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At least 613 records · Page 34

All sources NASA NTRS DOE OSTI

NASA NTRS2020

Land management and climate change determine second‐generation bioenergy potential of the US Northern Great Plains

Bioenergy with carbon capture and storage (BECCS) has been proposed as a potential climate mitigation strategy raising concerns over trade‐offs with existing ecosystem services. We evaluate the feasibility of BECCS in the Upper Missouri River Basin (UMRB), a landscape with diverse land use, ownership, and bioenergy potential. We develop land‐use change scenarios and a switchgrass (Panicum virgatum L.) crop functional type to use in a land‐surface model to simulate second‐generation bioenergy production. By the end of this century, average annual switchgrass production over the UMRB ranges from 60 to 210 Tg dry mass/year and is dependent on the Representative Concentration Pathway for greenhouse gas emissions and on land‐use change assumptions. Under our simple phase‐in assumptions this results in a cumulative total production of 2,000–6,000 Tg C over the study period with the upper estimates only possible in the absence of climate change. Switchgrass yields decreased as average CO2 concentrations and temperatures increased, suggesting the effect of elevated atmospheric CO2 was small because of its C4 photosynthetic pathway. By the end of the 21st century, the potential energy stored annually in harvested switchgrass averaged between 1 and 4 EJ/year assuming perfect conversion efficiency, or an annual electrical generation capacity of 7,000–28,000 MW assuming current bioenergy efficiency rates. Trade‐offs between bioenergy and ecosystem services were identified, including cumulative direct losses of 1,000–2,600 Tg C stored in natural ecosystems from land‐use change by 2090. Total cumulative losses of ecosystem carbon stocks were higher than the potential ~300 Tg C in fossil fuel emissions from the single largest power plant in the region over the same time period, and equivalent to potential carbon removal from the atmosphere from using biofuels grown in the same region. Numerous trade‐offs from BECCS expansion in the UMRB must be balanced against the potential benefits of a carbon‐negative energy system.

climate change↗

NASA NTRSDate not supplied

DAA Use Case for Auto Cargo m:N Operations

A detect and avoid use-case was developed to highlight detect and avoid issues associated with m:N operations in the auto cargo domain. This work is being done in conjunction with industry partners and developed for the Operational Scenario and Environmental Description (OSED) for RTCA SC-228. The detect and avoid function is critical, required technology for unmanned aircraft to operation in the national airspace. RTCA SC-228 has published MOPS (phase 1 & 2) detailing the requirements and methods of compliance. This work will help address additional operational aspects of how/when DAA will be employed by unmanned systems. Specifically, this work focuses on “auto cargo” operations. Auto cargo, in this context, refers to regularly scheduled cargo-size aircraft that are flown remotely. The Remote Pilot In Command (RPIC), in this case, is responsible for multiple aircraft, flown simultaneously. The use-case details the use of DAA in this context, the potential issues and gaps that exist.

multi-vehicle control↗

NASA NTRSDate not supplied

Detecting Risk and Anomalies in Airplane Dynamics Through Entropic Analysis of Time Series Data

Despite recent efforts to move away from traditional threshold exceedance detection methods for aircraft state monitoring, modern aircraft still rely on safety thresholds to communicate to pilots the identification of an anomaly in the aircraft when a threshold is surpassed. Current anomaly detection methods mainly depend on uninterpretable machine learning models to learn complex patterns and relationships contained in the time series data of aircraft. Although these methods are capable of identifying known anomalies, their deficiency in interpretability presents a challenge when translating them to different aircraft. To overcome this deficiency, entropic analysis of aircraft dynamics seeks to characterize the complexity, or lack thereof, of the aircraft dynamics prior to the development of a risk scenario. This complexity characterization provides a more straightforward summary of state changes in the dynamics of flight variables. To build a foundation for entropic analysis, we analyzed the complexity of unstable approaches, an anomalous event present in many of today’s aviation accidents. The analysis revealed a statistically significant difference in the complexity distribution of flight variables under a stable approach versus an unstable approach. These differences in complexity were especially notable minutes before an approach was identified as unstable. Moreover, the multiscale entropic analysis revealed the presence of signal complexity at multiple time scales across multiple time windows before landing. By capturing state changes and corrections in the aircraft dynamics using entropy, advanced, yet still interpretable, sensor systems based on entropic frameworks from this study can be constructed in the future using classical machine learning approaches.

Risk detection↗

NASA NTRS2023

Machine Learning to Increase the Quality and Repeatability of 3D Printing - Workflow

The imprecise nature of three-dimensional (3D) printing limits the technology’s use beyond prototyping. For production of end-use parts, such as those for aerospace applications, improvements are needed to enhance quality and repeatability. Much of the difficulty in obtaining high quality printed parts lies in finding optimum printing parameters. Currently, this requires trial and error performed by an expert. Finding the optimum printing parameters is also obfuscated by the variation in optimum parameters throughout the part due to part geometry and printer effects. To allow for locally optimized printing parameters, one can envision a machine learning algorithm that could take in an object, predict the best printing parameters, and communicate these parameters to a printer. With this scenario in mind, we developed a tool that can predict and implement locally optimized printing parameters in 3D printing. This tool consists of elements designed to detect errors in a printed part, predict the probability of local flaws occurring at each point in the part, and select the optimal local parameters for the highest quality part given hardware limitations. The results of this work were highlighted in Advanced Materials Technologies. In this paper, we will discuss in greater depth the workflow and algorithms involved with this tool that were not detailed in the journal publication.

additive manufacturing↗

NASA NTRSDate not supplied

Artemis I Off-Nominal-Trajectory Design and Optimization

In order to achieve the Artemis I mission objectives to human-rate the Orion spacecraft even under off-nominal conditions, trajectories were developed to handle contingency scenarios: alternate missions for contingencies before or during the Trans-Lunar Injection burn, recoveries to return Orion to the nominal trajectory after a delayed or partial burn, and abort trajectories to return the spacecraft to Earth after a critical failure. In addition, disposal trajectories were generated for situations where recovery was not an option. Details are given on the trajectory characteristics, solution families, the generation of the trajectories, and operations considerations.

Artemis I↗

DOE OSTI2020

Model-Agnostic Algorithm for Real-Time Attack Identification in Power Grid using Koopman Modes

Malicious activities on measurements from sensors like Phasor Measurement Units (PMUs) can mislead the control center operator into taking wrong control actions resulting in disruption of operation, financial losses, and equipment damage. In particular, false data attacks initiated during power systems transients caused due to abrupt changes in load and generation can fool the conventional model-based detection methods relying on thresholds comparison to trigger an anomaly. In this paper, we propose a Koopman mode decomposition (KMD) based algorithm to detect and identify false data attacks in real-time. The Koopman modes (KMs) are capable of capturing the nonlinear modes of oscillation in the transient dynamics of the power networks and reveal the spatial embedding of both natural and anomalous modes of oscillations in the sensor measurements. The Koopman-based spatio-temporal nonlinear modal analysis is used to filter out the false data injected by an attacker. The performance of the algorithm is illustrated on the IEEE 68-bus test system using synthetic attack scenarios generated on GridSTAGE, a recently developed multivariate spatio-temporal data generation framework for simulation of adversarial scenarios in cyber-physical power systems.

Nandanoori, Sai Pushpak↗

DOE OSTI2022

Electrification Futures Study

Through the Electrification Futures Study (EFS), NREL explored the impacts of widespread electrification in all U.S. economic sectors. For the multiyear study, NREL and its research partners - Electric Power Research Institute, Evolved Energy Research, Lawrence Berkeley National Laboratory, Northern Arizona University, and Oak Ridge National Laboratory - used multiple analytic tools and models to develop and assess electrification scenarios designed to quantify potential energy, economic, and environmental impacts to the U.S. power system and broader economy. This presentation summarizes the analysis and key findings from across the EFS publications, with a focus on the data and results that are most relevant - and of most interest - to the state of Montana.

EFS↗

NASA NTRS2021

A Ground-Delay-Based Approach to Reduce Impedance-Based Airspace Complexity

This paper introduces a ground-delay-based traffic management approach to reduce the impedance-based airspace complexity for a given scenario. This work extends our prior research on developing an impedance-based complexity metric for unmanned aircraft system traffic scenario classification. Impedance-based metric was evaluated for 1045 randomly generated scenarios. Scenarios with overall impedance above a certain threshold were declared as not feasible. A ground-delay-based approach was developed to be applied to the rest of the scenarios so as to remediate any scenarios with small areas of high impedance on their impedance maps. A sample application is shown for a scenario with sixty flights. The detailed trade-offs between overall accrued system delay, the number of delayed flights, the total number of conflicts and the highest impedance observed as a function of the delay tolerance for each aircraft are provided. Potential applications to Urban Air Mobility traffic scenarios are also discussed.

ground-delay based traffic management↗

NASA NTRS1998

Launch Vehicle Assessment for Space Solar Power

A recently completed study at Georgia Tech examined various launch vehicle options for deploying a future constellation of Space Solar Power satellites of the Suntower configuration. One of the motivations of the study was to determine whether the aggressive $400/kg launch price goal established for SSP package delivery would result in an attractive economic scenario for a future RLV developer. That is, would the potential revenue and traffic to be derived from a large scale SSP project be enough of an economic "carrot" to attract an RLV company into developing a new, low cost launch vehicle to address this market. Preliminary results presented in the attached charts show that there is enough economic reward for RLV developers, specifically in the case of the latest large GEO-based Suntower constellations (over 15,500 MT per year delivery for 30 years). For that SSP model, internal rates of return for the 30 year economic scenario exceed 22%. However, up-front government assistance to the RLV developer in terms of ground facilities, operations technologies, guaranteed low-interest rate loans, and partial offsets of some vehicle development expenses is necessary to achieve these positive results. This white paper is meant to serve as a companion to the data supplied in the accompanying charts. It's purpose is to provide more detail on the vehicles and design processes used, to highlight key decisions and issues, and to emphasize key results from each phase of the Georgia Tech study.

Olds, John R.↗

DOE OSTI2025

Use Case Specification

Over the past three years, the Use Case Specification project has provided scenarios that have driven the development of key E-COMP capabilities and demonstrated their application to problems that the electric power industry is facing. These scenarios have provided the basis for which each Thrust has performed technical work, tying together E-COMP work under a common umbrella. Documented in this report is a summary of the background, motivations, and work – completed or proposed – under the three E-COMP use cases pursued to date: Offshore Wind, Remote Communities on the Olympic Peninsula, and Large Electric Loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1994

A Chemical Containment Model for the General Purpose Work Station

Contamination control is a critical safety requirement imposed on experiments flying on board the Spacelab. The General Purpose Work Station, a Spacelab support facility used for life sciences space flight experiments, is designed to remove volatile compounds from its internal airpath and thereby minimize contamination of the Spacelab. This is accomplished through the use of a large, multi-stage filter known as the Trace Contaminant Control System. Many experiments planned for the Spacelab require the use of toxic, volatile fixatives in order to preserve specimens prior to postflight analysis. The NASA-Ames Research Center SLS-2 payload, in particular, necessitated the use of several toxic, volatile compounds in order to accomplish the many inflight experiment objectives of this mission. A model was developed based on earlier theories and calculations which provides conservative predictions of the resultant concentrations of these compounds given various spill scenarios. This paper describes the development and application of this model.

Flippen, Alexis A.↗

NASA NTRS1992

Flight deck engine advisor

The focus of this project is on alerting pilots to impending events in such a way as to provide the additional time required for the crew to make critical decisions concerning non-normal operations. The project addresses pilots' need for support in diagnosis and trend monitoring of faults as they affect decisions that must be made within the context of the current flight. Monitoring and diagnostic modules developed under the NASA Faultfinder program were restructured and enhanced using input data from an engine model and real engine fault data. Fault scenarios were prepared to support knowledge base development activities on the MONITAUR and DRAPhyS modules of Faultfinder. An analysis of the information requirements for fault management was included in each scenario. A conceptual framework was developed for systematic evaluation of the impact of context variables on pilot action alternatives as a function of event/fault combinations.

Shontz, W. D.↗

DOE OSTI2022

Quantifying Impacts of Renewable Electricity Deployment on Air Quality and Human Health in Southeast Asia Based on AIMS III Scenarios

This study augments the ASEAN Interconnection Masterplan Study III (AIMS III) by quantifying changes to air quality and human health that result from its renewable integration and transmission interconnection scenarios. Performing this analysis requires translation of the changes in projected generation from different power sector fuel sources in the AIMS III scenarios to changes in air pollutant emissions, developing what is known as an emissions inventory for each scenario and year evaluated. An emissions inventory represents who emits air pollutants, from where the pollutants are emitted, when, and how much of which air pollutants are emitted. With the assistance of the ASEAN Centre for Energy and leveraging the best available in-region public data sources, the National Renewable Energy Laboratory (NREL) team compiled a detailed inventory of power plants in the ASEAN region, mapping their PM 2.5 , sulfur oxides (SOx), and nitrogen oxides (NOx) emissions. A new, first-of-its-kind, and user-friendly global air quality model, Global InMAP (Thakrar et al. 2022), is then used to transform the inventory of changes in emissions to changes in concentration of fine particulate matter. Global InMAP then maps the location of human populations in ASEAN countries to calculate humans' exposure to PM 2.5 and estimate excess PM 2.5 -caused mortality attributable to thermal generation sources, as modeled in the AIMS III scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Quantifying Impacts of Renewable Electricity Deployment on Air Quality and Human Health in Southeast Asia Based on Aims III Scenarios

Exposure to outdoor air pollution is the largest environmental risk factor for death and disease worldwide, associated with millions of cases of excess deaths (mortality) each year. Although there are many pollutants in the air that affect our health, the most important class of pollutants is fine particulate matter, PM 2.5 , which are airborne particles of diameter ≤2.5 micrometers (µm). These particles are small enough to deposit deep in the respiratory system where they can then enter the bloodstream, traveling and causing damage to other bodily systems. Exposure to outdoor (ambient) PM 2.5 has been found to be the most important environmental risk factor for mortality in Southeast Asia, associated with 130,000 - 320,000 excess deaths in Association of Southeast Asian Nations (ASEAN) member countries in 2019. Southeast Asia, especially its mega-cities, but also other areas, has some of the worst air quality in the world. Almost all human activity emits air pollutants. Fine particulate matter is both directly emitted and formed in the atmosphere through chemical reactions, the latter of which requires modeling to predict. Power generation is one of the major sources of air pollutants that lead to elevated concentrations of fine particulate matter, including in Southeast Asia. Fossil fuel combustion for power generation, especially coal but also diesel, is the main source of air pollutant emissions from power generation. While natural gas burns cleaner than coal or diesel, in the quantities combusted for power generation in Southeast Asia, it is also a significant emitter. This study augments the ASEAN Interconnection Masterplan Study III (AIMS III) by quantifying changes to air quality and human health that result from its renewable integration and transmission interconnection scenarios. Performing this analysis requires translation of the changes in projected generation from different power sector fuel sources in the AIMS III scenarios to changes in air pollutant emissions, developing what's known as an emissions inventory for each scenario and year evaluated. We then use for the first time a new global, reduced-complexity air quality model to transform the changes in emissions to changes in air pollutant concentration of the deadliest air pollutant for human health, fine particulate matter (or PM 2.5 ). The air quality model, Global InMAP, then utilizes the location of human population in ASEAN countries to calculate exposure to PM 2.5 concentration changes and translates that to estimates of excess mortality attributable to the AIMS III scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1986

DIOGENES: Expert system for extraction of data system requirements

AA The initial operations concept expresses information about system objectives, and defines the system users, system interfaces, and operational performance constraints. We have developed a prototype expert system which has established the feasibility of automating a scenario-driven methodology for deriving top-level specifications and preliminary designs for user data systems. This scenario-driven methodology uses an initial design, an initial operations concept, and user scenarios as the starting point for system definition. The top-level initial design is a functional description of the system in the form of an annotated data flow diagram. The initial operations concept expresses informationabout system objectives, and defines the system users, system interfaces, and operational performance constraints. The user scenarios are detailed time-lined descriptions of user activities, developed by prospective end users. These scenarios, along with the initial design and operations concept, are analyzed and iterated by the expert system to form a consistent set. The resulting User Scenario-Operation Set plays a key role in the development of requirements and system tests.

Hobbs, Robert W.↗

DOE OSTI2023

Simulation-based characterization of the variability of earthquake risk to buildings in the near-field

Recent advancements in high performance computing platforms and computational workflow for regional-scale simulations are enabling unprecedented modeling of fault-to-structure earthquake processes. Regional simulations resolving ground motions at frequencies relevant to engineered systems are becoming computationally viable and provide a new capability to improve understanding of the geographical distribution and intensity of risk to buildings and critical infrastructure. As computational capabilities advance, it is essential to move beyond illustrative single rupture realizations for scenario earthquake events towards the development of a full suite of rupture realizations that appropriately characterize the range of risk to building systems. The work described in this article investigates the application of a suite of fault rupture realizations with the objective of assessing near-fault, site-specific seismic demand variability for building structures. A representative high-performance regional-scale computational model is utilized to execute ground motion and building response simulations based on 18 kinematic rupture realizations of an M7 strike-slip scenario earthquake. The fault rupture models for the scenario earthquake are created by systematically perturbing the hypocenter location and stochastically generating rupture parameters (slip, rise time, rake angle) to represent a breadth of ground motion intensities resulting from the spatial and temporal variabilities of an earthquake rupture process. The resulting seismic demand variability for three-story (short period) and forty-story (long period) steel moment-resisting frame buildings is characterized in terms of the median and distribution of peak inter-story drift ratio for a range of near-fault sites. The full suite of 18 fault rupture realizations and approximately 280,000 nonlinear dynamic building simulations indicate that the three-story building undergoes higher median seismic demand and significantly greater variability of demand at a given site than the forty-story building, which has important implications for the level of certainty in predicting building performance during an earthquake. The simulations performed provide deeper insight into the relationship between fault rupture parameterization and building response, which is essential information for developing a representative suite of rupture realizations for specific earthquake scenarios.

58 GEOSCIENCES↗

NASA NTRS2010

Using the Integrated Vehicle Health Management Research Test and Integration Plan Wiki to Identify Synergistic Test Opportunities

The National Aeronautics and Space Administration (NASA) and the aviation industry have recognized a need for developing a method to identify and combine resources to carry out research and testing more efficiently. The Integrated Vehicle Health Management (IVHM) Research Test and Integration Plan (RTIP) Wiki is a tool that is used to visualize, plan, and accomplish collaborative research and testing. Synergistic test opportunities are developed using the RTIP Wiki, and include potential common resource testing that combines assets and personnel from NASA, industry, academia, and other government agencies. A research scenario is linked to the appropriate IVHM milestones and resources detailed in the wiki, reviewed by the research team members, and integrated into a collaborative test strategy. The scenario is then implemented by creating a test plan when appropriate and the research is performed. The benefits of performing collaborative research and testing are achieving higher Technology Readiness Level (TRL) test opportunities with little or no additional cost, improved quality of research, and increased communication among researchers. In addition to a description of the method of creating these joint research scenarios, examples of the successful development and implementation of cooperative research using the IVHM RTIP Wiki are given.

Koelfgen, Syri J.↗

NASA NTRS2018

The Behavior, Constraint, and Scenario (BeCoS) Tool: A Web-Based Software Application for Modeling Behaviors and Scenarios

The Behavior, Constraint, and Scenario (BeCoS) tool has been developed to allow engineers to specify system and component behaviors. The tool is a web application that is developed in JavaScript and uses the React framework for the user interface and Redux for maintaining application state. The foundation of the tool is its underlying ontology, which expands upon a previously-defined behavior ontology with a scenario ontology. The behavior ontology includes elements like behaving elements, state variables, parameters, and constraints, while the scenario ontology includes core constructs like activities, temporal constraints, and timepoints. BeCoS allows users to easily create behaving elements and to specify their state variables, parameters, state machines, and constraints. BeCoS also allows users to develop temporal constraint networks that specify constraints on component states over time. BeCoS is a prototype tool that has been deployed and tested by systems engineers on the Europa Clipper project, which generated several use cases and helped steer its current developmental effort. By enabling systems engineers to specify behavior in a semantically-rigorous manner, BeCoS is an enabling technology for analyses that previously could not be performed, and when exporting its model to other tools, allows for consistent behavior models to be used.

Ingham, Michel D.↗