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At least 199 records · Page 11

Graphical Visualization of Human Exploration Capabilities

NASA's pioneering space strategy will require advanced capabilities to expand the boundaries of human exploration on the Journey to Mars (J2M). The Evolvable Mars Campaign (EMC) architecture serves as a framework to identify critical capabilities that need to be developed and tested in order to enable a range of human exploration destinations and missions. Agency-wide System Maturation Teams (SMT) are responsible for the maturation of these critical exploration capabilities and help formulate, guide and resolve performance gaps associated with the EMC-identified capabilities. Systems Capability Organization Reporting Engine boards (SCOREboards) were developed to integrate the SMT data sets into cohesive human exploration capability stories that can be used to promote dialog and communicate NASA's exploration investments. Each SCOREboard provides a graphical visualization of SMT capability development needs that enable exploration missions, and presents a comprehensive overview of data that outlines a roadmap of system maturation needs critical for the J2M. SCOREboards are generated by a computer program that extracts data from a main repository, sorts the data based on a tiered data reduction structure, and then plots the data according to specified user inputs. The ability to sort and plot varying data categories provides the flexibility to present specific SCOREboard capability roadmaps based on customer requests. This paper presents the development of the SCOREboard computer program and shows multiple complementary, yet different datasets through a unified format designed to facilitate comparison between datasets. Example SCOREboard capability roadmaps are presented followed by a discussion of how the roadmaps are used to: 1) communicate capability developments and readiness of systems for future missions, and 2) influence the definition of NASA's human exploration investment portfolio through capability-driven processes. The paper concludes with a description of planned future work to modify the computer program to include additional data and of alternate capability roadmap formats currently under consideration.

Rodgers, Erica M.↗

Exploration Medical Capability Clinical Decision Support System Concept of Operations

The Clinical Decision Support (CDS) project supports the Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP). Specifically, the CDS project addresses the ExMC gap, Medical-701: Enhance medical capabilities within an exploration medical system. For long-duration, deep space missions, computational and data resources will play an important role in maintaining crew health, wellness and performance where the crew will need to be more self-reliant as we enter a new era in space exploration to return to the moon and explore Mars. These ambitious goals will require significant change in in-flight medical care due to constraints on mass, volume, power, crew time, skills reduction over time and medical evacuation capabilities. These constraints make it absolutely necessary to develop transformative solutions using new technologies. Unlike the current paradigm for crew health in low-Earth orbit missions that rely on constant communication with Mission Control, the deep space missions will experience communication delays and possibly, no communications for finite periods of time. Hence, crew health management will benefit from analytics’ capabilities to augment decision support. A comprehensive, multi-functional on-board clinical decision support system (CDSS) will help crews assess and diagnose conditions, decide appropriate responses, and guide the provision of tailored and evidence-based treatments, while reflecting contextual factors and constraints. The context may include present and historical data, viable diagnostic equipment, available supplies and medications, and vehicle and environmental health. Communication time with ground-based personnel is delayed or non-existent during significant portions of the mission so the crew will need to autonomously respond to health, performance and medical situations, particularly those that are unplanned. The CDSS must also provide additional capabilities as complex as training for an emergency situation while augmenting non-expert practitioner skillsets if the Crew Medical Officer (CMO) is incapacitated, and as routine as facilitating delayed communication with flight surgeons on the ground. The CDSS must connect complex issues involving health, wellness, task performance and environmental domains. Furthermore, CDSS functionality will focus on semi-autonomous and autonomous decision-making by the crew that is necessary to address challenges in executing a self-contained medical system that enables health care without assistance from ground clinical experts. The document, ExMC CDSS Architecture Recommendation, (HRP- 48032) establishes a description of the envisioned CDSS architecture. The analytics, descriptive or advanced, contained in a CDSS will interface with the integrated crew health and performance architecture that provides the appropriate data sets. The aim of the CDS project is to develop requirements for a CDSS through a series of test-bed prototype developments and demonstrations.

HRP↗

Space Science and Technology Partnership Forum: In-Space Assembly Data Collection and Analysis

The Space Science and Technology Partnership Forum was established in 2015 to identify synergistic efforts and technologies across the government. In-Space Assembly (iSA) is the focus of the topic area that NASA is currently coordinating with other government agencies. This paper focuses on the data collection process, the data analysis of that information, and preliminary insights gleaned from the data. The goal of the analysis is to understand the linkages within the collected data, identifying synergies and gaps, and provide visualization of the current state of iSA needs and capability development across the government. Capability roadmaps, Venn diagrams, bubble charts, and scorecards (an overview of each individual iSA capability) are used to visualize the results of this analysis, which reveals areas of possible inter-agency collaboration, investment gaps in capabilities relative to the need, and capabilities that warrant engagement across multiple agencies to eliminate potential inefficiencies.

Arney, Dale C.↗

Space Science and Technology Partnership Forum: In-Space Assembly Data Collection and Analysis

The Space Science and Technology Partnership Forum was established in 2015 to identify synergistic efforts and technologies across the government. In-Space Assembly (iSA) is the focus of the topic area that NASA is currently coordinating with other government agencies. This paper focuses on the data collection process, the data analysis of that information, and preliminary insights gleaned from the data. The goal of the analysis is to understand the linkages within the collected data, identifying synergies and gaps, and provide visualization of the current state of iSA needs and capability development across the government. Capability roadmaps, Venn diagrams, bubble charts, and scorecards (an overview of each individual iSA capability) are used to visualize the results of this analysis, which reveals areas of possible inter-agency collaboration, investment gaps in capabilities relative to the need, and capabilities that warrant engagement across multiple agencies to eliminate potential inefficiencies.

Dale C Arney↗

Abbreviated Technical Report: Experimentally Interrogating Detonation Chemistry on Sub-Nanosecond to Nanosecond Timescales

Direct experimental measurement of chemical reactions during high explosive detonation remains challenging. Theory and modeling have long preceded experiment in the fundamental physical and chemical kinetic properties of detonation, and experimentation at the relevant timescales are needed to both validate models and provide fundamental understanding of detonation. In this LDRD-ER project, two approaches, x-ray diffraction and core-level x-ray Raman, were developed and used to further experimental capabilities to address this gap. We further developed dynamic x-ray diffraction to directly detect nanodiamond formation during detonation, providing experimental data towards resolving longstanding controversy in the scientific literature, and although the full kinetics have not yet been fully mapped, diamond diffraction appears on the same timescales as detonation soot formation. In the second research thrust, we have developed core-level x-ray Raman for use with high explosives. This technique provides information analogous to x-ray absorption spectroscopy and electron energy loss spectroscopy, but uses inelastic scattering of hard x-rays that can interrogate chemistry around light elements much deeper into the material. The low cross section and requisite high solid angle collection have hindered its use for ultra-fast spectroscopy. We developed and tested a high-q spectrometer which will substantially increase cross section and signal-to-noise, showing this method will also not dramatically alter, compared to x-ray absorption, the most discriminating spectral features of C, N, and O from various high explosives and expected detonation products. We have also used x-ray Raman combined with OCEAN electronic structure calculations to explore dynamic photodegradation mechanisms in PETN and CL-20 explosives. This provides a pathway towards implementing capability to dynamically explore chemistry at an x-ray free electron laser.

36 MATERIALS SCIENCE↗

Public Health Response and Medical Management of Internal Contamination in Past Radiological or Nuclear Incidents: A Review

Following a radiological or nuclear emergency, workers, responders and the public may be internally contaminated with radionuclides. Screening, monitoring and assessing any internal contamination and providing necessary medical treatment, especially when a large number of individuals are involved, is challenging. Experience gained and lessons learned from the management of previous incidents would help to identify gaps in knowledge and capabilities on preparedness for and response to radiation emergencies. In this paper, eight largescale and five workplace radiological and nuclear incidents are reviewed cross 14 technical areas, under the broader topics of emergency preparedness, emergency response and recovery processes. The review findings suggest that 1) new strategies, algorithms and technologies are explored for rapid screening of large populations; 2) exposure assessment and dose estimation in emergency response and dose reconstruction in recovery process are supported by complementary sources of information, including ‘citizen science’; 3) surge capacity for monitoring and dose assessment is coordinated through national and international laboratory networks; 4) evidence-based guidelines for medical management and follow-up of internal contamination are urgently needed; 5) mechanisms for international and regional access to medical countermeasures are investigated and implemented; 6) long-term health and medical follow up programs are designed and justified; and 7) capabilities and capacity developed for emergency response are sustained through adequate resource allocation, routine nonemergency use of technical skills in regular exercises, training, and continuous improvement.

61 RADIATION PROTECTION AND DOSIMETRY↗

Importance of Spatially Continuous Urban Surface Properties in Urban‐Resolving Earth System Modeling

Accurate representation of urban properties and processes at higher resolutions in global modeling systems is essential for advancing our ability to capture the complexities of urban systems and informing effective resilience strategies. However, the prescription of coarse global-scale urban properties in most state-of-the-art Earth system models (ESMs) is limiting their potential for capturing urban signals as they advance toward kilometer-scale simulation capabilities. To bridge this gap in inadequate urban property representation and to advance urban-resolving Earth system modeling, this work integrates the newly-developed global 1 km-resolution facet-level urban surface property data set, U-Surf, into the land component of Community Earth System Model (CESM)—Community Terrestrial System Model (CTSM). The land-only CTSM simulations are validated against satellite measurements, ground-based urban weather stations, flux tower observations, and reanalysis data. Results demonstrate that the enhanced urban properties allow improved simulations of urban meteorology and surface energy fluxes compared to the default coarse-resolution categorical urban canopy parameters. Spatial scaling analysis reveals regime-dependent information loss during resolution aggregation, as well as substantial scale-dependent variations in urban surface energy flux representation. Furthermore, these findings have critical implications for coupled Earth system modeling when including the effect of land-atmosphere interaction. This work establishes a foundation for future urban-resolving kilometer-scale ESM development, which will enable systematic intra- and inter-city comparisons that inform urban adaptation strategies across diverse global urban environments.

Cheng, Yifan [University of Illinois Urbana-Champa↗

Addressing the Safety of Next-Generation Batteries

Owing to increasing demand for low-cost energy storage with secure material supply chains, the battery community is approaching a pivotal shift beyond conventional lithium-ion (Li-ion) towards next-generation cells. Technologies that include alkali-metal anodes, solid electrolytes and earth-abundant materials such as sodium (Na) and sulfur (S) are reaching commercialization in cells. The abuse tolerance and thermal runaway hazards of such technologies diverge from conventional Li-ion cells. Consequently, designing safe batteries with next-generation materials requires a holistic approach to characterize cells and to understand their responses to abuse conditions from the beginning to the end of life. Here we provide a Perspective on how the safety and abuse tolerance of cells are likely to change for up-and-coming technologies; challenges and opportunities for reimagining safe cell and battery designs; gaps in our knowledge; capabilities for understanding the hazards of thermal runaway and how to address them; how standard abuse tests may need to adapt to new challenges; and how research needs to support affected professionals, from pack designers to first responders, to manage hazards and ensure safe roll-out of next-generation cells into applications like electric vehicles (EVs). Finally, given the large number of next-generation technologies being explored, we encourage giving priority to safety-focused research in proportion to the rate of manufacturing scale-up of each specific technology.

25 ENERGY STORAGE↗

DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection

Abstract Artificial intelligence methods show great promise in increasing the quality and speed of work with large astronomical datasets, but the high complexity of these methods leads to the extraction of dataset-specific, non-robust features. Therefore, such methods do not generalize well across multiple datasets. We present a universal domain adaptation method, DeepAstroUDA , as an approach to overcome this challenge. This algorithm performs semi-supervised domain adaptation (DA) and can be applied to datasets with different data distributions and class overlaps. Non-overlapping classes can be present in any of the two datasets (the labeled source domain, or the unlabeled target domain), and the method can even be used in the presence of unknown classes. We apply our method to three examples of galaxy morphology classification tasks of different complexities (three-class and ten-class problems), with anomaly detection: (1) datasets created after different numbers of observing years from a single survey (Legacy Survey of Space and Time mock data of one and ten years of observations); (2) data from different surveys (Sloan Digital Sky Survey (SDSS) and DECaLS); and (3) data from observing fields with different depths within one survey (wide field and Stripe 82 deep field of SDSS). For the first time, we demonstrate the successful use of DA between very discrepant observational datasets. DeepAstroUDA is capable of bridging the gap between two astronomical surveys, increasing classification accuracy in both domains (up to 40 % on the unlabeled data), and making model performance consistent across datasets. Furthermore, our method also performs well as an anomaly detection algorithm and successfully clusters unknown class samples even in the unlabeled target dataset.

79 ASTRONOMY AND ASTROPHYSICS↗

Techno-Economic Analysis: Best Practices and Assessment Tools

A team at Sandia National Laboratories (SNL) recognized the growing need to maintain and organize the internal community of Techno - Economic Assessment analysts at the lab . To meet this need, an internal core team identified a working group of experienced, new, and future analysts to: 1) document TEA best practices; 2) identify existing resources at Sandia and elsewhere; and 3) identify gaps in our existing capabilities . Sandia has a long history of using techno - economic analyses to evaluate various technologies , including consideration of system resilience . Expanding our TEA capabilities will provide a rigorous basis for evaluating science, engineering and technology - oriented projects, allowing Sandia programs to quantify the impact of targeted research and development (R&D), and improving Sandia's competitiveness for external funding options . Developing this working group reaffirms the successful use of TEA and related techniques when evaluating the impact of R&D investments, proposed work, and internal approaches to leverage deep technical and robust, business - oriented insights . The main findings of this effort demonstrated the high - impact TEA has on future cost, adoption for applications and impact metric forecasting insights via key past exemplar applied techniques in a broad technology application space . Recommendations from this effort include maintaining and growing the best practices approaches when applying TEA, appreciating the tools (and their limits) from other national laboratories and the academic community, and finally a recognition that more proposals and R&D investment decision s locally at Sandia , and more broadly in the research community from funding agencies , require TEA approaches to justify and support well thought - out project planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

LandRAY Final Report

The overarching Project objective is to demonstrate the feasibility of using an innovative Power Take-Off (PTO) Module, to be used in the Columbia Power Technologies, Inc. (C·Power) utility-scale wave energy converter (WEC). The PTO Module uniquely combines a large-diameter, direct-drive, rotary permanent magnet generator; a patent-pending rail-bearing system; and a corrosion-resistant fiber-reinforced-plastic structure. The rail bearing system allows for: • A flexible non-rigid and low-cost generator frame as compared to conventional machines. • A reduction of air gap and consequently lower cost electromagnetic design • Ability to reduce costs by increasing diameter to much larger dimensions, while maintaining the small air gap. • A direct drive electro-mechanical solution that is the fastest and most precise approach for responding to the dynamic variability of forces from wave energy. The land-based test of the PTO Module (DDP1) will provide an important risk reduction phase, to demonstrate the reliability and feasibility of a large-diameter, small air-gap generator that is capable of delivering high efficiency, fault-tolerance and relatively simple "at-sea" maintenance capabilities – qualities that are essential for cost-effective wave energy devices. This is the first known test of such a system.

16 TIDAL AND WAVE POWER↗

2021 NIRT Mini Drill (After Action Report)

During the summer and fall of 2021, several functional area drills were held that focused on exercising Consequence Management’s (CM) ability to extract and use data from RadResponder for the purpose of answering intermediate-phase questions presented as technical inject requests for information (RFI) in Sandia National Laboratories (SNL) Consequence Management Operational System (COSMOS) software. The scenario chosen was that of Northern Lights 2016 (NL16) which was a large-scale nuclear power plant (NPP) release exercise in the state of Minnesota. The NL16 data was extracted from the Radiological Assessment and Monitoring System (RAMS) event where it was created and was reformatted for implanting to a new RadResponder event. Next, the beta-version of a laboratory sample data simulator was used to generate more sample data that was injected to the event. Five “mini-drills” were devised with each prompt defined by a data-based need. For each drill, a team of assessment and NARAC scientists worked the problem using the drill prompt and the available data in RadResponder. The teams held a kickoff meeting, had several days to work the problem, and then reported their results as well as observations in a hotwash. Several areas for improvement in both the software and process were identified during the course of these drills. This report will document the process of addressing each RFI and the discovered gaps in both software capability and methodology so that they can be considered for future development and investment by the CM and NIRT programs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

AI-Enabled Robots for Automated Nondestructive Evaluation and Repair of Power Plant Boilers. Final Report

Boiler failure could cause loss of life and safety issues, cost hundreds of thousands of dollars in equipment repairs, property damage and production losses, and drive up the cost of electric power. Boiler maintenance is challenging and risky for inspectors working on scaffolding in confined hazardous spaces inside of a boiler and sometimes the space is hard to access. The operation is also time-consuming due to the large area of vertical structures for inspection and the tremendous effort needed for scaffolding. Recently, the use of robotics (e.g., drones and crawlers) in power plants for maintenance is growing rapidly. However, the existing robotics solutions show two notable technological gaps: no live repair capability, and no Artificial Intelligence (AI) for smart autonomy. The objective of this project is to develop an integrated autonomous robotic platform that is equipped with compact non-destructive evaluation (NDE) sensors to perform live inspection, operates onboard repair devices to perform live repair, and uses AI for intelligent data fusion and predictive analysis for automated and smart spatiotemporal inspection, analysis and repair of the furnace walls in coal-fired boilers. The approach to achieve the objective includes developing NDE sensors with signal processing techniques, designing and evaluating repair devices for robots based on fusion and solid-state technologies, and an autonomous robotic platform that can attach to and navigate on boiler furnace walls using magnetic drive tracks. The robot is also powered by AI to automate data gathering (e.g., 3D mapping and damage localization) and predictive analysis. This project has advanced the state-of-the-art by providing technological breakthroughs including compact NDE and repair tools for robots, AI capabilities for smart autonomy, and a robotic platform for automated boiler maintenance. This project has great potential to result in significant benefits including limiting or eliminating the need to send operators to assess difficult-to-access or hazardous areas, enabling automated live inspection and repair, avoiding time consuming scaffolding (especially for partial maintenance during unplanned outage), collecting comprehensive and well-organized data smartly, and avoiding or limiting the need for onsite or remote piloting technicians. The impacts can be tremendous in terms of the time and cost savings, reducing the risk for human operators, and increasing boiler reliability, usability, and efficiency. In addition, by developing the new technologies on the autonomous inspection and repair robot, by involving multiple undergraduate and graduate students working together with the faculty members on this project, and by generating knowledge and building up collaborations with industrial partners, this effort will significantly update the education capabilities, support long-term fundamental research, and maintain the leadership of Colorado School of Mines and Michigan State University in energy fields.

20 FOSSIL-FUELED POWER PLANTS↗

Communication Requirements in 5G-Enabled Healthcare Applications: Review and Considerations

Fifth generation (5G) mobile communication technology can enable novel healthcare applications and augment existing ones. However, 5G-enabled healthcare applications demand diverse technical requirements for radio communication. Knowledge of these requirements is important for developers, network providers, and regulatory authorities in the healthcare sector to facilitate safe and effective healthcare. In this paper, we review, identify, describe, and compare the requirements for communication key performance indicators in relevant healthcare use cases, including remote robotic-assisted surgery, connected ambulance, wearable and implantable devices, and service robotics for assisted living, with a focus on quantitative requirements. We also compare 5G-healthcare requirements with the current state of 5G capabilities. Finally, we identify gaps in the existing literature and highlight considerations for this space.

5G networks↗

Elevated temperature crack growth

Alloy 718 crack growth experiments were conducted to assess the ability of the selected path-independent (P-I) integrals to describe the elevated temperature crack growth behavior. These tests were performed on single edge notch (SEN) specimens under displacement control with multiple extensometers to monitor the specimen and crack mouth opening displacement (CMOD). The displacements in these tests were sufficiently high to induce bulk cyclic inelastic deformation of the specimen. Under these conditions, the linear elastic fracture mechanics (LEFM) parameter K does not correlate the crack growth data. The experimentally measured displacement gradients at the end of specimen gage length were used as the boundary conditions in elastic-plastic finite element method (FEM) analyses. These analyses were performed with a node release approach using CYANIDE, a GEAE FEM code, which included a gap element which is capable of efficiently simulating crack closure. Excellent correlation was obtained between the experimentally measured and predicted variation of stress and CMOD with crack length and the stress-CMOD loops for Alloy 718 tests conducted at 538 C. This confirmed the accuracy of the FEM crack growth simulation approach. The experimentally measured crack growth rate data correlated well the selected P-I integrals. These investigations have produced significant progress in developing P-I integrals as non-linear fracture mechanics parameters. The results suggest that this methodology has the potential of accurately describing elevated temperature crack growth behavior under the combined influence of thermal cycling and bulk elastic-inelastic deformation states.

Kim, K. S.↗

Solar energetic particle events: Statistical modelling and prediction

Solar energetic particle events (SEPEs) can have a significant effect on the design and operation of earth orbiting and interplanetary spacecraft. In relation to this, the calculation of proton fluences and fluxes are considered, describing the current state of the art in statistical modeling. A statistical model that can be used for the estimation of integrated proton fluences for different mission durations of greater than one year is reviewed. The gaps in the modeling capabilities of the SEPE environment, such as a proton flux model, alpha particle and heavy ion models and solar cycle variations are described together with the prospects for the prediction of events using neural networks.

Gabriel, S. B.↗

Toward the Development of an Integrated Global Observing Strategy

In the current environment of stagnant or shrinking budgets for space research and exploration, nations can no longer afford to develop costly systems in a vacuum. Greater coordination of existing and planned systems, both among space agencies and between the space agencies and user communities, will enable the maximization of global investments in all areas of space-related research. In this manner, a group of space agencies has embarked on an initiative to link their activities in Earth observation with complementary observation programs. The goal of this initiative is to develop a comprehensive strategy for enhanced levels of support to scientific, operational and research communities. The space agencies, through the Committee on Earth Observation Satellites (CEOS), have embraced the concept of an Integrated Global Observing Strategy (IGOS), primarily in fulfillment of their own set of objectives and to derive greater benefit from both operating and planned Earth observing systems. Through working together, CEOS agencies are in a position to plan their Earth observation projects with the minimum of unnecessary overlap and to devise joint strategies for addressing serious gaps in their observation capabilities. Ultimately, an IGOS should be the joint product of all groups involved in the collection and analysis of both space-based and in-situ data. CEOS is actively seeking IGOS -related partnerships with the Global Climate, Global Ocean and Global Terrestrial Observing Systems, their intergovernmental Sponsors, the International Group of Funding Agencies for Global Change Research, and other scientific and user organizations including the International Geosphere-Biosphere Programme and the World Climate Research Programme.

Charles, Leslie Bermann↗

Fast Particle Methods for Multiscale Phenomena Simulations

We are developing particle methods oriented at improving computational modeling capabilities of multiscale physical phenomena in : (i) high Reynolds number unsteady vortical flows, (ii) particle laden and interfacial flows, (iii)molecular dynamics studies of nanoscale droplets and studies of the structure, functions, and evolution of the earliest living cell. The unifying computational approach involves particle methods implemented in parallel computer architectures. The inherent adaptivity, robustness and efficiency of particle methods makes them a multidisciplinary computational tool capable of bridging the gap of micro-scale and continuum flow simulations. Using efficient tree data structures, multipole expansion algorithms, and improved particle-grid interpolation, particle methods allow for simulations using millions of computational elements, making possible the resolution of a wide range of length and time scales of these important physical phenomena.The current challenges in these simulations are in : [i] the proper formulation of particle methods in the molecular and continuous level for the discretization of the governing equations [ii] the resolution of the wide range of time and length scales governing the phenomena under investigation. [iii] the minimization of numerical artifacts that may interfere with the physics of the systems under consideration. [iv] the parallelization of processes such as tree traversal and grid-particle interpolations We are conducting simulations using vortex methods, molecular dynamics and smooth particle hydrodynamics, exploiting their unifying concepts such as : the solution of the N-body problem in parallel computers, highly accurate particle-particle and grid-particle interpolations, parallel FFT's and the formulation of processes such as diffusion in the context of particle methods. This approach enables us to transcend among seemingly unrelated areas of research.

Koumoutsakos, P.↗