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At least 721 records · Page 40

Highly parallel sparse Cholesky factorization

Several fine grained parallel algorithms were developed and compared to compute the Cholesky factorization of a sparse matrix. The experimental implementations are on the Connection Machine, a distributed memory SIMD machine whose programming model conceptually supplies one processor per data element. In contrast to special purpose algorithms in which the matrix structure conforms to the connection structure of the machine, the focus is on matrices with arbitrary sparsity structure. The most promising algorithm is one whose inner loop performs several dense factorizations simultaneously on a 2-D grid of processors. Virtually any massively parallel dense factorization algorithm can be used as the key subroutine. The sparse code attains execution rates comparable to those of the dense subroutine. Although at present architectural limitations prevent the dense factorization from realizing its potential efficiency, it is concluded that a regular data parallel architecture can be used efficiently to solve arbitrarily structured sparse problems. A performance model is also presented and it is used to analyze the algorithms.

Gilbert, John R.↗

Conceptual Design of a Tiltduct Reference Vehicle for Urban Air Mobility

NASA is establishing a fleet of conceptual air vehicle designs to support research and development for Urban Air Mobility (UAM). This fleet of vehicles will enable examination of the sensitivity of UAM vehicle designs to technology assumptions, identify key research and development needs for UAM aircraft, and provide the UAM community with reference vehicles that are publicly available and based upon known assumptions. To date, five six-passenger UAM reference vehicles have been published: a single-main-rotor helicopter, a side-by-side helicopter, a quadrotor, a lift-plus-cruise, and a tiltwing. To increase the breadth of vehicle technologies encapsulated in the fleet of NASA UAM reference vehicles, this paper establishes a tiltduct vehicle as an addition to the fleet. The fleet will continue to evolve as future analyses and trade studies are performed. The tiltduct UAM reference vehicle has six tilting ducted proprotors. This paper describes the initial configuration downselection; discusses ducted proprotor design rules of thumb as they applied to the conceptual design of the reference vehicle; describes the vehicle sizing, trade studies, and tuning of models performed; and finally, compares the resulting tiltduct vehicle against the other six-passenger NASA UAM reference vehicles. The high-level analyses performed for this study did not indicate significant differences in performance between the tiltduct and tiltwing reference vehicles, and so vehicle performance alone may not be a key driver in the selection of a tiltduct vehicle over a tiltwing vehicle. However, if ducts are found to have significant acoustical benefits, then acoustical priorities may provide a compelling reason to incorporate ducted proprotors. One significant limitation of the design presented in this paper is that the ducted proprotor performance was tuned based upon performance characteristics observed during historical tests with disk loadings (defined as thrust divided by proprotor disk area) of 125-250 lb/ft$^2$. The tiltduct vehicle designed in this study has a disk loading of 30 lb/ft$^2$, to be more representative of UAM vehicles; further studies to understand performance of ducted proprotors at representative disk loadings are warranted.

Tiltduct↗

Dynamic modeling of orographically induced precipitation

Local orography governs the triggering of cloud formation and the enhancement of processes such as condensation and hydrometeor nucleation and growth in mountainous regions. Intense, lengthy precipitation events are typical upwind of the topographic divide, with sharply decreasing magnitude and duration on the lee side. Differences in mean annual precipitation of several hundred percent between windward slopes of orographic barriers and adjacent valleys or lee side slopes are not unusual. Because much of the streamflow in areas such as the western United States is derived from mountainous areas that are remote and often poorly instrumented, modeling of orographic precipitation has important implications for water resources management. Models of orographically induced precipitation differ by their treatment of atmospheric dynamics and by the extent to which they rely on bulk parameterization of cloud and precipitation physics. Adiabatic ascent and a direct proportionality between efficiency and orographically magnified updrafts are the most frequent assumptions in orographic precipitation modeling. Space-time discretization (i.e., resolution) is a major issue because of the high spatial variability of orographic precipitation. For a specific storm, relative errors as large as 50 to 100% are common in the forecast/hindcast of precipitation intensity and can be even larger in the case of catastrophic storms. When monthly or seasonal timescales are used to evaluate model performance, the magnitude of such errors decreases dramatically, reaching values as low as 10 to 15%. Current research is focusing on the development of data assimilation techniques to incorporate radar and satellite observations, and on the development of aggregation and disaggregation methodologies to address the implications of modeling a multiscale problem at restricted spatial and temporal resolutions.

Barros, Ana Paula↗

Global and Regional Radiative Forcing from 20 Reductions in BC, OC and SO4 an HTAP2 Multi-Model Study

In the Hemispheric Transport of Air Pollution Phase 2 (HTAP2) exercise, a range of global atmospheric general circulation and chemical transport models performed coordinated perturbation experiments with 20% reductions in emissions of anthropogenic aerosols, or aerosol precursors, in a number of source regions. Here, we compare the resulting changes in the atmospheric load and vertically resolved profiles of black carbon (BC), organic aerosols (OA) and sulfate (SO4/ from 10 models that include treatment of aerosols. We use a set of temporally, horizontally and vertically resolved profiles of aerosol forcing efficiency (AFE) to estimate the impact of emission changes in six major source regions on global radiative forcing (RF) pertaining to the direct aerosol effect, finding values between. 51.9 and 210.8mW/sq m/Tg for BC, between -2.4 and -17.9mW/sq m/Tg for OA and between -3.6 and -10.3W/sq m/Tg for SO4. In most cases, the local influence dominates, but results show that mitigations in south and east Asia have substantial impacts on the radiative budget in all investigated receptor regions, especially for BC. In Russia and the Middle East, more than 80 % of the forcing for BC and OA is due to extra-regional emission reductions. Similarly, for North America, BC emissions control in east Asia is found to be more important than domestic mitigations, which is consistent with previous findings. Comparing fully resolved RF calculations to RF estimates based on vertically averaged AFE profiles allows us to quantify the importance of vertical resolution to RF estimates. We find that locally in the source regions, a 20% emission reduction strengthens the radiative forcing associated with SO4 by 25% when including the vertical dimension, as the AFE for SO4 is strongest near the surface. Conversely, the local RF from BC weakens by 37% since BC AFE is low close to the ground. The fraction of BC direct effect forcing attributable to intercontinental transport, on the other hand, is enhanced by one-third when accounting for the vertical aspect, because long-range transport primarily leads to aerosol changes at high altitudes, where the BC AFE is strong. While the surface temperature response may vary with the altitude of aerosol change, the analysis in the present study is not extended to estimates of temperature or precipitation changes.

profiles of aerosol forcing efficiency (AFE)↗

Machine Learning-Based Atmospheric Phenomena Detection Platform

As the number of Earth pointing satellites has increased over the last several decades, the data volume retrieved from instruments onboard these satellites has also increased. It is expected that this trend will continue as more data intensive missions and small satellite constellations are launched. Currently, feature detection - namely atmospheric phenomena - in these datasets is performed manually and is thus not scalable with the growing data archives. Recent advancements in computational efficiency allow for the Earth science community to leverage machine learning to identify interesting atmospheric phenomena. Given the wide range of distinctive features in various atmospheric phenomena, a specialized machine learning model is required for accurate detection of these phenomena independently. The Phenomena Portal, developed at NASA IMPACT, is designed to provide visualization for the output from these machine learning models. In addition, detected events for each atmospheric phenomena are stored in a database that can be used to more easily use/subset larger spatiotemporal datasets. The user interface also incorporates additional features to enhance the user experience including spatiotemporal analysis, multiple base layer images, and a slider to filter events with lower probabilities of positive detection. Each detection supports user feedback on whether the detection is true or false that can then be stored and used to improve the machine learning model performance.

Gurung, Iksha↗

Utility of Emulation and Simulation Computer Modeling of Space Station Environmental Control and Life Support Systems

Over the years, computer modeling has been used extensively in many disciplines to solve engineering problems. A set of computer program tools is proposed to assist the engineer in the various phases of the Space Station program from technology selection through flight operations. The development and application of emulation and simulation transient performance modeling tools for life support systems are examined. The results of the development and the demonstration of the utility of three computer models are presented. The first model is a detailed computer model (emulation) of a solid amine water desorbed (SAWD) CO2 removal subsystem combined with much less detailed models (simulations) of a cabin, crew, and heat exchangers. This model was used in parallel with the hardware design and test of this CO2 removal subsystem. The second model is a simulation of an air revitalization system combined with a wastewater processing system to demonstrate the capabilities to study subsystem integration. The third model is that of a Space Station total air revitalization system. The station configuration consists of a habitat module, a lab module, two crews, and four connecting nodes.

Yanosy, James L.↗

Assessment of the Mars 2020 Entry, Descent, and Landing Simulation

On February 18, 2021, the Mars 2020 Perseverance rover successfully landed inside Jezero Crater at 18.44463 deg North latitude and 77.45088 deg East longitude. At 1026 kg, Perseverance is the largest, most sophisticated rover ever delivered to another planet. This event marked the ninth successful landing and fifth rover to be delivered at Mars. The Program to Optimize Simulated Trajectories II (POST2) is a trajectory simulation tool maintained by the NASA Langley Research Center. POST2 was the prime EDL performance simulation for Mars 2020. This tool has significant heritage on the previous Pathfinder, MER, Phoenix, InSight, and MSL landings. This paper presents a few initial comparisons between EDL flight telemetry and POST2 simulation predictions. These comparisons are important in order to understand how each of the individual models performed, as well as the integrated simulation as a whole. This information is fed forward to future missions, which benefit from the knowing where additional resources or study are needed and where uncertainties may be reduced to enable improved performance.

David W Way↗

Assessment of the Mars 2020 Entry, Descent, and Landing Simulation

On February 18, 2021, the Mars 2020 Perseverance rover successfully landed inside Jezero Crater at 18.44463 deg North latitude and 77.45088 deg East longitude. At 1026 kg, Perseverance is the largest, most sophisticated rover ever delivered to another planet. This event marked the ninth successful landing and fifth rover to be delivered at Mars. The Program to Optimize Simulated Trajectories II (POST2) is a trajectory simulation tool maintained by the NASA Langley Research Center. POST2 was the prime EDL performance simulation for Mars 2020. This tool has significant heritage on the previous Pathfinder, MER, Phoenix, InSight, and MSL landings. This paper presents a few initial comparisons between EDL flight telemetry and POST2 simulation predictions. These comparisons are important in order to understand how each of the individual models performed, as well as the integrated simulation as a whole. This information is fed forward to future missions, which benefit from the knowing where additional resources or study are needed and where uncertainties may be reduced to enable improved performance.

David Way↗

Global Design Optimization for Aerodynamics and Rocket Propulsion Components

Modern computational and experimental tools for aerodynamics and propulsion applications have matured to a stage where they can provide substantial insight into engineering processes involving fluid flows, and can be fruitfully utilized to help improve the design of practical devices. In particular, rapid and continuous development in aerospace engineering demands that new design concepts be regularly proposed to meet goals for increased performance, robustness and safety while concurrently decreasing cost. To date, the majority of the effort in design optimization of fluid dynamics has relied on gradient-based search algorithms. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space, can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables, and methods for predicting the model performance. In this article, we review recent progress made in establishing suitable global optimization techniques employing neural network and polynomial-based response surface methodologies. Issues addressed include techniques for construction of the response surface, design of experiment techniques for supplying information in an economical manner, optimization procedures and multi-level techniques, and assessment of relative performance between polynomials and neural networks. Examples drawn from wing aerodynamics, turbulent diffuser flows, gas-gas injectors, and supersonic turbines are employed to help demonstrate the issues involved in an engineering design context. Both the usefulness of the existing knowledge to aid current design practices and the need for future research are identified.

Shyy, Wei↗

Component-Level Selection and Qualification for the Global Ecosystem Dynamics Investigation (GEDI) Laser Altimeter Transmitter

Flight quality solid-state lasers require a unique and extensive set of testing and qualification processes, both at the system and component levels to insure the laser's promised performance. As important as the overall laser transmitter design is, the quality and performance of individual subassemblies, optics, and electro-optics dictate the final laser unit's quality. The Global Ecosystem Dynamics Investigation (GEDI) laser transmitters employ all the usual components typical for a diode-pumped, solid-state laser, yet must each go through their own individual process of specification, modeling, performance demonstration, inspection, and destructive testing. These qualification processes and results for the laser crystals, laser diode arrays, electro-optics, and optics, will be reviewed as well as the relevant critical issues encountered, prior to their installation in the GEDI flight laser units.

Frese, Erich A.↗

A figure of merit for AMTEC electrodes

As a method to compare the results of alkali metal thermoelectric converter (AMTEC) electrode performance measured under different conditions, an AMTEC figure of merit called ZA is proposed. This figure of merit is the ratio of the experimental maximum power for an electrode to a calculated maximum power density as determined from a recently published electrode performance model. The calculation of a maximum power density assumes that certain loss terms in the electrode can be reduced to essentially zero by improved cell design and construction, and that the electrochemical exchange current is determined from a standard value. Other losses in the electrode are considered inherent to the electrode performance. Thus, these terms remain in the determination of the calculated maximum power. A value of ZA near one, then, indicates an electrode performance near the maximum possible performance. The primary limitation of this calculation is that the small electrode effect cannot be included. This effect leads to anomalously high values of ZA. Thus, the electrode area should be reported along with the figure of merit.

Underwood, M. L.↗

Shear Stress Partitioning in Large Patches of Roughness in the Atmospheric Inertial Sublayer

Drag partition measurements were made in the atmospheric inertial sublayer for six roughness configurations made up of solid elements in staggered arrays of different roughness densities. The roughness was in the form of a patch within a large open area and in the shape of an equilateral triangle with 60 m long sides. Measurements were obtained of the total shear stress (tau) acting on the surfaces, the surface shear stress on the ground between the elements (tau(sub S)) and the drag force on the elements for each roughness array. The measurements indicated that tau(sub S) quickly reduced near the leading edge of the roughness compared with tau, and a tau(sub S) minimum occurs at a normalized distance (x/h, where h is element height) of approx. -42 (downwind of the roughness leading edge is negative), then recovers to a relatively stable value. The location of the minimum appears to scale with element height and not roughness density. The force on the elements decreases exponentially with normalized downwind distance and this rate of change scales with the roughness density, with the rate of change increasing as roughness density increases. Average tau(sub S): tau values for the six roughness surfaces scale predictably as a function of roughness density and in accordance with a shear stress partitioning model. The shear stress partitioning model performed very well in predicting the amount of surface shear stress, given knowledge of the stated input parameters for these patches of roughness. As the shear stress partitioning relationship within the roughness appears to come into equilibrium faster for smaller roughness element sizes it would also appear the shear stress partitioning model can be applied with confidence for smaller patches of smaller roughness elements than those used in this experiment.

Gillies, John A.↗

NASA GRC Stirling Technology Development Overview

The Department of Energy, Lockheed Martin (LM), Stirling Technology Company, and NASA Glenn Research Center (GRC) are developing a high-efficiency Stirling Radioisotope Generator (SRG) for potential NASA Space Science missions. The SRG is being developed for multimission use, including providing spacecraft onboard electric power for NASA deep space missions and power for unmanned Mars rovers. NASA GRC is conducting an in- house supporting technology project to assist in developing the Stirling convertor for space qualification and mission implementation. Preparations are underway for a thermalhacuum system demonstration and unattended operation during endurance testing of the 55-We Technology Demonstration Convertors. Heater head life assessment efforts continue, including verification of the heater head brazing and heat treatment schedules and evaluation of any potential regenerator oxidation. Long-term magnet aging tests are continuing to characterize any possible aging in the strength or demagnetization resistance of the permanent magnets used in the linear alternator. Testing of the magnet/lamination epoxy bond for performance and lifetime characteristics is now underway. These efforts are expected to provide key inputs as the system integrator, LM, begins system development of the SRG. GRC is also developing advanced technology for Stirling convertors. Cleveland State University (CSU) is progressing toward a multi-dimensional Stirling computational fluid dynamics code, capable of modeling complete convertors. Validation efforts at both CSU and the University of Minnesota are complementing the code development. New efforts have been started this year on a lightweight convertor, advanced controllers, high-temperature materials, and an end-to-end system dynamics model. Performance and mass improvement goals have been established for second- and third-generation Stirling radioisotope power systems.

Thieme, Lanny G.↗

An Integrated Gate Turnaround Management Concept Leveraging Big Data/Analytics for NAS Performance Improvements

The Integrated Gate Turnaround Management (IGTM) concept was developed to improve the gate turnaround performance at the airport by leveraging relevant historical data to support optimization of airport gate operations, which include: taxi to the gate, gate services, push back, taxi to the runway, and takeoff, based on available resources, constraints, and uncertainties. By analyzing events of gate operations, primary performance dependent attributes of these events were identified for the historical data analysis such that performance models can be developed based on uncertainties to support descriptive, predictive, and prescriptive functions. A system architecture was developed to examine system requirements in support of such a concept. An IGTM prototype was developed to demonstrate the concept using a distributed network and collaborative decision tools for stakeholders to meet on time pushback performance under uncertainties.

Big Data and Net-enabled ATM↗

Radar Reflectivity Simulated by a 2-D Spectra Bin Model: Sensitivity of Cloud-aerosol Interaction

The Goddard Cumulus Ensemble (GCE) model with bin spectra microphysics is used to simulate mesoscale convective systems.The model uses explicit bins to represent size spectra of cloud nuclei, water drops, ice crystals, snow and graupel. Each hydrometeorite category is described by 33 mass bins. The simulations provide a unique data set of simulated raindrop size distribution in a realistic dynamic frame. Calculations of radar parameters using simulated drop size distribution serve as an evaluation of numerical model performance. In addition, the GCE bin spectra modes is a very useful tool to study uncertainties related to radar observations; all the environmental parameters are precisely known. In this presentation, we concentrate on the discussion of Z-R (ZDR-R) relation in the simulated systems. Due to computational limitations, the spectra bin model has been run in two dimensions with 31 stretched vertical layers and 1026 horizontal grid points (1 km resolution). Two different cases, one in midlatitude continent, the other in tropical ocean, have been simulated. The continental case is a strong convection which lasted for two hours. The oceanic case is a persistent system with more than 10 hours' life span. It is shown that the simulated Z-R (ZDR-R) relations generally agree with observations using radar and rain gauge data. The spatial and temporal variations of Z-R relation in different locations are also analyzed. Impact of aerosols on cloud formation and raindrop size distribution was studied. Both clean (low CCN) and dirty (high CCN) cases are simulated. The Z-R relation is shown to vary considerable in the initial CCN concentrations.

Li, Kiaowen↗

Impact Assessment of Biomass Burning on Air Quality in Southeast and East Asia During BASE-ASIA

A synergy of numerical simulation, ground-based measurement and satellite observation was applied to evaluate the impact of biomass burning originating from Southeast Asia (SE Asia) within the framework of NASA's 2006 Biomass burning Aerosols in Southeast Asia: Smoke Impact Assessment (BASE-ASIA). Biomass burning emissions in the spring of 2006 peaked in MarcheApril when most intense biomass burning occurred in Myanmar, northern Thailand, Laos, and parts of Vietnam and Cambodia. Model performances were reasonably validated by comparing to both satellite and ground-based observations despite overestimation or underestimation occurring in specific regions due to high uncertainties of biomass burning emission. Chemical tracers of particulate K(+), OC concentrations, and OC/EC ratios showed distinct regional characteristics, suggesting biomass burning and local emission dominated the aerosol chemistry. CMAQ modeled aerosol chemical components were underestimated at most circumstances and the converted AOD values from CMAQ were biased low at about a factor of 2, probably due to the underestimation of biomass emissions. Scenario simulation indicated that the impact of biomass burning to the downwind regions spread over a large area via the Asian spring monsoon, which included Southern China, South China Sea, and Taiwan Strait. Comparison of AERONET aerosol optical properties with simulation at multi-sites clearly demonstrated the biomass burning impact via longrange transport. In the source region, the contribution from biomass burning to AOD was estimated to be over 56%. While in the downwind regions, the contribution was still significant within the range of 26%-62%.

biomass burning↗

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on current and forecast of traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. In this paper, a methodology using supervised learning is developed to build a predictive model for RCM decision-support from large volumes of historical data. Data from two full years (2018 and 2019) related to current and forecast weather, demand/capacity, etc. is collected, analyzed, and fused together. A variety of supervised learning algorithms are tested for predicting runway configuration and hyperparameter tuning is carried out to select the best performing model. The validation process involves two airports of low (Charlotte Douglas International Airport, CLT) and high (Denver International Airport, DEN) complexity of configuration decision-making. The results show significant promise for the two airports with test accuracy of 93% (CLT) and 73% (DEN). The methodology is scalable and generalizable to other airports across the U.S. National Airspace System.

air traffic management↗

Predicting Airport Runway Configuration for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on current and forecast of traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. In this paper, a methodology using supervised learning is developed to build a predictive model for RCM decision-support from large volumes of historical data. Data from two full years (2018 and 2019) related to current and forecast weather, demand/capacity, etc. is collected, analyzed, and fused together. A variety of supervised learning algorithms are tested for predicting runway configuration and hyperparameter tuning is carried out to select the best performing model. The validation process involves two airports of low (Charlotte Douglas International Airport, CLT) and high (Denver International Airport, DEN) complexity of configuration decision-making. The results show significant promise for the two airports with test accuracy of 93% (CLT) and 73% (DEN). The methodology is scalable and generalizable to other airports across the U.S. National Airspace System.

air traffic management↗