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At least 973 records · Page 54

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NASA NTRS2017

Safeguard: Progress and Test Results for a Reliable Independent On-Board Safety Net for UAS

As demands increase to use unmanned aircraft systems (UAS) for a broad spectrum of commercial applications, regulatory authorities are examining how to safely integrate them without compromising safety or disrupting traditional airspace operations. For small UAS, several operational rules have been established; e.g., do not operate beyond visual line-of-sight, do not fly within five miles of a commercial airport, do not fly above 400 feet above ground level. Enforcing these rules is challenging for UAS, as evidenced by the number of incident reports received by the Federal Aviation Administration (FAA). This paper reviews the development of an onboard system - Safeguard - designed to monitor and enforce conformance to a set of operational rules defined prior to flight (e.g., geospatial stay-out or stay-in regions, speed limits, and altitude constraints). Unlike typical geofencing or geo-limitation functions, Safeguard operates independently of the off-the-shelf UAS autopilot and is designed in a way that can be realized by a small set of verifiable functions to simplify compliance with existing standards for safety-critical systems (e.g. for spacecraft and manned commercial transportation aircraft systems). A framework is described that decouples the system from any other devices on the UAS as well as introduces complementary positioning source(s) for applications that require integrity and availability beyond what can be provided by the Global Positioning System (GPS). This paper summarizes the progress and test results for Safeguard research and development since presentation of the design concept at the 35th Digital Avionics Systems Conference (DASC '16). Significant accomplishments include completion of software verification and validation in accordance with NASA standards for spacecraft systems (to Class B), development of improved hardware prototypes, development of a simulation platform that allows for hardware-in-the-loop testing and fast-time Monte Carlo evaluations, and flight testing on multiple air vehicles. Integration testing with NASA's UAS Traffic Management (UTM) service-oriented architecture was also demonstrated.

Young, Steven D.↗

NASA NTRS2017

Revisiting Nuclear Thermal Propulsion for Human Mars Exploration

Nuclear Thermal Propulsion (NTP) has long been considered as a viable in-space transportation alternative for delivering crew and cargo to the Martian system. While technology development work in nuclear propulsion has continued over the year, general interest in NTP propulsion applications has historically been tied directly to the ebb and flow of interest in sending humans to explore Mars. As far back as the 1960’s, plans for NTP-based human Mars exploration have been proposed and periodically revisited having most recently been considered as part of NASA Design Reference Architecture (DRA) 5.0. NASA has been investigating human Mars exploration strategies tied to its current Journey to Mars for the past few years however, NTP has only recently been added into the set of alternatives under consideration for in-space propulsion under the Mars Study Capability (MSC) team, formerly the Evolvable Mars Campaign (EMC) team. The original charter of the EMC was to find viable human Mars exploration approaches that relied heavily on technology investment work already underway, specifically related to the development of large Solar Electric Propulsion (SEP) systems. The EMC team baselined several departures from traditional Mars exploration ground rules to enable these types of architectures. These ground rule changes included lower energy conjunction class trajectories with corresponding longer flight times, aggregation of mission elements in cis-Lunar space rather than Low Earth Orbit (LEO) and, in some cases, the pre-deployment of Earth return propulsion systems to Mars. As the MSC team continues to refine the in-space transportation trades, an NTP-based architecture that takes advantage of some of these ground rule departures is being introduced.

Percy, Thomas K.↗

NASA NTRS2016

Nasa Space Flight Instruments: Cost Time Trends

Are NASA’s space flight instruments becoming cheaper or more expensive as time marches forward? After analyzing the costs of hundreds of instruments launched over the last 30 years, the short answer to this question is no… and yes. This paper gives a visual analysis of the cost time trends for various NASA space flight instrument types, such as optical, particles detectors, fields detectors and microwave instruments. In addition to the statistical approaches utilized, such as significance tests, cluster analysis and principle components analysis (PCA), we will also discuss the intangibles which are likely at play, including technological progress, NASA policy and the luck of the draw associated with mission manifests. This analysis was performed as the main driver for the NASA Instrument Cost Model (NICM) recent cost estimating model redesign. Started in 2004, the first version of NICM was based off of instruments launched from 1985-2005, or 20 years’ worth of data. As NICM hit its 10-year anniversary, we wanted to know: should NICM continue to only use the most recent 20 years’ worth of data (1995-2015)? Are instruments becoming cheaper or more expensive as time marches forward? There is evidence in favor of a drop in the median dollar-per-kg value across some instrument types, but little in others. Whereas further research is needed to substantiate, Particles and Optical-Planetary instrument types show moderate to strong evidence of a downward trend in dollar-per-kg. Further research is required to study the nature of this trend (shift, taper, cyclic, etc.). Little evidence for a similar downward trend was detected for Fields or Microwave instruments, or Optical instruments on Earth Orbiting spacecraft. We presented evidence in favor of a drop in the median dollar-per-kg value for Particles and Optical-Planetary instrument types. While similar evidence was weak at best for Fields and Microwave instruments. We can speculate as to the causes for this effect, but we are also equipped to begin to rule out, or at least prioritize, some of the suspected drivers. We observed, for Particles and Optical-Planetary instruments, that perhaps a launch manifest effect was playing part of the role in the observed decrease in dollar-per-kg over the years, noting that the more flagship class missions, which have more money to spend on their instruments, were seen in the earlier years in our data, versus the later years which were dominated by less expensive class missions. However, if this were a dominating driver, would we not have seen the downward trend in the Fields and Microwave instruments as well, which were drawn from that same launch manifest? The fact that we did not observe this helps us rule out the launch manifest effect, and other drivers, such as advances in technology, that seem to be more likely suspects. In that case, however, why would technology advances be helping the Particles and Optical-Planetary instruments only? Why would it not be impacting Optical-Earth Orbiting instruments? Further suspects were looked at as well and ruled out, such as the “Faster, Better, Cheaper”era of NASA development which did not seem to actually impact trends by instrument type on a dollar-perkg scale. VI. Future Work A. Time Series Detailed Statistical Assessment The analysis discussed above sets the foundation for a more rigorous time series analysis of the data. Time series analysis will further explore evidence to-date of time trends for the instrument types which showed the strongest indicators for a decrease in dollar-per-kg: Optical (Planetary) and Particles instruments. More than providing evidence and top-level significance tests, time series analysis would help elucidate what kind of trend that exists in the data, their significance and allow statistically based forecasting (see Figure 10)

Mrozinksi, Joseph↗

NASA NTRS2020

Automating Test Consistency

Creating and controlling incredibly complex vehicles such as a rocket requires an unfathomable number of tests. Such tests are necessary to ensure a successful mission and that any issues are caught immediately. Once human lives become involved, the importance of such tests cannot be understated. Often times, however, tests may not be written in a consistent manner and such inconsistencies can lead to slowing down the test-writing process and may even create concerns with the test itself. Because of this, NASA has standards that should be followed by all test writers, but the list of standards is quite long and ensuring that tests follow this perfectly can be challenging. Older tests or tests written by individuals who are unfamiliar with this guide may not be following it which can lead to inconsistencies. To fix this issue, I have taken these human-readable rules and implemented them into an open-source linting program. Linting software is used to automatically check the style of code, and in this case, the tests. In doing so, any rules that the test developer may not have followed will be flagged upon running the software and they can quickly and accurately keep their test consistent with the rules that they are expected to follow.

Software↗

NASA NTRSDate not supplied

Reconstructing Subgrid Cloud Variability Guided by CloudSat/CALIPSO Observations

Predicting realistic cloud subgrid variability remains a challenge for Global Climate Models (GCMs) even though it can play an important role for proper representation of processes pertaining to cloud microphysics, precipitation, and radiation, but also for comparisons with satellite observations which are of much higher resolution than model grids. The diagnostic approach of subgrid cloud variability is commonly handled by subcolumn cloud generators. For a specific GCM, one ideally wants the subgrid variability used for comparisons with satellite observations to be created by the same generator and with the same rules as the one used for model integration. With this in mind, we have embarked in an effort to test and improve cloud subcolumn generators appropriate for GCMs. For this purpose, we use cloud (hydrometeor) products from active observations by the CloudSat radar (CPR) and the CALIPSO lidar (CALIOP). Cloud products from active sensors while suffering significant sampling and coverage drawbacks have the advantage of resolving both horizontal and vertical variability. The main question is: given a profile of cloud condensate mean and variance, can we create a subgrid cloud field that is statistically similar to the observed subgrid cloud field? By “statistically”, we suggest that we do not aspire to reproduce “well” each individual subgrid cloud field of a GCM-scale region, but that our generator performs well for a large ensemble of cases. We simulate radar, passive imager, and radiation flux fields from the observed 2D cloud fields and create one-point statistics; we use the profiles of cloud condensate mean and variance as input to the generator to create subgrid cloud fields; we compare the statistics; we adjust the rules of the generator to create the best possible agreement between the radar, imager and radiation field statistics. In this process, the active observations have actually a dual role: they provide the actual subgrid cloud field which can be reduced to a profile of mean and variance used by the subcolumn generator, but they also provide the rules needed by the generator, such as measures (e.g, decorrelation length) of the vertical overlap of cloud fraction and of the condensate horizontal variability. This presentation will show our progress using Cloudsat and CALIPSO products in this dual fashion.

cloud↗

NASA NTRSDate not supplied

Reconstructing Subgrid Cloud Variability Guided by CloudSat/CALIPSO Observations

Predicting realistic cloud subgrid variability remains a challenge for Global Climate Models (GCMs) even though it can play an important role for proper representation of processes pertaining to cloud microphysics, precipitation, and radiation, but also for comparisons with satellite observations which are of much higher resolution than model grids. The diagnostic approach of subgrid cloud variability is commonly handled by subcolumn cloud generators. For a specific GCM, one ideally wants the subgrid variability used for comparisons with satellite observations to be created by the same generator and with the same rules as the one used for model integration. With this in mind, we have embarked in an effort to test and improve cloud subcolumn generators appropriate for GCMs. For this purpose, we use cloud (hydrometeor) products from active observations by the CloudSat radar (CPR) and the CALIPSO lidar (CALIOP). Cloud products from active sensors while suffering signi􀂦cant sampling and coverage drawbacks have the advantage of resolving both horizontal and vertical variability. The main question is: given a profile of cloud condensate mean and variance, can we create a subgrid cloud field that is statistically similar to the observed subgrid cloud field? By “statistically”, we suggest that we do not aspire to reproduce “well” each individual subgrid cloud field of a GCM-scale region, but that our generator performs well for a large ensemble of cases. We simulate radar, passive imager, and radiation flux fields from the observed 2D cloud fields and create one-point statistics; we use the profiles of cloud condensate mean and variance as input to the generator to create subgrid cloud fields; we compare the statistics; we adjust the rules of the generator to create the best possible agreement between the radar, imager and radiation field statistics. In this process, the active observations have actually a dual role: they provide the actual subgrid cloud field which can be reduced to a profile of mean and variance used by the subcolumn generator, but they also provide the rules needed by the generator, such as measures (e.g, decorrelation length) of the vertical overlap of cloud fraction and of the condensate horizontal variability. This presentation will show our progress using Cloudsat and CALIPSO products in this dual fashion.

clouds↗

NASA NTRS2021

Assuring Intelligent Systems: Contingency Management for UAS

Unmanned aircraft systems (UAS) collaborate with humans to operate in diverse, safety-critical applications. However, assurance technologies need to be integrated into the design process in order to guarantee safe behavior, thereby enabling UAS operations in the National Airspace System (NAS). In this paper, formal methods are integrated with learning-enabled systems representations. The generation and representation of knowledge are captured via monadic second-order logic rules in the cognitive architecture Soar. These rules are translated into timed automata, and a proof of correctness for the translation is provided so that safety and liveness properties can be checked in the formal verification environment Uppaal. This approach is agnostic to the learning mechanism used to generate the learned rules (e.g., chunking, etc.). An example of a fault-tolerant, learning-enabled UAS deciding which of four contingency procedures to execute under a lost link scenario while overflying an urban area is used to illustrate the approach.

Intelligent Systems↗

NASA NTRS2021

Estimation of Snow Mass Information via Assimilation of C-Band Synthetic Aperture Radar Backscatter Observations Into an Advanced and Surface Model

This study assimilated Sentinel-1 C-band backscatter observations over snow-covered terrain into the Noah-Multiparameterization land surface model using support vector machine (SVM) regression and an ensemble Kalman filter to improve the modeled terrestrial snow mass estimates. The data assimilation (DA) experiment was conducted across Western Colorado from September 2016 to August 2017. As part of the DA experiments, the impact of a rule-based update was evaluated by comparing snow water equivalent (SWE) estimates via DA (with [ DAv1 ] and without [ DAv2 ] the rule-based update) against SNOTEL SWE measurements. Results confirmed that rule-based update helped minimize SVM controllability issues, and in turn, improved the accuracy of SWE estimates relative to both open loop (OL) and DAv2 . Comparison of SWE estimates from Sentinel-1 DAv1 against SNOTEL SWE revealed that 75% of stations showed improvements in bias and correlation coefficient relative to the OL. Assimilated SWE estimates also showed statistical improvements during both the snow accumulation and snow ablation periods. However, unbiased root mean square error showed a slight increase during the snow ablation period due to the large variability in the electromagnetic response of C-band backscatter over deep and/or wet snow. Improvement of the SWE estimates also resulted in improving river discharge estimates compared to in situ measurements. River discharge using Sentinel-1 DAv1 improved the Nash–Sutcliffe efficiency at all available stations. These results suggest that physically constrained SVM can serve as an efficient observation operator for snow mass DA through explicit consideration of the first-order C-band scattering mechanisms over different terrestrial snow conditions.

Jongmin Park↗

NASA NTRS2023

Analysis of VFR Traffic Uncertainty and its Impact on Uncrewed Aircraft Operational Capacity at Regional Airports

This paper proposes a method to characterize Visual Flight Rules traffic around a regional airport. The applicability of the method is discussed in the context of Uncrewed Aircraft operations at a regional airport. The relation between traffic interaction uncertainty and operational capacity at the runway is also investigated. The spatio-temporal distribution of traffic operating under Visual Flight Rules is analyzed from historical track data and visualized as heat maps generated at different altitudes. These are used to characterize the spatio-temporal uncertainty associated with traffic density, around a given airport, down to the runway. The traffic patterns at the runway are used to compute the runway capacity as a function of the probability of interaction with traffic operating under visual flight rules. Fort Worth Alliance is used as a representative regional airport for the study. Applications of the traffic characterization methods developed in this paper are also discussed.

VFR traffic, uncertainty, air mobility↗

NASA NTRS2023

Analysis of VFR Traffic Uncertainty and its Impact on Uncrewed Aircraft Operational Capacity at Regional Airports

VFR traffic↗

DOE OSTI2020

Demand response providing ancillary services: A comparison of opportunities and challenges in US wholesale markets

Interest in using demand response (DR) resources to supply low cost reliability products to the bulk electricity system is on the rise due to the uncertain impacts of increasing penetrations of intermittent generation and recent rulings supporting demand side participation in wholesale markets from the Federal Energy Regulatory Commission. However, organized electricity and ancillary services markets are just beginning to support DR resources for ancillary services, and the set of rules and requirements for participation are unique to each market. This paper discusses the opportunities that exist in the ancillary service markets in each US Independent System Operator territory and identifies challenges to market participation for demand response resources. It compares resource requirements, limits to aggregation, measurement and verification, bidding requirements, market timelines, and the types of organizations that can play in the markets. Additionally, it uses market clearing prices and market size to compare what value may be extracted from these markets, and identifies how these prices are currently determined. Using these criteria, PJM and ERCOT have the most favorable conditions for demand response participation in ancillary service markets, and changes to rules that effect aggregation and minimum resource size could promote more participation in other AS markets across the US.

MacDonald, Jason↗

DOE OSTI2021

Solar collector installation design system including exceptional condition management and display

Embodiments may include systems and methods to create and edit a representation of a worksite, to create various data objects, to classify such objects as various types of pre-defined “features” with attendant properties and layout constraints. As part of or in addition to classification, an embodiment may include systems and methods to create, associate, and edit intrinsic and extrinsic properties to these objects. A design engine may apply of design rules to the features described above to generate one or more solar collectors installation design alternatives, including generation of on-screen and/or paper representations of the physical layout or arrangement of the one or more design alternatives. In some embodiments, metadata about the design process, including the process of classifying features and providing user input, generating layouts, and then modifying those layouts, may be generated. The metadata may include information about exceptional conditions in the project state information or design. A list of exceptions corresponding to exceptional conditions may be generated, and the designer may interact with these exceptions in a variety of ways, such as by complying with rules to remove an item from the exceptions list or overriding the application of the rules. The exceptions may be non-blocking relative to other user actions.

Wayne, Gary↗

DOE OSTI2022

A Machine Learning-Assisted Framework to Control Thermally Anisotropic Building Envelopes in Residential Buildings

To curb the energy consumption of buildings and their related CO2 emissions, Oak Ridge National Laboratory (ORNL) has developed the thermally anisotropic building envelope (TABE) —a multi-layer design comprising insulation materials and metal foils connected to thermal loops. In this study, a machine learning-assisted framework was developed to control the TABE in residential buildings to reduce the computation load for future optimal rule-based control and application. First, a 2D finite element model was established in COMSOL to calculate the hourly heat flux through exterior walls installed with the TABE. Then, TABE wall heat fluxes were simulated for various given indoor and outdoor boundary conditions, as well as thermal loops fluid temperatures and flow rates. Since the finite element simulations are computationally expensive, an artificial neural network (ANN) was then trained to use as a proxy of the finite element (COMSOL) modeling. Finally, the trained ANN model was coupled with the EnergyPlus model to predict the energy consumption of a US Department of Energy prototype single-family house installed with the TABE. An optimal simple rule-based control was determined from predefined rules for a case study. The results demonstrate that the developed machine learning–assisted framework can reduce 99.9% of the computation time while efficiently managing residential building energy for installed TABE walls.

Shen, Zhenglai↗

DOE OSTI2024

Current and Future Technological Issues Challenges for Nuclear Graphite Components

Historical and current data requirements for component qualification, as-manufactured graphite material properties, Irradiated & degraded material issues, code rules – Construction & Operation, status of current ASME code rules, progress in design rules, degradation, construction vs. operation, what should we be planning, and new technical areas getting started.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Carbon emission responsive building control: A case study with an all-electric residential community in a cold climate

In the United States, buildings account for 35% of total energy-related carbon dioxide emissions, making them important contributors to decarbonization. Carbon intensities in the power grid are time-varying and can fluctuate significantly within hours, so shifting building loads in response to the carbon intensities can reduce a building’s operational carbon emissions. This paper presents a rule-based carbon responsive control framework that controls the setpoints of thermostatically controlled loads responding to the grid’s carbon emission signals in real time. Based on this framework, four controllers are proposed with different combinations of carbon accounting methods and control rules. To evaluate their performance, we performed simulation studies using models of a 27-home, all-electric, net zero energy residential community located in Basalt, Colorado, United States. The carbon intensity data of four future years from the Cambium data set are adopted to account for the evolving resource mix in the power grid. Various performance metrics, including energy consumption, carbon emission, energy cost, and thermal discomfort, were used to evaluate the performance of the controllers. Sensitivity analysis was also conducted to determine how the control thresholds and intervals affect the controllers’ performance. Simulation results indicate that the carbon responsive controllers can reduce the homes’ annual carbon emissions by 6.0% to 20.5%. However, the energy consumption increased by 0.9% to 6.7%, except in one scenario where it decreased by 2.2%. Compared to the baseline, the change in energy cost was between –2.9% and 3.4%, and thermal discomfort was also maintained within an acceptable range. The little impact on energy cost and thermal discomfort indicates there are no potential roadblocks for customer acceptance when rolling out the controllers in utility programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Mixed Tin-Titanium Oxides by Atomic Layer Deposition on Planar Substrates: Physical and Electronic Structure

Ternary atomic layer deposition of Sn-doped TiO x (Sn:TiO x ) and Ti-doped SnO x (Ti:SnO x ) was performed using tetrakisdimethylamidotitanium (IV) and tin(IV) with water at 150 °C on (1 0 0) Si and quartz substrates. The physical structure of the films was investigated using scanning electron, atomic force, and Kelvin probe force microscopies as well as spectroscopic ellipsometry, Raman spectroscopy, and X-ray diffraction. All as-deposited films are amorphous and possessed flat and conformal topographies with low surface roughness (<1 nm). Annealed Sn:TiO x and Ti:SnO x crystallize into the tetragonal anatase TiO 2 and cassiterite SnO 2 structures, respectively, without large variations to the film topography. The chemical composition of the as-deposited and annealed films was investigated through X-ray photoelectron spectroscopy. While dopants are homogenously mixed, the ternary ALD to form Sn:TiO x and Ti:SnO x surprisingly does not follow the rule of mixtures, despite similarities in both the growth rates of binary SnO x and TiO x and the precursors used. This finding is also supported by spectroscopic ellipsometry. Here, we postulate the deviation from the rule of mixtures is due to non-ideal surface chemistry of the binary ALD of SnO x . The optical bandgap of all films was quantified by the Tauc analysis and the valence band position was investigated by valence band X-ray photoelectron spectroscopy. Intra-bandgap states above the valence band maximum were observed for as-deposited Ti:SnO x and Sn:TiO x and ascribed to 5 s states from Sn 2+ ions. The presence of these intra-bandgap states induces enhanced visible absorption and bathochromic shifts to the apparent bandgap for all as-deposited films. Annealing the films removes the intra-bandgap states and increases the optical bandgap. Simplified band diagrams created using the data available demonstrated that the conduction and valence band positions did not vary between the positions of pure TiO 2 or SnO 2 with monotonic increases to the dopant incorporation.

36 MATERIALS SCIENCE↗

DOE OSTI2020

LieART 2.0 – A Mathematica application for Lie Algebras and Representation Theory

In this paper, we present LieART 2.0 which contains substantial extensions to the Mathematica application LieART (Lie Algebras and Representation Theory) for computations frequently encountered in Lie algebras and representation theory, such as tensor product decomposition and subalgebra branching of irreducible representations. The basic procedure is unchanged—it computes root systems of Lie algebras, weight systems and several other properties of irreducible representations, but new features and procedures have been included to allow the extensions to be seamless. The new version of LieART continues to be user friendly. New extended tables of properties, tensor products and branching rules of irreducible representations are included in the supplementary material for use without Mathematica software. LieART 2.0 now includes the branching rules to special subalgebras for all classical and exceptional Lie algebras up to and including rank 15.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Suhl instabilities in nanoscopic spheroids

We simulate the magnetization dynamics of a permalloy spheroid of nanoscopic size in zero external field, such that both dipolar and exchange interactions are important. Low excitation power is used to obtain the frequencies and mode patterns of many normal modes. At higher power, non-linear three and four mode couplings between magnons carrying orbital angular momentum are observed to give rise to Suhl instabilities. Suhl’s analysis of the selection rules governing the allowed processes is extended to initial states other than uniform precession. These rules are studied and confirmed by the simulations. Both down- and up-conversion are seen as well as three and four-mode processes. As a result, general trends are inferred for preferred instabilities among those that are allowed, although the thresholds for some instabilities appear to be very high.

3D nanomagnetism↗