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NASA NTRS2011

Towards Autonomous Operation of Robonaut 2

The Robonaut 2 (R2) platform, as shown in Figure 1, was designed through a collaboration between NASA and General Motors to be a capable robotic assistant with the dexterity similar to a suited astronaut [1]. An R2 robot was sent to the International Space Station (ISS) in February 2011 and, in doing so, became the first humanoid robot in space. Its capabilities are presently being tested and expanded to increase its usefulness to the crew. Current work on R2 includes the addition of a mobility platform to allow the robot to complete tasks (such as cleaning, maintenance, or simple construction activities) both inside and outside of the ISS. To support these new activities, R2's software architecture is being developed to provide efficient ways of programming robust and autonomous behavior. In particular, a multi-tiered software architecture is proposed that combines principles of low-level feedback control with higher-level planners that accomplish behavioral goals at the task level given the run-time context, user constraints, the health of the system, and so on. The proposed architecture is shown in Figure 2. At the lowest-level, the resource level, there exists the various sensory and motor signals available to the system. The sensory signals for a robot such as R2 include multiple channels of force/torque data, joint or Cartesian positions calculated through the robot's proprioception, and signals derived from objects observable by its cameras.

Badger, Julia M.↗

NASA NTRS2011

CropEx Web-Based Agricultural Monitoring and Decision Support

CropEx is a Web-based agricultural Decision Support System (DSS) that monitors changes in crop health over time. It is designed to be used by a wide range of both public and private organizations, including individual producers and regional government offices with a vested interest in tracking vegetation health. The database and data management system automatically retrieve and ingest data for the area of interest. Another stores results of the processing and supports the DSS. The processing engine will allow server-side analysis of imagery with support for image sub-setting and a set of core raster operations for image classification, creation of vegetation indices, and change detection. The system includes the Web-based (CropEx) interface, data ingestion system, server-side processing engine, and a database processing engine. It contains a Web-based interface that has multi-tiered security profiles for multiple users. The interface provides the ability to identify areas of interest to specific users, user profiles, and methods of processing and data types for selected or created areas of interest. A compilation of programs is used to ingest available data into the system, classify that data, profile that data for quality, and make data available for the processing engine immediately upon the data s availability to the system (near real time). The processing engine consists of methods and algorithms used to process the data in a real-time fashion without copying, storing, or moving the raw data. The engine makes results available to the database processing engine for storage and further manipulation. The database processing engine ingests data from the image processing engine, distills those results into numerical indices, and stores each index for an area of interest. This process happens each time new data is ingested and processed for the area of interest, and upon subsequent database entries, the database processing engine qualifies each value for each area of interest and conducts a logical processing of results indicating when and where thresholds are exceeded. Reports are provided at regular, operator-determined intervals that include variances from thresholds and links to view raw data for verification, if necessary. The technology and method of development allow the code base to easily be modified for varied use in the real-time and near-real-time processing environments. In addition, the final product will be demonstrated as a means for rapid draft assessment of imagery.

Harvey. Craig↗

NASA NTRS2013

The Herschel* PEP-HERMES Luminosity Function- I. Probing the Evolution of PACS Selected Galaxies to z approx. equal to 4

We exploit the deep and extended far-IR data sets (at 70, 100 and 160 μm) of the Herschel Guaranteed Time Observation (GTO) PACS Evolutionary Probe (PEP) Survey, in combination with the Herschel Multi-tiered Extragalactic Survey data at 250, 350 and 500 μm, to derive the evolution of the rest-frame 35-, 60-, 90- and total infrared (IR) luminosity functions (LFs) up to z ∼ 4.We detect very strong luminosity evolution for the total IR LF (LIR ∝ (1 + z)(sup 3.55 +/- 0.10) up to z ∼ 2, and ∝ (1 + z)(sup 1.62 +/- 0.51) at 2 less than z less than approximately 4) combined with a density evolution (∝ (1 + z)(sup −0.57 +/- 0.22) up to z ∼ 1 and ∝ (1 + z)(sup −3.92 +/- 0.34) at 1 less than z less than approximately 4). In agreement with previous findings, the IR luminosity density (ρIR) increases steeply to z ∼ 1, then flattens between z ∼ 1 and z ∼ 3 to decrease at z greater than approximately 3. Galaxies with different spectral energy distributions, masses and specific star formation rates (SFRs) evolve in very different ways and this large and deep statistical sample is the first one allowing us to separately study the different evolutionary behaviours of the individual IR populations contributing to ρIR. Galaxies occupying the well-established SFR-stellar mass main sequence (MS) are found to dominate both the total IR LF and ρIR at all redshifts, with the contribution from off-MS sources (≥0.6 dex above MS) being nearly constant (∼20 per cent of the total ρIR) and showing no significant signs of increase with increasing z over the whole 0.8 < z <2.2 range. Sources with mass in the range 10 ≤ log(M/solar mass) ≤ 11 are found to dominate the total IR LF, with more massive galaxies prevailing at the bright end of the high-z (greater than approximately 2) LF. A two-fold evolutionary scheme for IR galaxies is envisaged: on the one hand, a starburst-dominated phase in which the Super Massive Black Holes (SMBH) grows and is obscured by dust (possibly triggered by a major merging event), is followed by an AGN-dominated phase, then evolving towards a local elliptical. On the other hand, moderately star-forming galaxies containing a low-luminosity AGN have various properties suggesting they are good candidates for systems in a transition phase preceding the formation of steady spiral galaxies.

Herschel↗

NASA NTRS2009

The Deep Impact Network Experiment Operations Center Monitor and Control System

The Interplanetary Overlay Network (ION) software at JPL is an implementation of Delay/Disruption Tolerant Networking (DTN) which has been proposed as an interplanetary protocol to support space communication. The JPL Deep Impact Network (DINET) is a technology development experiment intended to increase the technical readiness of the JPL implemented ION suite. The DINET Experiment Operations Center (EOC) developed by JPL's Protocol Technology Lab (PTL) was critical in accomplishing the experiment. EOC, containing all end nodes of simulated spaces and one administrative node, exercised publish and subscribe functions for payload data among all end nodes to verify the effectiveness of data exchange over ION protocol stacks. A Monitor and Control System was created and installed on the administrative node as a multi-tiered internet-based Web application to support the Deep Impact Network Experiment by allowing monitoring and analysis of the data delivery and statistics from ION. This Monitor and Control System includes the capability of receiving protocol status messages, classifying and storing status messages into a database from the ION simulation network, and providing web interfaces for viewing the live results in addition to interactive database queries.

Delay/Disruption Tolerant Network (DTN)↗

NASA NTRS2016

Exploration Clinical Decision Support System: Medical Data Architecture

The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear dimension biomarkers that enable image content-based retrieval and criteria assessment. In addition, a data mining engine (DME) is applied to cross-sectional adult surveys for predicting occurrence of renal calculi, ranked by statistical significance of demographics and specific food ingestion. In addition to this precursor space flight algorithm training, the DME will utilize a feature-engineering capability for unstructured clinical text classification health discovery. The ECDS backbone is a proposed multi-tier modular architecture providing data messaging protocols, storage, management and real-time patient data access. Technology demonstrations and success metrics will be finalized in FY16.

Biomedical support↗

NASA NTRS2015

Low Density Supersonic Decelerator Flight Dynamics Test-1 Flight Design and Targeting

NASA's Low Density Supersonic Decelerator (LDSD) program was established to identify, develop, and eventually qualify to Test [i.e. Technology] Readiness Level (TRL) - 6 aerodynamic decelerators for eventual use on Mars. Through comprehensive Mars application studies, two distinct Supersonic Inflatable Aerodynamic Decelerator (SIAD) designs were chosen that afforded the optimum balance of benefit, cost, and development risk. In addition, a Supersonic Disk Sail (SSDS) parachute design was chosen that satisfied the same criteria. The final phase of the multi-tiered qualification process involves Earth Supersonic Flight Dynamics Tests (SFDTs) within environmental conditions similar to those that would be experienced during a Mars Entry, Descent, and Landing (EDL) mission. The first of these flight tests (i.e. SFDT-1) was completed on June 28, 2014 with two more tests scheduled for the summer of 2015 and 2016, respectively. The basic flight design for all the SFDT flights is for the SFDT test vehicle to be ferried to a float altitude of 120 kilo-feet by a 34 thousand cubic feet (Mcf) heavy lift helium balloon. Once float altitude is reached, the test vehicle is released from the balloon, spun-up for stability, and accelerated to supersonic speeds using a Star48 solid rocket motor. After burnout of the Star48 motor the vehicle decelerates to pre-flight selected test conditions for the deployment of the SIAD system. After further deceleration with the SIAD deployed, the SSDS parachute is then deployed stressing the performance of the parachute in the wake of the SIAD augmented blunt body. The test vehicle/SIAD/parachute system then descends to splashdown in the Pacific Ocean for eventual recovery. This paper will discuss the development of both the test vehicle and the trajectory sequence including design trade-offs resulting from the interaction of both engineering efforts. In addition, the SFDT-1 nominal trajectory design and associated sensitivities will be discussed as well as an overview of the on-board flight software used to trigger and sequence the main flight events necessary to deploy the deceleration technologies. Finally, as-flown performance of the SFDT-1 system will be discussed.

Ivanov, Mark↗

NASA NTRS2018

Supplier Research & Analysis Approach

"The implementation of NASA GSFC's portfolio of mission projects relies upon inter-connected, multi-tiered supply chains of organizations operating under direct and indirect contracts and other agreements throughout the U.S. and around the world. These supply chains are subject to an inter-related array of technical/production, business, market and security risks that are amplified by the ongoing globalization of industry and technology and which can disrupt or threaten the production and delivery of products and services when needed and in conformance with requirements. In recognition of such risks and associated challenges, GSFC's SMA directorate launched an innovative Supplier Research and Analysis (SRA) capability three years ago to gain greater insight into the operating environment, performance, capabilities and viability of current and prospective suppliers for GSFC projects and proposals. The capability uses business intelligence techniques and primarily open source information resources as part of a cost-effective, non-intrusive methodology to produce several types of research and analysis reports. The reports are based on a holistic analytical framework encompassing key technical/production, business enterprise management, market and security factors, and feature in-depth information, summary information profiles, SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis, and candidate risk concerns in order to pro-actively support SMA and project management needs. The SRA capability, which is designed to complement and support ongoing SMA/project management activities and practices, has produced over 95 reports since its start-up in early 2015. This presentation addresses the approach, methodology and performance of the Supplier Research and Analysis (SRA) capability and its value in assuring the success of NASA mission projects. In doing so, the presentation provides lessons-learned, best practices, case examples and address how it fits into the development of an enterprise-level Supply Chain Risk Management capability."

supplier research and analysis↗

NASA NTRS2018

Auto Tracking Antenna Platform

The present invention is an auto tracking antenna platform upon which multiple antenna elements can be mounted to track a common moving object. The antenna tracking platform generally comprises a bottom pedestal enclosing a rotary azimuth actuator for controlled-rotary motion about the single vertical (z) axis, and an upper multi-tier framework housing a horizontal antenna-mounting beam pivotally supported for rotation about a horizontal (x) axis, and a drive assembly for direct-drive rotation of the antenna-mounting bar. Antenna elements are mounted along the horizontal mounting bar and the feeds routed through the azimuth actuator. This enables the use of fiber optic rotary joints or slip rings to pass data and video, instead of RF (waveguide) rotary joints which are required to pass high power RF signals.

Sanner, Kurt G↗

NASA NTRS2018

Supply Chain Research and Analysis for Space Systems

The implementation of NASA GSFC's portfolio of mission projects relies upon inter-connected, multi-tiered supply chains of organizations operating under direct and indirect contracts and other agreements throughout the U.S. and around the world. These supply chains are subject to an inter-related array of technical/production, business, market and security risks that are amplified by the ongoing globalization of industry and technology and which can disrupt or threaten the production and delivery of products and services when needed and in conformance with requirements. In recognition of such risks and associated challenges, GSFC's SMA directorate launched an innovative Supply Chain Research and Analysis capability three years ago to gain greater insight into the operating environment, performance, capabilities and viability of current and prospective suppliers for GSFC projects and proposals. The capability uses business intelligence techniques and primarily open source information resources as part of a cost-effective, non-intrusive methodology to produce several types of research and analysis reports. The reports are based on a holistic analytical framework encompassing key technical/production, business enterprise management, market and security factors, and feature in-depth information, summary information profiles, SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis, and candidate risk concerns in order to pro-actively support SMA and project management needs. The SRA capability, which is designed to complement and support ongoing SMA/project management activities and practices, has produced over 105 reports since its start-up in early 2015.This presentation addresses the approach, methodology and performance of the Supply Chain Research and Analysiscapability and its value in assuring the success of NASA mission projects. In doing so, the presentation provides lessons-learned, best practices, case examples and address how it fits into the development of an enterprise-level Supply Chain Risk Management capability.

supply chain risk management↗

NASA NTRS2019

Air Traffic Management Technology Demonstration-1 (ATD-1) Avionics Phase 2 Flight Test Training for Interval Management

Prior to the successful flight test validation of a new avionics prototype, participants from Boeing, Honeywell, and United Airlines underwent group training at NASA Langley Research Center. New prototype software for an algorithm which enables greater efficiency in high-density airspace, called Interval Management, was to be incorporated into Electronic Flight Bags and placed in the cockpit for pilot usage. The goals of the training were to teach the flight test pilots how to operate the new software, establish techniques to simultaneously position three aircraft prior to each test scenario, and ensure a common communication protocol among team members when coordinating the position of aircraft for the next scenario. The multi-tiered interactive training regimen consisted of a process that continually built upon previous foundational material. The primary learning elements were 1) a portable computer-based trainer that was provided to the pilots prior to classroom training sessions, 2) classroom learning, 3) full mock-up simulator training, and 4) refresher training just prior to the flight test. Each part of the regimen was designed to repeat and build upon the previous element. The purpose of this Technical Memorandum is to inform the aviation industry how flight training for Interval Management was conducted at Langley Research Center in order to reduce overall development costs of future Interval Management training programs. Secondly, the paper provides insight regarding the decision-making process when attempting to conduct a flight test.

Roper, Roy D.↗

NASA NTRSDate not supplied

Harnessing Synthetic Communities and Microbial Recycling of Space Waste Streams for Biomanufacturing Applications

The long-term habitation of extraterrestrial environments such as the Moon or Mars presents significant challenges including supplying materials to sustain life. Off-world recycling of waste materials into biomanufacturer products may ameliorate this. Current literature highlights the need for efficient waste recycling systems to support the bioproduction of essential materials including foods, pharmaceuticals, and biomaterials. The study herein concerns itself with the investigation of three key aspects: 1) formulating an optimal wastewater media on which to grow recombinant microbes for bioproduction in space, 2) examining the potential for constructing stable and metabolically synergistic synthetic microbial communities for largescale and multi-tiered biomanufacturing, and 3) testing the efficacy of one such bioengineered enzyme, cutinase, on the degradation of PET plastics characteristic of those found in ISS waste as a model for recombinant recycling-based biomanufacturing of mission-critical substrates. Formulation of an optimal wastewater media involved growing several microorganisms on mixtures of synthetic planetary wastes representative of those found in space waste systems, combined with simple carbon sources derived from a physio-chemical CO conversion system to determine their growth potential. Potential synthetic microbial communities were conceptually designed, and their stability and metabolic synergism was evaluated within the context of co-cultures. Cutinase activity assays were utilized to determine the efficacy of bioengineered cutinase on PET plastic degradation. Findings will contribute to optimization of wastewater-based media formulations, data on stable synthetic microbial communities for bioproduction, and effective methods for measuring cutinase-based PET plastic degradation. These outcomes support the development of sustainable waste recycling systems for space habitation and aim to fill gaps in the current literature and proposing innovative solutions for waste recycling in space environments. By leveraging synthetic biology this study seeks to enhance the feasibility of long-term extraterrestrial habitation through sustainable resource management.

Bioprocessing↗

DOE OSTI2021

Data Analysis Approach for Large Data Volumes in a Connected Community

Recent advancements within smart neighborhoods where utilities are enabling automatic control of appliances such as heating, ventilation, and air conditioning (HVAC) and water heater (WH) systems are providing new opportunities to minimize energy costs through reduced peak load. This requires systematic collection, storage, management, and in-memory processing of large volumes of streaming data for fast performance. In this paper, we propose a multi-tier layered IoT software framework that enables effective descriptive and predictive data analysis for understanding live operation of the neighborhood, fault identification, and future opportunities for further optimization of load curves. We then demonstrate how we achieve live situational awareness of the connected neighborhood through a suite of visualization components. Finally, we discuss a few analytic dashboards that address questions such as peak load reductions obtained due to optimization, customer preference for automatic control of appliances (do they override the automatic control of HVAC?, etc.). 1 1 This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Chinthavali, Supriya↗

DOE OSTI2021

Synchronization between processes in a coordination namespace

A system and method of supporting point-to-point synchronization among processes/nodes implementing different hardware barriers in a tuple space/coordinated namespace (CNS) extended memory storage architecture. The system-wide CNS provides an efficient means for storing data, communications, and coordination within applications and workflows implementing barriers in a multi-tier, multi-nodal tree hierarchy. The system provides a hardware accelerated mechanism to support barriers between the participating processes. Also architected is a tree structure for a barrier processing method where processes are mapped to nodes of a tree, e.g., a tree of degree k to provide an efficient way of scaling the number of processes in a tuple space/coordination namespace.

Jacob, Philip↗

DOE OSTI2022

Synchronization between processes in a coordination namespace

A system and method of supporting point-to-point synchronization among processes/nodes implementing different hardware barriers in a tuple space/coordinated namespace (CNS) extended memory storage architecture. The system-wide CNS provides an efficient means for storing data, communications, and coordination within applications and workflows implementing barriers in a multi-tier, multi-nodal tree hierarchy. The system provides a hardware accelerated mechanism to support barriers between the participating processes. Also architected is a tree structure for a barrier processing method where processes are mapped to nodes of a tree, e.g., a tree of degree k, to provide an efficient way of scaling the number of processes in a tuple space/coordination namespace.

Jacob, Philip↗

DOE OSTI2023

Resource-aware compression

Systems, apparatuses, and methods for implementing a multi-tiered approach to cache compression are disclosed. A cache includes a cache controller, light compressor, and heavy compressor. The decision on which compressor to use for compressing cache lines is made based on certain resource availability such as cache capacity or memory bandwidth. This allows the cache to opportunistically use complex algorithms for compression while limiting the adverse effects of high decompression latency on system performance. To address the above issue, the proposed design takes advantage of the heavy compressors for effectively reducing memory bandwidth in high bandwidth memory (HBM) interfaces as long as they do not sacrifice system performance. Accordingly, the cache combines light and heavy compressors with a decision-making unit to achieve reduced off-chip memory traffic without sacrificing system performance.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

SURVEILLANCE DETECTION FOR TRANSPORTATION OPERATIONS PERSONNEL TO PREVENT HIJACKING, THEFT, SABOTAGE, AND MALICIOUS SECURITY EVENTS DURING TRANSPORTING NUCLEAR MATERIAL

The secure transportation of high-consequence materials, including nuclear and radiological assets, is a critical global priority in the face of escalating terrorism, security threats, and violent protests targeting these operations. Effective surveillance detection—the ability to identify, assess, and respond to potential threats across a continuum of scenarios—is paramount in addressing these challenges. This paper outlines a phased, multi-tiered training program designed to strengthen the surveillance detection capabilities of organizations responsible for nuclear material transport. The proposed training program adopts a progressive approach, gradually increasing in technical complexity to provide participants with comprehensive knowledge and tools for implementing robust security strategies. It targets a wide spectrum of stakeholders, including competent authorities, regulators, inspectors, shippers, carriers, law enforcement, and emergency response personnel, equipping them to plan, evaluate, and safeguard nuclear material transportation effectively. Each phase of the program emphasizes distinct elements of the surveillance detection continuum and transport security, focusing on critical topics such as threat identification, adversary task timelines, protective methodologies, and attack mitigation strategies. The training framework is anchored in technical exchanges and scenario-driven courses that reflect real-world complexities and challenges. By addressing the surveillance detection continuum comprehensively—from early threat assessment to active countermeasures—the program reinforces global efforts to secure nuclear assets. It aligns with international security objectives and fosters a strong security culture within participating organizations, ensuring personnel are prepared to counter potential threats and maintain the safe, secure movement of these materials. Ultimately, this initiative aims to enhance preparedness, security, and response capabilities, supporting the global mission to safeguard high-consequence materials against evolving threats.

Zineddin, Dr. Z. [ORNL] (ORCID:0009000848740725)↗