Results for “Use Cases” — Page 7

NASA NTRS2018

Assessing the Skill of Chlorophyll Forecasts: Latest Development and Challenges Ahead Using the Case of the Equatorial Pacific

Using a global ocean biogeochemical model combined with a forecast of physical oceanic and atmospheric variables from the NASA Global Modeling and Assimilation Office, we assess the skill of a chlorophyll concentrations forecast in the Equatorial Pacific for the period 2012-2015 with a focus on the forecast of the onset of the 2015 El Nino event. Using a series of retrospective 9-month hindcasts, we assess the uncertainties of the forecasted chlorophyll by comparing the monthly total chlorophyll concentration from the forecast with the corresponding monthly ocean chlorophyll data from the Suomi-National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (S-NPP VIIRS) satellite. The forecast was able to reproduce the phasing of the variability in chlorophyll concentration in the Equatorial Pacific, including the beginning of the 2015-2016 El Nino. The anomaly correlation coefficient (ACC) was significant (p less than 0.05) for forecast at 1-month (R=0.33), 8-month (R=0.42) and 9-month (R=0.41) lead times. The root mean square error (RMSE) increased from 0.0399 microgram chl L(exp -1) for the 1-month lead forecast to a maximum of 0.0472 microgram chl L(exp -1) for the 9-month lead forecast indicating that the forecast of the amplitude of chlorophyll concentration variability was getting worse. Forecasts with a 3-month lead time were on average the closest to the S-NPP VIIRS data (23% or 0.033 microgram chl L(exp -1)) while the forecast with a 9-month lead time were the furthest (31% or 0.042 microgram chl L(exp -1)). These results indicate the potential for forecasting chlorophyll concentration in this region but also highlights various deficiencies and suggestions for improvements to the current biogeochemical forecasting system. This system provides an initial basis for future applications including the effects of El Nino events on fisheries and other ocean resources given improvements identified in the analysis of these results.

El Nin↗

NASA NTRS2003

Test-Case Generation using an Explicit State Model Checker Final Report

In the project 'Test-Case Generation using an Explicit State Model Checker' we have extended an existing tools infrastructure for formal modeling to export Java code so that we can use the NASA Ames tool Java Pathfinder (JPF) for test case generation. We have completed a translator from our source language RSML(exp -e) to Java and conducted initial studies of how JPF can be used as a testing tool. In this final report, we provide a detailed description of the translation approach as implemented in our tools.

Heimdahl, Mats P. E.↗

DOE OSTI2025

Employing MACS/ViBRANT as a Surrogate MARVEL Reactor for Startup Reactivity Tuning and Supervisory Control Processes

Advanced nuclear reactors are a key part of the future of nuclear energy both in the United States and globally. They offer unique benefits for various energy-demanding applications, including use in remote locations, compact size, modular manufacturing, remote monitoring, low and/or variable power rating operation, and reliance on novel technologies to enhance operational safety. To achieve economic feasibility, advanced reactors must significantly reduce their workforces in comparison with the current fleet. Achieving this reduction will occur through reducing staff workloads using technology to achieve autonomous or semi-autonomous operations, demonstrated by comprehensive testing and validation activities. These operations will require both software and hardware platforms during the design and testing phases. While simulations are useful during the design phase, their performance can significantly deviate during actual deployment on hardware. This report presents the outcomes of a collaborative technical initiative between the U.S. Department of Energy (DOE) Microreactor Program (MRP) and Advanced Sensors and Instrumentation (ASI) Program. The collaboration utilized the Microreactor Automated Control System (MACS) hardware platform to bridge the gap between theoretical reactor design and actual startup and control operations. Two key use cases were investigated: facilitating the startup testing period and demonstrating supervisory control. The first use case details the key Microreactor Applications Research Validation and Evaluation (MARVEL) reactor startup physics testing activities conducted using the MACS platform. These activities included drum worth measurements, shutdown margin assessment, temperature feedback analysis, and scram time evaluation, as well as unique testing that would apply to the MARVEL reactor to demonstrate the testing methodologies in a low-risk environment. The MACS platform, serving as a surrogate representation of the MARVEL reactor, proved instrumental in performing these tests. The exercise revealed aspects that led to optimized processes, refined hardware design, and enhanced base software capabilities. By maturing methods and technologies in this manner, the initiative promises to reduce wasted time in the actual on-site reactor deployment effort, thereby saving significant time and resources. The second use case focuses on the development and implementation of supervisory control methods aimed at managing core tilt, which can result from asymmetrical operations or manufacturing imperfections in fuel rods or reactivity control devices. A key objective was to assess and compare the use of artificial intelligence (AI) for supervisory control. The effort aimed to define the role of supervisory control to enhance performance without risking control instability. This effort explored three distinct approaches: rules-based (RB) methods, optimization techniques, and reinforcement learning (RL) algorithms. Each approach was evaluated for its ease of implementation, its usability, and its effectiveness in responding to asymmetries in neutron flux. Comparative analysis of these approaches provided valuable insights into their applicability and effectiveness, offering a robust framework for advanced reactor operations. Together, these two use cases highlight the potential of hardware test beds to help streamline the design, operation, and control of advanced nuclear reactors. This collaborative effort underscores the importance of continued innovation and experimentation in achieving the next generation of safe, reliable, and economically viable nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2016

Toward a New Generation of Agricultural System Data, Models, and Knowledge Products: State of Agricultural Systems Science

We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.

Livestock models↗

DOE OSTI2024

SIGHT: Stacked Integration of Geospatial Hierarchical Typologies for Inferring Building Characteristics

Building characteristics are often absent in building stock datasets, particularly in regions most vulnerable to climate change and requiring effective disaster management strategies. Traditional machine learning approaches, while widely used to predict building attributes, typically neglect the spatial context of the data, leading to less accurate and reliable outcomes. To address these challenges, this paper introduces a novel algorithm, the Stacked Integration of Geospatial Hierarchical Typologies. This algorithm adapts a meta-learning framework to incorporate geospatial context into the predictive modeling process. We demonstrate the utility of the algorithm through two primary use cases: building use type classification and building height prediction. The algorithm consistently achieved or exceeded a 0.94 macro average F1 score across five geographically distinct countries for building use type classification. For building height prediction, it accurately predicted heights with a root mean square error of 3.01 in a comprehensive study using roughly 3.6 million buildings in Japan. These results underscore the benefits of integrating spatial hierarchies into machine learning models, enhancing both predictive accuracy and reliability in geospatial modeling. This work introduces a new algorithm to address the pervasive data sparsity issue in existing building stock datasets.

Adams, Daniel [ORNL] (ORCID:0000000196950577)↗

NASA NTRSDate not supplied

Shadow Evaluation of the ATD-2 Phase 3Trajectory Option Set Reroute Capability in the North Texas Metroplex

This paper presents results of NASA’s Airspace Technology Demonstration 2 Phase 3 Trajectory Option Set reroute capability designed to resolve a demand capacity imbalance along the terminal airspace boundary. We focus on Candidate flights generated during the Stormy 2020 Shadow Evaluation which was the result of using the system to passively collect predictions for each flight at the OUT event. Benefit metrics associated with the predictions are defined for the individual rerouted flight and also the system-wide savings. Candidate flights are grouped into three distinct use cases and the benefit mechanism is explained for each use case along with illustrative data. Analysis of the different use cases shed light on the underlying causes of the reroute opportunities. Lessons learned from the Stormy 2020 Shadow Evaluation including the importance of reroutes during recovery from Severe Weather Avoidance Programs and also reroutes in the absence of terminal airspace constraints will be incorporated into the Phase 3 Field Evaluation in 2021 to maximize reroute opportunities.

Airspace Technology Demonstration 2↗

NASA NTRSDate not supplied

Preliminary Study of Alternative Propellant Performance for a CNTR

Centrifugal Nuclear Thermal Propulsion is an advanced propulsion concept engine which utilizes a bubble through nuclear reactor to directly heat the propellent, containing the liquid fuel in rotating cylinders using centrifugal force. Past studies have almost exclusively focused on hydrogen propellant configurations of the engine with a theoretical performance of 1800 seconds specific impulse. Recent interest in alternative propellants has created a use case for using storable propellants at the cost of lower performance. Most notably ammonia, methane, and propane. The object of this work is to down select viable alternative propellants for use in a CNTR.

Mitchell Schroll↗

NASA NTRS2022

Enabling Innovative Research on the International Space Station to Solve the Challenges of A Human Mission to Mars: Results of the ISS4Mars International Workshops 2020–2021

During the ISS4Mars workshops in 2020–2021, personnel from the International Space Station (ISS) partner agencies convened to reflect on scenarios for how the ISS could be used and its operations possibly modified to simulate aspects of a human mission to Mars. Scientific leaders, operations experts, crewmembers, managers, and flight surgeons discussed the five hazards of human spaceflight—gravity transitions, radiation, isolation and confinement, distance from Earth, and hostile closed environments—and considered how an ISS-based analog of Mars transit could benefit assessments and mitigations of these hazards. A focused writing team then discussed the advantages and disadvantages of each approach identified by the workshop participants before developing a set of eight use cases to consider the feasibility of implementing on the ISS. The writing team also identified the prerequisites needed, including ground analog studies simulating a mission to Mars required to verify measurements and procedures, before testing could begin on the ISS. Five of the use cases were considered feasible to assess in simulations using an ISS-based analog of Mars transit if some ground rules and assumptions were met. These five use cases were Earth-independent medical operations, Earth-independent integrated operations, life support and food for a one year duration, lower-body negative pressure as a countermeasure against the effects of exposure to microgravity, and fitness levels after landing. In addition, three more extensive interventions—extended Mars surface operations, a small-volume transit analog, and artificial gravity—were deemed unfeasible for testing on the ISS. Experience gained from the five use cases executed on the ISS may help answer some of the questions in the deferred scenarios, or it may be possible to complete them on another platform (e.g. commercial space station, lunar habitat). Simulating conditions during a Mars mission on the ISS will afford higher fidelity for assessing multiple integrated hazards of human spaceflight, however, ground analogs of Mars missions can be used to ensure effective measures and experimental design before testing begins on the ISS. The strategic concepts refined as part of these workshops were brought to a multilateral forum, Mulitlateral Human Research Planel for Exploration (MHRPE), where ISS partner agencies are now discussing implementation plans to provide new opportunities to use the ISS to prepare for deep space exploration over the coming decade. In this publication we present a summary of the international strategic plans for future research that will enable operations, software, and countermeasures to be developed that will reduce the risk to humans during future crewed missions to Mars.

Human space exploration↗

NASA NTRS1988

Transfer impedance measurements of the space shuttle Solid Rocket Motor (SRM) joints, wire meshes and a carbon graphite motor case

Using three different current injection methods and a simple voltage probe, transfer impedances for Solid Rocket Motor (SRM) joints, wire meshes, aluminum foil, Thorstrand and a graphite composite motor case were measured. In all cases, the surface current distribution for the particular current injection device was calculated analytically or by finite difference methods. The results of these calculations were used to generate a geometric factor which was the ratio of total injected current to surface current density. The results were validated in several ways. For wire mesh measurements, results showed good agreement with calculated results for a 14 by 18 Al screen. SRM joint impedances were independently verified. The filiment wound case measurement results were validated only to the extent that their curve shape agrees with the expected form of transfer impedance for a homogeneous slab excited by a plane wave source.

Papazian, Peter B.↗

DOE OSTI2024

Leveraging NREL's ResStock & ComStock Dataset to Evaluate Building Stock Electrification: Preprint

Residential and commercial buildings accounted for 40% of U.S. energy consumption in 2022 and represent a significant opportunity for decarbonization through energy efficiency and electrification, and for grid planning. Building stock energy modeling is a powerful tool that can evaluate what-if scenarios as utilities, municipalities, policymakers, building owners and others work towards equitable building decarbonization and climate goals. This presentation will highlight several high-impact use cases of the National Renewable Energy Laboratory (NREL)'s highly granular, bottom-up building stock energy modeling tools, ResStock and ComStock. These use cases cover a wide range of project scale, from neighborhood electrification analysis and municipality long-term energy planning, to state energy code development and national policy evaluation. This presentation will showcase specific real-world applications for which ResStock and ComStock have been utilized across the country, including California codes and standards cost-effectiveness analysis, New York City affordable housing electrification cost gap analysis, and California targeted electrification and gas decommissioning analysis. For each use case, this presentation will illustrate how ResStock and ComStock played a crucial role in accurately characterizing regional building stocks, providing discrete and aggregated end-use load shapes, and calculating lifecycle consumption, emissions, and costs for a variety of building electrification strategies and scenarios. Finally, this presentation will demonstrate how the data provided by ResStock and ComStock can help unlock significant outcomes for these use cases, including but not limited to, customer bill impact, incentive and program design, and energy equity analyses.

building stock modeling↗

NASA NTRSDate not supplied

Identification and Development of Coordination Procedures Between Upper Class E Traffic Management (ETM) and Surrounding Air Traffic Operations

A recent interest in novel, non-traditional vehicles / missions that plan to operate in Upper Class E (UCE) airspace at or above 60,000 ft has led to efforts by NASA, FAA and the stakeholder communities to research and develop a new concept called Upper Class E Traffic Management (ETM). ETM concept proposes to handle the influx of diverse traffic mix around FL600 and above, utilizing a new traffic management infrastructure, supported by federated service suppliers that are developed by the community stakeholders, for coordinating, monitoring, and executing vehicle operational intent in a designated airspace called ETM Cooperative Area (CA). ETM vehicles are generally expected to reach and operate in ETM CA by first transiting through Class A airspace and potentially through UCE airspace that sits outside of ETM CA. In this paper, a set of use cases have been identified and step-by-step procedures have been developed to handle nominal transitions of ETM vehicles between these operational areas, as well as additional use cases and procedures for authorization and termination of ETM CAs in Class A and/or UCE airspace. The overall research effort in this paper has revealed potential challenges and open questions related to these use cases, especially for the interactions between ETM CA and UCE in both vehicle transition and ETM CA authorization scenarios. The use cases and procedures developed in this paper will inform future ETM integration efforts, as well as research and development into decision support tools needed for the integration.

Upper Class E Traffic Management (ETM)↗

DOE OSTI2024

Resilient and Cost-Effective Hybrid Li-Ion Battery Energy Storage System for Sites with Solar Generation and Electric Vehicle (EV) Charging (CRADA Final Report, CRD-19-00799)

The batteries of an energy storage system designed for multiple use-cases are traditionally selected to withstand the highest rate at which a battery is discharged relative to its maximum capacity (C-rate) and cycling requirements of the most intense use-case. However, this is not cost-effective given that the price of the batteries is strongly correlated to C-rate and cyclability. We propose to establish design guidelines for a hybrid energy storage system and test an edge controller that uses high-power and high-energy batteries for high- cyclability use cases such as frequency regulation and electric vehicle (EV) charging and low-cost batteries for low-power and low-cyclability use cases such as summer peak loads. The three main objectives of this proposal are (i) establishing sizing guidelines for such a hybrid storage system, (ii) installing a hybrid storage system in the Energy Systems Integration Facility (ESIF) sized based on those guidelines, and (iii) testing an edge controller specific for the system through hardware tests.

14 SOLAR ENERGY↗

NASA NTRS2017

XTCE (XML Telemetric and Command Exchange) Standard Making It Work at NASA. Can It Work For You?

The XML Telemetric and Command Exchange (XTCE) standard is intended as a way to describe telemetry and command databases to be exchanged across centers and space agencies. XTCE usage has the potential to lead to consolidation of the Mission Operations Center (MOC) Monitor and Control displays for mission cross-support, reducing equipment and configuration costs, as well as a decrease in the turnaround time for telemetry and command modifications during all the mission phases. The adoption of XTCE will reduce software maintenance costs by reducing the variation between our existing mission dictionaries. The main objective of this poster is to show how powerful XTCE is in terms of interoperability across centers and missions. We will provide results for a use case where two centers can use their local tools to process and display the same mission telemetry in their MOC independently of one another. In our use case we have first quantified the ability for XTCE to capture the telemetry definitions of the mission by use of our suite of support tools (Conversion, Validation, and Compliance measurement). The next step was to show processing and monitoring of the same telemetry in two mission centers. Once the database was converted to XTCE using our tool, the XTCE file became our primary database and was shared among the various tool chains through their XTCE importers and ultimately configured to ingest the telemetry stream and display or capture the telemetered information in similar ways.Summary results include the ability to take a real mission database and real mission telemetry and display them on various tools from two centers, as well as using commercially free COTS.

CCSDS↗

DOE OSTI2024

EMT data generation

The integration of inverter-based resources (IBRs) in power systems is accelerating, bringing with it significant benefits such as reduced greenhouse gas emissions, improved grid resilience, and increased energy independence. Despite these advantages, the widespread adoption of IBRs introduces several challenges, including issues related to grid stability, increased operational complexity, and the need for updated regulatory frameworks. To address these challenges, IEEE released Standard 2800 in 2022, which sets forth the necessary interconnection capabilities and performance criteria for IBRs connected to transmission and sub-transmission systems. This standard outlines the performance requirements to ensure the reliable integration of IBRs into the bulk power system. Furthermore, in 2023, the North American Electric Reliability Corporation (NERC) published a reliability guideline for electromagnetic transient (EMT) modeling of BPS-connected IBRs. This guideline provides recommendations for developing EMT model requirements, performing model quality checks, and implementing verification practices specifically for EMT models representing BPS-connected inverter-based resources in reliability studies conducted by transmission planners and planning coordinators. These standards and guidelines have a profound impact on EMT studies for transmission networks, influencing system stability analyses, grid recovery and resynchronization processes, fault ride-through evaluations, protection and coordination strategies, advanced control methodologies, and the inclusion of IBRs in transient models of transmission networks. As a result, the generation of EMT data is crucial for conducting various transient-based studies to understand the impact of IBRs. EMT data generation use cases serve as the basis for scenarios in event detection and identification use cases, providing comprehensive details about EMT data generation for transmission grids with inverter-based resources. These use cases supply sufficient training and validation datasets for subsequent EMT analysis algorithms.

Xia, Qianxue↗

NASA NTRSDate not supplied

CLINICAL DECISION SUPPORT: PATH TO FUNCTIONAL REQUIREMENTS

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

clinical decision support↗

NASA NTRSDate not supplied

Clinical Decision Support: Path to Functional Requirements

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

Clinical decision support↗

NASA NTRSDate not supplied

The AIRNOISE-UAM Tool and its Application to ATM-X

The noise disruption caused by Urban Air Mobility (UAM) vehicles will be a major factor in public acceptance of UAM. The noise exposure caused by fixed-wing aircraft and helicopters is predicted using Aviation Environment and Design Tool (AEDT) software at the airport. The base noise is calculated by interpolation or extrapolation of Noise-Power-Distance (NPD) database in the AEDT. In this presentation, a new noise prediction tool "AIRNOISE-UAM" is developed with a new NPD database for eVTOL vehciles in collaboration with a RVLT team. The noise exposure results have been verified with those from AEDT. Lastly, we demonstrate two use cases of AIRNOISE-UAM to the ATM-X project. The first use case is to develop noise exposure maps for FAA UAM compliance planning. The sceond use case is to develop noise-aware flight route planning algorithm.

Urban Air Mobility↗

NASA NTRS2015

Deriving Earth Science Data Analytics Requirements

Data Analytics applications have made successful strides in the business world where co-analyzing extremely large sets of independent variables have proven profitable. Today, most data analytics tools and techniques, sometimes applicable to Earth science, have targeted the business industry. In fact, the literature is nearly absent of discussion about Earth science data analytics. Earth science data analytics (ESDA) is the process of examining large amounts of data from a variety of sources to uncover hidden patterns, unknown correlations, and other useful information. ESDA is most often applied to data preparation, data reduction, and data analysis. Co-analysis of increasing number and volume of Earth science data has become more prevalent ushered by the plethora of Earth science data sources generated by US programs, international programs, field experiments, ground stations, and citizen scientists.Through work associated with the Earth Science Information Partners (ESIP) Federation, ESDA types have been defined in terms of data analytics end goals. Goals of which are very different than those in business, requiring different tools and techniques. A sampling of use cases have been collected and analyzed in terms of data analytics end goal types, volume, specialized processing, and other attributes. The goal of collecting these use cases is to be able to better understand and specify requirements for data analytics tools and techniques yet to be implemented. This presentation will describe the attributes and preliminary findings of ESDA use cases, as well as provide early analysis of data analytics toolstechniques requirements that would support specific ESDA type goals. Representative existing data analytics toolstechniques relevant to ESDA will also be addressed.

data analytics↗