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NASA NTRS2008

AutoBayes Program Synthesis System Users Manual

Program synthesis is the systematic, automatic construction of efficient executable code from high-level declarative specifications. AutoBayes is a fully automatic program synthesis system for the statistical data analysis domain; in particular, it solves parameter estimation problems. It has seen many successful applications at NASA and is currently being used, for example, to analyze simulation results for Orion. The input to AutoBayes is a concise description of a data analysis problem composed of a parameterized statistical model and a goal that is a probability term involving parameters and input data. The output is optimized and fully documented C/C++ code computing the values for those parameters that maximize the probability term. AutoBayes can solve many subproblems symbolically rather than having to rely on numeric approximation algorithms, thus yielding effective, efficient, and compact code. Statistical analysis is faster and more reliable, because effort can be focused on model development and validation rather than manual development of solution algorithms and code.

Schumann, Johann↗
NASA NTRS2017

An Elementary Algorithm for Autonomous Air Terminal Merging and Interval Management

A central element of air traffic management is the safe merging and spacing of aircraft during the terminal area flight phase. This paper derives and examines an algorithm for the merging and interval managing problem for Standard Terminal Arrival Routes. It describes a factor analysis for performance based on the distribution of arrivals, the operating period of the terminal, and the topology of the arrival routes; then presents results from a performance analysis and from a safety analysis for a realistic topology based on typical routes for a runway at Phoenix International Airport. The heart of the safety analysis is a statistical derivation on how to conduct a safety analysis for a local simulation when the safety requirement is given for the entire airspace.

White, Allan L.↗
NASA NTRS2018

Assessing Version 4 of the SMAP L4_SM Data Product

Version 4 of the SMAP Level 4 Surface and Root Zone Soil Moisture (L4_SM) product benefits from an improved land surface modeling system. Surface soil moisture is typically drier by several volumetric percent in Version 4 compared to Version 3, whereas root zone soil moisture is wetter in Version 4 in some regions and drier in others. Results from core validation site comparisons show that Version 4 of the L4_SM data product meets the accuracy requirement, which is formulated in terms of the RMSE after removal of the long-term mean difference (ubRMSE). The overall ubRMSE of the 3-hourly L4_SM data at the 9 km scale is 0.039 m3 m-3 for surface soil moisture and 0.029 m3 m-3 for root zone soil moisture, below the 0.04 m3 m-3 requirement. L4_SM surface and root zone soil moisture estimates are more skillful than model-only simulation estimates that are not informed by SMAP brightness temperature observations, with statistically significant improvements at the 5% level for surface soil moisture R and anomaly R values. Results from comparisons of the L4_SM product to in situ measurements from more than 400 sparse network sites corroborate the core validation site results.

Reichle, R.↗
NASA NTRSDate not supplied

Wavelength Calibration of the Full-sun Ultraviolet Rocket SpecTrograph: (FURST)

The Sun has a well-known periodicity in sunspot number and magnetic field variation. The underlying cause of this 11-year cycle is not fully understood and has yet to be connected with those processes in other stellar objects. The Full-sun Ultraviolet Rocket SpecTrograph (FURST) is a sounding rocket payload being developed by Montana State University (MSU) alongside the Marshall Space Flight Center (MSFC) solar physics group. Scheduled to launch from White Sands Missile Range (WSMR) in 2022, this instrument is unique in that it will provide the connection between stellar observatories with measurements of our Sun. It will achieve this through extremely high-resolution full-disk spectroscopy in EUV. We aim to obtain a wavelength resolution R > 10,000 in the 115 - 181 nm range, on par with that of the Hubble (HST) Space Telescope Imaging Spectrograph (STIS). The Lyman Alpha line (121 nm) is known to oversaturate most CCD electronics and is of particular challenge for this spectral range. In addition, this resolution goal will allow us to study the 3 km/s motion (a Doppler-shift of about 0.01 Angstroms) of the relatively low-temperature plasma in the chromosphere and lower corona. This paper will present the results of our simulation of the diagnostic lamp signal to be used in this wavelength calibration. To test the viability of this precise of a device, we are building a collimator capable of calibrating the FURST instrument under these strict radiometric requirements. By way of a diagnostic lamp simulation, we will account for photon noise, CCD electronic readout noise, and statistical error. These will lead to the development of our pre- and post-launch calibration plan. Future work includes absolute radiometric and wavelength calibration with this new collimator. In addition, the ability of FURST to measure extremely small Doppler-shifts will provide capabilities for planetary atmospheric scientists. This impact is coupled with the diverse international partnership created by the closely-knit Sounding Rocket teams across the globe. These Sounding Rockets have an even broader impact, as they encourage future satellite missions under the prospect of long-term observations.

FURST↗
NASA NTRS2019

The volumetric rate of normal type Ia supernovae in the local Universe discovered by the Palomar Transient Factory

We present the volumetric rate of normal type Ia supernovae (SNe Ia) discovered by the Palomar Transient Factory (PTF). Using strict data-quality cuts, and considering only periods when the PTF maintained a regular cadence, PTF discovered 90 SNe Ia at z ≤ 0.09 in a well-controlled sample over three years of operation (2010–2012). We use this to calculate the volumetric rate of SN Ia events by comparing this sample to simulations of hundreds of millions of SN Ia light curves produced in statistically representative realizations of the PTF survey. This quantifies the recovery efficiency of each PTF SN Ia event, and thus the relative weighting of each event. From this, the volumetric SN Ia rate was found to be r(v) = 2.43 ± 0.29 (stat)(+0.33,−0.19)(sys) × 10^(−5) SNe per yr Mpc^(-3) h(3,70). This represents the most precise local measurement of the SNIa rate. We fit a simple SNIa delay-time distribution model, ∝ t^(−β) , to our PTF rate measurement combined with a literature sample of rate measurements from surveys at higher redshifts. We find β ∼ 1, consistent with a progenitor channel governed by the gravitational inspiral of binary white dwarfs.

C. Frohmaier↗
NASA NTRS2022

Development of a “Nature Run” for Observing System Simulation Experiments (OSSEs) for Snow Mission Development

Snow is a fundamental component of global and regional water budgets, particularly in mountainous areas and regions downstream that rely on snowmelt for water resources. Land surface models (LSMs) are commonly used to develop spatially distributed estimates of snow water equivalent (SWE) and runoff. However, LSMs are limited by uncertainties in model physics and parameters, among other factors. In this study, we describe the use of model calibration tools to improve snow simulations within the Noah-MP LSM as the first step in an observing system simulation experiment (OSSE). Noah-MP is calibrated against the University of Arizona (UA) SWE product over a western Colorado domain. With spatially varying calibrated parameters, we run calibrated and default Noah-MP simulations for water years 2010–20. By evaluating both simulations against the UA dataset, we show that calibration decreases domain averaged temporal RMSE and bias for snow depth from 0.15 to 0.13 m and from −0.036 to −0.0023 m, respectively, and improves the timing of snow ablation. Increased snow simulation performance also improves estimates of model-simulated runoff in four of six study basins, though only one has statistically significant improvement. Spatially distributed Noah-MP snow parameters perform better than default uniform values. We demonstrate that calibrating variables related to snow albedo calculations and rain–snow partitioning, among other processes, is a necessary step for creating a nature run that reasonably approximates true snow conditions for the OSSEs. Additionally, the inclusion of a snowfall scaling term can address biases in precipitation from meteorological forcing datasets, further improving the utility of LSMs for generating reliable spatiotemporal estimates of snow.

Melissa L. Wrzesien↗
NASA NTRSDate not supplied

Aerothermal Analysis of the Dragonfly Titan Entry

The Dragonfly mission will send a rotorcraft lander to the surface of Saturn’s moon Titan as part of the New-Frontiers program. This will be the first spacecraft to land on Titan since the Huygens probe’s descent in January of 2005 and only the second spacecraft to enter Titan’s atmosphere. The Dragonfly entry capsule is significantly larger than the Huygens probe and will experience higher aerothermal environments. This poster will provide an overview of the aerothermodynamic models used in the Dragonfly aeroshell design process. Titan provides a unique entry environment that has several fundamental differences from the environments at the more common entry destinations of Earth and Mars. The lack of atmospheric oxygen significantly reduces heatshield recession (expected to be negligible), which simplifies material response analysis but also reduces the efficiency of the thermal protection system. The atmos-phere is composed of mostly nitrogen and trace amounts of methane. During hypersonic entry this methane dissociates and leads to the formation of the molecule CN, which is known to radiate strongly in the shock layer. Current Dragonfly heating predictions estimate that radiation contributes about 50% of the total heat flux along the forebody and up to 90% on the aftbody, making radiation a key element of aerothermal analysis. To properly address the importance of radiation, a unique radiative-heating correlation was developed that incorporates normal-shock equilibrium chemistry predictions based on work from the Mars 2020 program. These new heating correlations agree well with Computational Fluid Dynamics (CFD) predictions and enable large-scale trajectory analyses by providing rapid heating predictions along candidate trajectories. Dragonfly aerothermal environments are generated with the Data Parallel Line Relaxation (DPLR) finite-volume Navier-Stokes solver alongside the Nonequilibrium Radiative Transport and Spectra (NEQAIR) radiation transport code. DPLR produces shock-aligned flowfields that incorporate the effects of both chemical and thermal nonequilibrium while NEQAIR solves the radiation transport equations along lines-of-sight through the flowfield solutions to predict the radiative heating on the aeroshell. Titan’s atmosphere produces complex thermal and chemical nonequilibria and so classical radiation approximations that extrapolate from a single line-of-sight, such as the Tangent-Slab method, were found to overpredict peak radiative heat fluxes by 10-20%. Therefore, all radiative heating is directly calculated using 3-D transport for both the forebody and aftbody to reduce unnecessary conservatism. A 21-species finite-rate chemistry model, including electrons and ionized species, is used in the CFD to ensure accurate vehicle heating predictions (the level of ionization is particularly for accurate radiative flux predictions). This poster will cover: 1) The models and assumptions used to simulate entry into Titan’s atmosphere, 2) Dragonfly aerothermal engineering correlations alongside statistical heating values, and 3) Driving aerothermal considerations for a Titan entry such as CN formation and radiation-flowfield coupling.

EDL↗
NASA NTRS2017

Validating a Monotonically-Integrated Large Eddy Simulation Code for Subsonic Jet Acoustics

The results of subsonic jet validation cases for the Naval Research Lab's Jet Engine Noise REduction (JENRE) code are reported. Two set points from the Tanna matrix, set point 3 (Ma = 0.5, unheated) and set point 7 (Ma = 0.9, unheated) are attempted on three different meshes. After a brief discussion of the JENRE code and the meshes constructed for this work, the turbulent statistics for the axial velocity are presented and compared to experimental data, with favorable results. Preliminary simulations for set point 23 (Ma = 0.5, Tj=T1 = 1.764) on one of the meshes are also described. Finally, the proposed configuration for the farfield noise prediction with JENRE's Ffowcs-Williams Hawking solver are detailed.

subsonic jet↗
NASA NTRS1994

Monte Carlo simulation of the terrestrial hydrogen exosphere

Methods for Monte Carlo simulation of planetary exospheres have evolved from early work on the lunar atmosphere, where the regolith surface provides a well defined exobase. A major limitation of the successor simulations of the exospheres of Earth and Venus is the use of an exobase surface as an artifice to separate the collisional processes of the thermosphere from a collisionles exosphere. In this paper a new generalized approach to exosphere simulation is described, wherein the exobase is replaced by a barometric depletion of the major constitents of the thermosphere. Exospheric atoms in the thermosphere-exosphere transition region, and in the outer exosphere as well, travel in ballistic trajectories that are interrupted by collisons with the background gas, and by charge exchange interactions with ionospheric particles. The modified simulator has been applied to the terrestrial hydrogen exosphere problem, using velocity dependent differential cross sections to provide statistically correct collisional scattering in H-O and H-H(+) interactions. Global models are presented for both solstice and equinox over the effective solar cycle range of the F(sub 10.7) index (80 to 230). Simulation results show significant differences with previous terrestrial exosphere models, as well as with the H distributions of the MSIS-86 thermosphere model.

Hodges, R. Richard, Jr.↗
NASA NTRS1974

Channel simulation for direct detection optical communication systems

A technique is described for simulating the random modulation imposed by atmospheric scintillation and transmitter pointing jitter on a direct detection optical communication system. The system is capable of providing signal fading statistics which obey log normal, beta, Rayleigh, Ricean or chi-squared density functions. Experimental tests of the performance of the Channel Simulator are presented.

Tycz, M.↗
NASA NTRS2013

Validating an Air Traffic Management Concept of Operation Using Statistical Modeling

Validating a concept of operation for a complex, safety-critical system (like the National Airspace System) is challenging because of the high dimensionality of the controllable parameters and the infinite number of states of the system. In this paper, we use statistical modeling techniques to explore the behavior of a conflict detection and resolution algorithm designed for the terminal airspace. These techniques predict the robustness of the system simulation to both nominal and off-nominal behaviors within the overall airspace. They also can be used to evaluate the output of the simulation against recorded airspace data. Additionally, the techniques carry with them a mathematical value of the worth of each prediction-a statistical uncertainty for any robustness estimate. Uncertainty Quantification (UQ) is the process of quantitative characterization and ultimately a reduction of uncertainties in complex systems. UQ is important for understanding the influence of uncertainties on the behavior of a system and therefore is valuable for design, analysis, and verification and validation. In this paper, we apply advanced statistical modeling methodologies and techniques on an advanced air traffic management system, namely the Terminal Tactical Separation Assured Flight Environment (T-TSAFE). We show initial results for a parameter analysis and safety boundary (envelope) detection in the high-dimensional parameter space. For our boundary analysis, we developed a new sequential approach based upon the design of computer experiments, allowing us to incorporate knowledge from domain experts into our modeling and to determine the most likely boundary shapes and its parameters. We carried out the analysis on system parameters and describe an initial approach that will allow us to include time-series inputs, such as the radar track data, into the analysis

Statistical emulation↗
NASA NTRS1997

Large-Eddy Simulation of Transition to Turbulence in Boundary Layers

Large-eddy simulation results for laminar-to-turbulent transition in a spatially developing boundary layer are presented. The disturbances are ingested into a laminar flow through an unsteady suction-and-blowing strip. The filtered, three-dimensional time- dependent Navier-Stokes equations are integrated numerically using spectral, high-order finite-difference, and three-stage low-storage Runge-Kutta methods. The buffer-domain technique is used for the outflow boundary condition. The localized dynamic model used to parameterize the subgrid-scale stresses begins to have a significant impact at the beginning of the nonlinear transition (or intermittency) region. The flow structures commonly found in experiments are also observed in the present simulation; the computed linear instability modes and secondary instability lambda-vortex structures are in agreement with the experiments, and the streak-like-structures and turbulent statistics compare with both the experiments and the theory. The physics captured in the present LES are consistent with the experiments and the full Navier-Stokes simulation (DNS), at a significant fraction of the DNS cost. A comparison of the results obtained with several SGS models shows that the localized model gives accurate results both in a statistical sense and in terms of predicting the dynamics of the energy-carrying eddies, without ad hoc adjustments.

Huai, Xiao-Li↗
NASA NTRS1992

Fault detection and diagnosis using neural network approaches

Neural networks can be used to detect and identify abnormalities in real-time process data. Two basic approaches can be used, the first based on training networks using data representing both normal and abnormal modes of process behavior, and the second based on statistical characterization of the normal mode only. Given data representative of process faults, radial basis function networks can effectively identify failures. This approach is often limited by the lack of fault data, but can be facilitated by process simulation. The second approach employs elliptical and radial basis function neural networks and other models to learn the statistical distributions of process observables under normal conditions. Analytical models of failure modes can then be applied in combination with the neural network models to identify faults. Special methods can be applied to compensate for sensor failures, to produce real-time estimation of missing or failed sensors based on the correlations codified in the neural network.

Kramer, Mark A.↗
NASA NTRS1994

Voids and constraints on nonlinear clustering of galaxies

Void statistics of the galaxy distribution in the Center for Astrophysics Redshift Survey provide strong constraints on galaxy clustering in the nonlinear regime, i.e., on scales R equal to or less than 10/h Mpc. Computation of high-order moments of the galaxy distribution requires a sample that (1) densely traces the large-scale structure and (2) covers sufficient volume to obtain good statistics. The CfA redshift survey densely samples structure on scales equal to or less than 10/h Mpc and has sufficient depth and angular coverage to approach a fair sample on these scales. In the nonlinear regime, the void probability function (VPF) for CfA samples exhibits apparent agreement with hierarchical scaling (such scaling implies that the N-point correlation functions for N greater than 2 depend only on pairwise products of the two-point function xi(r)) However, simulations of cosmological models show that this scaling in redshift space does not necessarily imply such scaling in real space, even in the nonlinear regime; peculiar velocities cause distortions which can yield erroneous agreement with hierarchical scaling. The underdensity probability measures the frequency of 'voids' with density rho less than 0.2 -/rho. This statistic reveals a paucity of very bright galaxies (L greater than L asterisk) in the 'voids.' Underdensities are equal to or greater than 2 sigma more frequent in bright galaxy samples than in samples that include fainter galaxies. Comparison of void statistics of CfA samples with simulations of a range of cosmological models favors models with Gaussian primordial fluctuations and Cold Dark Matter (CDM)-like initial power spectra. Biased models tend to produce voids that are too empty. We also compare these data with three specific models of the Cold Dark Matter cosmogony: an unbiased, open universe CDM model (omega = 0.4, h = 0.5) provides a good match to the VPF of the CfA samples. Biasing of the galaxy distribution in the 'standard' CDM model (omega = 1, b = 1.5; see below for definitions) and nonzero cosmological constant CDM model (omega = 0.4, h = 0.6 lambda(sub 0) = 0.6, b = 1.3) produce voids that are too empty. All three simulations match the observed VPF and underdensity probability for samples of very bright (M less than M asterisk = -19.2) galaxies, but produce voids that are too empty when compared with samples that include fainter galaxies.

Vogeley, Michael S.↗
NASA NTRS1983

A helicopter flight investigation of roll-control sensitivity, damping and cross coupling in a low altitude lateral maneuvering task

A helicopter in-flight simulation was conducted to determine the effects of variations in roll damping, roll sensitivity, and pitch and roll rate cross-coupling on helicopter flying qualities in a low altitude maneuver. The experiment utilized the UH-1H helicopter in-flight simulator, which is equipped with the V/STOLAND avionics system. The response envelope of this vehicle allowed simulation of configurations with low to moderate damping and sensitivity. A visual, low level slalom course was set up, consisting of constant speed and constant altitude S-turns around the 1000 ft makers of an 8000 ft runway. Results are shown in terms of Cooper-Harper pilot ratings, pilot commentary, and statistical and frequency analyses of the lateral characteristics. These results show good consistency with previous ground simulator results and are compared with existing flying qualities criteria.

Corliss, L. D.↗
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 NTRS1972

The MSFC UNIVAC 1108 EXEC 8 simulation model

A model is presented which simulates the MSFC Univac 1108 multiprocessor system. The hardware/operating system is described to enable a good statistical measurement of the system behavior. The performance of the 1108 is evaluated by performing twenty-four different experiments designed to locate system bottlenecks and also to test the sensitivity of system throughput with respect to perturbation of the various Exec 8 scheduling algorithms. The model is implemented in the general purpose system simulation language and the techniques described can be used to assist in the design, development, and evaluation of multiprocessor systems.

Williams, T. G.↗