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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2009

Determining Surface Roughness in Urban Areas Using Lidar Data

An automated procedure has been developed to derive relevant factors, which can increase the ability to produce objective, repeatable methods for determining aerodynamic surface roughness. Aerodynamic surface roughness is used for many applications, like atmospheric dispersive models and wind-damage models. For this technique, existing lidar data was used that was originally collected for terrain analysis, and demonstrated that surface roughness values can be automatically derived, and then subsequently utilized in disaster-management and homeland security models. The developed lidar-processing algorithm effectively distinguishes buildings from trees and characterizes their size, density, orientation, and spacing (see figure); all of these variables are parameters that are required to calculate the estimated surface roughness for a specified area. By using this algorithm, aerodynamic surface roughness values in urban areas can then be extracted automatically. The user can also adjust the algorithm for local conditions and lidar characteristics, like summer/winter vegetation and dense/sparse lidar point spacing. Additionally, the user can also survey variations in surface roughness that occurs due to wind direction; for example, during a hurricane, when wind direction can change dramatically, this variable can be extremely significant. In its current state, the algorithm calculates an estimated surface roughness for a square kilometer area; techniques using the lidar data to calculate the surface roughness for a point, whereby only roughness elements that are upstream from the point of interest are used and the wind direction is a vital concern, are being investigated. This technological advancement will improve the reliability and accuracy of models that use and incorporate surface roughness.

Holland, Donald↗
DOE OSTI2023

Building Environmental Justice and Equity into the Development of Critical Mineral Industries

The global transition toward low-carbon energy not only means an increase in demand for clean electricity and renewable resources, but also an increase in demand for the critical minerals (CMs) and rare earth elements (REEs) that these technologies rely upon. Indeed, low-carbon energy technologies, such as those used for wind turbines and electric vehicle motors, require significantly more lithium, nickel, cobalt, manganese, graphite, and other CMs than fossil-based energy technologies. The growing demand for new forms of low- carbon energy will necessitate a proportional scale-up of CM and REE extraction and processing. Presently, the majority of extraction and processing activities for CMs and REEs are concentrated in very few countries, primarily in China and the Global South. CM and REE supply chain activities conducted in or controlled by these countries are commonly associated with widespread and well- documented human rights abuses and environmental degradation. As a result of concerns related to supply chain security, worker welfare, and the overall need for additional sources of CMs and REEs, governments worldwide have begun to explore policy pathways for the development of new supply chains. The development of new supply chains for CMs and REEs re s a multifold opportunity to accelerate the global deployment of low-carbon energy fleets, reduce global carbon emissions, build political resilience—and also to enhance policy objectives of environmental justice and equity in the clean energy transition. Fulfilling these policy objectives requires energy producers to navigate a maze of global supply chain policies designed to shape and accelerate the growth of new markets. In the United States, for instance, President Biden recently implemented fiscal and trade policies that incentivize both domestic and global reliance on U.S.-produced CMs and REEs, leveraging key relationships in Asia and Europe to ensure the accelerated buildout of the U.S. supply chain. The Biden Administration’s framework also emphasizes that new supply chains for CMs, REEs, and other low-carbon energy pathways must generate benefits for marginalized and disadvantaged communities, build energy equity, and contribute to the Biden Administration’s vision of environmental justice. present CM and REE supply chains include several stages, including mining, processing, transport, utilization, and disposal, each of which involves different environmental justice considerations and potential injustices. This study explores how technical innovation, paired with responsible community engagement and empowerment, can help inform the development of energy equity and environmental justice at all stages of new supply chains. The study highlights these opportunities on a broad scale. We also lend a specific focus to research at the University of Wyoming School of Energy Resources that aims to guide the development of CM and REE industries in communities with high economic dependence on coal and other fossil fuel industries, identifying pathways to grow a U.S. domestic supply chain by producing CMs from coal, coal by-products, and coal waste streams. These production pathways represent a potential new supply for CMs across the U.S. and elsewhere, thereby enhancing national security and accelerating the widespread deployment of low-carbon energy technologies, while also generating alternative applications for remaining coal reserves and aiding in a just transition for rural energy-producing communities.

Gerace, Selena↗
NASA NTRS2020

Research Report: Building a Wide Reach Corpus for Secure Parser Development

Whether developing from a specification or deriving parsers from samples, LangSec parser developers require widereach corpora of their target file format in order to identify key edge cases or common deviations from the format’s specification. In this work-in-progress paper, we report the details of several methods we’ve used to gather 30 million files, extract features and make these features amenable to search and other analytics. This paper documents opportunities and limitations of some popular open source data and tools and this paper will benefit researchers who need to efficiently gather a large file corpus.

Timmaraju, Virisha↗
DOE OSTI2023

Deep learning of electrochemical CO 2 conversion literature reveals research trends and directions

Large-scale and openly available material science databases are mainly composed of computer simulation results rather than experimental data. Some examples include the Materials Project, Open Quantum Materials Database, and Open Catalyst 2022. Unfortunately, building large-scale experimental databases remains challenging due to the difficulties in consolidating locally distributed datasets. In this work, focusing on the catalysis literature of CO 2 reduction reactions (CO 2 RRs), we present a machine learning (ML)-based protocol for selecting highly relevant papers and extracting important experimental data. First, we report a document embedding method (Doc2Vec) for collecting papers of greatest relevance to the specific target domain, which yielded 3154 CO 2 RR-related papers from six publishers. Next, we developed named entity recognition (NER) models to extract twelve entities related to material names (catalyst, electrolyte, etc.) and catalytic performance (Faradaic efficiency, current density, etc.). Further, among several tested models, the MatBERT-based approach achieved the highest accuracy, with an average F1-score of 90.4% and an F1-score of 95.2% in a boundary relaxation evaluation scheme. The accurate and accelerated NER-based data extraction from a large volume of catalysis literature enables temporal trend analyses of the CO 2 RR catalysts, products, and performances, revealing the potentially effective material space in CO 2 RRs. While this work demonstrates the effectiveness of our ML-based text mining methods for specifically CO 2 RR literature, the methods and approach are applicable to and may be used to accelerate the development of other catalytic chemical reactions.

36 MATERIALS SCIENCE↗
NASA NTRS2014

Robonaut 2 - IVA Experiments On-Board ISS and Development Towards EVA Capability

Robonaut 2 (R2) has completed its fixed base activities on-board the ISS and is scheduled to receive its climbing legs in early 2014. In its continuing line of firsts, the R2 torso finished up its on-orbit activities on its stanchion with the manipulation of space blanket materials and performed multiple tasks under teleoperation control by IVA astronauts. The successful completion of these two IVA experiments is a key step in Robonaut's progression towards an EVA capability. Integration with the legs and climbing inside the ISS will provide another important part of the experience that R2 will need prior to performing tasks on the outside of ISS. In support of these on-orbit activities, R2 has been traversing across handrails in simulated zero-g environments and working with EVA tools and equipment on the ground to determine manipulation strategies for an EVA Robonaut. R2 made significant advances in robotic manipulation of deformable materials in space while working with its softgoods task panel. This panel features quarter turn latches that secure a space blanket to the task panel structure. The space blanket covers two cloth cubes that are attached with Velcro to the structure. R2 was able to open and close the latches, pull back the blanket, and remove the cube underneath. R2 simulated cleaning up an EVA worksite as well, by replacing the cube and reattaching the blanket. In order to interact with the softgoods panel, R2 has both autonomously and with a human in the loop identified and localized these deformable objects. Using stereo color cameras, R2 identified characteristic elements on the softgoods panel then extracted the location and orientation of the object in its field of view using stereo disparity and kinematic transforms. R2 used both vision processing and supervisory control to successfully accomplish this important task. Teleoperation is a key capability for Robonaut's effectiveness as an EVA system. To build proficiency, crewmembers have attempted increasingly difficult tasks using R2 inside the Station. After donning motion capture equipment and a virtual reality visor, Expedition 34/35 flight engineer Tom Marshburn began operations with simple hand movements. Having gained confidence, Marshburn guided R2's arms in a leader-follower exercise with crewmate Chris Cassidy. He was also able to use the hand to grab a tumbling roll of tape, a task only demonstrable in microgravity. Later efforts saw Cassidy handle softgoods through shared control with ground operators, mimicking an activity previously achieved using only autonomy. Robotic climbing through the ISS on handrails requires both precision motion and compliant grasps in order to both position grippers on handrails/seat track and prevent large internal forces. R2 climbs using actively controlled compliance and torque limiting to meet both the precision and softness requirements. During a step, the attached leg is controlled to be strong and stiff in order to maintain precision trajectory tracking. The swing leg is controlled to be stiff but weak to minimize unintentional impact forces while maintaining precision. During a simulated dual limb grasp (as shown in Figure 1), the R2 controller maintains one limb rigid and one limb soft to prevent large internal forces from building up. R2's grippers also use a form of force control to limit grip force while not fully closed on either a handrail or seat track thus limiting unintentional forces on cables/objects that may be present in R2's translational path. The on-board torso R2 safety system relies on a single end-effector velocity limit to prevent potential impact forces from exceeding Station maximum load requirements. R2's mobile configuration required modifications to the velocity limiting safety function due to its large, dynamic inertia. R2's legs maneuver the robot's mass creating configuration dependent, joint-relative inertias. A single all-encompassing velocity limit to cover worst case inertia is prohibitively low. The upgraded R2 control and safety systems solve this problem using momentum limiting, momentum control, and kinetic energy minimization. Momentum and kinetic energy take the robot mass into account relieving low velocity restrictions on low inertia end-effectors while ensuring that the overall mass of R2 is limited from hazardous velocities. The momentum of R2's five safety nodes (each of the four end-effectors and the body) is monitored and compared to a single momentum limit. If any of the five nodes exceeds the safety limit, the motor power is removed and the robot comes to a stop. Momentum control/limiting also provides a simple, reliable method to integrate hand held tools into the safety system by providing the tool mass to the control system thus automatically reducing the allowable velocity of the end-effector with the tool. Work on the ground continues to build the skill set for an EVA Robonaut. Recent experiments (Figure 2) demonstrate how a teleoperator can use R2 to manipulate a tether hook, an important safety precaution on spacewalks. Another task displayed Robonaut's ability to pull back a protective jacket over a hose and search for damage, as well as inspect a quick-disconnect fitting for debris. Demonstrations such as these are indicative of EVA work done on ISS, specifically seen during a series of spacewalks over 2012 and 2013 where astronauts searched for an ammonia leak in one of the external cooling loops. Through experiments both on ISS and on the ground, R2 is evolving and providing the information needed to plan out the upgrades that will make an EVA Robonaut an effective tool. With the addition of legs, R2 will start climbing inside the space station and supply invaluable information on how the climbing strategies and task stabilization techniques must be refined. Ground R2 systems will continue to work with additional EVA tools and equipment in preparation for onboard IVA testing and future EVA applications.

Diftler, Myron↗
NASA NTRS2022

Environmental Testing of the OVEN System for Lunar Water Extraction and Prospecting

Introduction: The presence of water ice in permanently shadowed regions on the lunar surface [1] may enable a sustained human presence on the Moon with minimal need for consumables. However, in order to develop a long term utilization plan that includes the usage of in-situ water we must first understand the abundance, stratigraphy and distribution of this re-source. Multiple space agencies currently have plans for lunar water prospecting missions. The Optimized Volatile Extraction Node (OVEN) was designed for water prospecting missions that require samples to be weighed, sealed, and heated as the means of determining water concentration. This method of water quantification necessitates a fair amount of automation, so a rigorous environmental test program was performed in order to build confidence in the performance of the OVEN design. The work presented here describes the OVEN environmental test program as well as ongoing efforts to improve on the design. Vibration: The OVEN participated in two rounds of random vibration tests. The first test was a stand-alone test performed at the Energy Systems Test Area of the Johnson Space Center. The second test was an integrated test with the mobile platform developed for the Resource Prospector project. The OVEN survived both tests without damage, but the tests did provide valuable lessons learned with regards to specific operations. Thermal Vacuum: The OVEN was successfully demonstrated at a temperature range of -50 to 75 C in a thermal vacuum chamber. The need to heat motor gearboxes at lower temperatures was predetermined so this test program was completed by implementing a method of gearbox heating that used the existing circuitry within the motors. Dust: A custom dynamometer was built in order to determine the torque required to move the various mechanisms within the OVEN at a range of temperatures. The OVEN system was coated with lunar dust simulant in order to determine mechanism torques under a worst-case operating condition. Sublimation: Sublimation losses within the OVEN were quantified through a series of test configurations, including an integrated test in a thermal vacuum chamber at Glenn Research Center [2]. Current Work: The OVEN subsystem is currently not a component of any existing prospecting missions, but work continues that will take the lessons learned from previous environmental tests and improve on the design in order to be considered for future prospecting opportunities. References: [1] Colaprete, A., Schultz, P., Heldmann, J., Wooden, D., Shirley, M., Ennico, K., ... & Sollitt, L. (2010). Detection of water in the LCROSS ejecta plume. science, 330(6003), 463-468. [2] Kleinhenz, J., Smith, J., Roush, T., Colaprete, A., Zacny, K., Paulsen, G., ... & Paz, A. (2018). Volatiles Loss from water bearing regolith simulant at Lunar Environments. In Earth and Space 2018: Engineering for Extreme Environments (pp. 454-466). Reston, VA: American Society of Civil Engineers.

A Paz↗
NASA NTRSDate not supplied

Gaseous By-Product of Thermal Vacuum Processing of Lunar Highland Simulant

Scientists at Kennedy Space Center are advancing technologies to achieve oxygen extraction on the Lunar surface. One such technology is Molten Regolith Electrolysis (MRE) in which regolith simulant is melted under high temperatures to perform oxygen extraction through electrolysis of the melt pool. A study was conducted to understand the molten formation and proper-ties of Lunar Highlands Simulants (LHS-1) under high vacuum environments ranging between 10-6 Torr. These studies include investigating the regolith melt behavior and by-product gas analysis systems to prepare for pilot plant development and operations. The off-gassing rates and pressure build-up, gaseous compounds, and material compatibility may be a risk to MRE systems. The KSC findings are reported here for inclusion into future mis-sion architecture and operational planning. The four stages of the experiment were vacuum, resistive heating, regolith melt and gas detection. The regolith mass of 70 g was melted in a 40 cm tall x 50 cm diameter vacuum chamber at temperature increase rate 47 ℃ /min and ramp rate of 1 ampere/3 min up to an 18-amp maximum. The test is conducted for about 60 minutes and the constituent gases produced during heating of regolith is monitored with a re-sidual gas analyzer. During the molten formation, primary off-gassing volatiles included water vapor (18 amu), a peak at 44 amu (FeO2 – expected), and atomic oxygen (16 amu), among a series of other compounds that could create compatibility issues such as magnesium, chlorine, and silicon oxide. These results add to the knowledge required for successful oxygen extraction on the moon.

Molten Regolith Electrolysis↗
DOE OSTI2022

Turning Natural Herbaceous Fibers into Advanced Materials for Sustainability

Considering the growing concerns about natural resource depletion, energy inequality, and climate crises, biomass-derived materials—the most abundant organic matter on the planet—have received a lot of attention as a potential alternative to petroleum-based plastics. Herbaceous biomasses and extracted cellulose have recently been extensively used in the development of high-performance and multifunctional materials. Herbaceous biomass has sparked interest due to its species diversity, abundance, low cost, lightweight, and sustainability. This review discusses the structure versus property relationships of various sources of herbaceous biomasses (e.g., sugarcane, straw, and bamboo) and their extracted biomaterials, as well as the latest emerging applications from macro- and microscales to nanoscales. We report, high-strength structural materials, porous carbon materials, multichannel materials, and flexible materials are examples of these applications, which include sustainable electronics, environmentally friendly energy harvesting, smart materials, and biodegradable structural buildings.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Towards replacing physical testing of granular materials with a Topology-based Model

In the study of packed granular materials, the performance of a sample (e.g., the detonation of a high-energy explosive) often correlates to measurements of a fluid flowing through it. The “effective surface area,” the surface area accessible to the airflow, is typically measured using a permeametry apparatus that relates the flow conductance to the permeable surface area via the Carman-Kozeny equation. This equation allows calculating the flow rate of a fluid flowing through the granules packed in the sample for a given pressure drop. However, Carman-Kozeny makes inherent assumptions about tunnel shapes and flow paths that may not accurately hold in situations where the particles possess a wide distribution in shapes, sizes, and aspect ratios, as is true with many powdered systems of technological and commercial interest. To address this challenge, we replicate these measurements virtually on micro-CT images of the powdered material, introducing a new Pore Network Model based on the skeleton of the Morse-Smale complex. Pores are identified as basins of the complex, their incidence encodes adjacency, and the conductivity of the capillary between them is computed from the cross-section at their interface. We build and solve a resistive network to compute an approximate laminar fluid flow through the pore structure. Here, we provide two means of estimating flow-permeable surface area: (i) by direct computation of conductivity, and (ii) by identifying dead-ends in the flow coupled with isosurface extraction and the application of the Carman-Kozeny equation, with the aim of establishing consistency over a range of particle shapes, sizes, porosity levels, and void distribution patterns.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Understanding plasma turbulence through exact coherent structures

Plasma turbulence is a key challenge in understanding transport phenomena in magnetically confined plasmas. This work presents a generalized framework to analyze plasma turbulence that utilizes periodic orbit theory. In periodic orbit theory, doubly periodic solutions (coherent structures) of the governing equation(s) serve as building blocks of the considered turbulent dynamics. To illustrate the concept and method, the particularly simple Kuramoto–Sivashinsky (referred to here as LMRT for the original authors: LaQuey, Mahajan, Rutherford, and Tang) trapped-ion mode toy model is used. By applying numerical optimization techniques to the LMRT equation, we extract coherent spacetime patterns that represent the library of allowable fundamental structures of the equation. These structures provide a framework to systematically describe turbulence as a composition of recurrent solutions, revealing an underlying order within chaotic plasma motion. Although illustrated here using the simplified LMRT model for clarity, this framework provides a general strategy that can be extended to more complex and realistic models of plasma turbulence, including gyrokinetic systems. This offers a new method for predicting and potentially controlling transport processes in fusion plasmas by providing a bridge between nonlinear dynamical systems theory and plasma physics in the form of a generalized framework with which to analyze and understand spatially extended nonlinear partial differential equations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Towards a study protocol: A data-driven workflow to identify error sources in direct ink write mechatronics

Abstract Using Direct Ink Write (DIW) technology in a rapid and large-scale production requires reliable quality control for printed parts. Data streams generated during printing, such as print mechatronics, are massive and diverse which impedes extracting insights. In our study protocol approach, we developed a data-driven workflow to understand the behavior of sensor-measured X- and Y- axes positional errors with process parameters, such as print velocity and velocity control. We uncovered patterns showing that instantaneous changes in the velocity, when the build platform accelerates and decelerates, largely influence the positional errors, especially in the X- axis due to the hardware architecture. Since DIW systems share similar mechatronic inputs and outputs, our study protocol approach is broadly applicable and scalable across multiple systems. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2021

Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems

Engineering cellular metabolism for targeted biosynthesis can require extensive design-build-test-learn (DBTL) cycles as the engineer works around the cell's survival requirements. Alternatively, carrying out DBTL cycles in cell-free environments can accelerate this process and alleviate concerns with host compatibility. A promising approach to cell-free metabolic engineering (CFME) leverages metabolically active crude cell extracts as platforms for biomanufacturing and for rapidly discovering and prototyping modified proteins and pathways. Realizing these capabilities and optimizing CFME performance requires methods to characterize the metabolome of lysate-based cell-free platforms. That is, analytical tools are necessary for monitoring improvements in targeted metabolite conversions and in elucidating alterations to metabolite flux when manipulating lysate metabolism. In this work, metabolite analyses using high-performance liquid chromatography (HPLC) coupled with either optical or mass spectrometric detection were applied to characterize metabolite production and flux in E. coli S30 lysates. Specifically, this report describes the preparation of samples from CFME lysates for HPLC analyses using refractive index detection (RID) to quantify the generation of central metabolic intermediates and by-products in the conversion of low-cost substrates (i.e., glucose) to various high-value products. The analysis of metabolite conversion in CFME reactions fed with 13 C-labeled glucose through reversed-phase liquid chromatography coupled to tandem mass spectrometry (MS/MS), a powerful tool for characterizing specific metabolite yields and lysate metabolic flux from starting materials, is also presented. Altogether, applying these analytical methods to CFME lysate metabolism enables the advancement of these systems as alternative platforms for executing faster or novel metabolic engineering tasks.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2024

Interim Measures Pilot Study Completion Report, South Repeater Building, Solid Waste Management Unit 121, Hydraulic Containment and Groundwater Treatment System for Per- and Polyfluoroalkyl Substances

This Per- and Polyfluoroalkyl Substances (PFAS) Interim Measures Pilot Study Completion Report was prepared for the National Aeronautics and Space Administration by AECOM Technical Services, Inc. under Contract 80KSC019D0010, Task Order 80KSC021F0096. The purpose of this report is to document the pilot study activities at the South Repeater Building, Solid Waste Management Unit (SWMU) 121. This report details the additional assessment activities completed from June 2023 through November 2023 and the subsequent pilot study completed at the South Repeater Building conducted in December 2023 through February 2024. Initial activities were conducted in accordance with the Pilot Study Work Plan (NASA 2023), submitted to the KSC Remediation Team and accepted by the team on October 26, 2023. The objectives of the pilot study were to: • Provide information on aquifer characteristics and to aid in future modeling and remedial design activities to mitigate off-KSC migration of PFAS compounds. • Develop information on characteristics of the surficial aquifer system, specifically transmissivity, storage coefficient, hydraulic conductivity, and vertical hydraulic conductivity. • Obtain data to support construction and calibration of a groundwater flow model. • Acquire design parameters necessary for future remedial design activities, specifically radius of influence, drawdown, flow rates, and pump settings. The following activities were completed to meet the pilot study objectives: • Groundwater and surface water sampling • Geophysical investigation via Hydraulic Profiling Tool (HPT) and soil sampling • Installation of observation and extraction wells via rotosonic techniques • Slug, step, and pump testing activities • Initial modeling efforts for a groundwater hydraulic containment system. Results of the pilot study and modeling activities are being used in the development of a groundwater containment and treatment system for the site.

PFAS↗
DOE OSTI2026

Investigating shock-induced chemical reactions in Ni+Al multilayers: A continuum-based mesoscale approach with Arrhenius kinetics and artificial thermal conduction

A new continuum-based mesoscale modeling approach for shock-induced chemical reactions (SICRs) in Ni+Al multilayers is demonstrated in Sandia’s shock physics hydrocode, CTH. The approach utilizes Arrhenius-type kinetics and artificial thermal conduction. Our work builds upon previous efforts to parameterize equations of state for Ni x Al y [J. Appl. Phys. 137, 075102 (2025)], as well as simulations of inert shocks in realistic 2D microstructures [J. Appl. Phys. 137, 225301 (2025)]. To calibrate the reaction kinetics, pairs of the reaction coordinate, R′, vs time are extracted from the molecular dynamics (MD) literature. Here, the MD-informed kinetics are used to simulate the dynamic evolution of pressure and temperature in 2D mesoscale simulations. Overall, the MD-informed kinetics obtained for planar interfaces are too slow, as initial reaction is not observed on a nanosecond time scale. Even with quasi-periodic shock focusing leading to the formation of so-called “hot-spots,” the hot spots are unable to grow and coalesce using the fitted Arrhenius rate constants. However, by increasing the rate constants by two orders of magnitude, SICRs are observed at a shock pressure near 30 GPa, which is supported by experiments. Consequently, these mesoscale simulations suggest that unresolved shear-based mechanical mixing might possibly account for the discrepancies in kinetic rates, with shock-generated intense perturbations, interfacial vortical flows, and elevated temperatures serving as favorable reaction conditions. Future work will calibrate a shear-dependent reaction rate from the MD simulations with realistic interfaces that are wavy, diffuse, and disordered.

Kittell, David E. [Sandia National Laboratories (S↗
NASA NTRS2021

Dendroarchaeological Analysis of the Terminal Warehouse in New York City Reveals A History of Long-Distance Timber Transport During the Gilded Age

The Gilded Age of the late 19th century marked a period of rapid development and urbanization in New York City, U.S. To accommodate the high demand in wood products during that time, the timbers used for development of the city were increasingly sourced from locations distant from the northeastern United States. The Terminal Warehouse in the Chelsea neighborhood of New York City was one of many large buildings erected during this period of city expansion, and is an important symbol of New York City commerce during the late 1800s. To determine the history and provenance of timbers used in the construction of the Terminal Warehouse, we used tree-ring analysis on longleaf pine (Pinus palustris Mill.) joists that were original to the building. The ring-width patterns on the joists cross dated well internally, suggesting a common origin of the sampled lumber. Further, our Terminal Warehouse tree-ring chronology (1512–1891 C.E.) correlated strongly with existing tree-ring chronologies from western/central Georgia and eastern Alabama, indicating that the timbers were extracted from this region of the southeastern United States. The provenancing and dating of the Terminal Warehouse timbers underscores the important role that southern pines played in the expansion and development of New York City during the Gilded Age.

Dendroprovenance↗
DOE OSTI2021

Trace explosive residue detection of HMX and RDX in post-detonation dust from an open-air environment

Explosives are often used in industry, geology, mining, and other applications, but it is not always clear what remains after a detonation or the fate and transport of any residual material. The goal of this study was to determine to what extent intact molecules of high explosive (HE) compounds are detectable and quantifiable from post-detonation dust and particulates in a field experiment with varied topography. We focused on HMX (1,3,5,7-Tetranitro-1,3,5,7-tetrazocane), which is less studied in field detonation literature, as the primary explosive material and RDX (1,3,5-Trinitroperhydro-1,3,5-triazine) as the secondary material. The experiment was conducted at Site 300, Lawrence Livermore National Laboratory’s Experimental Test Site, in California, USA. Two 20.4 kg and one 40.8 kg above ground explosions (primarily comprised of LX-14, an HMX-based polymer-bonded high explosive) were detonated on an open-air firing area on separate days. The complex terrain of the firing area (e.g., buildings, berm, low-height obstacles) was advantageous to study HE deposition in relation to plume dynamics. Three types of samples were collected up to 100 m away from each shot: surface swipes of aluminum plates, surface swipes of fixed objects, and filters from air samples. We used atmospheric flow tube-mass spectrometry (AFT-MS) to quantify picogram levels of molecular residue of HE material in the post-detonation dust. An aliquot of sample extract in methanol (e.g., 1 µL of 0.5 mL) was placed onto a resistive material and then thermally desorbed into the AFT-MS. We successfully detected and quantified both HMX and RDX in many of the samples. Based on mass (pg) detected and solution dilution, we back-calculated the mass collected on the swipe or filter (ng per sample). The aerial distribution of molecular residue was consistent with the path of the plume, which was strongly determined by wind speed and direction at the time of each shot. The quantity of material detected appeared to correlate more with distance from the shot and the wind conditions than with shot size. This study demonstrates that the picogram detection levels of AFT-MS are well-suited for quantification of analytes (e.g., HMX and RDX) in environmental samples.

atmospheric flow tube-mass spectrometry (AFT-MS), ↗
NASA NTRS1989

A fast lightstripe rangefinding system with smart VLSI sensor

The focus of the research is to build a compact, high performance lightstripe rangefinder using a Very Large Scale Integration (VLSI) smart photosensor array. Rangefinding, the measurement of the three-dimensional profile of an object or scene, is a critical component for many robotic applications, and therefore many techniques were developed. Of these, lightstripe rangefinding is one of the most widely used and reliable techniques available. Though practical, the speed of sampling range data by the conventional light stripe technique is severely limited. A conventional light stripe rangefinder operates in a step-and-repeat manner. A stripe source is projected on an object, a video image is acquired, range data is extracted from the image, the stripe is stepped, and the process repeats. Range acquisition is limited by the time needed to grab the video images, increasing linearly with the desired horizontal resolution. During the acquisition of a range image, the objects in the scene being scanned must be stationary. Thus, the long scene sampling time of step-and-repeat rangefinders limits their application. The fast range sensor proposed is based on the modification of this basic lightstripe ranging technique in a manner described by Sato and Kida. This technique does not require a sampling of images at various stripe positions to build a range map. Rather, an entire range image is acquired in parallel while the stripe source is swept continuously across the scene. Total time to acquire the range image data is independent of the range map resolution. The target rangefinding system will acquire 1,000 100 x 100 point range images per second with 0.5 percent range accuracy. It will be compact and rugged enough to be mounted on the end effector of a robot arm to aid in object manipulation and assembly tasks.

Gruss, Andrew↗
NASA NTRSDate not supplied

Transcribing Air Traffic Control System Command Center Planning Telecons Using Cloud-Based Automatic Speech Recognition

This paper addresses the challenge of using Automatic Speech Recognition (ASR) technology to transcribe regular teleconferences that happen between FAA Air Traffic Control System Command Center (ATCSCC) planners, stakeholders and air users. These planning teleconferences (aka telecons or planning webinars) are an integral part of managing air traffic in the U.S. National Airspace System (NAS). In particular, the meetings facilitate the creation and modification of various traffic management initiatives (TMIs), that are used to regulate the flow of air traffic. This is typically a human intensive process, requiring specialists to listen to the entire meeting audio (10-20 minutes duration) and inferring the state of the NAS (e.g., weather phenomenon) that was discussed. It would be advantageous to have digital transcripts of the audio and have useful information (e.g., related to TMIs) automatically extracted from the transcripts. In this regard, we are exploring the adoption of state-of-the-art speech to text and Natural Language Processing (NLP) tools that will achieve our objective of digitizing the webinar audio. Unfortunately, the highly technical phraseology present in the audio and limited data availability for model building make ASR difficult. To overcome this challenge, we have taken the critical first step in creating a human transcription dataset from ~20 hours of speech in the ATCSCC audio with the help of subject matter experts. A novelty of our work is the creation of a ground truth transcription dataset for ATCSCC teleconference webinars, which is particularly important for Aviation domain-specific NLP tasks. Using Microsoft Speech Studio, a cloud-based ASR platform, we have fine-tuned the English pre-trained ASR models (available in speech studio) and achieved an average word error rate (WER) of 6.81%. The baseline ASR also provides a digital version of each planning webinar, making it accessible and text-searchable for future references. Additionally, the transcriptions can serve as a bridge between raw audio data and a range of text-based NLP tasks, such as named entity recognition (NER) and intent classification, potentially enhancing the digital footprint of the webinars and other connected data sources. Our work has several potential applications. Firstly, the transcriptions can be analyzed to understand the complex decision process of creating, implementing and modifying TMIs and may also contribute to TMI prediction services. Secondly, our dataset and model can be used to develop more accurate ASR systems for aviation-specific language, which can bring about digital communication in the aviation industry (and aid current “voice only” communications, which are inherently error-prone). Lastly, the transcriptions themselves can be used as a valuable resource for training other NLP models.

Stephen S. B. Clarke↗