Search NASA⌕ Search

SEARCH · Search NASA

Results for “decision guide”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

MSD CoP Webinar: Metrics for Human Wellbeing

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Human well-being is an inherently multidimensional concept that broadly refers to what constitutes the "good life". Characterizing well-being requires a wide range of measures of quality of life. Taken together, these can provide a description of well-being and better guide decision making. In this webinar, our panel will first summarize the key themes and recommendations of interdisciplinary conversations that occurred during the course of a two-day, in-person workshop convened by PNNL September 27-28, 2023, which laid the foundations for a new research direction of well-being science and application. Next, they will present research exploring several dimensions of human well-being and their links to equity: energy security, food security, and economic measures. Finally, we will introduce the new Equity Working Group, gather community input to inform its activities, and provide avenues for ongoing engagement. Presenters : Stephanie Waldhoff (Joint Global Change Research Institute, Pacific Northwest National Laboratory; Invited Speaker), Brian O'Neill (Joint Global Change Research Institute, Pacific Northwest National Laboratory; Invited Speaker), Rebecca Saari (University of Waterloo; Co-Chair), Amanda Giang (University of British Columbia; Co-Chair), Sarah Fletcher (Stanford University; Co-Chair), and Matt Sparks (University of Waterloo; Communications Officer) Moderator: Pat M. Reed (MSD CoP Facilitation Team) This webinar was held on: May 29, 2024 from 1-2:15 PM ET

Equity↗
NASA NTRS2007

Aerial Videography From Locally Launched Rockets

A method of quickly collecting digital imagery of ground areas from video cameras carried aboard locally launched rockets has been developed. The method can be used, for example, to record rare or episodic events or to gather image data to guide decisions regarding treatment of agricultural fields or fighting wildfires. The method involves acquisition and digitization of a video frame at a known time along with information on the position and orientation of the rocket and camera at that time. The position and orientation data are obtained by use of a Global Positioning System receiver and a digital magnetic compass carried aboard the rocket. These data are radioed to a ground station, where they are processed, by a real-time algorithm, into georeferenced position and orientation data. The algorithm also generates a file of transformation parameters that account for the variation of image magnification and distortion associated with the position and orientation of the camera relative to the ground scene depicted in the image. As the altitude, horizontal position, and orientation of the rocket change between image frames, the algorithm calculates the corresponding new georeferenced position and orientation data and the associated transformation parameters. The output imagery can be rendered in any of a variety of formats. The figure presents an example of one such format.

Lyle, Stacey D.↗
NASA NTRS2013

Advanced Economic Analysis

An Economic Analysis (EA) is a systematic approach to the problem of choosing the best method of allocating scarce resources to achieve a given objective. An EA helps guide decisions on the "worth" of pursuing an action that departs from status quo ... an EA is the crux of decision-support.

Greenberg, Marc W.↗
NASA NTRS2016

Drought Impacts on Agricultural Production and Land Fallowing in California's Central Valley in 2015

The ongoing drought in California substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to mitigation of drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in fallow acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to time-series data from Landsat TM (Thematic Mapper), ETM+ (Enhanced Thematic Mapper Plus), OLI (Operational Land Imager), and MODIS (Moderate Resolution Imaging Spectroradiometer). Our effort has been focused on development of indicators of drought impacts in the March-August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 650 fields from March-September in 2014 and 2015. We present the algorithm along with updated results from the accuracy assessment, and data and maps of land fallowing in the Central Valley in 2015.

Valleys↗
NASA NTRS2019

Advancing Asteroid Threat Assessment

Asteroid Threat Assessment for Planetary Defense [Asteroid Threat Assessment Project (TAP) at NASA Ames Research Center]. Objectives: Develop models and data to characterize the potential damage and risks due to asteroid strikes on Earth. Provide results that can help guide decisions and planning: Asteroid surveys; Mitigation systems; Disaster response.

Wheeler, Lorien↗
NASA NTRSDate not supplied

Relating Land Cover Change to Runoff Distribution Using NASA Earth Observations in Riley County, Kansas

Riley County, Kansas, has observed increased levels of flooding, potentially due to changes in land use/land cover (LULC) and seasonal vegetation variation. This study contrasts two methods of generating runoff curve numbers (CN) from 2006-2020. (1) The traditional Soil Conservation Service CN calculation method uses a look-up table and tracked LULC to determine runoff changes. These tables allow for CN values specific to various land and crop cover types and account for various farming best practices but lack flexibility in calculations for various seasons or plant health. (2) A dynamic method employs normalized difference vegetation index (NDVI) compiled over the rainy season each year to calculate CN using seasonal vegetation. This method allows for a more precise analysis of runoff variability within and between rainy seasons because it can be updated with greater temporal detail and it captures higher spatial resolutions by using NDVI as a proxy for LULC. This study further uses inputs from the United States Geologic Survey (USGS) National Land Cover Database (NLCD), the United States Department of Agriculture (USDA) Cropland Data Layer, and Landsat imagery to create more precise LULC raster datasets including both urban cover and crop-specific land use and curve number maps of the area. Results can guide decision makers in the City of Manhattan, Riley County Department of Planning and Development, Riley County Conservation District, the Kansas Forest Service, and the Kansas Department of Health and Environment toward informed decisions on resiliency strategies to address future flooding.

Ella Griffith↗
NASA NTRS2020

Riley County Water Resources Project Summary - Comparing Runoff Curve Calculation Methods to Inform Local Resiliency Initiatives in Riley County, Kansas

Riley County, Kansas, has observed increased levels of flooding, potentially due to changes in land use/land cover (LULC) and seasonal vegetation variation. This study contrasts two methods of generating runoff curve numbers (CN) from 2006-2020. (1) The traditional Soil Conservation Service CN calculation method uses a look-up table and tracked LULC to determine runoff changes. These tables allow for land cover-specific CN and account for various farming techniques but lack flexibility in calculations for various seasons or plant health. (2) A dynamic method employs normalized difference vegetation index (NDVI) compiled over the rainy season each year to calculate CN using seasonal vegetation. This method allows for a more precise analysis of runoff variability within and between rainy seasons because it can be updated with greater temporal detail and captures higher spatial resolutions by using NDVI as a proxy for LULC. This study further uses inputs from the United States Geological Survey (USGS) National Land Cover Database (NLCD), the United States Department of Agriculture (USDA) Cropland Data Layer, and Landsat imagery to create more precise LULC raster datasets including both urban cover and crop-specific land use and curve number maps of the area. Results can guide decision makers in the City of Manhattan, Riley County Department of Planning and Development, Riley County Conservation District, the Kansas Forest Service, and the Kansas Department of Health and Environment toward informed decisions on resiliency strategies to address future flooding.

DEVELOP Project Summary↗
NASA NTRSDate not supplied

Quantifying Uncertainty of Landing and Takeoff Noise for Commercial Supersonic Aircraft

Of the many challenges faced by manufacturers attempting to offer supersonic travel to the public, the uncertainty in predicting the noise of these aircraft in airport operations has an immediate impact. No noise regulation exists in FAA or ICAO for certifying such aircraft, as these organization require solid data, usually from existing aircraft. Manufacturers are taking large risks to design a vehicle not knowing whether it will be allowed to fly. A partial solution to this conundrum is to use physics-based simulations to provide the “data” used to calibrate system-level prediction methods, carefully documenting the uncertainty of the method for application to supersonic aircraft. A close look at the accuracy of empirical prediction methods points to areas where improvements need to be made if noise studies of supersonic aircraft are to be useful. As NASA embarks on a focused research program to improve predictions of noise from the noise-dominant propulsion noise of commercial supersonic aircraft, this paper documents the work done to baseline the uncertainties found in today’s noise prediction methods. A relatively simplistic method was developed, summarizing the error of the empirical methods on a component basis and following their impact on the total aircraft during landing and takeoff operations using Monte Carlo analysis. By this method it is found that current empirical noise prediction methods have an uncertainty of 1.5 EPNdB cumulative for propulsion noise of a representative conventional subsonic passenger aircraft. When applied to likely near-term supersonic commercial aircraft, the uncertainty is 7.6 EPNdB cumulative, a difference that must be reduced if the prediction methods are to guide decision makers.

Airport noise↗
NASA NTRSDate not supplied

Game Based Learning For Earth Science Applications Training

Current NASA Earth capacity development programs employ mechanisms ranging from online resource sharing, and virtual and in-person trainings to share knowledge. While these programs are highly successful at engaging individuals around the world – in 2018, over 8000 individuals and over 2000 institutions from all 50 US states and over 140 countries were engaged through over 150 projects and trainings – user feedback has highlighted the desire for expanded hands-on, practical experiences in incorporating NASA EO insights with localized data and actions. We aim to address this gap by leveraging the benefits of game-based learning to build user skills in integrating NASA and local EO data to guide decisions for climate resiliency and hazard planning. This project is being executed as a two-phase crowdsourced challenge: 1) Phase 1 will require a well-researched product concept that reflects an understanding of NASA’s Earth data and tools and user needs, and proposes an innovative and interactive game or extended reality experience to train users in identifying relevant NASA data and applying insights to their climate resiliency decisions; 2) Winners of Phase 1 will be provided seed funding to develop a working prototype of the product. We aim to award 1-3 final winners to support the development of more than one game, thereby ensuring that NASA's diverse audiences around the world can access training games that best suit their needs and capabilities. This EO training game project fits in the NASA Earth Science Applied Sciences Program’s Capacity Development Program, contributing to the program mission of “helping people around the world better understand [NASA’s Earth] data and find ways to use them” (https://appliedsciences.nasa.gov/what-we-do/capacity-building). The final training game will complement existing programmatic activities of workforce development, trainings, and collaborative projects, while providing the unique value of providing interactive experiences to users and collecting real-time data and feedback to improve NASA’s Earth applications’ products and services related to climate resilience.

Human centered design↗
NASA NTRSDate not supplied

DEVELOP: Building Capacity in Early Career Individuals to Apply NASA Earth Observations in Health and Air Quality

The NASA DEVELOP National Program builds capacity to use and apply NASA Earth observations to address environmental concerns around the globe. The DEVELOP model builds capacity in both participants (students, recent graduates, and early and transitioning career professionals), who conduct the projects, and partners (decision and policy makers), who are recipients of project methodologies and results. While projects focus on a spectrum of thematic topics, health and air quality related topics made up more than a quarter of DEVELOP’s FY2023 project portfolio. These projects worked in collaboration with over 30 partner organizations throughout the US and internationally to explore how Earth observations could support decision making in areas such as health and air quality, wildland fires, climate, urban development, and transportation and infrastructure. This presentation provides an overview of the DEVELOP model of building capacity to use Earth observation data, environmental decision-making needs identified in health and air quality relevant projects, DEVELOP project case studies, commonly utilized data sources, and lessons learned. Key takeaways include best practices for project development and execution, how to balance learning with delivering impactful results for partners, and water resource relevant decisions guided by project end products.

Remote sensing↗
NASA NTRSDate not supplied

An Analysis of Extended Reality Mockups for Use in Verification: Phase 2

NASA commercial providers are increasing their use of Virtual Reality (VR) and Hybrid Reality (HR) technologies in their system development process. The use of these technologies, collectively referred to as Extended Reality (XR) technologies, has been limited to the development phase, but there have been requests to integrate VR and HR mockups into verifications. Verifications require, at minimum, a high-fidelity mockup for activities involving human participation (tests, demonstrations, inspections). HR technology shares many of the strengths but may not share some of the critical shortcomings of VR. Specifically, HR allows for integrating physical objects, such as a suit, which may be critical to evaluating a system. Adopting HR technology still has many of the same challenges as VR. Namely, there is little to no data about the validity of evaluations conducted with HR mockups, an established process, or criteria for evaluating the appropriateness of HR mockups. Because verifications are final and only need to happen once, HR mockups must be adequately vetted before being approved for use in verifications. Further hindering the adoption of these technologies is the lack of consensus on what constitutes a high-fidelity XR mockup. Even for physical mockups, there are guidelines and common criteria, but nothing has been formalized. Discussion about when an XR mockup can be used would be greatly helped by clearly defining what a high-fidelity XR mockup is and how it might be measured. The team will engage with relevant stakeholders to learn more about the benefits and challenges of adopting hybrid reality mockups for verification. The team will build upon work from Phase 1 by maturing a framework to guide decisions for evaluating XR mockups for use in verifications. The team will also conduct experimental studies to evaluate advantages and tradeoffs of hybrid/mixed reality relative to physical and virtual reality mockups. Finally, data from Phase 1 and Phase 2 will be synthesized into a set of best practices for developing and validating XR mockups for verification. We will highlight the work conducted to date in Phase 2. We will present the status of the XR for Verification Framework, a summary of best practices identified thus far, and give a synopsis of future work.

verification testing↗
DOE OSTI2020

Non-invasive in-situ imaging of interior of nuclear reactors

Techniques, systems, and devices are disclosed for non-invasive monitoring and imaging of nuclear fuel inside a nuclear reactor using muon detector arrays. In one aspect, these detector arrays are placed outside the reactor vessel or building for investigating the reactors without access to the cores, therefore the imaging process is non-invasive. In some implementation, these detector arrays measure both muon scattering and absorption to enable imaging and characterizing not only the very high-Z fuel materials, but also other materials in the reactor, thereby obtaining a more complete picture of reactor status. When applied to damaged reactors, the disclosed proposed techniques, systems, and devices, through the process of providing an image, can reveal the presence (or absence) of damage to fuel rod assemblies or puddles of molten fuel at the bottom of the containment vessel, thus providing crucial information to guide decisions about remedial actions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Overview of Salt Repository Research and Development for Spent Nuclear Fuel and High-level Nuclear Waste in the United States - 20307

This paper summarizes the current US Department of Energy Office of Nuclear Energy's (DOE-NE) work towards developing and executing a research and development program that addresses both scientific and technical issues related to long-term disposal of spent nuclear fuel (SNF) and high-level waste (HLW) in a hypothetical bedded salt based geological repository. A primary goal of the program is to create a generic Geologic Disposal Safety Assessment (GDSA) Framework that can be used to help guide decisions on siting a possible future bedded salt repository. The generic GDSA work includes analysis of the impacts of heat generation caused by decay of short-lived radionuclides. We report progress in four primary areas. First, we discuss the development and recent modifications of a research and development road-map. Second, we briefly describe an experimental approach to better understand thermal processes in salt. Third, we highlight collaborations with the international research community that leverage salt-based repository science around the world. Finally, we discuss how our findings are being used to aid in the development of a generic safety assessment for a bedded salt repository containing SNF and HLW. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Calibration and Uncertainty Estimation Using the Ensemble Kalman Filter with a Large Subsurface Flow and Transport Model - 20321

At routinely monitored groundwater contamination sites, periodically measured environmental conditions such as groundwater levels and contaminant concentrations are used to inform and confirm a conceptual site model (CSM) and guide the development and calibration of a numerical groundwater flow and transport model. The calibration of groundwater flow and transport models after each measurement (sampling) event can illuminate deficiencies in a CSM, identify areas where additional monitoring is warranted, and predict the behavior of the system to guide decision making. However, manual and automated (e.g. PEST) model calibration tools can be time-consuming and computationally expensive to implement after each sampling event. Perhaps as a result, such calibration tools generally utilize all available monitoring data simultaneously rather than sequentially assimilating monitoring data one sampling event at a time as the results from sampling become available. A more real-time data assimilation approach may reduce parameter uncertainty, quantify the value of additional monitoring data, and produce a usable model more quickly and with less effort. To mitigate the potential time-consuming aspects of manual and widely applied automated calibration techniques, a data assimilation algorithm called the ensemble Kalman filter (EnKF) was evaluated as a relatively efficient method of model calibration and uncertainty assessment via the sequential integration of monitoring data into a model. The EnKF was able to successfully and efficiently assimilate monitoring and modeling data to calibrate a complex flow and transport model at a real-world site with significant subsurface heterogeneity, uncertainty, and 12 years of monitoring data (over 4,000 individual measurements of groundwater levels and over 2,500 measurements of contaminant concentrations). Starting with an uncalibrated model data from annual sampling events were sequentially assimilated, and the resultant predication errors and estimated parameter uncertainties were tracked. After all monitoring data were assimilated, both flow and transport residuals at the end of the EnKF process were comparable to those produced via a concurrent PEST calibration effort but required fewer model simulations. Both uncertainty and prediction errors decreased over time. In a real-time application, the adequacy of the model could be assessed after each sampling event. The benefits of such a real-time approach to utilizing monitoring data include reduced costs (in the form of model updates or site characterization efforts), early flagging of possible errors in the CSM, and a reduced risk of overfitting and corresponding increased confidence in model predictions. This tool may be particularly useful compared to other calibration techniques (e.g. manual, PEST) when model runtimes are long, calibration parameters are many, or parameter uncertainty is large. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Pathways Toward Electric Mobility in Hennepin County, Minnesota

This fact sheet presents the findings from a comprehensive community engagement initiative focused on advancing equitable transportation electrification in Hennepin County. This initiative responds to the critical need for inclusive and sustainable mobility solutions in the face of rising environmental and financial challenges in the transportation sector. This project has two goals. First, to learn what each community's priorities are and share them with the city, county, and state government to inform transportation plans and projects. Second, to bridge divides between government and community, building pathways for community-guided decision making on future transportation plans.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2024

Enabling Scale-Up Through Multi-Fidelity Adaptive Computing

We present ideas from our ongoing work in adaptive computing - an optimization framework that allows us to strategically deploy various fidelity level experiments and simulations to guide decision making. The framework aims to enable uncertainty quantified scale-up of simulations and experiments, which causes increased complexity. A key feature of the framework is the integration of user-specified local model trustworthiness estimates. Adaptive sampling strategies allow us to optimally exploit the multiple fidelity level information and trustworthiness measures to arrive at the best decisions within a highly limited budget of objective function evaluations.

adaptive sampling↗