Techniques for suppressing anomalous response to vacuum ultraviolet radiation in the charged- particle lunar environment experiment.
Procedures to suppress anomalous response to vacuum UV radiation in lunar environment experiment
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Procedures to suppress anomalous response to vacuum UV radiation in lunar environment experiment
The growth of wheat (triticum aestivum) was studied in an enclosed controlled environment for a period of 70 days. The exchange of gases (photosynthesis, respiration), water (transpiration) and the consumption of mineral elements (nitrogen, phosphorus, potassium) were continuously measured. The dynamical relations observed in the different physiological functions, under the influence of growth and in response to environment modifications are presented. The influence of carbon dioxide content during growth (normal or double percentage) was made clear.
All earth-orbiting spacecraft are susceptible to high-speed impacts by pieces of orbital debris. To prevent mission failure and possibly loss of life, protection against perforation by high-speed orbital debris particles must be included in the spacecraft design. Although any number of materials can be used to manufacture perforation-resistant structures, aluminum is often used in such systems because of its relatively high strength-to-weight ratio. This paper presents the results of a study in which the high speed impact response characteristics of dual-wall structures made from two different aluminum alloys were analyzed to determine which alloy would be more suitable for use in a perforation-resistant dual-wall structural system that is to be exposed to the orbital debris environment. Impact response characteristics were obtained numerically and experimentally. At impact speeds below 7 km/s, it was found that the two aluminum alloys considered contributed similar levels of perforation resistance; at speeds in excess of 7 km/s, aluminum 2219-T87 was superior to aluminum 5546-H116 in preventing perforation of dual-wall structural systems.
Future long-duration missions to the International Space Station (ISS) and beyond will require a sustainable supply of food to support human crews. The spaceflight cabin environment often contains very high concentrations of CO2, and it is therefore crucial to understand plant responses to elevated CO2 (eCO2) environments. Much focus has been given to plant photosynthetic and performance parameters in response to eCO2, but studies on the effects of eCO2 on nitrogen uptake are poorly understood. Our previous work at The University of Sheffield, UK using novel stable isotope approaches has shown enhanced ammonium uptake and preference compared to nitrate at eCO2 in varieties of spring barley, hypothesized to be an indirect consequence of changes in photosynthesis and photorespiration. However, several varieties did not display altered preference under eCO2 and the universality of this response remains to be understood. In this NASA NPP project, several candidate crop species such as lettuce, radish and tomato will be screened using stable isotopes to assess whether N preference changes in favor of ammonium in response to eCO2 and whether this remains true at super-elevated CO2 (seCO2), which is often experienced on the ISS. Photosynthetic and related measurements will help to disentangle the relationship between these responses and photosynthesis. This work will enable the development of optimized nutrient regimes for candidate crops in space and in future Lunar and Martian habitats and will pave the way for selection of crop varieties adapted to an eCO2 and/or seCO2 environment. Moreover, this research will further our understanding of plant responses to the eCO2 environment brought about by climate change, allowing the development of future-proof crops that will help to maintain food security. This NPP Fellowship is funded by NASA Space Biology.
Many terrestrial biosphere models depend on an understanding of the relationship between stomatal conductance and photosynthesis. However, unlike the measurement of photosynthetic parameters, such as the maximum carboxylation capacity, where standard methods (e.g., CO 2 response or ACi curves) are widely accepted, a consensus method for empirically measuring parameters representing stomatal response has not yet emerged. Most models of stomatal response to environment represent stomatal conductance as being bounded by a lower intercept parameter (g 0 ), and linearly scaled based on a multivariate term described by the stomatal slope parameter (g 1 ). Here we employ the widely used Unified Stomatal Optimization model, to test whether g 1 and g 0 parameters are impacted by the choice of measurement method, either on an intact branch, or a cut branch segment stored in water. We measured paired stomatal response curves on intact and excised branches of a hybrid poplar clone (Populus deltoides Bartr. x Populus nigra L. OP367), measured twice over a diurnal period. We found that predawn branch excision did not significantly affect measured g 0 and g 1 when measured within 4 h of excision. Measurement in the afternoon resulted in significantly higher values of g 1 and lower values of g0, with values changing by 55% and 56% respectively. Excision combined with afternoon measurement resulted in a marked effect on parameter estimates, with g1 increasing 89% from morning to afternoon and a 25% lower g 1 for cut branches than those measured in situ. We also show that in hybrid poplar the differences in parameter estimates obtained from plants measured under different conditions can directly impact models of canopy function, reducing modeled transpiration by 18% over a simulated 12.5-hour period. While these findings are only for a single isohydric woody species, our findings suggest that stomatal optimality parameters may not remain constant throughout the day.
A study involving the Controlled Impact Demonstration (CID) of a transport category aircraft was conducted with the objective to improve occupant safety during survivable crash scenarios. in connection with this study, the first remotely-piloted Full-Scale Transport aircraft was purposely crashed into the California desert. The program was initated to demonstrate the effectiveness of an imisting kerosene (AMK), a fuel additive emplyed to reduce postcrash fires. The unmanned CID flight carried 73 life-like flight research dummies, multiple experiments, high-speed interior cabin cameras, and the high-environment Crash Response Data System. Attention is given to the design approach, a block diagram of the Crash Response Data System, measurements, the digital data subsystem, signal conditioning, telemetry, on-board recording, the power subsystem, preflight checkout and calibration, and aspects of system qualification.
The Hughes SCREENS (Space Craft Response to Environments of Space) technique was applied to generic spin and 3-axis stabilized spacecraft models. It involved the NASCAP modeling for surface charging and lumped element modeling for transients coupling into a spacecraft. A differential voltage between antenna and spun shelf of approx. 400 V and current of 12 A resulted from discharge at antenna for the spinner and approx. 3 kv and 0.3 A from a discharge at solar panels for the 3-axis stabilized Spacecraft. A typical interface circuit response was analyzed to show that the transients would couple into the Spacecraft System through ground points, which are most vulnerable. A compilation and review was performed on 15 years of available data from electron and ion current collection phenomena. Empirical models were developed to match data and compared with flight data of Pix-1 and Pix-2 mission. It was found that large space power systems would float negative and discharge if operated at or above 300 V. Several recommendations are given to improve the models and to apply them to large space systems.
The simulated response is described of a STOL aircraft to Microwave Landing System (MLS) multipath errors during final approach and touchdown. The MLS azimuth, elevation, and DME multipath errors were computed for a relatively severe multipath environment at Crissy Field California, utilizing an MLS multipath simulation at MIT Lincoln Laboratory. A NASA/Ames six-degree-of-freedom simulation of an automatically-controlled deHavilland C-8A STOL aircraft was used to determine the response to these errors. The results show that the aircraft response to all of the Crissy Field MLS multipath errors was small. The small MLS azimuth and elevation multipath errors did not result in any discernible aircraft motion, and the aircraft response to the relatively large (200-ft (61-m) peak) DME multipath was noticeable but small.
The Natural Environment Branch at NASA's Marshall Space Flight Center (MSFC) has the responsibility to provide natural environments engineering support to programs and projects. The Natural Environments Branch is responsible for natural environments definitions, modeling, database development, and analytical assessments of effects. Natural Environments Branch personnel develop requirements for flight projects and provide operational support for space and launch vehicle systems. To accomplish these responsibilities, models and analytical tools have been developed in the areas of planetary atmospheres, meteoroids, ionizing radiation, plasmas and ionospheres, magnetic and gravitational fields, spacecraft charging modeling, and radiation effects on electronic parts. This paper will build on a previous paper published in 2006 and provide updated descriptions of the capabilities within the Natural Environments Branch1. Updates describing improvements and new releases of several analytical tools and models will be presented. Separate sections will specifically describe modifications in the Meteoroid Engineering Model (MEM), and the Marshall Solar Activity Future Estimation (MSAFE) capabilities.
The aerospace industry uses vibration shaker tables to perform component durability testing. These dynamic environments tests often have a hard time replicating the service environment of a component due to a mismatch in the applied force or the boundary condition. Figure 1 shows the desired outcome of a dynamic environments test. The measured responses in a lab test, ideally, should match the measured response of the service environment field test. One way to address the mismatch between field environment and lab environment is with test fixture design. The test fixture attaches the component under test to the shaker table. Single-axis shakers are the industry standard type of shaker table, and, therefore, test fixtures are often rigid in order to minimize cross-axis responses.
Researchers at the NASA Glenn Research Center have developed a research-level code for forced response analysis for turbomachinery that provides a streamlined framework for aeromechanics analysis, as well as for generating Goodman diagrams. The Forced Response Aeromechanics Analysis in a MATLAB-Based Environment (FRAAME, Version 1) code is designed to accept blade surface unsteady pressure time histories generated by three-dimensional (3D) Unsteady Reynolds-Averaged Navier-Stokes (URANS) code TURBO and modal displacements, modal stresses, and static stresses generated via expanded ANSYS® (Ansys, Inc.) cyclic symmetry analysis. The code’s looping structure allows for largescale analyses, including many blade surface pressure files, modal displacements, and modal stress files for full annulus forced response analysis, including a modal summation method for multiple engine orders and modes. This code is applied to the R24 fan geometry for the Boundary Layer Ingesting Inlet/Distortion-Tolerant Fan (BLI2DTF) project, a propulsion system being developed to increase the fuel efficiency of future aircraft, to serve as validation of experimental data as well as external simulation results. This tool’s functional, modular form is intended to allow users to make modifications easily. Those modifications can include requests for information for any step in the analysis process, as well as adding various functions to compute additional information of interest. It is also written, given sufficient input information, as a general blade geometry forced response solver that is not necessarily specific to the R24 geometry but is used here for verification of code functionality and accuracy. Although forced response analysis tools are also available in commercially available code packages, the post-processing FRAAME code offers reliable, fast, and scalable forced response analysis and Goodman diagram generation for large cases utilizing, specifically, TURBO and ANSYS® results information in an effort to streamline forced response and high cycle fatigue analyses.
Plutonium (Pu) has, in theory, well defined crystal structures: its atoms are arranged in regular spatial patterns. But Pu is radioactive, and as its nuclei decay those regular spatial patterns are interrupted. The interruptions are lattice imperfections, which are known to affect how materials respond to their environment. To adequately model Pu, we need to know which lattice imperfections are present, how they interact with each other, and how they affect the material’s response to its environment. The work presented here aims to use density functional theory (DFT) calculations to begin to answer the latter, in particular, how individual lattice imperfections affect measurable effects including thermal expansion (the change in volume in response to a change in temperature), heat capacity (the amount of thermal energy needed to change a material’s temperature), and elastic moduli (a material’s resistance to applied stresses). Pu poses many computational challenges. The $\textit{f}$ electrons require special attention. Of all the elements, Pu has the largest number of electrons that must be included in the calculations. Thermal effects require calculating the phonons (the lattice vibrations), which for systems containing lattice imperfections demand large, complex computational cells - but computational resources limit the size and complexity. With careful restructuring of how the calculations are performed, all these challenges have been met to enable calculations that provide insight into how lattice imperfections affect Pu’s response to its environment. Reported here are the computational challenges and the advances developed to meet them, along with the first results showing the strong effect that one prototype lattice imperfection (an interstitial Pu atom in a delta-phase Pu lattice) has on Pu’s response to its environment.
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A detector-specific deep learning (DL) approach is presented for spectra-to-exposure conversion using large-format sodium iodide (NaI(Tl)) detectors deployed for in situ environmental radiation measurements in emergency response scenarios. Accurate determination of exposure from NaI spectra is challenging due to poor energy resolution, partial energy absorption, and the strong sensitivity of traditionally deployed analytical conversion methods to calibrated source geometry and pre-deployment assumptions. Here, to address these limitations, a multi-layer perceptron model was trained on a hybrid in situ /Monte Carlo dataset constructed to span a broad range of photon energies, spatial extents, and realistic deployment variability, representative of general in situ emergency response conditions. The DL model was evaluated against commonly fielded analytical approaches under matched simulation conditions, including a single-factor method, a G-function method, and a modeled pressurized ion chamber (PIC) baseline. This study was intentionally computational in scope to enable controlled, like-for-like comparisons between conversion techniques while minimizing confounding real-world variability. Comparison to the modeled PIC provides contextual benchmarking and is not intended as a field inter-comparison with deployed instruments. Across the evaluated 20 keV to 3 MeV energy range, the DL approach consistently exhibited higher accuracy and reduced variance relative to the analytical methods against a deterministically calculated exposure. This may indicate improved robustness to spectral complexity without reliance on source-, geometric-, or spectral region-specific optimization. While results do not represent real-world validation, the presented work demonstrates that deep learning may effectively learn the nonlinear detector response-to-exposure relationship for asymmetric NaI(Tl) detectors and offers a promising pathway for improving in situ exposure estimation using spectroscopic systems already integrated into initial real-time emergency response operations.
The recent development of non-fullerene acceptors (NFA) has led to an abrupt increase in the organic photovoltaic (OPV) efficiency from ~12% to ~20%. NFA OPVs can generate photocurrent efficiently without much energy loss, which contrasts with the large energy loss often needed for generating free charges from excitons in fullerene OPVs. Here, we argue that entropy-driven charge separation, which allows excitons to spontaneously gain heat from the environment, is responsible for the exceptionally low energy loss found in NFA OPVs. The entropic driving force is maximized when the delocalized electron and hole wave functions in the CT exciton intersect each other via pointlike junctions. Furthermore, these pointlike junctions are abundant in the polymer/NFA bulk heterojunction which consists of intertwined, stringlike donor and acceptor domains in which electron delocalizes anisotropically. Such microstructure favors entropy-driven charge separation, which can enable charge separation with a minimal energy loss.
Molybdenum (Mo) imposes strict loading limits in conventional borosilicate nuclear waste glasses due to the tendency of tetrahedral molybdate [MoO 4 ] 2− species to phase-separate and crystallize as alkali molybdates. Here, we demonstrate an unprecedented 13.96 wt % (7.51 mol %) MoO 3 solubility in peraluminous sodium aluminoborosilicate glasses a ∼15× increase over their peralkaline counterparts. Using Raman spectroscopy, multinuclear and dipolarcorrelation magic angle spinning nuclear magnetic resonance (MAS NMR), electron paramagnetic resonance (EPR), and scanning transmission electron microscopy (STEM)-energy dispersive spectroscopy (EDS), we reveal that Nadeficient, low optical basicity conditions stabilize octahedral MoO 6 units, which polymerize into molybdite-like Mo−O clusters dispersed within the glass matrix. These Mo-rich clusters suppress the formation of depolymerized [MoO 4 ] 2− environments typically responsible for Na 2 MoO 4 precipitation and instead promote the formation of Na 2 Mo 2 O 7 as the saturation phase. Concurrently, Mo solubility drives the conversion of AlO 4 − to higher-coordination AlO 5 species, liberating Na + that is subsequently sequestered in molybdate-rich domains. The combined evolution of Mo coordination, modifier redistribution, and network depolymerization provides a mechanistic basis for the markedly enhanced Mo solubility in peraluminous compositions. These findings establish new structural guidelines for designing aluminoborosilicate waste forms with substantially greater capacity to incorporate Mo-rich nuclear waste streams.