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The National Aeronautics and Space Administration's (NASA'a) New Millennium Program (NMP) has embarked on a technology flight-validation demonstration program to enable the kinds of missions that NASA envisions for the 21st century. Embedded in the program is the concept of rapid mission development supported by a fast-track procurement process.
In addition to acquiring multispectral data, the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) will also acquire along-track stereo data. ASTER is capable of acquiring 771 digital stereo pairs per day, each covering 60 x 60 km on the ground, at 15 m resolution with a base/height ratio of 0.6.
The VIGILANTE project is a planned vision system capable of tracking and recognizing targets in real time, on a small airborne platform.
This paper describes the application of Artificial Intelligence planning techniques to the problem of antenna track plan generation for a NASA Deep Space Communications Station.
During long-term space missions, microbial cultures accumulate the effects of low-dose radiation, microgravity, and other factors; altered growth and metabolic activity may occur before viability effects. This could affect functionality of bioreactors or other bio-enabled mission systems, as well as shed light on human health. Spaceflight microbiology studies beyond the low Earth orbit exposure afforded by the ISS have been limited. Nanosatellites offer an increasingly popular alternative for deep space missions. However, the communications delay requires biofluidic automation of a pre-defined experimental protocol, and the lack of sample return (reliance on sensors in flight) can significantly limit feasible investigations. Previous biological CubeSats (PharmaSat, O/OREOS, EcAMSat) have used alamarBlue, an off-the-shelf formulation of the redox indicator dye resazurin, to track metabolic activity, as will BioSentinel, the upcoming interplanetary microbiology experiment. A series of ground experiments (see abstracts by Liddell, Santa Maria, and A. Kim) were conducted using a microbial culture system outfitted with an electrochemical sensor array (electrical conductivity, pH, oxidation-reduction potential, and dissolved oxygen) with alamarBlue and the same strain of Saccharomyces cerevisiae as BioSentinel. By improving mapping of measured changes in alamarBlue kinetics to physicochemical changes, and ultimately to biological alterations such as shifted metabolic pathways, this work supplements data analyses from past missions and planning for future missions using alamarBlue to characterize space radiation effects. Initial results indicate that alamarBlue acts like a redox buffer; its presence significantly changes redox kinetics in otherwise identical cultures. The initial color change (blue resazurin reduced to red/pink resorufin) appears as a redox plateau. A second plateau, likely corresponding to the second color transition (resorufin to the colorless hydroresorufin), occurs at a lower redox value. The relationship to carbon source exhaustion, dissolved oxygen depletion, cell death, and measured redox potential is complex and still under study.
This work investigates the use of a star tracker that senses star light in the short wave infra-red wavelengths, specifically at the photometric H-band. The number of stars available for tracking and the corresponding photometric H-band magnitude is presented using information derived from the Two Micron All Sky Survey (2MASS) catalog. The probability of observing at least four stars in the star tracker’s field of view (FOV) at a given H-band magnitude or brighter is also presented. Finally, a notional short wave infra-red (SWIR) star tracker design is presented using the parameters calculated for the expected number of stars observed at the corresponding magnitudes in the photometric H-band. The results for the SWIR star tracker indicate the potential for a reduced FOV as compared to the visible wavelengths and relaxed star magnitude sensing requirements.
The paper presents an Extended Kalman Filter based framework for airborne target tracking using dynamic information fusion from multi-modal sensors with geodiversity. First, the algorithm execution location is determined using an optimal data migration strategy, next the sensors information is dynamically fused at each estimation instance using validity flag for each sensor reading, finally the target estimation is updated based on the fused innovation vector. The approach is applied to synthetic data generated from the radar and camera models located on the ground for the simulated target flight in Reflection simulation environment.
Autonomous operations are a crucial aspect in the context of Advanced Air Mobility and other emerging aviation markets. In order to enable this autonomy, an accurate and detailed understanding of the positions of the various vehicles in the air is necessary. Full localization independent of on-board sensors makes the system suitable for noncooperative vehicles. This paper focuses on the object tracking part that relies on distributed ground-based RF and other sensor fusion, considering specific properties and limitations of different sensor types. Results show satisfactory performance in nominal scenarios with full coverage for some sensor types, but RF signals are challenging because of their nature. This paper includes the results from simulations as well as field tests to support the observations and conclusions.
The Lightweight Surface Manipulation System, or LSMS, is a family of scalable long-reach cable-actuated manipulators. The design of the LSMS has a high payload ratio for efficient operations on planetary surfaces like the Moon or Mars. The LSMS has nonlinear, coupled, and hybrid dynamics. The engineering decisions that led to these challenging dynamics make this structure light and efficient. This paper proposes a novel trajectory tracking algorithm for these cranes that facilitates precise autonomous and teleoperated operations. This algorithm enables these robots to follow complex trajectories that avoid obstacles and pickup regolith in a construction site.
The Lightweight Surface Manipulation System, or LSMS, is a family of scalable long-reach cable-actuated manipulators. The design of the LSMS has a high payload ratio for efficient operations on planetary surfaces like the Moon or Mars. The LSMS has nonlinear, coupled, and hybrid dynamics. The engineering decisions that led to these challenging dynamics make this structure light and efficient. This paper proposes a novel trajectory tracking algorithm for these cranes that facilitates precise autonomous and teleoperated operations. This algorithm enables these robots to follow complex trajectories that avoid obstacles and pickup regolith in a construction site.
Orbital debris may collide with crewed and robotic spacecraft, placing them at risk. The wide range of debris, from 9,000-kilogram rocket bodies to millions of millimeter-size debris, has led to a similarly wide range of proposed actions for addressing the risks posed by debris. However, the costs and benefits of these actions have historically been unknown. This is a challenge for decision makers who are choosing which actions to support through technology development or policy changes. NASA’s Office of Technology, Policy, and Strategy is addressing these technical and economic uncertainties by building a capability to (1) complete rigorous calculations of the net present value of each action, (2) identify an optimal portfolio of actions to reduce risk, and (3) quantitatively analyze policies related to space sustainability. This report describes our progress toward that capability and to solicit feedback from the space and economic communities. Our previous work(Colvin, Karcz, and Wusk. 2023), referred to here as Phase 1, assessed the costs and benefits of performing debris remediation on operationally relevant timescales. The current paper summarizes the work of Locke and Colvin (2024), which contains major updates to the risk model used in Phase 1 and expands the breadth of actions considered to include mitigating the creation of debris, improving the ability to track debris, and more methods for cleaning up existing debris. We demonstrate that our approach of measuring risks in dollars allows for the effectiveness of seemingly incommensurate actions to be compared and generates insights that other approaches to measuring risk have missed.
This poster informs about the ongoing development project of the Mass Tracking System (MTG) taking place in Fuels Conditioning Complex at MFC. The information is about the MTG utilization, the possible complications in the future with the system and the solution for those complication. Furthermore, the poster reports about the progress and the future plans of the project after brief insight on how the MTG operates in the facility. Essentially, the project is separated in three different phases starting with the back-end development focusing on conversion and migration phases and finalizing with the front-end development of the website phase to provide FCF with versatile and efficient system.
Although strain underpins the behavior of many transition-oxide-based magnetic nanomaterials, it is elusive to quantify. Since the formation of orbital molecules is sensitive to strain, a metal–insulator transition should be a window into nanocrystallite strain. Using three sizes of differently strained Fe 3 O 4 polycrystalline nanorods, the impact of strain on the Verwey transition and the associated formation and dissolution processes of quasiparticle trimerons is tracked. In 40 and 50 nm long nanorods, increasing isotropic strain results in Verwey transitions going from T V ≈ 60 K to 20 K. By contrast, 700 nm long nanorods with uniaxial strain along the (110) direction have T V ≈ 150 K—the highest value reported thus far. A metal–insulator transition, like T V in Fe 3 O 4 , can be used to determine the effective strain within nanocrystallites, thus providing new insights into nanoparticle properties and nanomagnetism.
ABSTRACT This paper presents the multi‐species global impurity transport capability developed in a GPU‐accelerated fully 3D unstructured mesh‐based code, GITRm, to simultaneously track multiple impurity species and handle interactions of these impurities with mixed‐material surfaces. Different computational approaches to model particle‐surface interaction or surface response have been developed and compared. Sheath electric field is taken into account by employing a fast distance‐to‐boundary calculation, which is carried out in parallel on distributed or partitioned meshes on multiple GPUs without the need for any inter‐process communication during the simulation. Several example cases, including two for the DIII‐D tokamak, that is, one with the SAS‐V divertor and the other with the collector probes, are used to demonstrate the utility of the current multi‐species capability. For the DIII‐D probe case, the capability of GITRm to resolve the spatial distribution of particles in localized regions, such as diagnostic probes, within non‐axisymmetric tokamak geometries is demonstrated. These simulations involve up to 320 million particles and utilize up to 48 GPUs.
Abstract A substantial fraction of nitrogen (N) fertilizer applied in agricultural systems is not incorporated into crops and moves below the rooting zone as nitrate (NO 3 − ). Understanding mechanisms for soil N retention below the rooting zone and leaching to groundwater is essential for our ability to track the fate of added N. We used dual stable isotopes of nitrate (δ 15 N–NO 3 − and δ 18 O–NO 3 − ) and water (δ 18 O–H 2 O and δ 2 H–H 2 O) to understand the mechanisms driving nitrate leaching at three depths (0.8, 1.5, and 3.0 m) of an irrigated corn field sampled every 2 weeks from 2016 to 2020 in the southern Willamette Valley, Oregon, USA. Distinct periods of high nitrate concentrations with lower δ 15 N–NO 3 − values indicated that a portion of that nitrate was from recent fertilizer applications. We used a mixing model to quantify nitrate fluxes associated with recently added fertilizer N versus older, legacy soil N during these “fertilizer signal periods.” Nitrate leached below 3.0 m in these periods made up a larger proportion of the total N leached at that depth (∼52%) versus the two shallower depths (∼13%–16%), indicating preferential movement of recently applied fertilizer N through the deep soil into groundwater. Further, N associated with recent fertilizer additions leached more easily when compared to remobilized legacy N. A high volume of fall and winter precipitation may push residual fertilizer N to depth, potentially posing a larger threat to groundwater than legacy N. Optimizing fertilizer N additions could minimize fertilizer losses and reduce nitrate leaching to groundwater.
We develop a geometric framework in Feynman-parameter space to determine constraints on the sequential discontinuities of Feynman integrals. Our method is based on tracking the deformation of the integration contour as external kinematics are analytically continued. This procedure imposes powerful constraints on the analytic structure of Feynman integrals, providing crucial inputs for their bootstrap. We demonstrate the usefulness of this framework by applying it to integrals in dimensional regularization, with higher propagator powers, and to examples with non-uniform transcendental weight. The method is illustrated with several one- and two-loop calculations.
A search for long-lived particles using final states including a displaced vertex with low-momentum tracks, large missing transverse momentum, and a jet from initial-state radiation is presented. This search uses proton-proton collision data at a center-of-mass energy of 13 TeV collected by the CMS experiment at the CERN LHC in 2017 and 2018, with a total integrated luminosity of 100 fb −1 . This analysis adopts specific supersymmetric (SUSY) coannihilation scenarios as benchmark signal models, characterized by a next-to-lightest SUSY particle (NLSP) with a mass difference of less than 25 GeV relative to the lightest SUSY particle, assumed to be a bino-like neutralino. In the top squark $\huge{(}$$\tilde{\textrm{t}}$$\huge{)}$ NLSP model, the NLSP is a long-lived $\tilde{\textrm{t}}$, while in the bino-wino NLSP scenario, the mass-degenerate NLSPs are a wino-like long-lived neutralino and a short-lived chargino. The search excludes top squarks with masses less than 400–1100 GeV and wino-like neutralinos with masses less than 220–550 GeV, depending on the signal parameters, including the mass difference, mass, and lifetime of the long-lived particle. It sets the most stringent limits to date for the $\tilde{\textrm{t}}$ and bino-wino NLSP models.
This paper presents two searches for the electroweak production of higgsinos with compressed mass spectra using 140 fb−1 of s=13$$ \sqrt{s}=13 $$ TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider. Events are required to feature an energetic jet, large missing transverse momentum, and at least one low-momentum charged particle that serves as a candidate higgsino decay product. In the first search, targeting higgsino mass splittings in the range of 0.3–1 GeV, the higgsinos are expected to predominantly decay into pions that are identified as low-momentum charged particles with large transverse impact parameters due to the long higgsino lifetime (cτ ≈ ?(0.1–10 mm)), and neural networks are used to discriminate between signal and background processes. The second search targets larger mass splittings in the range of 1–3 GeV, where the higgsinos are expected to decay promptly into low-momentum leptons, one of which is identified by dedicated low-momentum electron or muon taggers based on neural networks utilising tracking and calorimeter information. No significant excess above the Standard Model prediction is observed in either search and the results are interpreted within simplified models, to set lower limits on the masses of the higgsino-like charginos and neutralinos. Together, these searches exclude chargino masses below 126 GeV at 95% confidence level for mass splittings between the chargino and lightest neutralino in the range of 0.3–2 GeV. This represents the first ATLAS constraints in a portion of this parameter space and surpasses the limits previously set by other experiments.