Results for “knowledge systems” — Page 58

NASA NTRS2016

Performance of the Primary Mirror Center-of-curvature Optical Metrology System During Cryogenic Testing of the JWST Pathfinder Telescope

The James Webb Space Telescope (JWST) primary mirror (PM) is 6.6 m in diameter and consists of 18 hexagonal segments, each 1.5 m point-to-point. Each segment has a six degree-of-freedom hexapod actuation system and a radius-of-curvature (RoC) actuation system. The full telescope will be tested at its cryogenic operating temperature at Johnson Space Center. This testing will include center-of-curvature measurements of the PM, using the Center-of-Curvature Optical Assembly (COCOA) and the Absolute Distance Meter Assembly (ADMA). The COCOA includes an interferometer, a reflective null, an interferometer-null calibration system, coarse & fine alignment systems, and two displacement measuring interferometer systems. A multiple-wavelength interferometer (MWIF) is used for alignment & phasing of the PM segments. The ADMA is used to measure, and set, the spacing between the PM and the focus of the COCOA null (i.e. the PM center-of-curvature) for determination of the ROC. The performance of these metrology systems was assessed during two cryogenic tests at JSC. This testing was performed using the JWST Pathfinder telescope, consisting mostly of engineering development & spare hardware. The Pathfinder PM consists of two spare segments. These tests provided the opportunity to assess how well the center-of-curvature optical metrology hardware, along with the software & procedures, performed using real JWST telescope hardware. This paper will describe the test setup, the testing performed, and the resulting metrology system performance. The knowledge gained and the lessons learned during this testing will be of great benefit to the accurate & efficient cryogenic testing of the JWST flight telescope.

optical testing↗

NASA NTRS2017

Development of Increasingly Autonomous Traffic Data Manager Using Pilot Relevancy and Ranking Data

NASA's Safe Autonomous Systems Operations (SASO) project goal is to define and safely enable all future airspace operations by justifiable and optimal autonomy for advanced air, ground, and connected capabilities. This work showcases how Increasingly Autonomous Systems (IAS) could create operational transformations beneficial to the enhancement of civil aviation safety and efficiency. One such IAS under development is the Traffic Data Manager (TDM). This concept is a prototype 'intelligent party-line' system that would declutter and parse out non-relevant air traffic, displaying only relevant air traffic to the aircrew in a digital data communications (Data Comm) environment. As an initial step, over 22,000 data points were gathered from 31 Airline Transport Pilots to train the machine learning algorithms designed to mimic human experts and expertise. The test collection used an analog of the Navigation Display. Pilots were asked to rate the relevancy of the displayed traffic using an interactive tablet application. Pilots were also asked to rank the order of importance of the information given, to better weight the variables within the algorithm. They were also asked if the information given was enough data, and more importantly the "right" data to best inform the algorithm. The paper will describe the findings and their impact to the further development of the algorithm for TDM and, in general, address the issue of how can we train supervised machine learning algorithms, critical to increasingly autonomous systems, with the knowledge and expertise of expert human pilots.

Le Vie, Lisa R.↗

NASA NTRS2017

Future Food Production System Development Pulling from Space Biology Crop Growth Testing in Veggie

Preliminary crop testing using Veggie indicates the environmental conditions provided by the ISS are generally suitable for food crop production. When plant samples were returned to Earth for analysis, their levels of nutrients were comparable to Earth-grown ground controls. Veggie-grown produce food safety microbiology analysis indicated that space-grown crops are safe to consume. Produce sanitizing wipes were used on-orbit to further reduce risk of foodborne illness. Validation growth tests indicated abiotic challenges of insufficient or excess fluid delivery, potentially reduced air flow leading to excess water, elevated CO2 leading to physiological responses, and microorganisms that became opportunistic pathogens. As NASA works to develop future space food production, several areas of research to define these systems pull from the Veggie technology validation tests. Research into effective, reusable water delivery and water recovery methods for future food production systems arises from abiotic challenges observed. Additionally, impacts of elevated CO2 and refinement of fertilizer and light recipes for crops needs to be assessed. Biotic pulls include methods or technologies to effectively sanitize produce with few consumables and low inputs; work to understand the phytomicrobiome and potentially use it to protect crops or enhance growth; selection of crops with high harvest index and desirable flavors for supplemental nutrition; crops that provide psychosocial benefits, and custom space crop development. Planning for future food production in a deep space gateway or a deep space transit vehicle requires methods of handling and storing seeds, and ensuring space seeds are free of contaminants and long-lived. Space food production systems may require mechanization and autonomous operation, with preliminary testing initiated to identify operations and capabilities that are candidates for automation. Food production design is also pulling from Veggie logistics lessons, as we learn about growing at different scales and move toward developing systems that require less launch mass. Veggie will be used as a test bed for novel food production technologies. Veggie is a relatively simple precursor food production system but the knowledge gained from space biology validation tests in Veggie will have far reaching repercussions on future exploration food production.

Veggie↗

NASA NTRS2017

Future Food Production System Development Pulling From Space Biology Crop Growth Testing in Veggie

Preliminary crop testing using Veggie indicates the environmental conditions provided by the ISS are generally suitable for food crop production. When plant samples were returned to Earth for analysis, their levels of nutrients were comparable to Earth-grown ground controls. Veggie-grown produce food safety microbiology analysis indicated that space-grown crops are safe to consume. Produce sanitizing wipes were used on-orbit to further reduce risk of foodborne illness. Validation growth tests indicated abiotic challenges of insufficient or excess fluid delivery, potentially reduced air flow leading to excess water, elevated CO2 leading to physiological responses, and microorganisms that became opportunistic pathogens. As NASA works to develop future space food production, several areas of research to define these systems pull from the Veggie technology validation tests. Research into effective, reusable water delivery and water recovery methods for future food production systems arises from abiotic challenges observed. Additionally, impacts of elevated CO2 and refinement of fertilizer and light recipes for crops needs to be assessed. Biotic pulls include methods or technologies to effectively sanitize produce with few consumables and low inputs; work to understand the phytomicrobiome and potentially use it to protect crops or enhance growth; selection of crops with high harvest index and desirable flavors for supplemental nutrition; crops that provide psychosocial benefits, and custom space crop development. Planning for future food production in a deep space gateway or a deep space transit vehicle requires methods of handling and storing seeds, and ensuring space seeds are free of contaminants and long-lived. Space food production systems may require mechanization and autonomous operation, with preliminary testing initiated to identify operations and capabilities that are candidates for automation. Food production design is also pulling from Veggie logistics lessons, as we learn about growing at different scales and move toward developing systems that require less launch mass. Veggie will be used as a test bed for novel food production technologies. Veggie is a relatively simple precursor food production system but the knowledge gained from space biology validation tests in Veggie will have far reaching repercussions on future exploration food production. This work is supported by NASA.

Plants↗

NASA NTRS2017

Network Analysis of Rodent Transcriptomes in Spaceflight

Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

genomics↗

NASA NTRS2019

State Predictor of Classification Cognitive Engine Applied to Channel Fading

This study presents the application of machine learning (ML) to a space-to-ground communication link, showing how ML can be used to detect the presence of detrimental channel fading. Using this channel state information, the communication link can be used more efficiently by reducing the amount of lost data during fading. The motivation for this work is based on channel fading observed during on-orbit operations with NASA's Space Communication and Navigation (SCaN) testbed on the International Space Station (ISS). This paper presents the process to extract a target concept (fading and not-fading) from the raw data. The pre-processing and data exploration effort is explained in detail, with a list of assumptions made for parsing and labelling the dataset. The model selection process is explained, specifically emphasizing the benefits of using an ensemble of algorithms with majority voting for binary classification of the channel state. Experimental results are shown, highlighting how an end-to-end communication system can utilize knowledge of the channel fading status to identity fading and take appropriate action. With a laboratory testbed to emulate channel fading, the overall performance is compared to standard adaptive methods without fading knowledge, such as adaptive coding and modulation.

Fading↗

NASA NTRS2020

Dynamic Medical Risk Assessment Supported by Inference Networks

The Human Research Program's next generation risk model, the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT), provides researchers with estimates of astronaut medical and health risk. MEDPRATs Susceptibility Inference Network (SIN) facilitates the dynamic component of this tool. The SIN provides MEDPRAT with a "memory" that allows the system to use knowledge of what simulation events have occurred to alter the representative probability that future simulation events will occur during a given trial. The SIN allows for the medical events being simulated to be related to, and influence the likelihood of one another, providing a more robust risk estimate. We present initial work of our efforts to mathematically quantify and represent these dependent relationships between medical events.

McIntyre, L.↗

NASA NTRSDate not supplied

Lunar Rover Optimization Platform for Wheel Traction Studies

Robotic mobility systems expand the reach of future scientific and exploration missions to celestial bodies. Understanding the traction performance of these systems is necessary knowledge that informs mission-level requirements, such as power budgets and navigation envelopes. This paper covers the design, development, and verification of the four wheeled Lunar Rover Optimization Platform (LROP). This mass optimized platform is targeted to emulate future medium class rovers weighing up to 90 kg. The LROP has the ability to conduct various wheel design experiments such as obstacle traversal, slope ascent, and drawbar pull over a wheel loading range of 4.5 to 22.7 kg. The platform also has the ability to shift its center of gravity (CG) laterally and longitudinally to explore the CG shift effects on mobility performance. This knowledge is valuable for future rover designers exploring different payload packaging solutions. In this paper results from obstacle traversal test with varying angle of attack (AOA) and longitudinal CG position are reported along with results from slope ascent testing which proved-out the LROPs capabilities.

Stephen Gerdts↗

NASA NTRS1993

Operations Automation Using the Link Monitor and Control Operator Assistant

The Link Monitor & Control Operator Assistant (LMC OA) is a knowledge-based prototype system which uses Artificial Intelligence (AI) techniques to provide semi-automated monitor and control functions to support operations of the Deep Space Network (DSN) 70-Meter antenna at the Goldstone Deep Space Communications Camplex (DSCC).

Goldstone↗

NASA NTRS1993

DataHub: Science Data Management in Support of Interactive Exploratory Analysis

The DataHub addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, videlicet knowledge-based expert systems, science visualization, and science data management. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system.

science↗

NASA NTRS2021

Next generation lunar laser retroreflectors for fundamental physics and lunar science

Lunar Laser Ranging (LLR) data represent a powerful tool to understand the dynamics of the Earth-Moon system and the deep lunar interior. Over the past five decades, the ground station technology has significantly improved, whereas the lunar laser retroreflector arrays (LRAs) on the lunar surface did not. Current instrumental LLR error budget is dominated by the spread of the returning laser pulse due to the large size of the arrays. Next-generation single solid lunar Cube Corner Retroreflectors (CCRs) of large optical diameter (whose LLR performance is unaffected by that time spread) aim to fully exploit the current laser ranging station capabilities to attain LLR accuracy below current centimeter value down to the desired millimeter level and much higher data collection rates. Such improvements will have a significant impact, enabling more refined ephemerides, improved tests of General Relativity (GR) and of other theories of relativistic gravity in the Sun-Earth-Moon system and improved knowledge of the properties of the lunar interior.

L. Porcelli↗

NASA NTRSDate not supplied

Developing Mass Spectrometry for Water Quantitation and Volatiles Analysis from In-Situ Regolith

With a revived focus to create a sustainable hu-man presence on the moon, and in preparation for future Mars exploration, it is imperative that all resources are utilized to their fullest potential [1]. In-Situ Resource Utilization (ISRU) will be critical for future mission success as it would enable in-dependent operation of missions while reducing the dependence on the complex supply chain created between the Earth, the moon and Mars. One of the most critical resources that has been identified for ISRU on the lunar surface is water [2]. Water is a versatile resource that can be used in various space operations, such as ra-diation shielding and conversion to oxygen (O2) for propellant [3,4]. One of the most water rich resources is thought to be within the regolith lo-cated in the permanently shadowed regions (PSR) of the Moon; several upcoming missions, such as PRIME-1 and VIPER, are already sched-uled to confirm this hypothesis [5,6]. However, there are currently no missions planned to quanti-fy the abudance of water at these regions. The quantity of water contained in the ice will inform and help the development of future ISRU plants and operation. Water and other volatile gases can be detect-ed upon controlled heating of icy lunar regolith for an accurate quantification of water. This method is similar to thermogravimetric analysis, which was used to analyze Apollo lunar regolith sam-ples. However, losses via sublimation/evaporation or contamination may have occurred with the samples due to the transit and exposure to the terrestrial environment. Furthermore, water would not be expected for these samples since they were not collected from a PSR. Thus, for more accurate results, icy lunar regolith should be ana-lyzed in situ to provide the most representative composition of both water and other volatile gas-es. The Light Water Analysis and Volatile Extract (LightWAVE) project aims to address this knowledge gap. A system has been developed to collect, heat and analyze evolved gases from lu-nar regolith on the lunar surface. The gases will be analyzed by a modified commercial off the shelf (COTS) residual gas analyzer (RGA) quad-rupole mass spectrometer. Evolved gases from heated regolith samples can be identified by the observed mass-to-charge (m/z) ratios, and the peak intensities correlate to the abundances of the observed gases for quantitation. Therefore, our group is developing a calibration methodology utilizing a COTS RGA to quantitate water from in-situ regolith samples on the lunar surface. The partial pressure of water and ideal gas law will be used to quantify the total water evolved from a regolith sample. Here we present our methodol-ogy for the design and calibration for water quan-titation using a COTS RGA.

Nilab Azim↗

NASA NTRS2022

Herbarium records provide reliable phenology estimates in the understudied tropics

1. Plant phenology has been shifting dramatically in response to climate change, a shift that may have significant and widespread ecological consequences. Of particular concern are tropical biomes, which represent the most biodiverse and imperilled regions of the world. However, compared to temperate floras, we know little about phenological responses of tropical plants because long-term observational datasets from the tropics are sparse. 2. Herbarium specimens have greatly increased our phenological knowledge in temperate regions, but similar data have been underutilized in the tropics and their suitability for this purpose has not been broadly validated. Here, we compare phenological estimates derived from field observational data (i.e. plot surveys) and herbarium specimens at various spatial and taxonomic scales to determine whether specimens can provide accurate estimations of reproductive timing and its spatial variation. 3. Here, we demonstrate that phenological estimates from field observations and herbarium specimens coincide well. Fewer than 5% of the species exhibited significant differences between flowering periods inferred from field observations versus specimens regardless of spatial aggregation. In contrast to studies based on field records, herbarium specimens sampled much larger geographic and climatic ranges, as has been documented previously for temperate plants, and effectively captured phenological responses across varied environments. 4. Synthesis. Herbarium specimens are verified to be a vital resource for closing the gap in our phenological knowledge of tropical systems. Tropical plant reproductive phenology inferred from herbarium records is widely congruent with field observations, suggesting that they can and should be used to investigate phenological variation and their associated environmental cues more broadly across tropical biomes.

Brazil↗

NASA NTRS2021

Collective Transport of Unconstrained Objects via Implicit Coordination and Adaptive Compliance

We present a decentralized control algorithm for robots to aid in carrying an unknown load. Coordination occurs solely through sensing of the forces on or movement of the shared load. Robots prevent undesired motion of the load while permitting movement in the task-relevant subspace, and stabilize against unexpected events by a transient decrease in compliance. The algorithm requires no direct communication between agents, and minimal knowledge of the system or task. We demonstrate the approach in simulation using a commercially available compliant robotic platform.

Nicole E. Carey↗

NASA NTRSDate not supplied

Trajectory Planning and Online Performance Model Estimation for Advanced Air Mobility

We propose a framework for adaptive guidance based on optimal control and estimation using closed-loop performance models. In the proposed approach, parameters of a reduced-order performance model are estimated in real time so that trajectories and guidance commands are replanned with more accurate knowledge of the system's response and performance capabilities. To apply this methodology to flight control systems, we introduce a simple yet expressive performance model modified from a reference linear design model. The proposed framework is applied to guidance of a simulated Advanced Air Mobility class concept aircraft experiencing control effector failures. We demonstrate that, by optimizing performance model parameters in real time, guidance commands can be intelligently adjusted to recover system stability and the performance of a full-order vehicle model, even in the event of effector failures. Furthermore, the reduced-order performance model requires a fraction of the computational cost of the full-order model, facilitating real-time use of adaptive, optimal guidance.

Differential dynamic programming↗

NASA NTRSDate not supplied

Trajectory Planning and Online Performance Model Estimation for Advanced Air Mobility

We propose a framework for adaptive guidance based on optimal control and estimation using closed-loop performance models. In the proposed approach, parameters of a reduced-order performance model are estimated in real time so that trajectories and guidance commands are replanned with more accurate knowledge of the system's response and performance capabilities. To apply this methodology to flight control systems, we introduce a simple yet expressive performance model modified from a reference linear design model. The proposed framework is applied to guidance of a simulated Advanced Air Mobility class concept aircraft experiencing control effector failures. We demonstrate that, by optimizing performance model parameters in real time, guidance commands can be intelligently adjusted to recover system stability and the performance of a full-order vehicle model, even in the event of effector failures. Furthermore, the reduced-order performance model requires a fraction of the computational cost of the full-order model, facilitating real-time use of adaptive, optimal guidance.

Differential dynamic programming↗

DOE OSTI2019

Graph Generation with a Focusing Lexicon

Reference datasets are an essential part of developing effective data exploration tools. Many reference datasets are synthetic in nature, seeding real-world properties into generation routines. Others are laboriously curated from original source materials. This is a time-consuming process that requires significant domain expertise all along the process. This paper presents a third path: deriving a network from real-world source materials using automated tools. By properly grounding the tools in a small collection of curated documents, a larger corpus be automatically processed with greater confidence. The end system leverages human knowledge (in the initial document curation), but with much less time commitment enabled by automation. Our ultimate goal is to produce reference datasets, derived from real-world data that capture aspects salient to a specific activity in the context of all of the activities in the data-set. Our reference datasets take the form of graphs.

Chandra Shekar, Mayanka↗

DOE OSTI2022

Stability analysis of a one-dimensional multiphysics model of a molten salt fast reactor

Reactor designs with a fast neutron spectrum have recently moved into the research focus for possible Generation IV reactor concepts - a representative of which is the molten salt fast reactor (MSFR). In order to assess the safety and reliability of this reactor concept, it is necessary to obtain knowledge of the system behaviour. An important part of this research concerns the dynamical stability of the MSFR. Research regarding the MSFR stability so far has either been using linearized models for stability criteria or only been examining certain transients at fixed parameter values. This work delivers a comprehensive stability analysis for a non-linearized MSFR model, and a wide range of values for all relevant parameters. For this purpose, a one-dimensional MSFR model was set up, taking neutron kinetics and thermal hydraulics in the form of a system of differential equations into account. The stability of this model was investigated by means of the numerical tool MATCONT, which was used to monitor the evolution of a so-called fixed-point solution, here referring to the steady state at operating conditions of the system, while system parameters got varied. The MATCONT analyses showed no loss of stability for any of the considered parameter variations and no solutions that might co-exist in parallel with the steady-state fixed-point solution. Therefore these results indicate a stable fixed point to which all solution transients converge, making the considered MSFR model insusceptible to deviations from the equilibrium. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗