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

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At least 451 records · Page 25

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↗

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↗

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↗

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↗

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↗

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↗

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.↗

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↗

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.↗

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.↗

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.↗

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.↗

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.↗

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.

Inghams, Michel D.↗

Subsonic Ultra Green Aircraft Research

This Final Report summarizes the work accomplished by the Boeing Subsonic Ultra Green Aircraft Research (SUGAR) team in Phase 1, which includes the time period of October 2008 through March 2010. The team consisted of Boeing Research and Technology, Boeing Commercial Airplanes, General Electric, and Georgia Tech. The team completed the development of a comprehensive future scenario for world-wide commercial aviation, selected baseline and advanced configurations for detailed study, generated technology suites for each configuration, conducted detailed performance analysis, calculated noise and emissions, assessed technology risks, and developed technology roadmaps. Five concepts were evaluated in detail: 2008 baseline, N+3 reference, N+3 high span strut braced wing, N+3 gas turbine battery electric concept, and N+3 hybrid wing body. A wide portfolio of technologies was identified to address the NASA N+3 goals. Significant improvements in air traffic management, aerodynamics, materials and structures, aircraft systems, propulsion, and acoustics are needed. Recommendations for Phase 2 concept and technology projects have been identified.

Bradley, Marty K.↗

Development of the Orion Crew Module Static Aerodynamic Database: Supersonic/Subsonic - Par 2

This work describes the process of developing the nominal static aerodynamic coefficients and associated uncertainties for the Orion Crew Module for Mach 8 and below. The database was developed from wind tunnel test data and computational simulations of the smooth Crew Module geometry, with no asymmetries or protuberances. The database covers the full range of Reynolds numbers seen in both entry and ascent abort scenarios. The basic uncertainties were developed as functions of Mach number and total angle of attack from variations in the primary data as well as computations at lower Reynolds numbers, on the baseline geometry, and using different flow solvers. The resulting aerodynamic database represents the Crew Exploration Vehicle Aerosciences Project's best estimate of the nominal aerodynamics for the current Crew Module vehicle.

Bibb, Karen L.↗

Distributed Monitoring of the R(sup 2) Statistic for Linear Regression

The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and one or more dependent target variables. This problem becomes challenging for large scale data in a distributed computing environment when only a subset of instances is available at individual nodes and the local data changes frequently. Data centralization and periodic model recomputation can add high overhead to tasks like anomaly detection in such dynamic settings. Therefore, the goal is to develop techniques for monitoring and updating the model over the union of all nodes data in a communication-efficient fashion. Correctness guarantees on such techniques are also often highly desirable, especially in safety-critical application scenarios. In this paper we develop DReMo a distributed algorithm with very low resource overhead, for monitoring the quality of a regression model in terms of its coefficient of determination (R2 statistic). When the nodes collectively determine that R2 has dropped below a fixed threshold, the linear regression model is recomputed via a network-wide convergecast and the updated model is broadcast back to all nodes. We show empirically, using both synthetic and real data, that our proposed method is highly communication-efficient and scalable, and also provide theoretical guarantees on correctness.

Bhaduri, Kanishka↗

Study and Demonstration of Planning and Scheduling Concepts for the Earth Observing System Data and Information System

The University of Colorado's Laboratory for Atmospheric and Space Physics (CU/LASP) along with the Goddard Space Flight Center (GSFC) and the Jet Propulsion Laboratory (JPL) designed, implemented, tested, and demonstrated a prototype of the distributed, hierarchical planning and scheduling system comtemplated for the Earth Observing System (EOS) project. The planning and scheduling prototype made use of existing systems: CU/LASP's Operations and Science Instrument Support Planning and Scheduling (OASIS-PS) software package; GSFC's Request Oriented Scheduling Engine (ROSE); and JPL's Plan Integrated Timeliner 2 (Plan-It-2). Using these tools, four scheduling nodes were implemented and tied together using a new communications protocol for scheduling applications called the Scheduling Applications Interface Language (SAIL). An extensive and realistic scenario of EOS satellite operations was then developed and the prototype scheduling system was tested and demonstrated using the scenario. Two demonstrations of the system were given to NASA personnel and EOS core system (ECS) contractor personnel. A comprehensive volume of lessons learned was generated and a meeting was held with NASA and ECS representatives to review these lessons learned. A paper and presentation on the project's final results was given at the American Institute of Aeronautics and Astronautics Computing in Aerospace 9 conference.

Davis, Randal↗