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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The adaptive changes of the neurovestibular system to microgravity, which result in space motion sickness (SMS), are studied. A list of symptoms, which range from vomiting to drowsiness, is provided. The two patterns of symptom development, rapid and gradual, and the duration of the symptoms are described. The concept of sensory conflict and rearrangements to explain SMS is being investigated.
This study is part of an ongoing program of research examining the psychological effects of isolation and confinement on individual adaptation, productivity and group relations in Antarctic winter personnel. This environment is used as an analogue for long-duration space mission scenarios, such as a space station sojourn, or a mission to Mars. Earlier results from this and other environments have demonstrated that: (1) most changes in psychological well-being are event-related and of relatively short duration; and (2) the greatest problem facing most individuals is interpersonal conflict. Content analysis of responses to open-ended questions has identified the numerous enjoyable aspects of Antarctic living, and confirmed that many of the problems reported were interpersonal in nature, and that problems varied significantly by station. Current work is exploring the effects of team assignment on the self-reported psychological changes and self-evaluations of members of isolated teams. This work includes identifying the dimensions by which subjects determine how well they are functioning. These dimensions (e.g., work, social life, internal emotional state) appear to play an important role in how subjects evaluate many aspects of life in isolation.
This paper contains a simulation study of a real-time adaptive least-squares drag minimization algorithm for an aeroelastic model of a flexible wing aircraft. The aircraft model is based on the NASA Generic Transport Model (GTM). The wing structures incorporate a novel aerodynamic control surface known as the Variable Camber Continuous Trailing Edge Flap (VCCTEF). The drag minimization algorithm uses the Newton-Raphson method to find the optimal VCCTEF deflections for minimum drag in the context of an altitude-hold flight control mode at cruise conditions. The aerodynamic coefficient parameters used in this optimization method are identified in real-time using Recursive Least Squares (RLS). The results demonstrate the potential of the VCCTEF to improve aerodynamic efficiency for drag minimization for transport aircraft.
The application of deep machine learning methods in astronomy has exploded in the last decade, with new models showing remarkably improved performance on benchmark tasks. Not nearly enough attention is given to understanding the models' robustness, especially when the test data are systematically different from the training data, or "out of domain." Domain shift poses a significant challenge for simulation-based inference, where models are trained on simulated data but applied to real observational data. In this paper, we explore domain shift and test domain adaptation methods for a specific scientific case: simulation-based inference for estimating galaxy cluster masses from X-ray profiles. We build datasets to mimic simulation-based inference: a training set from the Magneticum simulation, a scatter-augmented training set to capture uncertainties in scaling relations, and a test set derived from the IllustrisTNG simulation. We demonstrate that the Test Set is out of domain in subtle ways that would be difficult to detect without careful analysis. We apply three deep learning methods: a standard neural network (NN), a neural network trained on the scatter-augmented input catalogs, and a Deep Reconstruction-Regression Network (DRRN), a semi-supervised deep model engineered to address domain shift. Although the NN improves results by 17% in the Training Data, it performs 40% worse on the out-of-domain Test Set. Surprisingly, the Scatter-Augmented Neural Network (SANN) performs similarly. While the DRRN is successful in mapping the training and Test Data onto the same latent space, it consistently underperforms compared to a straightforward Yx scaling relation. These results serve as a warning that simulation-based inference must be handled with extreme care, as subtle differences between training simulations and observational data can lead to unforeseen biases creeping into the results.
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Crystal truncation rod (CTR) X-ray diffraction is an invaluable tool for measuring mineral surface and adsorbate structures, and has been applied to several environmentally and geochemically important systems. Traditionally, the method has been restricted to single crystals with lateral dimensions >3 mm. Minerals that meet this size criterion represent a minute fraction of those that are relevant to interfacial geochemistry questions, however. Crystal screening, data collection, and CTR measurement methods have been developed for crystals of <0.3 mm in lateral size using the manganese oxide mineral chalcophanite (ZnMn 3 O 7 •3H 2 O) as a case study. Furthermore, this work demonstrates the feasibility of applying the CTR technique to previously inaccessible surfaces, opening up a large suite of candidate substrates for future study.
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