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At least 883 records · Page 49

Clinical Decision Support Software: Modeling and Capabilities

With its distance from Earth and communication delays, exploration space flight will place new demands for crew autonomy. Crewmembers operating during such missions require a dedicated Clinical Decision Support System (CDSS) that enhances their earth independence by augmenting their knowledge, skills, and abilities in different medical scenarios. A CDSS is a software application that must function optimally in diverse and varied scenarios (while interfacing with and providing actionable information to appropriate vehicle systems) to augment crew performance by enhancing or adding knowledge, skills, and abilities that preserve health and wellness and ultimately helping to ensure mission success. In addition, the software tool should provide various functions and computational models to meet the demands of astronauts beyond low earth orbit.

B Russell↗

Digital Tools for the Preventive Conservation of Built Heritage: The Church of Santa Ana in Seville

Historic Building Information Modelling (HBIM) plays a pivotal role in heritage conservation endeavours, offering a robust framework for digitally documenting existing structures and supporting conservation practices. However, HBIM’s efficacy hinges upon the implementation of case-specific approaches to address the requirements and resources of each individual asset and context. This paper defines a flexible and generalisable workflow that encompasses various aspects (i.e., documentation, surveying, vulnerability assessment) to support risk-informed decision making in heritage management tailored to the peculiar conservation needs of the structure. This methodology includes an initial investigation covering historical data collection, metric and condition surveys and non-destructive testing. The second stage includes Finite Element Method (FEM) modelling and structural analysis. All data generated and processed are managed in a multi-purpose HBIM model. The methodology is tested on a relevant case study, namely, the church of Santa Ana in Seville, chosen for its historical significance, intricacy and susceptibility to seismic action. The defined level of detail of the HBIM model is sufficient to inform the structural analysis, being balanced by a more accurate representation of the alterations, through linked orthophotos and a comprehensive list of alphanumerical parameters. This ensures an adequate level of information, optimising the trade-off between model complexity, investigation time requirements, computational burden and reliability in the decision-making process. Field testing and FEM analysis provide valuable insight into the main sources of vulnerability in the building, including the connection between the tower and nave and the slenderness of the columns.

Chaves, Estefanía↗

ATM TestBed 2021 Simulating & Testing for the Future of Flight

TestBed is a NASA facility that not only connects geographically distributed tools without having to worry about obsolescence, but it is also a comprehensive one-stop-access simulation framework that allows researchers to develop and test solutions to current and future challenges more quickly by addressing development pain points, while also facilitating the connection of simulators and new tools to a variety of organizations, allowing for faster testing and development. Specifically, TestBed enables one to better characterize the impact of a new technology under development and to communicate its impact to stakeholders.

Air Traffic Management↗

Developing an Automated Uncertainty Quantification Tool to Improve Watershed-Scale Predictions of Water and Nutrient Cycling

Managing the flow of water, nutrients, and contaminants in watersheds is vital to addressing pressing issues related to water scarcity, access to clean drinking water, energy production, resilience to natural and anthropogenic perturbations, and ecological restoration. Decisions about the management of watersheds critically depend on the accuracy with which the flow of water and chemicals through the watershed can be predicted by computer models. Prediction uncertainty can be reduced by matching the model to data, which are collected in the field at great expense. The contribution of watershed characterization data to reducing uncertainty of relevant model predictions can be evaluated in a so-called data-worth analysis, which provides transparent, quantitative metrics about a data set’s value for the support of relevant watershed management objectives. To achieve this goal, we developed a software package that implements the data-worth analysis approach for use with state-of-the-art watershed models. The purpose of the proposed data-worth analysis is to help decision-makers allocate resources for watershed characterization such that the uncertainty in model predictions can be significantly reduced, which leads to better, more effective management decisions. At the same time, watershed characterization costs can be reduced. The specific technical objectives of this SBIR/STTR Phase II project were to develop a framework and associated software toolsets that implement the uncertainty quantification and data-worth analysis approach for use with state-of-the-art watershed models. This goal was achieved by (A) developing a user-friendly, robust software package that is accessible to a wide audience, including watershed managers, policy-makers, and public stakeholders; (B) by demonstrating application of the prototype on several use cases that are representative of complex watershed management challenges spanning a range of scales and that consider different open-source, DOE-based codes and other modeling platforms; and (C) by gathering information about the needs and requirements from potential users to help guide future developments, ensuring that the final product will be commercially viable. The developed software consists of a graphical user interface that guides the user through a sequence of analysis steps, supported by toolsets that leverage state-of-the-art computational simulation-optimization capabilities. A prototype of the software runs on multiple platforms (PC, Mac, multi-processor Linux environment), is linked to diverse watershed simulators (e.g., ECOSYS, TOUGH2, TOUGHREACT, Amanzi-ATS), performs multiple analysis tasks (predictive simulations, sensitivity analysis, uncertainty analysis, automatic parameter estimation, and data-worth analysis, multicomponent geothermometry), and is readily extensible to include external simulators and analysis tools. The software is being commercialized and will be continually updated to address user needs.

58 GEOSCIENCES↗

Selection of Vadose Zone Flow and Transport Properties with Gravel Fraction Corrections for the Hanford Site Composite Analysis and Cumulative Impact Evaluation

This environmental calculation file (ECF) is a compilation of hydrologic and radiological/chemical properties to be used for the updated Hanford Site Composite Analysis (CA) and Cumulative Impact Evaluation (CIE) vadose zone (VZ) modeling. The CA will provide an all-pathways dose projection to a hypothetical future member of the public from all planned low-level radioactive waste disposal facilities and potential contributions from all other projected end-state sources of radioactive material left at the Hanford Site following site closure. Its primary purpose is to support the decision-making process of the U.S. Department of Energy (DOE) under DOE O 435.1 Chg 1, Radioactive Waste Management, related to managing low-level waste disposal facilities at the Hanford Site. The CIE evaluates the effects of cleanup decisions regarding groundwater quality in the Hanford Site Central Plateau (DOE/RL-2018-69, Cumulative Impact Evaluation Technical Approach Document). Due to the complexity and large number of waste sites in source operable units (OUs), the computational tools used for the CIE must be capable of representing a range of site conditions and source terms in the VZ while also efficiently computing the impact that cleanup decisions have on the underlying aquifer. Waste-site proximity between and within source OUs has resulted in contaminants commingling in the vadose and saturated zones in complex ways. Plume commingling requires cleanup decisions to be evaluated considering the surrounding waste sites and existing groundwater contamination, therefore demonstrating the need to evaluate cumulative impacts from the VZ to groundwater.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Integration Process for the Habitat Demonstration Unit

The Habitat Demonstration Unit (HDU) is an experimental exploration habitat technology and architecture test platform designed for analog demonstration activities The HDU project has required a team to integrate a variety of contributions from NASA centers and outside collaborators and poses a challenge in integrating these disparate efforts into a cohesive architecture To complete the development of the HDU from conception in June 2009 to rollout for operations in July 2010, a cohesive integration strategy has been developed to integrate the various systems of HDU and the payloads, such as the Geology Lab, that those systems will support The utilization of interface design standards and uniquely tailored reviews have allowed for an accelerated design process Scheduled activities include early fit-checks and the utilization of a Habitat avionics test bed prior to equipment installation into HDU A coordinated effort to utilize modeling and simulation systems has aided in design and integration concept development Modeling tools have been effective in hardware systems layout, cable routing and length estimation, and human factors analysis Decision processes on the shell development including the assembly sequence and the transportation have been fleshed out early on HDU to maximize the efficiency of both integration and field operations Incremental test operations leading up to an integrated systems test allows for an orderly systems test program The HDU will begin its journey as an emulation of a Pressurized Excursion Module (PEM) for 2010 field testing and then may evolve to a Pressurized Core Module (PCM) for 2011 and later field tests, depending on agency architecture decisions The HDU deployment will vary slightly from current lunar architecture plans to include developmental hardware and software items and additional systems called opportunities for technology demonstration One of the HDU challenges has been designing to be prepared for the integration of presently unanticipated systems Results of the HDU field tests will influence future designs of habitat systems.

Gill, Tracy↗

Crop-CASMA - A Web GIS Tool for Cropland Soil Moisture Monitoring and Assessment Based on SMAP Data

Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA- a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.

Zhengwei Yang↗

Crop-CASMA - A Web GIS Tool for Cropland soil moisture Monitoring and Assessment Based on SMAP Data

Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA - a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.

Reichle, Rolf H.↗

A review on recent machine learning applications for imaging mass spectrometry studies

Imaging mass spectrometry (IMS) is a powerful analytical technique widely used in biology, chemistry, and materials science fields that continue to expand. IMS provides a qualitative compositional analysis and spatial mapping with high chemical specificity. The spatial mapping information can be 2D or 3D depending on the analysis technique employed. Due to the combination of complex mass spectra coupled with spatial information, large high-dimensional datasets (hyperspectral) are often produced. Therefore, the use of automated computational methods for an exploratory analysis is highly beneficial. The fast-paced development of artificial intelligence (AI) and machine learning (ML) tools has received significant attention in recent years. These tools, in principle, can enable the unification of data collection and analysis into a single pipeline to make sampling and analysis decisions on the go. There are various ML approaches that have been applied to IMS data over the last decade. Here, in this review, we discuss recent examples of the common unsupervised (principal component analysis, non-negative matrix factorization, k-means clustering, uniform manifold approximation and projection), supervised (random forest, logistic regression, XGboost, support vector machine), and other methods applied to various IMS datasets in the past five years. The information from this review will be useful for specialists from both IMS and ML fields since it summarizes current and representative studies of computational ML-based exploratory methods for IMS.

47 OTHER INSTRUMENTATION↗

Advanced Weather Awareness and Reporting Enhancements

AWARE (Aviation Weather Awareness and Reporting Enhancements) was a NASA Cooperative Research and Development program conducted jointly by Rockwell Scientific, Rockwell Collins, and NASA. The effort culminated in an enhanced weather briefing and reporting tool prototype designed to integrate graphical and text-based aviation weather data to provide clear situational awareness in the context of a specific pilot, flight and equipment profile. The initial implementation of AWARE was as a web-based preflight planning tool, specifically for general aviation pilots, who do not have access to support such as the dispatchers available for commercial airlines. Initial usability tests showed that for VFR (Visual Flight Rules) pilots, AWARE provided faster and more effective weather evaluation. In a subsequent formal usability test for IFR (Instrument Flight Rules) pilots, all users finished the AWARE tests faster than the parallel DUAT tests, and all subjects graded AWARE higher for effectiveness, efficiency, and usability. The decision analysis basis of AWARE differentiates it from other aviation safety programs, providing analysis of context-sensitive data in a personalized graphical format to aid pilots/dispatchers in their complex flight requirements.

Busquets, Anthony M.↗

The ICESat-2 Mission: Land, Ocean, and Inland Water Data Products for Middle and Low Latitude Science and Applications

NASA’s Ice, Cloud, and Land Elevation Satellite (ICESat-2) is a polar orbiting mission, launched on September 15, 2018, with over two years of nearly continuous observations. The sole instrument onboard is the Advanced Topographic Laser Altimeter System (ATLAS), a micropulse, high repetition rate, six-beam, 532 nm Lidar with photon-counting technology. Although designed primarily for detecting height changes in ice caps and sea ice in the high latitudes, it continuously observes all terrain in its track including middle and low latitude regions as well, during approximately 15 orbits per day. The official ICESat-2 products include not only cryosphere data but also global high resolution parameters associated with tree canopies, land surface, oceans, and over 1.5 million inland water bodies consisting of lakes, rivers and coastal waters. This presentation provides an overview and the status of the ICESat-2 mission including: i) a summary of the salient technological features and orbit design, ii) the official ICESat-2 science data products for ice, vegetation canopy, ocean sea level, and inland water including several examples in the middle and low latitudes, iii) a list of NASA sponsored software tools for globally browsing the two year archive and for processing both the raw data and the official ICESat-2 geophysical data products, and iv) avenues for interested users to connect with the ICESat-2 Applications Program for answering questions and assistance in possibly using ICESat-2 data in your particular science or application. The overall goal is to facilitate the use of ICESat-2 data not only for science investigations but also for improved decision support applications with societal benefit. Additional ICESat-2 information, documentation and data products are publicly available at https://nsidc.org/data/icesat-2

ICESat-2↗

Planning Near-Term Tasks for the Development of Advanced Reactor Mechanistic Source Term Modeling and Simulation Tools

To assist both the advanced reactor industry and U.S. Nuclear Regulatory Commission (NRC) in the pursuit of reactor design and licensing, the U.S. Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has established a mechanistic source term (MST) research project under the auspices of the Application Drivers technical area. The MST research project is a collaboration between Argonne National Laboratory (Argonne) and Sandia National Laboratories (SNL) with a high-level objective to coordinate the development of comprehensive advanced reactor MST mod/sim capabilities to support risk-informed design and licensing decisions. As part of this effort, an MST mod/sim development pathway was developed in FY21, which outlines the high-level objectives and near-term tasks necessary to achieve the project objectives. Since publication of the development pathway, Argonne and SNL have been addressing the “near-term tasks” outlined in the report. The current provides a status update of the progress achieved in the fourth quarter of FY21. The report structure follows that of ref and is divided by advanced reactor type: High temperature gas reactor (HTGR), molten salt reactor (MSR) including fluoride salt-cooled high temperature reactor (FHR), and sodium fast reactor (SFR). Each section reviews the near-term tasks associated with the reactor type, current progress, and future plans. The near-term tasks associated with consequence modeling are reviewed in an upcoming work by SNL.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Washington Health & Air Quality: Quantifying Air Quality Parameters and Validating Air Pollution Sources Impacting the Health of Puget Sound Residents Through the Use of NASA and ESA Remote Sensing Data

In the Puget Sound region of Washington, high levels of air pollutants put residents’ health at risk by increasing their likelihood of developing critical respiratory conditions. This project used remotely-sensed data to investigate aerosol optical depth (AOD) from NASA satellite sensors including the Terra and Aqua MODerate Resolution Imaging Spectroradiometer (MODIS) and European Space Agency Copernicus Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI). The team visualized the most recent data in Google Earth Engine (GEE) API to display air pollution trends in Washington State, which will support the Puget Sound Clean Air Agency’s (PSCAA) decision-making processes. The team performed linear regressions using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to form a relationship between ground-level microscopic particles (PM2.5) and AOD in the Puget Sound region, validating the relationship using concentration readings taken from Environmental Protection Agency (EPA) air quality monitors. The team utilized estimated PM2.5 and other satellite data to produce a web-based tool and to evaluate the effectiveness of using such a tool for near real-time air quality monitoring within a particular region. The team found that the tool provides useful supplementary data that fills in the gaps of the PSCAA’s air monitoring network.

Health & Air Quality↗

Washington Health & Air Quality: Quantifying Air Quality Parameters and Validating Air Pollution Sources Impacting the Health of Puget Sound Residents Through the Use of NASA and ESA Remote Sensing Data

In the Puget Sound region of Washington, high levels of air pollutants put residents’ health at risk by increasing their likelihood of developing critical respiratory conditions. This project used remotely-sensed data to investigate aerosol optical depth (AOD) from NASA satellite sensors including the Terra and Aqua MODerate resolution Imaging Spectroradiometer (MODIS) and European Space Agency Copernicus Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI). The team visualized the most recent data in Google Earth Engine (GEE) API to display air pollution trends from Northern California to British Columbia, which will support the Puget Sound Clean Air Agency’s (PSCAA) decision-making processes. The team performed linear regressions using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to form a relationship between ground-level microscopic particles (PM2.5) and AOD in the Puget Sound region, validating the relationship using concentration readings taken from Environmental Protection Agency (EPA) air quality monitors. The team utilized estimated PM2.5 and other satellite data to produce a web-based tool and to evaluate the effectiveness of using such a tool for near real-time air quality monitoring within a particular region. The team found that the tool provides useful supplementary data that fills in the gaps of the PSCAA’s air monitoring network.

Health & Air Quality↗

2018 NISAR Applications Workshop: Forest and Disturbance; Workshop Report

Forest lands cover the globe and are important sources for providing ecosystem services including: carbon sequestration, biodiversity, timber, air and water quality. As such, counties around the world have dedicated programs for managing them. Accurate and timely information concerning the status of these forests (moisture, biomass, disturbance type, etc.) is essential to those Nations’ human and ecological health as well as economy. The joint NASA/US Forest Service workshop focused on arming forest land managers with observations and remote sensing information from the upcoming NASA-ISRO (Indian Space Research Organization) SAR (Synthetic Aperture Radar) (NISAR) satellite mission (expected to launch early 2022). Participants included representatives from different US Federal Agencies, private sector, and non-governmental organizations (NGO) that are key players in facilitating integration of Earth Observations (EO) into forest management and decision support workflows. They included scientists, technicians, and program managers with a responsibility for data acquisition and exploitation such as product development, delivery, and use, and capacity building. Discussions were held over two days to convey the broader forest and disturbance community information needs for various representative participants and programs and to facilitate the delivery of NISAR mission geospatial products and observational capabilities. Case studies were presented to demonstrate the current state of practice in the use of SAR remote sensing for applications of direct importance to forest and disturbance land management community. Eleven organizations presented their information requirements in response to a set of questions provided by the NASA team, then the NASA team responded by describing the degree to which NISAR could meet these requirements. Discussion ensued about needed data product specifications to increase utility (e.g., projection, latency, etc.), tools and capacity building. The general findings of this workshop were that (a) NISAR observations will be particularly useful to the global forest carbon and disturbance monitoring applications, but that certain data product design decisions (projections and radiometric and terrain corrections) need to be considered to increase utility; b) the biomass and disturbance detection algorithms meet many of the community needs, however there are other information products of value (e.g., soil moisture or disturbance classification, not just detection) and all products should be compliant with existing community standards for reporting uncertainty; c) providing SAR education to the community will be key specifically thinking about putting the information first and the SAR theory second, providing a simple guide of standard data processing steps (e.g., dB (decibel) to power conversion and speckle filtering); d) the community needs a user-friendly interface for finding free, archived data over their geographic regions of interest; e) user-friendly tools that connect to open-sources GIS (Global Information System) software (e.g., QGIS (Quantum GIS)) that include a graphical user interface (GUI) for SAR processing that enables both download and cloud processing. To integrate these findings and prepare the community before NISAR launches, it was suggested that there be a dedicated NISAR Forest and Disturbance Applications Working Group (as per the specifications in the NISAR Utilization Plan). After launch, it was decided that the community continue capacity building activities.

Stavros, Natasha↗

FracML: A Machine Learning Based Tool to Quantify Reservoir Scale Fracture Network for CO2 Storage

Poster on “FRACML: A Machine Learning Based Tool to Quantify Reservoir Scale Fracture Network for CO2 Storage” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. The accurate characterization of subsurface fracture networks is essential for the secure operation of carbon capture, utilization, and storage (CCUS) projects. A thorough understanding of the spatial distribution of subsurface faults and fractures is crucial for predicting CO2 plume evolution and minimizing risks such as potential leakage into overlying formations or induced seismicity. In this context, robust fracture network quantification plays a pivotal role in reservoir management, providing the data necessary to fine-tune operational parameters, and ensure the environmental and economic viability of CCUS projects. As part of the U.S. Department of Energy’s SMART (Science-informed Machine Learning for Accelerating Real-time Decisions in Subsurface Applications) initiative, we focused on the development and application of a machine learning-based tool (FRACML) designed to quantify and map fracture networks using real-world (non-synthetic) data from an active CO2 injection site. Our objective is to demonstrate the utility of this tool in improving operational efficiency and safety across CCUS sites.

artifical intelligence / machine learning (AI/ML)↗

RETRO RX

RETRO Rx is an R&D 100 Gold Award-winning suite of tools that provides a new class of analytics in the space between traditional epidemiological models and unanalyzed spreadsheets of data. Unlike traditional models, these tools provide analysts, scientists, practitioners, and decision makers a way to easily and effectively do sophisticated analyses using a simple user interface. AIDO guides users at the early stages of a disease outbreak by comparing the current parameters to historic outbreaks. RED Alert constructs a broad historical picture of disease incidence (recent outbreak included) to detect disease reemergence at its earliest stages, locally and globally. RETRO Rx compiles data and presents analysis in a clear, concise visual format to support disease mitigation and prevention planning. Both are available currently as web-based apps. A prototype of the RED Alert mobile app with enhanced functionality is available for beta testing and AIDO mobile app development is planned.

59 BASIC BIOLOGICAL SCIENCES↗

Technology Assessments within NASA's Integrated Technology Assessment Center

NASA's Advanced Space Transportation Program (ASTP) founded the Integrated Technology Assessment Center (ITAC) to provide a comprehensive, systematic approach to identify long-term technology needs, to quantify payoffs for technology investments, and to assess the progress of ASTP-sponsored technology programs in the hypersonics/Earth-to-orbit area. To accomplish these goals, the ITAC has assembled an experienced team representing a broad sector of the aerospace community and developed a systematic assessment process complete with supporting tools. In the ITAC approach, concepts for transportation systems are first selected based on relevance to the ASTP. Models of these concepts are then developed and data on advanced technologies are collected. Projections of key technology characteristics with respect to the specific concepts of interest are made. Both the models and technology projections are then fed into the ITAC's probabilistic systems analysis framework. The probabilistic outputs are weighed against metrics of interest to ASTP and a multivariate decision making process is used to provide inputs for technology prioritization within the ASTP. At present, the ITAC program is working to evaluate a variety of technologies for three two-stage hypersonic vehicle concepts. Concepts include an all rocket, vertical take off-horizontal landing (VTHL) system, a horizontal take-off-horizontal landing (HTHL) RBCC-propelled first stage/all rocket second stage system, and an HTHL turbine-based first stage/all rocket second stage system. This paper will provide a status update of the ITAC program including current results and plans.

Taylor, J. L.↗