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The Activity Profiles and Peak Flux of Radar Meteor Showers

Meteor showers are transient phenomena; a limited duration is what distinguishes a shower from a sporadic source. They do not, however, have clear start and end times; instead, shower activity gradually (or rapidly) increases over time, reaches a peak, and then decays. In this report, we examine the activity profiles of 38 meteor showers using 20 years of single-station shower fluxes from the Canadian Meteor Orbit Radar (CMOR). We find that a number of showers, such as the Southern delta Aquariids (SDAs), exhibit a broad maximum in activity rather than a sharp peak. We also find that approximately one-third of showers exhibit asymmetric activity profiles in which the rate in which activity rises prior to the peak differs from the rate at which it decays after the peak. We provide a functional form for meteor shower activity profiles that incorporates these features and use these profile fits to estimate each shower’s peak flux. This report also includes an uncertainty analysis for CMOR fluxes. This includes the first (to our knowledge) characterization of systematic uncertainty in radar meteor fluxes.

A V Moorhead↗

Advanced Power-Hardware-in-the-Loop Evaluation of Inverter-Based Resources (IBRs)

Power-hardware-in-the-loop evaluation of IBRs has become more and more important as it provides reliable testing results to investigate the real responses of inverters with interconnected systems. A successful laboratory PHIL testing gives confidence of the hardware system to be deployed and de-risk technology integration prior to field deployment. So far, there are two important applications for PHIL evaluation: (1) test stability and functionality of large utility inverters into the system when it interconnects to the distribution systems/microgrids; and (2) test the collective grid service that inverters can provide to the grid. For the first application, the PHIL evaluation has high requirements for the stability and accuracy of the PHIL interface as the close-loop in digital real time simulator (DRTS) should replicate the actual current and voltage dynamics in the inverter. This is challenging because of the delays, sensing errors, nonlinearities of inverters, and hardware bandwidth limitations of the elements in the HIL loop. For the second application, multiple inverters will be tested resulting in multiple PCCs, which naturally causes competing dynamics and oscillations among hardware inverters if traditional PHIL interface is used. Therefore, new PHIL interface should be developed to compromise between stability and accuracy and represent the dispatched grid services for the hardware inverters. In this presentation, we will share our latest work in developing PHIL interface in these two applications to address the two key challenges.

DERMS↗

Structural Propensities in Cs2MBiX6 (M=Na, Ag; X=Cl, Br) Bismuth Halide Double Perovskites

A previously unreported low-temperature phase transition in the bismuth halide double perovskite Cs2AgBiCl6 is reported, thereby establishing trends in the structural ground state across Cs2NaBiCl6, Cs2AgBiCl6, and Cs2AgBiBr6. Using the combined toolkit of variable-temperature synchrotron X-ray and neutron powder diffraction, Raman spectroscopy, and density-functional theory–based electronic structure modeling, we demonstrate a cubic Fm¯3m → tetragonal I4/m transition upon cooling with distinct onset temperatures. Neutron powder diffraction refinements permit the unambiguously assignment of the low-temperature phase of Cs2NaBiCl6 to I4/m, correcting prior reports of an I4/mmm ground state. Cs2AgBiCl6 is also found to transforms to a structure crystallizing in the I4/m space group at low temperatures. Temperaturedependent Raman data and density-functional theory-based modeling capture the softening and freezing of out-of-phase octahedral-tilt modes and quantify relative instabilities. Solid-state nuclear magnetic resonance spectroscopy at room temperature completes the characterization and helps underpin the subtle differences in covalency across the compounds. Trends in the phase transition temperature Ts and tilt magnitudes emerge from coupled effects of halide identity, M(I)–site bonding character, and a mismatch between interatomic distances. These results establish the structure– dynamics–bonding framework for tuning tilt-driven instabilities in halide double perovskites.

Tian, Haowen↗

Enhancements to the SSME transfer function modeling code

This report details the results of a one year effort by Ohio University to apply the transfer function modeling and analysis tools developed under NASA Grant NAG8-167 (Irwin, 1992), (Bartholomew, 1992) to attempt the generation of Space Shuttle Main Engine High Pressure Turbopump transfer functions from time domain data. In addition, new enhancements to the transfer function modeling codes which enhance the code functionality are presented, along with some ideas for improved modeling methods and future work. Section 2 contains a review of the analytical background used to generate transfer functions with the SSME transfer function modeling software. Section 2.1 presents the 'ratio method' developed for obtaining models of systems that are subject to single unmeasured excitation sources and have two or more measured output signals. Since most of the models developed during the investigation use the Eigensystem Realization Algorithm (ERA) for model generation, Section 2.2 presents an introduction of ERA, and Section 2.3 describes how it can be used to model spectral quantities. Section 2.4 details the Residue Identification Algorithm (RID) including the use of Constrained Least Squares (CLS) and Total Least Squares (TLS). Most of this information can be found in the report (and is repeated for convenience). Section 3 chronicles the effort of applying the SSME transfer function modeling codes to the a51p394.dat and a51p1294.dat time data files to generate transfer functions from the unmeasured input to the 129.4 degree sensor output. Included are transfer function modeling attempts using five methods. The first method is a direct application of the SSME codes to the data files and the second method uses the underlying trends in the spectral density estimates to form transfer function models with less clustering of poles and zeros than the models obtained by the direct method. In the third approach, the time data is low pass filtered prior to the modeling process in an effort to filter out high frequency characteristics. The fourth method removes the presumed system excitation and its harmonics in order to investigate the effects of the excitation on the modeling process. The fifth method is an attempt to apply constrained RID to obtain better transfer functions through more accurate modeling over certain frequency ranges. Section 4 presents some new C main files which were created to round out the functionality of the existing SSME transfer function modeling code. It is now possible to go from time data to transfer function models using only the C codes; it is not necessary to rely on external software. The new C main files and instructions for their use are included. Section 5 presents current and future enhancements to the XPLOT graphics program which was delivered with the initial software. Several new features which have been added to the program are detailed in the first part of this section. The remainder of Section 5 then lists some possible features which may be added in the future. Section 6 contains the conclusion section of this report. Section 6.1 is an overview of the work including a summary and observations relating to finding transfer functions with the SSME code. Section 6.2 contains information relating to future work on the project.

Irwin, R. Dennis↗

Bayesian prior construction for uncertainty quantification in first-principles statistical mechanics

First-principles statistical mechanics enables the prediction of thermodynamic and kinetic properties of materials, but is computationally expensive. Many approaches require surrogate models to calculate energies within Monte Carlo or molecular dynamics simulations. Inexpensive surrogates such as cluster expansions enable otherwise intractable calculations by interpolating data from higher accuracy methods, such as Density Functional Theory (DFT). Surrogate models introduce uncertainty into downstream calculations, in addition to any uncertainty inherent to DFT calculations. Bayesian frameworks address this by quantifying uncertainty and incorporating expert knowledge through priors. However, constructing effective priors remains challenging. This work introduces and describes practical strategies for building Bayesian cluster expansions, focusing on basis truncation, hyperparameter selection, and ground state replication. We analyze multiple basis truncation schemes, compare cross-validation to the evidence-approximation for hyperparameter optimization, and provide methods to find and enforce ground-state-preserving models through priors. Additionally, we compare the uncertainties between different approximations to DFT (LDA, PBE, SCAN) against the uncertainty introduced with the use of cluster expansion surrogate models. These approaches are demonstrated on the BCC Li x Mg 1-x and Li x Al 1-x alloys, which are both of interest for solid-state Li batteries. Our results provide guidelines for constructing and utilizing Bayesian cluster expansions, thereby improving the transparency of materials modeling. Furthermore, the approaches and insights developed in this work can be transferred to a wide range of cluster expansion surrogate models, including the atomic cluster expansion and related machine-learned interatomic potential architectures.

Alloy theory↗

Dark Energy Survey Year 3 results: Constraints on extensions to Λ CDM with weak lensing and galaxy clustering

We constrain six possible extensions to the Λ cold dark matter (CDM) model using measurements from the Dark Energy Survey’s first three years of observations, alone and in combination with external cosmological probes. The DES data are the two-point correlation functions of weak gravitational lensing, galaxy clustering, and their cross-correlation. We use simulated data vectors and blind analyses of real data to validate the robustness of our results to astrophysical and modeling systematic errors. In many cases, constraining power is limited by the absence of theoretical predictions beyond the linear regime that are reliable at our required precision. The Λ CDM extensions are dark energy with a time-dependent equation of state, nonzero spatial curvature, additional relativistic degrees of freedom, sterile neutrinos with eV-scale mass, modifications of gravitational physics, and a binned σ 8 ( z ) model which serves as a phenomenological probe of structure growth. For the time-varying dark energy equation of state evaluated at the pivot redshift we find ( w p , w a ) = ( - 0.9 9 - 0.17 + 0.28 , - 0.9 ± 1.2 ) at 68% confidence with z p = 0.24 from the DES measurements alone, and ( w p , w a ) = ( - 1.0 3 - 0.03 + 0.04 , - 0. 4 - 0.3 + 0.4 ) with z p = 0.21 for the combination of all data considered. Curvature constraints of Ω k = 0.0009 ± 0.0017 and effective relativistic species N eff = 3.1 0 - 0.16 + 0.15 are dominated by external data, though adding DES information to external low-redshift probes tightens the Ω k constraints that can be made without cosmic microwave background observables by 20%. For massive sterile neutrinos, DES combined with external data improves the upper bound on the mass m eff by a factor of 3 compared to previous analyses, giving 95% limits of ( Δ N eff , m eff ) ≤ ( 0.28 , 0.20 eV ) when using priors matching a comparable Planck analysis. For modified gravity, we constrain changes to the lensing and Poisson equations controlled by functions Σ ( k , z ) = Σ 0 Ω Λ ( z ) / Ω Λ , 0 and μ ( k , z ) = μ 0 Ω Λ ( z ) / Ω Λ , 0 , respectively, to Σ 0 = 0. 6 - 0.5 + 0.4 from DES alone and ( Σ 0 , μ 0 ) = ( 0.04 ± 0.05 , 0.0 8 - 0.19 + 0.21 ) for the combination of all data, both at 68% confidence. Overall, we find no significant evidence for physics beyond Λ CDM .

79 ASTRONOMY AND ASTROPHYSICS↗

Rational Design of Nanoplasmonic Array Geometries for Biosensing

Background: Molecular diagnostics provide early and accurate diagnosis, which is essential for the prevention and treatment of infectious as well as chronic diseases. These tests are designed to detect disease-specific bioanalytes such as nucleic acid (DNA or RNA) or protein (antigens, antibodies) biomarkers. In the context of infectious disease diagnosis, nucleic acid-based detection methods are known to provide more specific and sensitive results. Here, the presence of a unique sequence belonging to the pathogenic genomic material is targeted to identify species, organism, genera and/or antimicrobial resistant gene markers. The majority of the common nucleic acid based diagnostic techniques require amplification (polymerase chain reaction, isothermal amplification etc.) of the pathogenic genetic material prior to detection impacting diagnostic speed, complexity, and cost thereby limiting ease of use. Thus, the development of simplified nucleic acid-based diagnostics that can be even used in resource-poor settings may hugely benefit patients across the globe. Nanopath is a molecular diagnostics company utilizing a solid-state nanosensor to enable sequence-specific detection of target nucleic acids without the need of amplification. These nanostructures enable ultra-sensitive biomarker detection using geometric, feature-dependent properties highly dependent on the local dielectric environment, allowing them to be sensitive to low concentration binding events. This paper describes an application of this approach to provide highly relevant clinical information within a single doctor’s office visit. Intro: The Nanopath team is in collaboration with NASA (National Aeronautics and Space Administration) and NIST (National Institute of Standards and Technology) to push the bounds of the fundamental physics associated with their biosensing platform. The ability of metals to support electromagnetic surface waves gives rise to surface plasmons when optically illuminated. This property, and its strong sensitivity to changes in the local refractive index, allows for the use of metal nanoparticles as ultra-sensitive transducers. In prior work by members of this team, ensembles of randomly oriented nanoparticles (i.e., colloidal nanorods dispersed on chip) were employed for sequence-specific nucleic acid sensing (1-3). While these particle sensors have the advantage of rapid fabrication, they suffer from low sensitivity and quality factor due to the random particle dispersity. In contrast, in this study we employ ordered array nanoparticle ensembles which can be used to improve sensor sensitivity and figure-of-merit. Study Methods Overview: In this talk, we detail the results of sensing experiments and computational simulations to outline a rational design of the structure of these plasmonic nanoparticle arrays for biomolecular sensing. Through simulation and experiment, we iteratively tailor nanostructure dimension to provide high quality signal and large resonance shifts upon modeled nucleic acid binding. In particular, full-wave electromagnetic simulations were conducted using Lumerical photonic simulation software in which periodic boundary conditions were applied in the x- and y- dimensions for each of the nanoplasmonic sensor geometries. To simulate the resonance response to changes in the bulk solution in contact with the sensor surface, the refractive index of the surrounding media was changed appropriately. Nucleic acid hybridization events were modeled using either using spherical structures approximating the relevant radius of genomic material as estimated by polymer models, or as conformal layers with the known refractive indices for nucleic acids. On the basis of initial simulations, nanosensors were fabricated using traditional electron-beam lithography protocols at NIST. To evaluate consensus between simulations and experiments, bulk sensing experiments were carried out in which the resonance peaks were obtained by submerging the sensors in refractive index standards. Key nanosensor characteristics including resonance peak locations, resonance peak shifts as a function of refractive index, and figure of merit (FOM) of extinction curves were examined between the experimental and simulation results prior to proceeding with simulations on additional geometries and more complex solution conditions, and further device fabrication. This iterative process is repeated toward a rational design of nanoplasmonic array geometries for biosensing optimizing response for targeted disease detection. In summary, this study puts forth a methodology for rational design and characterization of regularly spaced nanoparticle arrays for optics-based biosensing. The results of this study will allow for more informed design of nanostructure geometries towards sequence-specific nucleic acid detection. These improved designs have the potential to improve clinical sensitivity and limit-of-detection across disease indication.

sensor↗

Functional prescription for EFT matching

We simplify the one-loop functional matching formalism to develop a streamlined prescription. The functional approach is conceptually appealing: all calculations are performed within the UV theory at the matching scale, and no prior determination of an Effective Field Theory (EFT) operator basis is required. Our prescription accommodates any relativistic UV theory that contains generic interactions (including derivative couplings) among scalar, fermion, and vector fields. As an example application, we match the singlet scalar extended Standard Model (SM) onto SMEFT.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Isotope effects on the structural transformation and relaxation of deeply supercooled water

Herein, we have examined the structure of supercooled liquid D 2 O as a function of temperature between 185 and 255 K using pulsed laser heating to rapidly heat and cool the sample on a nanosecond timescale. The liquid structure can be represented as a linear combination of two structural motifs, with a transition between them described by a logistic function centered at 218 K with a width of 10 K. The relaxation to a metastable state, which occurred prior to crystallization, exhibited nonexponential kinetics with a rate that was dependent on the initial structural configuration. When the temperature is scaled by the temperature of maximum density, which is an isostructural point of the isotopologues, the structural transition and the non-equilibrium relaxation kinetics of D 2 O agree remarkably well with those for H 2 O.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient quantum simulation of QCD jets on the light front

Quark and gluon jets provide one of the best ways to probe the matter produced in ultrarelativistic high-energy collisions, from cold nuclear matter to hot quark-gluon plasma. In this work, we propose a unified framework for efficient quantum simulation of many-body dynamics using the ( 3 + 1 )-dimensional QCD Hamiltonian on the light front, particularly suited for studying the scattering of quark and gluon jets on nuclear matter in heavy-ion collisions. We describe scalable methods for mapping physical degrees of freedom onto qubits and for simulating in-medium jet evolution. We then validate our framework by implementing an algorithm that directly maps second-quantized Fock states onto qubits and uses Trotterized simulation for simulating time dynamics. Using a classical emulator, we investigate the evolution of quark and gluon jets with up to three particles in Fock states, extending prior studies. These calculations enable the study of key observables, including jet momentum broadening, particle production, and parton distribution functions. Published by the American Physical Society 2025

Qian, Wenyang (ORCID:0000000155250996)↗

Uncertainty Visualization of Critical Points of 2D Scalar Fields for Parametric and Nonparametric Probabilistic Models

This paper presents a novel end-to-end framework for closed-form computation and visualization of critical point uncertainty in 2D uncertain scalar fields. Critical points are fundamental topological descriptors used in the visualization and analysis of scalar fields. The uncertainty inherent in data (e.g., observational and experimental data, approximations in simulations, and compression), however, creates uncertainty regarding critical point positions. Uncertainty in critical point positions, therefore, cannot be ignored, given their impact on downstream data analysis tasks. Here, in this work, we study uncertainty in critical points as a function of uncertainty in data modeled with probability distributions. Although Monte Carlo (MC) sampling techniques have been used in prior studies to quantify critical point uncertainty, they are often expensive and are infrequently used in production-quality visualization software. We, therefore, propose a new end-to-end framework to address these challenges that comprises a threefold contribution. First, we derive the critical point uncertainty in closed form, which is more accurate and efficient than the conventional MC sampling methods. Specifically, we provide the closed-form and semianalytical (a mix of closed-form and MC methods) solutions for parametric (e.g., uniform, Epanechnikov) and nonparametric models (e.g., histograms) with finite support. Second, we accelerate critical point probability computations using a parallel implementation with the VTK-m library, which is platform portable. Finally, we demonstrate the integration of our implementation with the ParaView software system to demonstrate near-real-time results for real datasets.

97 MATHEMATICS AND COMPUTING↗

Exposing new taxonomic variation with inflammation — a murine model-specific genome database for gut microbiome researchers

The murine CBA/J mouse model widely supports immunology and enteric pathogen research. This model has illuminated Salmonella interactions with the gut microbiome since pathogen proliferation does not require disruptive pretreatment of the native microbiota, nor does it become systemic, thereby representing an analog to gastroenteritis disease progression in humans. Despite the value to broad research communities, microbiota in CBA/J mice are not represented in current murine microbiome genome catalogs. Here we present the first microbial and viral genomic catalog of the CBA/J murine gut microbiome. Using fecal microbial communities from untreated and Salmonella-infected, highly inflamed mice, we performed genomic reconstruction to determine the impacts on gut microbiome membership and functional potential. From high depth whole community sequencing (~ 42.4 Gbps/sample), we reconstructed 2281 bacterial and 4516 viral draft genomes. Salmonella challenge significantly altered gut membership in CBA/J mice, revealing 30 genera and 98 species that were conditionally rare and unsampled in non-inflamed mice. Additionally, inflamed communities were depleted in microbial genes that modulate host anti-inflammatory pathways and enriched in genes for respiratory energy generation. Our findings suggest decreases in butyrate concentrations during Salmonella infection corresponded to reductions in the relative abundance in members of the Alistipes. Strain-level comparison of CBA/J microbial genomes to prominent murine gut microbiome databases identified newly sampled lineages in this resource, while comparisons to human gut microbiomes extended the host relevance of dominant CBA/J inflammation-resistant strains. This CBA/J microbiome database provides the first genomic sampling of relevant, uncultivated microorganisms within the gut from this widely used laboratory model. Using this resource, we curated a functional, strain-resolved view on how Salmonella remodels intact murine gut communities, advancing pathobiome understanding beyond inferences from prior amplicon-based approaches. Salmonella-induced inflammation suppressed Alistipes and other dominant members, while rarer commensals like Lactobacillus and Enterococcus endure. The rare and novel species sampled across this inflammation gradient advance the utility of this microbiome resource to benefit the broad research needs of the CBA/J scientific community, and those using murine models for understanding the impact of inflammation on the gut microbiome more generally.

59 BASIC BIOLOGICAL SCIENCES↗

Remote Measurements of Snowfalls in Wakasa Bay, Japan with Airborne Millimeter- wave Imaging Radiometer and Cloud Radar

In this paper we explore the application of combined millimeter-wave radar and radiometry to remotely measure snowfall. During January-February of 2003, a field campaign was conducted with the NASA P-3 aircraft in Wakasa Bay, Japan for the validation of the AMSRE microwave radiometer on board the Aqua satellite. Among the suite of instruments-on board the P-3 aircraft were the Millimeter-wave Imaging Radiometer (MIR) from the NASA Goddard Space Flight Center and the 94 GHz Airborne Cloud Radar (ACR) which is co-owned and operated by NASA Jet Propulsion Laboratory/University of Massachusetts. MIR is a total power, across-track scanning radiometer that measures radiation at the frequencies of 89, 150, 183.3 +/- 1, 183.3 +/- 3, 183.3 +/-7, 220, and 340 GHz. The MIR has flown many successful missions since its completion in May 1992. ACR is a newer instrument and flew only a few times prior to the Wakasa Bay deployment. These two instruments which are particularly well suited for the detection of snowfall functioned normally during flights over snowfall and excellent data sets were acquired. On January 14, 28, and 29 flights were conducted over snowfall events. The MIR and ACR detected strong signals during periods of snowfall over ocean and land. Results from the analysis of these concurrent data sets show that (1) the scattering of millimeter-wave radiation as detected by the MIR is strongly correlated with ACR radar reflectivity profiles, and (2) the scattering is highly frequency-dependent, the higher the frequency the stronger the scattering. Additionally, the more transparent channels of the MIR (e.g., 89, 150, and 220 GHz) are found to display ambiguous signatures of snowfall because of their exposure to surface features. Thus, the snowfall detection and retrievals of snowfall parameters, such as the ice water path (IWP) and median mass diameter (D(me)) are best conducted at the more opaque channels near 183.3 GHz and 340 GHz. Retrievals of IWP and D(me) using the MIR measurements at 183.3 and 340 GHZ are currently in progress, and the results will be compared with those derived from the ACR reflectivity profiles. Implication from this comparison will be discussed.

Wang, J. R.↗

Restoration of plasma volume after 16 days of head-down tilt induced by a single bout of maximal exercise

Seven healthy men performed maximal exercise 24 h before the end of 16 days exposure to 6 degrees head-down tilt (HDT) to test the hypothesis that such an exercise technique could restore plasma volume (PV) at the end of a simulated space mission. Exercise consisted of supine cycling with graded work rates increasing by 16 W/min to volitional fatigue and required an average of 16 min. The experimental protocol was a standard cross-over design in which the order of treatment (exercise or control) was counterbalanced across all seven subjects. PV, fluid intake (ad libitum), urine output, renal function, and hormones associated with fluid homeostasis were measured before HDT, 24 h before the end of HDT just prior to exercise, and at the end of HDT 24 h after exercise. HDT reduced PV by 16% in both control and exercise conditions. Maximal exercise completely restored plasma volume within 24 h to 3.9 +/- 3.2% of pre-HDT levels despite continued HDT. Compared with control, exercise induced a 660-ml larger positive fluid balance because of greater fluid intake and reduced urine volume during the 24 h after exercise. These results suggest that one bout of maximal leg exercise before return from 16 days of spaceflight may be completely effective in stimulating thirst and restoring plasma volume to preflight levels.

Non-NASA Center↗

Retrieval of Mir Solar Array

A Russian solar array panel removed in November 1997 from the non-articulating photovoltaic array on the Mir core module was returned to Earth on STS-89 in January 1998. The panel had been exposed to low Earth orbit (LEO) for 10 years prior to retrieval. The retrieval provided a unique opportunity to study the effects of the LEO environment on a functional solar array. To take advantage of this opportunity, a team composed of members from RSC-Energia (Russia), the Boeing Company, and the following NASA Centers--Johnson Space Center, Kennedy Space Center, Langley Research Center, Marshall Space Flight Center, and Lewis Research Center--was put together to analyze the array. After post-retrieval inspections at the Spacehab Facility at Kennedy in Florida, the array was shipped to Lewis in Cleveland for electrical performance tests, closeup photodocumentation, and removal of selected solar cells and blanket material. With approval from RSC-Energia, five cell pairs and their accompanying blanket and mesh material, and samples of painted handrail materials were selected for removal on the basis of their ability to provide degradation information. Sites were selected that provided different sizes and shapes of micrometeoroid impacts and different levels of surface contamination. These materials were then distributed among the team for round robin testing.

Rutledge, Sharon K.↗

Influence of Hydroponically Grown Hoyt Soybeans and Radiation Encountered on Mars Missions on the Yield and Quality of Soymilk and Tofu

Soybeans were chosen for hmar and planetary missions due to their nutritive value and ability to produce oil and protein for further food applications. However, soybeans must be processed into foods prior to crew consumption. Wilson et al. (2003) raised questions about (1) the influence of radiation (on germination and functional properties) that the soybeans would be exposed to during bulk storage for a Mars mission, and (2) the impact of using hydroponically grown versus field grown soybeans on the yield and quality of soyfoods. The influence of radiation can be broken down into two components: (A) affect of surface pasteurization to ensure the astronauts safety from food-borne illnesses (a Hazard Analysis Critical Control Point), and (B) affect of the amount of radiation the soybeans receive during a Mars mission. Decreases in the amount of natural antioxidants and free radical formation and oxidation induced changes in the soybean (lipid, protein, etc.) will influence the nutritional value, texture, quality, and safety of soyfoods made from them. The objectives of this project are to (1) evaluate the influence of gamma and electron beam radiation on bulk soybeans (HACCP, CCP) on the microbial load, germination, ease of processing, and quality of soymilk and tofu; (2) provide scale up and mass balance data for Advanced Life Support subsystems including Biomass, Solid Waste Processing, and Water Recovery Systems; and (3) to compare Hoyt field grown to hydroponically grown Hoyt soybeans for soymilk and tofu production. The soybean cultivar Hoyt, a small standing, high protein cultivar that could grow hydroponically in the AIMS facility on Mars) was evaluated for the production of soymilk and tofu. The quality and yield of the soymilk and tofu from hydroponic Hoyt, was compared to Vinton 81 (a soyfood industry standard), field Hoyt, IA 2032LS (lipoxygenase-free), and Proto (high protein and antioxidant potential). Soymilk and tofu were produced using the Japanese method. The soymilk was coagulated with calcium sulfate dihydrate. Soybeans and tofu were evaluated using chemical, microbial, and instrumental sensory methods. The surface radiation of whole dry soybeans using electron beam or gamma rays at 10 or 30 kGy did provide microbial safety for the astronauts. However, these doses caused oxidative changes that resulted in tofu with rancid aroma, darkening of the tofu, lower tofu yields, more solid waste, and loss of the ability of the seeds to germinate. While lower doses may reduce these problems, we lose the ability to insure microbial safety (cross-contamination) of bulk soybeans for the astronauts. Counter measures could include vacuum packaging, radiating under freezing conditions. A No Effect Dose for food quality, below 10 kGy needs to be determined. Better estimates of the radiation that the food will be exposed to need to determined and shared. Appropriate shielding for the food as well as the astronauts needs to be developed. The Hoyt soybean did not provide a high yielding, high quality tofu. A new small scale system for evaluating soybeans was developed using 50 g quantities of soybeans.

Wilson, Lester A.↗

Simulation Results for Airborne Precision Spacing along Continuous Descent Arrivals

This paper describes the results of a fast-time simulation experiment and a high-fidelity simulator validation with merging streams of aircraft flying Continuous Descent Arrivals through generic airspace to a runway at Dallas-Ft Worth. Aircraft made small speed adjustments based on an airborne-based spacing algorithm, so as to arrive at the threshold exactly at the assigned time interval behind their Traffic-To-Follow. The 40 aircraft were initialized at different altitudes and speeds on one of four different routes, and then merged at different points and altitudes while flying Continuous Descent Arrivals. This merging and spacing using flight deck equipment and procedures to augment or implement Air Traffic Management directives is called Flight Deck-based Merging and Spacing, an important subset of a larger Airborne Precision Spacing functionality. This research indicates that Flight Deck-based Merging and Spacing initiated while at cruise altitude and well prior to the Terminal Radar Approach Control entry can significantly contribute to the delivery of aircraft at a specified interval to the runway threshold with a high degree of accuracy and at a reduced pilot workload. Furthermore, previously documented work has shown that using a Continuous Descent Arrival instead of a traditional step-down descent can save fuel, reduce noise, and reduce emissions. Research into Flight Deck-based Merging and Spacing is a cooperative effort between government and industry partners.

Barmore, Bryan E.↗

ROPEC - ROtary PErcussive Coring Drill for Mars Sample Return

The ROtary Percussive Coring Drill is a light weight, flight-like, five-actuator drilling system prototype designed to acquire core material from rock targets for the purposes of Mars Sample Return. In addition to producing rock cores for sample caching, the ROPEC drill can be integrated with a number of end effectors to perform functions such as rock surface abrasion, dust and debris removal, powder and regolith acquisition, and viewing of potential cores prior to caching. The ROPEC drill and its suite of end effectors have been demonstrated with a five degree of freedom Robotic Arm mounted to a mobility system with a prototype sample cache and bit storage station.

Chu, Philip↗