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All sources NASA NTRS DOE OSTI

NASA NTRS2018

Development of the Multi-Purpose Transportation System for the Space Launch System (SLS) Core Stage (CS) Flight Article

NASA's Multi-Purpose Transportation System (MPTS) is designed to transport the Space Launch System (SLS) vehicle segments by waterway and roadway. It is tasked with transporting the vehicle from where it is manufactured to its intermediate test location and final launch destination. Its design incorporates mechanisms that release degrees of freedom to prevent excessive loading during transit and ensure a successful delivery of the vehicle to its intended destination. In addition to the Core Stage (CS) flight article, the system will also move three Structural Test Articles (STAs), the Dynamic Demonstration Unit (DDU), and a simulated CS Pathfinder (weight, center of gravity, outer mold line dimensions, and overall length) over road terrain at four NASA centers and on the Pegasus barge. The MPTS independently supports the article at both ends while operating as a combined unit through automated monitoring of its released degree of freedom and corrective responses. This allows the system to constrain its payload in a statically determinate manner while traversing highly variable terrain. Multi-body simulation of the transportation route is useful to predict free-body motion within its range of mobility. The MPTS has completed its design and analysis developmental cycles. This paper describes the design challenges encountered in developing this system of large-scale structure, which incorporates complex mechanisms. The unique techniques and methodologies developed for analytical assessment of the hardware are also discussed.

Sandridge, Sarah↗

DOE OSTI2020

Re-Envisioning RCx: Achieving Max Potential HVAC Controls Retrofits through Modernized BAS Hardware and Software

Most existing buildings have sub-optimal heating, ventilation, and air conditioning (HVAC) controls, resulting in wasted energy and occupant discomfort. Retro-commissioning (RCx) addresses many of these issues, but it is a lengthy and highly customized process. Limited capabilities of existing building automation system hardware restricts the scope of most RCx projects. Incentive programs consider building automation system (BAS) hardware retrofits to be high-capital investments and do not allow them in typical RCx programs. This paper describes work that the authors are leading to facilitate technical and market innovation in the BAS industry to unlock large savings in existing commercial buildings through deep retrofits of BAS hardware and software. California and New York research projects are demonstrating BAS retrofits leveraging the American Society of Heating, Refrigeration, and Air Conditioning Engineers’ (ASHRAE) new Guideline 36 high performance sequences of operation to achieve greater than 20 percent whole building energy savings, while saving costs and reducing risk through streamlined processes and standardization across BAS manufacturer product lines and across implementation practices. This paper describes market barriers that impede achieving deep savings from BAS retrofits in custom incentive and traditional RCx programs and presents a new maximum potential BAS retrofit model that addresses these barriers. The new model leverages the authors’ efforts in market enablement through open standards, BAS industry partnerships, and tools for cost-effective scaling that includes tools for project screening, savings calculations, and measurement and verification (M&V). This approach is widely applicable and will be ready for at-scale implementation within two years.

Paliaga, Gwelen↗

NASA NTRS2004

Development of a Lunar Consumables Storage and Distribution Depot

NASA is in the preliminary planning stages for a future lunar base as a response to President George W. Bush's recent announcement of a new sustained exploration program beyond low earth orbit. Kennedy Space Center engineers are supporting this program by utilizing experience in Spaceport system design and operations to help develop a Lunar Consumables Depot. This depot will store propellants, life support fluids, and other consumables either transported from Earth or manufactured from In Situ resources. The depot will distribute these consumables in an energy efficient manner to end users including spacecraft, habitation modules, and rovers. This paper addresses some of the changes to lunar base architecture design as a result of advances in knowledge of lunar resources over the past 35 years, as well as technology advances in the area of In Situ Resource Utilization and consumable storage and distribution. A general system level description of the depot will be presented, including overall design philosophy and high level requirements. Finally, specific subsystem technologies that have been or will be developed by KSC will be addressed. Examples of these technologies are automated umbilicals, cryogenic refrigerators, novel storage vessels, advanced heat switches and heat exchangers, and self healing gaskets and wires.

Mueller, Robert P.↗

DOE OSTI2024

Manufacturability-based optical design optimization for advanced Kirkpatrick–Baez X-ray focusing mirrors

The advanced Kirkpatrick–Baez (AKB) mirror setup is an effective and compelling solution to provide stable X-ray nano-focusing for synchrotron radiation or free-electron laser beamlines. We propose an AKB mirror design optimization approach to mitigate the difficulties associated with mirror fabrication by minimizing the total slope ranges of the four curved mirrors while achieving the expected focusing performance. In the optimization, we have considered geometry constraints to ensure the beam acceptance with the required clear aperture, the diffraction-limited focal size with the adequate numerical aperture, and the desired mirror gaps for adjustment and the necessary working distance for the sample stage. Additionally, practical constraints linked to mirror metrology and fabrication, such as mirror length limits and curvature uncertainty in measurement, are taken into account. Furthermore, progressive objective optimization eliminates the need for any initial guess, fully automating the AKB optimization process. This approach facilitates the development of an elegant Wolter-I or Wolter-III type AKB design solution that satisfies these multiple constraints. In cases where constraints cannot be simultaneously satisfied, the optimization results provide valuable insights into areas where trade-offs need to be considered. Simulations with ray tracing and wavefront propagation validate the optimized AKB design showing high tolerance to the beam incident angle.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Evaluating the Effectiveness of a Detection and Deterrent System in Reducing Golden Eagle Fatalities at Operational Wind Facilities

The Renewable Energy Wildlife Institute (REWI) was appointed as the prime awardee of DOE award number DE-EE0007883 to lead a team of scientists, wind developers, and technology manufacturers toward the overarching goal of evaluating the effectiveness of the current DTBird system in minimizing the risk of golden eagles (Aquila chrysaetos) and other large soaring raptors from approaching the rotor-swept zone (RSZ) of operating wind turbines. As part of this goal, the team set out to 1) quantify the expected reduction in collision risk for golden eagles from operation of the detection and deterrence modules in a manner that supports the approach used by the U.S. Fish and Wildlife Service (USFWS) to assess and credit facility operators for their efforts to minimize predicted collision fatalities and 2) provide information to help improve the technology to maximize its effectiveness. DTBird is an automated detection and audio deterrent system created by the Spanish company Liquen, designed to discourage birds from entering the RSZ of spinning wind turbines. The system uses cameras to automatically detect airborne targets of interest, records each such event in an online database, and triggers a warning signal (loud sound) if the tracked object has moved close to the turbine. If the object moves even closer to the RSZ, a more aggressive dissuasion signal is broadcast. To meet our objectives, the team conducted a two-year experiment at the Goodnoe Hills wind facility in Washington state, in which 14 turbines were outfitted with DTBird units. Daily, each DTBird-equipped turbine was randomly assigned to a control or treatment group. Treatment turbines operated with DTBird running as intended—broadcasting warning or deterrent signals when DTBird detected a target within range. On control turbines, no sound signals were broadcast if a moving target triggered the DTBird system. The team also flew unmanned aerial vehicles (UAVs) designed to coarsely mimic the general size, weight, and coloration of golden eagles in programmed flight transects across DTBird detection ranges to quantify DTBird’s ability to detect intended targets and to evaluate factors that influence the probability of detection and DTBird’s response distances. Additionally, the team evaluated the behavioral responses of in situ eagles exposed to spinning turbines alone (visual and sound influences) versus spinning turbines plus broadcasted DTBird audio deterrents, to estimate the effectiveness of deterrence by the DTBird system. The data and results from these investigations were combined with those from a pilot study conducted at the Manzana Wind Power Project in California to better evaluate DTBird’s effectiveness across different landscapes.

17 WIND ENERGY↗

DOE OSTI2026

High-throughput small-angle X-ray scattering reveals effective structure factor transitions linked to high-concentration antibody viscosity

High-concentration monoclonal antibody (mAb) formulations are often constrained by elevated viscosity, largely driven by protein–protein interactions, which complicates manufacturing and limits subcutaneous delivery. Early viscosity risk assessment is essential during discovery, yet traditional measurements require large sample volumes, and lack high-throughput capability. Here, we develop a high-throughput small-angle X-ray scattering (SAXS) protocol to detect mAb self-association at dilute concentrations, enabling early predictive insights into high-concentration viscosity. Synchrotron SAXS measurements were conducted for 21 mAbs formulated in a histidine buffer at pH 6.0. An initial subset of 10 mAbs analyzed across 1–150 mg/mL revealed that effective structure factor transitions in the low-q region, indicative of interparticle interactions, consistently emerged below 25 mg/mL. Subsequently, 11 additional mAbs were analyzed at 1–25 mg/mL using automated liquid handling and flow cells to enable high-throughput screening. High-viscosity mAbs exhibited detectable low-q upturns at concentrations ≤10 mg/mL, whereas low-viscosity mAbs showed downturns. A classification criterion based on effective structure factor transitions accurately classified all high- and low-viscosity mAbs at 150 mg/mL, offering a scalable, sample-efficient alternative to conventional methods. These results extend recent findings on the concentration-dependent sensitivity of SAXS to short-range attractions, demonstrating that they can emerge at lower concentrations than previously reported. This study presents the most comprehensive and diverse SAXS dataset for mAbs reported to date within a single formulation, providing a valuable resource for developing and validating coarse-grained models that can more accurately capture intermolecular interactions governing high-concentration solution behavior, thereby enabling rational antibody engineering and improved developability.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Image-Based Fracture Surface Defect Characterization Methods for Additively Manufactured Ti-6Al-4V Tested in Fatigue

Abstract Fatigue initiation in additively manufactured samples/parts often occurs at processed-induced defects such as lack-of-fusion (LoF), keyhole, or other morphological/microstructural defects that have unique characteristics and measurable qualities. Attempts at identifying and minimizing such defects have utilized optimized processing conditions along with in situ and ex situ characterization that includes metallography and/or X-ray computed tomography (XCT). This paper highlights the benefits of using fracture surface analyses to detect and quantify defects that may not be detected by metallography/XCT due to sectioning and resolution limits. In addition to using manual quantification of fatigue initiating LoF and keyhole defects on fracture surfaces, image-based machine learning using convolutional neural networks such as U-Net were also used to automate the process. Statistical analyses were used to identify the extreme cases of defects that initiated and accelerated fatigue and to model the distribution of defect size and shape characteristics to distinguish the type of defect. Initial results show agreement between trained machine learning models and ground truth data in defect segmentation, and the distributions of defect characteristics are distinguishable to particular process-induced defect types.

Materials Science↗

DOE OSTI2024

Bench-Scale Development of a Novel Direct Air Capture Technology Using High-Capacity Structured Sorbents

The work performed under this project has resulted into development of a DAC technology utilizing a structured sorbent to capture CO 2 from ambient air with a key innovation of direct Joule heating of the sorbent for CO 2 desorption. A working SMA, fully integrated with an electrically resistive heating layer, high surface area support, and high CO 2 capacity sorbent coated onto a commercial ceramic monolithic substrate, was successfully developed and demonstrated over >200 adsorption-desorption cycles in a high-fidelity bench test unit directly using ambient air. A cordierite-based monolith was selected as a substrate owing to its high surface area, low bulk density, low heat capacity, and commercial availability. Reaction kinetics study conducted during this project led to development of a promoter for the base Na 2 CO 3 sorbent that could be incorporated into the sorbent to enhance to achieve higher CO 2 adsorption/desorption rates, greater working capacity, and reduced regeneration temperature. An accelerated aging study was conducted in a TGA to determine sorbent stability and no degradation in the sorbent performance was observed even after 250 adsorption-desorption cycles. An electrically resistive heating layer was developed with tunable electrical properties. The heating layer was coated onto the selected cordierite substrate. Aging studies performed showed the electrical properties and heating performance was stable after 500 heating and cooling cycles. The collective findings on the selected cordierite substrate, robust heating layer, promoter and sorbent selection were used to synthesize a full, 6”x6” SMA for bench-scale testing. The bench-scale DAC system was constructed to test full size SMAs using real ambient air for adsorption and joule heating for regeneration. After completing shakedown and commissioning of the 1 kg/day of CO 2 capacity DAC bench unit, an extended operation was performed to complete over 230 cycles with the full size SMA. This testing showed no observable degradation in sorbent performance. A detailed process model, TEA and LCA were developed for a conceptual 100,000 TPY CO 2 removal DAC facility. The LCA results show the net CO 2 e emissions from the DAC system are highly dependent on the electricity source. All other factors, including SMA manufacturing, materials for facility enclosure, etc., are minor cost contributors compared to the energy consumption required for CO 2 removal. With the successful development and validation of the SMA for the sustained performance for CO 2 removal from ambient air with joule heated regeneration in this project, a fully integrated 1 TPY bench-scale DAC system is currently in development with the support of DOE/FECM (DE-FE0032243). The project objective is to demonstrate the engineering design of the DAC system to produce a continuous, high purity CO 2 stream from ambient air. This project will address and validate key engineering features of the DAC system including the gas sealing mechanism and panels, enclosure and air contactor design, and automation sequence to achieve continuous CO 2 production.

42 ENGINEERING↗

DOE OSTI2024

In situ Synchrotron X‐ray Metrology Boosted by Automated Data Analysis for Real‐time Monitoring of Cathode Calcination

Abstract Synchrotron X‐ray‐based in situ metrology is advantageous for monitoring the synthesis of battery materials, offering high throughput, high spatial and temporal resolution, and chemical sensitivity. However, the rapid generation of massive data poses a challenge to on‐site, on‐the‐fly analysis needed for real‐time process monitoring. Here, a weighted lagged cross‐correlation (WLCC) similarity approach is presented for automated data analysis, which merges with in situ synchrotron X‐ray diffraction metrology to monitor the calcination process of the archetypal nickel‐based cathode, LiNiO 2 . The WLCC approach, incorporating variables that account for peak shifts and width changes associated with structural transformations, enables rapid extraction of phase progression within 10 seconds from tens of diffraction patterns. Details are captured, from initial precursors to intermediates and the final layered LiNiO 2 , providing information for agile on‐site adjustments during experiments and complementing post hoc diffraction analysis by offering insights into early‐stage phase nucleation and growth. Expanding this data‐powered platform paves the way for real time calcination process monitoring and control, which is pivotal to quality control in battery cathode manufacturing.

36 MATERIALS SCIENCE↗

NASA NTRS1998

A Status of the Advanced Space Transportation Program from Planning to Action

A Technology Plan for Enabling Commercial Space Business was presented at the 48th International Astronautical Congress in Turin, Italy. This paper presents a status of the program's accomplishments. Technology demonstrations have progressed in each of the four elements of the program; (1) Low Cost Technology, (2) Advanced Reusable Technology, (3) Space Transfer Technology and (4) Space Transportation Research. The Low Cost Technology program element is primarily focused at reducing development and acquisition costs of aerospace hardware using a "design to cost" philosophy with robust margins, adapting commercial manufacturing processes and commercial off-the-shelf hardware. The attributes of this philosophy for small payload launch are being demonstrated at the component, sub-system, and system level. The X-34 "Fastrac" engine has progressed through major component and subsystem demonstrations. A propulsion system test bed has been implemented for system-level demonstration of component and subsystem technologies; including propellant tankage and feedlines, controls, pressurization, and engine systems. Low cost turbopump designs, commercial valves and a controller are demonstrating the potential for a ten-fold reduction in engine and propulsion system costs. The Advanced Reusable Technology program element is focused on increasing life through high strength-to-weight structures and propulsion components, highly integrated propellant tanks, automated checkout and health management and increased propulsion system performance. The validation of rocket based combined cycle (RBCC) propulsion is pro,-,ressing through component and subsystem testing. RBCC propulsion has the potential to provide performance margin over an all rocket system that could result in lower gross liftoff weight, a lower propellant mass fraction or a higher payload mass fraction. The Space Transfer Technology element of the program is pursuing technology that can improve performance and dramatically reduce the propellant and structural mass of orbit transfer and deep space systems. Flight demonstration of ion propulsion is progressing towards launch. Ion propulsion is the primary propulsion for Deep Space 1; a flyby of comet West-kohoutek-lkemura and asteroid 3352 McAuliffe. Testing of critical solar-thermal propulsion subsystems have been accomplished and planning is continuing for the flight demonstration of an electrodynamic tether orbit transfer system. The forth and final element of the program, Space Transportation Research, has progressed in several areas of propulsion research. This element of the program is focused at long-term (25 years) breakthrough concepts that could bring launch costs to a factor of one hundred below today's cost or dramatically expand planetary travel and enable interstellar travel.

Lyles, Garry↗

DOE OSTI2026

Superionic conduction in solid polymer electrolytes – decoupling ion transport from segmental relaxation

Solvent-free, solid polymer electrolytes (SPEs) are promising candidates for next-generation, electrochemical energy storage systems due to their potential to enhance safety and performance, enable flexible device architectures, and streamline manufacturing processes. Conventional SPEs suffer from limited ionic conductivity due to the strong coupling between ion transport and (generally slow) polymer segmental relaxation. The realization of superionic conduction in SPEs, in which ions move faster than the structural relaxation of the polymers, requires a shift in design principles to promote this type of decoupled ion motion. In this perspective, we discuss how polymer architecture, ion–ion correlations, and ion–polymer interactions can unlock superionic behavior. We highlight several key design features, such as crystallinity, bulky side groups, high molecular weight, and percolating ionic aggregation, with a focus on creating low-barrier transport pathways in various polymer systems. We also demonstrate opportunities to combine polymer chemistry and data science through high-throughput and automated screening approaches to reveal how phase behavior, ion dynamics, and ionic interactions govern transport, thereby potentially enabling data-driven discovery of superionic polymer electrolyte materials.

Yang, Mengying [Univ. of Delaware, Newark, DE (Uni↗

NASA NTRSDate not supplied

Open-source Numerical Modeling of Solidification Cracking Susceptibility: Application to Refractory Alloy Systems

Introduction. Alloys such as aluminum, nickel-base, and austenitic stainless steels are susceptible to solidification cracking during welding and 3D printing. Compositional optimization is one method used to effectively mitigate solidification cracking of those alloy systems. With the surge in hypersonic and in-space propulsion activities, refractory metals (Nb, Mo, Ta, W, and Re) and their alloy derivatives are increasing in importance due to their extreme high melting point and retention of high-temperature strength; however, their chemistry was most typically optimized to promote ductility during mechanical operations such as drawing and forming. Welding of such alloys has been a challenge due to a number of issues including solidification cracking, atmospheric contamination (O, C, and N), as well as a shift in ductile-to-brittle transition to higher temperature following grain growth induced by welding. Compositional optimization of refractory alloys for solidification cracking resistance in particular is desirable as their usage increases with the advent of advanced manufacturing methods such as 3D printing. This work evaluates the effect of compositional variation in refractory metal systems on the solidification cracking susceptibility with the goals of optimizing existing alloys and joining process techniques, and formulating new alloys with increased solidification cracking resistance. Experimental Procedures. A python code was developed in a Jupyter notebook environment (Michael and Sowards, 2023) to facilitate the calculation of crack susceptibility index proposed by Kou (2015). Composition is entered as a single point, or as a 1-D or 2-D array. The notebook calls pycalphad (Otis and Liu, 2017 and Bocklund et al, 2020) to calculate the evolution of fraction solid as a function of temperature (under either Scheil or equilibrium assumptions) and then evaluates steepness of the fraction solid curve near the terminal stage of solidification to predict solidification cracking resistance. Open source thermodynamic databases available at online repositories are used (van de Walle). The process is setup in an automated fashion to generate plots that show variation in solidification cracking susceptibility according to composition on 1-D line plots or 2-D contour plots. The Jupyter notebook and crack susceptibility algorithm was also integrated with a widely used commercial CALPHAD code for validation and alloy exploration. Results and Discussion. The crack susceptibility model was first validated against a series of refractory alloy compositions evaluated in past work which utilized a specialized Varestraint test built inside a vacuum chamber environment (Lessman and Gold, 1971). The alloys tested in the Varestraint apparatus included T-111 (Ta-8W-2Hf), ASTAR-811C (Ta-8W-1Re-0.7Hf-0.025C), FS-85 (Nb-27Ta-10W-1Zr), T-222 (Ta-9.6W-2.4Hf-0.01C), Ta-10W, B-66 (Nb-5Mo-5V-1Zr), and SCb-291 (Nb-10W-10Ta). The initial test of the model showed a strong correlation with empirical Varestraint data, i.e., a Spearman rank correlation between model predictions and hot cracking measurements was observed to be greater than 0.8. Following the validation, a set of refractory metal binary mixtures was investigated to evaluate sensitivity of Nb, Mo, W, and Ta to C, N, and O content. A series of plots were produced that suggest ppmw ranges of C, N, and O where solidification cracking increases significantly and reaches a maximum. Also comparative ranking of each primary refractory metal to each interstitial was produced. For example C produces greater cracking response in Mo whereas O produces greater cracking response in Ta and Nb. Such compositional values have utility in setting limits on pickup of these interstitial elements during welding and printing rather than using a one-size-fits-all approach. Furthermore, the results have use in determining additive powder recycling requirements, which is especially pertinent for refractory metal powders due to their high cost compared to conventional alloys. Another application created thousands of hypothetical alloys within the nominal specified composition range of two widely used refractory alloys C103 (Nb-10Hf-1Ti) and TZM (Mo-0.5Ti-0.1Zr). The cracking index was calculated for the alloys and results were fed into machine learning regression techniques including Multiple Linear Regression, Ridge Regression, and Lasso Regression to determine relative potency each alloying element had on computed solidification cracking index. A series of linear equations were produced that relate composition of C103 and TZM to solidification cracking index. The crack susceptibility of C103 for example is described by an equation of the form: cracking index ~ O + 0.667*C + 0.635*N + 0.00037*Ta – 0.0008*Hf (in wt.%) From that equation, it is clear that O has strong propensity to induce solidification cracking. Interestingly, Hf is shown to reduce calculated cracking response. Finally, realizing the potential of this method to discover new refractory alloy formulations across the period table that have low solidification cracking sensitivity, the code was applied to new untested alloy systems including W-Zr-C, W-Ta-C, and others. Conclusions. In summary, an open source numerical method has been developed using Python code to calculate Kou’s crack susceptibility index. The method was applied to refractory metals which are inherently difficult to study from a weldability testing standpoint since inert shielding gas is not sufficient and welding is typically done in vacuum, especially in light of findings presented here where oxygen has profound influence on solidification cracking. This work revealed the effect of compositional variations on a series of refractory metals and showed the framework defined here will be useful in 1) the development of new alloys that have improved weldability and 3D printability, 2) placing compositional limits on existing alloys, and 3) ensuring adequate controls of manufacturing processes such as 3D printing where powder reuse is critical. Keywords. pycalphad; Python; refractory metals; solidification cracking. References. B. Bocklund et. al. (2020) http://doi.org/10.5281/zenodo.3630657. S. Kou. (2015) https://doi.org/10.1016/j.actamat.2015.01.034. G.G. Lessmann and R.E. Gold. Welding Journal, issue 1, pp. 1-s – 8-s (1971). F.N. Michael and J.W. Sowards. NASA/TM-20230002218 (2023). R. Otis and Z.-K. Liu. (2017) http://doi.org/10.5334/jors.140. A. Van de Wallle et. al. (2018) https://doi.org/10.1016/j.calphad.2018.04.003.

pycalphad↗

NASA NTRS2012

Alabama Disasters: Leveraging NASA EOS to Explore the Environmental and Economic Impact of the April 27 Tornado Outbreak

The disastrous tornado outbreak in Alabama on April 27, 2011 greatly impacted the economy of the state. On record, the tornado outbreak was the second deadliest tornado outbreak in U.S. When considering the agricultural and value-added activities such as food and timber processing, farm inputs, manufacturing, transportation, and retail sales, the dollar value of Alabama agribusiness annually exceeds $40 billion (NASS, 2011). This research aims to examine how the timber and agriculture damage affected the state economy of Alabama and will be used to aid in long-term economic recovery. ASTER imagery was used along with ground-truthed NASS (National Agriculture Statistics Service) crop location records to verify the economic impact tornadoes had on the agricultural economy of the state. This swath damage can be calculated by correlating tornado path with NASS statistics on crop yield, precisely showing the fields affected and dollars lost to this disaster. Not only can this be executed manually using ENVI and ArcGIS, but also through the use of Python, a programming language that has the ability to automate the process, creating a product for initial damage assessment.

Herdy, Claire↗

NASA NTRS2012

Alabama Disasters: Leveraging NASA EOS to Explore the Environmental and Economic Impact of the April 27 Tornado Outbreak

Herdy, Claire↗

NASA NTRS2016

High Precision Sunphotometer using Wide Dynamic Range (WDR) Camera Tracking

The NASA Ames Sun-photometer-Satellite Group, DOE, PNNL Atmospheric Sciences and Global Change Division, and NASA Goddards AERONET (AErosol RObotic NETwork) team recently collaborated on the development of a new airborne sunphotometry instrument that provides information on gases and aerosols extending far beyond what can be derived from discrete-channel direct-beam measurements, while preserving or enhancing many of the desirable AATS features (e.g., compactness, versatility, automation, reliability). The enhanced instrument combines the sun-tracking ability of the current 14-Channel NASA Ames AATS-14 with the sky-scanning ability of the ground-based AERONET Sunsky photometers, while extending both AATS-14 and AERONET capabilities by providing full spectral information from the UV (350 nm) to the SWIR (1,700 nm). Strengths of this measurement approach include many more wavelengths (isolated from gas absorption features) that may be used to characterize aerosols and detailed (oversampled) measurements of the absorption features of specific gas constituents. The Sky Scanning Sun Tracking Airborne Radiometer (3STAR) replicates the radiometer functionality of the AATS14 instrument but incorporates modern COTS technologies for all instruments subsystems. A 19-channel radiometer bundle design is borrowed from a commercial water column radiance instrument manufactured by Biospherical Instruments of San Diego California (ref, Morrow and Hooker)) and developed using NASA funds under the Small Business Innovative Research (SBIR) program. The 3STAR design also incorporates the latest in robotic motor technology embodied in Rotary actuators from Oriental motor Corp. having better than 15 arc seconds of positioning accuracy. Control system was designed, tested and simulated using a Hybrid-Dynamical modeling methodology. The design also replaces the classic quadrant detector tracking sensor with a wide dynamic range camera that provides a high precision solar position tracking signal as well as an image of the sky in the 45 field of view around the solar axis, which can be of great assistance in flagging data for cloud effects or other factors that might impact data quality.

aerosols↗

NASA NTRSDate not supplied

Design and Applications of Tethered Spacecraft Simulators

Small, tethered spacecraft, or space tugs, are a promising space capability. They can be deployed on tethers and used for a wide variety of in-space activities; a large portion of which fall under in-space servicing, assembly, manufacturing (ISAM) functions. This includes functions such as structural mating and assembly, servicing, proximity operations, capture, docking, mating, and relocation. However, there is a great deal of work to be done to raise the Technology Readiness Level (TRL) of the capabilities needed to fully realize these capabilities. The Flat Floor Robotics Lab (FFRL) at NASA’s Marshall Spaceflight Center (MSFC) has been working on space tug development for several years. The eponymous floor is 44 by 86 feet, made from a self-leveling epoxy. This creates an extremely smooth surface that air bearings can float on with very little friction, creating a simulation of zero gravity in a two-dimensional plane. The lab has several platforms of various sizes that act as vehicle simulators for testing sensors, control algorithms, mechanisms, etc. One of these platforms is a small spacecraft simulator, which can be tethered to simulate a space tug. In the last several months, the FFRL team has been working with MSFC’s welding group to conduct a laser beam welding demonstration on air bearing platforms. This demo is utilizing a space tug simulator to fly up to a floating weld platform, where two parts are clamped together and laser welded. The space tug simulator has an air bearing to provide float, as well as several actuated air thrusters to provide propulsion and make the simulator maneuverable. Currently, flights of this simulator are completed by a human operator. An RF hand controller sends signals to both actuate and fire three sets of thrusters on the simulator. This makes any maneuvers of the space tug highly subject to human error, and operators must have dedicated practice time before being able to perform maneuvers with any sufficient reliability. For the current laser welding demonstration, human operated performance is sufficient, but future implementations of in-space welding and other ISAM efforts will require higher precision, reliability, and autonomy. MSFC has funded a project that will allow a small team in the FFRL to develop the next generation of space tug simulator, which will be automated. Closed loop control will allow a user to command a position, or set of positions, that the simulator will be able to “fly” to on its own. This Maneuverable Automated Tethered Spacecraft (MATS) simulator will have configurable design, to allow a variety of payloads and mission configurations to be demonstrated on the air bearing floor. This will be an invaluable test bed for low and mid TRL advancement for space tether mission subsystems, such as more advanced demonstrations of in-space welding. Once one MATSS is constructed and demonstrated effectively, several more can be built, enabling more advanced tether missions; Electric Sail test beds, sensor arrays, and other science-enabling missions. This paper will detail the design and test of the FFRL’s MATS simulator, including efforts to establish closed loop control and autonomous capabilities. It will also detail use cases for this technology, and how it will further develop both develop science and exploration missions.

Space Tethers↗

NASA NTRS2006

Deep Space Network, Cryogenic HEMT LNAs

Exploration of the Solar System with automated spacecraft that are more than ten astronomical units (1 AU = 149,597,870.691 km) from earth requires very large antennae employing extremely sensitive receivers. A key figure of merit in the specification of the spacecraft-to-earth telecommunications link is the ratio of the antenna gain to operatio nal noise temperature (G/Top) of the system. The Deep Space Network (DSN) receivers are cryogenic, low-noise amplifiers (LNAs) which addres s the need to maintain Top as low as technology permits. Historicall y, the extra-ordinarily sensitive receive systems operated by the DSN have required ctyogenically cooled, ruby masers, operating at a physi cal temperature near the boiling point of helium, as the LNA. Althoug h masers continue to be used today, they are hand crafted at JPL and expensive to manufacture and maintain. Recent advances in the developm ent of indium phosphide (InP) based high electron mobility transistor s (HEMTs) combined with cryogenic cooling near the boiling point of h ydrogen have made this alternate technology comparable with and a fraction of the cost of maser technology. InP HEMT LNA modules are demons trating noise temperatures less than ten times the quantum noise limi t (10hf/k) from 1 to 100 GHz. To date, the lowest noise LNA modules developed for the DSN have demonstrated noise temperatures of 3.5 K and 8.5 K at 8.5 K at 32 GHz, respectively. Front-end receiver packages employing these modules have demonstrated operating system noise temperatures of 17 K at 8.4 GHz (on a 70m antenna at zenith) and 39 K at 3 2 GHz (on a 34m antenna at zenith). The development and demonstration of cryogenic, InP HEMT based front-end amplifiers for the DSN requir es accurate component and module characterization, and modeling from 1 to 100 GHz at physical temperatures down to 12 K. The characterizati on and modeling begins with the HEMT chip, proceeds to the multi-stag e HEMT LNA module, and culminates with the complete front-end cryogenic receiver package for the antenna. This presentation will provide a n overview of this development process. Examples will be shown for de vices, LNA modules, front-end receiver packages, antennae employing these packages and the improvements to the down-link capacity.

low-noise amplifiers (LNAs)↗

DOE OSTI2020

DEEP CELLULAR RECURRENT NEURAL ARCHITECTURE FOR EFFICIENT MULTIDIMENSIONAL TIME-SERIES DATA PROCESSING

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in complexity and size to accommodate the additional dimensionality of time. Specifically, the biologically inspired learning based models known as artificial neural networks that have shown extraordinary success in pattern recognition, tend to grow prohibitively large and cumbersome in the presence of large scale multi-dimensional time series biomedical data such as EEG. Consequently, this work aims to develop representative ML and DL models for robust and efficient large scale time series processing. First, we design a novel ML pipeline with efficient feature engineering to process a large scale multi-channel scalp EEG dataset for automated detection of epileptic seizures. With the use of a sophisticated yet computationally efficient time-frequency analysis technique known as harmonic wavelet packet transform and an efficient self-similarity computation based on fractal dimension, we achieve state-of-the-art performance for automated seizure detection in EEG data. Subsequently, we investigate the development of a novel efficient deep recurrent learning model for large scale time series processing. For this, we first study the functionality and training of a biologically inspired neural network architecture known as cellular simultaneous recurrent neural network (CSRN). We obtain a generalization of this network for multiple topological image processing tasks and investigate the learning efficacy of the complex cellular architecture using several state-of-the?art training methods. Finally, we develop a novel deep cellular recurrent neural network (CDRNN) architecture based on the biologically inspired distributed processing used in CSRN for processing time series data. The proposed DCRNN leverages the cellular recurrent architecture to promote extensive weight sharing and efficient, individualized, synchronous processing of multi-source time series data. Experiments on a large scale multi-channel scalp EEG, and a machine fault detection dataset show that the proposed DCRNN offers state-of-the-art recognition performance while using substantially fewer trainable recurrent units.

Vidyaratne, Lasitha S.↗