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At least 487 records · Page 27

Gaps List KSC Space Crop Production Project Scientist: Interview Evaluation

The Space Crop Production (SCP) Program at the NASA Kennedy Space Center (KSC) is aimed at achieving nutrient supplementation and moving towards caloric independence from Earth by growing crops for astronauts. However, growing crops outside of Earth’s orbit creates many new challenges. The KCS SCP Project Scientists have developed a method of organizing these challenges, called the Gaps List. This Gaps List is a dynamic, taxonomically arranged list of missing knowledge and technologies needed to reach production goals. The purpose of this evaluation was to assess the effectiveness and current research coverage of the Gaps List by using it to document KSC SCP Program research. It was determined that there are several needs within the SCP Program that are not being met, as well as, many deficiencies within the Gaps List. Gaps involving hardware were largely unrecognized by both the KSC researchers and the funding sources that would typically support them. The KSC SCP Project will require more engineering and physical sciences support to fill those gaps. The Gaps List was found to be out of date and in need of rearrangement. A recommendation from this review was that the Gaps List be reassessed at regular intervals to ensure all gaps, and relevant research topics are included. To better understand the gaps within the list, any assessment needs to include a measure of priority, dependency, and breadth. These measures may be included within or alongside the current taxonomical arrangement of the Gaps List.

Chloe Sophia Alexander↗

Gaps List KSC Space Crop Production Project Scientist: Interview Evaluation

The Space Crop Production (SCP) Program at the NASA Kennedy Space Center (KSC) is aimed at achieving nutrient supplementation and moving towards caloric independence from Earth by growing crops for astronauts. However, growing crops outside of Earth’s orbit creates many new challenges. The KCS SCP Project Scientists have developed a method of organizing these challenges, called the Gaps List. This Gaps List is a dynamic, taxonomically arranged list of missing knowledge and technologies needed to reach production goals. The purpose of this evaluation was to assess the effectiveness and current research coverage of the Gaps List by using it to document KSC SCP Program research. It was determined that there are several needs within the SCP Program that are not being met, as well as, many deficiencies within the Gaps List. Gaps involving hardware were largely unrecognized by both the KSC researchers and the funding sources that would typically support them. The KSC SCP Project will require more engineering and physical sciences support to fill those gaps. The Gaps List was found to be out of date and in need of rearrangement. A recommendation from this review was that the Gaps List be reassessed at regular intervals to ensure all gaps, and relevant research topics are included. To better understand the gaps within the list, any assessment needs to include a measure of priority, dependency, and breadth. These measures may be included within or alongside the current taxonomical arrangement of the Gaps List.

Chloe S. Alexander↗

Quinoa Phenotyping Methodologies: An International Consensus

Quinoa is a crop originating in the Andes but grown more widely and with the genetic potential for significant further expansion. Due to the phenotypic plasticity of quinoa, varieties need to be assessed across years and multiple locations. To improve comparability among field trials across the globe and to facilitate collaborations, components of the trials need to be kept consistent, including the type and methods of data collected. Here, an internationally open-access framework for phenotyping a wide range of quinoa features is proposed to facilitate the systematic agronomic, physiological and genetic characterization of quinoa for crop adaptation and improvement. Mature plant phenotyping is a central aspect of this paper, including detailed descriptions and the provision of phenotyping cards to facilitate consistency in data collection. High-throughput methods for multi-temporal phenotyping based on remote sensing technologies are described. Tools for higher-throughput post-harvest phenotyping of seeds are presented. A guideline for approaching quinoa field trials including the collection of environmental data and designing layouts with statistical robustness is suggested. To move towards developing resources for quinoa in line with major cereal crops, a database was created. The Quinoa Germinate Platform will serve as a central repository of data for quinoa researchers globally.

59 BASIC BIOLOGICAL SCIENCES↗

Fire-Resistant Textile Development for Exploration Vehicles With Enriched-Oxygen Cabin Environments

Material selection is a key part of the National Aeronautics and Space Administration (NASA) spacecraft fire safety management plan. Non-flammable textiles are necessary to ensure large-scale flame propagation events do not occur inside a spacecraft. An increased use of textiles and other softgood material is crucial to the pursuit of exploration spaceflight to reduce mass and volume. Exploration spaceflight missions benefit from enriched oxygen cabin environments (>21% O2) by allowing a reduced prebreathe protocol before Extravehicular Activity (EVA). However, materials become exponentially more flammable the higher the O2 levels become. Recent testing within the agency has revealed the lack of commercial-off-the-shelf (COTS) materials that can meet safety requirements in oxygen-enriched environments. Most of the fibers and textiles developed during Apollo (100% O2 cabin environment) and Skylab (>70% O2 cabin environment) are no longer commercially available due to those Programs ending and the discontinuation of raw materials or closure of the original manufacturers. As NASA returns to higher oxygen concentrations inside spacecraft, non-flammable textile development efforts have begun to meet the agency’s needs. This paper discusses those efforts including overall fire safety approach, state-of-the-art textile review and testing, an agency-wide assessment of textile needs performed by the NASA Engineering and Safety Center (NESC), the textile development strategy and expected challenges.

Mary Walker↗

Gaps List KSC Space Crop Production Project Scientist: Interview Evaluation

The Space Crop Production (SCP) at the NASA Kennedy Space Center (KSC) is aimed at achieving nutrient supplementation and moving towards caloric independence from Earth by growing crops for astronauts. However, growing crops outside of Earth’s orbit creates many new challenges. The KCS SCP Project Scientists have developed a method of organizing these challenges, called the Gaps List. This Gaps List is a dynamic, taxonomically arranged list of missing knowledge and technologies needed to reach production goals. The purpose of this evaluation was to assess the effectiveness and current research coverage of the Gaps List by using it to document the KSC SCP Program research. In evaluating the research, it was determined that several needs within the SCP Program that are not being met, and many deficiencies within the Gaps List were encountered. Gaps involving hardware were largely unrecognized by the KSC researchers and the funding sources that would typically support them. The KSC SCP Project will require more engineering and physical sciences support to close those gaps. The Gaps List was found to be out of date and in need of rearrangement. A recommendation from this review was that the Gaps List be reassessed at regular intervals to ensure all gaps and relevant research topics are included. In order to better understand the gaps within the list, any assessment needs to include a measure of priority, dependency and breadth. These measures may be included within or along side the current taxonomical arrangement of the Gaps List.

Space Crop Production↗

Integrating Formal Methods and Testing 2002

Traditionally, qualitative program verification methodologies and program testing are studied in separate research communities. None of them alone is powerful and practical enough to provide sufficient confidence in ultra-high reliability assessment when used exclusively. Significant advances can be made by accounting not only tho formal verification and program testing. but also the impact of many other standard V&V techniques, in a unified software reliability assessment framework. The first year of this research resulted in the statistical framework that, given the assumptions on the success of the qualitative V&V and QA procedures, significantly reduces the amount of testing needed to confidently assess reliability at so-called high and ultra-high levels (10-4 or higher). The coming years shall address the methodologies to realistically estimate the impacts of various V&V techniques to system reliability and include the impact of operational risk to reliability assessment. Combine formal correctness verification, process and product metrics, and other standard qualitative software assurance methods with statistical testing with the aim of gaining higher confidence in software reliability assessment for high-assurance applications. B) Quantify the impact of these methods on software reliability. C) Demonstrate that accounting for the effectiveness of these methods reduces the number of tests needed to attain certain confidence level. D) Quantify and justify the reliability estimate for systems developed using various methods.

Cukic, Bojan↗

Respiratory Toxicity of Lunar Highland Dust

Lunar dust exposures occurred during the Apollo missions while the crew was on the lunar surface and especially when microgravity conditions were attained during rendezvous in lunar orbit. Crews reported that the dust was irritating to the eyes and in some cases respiratory symptoms were elicited. NASA s vision for lunar exploration includes stays of 6 months on the lunar surface hence the health effects of periodic exposure to lunar dust need to be assessed. NASA has performed this assessment with a series of in vitro and in vivo tests on authentic lunar dust. Our approach is to "calibrate" the intrinsic toxicity of lunar dust by comparison to a nontoxic dust (TiO2) and a highly toxic dust (quartz) using intratrachael instillation of the dusts in mice. A battery of indices of toxicity is assessed at various time points after the instillations. Cultures of selected cells are exposed to test dusts to assess the adverse effects on the cells. Finally, chemical systems are used to assess the nature of the reactivity of various dusts and to determine the persistence of reactivity under various environmental conditions that are relevant to a space habitat. Similar systems are used to assess the dissolution of the dust. From these studies we will be able to set a defensible inhalation exposure standard for aged dust and predict whether we need a separate standard for reactive dust. Presently-available data suggest that aged lunar highland dust is slightly toxic, that it can adversely affect cultured cells, and that the surface reactivity induced by grinding the dust persists for a few hours after activation.

James, John T.↗

A public website for the automated assessment and validation of SARS-CoV-2 diagnostic PCR assays

Abstract Summary Polymerase chain reaction-based assays are the current gold standard for detecting and diagnosing SARS-CoV-2. However, as SARS-CoV-2 mutates, we need to constantly assess whether existing PCR-based assays will continue to detect all known viral strains. To enable the continuous monitoring of SARS-CoV-2 assays, we have developed a web-based assay validation algorithm that checks existing PCR-based assays against the ever-expanding genome databases for SARS-CoV-2 using both thermodynamic and edit-distance metrics. The assay-screening results are displayed as a heatmap, showing the number of mismatches between each detection and each SARS-CoV-2 genome sequence. Using a mismatch threshold to define detection failure, assay performance is summarized with the true-positive rate (recall) to simplify assay comparisons. Availability and implementation The assay evaluation website and supporting software are Open Source and freely available at https://covid19.edgebioinformatics.org/#/assayValidation, https://github.com/jgans/thermonucleotide BLAST and https://github.com/LANL-Bioinformatics/assay_validation. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

An assessment model for atmospheric composition

Predicting future perturbations to global air quality and climate requires, as a prerequisite, prognostic models for the composition of the Earth's atmosphere. Such assessment models are needed to evaluate the impact on our environment of different social choices that affect emissions of the photochemically and radiatively important trace gases. Our presentation here of a prototype assessment model is intended to encourage public scientific discussions of the necessary components of the model and their interactions, with the recognition that models similar to this will likely be used by the Environmental Protection Agency and other regulatory agencies in order to assess the effect of changes in atmospheric composition on climate over the next century.

Prather, Michael J.↗

Sensorimotor Countermeasures

Exploration class missions will include multiple transitions between gravitational environments, sometimes after long periods in microgravity, which will impact the neurovestibular system and sensorimotor capabilities. New countermeasures and assessment tools are needed to enhance preflight disorientation training, maintain inflight physical performance, and accelerate recovery following transitions between gravity environments so that crew are enabled to perform critical exploration mission tasks. The Sensorimotor Countermeasures capability area encompasses three projects. 1) The Upright Proprioception Retention via Inflight Training and Evaluation (UPRITE) system is being developed as an in-flight countermeasure that will mitigate the degradation of balance control mechanisms, which will improve post-flight postural stability. The development of such a countermeasure is not simply a matter of adapting a ground-based training program for spaceflight. The way that we control balance in a gravitational environment cannot be duplicated in 0g. Therefore, the UPRITE system challenges proprioception and tactile function using a 0g configuration. The steps to develop the countermeasure have been broken into seven phases: training type, controllable board factors, protocol development, 0g hardware test, training efficacy, ISS hardware demonstration, and countermeasure verification. 2) Unobtrusive Monitoring Tools and Operational Assessments (aka Head/Body Assessments) are being developed to quantify crew member sensorimotor adaptation following gravitational transitions. Three areas are needed in this development 1) explore, develop, and validate unobtrusive monitoring tools, 2) define sensorimotor performance metrics, and 3) explore capabilities to enhance sensorimotor assessment tasks for operational use and validate assessment tasks via high-fidelity analogs. 3) The Spatial Disorientation Trainer is being developed as a portable training capability to simulate the performance of landing and recovery type tasks while experiencing vertigo due to post-flight vestibular alterations. These simulations can be used 1) across research studies investigating the impacts of vestibular disruption on operational performance/assessments, 2) to train astronauts for upcoming spaceflight missions, and 3) to educate space medicine and operational personnel prior to providing post-flight support.

Scott Jonathan Wood↗

L-PBF High-Throughput Data Pipeline Approach for Multi-modal Integration

Abstract Metal-based additive manufacturing requires active monitoring solutions for assessing part quality. Multiple sensors and data streams, however, generate large heterogeneous data sets that are impractical for manual assessment and characterization. In this work, an automated pipeline is developed that enables feature extraction from high-speed camera video and multi-modal data analysis. The framework removes the need for manual assessment through the utilization of deep learning techniques and training models in a weakly supervised paradigm. We demonstrate this pipeline’s capability over 700,000 high-speed camera frames. The pipeline successfully extracts melt pool and spatter geometries and links them to corresponding pyrometry, radiography, and processparameter information. 715 individual prints are examined to reveal melt pool areas that exceeds 0.07 mm 2 and pyrometry signal over a threshold (375 pyrometry units) were more likely to have defects. These automated processes enable massive throughput of characterization techniques.

36 MATERIALS SCIENCE↗

Space Induced Discharge Model to Be Used on Interface Circuit Vulnerability Assessment

Charging can occur in space due to plasma and high energy particles. Charging is especially severe in certain earth orbits such as geostationary orbit, medium earth orbit and highly inclined orbit. A spacecraft that travels to other planets such as Jupiter also encounters high level of charging due to Jupiter’s radiation belt. The major concern for spacecraft operation due to charging is the survival of sensitive electrical circuits. Dielectrics and floating metal can charge up and discharge onto interface circuits. The electrical circuits need to be evaluated for survival from the electrostatic-discharge (ESD) threat. Both ESD induced upset and damage need to be assessed. The interface circuits are often located inside a shielded unit in the spacecraft structure or a shielded vault with sufficient radiation shielding to avoid surface and internal charging. The materials external to the highly shielded area can charge up and discharge onto wires that can directly dissipate the ESD onto the interface circuits. Figure 1 shows a possible discharge mechanism onto the interfacing circuits. If the wire has an external shield or a coaxial line, some or most of the discharge can flow on the shield to chassis ground. There is always coupling from external discharge. If the wire has no shield, the discharge flows onto the interface circuit. Fig. 1 Possible discharge paths onto the interface circuits. The purpose of this article is to address how to model the ESD threat to be used as the discharge source onto the interface circuit based on the electron beam test data. Different models are needed for different impedances associated with the interface circuits. Once those models are derived, one needs to analyze the interface circuit with the corresponding model using an electrical simulation tool. Then, the circuit’s front-end components can be assessed for damage and upset. Upset is highly dependent on the circuit operation and system requirements, and thus it is not addressed any further. Damage of electrical parts is often rated under Human-Body-Model (HBM) ESD. One can utilize this industry-wide available information to assess the damage vulnerability due to space discharges. However, the HBM waveform does not always match the discharge waveform. To estimate the damage vulnerability of the circuit and set margin, one needs to compare the equivalent energy delivered to the victim between a HBM discharge and the results from an ESD source model based on actual discharges. This paper presents such a comparison for a few select cases.

Xie, Julie↗

Assessing boundary condition and parametric uncertainty in numerical-weather-prediction-modeled, long-term offshore wind speed through machine learning and analog ensemble

To accurately plan and manage wind power plants, not only does the time-varying wind resource at the site of interest need to be assessed but also the uncertainty connected to this estimate. Numerical weather prediction (NWP) models at the mesoscale represent a valuable way to characterize the wind resource offshore, given the challenges connected with measuring hub-height wind speed. The boundary condition and parametric uncertainty associated with modeled wind speed is often estimated by running a model ensemble. However, creating an NWP ensemble of long-term wind resource data over a large region represents a computational challenge. Here, we propose two approaches to temporally extrapolate wind speed boundary condition and parametric uncertainty using a more convenient setup in which a mesoscale ensemble is run over a short-term period (1 year), and only a single model covers the desired long-term period (20 year). We quantify hub-height wind speed boundary condition and parametric uncertainty from the short-term model ensemble as its normalized across-ensemble standard deviation. Then, we develop and apply a gradient-boosting model and an analog ensemble approach to temporally extrapolate such uncertainty to the full 20-year period, for which only a single model run is available. As a test case, we consider offshore wind resource characterization in the California Outer Continental Shelf. Both of the proposed approaches provide accurate estimates of the long-term wind speed boundary condition and parametric uncertainty across the region (R 2 >0.75), with the gradient-boosting model slightly outperforming the analog ensemble in terms of bias and centered root-mean-square error. At the three offshore wind energy lease areas in the region, we find a long-term median hourly uncertainty between 10 % and 14 % of the mean hub-height wind speed values. Finally, we assess the physical variability in the uncertainty estimates. In general, we find that the wind speed uncertainty increases closer to land. Also, neutral conditions have smaller uncertainty than the stable and unstable cases, and the modeled wind speed in winter has less boundary condition and parametric sensitivity than summer.

17 WIND ENERGY↗

The Automatic Assessment and Reduction of Noise Using Edge Pattern Analysis in Nonlinear Image Enhancement

Noise is the primary visibility limit in the process of non-linear image enhancement, and is no longer a statistically stable additive noise in the post-enhancement image. Therefore novel approaches are needed to both assess and reduce spatially variable noise at this stage in overall image processing. Here we will examine the use of edge pattern analysis both for automatic assessment of spatially variable noise and as a foundation for new noise reduction methods.

Jobson, Daniel J.↗

Lower Stratospheric Measurement Issues Workshop Report

The Lower Stratospheric Measurement Issues workshop was held on 17-19 Oct. 1990. The 3-day workshop was sponsored by the Atmospheric Effects of Stratospheric Aircraft (AESA) component of the High Speed Research Program (HSRP). Its purpose was to provide a scientific forum for addressing specific issues regarding chemistry and transport in the lower stratosphere, for which measurements are essential to an assessment of the environmental impact of a projected fleet of high speed civil transports (HSCTs). The objective of the workshop was to obtain vigorous and critical review of the following topics: (1) atmospheric measurements needed for the assessment; (2) present capability for making those measurements; and (3) areas in instrumentation or platform development essential to making the measurements.

Schmeltekopf, Arthur L.↗

Automatic Assessment and Reduction of Noise using Edge Pattern Analysis in Non-Linear Image Enhancement

Noise is the primary visibility limit in the process of non-linear image enhancement, and is no longer a statistically stable additive noise in the post-enhancement image. Therefore novel approaches are needed to both assess and reduce spatially variable noise at this stage in overall image processing. Here we will examine the use of edge pattern analysis both for automatic assessment of spatially variable noise and as a foundation for new noise reduction methods.

Jobson, Daniel J.↗

What Questions Would a Systems Engineer Ask to Assess Systems Engineering Models as Credible

Digital Systems Engineering strategies typically call for digital Systems Engineering models to be retained in repositories and certified as an authoritative source of truth (enabling model reuse, qualification, and collaboration). In order for digital Systems Engineering models to be certified as authoritative (credible), they need to be assessed - verified and validated - and with the amount of uncertainty in the model quantified (consider reusing someone else's model without knowing the author). Due to this increasing model complexity, the authors assert that traditional human-based methods for validating, verifying, and uncertainty quantification - such as human-based peer-review sessions - cannot sufficiently establish that a digital Systems Engineering model of a complex system is credible. Digital Systems Engineering models of complex systems can contain millions of nodes and edges. The authors assert that this level of detail is beyond the ability of any group of humans - even working for weeks at a time - to discern and catch every minor model infraction. In contrast, computers are highly effective at discerning infractions with massive amounts of information. The authors suggest that a better approach might be to focus the humans at what model patterns should be assessed and enable the computer to assess the massive details in accordance with those patterns - by running through perhaps 100,000 test loops. In anticipation of future projects to implement and automate the assessment of models at Sandia National Laboratories, a study was initiated to elicit input from a group of 25 Systems Engineering experts. The authors positioning query began with - 'What questions would a Systems Engineer ask to assess Systems Engineering models for credibility?" This report documents the results of that survey.

42 ENGINEERING↗

Fundamental Technology Development for Gas-Turbine Engine Health Management

Integrated vehicle health management technologies promise to dramatically improve the safety of commercial aircraft by reducing system and component failures as causal and contributing factors in aircraft accidents. To realize this promise, fundamental technology development is needed to produce reliable health management components. These components include diagnostic and prognostic algorithms, physics-based and data-driven lifing and failure models, sensors, and a sensor infrastructure including wireless communications, power scavenging, and electronics. In addition, system assessment methods are needed to effectively prioritize development efforts. Development work is needed throughout the vehicle, but particular challenges are presented by the hot, rotating environment of the propulsion system. This presentation describes current work in the field of health management technologies for propulsion systems for commercial aviation.

Mercer, Carolyn R.↗