior globe flattening. SANS remains a major obstacle to deep-space and planetary missions, requiring a better understanding of its etiology. Quantification of ocular, structural changes will improve our understanding of SANS pathophysiology. Methods were developed to quantify 3D optic nerve (ON) and ON sheath (ONS) geometries, ON tortuosity, and posterior globe deformation using MR imaging
Using Bayesian Estimation to Quantify the Risks of Spaceflight
Complex PRA is the best method and current gold standard, as it allows us to reflect changes (improvements) in individual spacecraft system risks over time. Yet, Bayesian methods using simple inputs allowed us to get estimates that are in line with high-complexity PRA. Here Bayesian estimation acts as a gut check on PRA (supposing a reasonable prior is used). Frequentist calculations can overestimate P(failure), especially when total number of trials are few (e.g., after Challenger). In general, Bayesian probability estimation can be used in any risk assessment situation to integrate what we think we know ahead of time with what we observe over time