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At least 577 records · Page 32

Research in Computational Astrobiology

We report on several projects in the field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. Research projects included modifying existing computer simulation codes to use efficient, multiple time step algorithms, statistical methods for analysis of astrophysical data via optimal partitioning methods, electronic structure calculations on water-nuclei acid complexes, incorporation of structural information into genomic sequence analysis methods and calculations of shock-induced formation of polycylic aromatic hydrocarbon compounds.

Chaban, Galina↗

Chemical Characterization and Reactivity Testing of Fuel-Oxidizer Reaction Product (Test Report)

The product of incomplete reaction of monomethylhydrazine (MMH) and nitrogen tetroxide (NTO) propellants, or fuel-oxidizer reaction product (FORP), has been hypothesized as a contributory cause of an anomaly which occurred in the chamber pressure (PC) transducer tube on the Reaction Control Subsystem (RCS) aft thruster 467 on flight STS-51. A small hole was found in the titanium-alloy PC tube at the first bend below the pressure transducer. It was surmised that the hole may have been caused by heat and pressure resulting from ignition of FORP. The NASA Johnson Space Center (JSC) White Sands Test Facility (WSTF) was requested to define the chemical characteristics of FORP, characterize its reactivity, and simulate the events in a controlled environment which may have lead to the Pc-tube failure. Samples of FORP were obtained from the gas-phase reaction of MMH with NTO under laboratory conditions, the pulsed firings of RCS thrusters with modified PC tubes using varied oxidizer or fuel lead times, and the nominal RCS thruster firings at WSTF and Kaiser-Marquardt. Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), accelerating rate calorimetry (ARC), ion chromatography (IC), inductively coupled plasma (ICP) spectrometry, thermogravimetric analysis (TGA) coupled to FTIR (TGA/FTIR), and mechanical impact testing were used to qualitatively and quantitatively characterize the chemical, thermal, and ignition properties of FORP. These studies showed that the composition of FORP is variable but falls within a limited range of compositions that depends on the fuel loxidizer ratio at the time of formation, composition of the post-formation atmosphere (reducing or oxidizing), and reaction or postreaction temperature. A typical composition contains methylhydrazinium nitrate (MMHN), ammonium nitrate (AN), methylammonium nitrate (MAN), and trace amounts of hydrazinium nitrate and 1,1-dimethylhydrazinium nitrate. The thermal decomposition reactions of FORP compositions used in this study were unremarkable, Neither the various compositions of FORP, the pure major components of FORP, nor mixtures of FORP with propellant-system corrosion products showed any unusual thermal activity when decomposed under laboratory conditions. Off-limit thruster operations were simulated by rapid mixing of liquid MMH and liquid NTO in a confined space. The test hardware was constructed with pressure- and temperature-measurement devices to determine if the expected fuel oxidizer reaction would result in increased energy release when FORP, FORP constituents, or propellant-system corrosion products were present. These tests demonstrated that FORP, MMHN, AN, or Inconel corrosion products can induce a mixture of MMH and NTO to produce component-damaging energies. The simulation-test program was not extensive enough to provide statistical probabilities for these events but did show that such events can occur. Damaging events required FORP or metal salts to be present at the initial mixing of MMH and NTO. Based on the results of these studies, it is suggested that removal or mitigation of a buildup of these materials may decrease the incidence of these high-energy, potentially damaging events.

Source record↗

The Effect of Cumulus Cloud Field Anisotropy on Domain-Averaged Solar Fluxes and Atmospheric Heating Rates

Cumulus clouds can become tilted or elongated in the presence of wind shear. Nevertheless, most studies of the interaction of cumulus clouds and radiation have assumed these clouds to be isotropic. This paper describes an investigation of the effect of fair-weather cumulus cloud field anisotropy on domain-averaged solar fluxes and atmospheric heating rate profiles. A stochastic field generation algorithm was used to produce twenty three-dimensional liquid water content fields based on the statistical properties of cloud scenes from a large eddy simulation. Progressively greater degrees of x-z plane tilting and horizontal stretching were imposed on each of these scenes, so that an ensemble of scenes was produced for each level of distortion. The resulting scenes were used as input to a three-dimensional Monte Carlo radiative transfer model. Domain-average transmission, reflection, and absorption of broadband solar radiation were computed for each scene along with the average heating rate profile. Both tilt and horizontal stretching were found to significantly affect calculated fluxes, with the amount and sign of flux differences depending strongly on sun position relative to cloud distortion geometry. The mechanisms by which anisotropy interacts with solar fluxes were investigated by comparisons to independent pixel approximation and tilted independent pixel approximation computations for the same scenes. Cumulus anisotropy was found to most strongly impact solar radiative transfer by changing the effective cloud fraction, i.e., the cloud fraction when the field is projected on a surface perpendicular to the direction of the incident solar beam.

Hinkelman, Laura M.↗

On the Statistical Analysis of X-ray Polarization Measurements

In many polarimetry applications, including observations in the X-ray band, the measurement of a polarization signal can be reduced to the detection and quantification of a deviation from uniformity of a distribution of measured angles of the form alpha plus beta cosine (exp 2)(phi - phi(sub 0) (0 (is) less than phi is less than pi). We explore the statistics of such polarization measurements using both Monte Carlo simulations as well as analytic calculations based on the appropriate probability distributions. We derive relations for the number of counts required to reach a given detection level (parameterized by beta the "number of sigma's" of the measurement) appropriate for measuring the modulation amplitude alpha by itself (single interesting parameter case) or jointly with the position angle phi (two interesting parameters case). We show that for the former case when the intrinsic amplitude is equal to the well known minimum detectable polarization (MDP) it is, on average, detected at the 3sigma level. For the latter case, when one requires a joint measurement at the same confidence level, then more counts are needed, by a factor of approximately equal to 2.2, than that required to achieve the MDP level. We find that the position angle uncertainty at 1sigma confidence is well described by the relation sigma(sub pi) equals 28.5(degrees) divided by beta.

Strohmayer, T. E.↗

Evaluation of a Head-Worn Display System as an Equivalent Head-Up Display for Low Visibility Commercial Operations

Research, development, test, and evaluation of fight deck interface technologies is being conducted by the National Aeronautics and Space Administration (NASA) to proactively identify, develop, and mature tools, methods, and technologies for improving overall aircraft safety of new and legacy vehicles operating in the Next Generation Air Transportation System (NextGen). One specific area of research was the use of small Head-Worn Displays (HWDs) to serve as a possible equivalent to a Head-Up Display (HUD). A simulation experiment and a fight test were conducted to evaluate if the HWD can provide an equivalent level of performance to a HUD. For the simulation experiment, airline crews conducted simulated approach and landing, taxi, and departure operations during low visibility operations. In a follow-on fight test, highly experienced test pilots evaluated the same HWD during approach and surface operations. The results for both the simulation and fight tests showed that there were no statistical differences in the crews' performance in terms of approach, touchdown and takeoff; but, there are still technical hurdles to be overcome for complete display equivalence including, most notably, the end-to-end latency of the HWD system.

Arthur, Jarvis (Trey) J., III↗

Full-Coverage High-Resolution Daily PM(sub 2.5) Estimation using MAIAC AOD in the Yangtze River Delta of China

Satellite aerosol optical depth (AOD) has been used to assess population exposure to fine particulate matter (PM (sub 2.5)). The emerging high-resolution satellite aerosol product, Multi-Angle Implementation of Atmospheric Correction(MAIAC), provides a valuable opportunity to characterize local-scale PM(sub 2.5) at 1-km resolution. However, non-random missing AOD due to cloud snow cover or high surface reflectance makes this task challenging. Previous studies filled the data gap by spatially interpolating neighboring PM(sub 2.5) measurements or predictions. This strategy ignored the effect of cloud cover on aerosol loadings and has been shown to exhibit poor performance when monitoring stations are sparse or when there is seasonal large-scale missngness. Using the Yangtze River Delta of China as an example, we present a Multiple Imputation (MI) method that combines the MAIAC high-resolution satellite retrievals with chemical transport model (CTM) simulations to fill missing AOD. A two-stage statistical model driven by gap-filled AOD, meteorology and land use information was then fitted to estimate daily ground PM(sub 2.5) concentrations in 2013 and 2014 at 1 km resolution with complete coverage in space and time. The daily MI models have an average R(exp 2) of 0.77, with an inter-quartile range of 0.71 to 0.82 across days. The overall Ml model 10-fold cross-validation R(exp 2) (root mean square error) were 0.81 (25 gm(exp 3)) and 0.73 (18 gm(exp 3)) for year 2013 and 2014, respectively. Predictions with only observational AOD or only imputed AOD showed similar accuracy.Comparing with previous gap-filling methods, our MI method presented in this study performed bette rwith higher coverage, higher accuracy, and the ability to fill missing PM(sub 2.5) predictions without ground PM(sub 2.5) measurements. This method can provide reliable PM(sub 2.5)predictions with complete coverage that can reduce biasin exposure assessment in air pollution and health studies.

PM2.5↗

(GO)2-SIM: a GCM-Oriented Ground-Observation Forward-Simulator Framework for Objective Evaluation of Cloud and Precipitation Phase

General circulation model (GCM) evaluation using ground-based observations is complicated by inconsistencies in hydrometeor and phase definitions. Here we describe (GO)2-SIM, a forward simulator designed for objective hydrometeor-phase evaluation, and assess its performance over the North Slope of Alaska using a 1-year GCM simulation. For uncertainty assessment, 18 empirical relationships are used to convert model grid-average hydrometeor (liquid and ice, cloud, and precipitation) water contents to zenith polarimetric micropulse lidar and Ka-band Doppler radar measurements, producing an ensemble of 576 forward-simulation realizations. Sensor limitations are represented in forward space to objectively remove from consideration model grid cells with undetectable hydrometeor mixing ratios, some of which may correspond to numerical noise.Phase classification in forward space is complicated by the inability of sensors to measure ice and liquid signals distinctly. However, signatures exist in lidar–radar space such that thresholds on observables can be objectively estimated and related to hydrometeor phase. The proposed phase-classification technique leads to misclassification in fewer than 8% of hydrometeor-containing grid cells. Such misclassifications arise because, while the radar is capable of detecting mixed-phase conditions, it can mistake water- for ice-dominated layers. However, applying the same classification algorithm to forward-simulated and observed fields should generate hydrometeor-phase statistics with similar uncertainty. Alternatively, choosing to disregard how sensors define hydrometeor phase leads to frequency of occurrence discrepancies of up to 40%. So, while hydrometeor-phase maps determined in forward space are very different from model "reality" they capture the information sensors can provide and thereby enable objective model evaluation.

Lamer, K.↗

Conditions of Loss Cone Filling by Scattering on the Curved Field Lines for 30 keV Protons During Geomagnetic Storm as Inferred From Numerical Trajectory Tracing

The rate of pitch angle scattering on the curved magnetic field lines is well parameterized by the ratio of the minimum field line curvature radius to the maximum effective particle gyroradius (K = RC/rg). The critical value of this ratio (Kcr) corresponding to the loss cone filling is of special interest since it corresponds to the low altitude isotropic boundaries (IBs). The early theoretical estimates gave Kcr = 8, whereas recent estimations of the K parameter on the field lines corresponding to the observed IBs during the geomagnetic storms revealed KIB values in the range of 3–30. We numerically trace the trajectories of the 30 keV protons in the magnetic field of the global magnetohydrodynamic simulation of the intense storm in order to infer statistical distribution of Kcr. The electric field and effects of nonstationarity are neglected in this study. It is found that although the Kcr values do show some variations during the course of the storm, its range is rather narrow 4 < Kcr < 8. The result suggests that higher KIB values found in the observational studies, if not caused by the magnetosphere-ionosphere mapping error, should be attributed to some other mechanism of pitch angle scattering. The Kcr values tend to be lower (4–6) during the main phase because the region of low K values approaches the Earth and the equatorial loss cone size becomes larger due to a larger equatorial magnetic field in the near earth region. The remaining variation of Kcr is explained by the presence of the guide component of the magnetic field.

S Dubyagin↗

Volcanic Stratospheric Injections up to 160 Tg(S) Yield a Eurasian Winter Warming Indistinguishable from Internal Variability

Early observational and modeling work suggested that low-latitude volcanic eruptions, comparable to the one of Pinatubo in 1991 or Krakatau in 1883, cause substantial surface warming over the northern continents at mid-latitudes in winter. The proposed mechanism consists of the formation of an anomalously strong Equator-to-pole temperature gradient in the stratosphere due to the presence of volcanic aerosols in the tropics, which are accompanied by an acceleration of the stratospheric polar vortex, which then shifts the Northern Annular Mode into a positive phase, resulting in warming surface temperatures over Eurasia. However, a large body of research in the past decade has shown that, for eruptions such as Pinatubo or Krakatau, no such warming is seen in simulations with more recent climate models which, in general, have much finer vertical and horizontal resolution than the early ones, and which have separated the forced response from the internal variability by using large ensembles of integrations. Since the proposed physical mechanism is sound, it is then possible that eruptions comparable to those of Pinatubo or Krakatau are simply too weak, but even larger ones might indeed be capable of causing Eurasian surface warming in winter. In this study, we explore this possibility using a state-of-the-art, stratosphere-resolving climate model, forced with prescribed aerosols from the Easy Volcanic Aerosol protocol. We consider eruptions with stratospheric sulfur injections of 5, 10, 20, 40, 80, and 160 Tg(S). With 20-member ensembles, we find that with injections of 20 Tg(S) or more – roughly twice the amplitude of the Pinatubo and Krakatau eruptions – our model simulates a winter surface warming over Eurasia, which is statistically significant with a t test given our 20-member ensembles. However, the forced volcanic signal on Eurasian winter surface temperatures is very small, barely exceeding the 1σ range of internal variability for the 160 Tg(S) injection case, and much smaller for smaller eruptions. Most importantly, the number of eruptions needed to establish statistical significance is considerably larger than the number of eruptions known to have occurred in the past 2000 years.

Volcanic eruptions↗

Assimilation of GPM-retrieved Ocean Surface Meteorology Data for Two Snowstorm Events during ICE-POP 2018

As a component of the National Aeronautics and Space Administration (NASA) Weather Focus Area and Global Precipitation Measurement (GPM) Ground Validation participation in the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018) field research and forecast demonstration programs, hourly ocean surface meteorology properties were retrieved from the GPM microwave observations for January – March 2018. In this study, the retrieved ocean surface meteorological products – 2-m temperature, 2-m specific humidity, and 10-m wind speed were assimilated into a regional numerical weather prediction (NWP) framework to explore the application of these observations for two heavy snowfall events during the ICE-POP 2018: 27-28 February, and 7-8 March 2018. The Weather Research and Forecasting (WRF) model and the community Gridpoint Statistical Interpolation (GSI) were used to conduct high resolution simulations and data assimilation experiments. The results indicate that the data assimilation has a large influence on surface thermodynamic and wind fields in the model initial condition for both events. With cycled data assimilation, significantly positive influence of the retrieved surface observation was found for the March case with improved quantitative precipitation forecast and reduced error in temperature forecast. A slightly smaller yet positive impact was also found in the forecast of the February case.

assimilation↗

Performance tests of signature extension algorithms

Comparative tests were performed on seven signature extension algorithms to evaluate their effectiveness in correcting for changes in atmospheric haze and sun angle in a Landsat scene. Four of the algorithms were cluster matching, and two were maximum likelihood algorithms. The seventh algorithm determined the haze level in both training and recognition segments and used a set of tables calculated from an atmospheric model to determine the affine transformation that corrects the training signatures for changes in sun angle and haze level. Three of the algorithms were tested on a simulated data set, and all of the algorithms were tested on consecutive-day data. The classification performance on the data sets using the algorithms is presented, along with results of statistical tests on the accuracy and proportion estimates. The three algorithms tested on the simulated data produced significant improvements over the results obtained using untransformed signatures. For the consecutive-day data, the tested algorithms produced improvements in most but not all cases. The tests indicated also that no statistically significant differences were noted among the algorithms.

Abotteen, R.↗

Role of Gravity Waves in Determining Cirrus Cloud Properties

Cirrus clouds are important in the Earth's radiation budget. They typically exhibit variable physical properties within a given cloud system and from system to system. Ambient vertical motion is a key factor in determining the cloud properties in most cases. The obvious exception is convectively generated cirrus (anvils), but even in this case, the subsequent cloud evolution is strongly influenced by the ambient vertical motion field. It is well know that gravity waves are ubiquitous in the atmosphere and occur over a wide range of scales and amplitudes. Moreover, researchers have found that inclusion of statistical account of gravity wave effects can markedly improve the realism of simulations of persisting large-scale cirrus cloud features. Here, we use a 1 -dimensional (z) cirrus cloud model, to systematically examine the effects of gravity waves on cirrus cloud properties. The model includes a detailed representation of cloud microphysical processes (bin microphysics and aerosols) and is run at relatively fine vertical resolution so as to adequately resolve nucleation events, and over an extended time span so as to incorporate the passage of multiple gravity waves. The prescribed gravity waves "propagate" at 15 m s (sup -1), with wavelengths from 5 to 100 km, amplitudes range up to 1 m s (sup -1)'. Despite the fact that the net gravity wave vertical motion forcing is zero, it will be shown that the bulk cloud properties, e.g., vertically-integrated ice water path, can differ quite significantly from simulations without gravity waves and that the effects do depend on the wave characteristics. We conclude that account of gravity wave effects is important if large-scale models are to generate realistic cirrus cloud property climatology (statistics).

OCStarr, David↗

Applications of Principled Search Methods in Climate Influences and Mechanisms

Forest and grass fires cause economic losses in the billions of dollars in the U.S. alone. In addition, boreal forests constitute a large carbon store; it has been estimated that, were no burning to occur, an additional 7 gigatons of carbon would be sequestered in boreal soils each century. Effective wildfire suppression requires anticipation of locales and times for which wildfire is most probable, preferably with a two to four week forecast, so that limited resources can be efficiently deployed. The United States Forest Service (USFS), and other experts and agencies have developed several measures of fire risk combining physical principles and expert judgment, and have used them in automated procedures for forecasting fire risk. Forecasting accuracies for some fire risk indices in combination with climate and other variables have been estimated for specific locations, with the value of fire risk index variables assessed by their statistical significance in regressions. In other cases, the MAPSS forecasts [23, 241 for example, forecasting accuracy has been estimated only by simulated data. We describe alternative forecasting methods that predict fire probability by locale and time using statistical or machine learning procedures trained on historical data, and we give comparative assessments of their forecasting accuracy for one fire season year, April- October, 2003, for all U.S. Forest Service lands. Aside from providing an accuracy baseline for other forecasting methods, the results illustrate the interdependence between the statistical significance of prediction variables and the forecasting method used.

Glymour, Clark↗

Clear line of sight (CLOS) statistics within cloudy regions and optimal sampling strategies for space-based lidars

Simulated cloud/hole fields as well as Landsat imagery are used in a computer model to evaluate several proposed sampling patterns and shot management schemes for pulsed space-based Doppler lidars. Emphasis is placed on two proposed sampling strategies - one obtained from a conically scanned single telescope and the other from four fixed telescopes that are sequentially used by one laser. The question of whether there are any sampling patterns that maximize the number of resolution areas with vertical soundings to the PBL is addressed.

Emmitt, G. D.↗

Turbulence Effects on Shaped Booms: Propagation Simulations Using KZKFourier

Upcoming X-59 aircraft flight tests as part of NASA’s Quesst Mission are expected to occur in a range of atmospheric conditions. Sensitivity of ground waveform acoustic metrics to turbulent perturbations during propagation complicates the determination of noise levels. A series of simulations through turbulence was executed using the KZKFourier model of Stout et al. to develop a database of results for expanding the functionality of NASA tools for estimating turbulence effects on shaped-boom ground waveforms. For 45 cases covering a seven-factor design space, multiple realizations of turbulence were generated to characterize statistical turbulence effects on levels of six acoustic metrics. An individual simulation in the study produced over one thousand waveforms across a virtual microphone array. Different measures were used to evaluate refinement of results with increasing number of simulations. Data suggest that mean effects and variability were most strongly influenced by propagation distance and velocity fluctuation intensity. Although local increases in acoustic metrics were common, the overall average result in all cases was a reduction in metric levels. Sensitivity of acoustic metrics varied, with mean reductions of up to 2 dB in Perceived Level occurring across the 45 cases.

turbulence↗

The Effect of Scale Dependent Discretization on the Progressive Failure of Composite Materials Using Multiscale Analyses

A multiscale modeling methodology, which incorporates a statistical distribution of fiber strengths into coupled micromechanics/ finite element analyses, is applied to unidirectional polymer matrix composites (PMCs) to analyze the effect of mesh discretization both at the micro- and macroscales on the predicted ultimate tensile (UTS) strength and failure behavior. The NASA code FEAMAC and the ABAQUS finite element solver were used to analyze the progressive failure of a PMC tensile specimen that initiates at the repeating unit cell (RUC) level. Three different finite element mesh densities were employed and each coupled with an appropriate RUC. Multiple simulations were performed in order to assess the effect of a statistical distribution of fiber strengths on the bulk composite failure and predicted strength. The coupled effects of both the micro- and macroscale discretizations were found to have a noticeable effect on the predicted UTS and computational efficiency of the simulations.

Ricks, Trenton M.↗

Comparison of Kalman filter and optimal smoother estimates of spacecraft attitude

Given a valid system model and adequate observability, a Kalman filter will converge toward the true system state with error statistics given by the estimated error covariance matrix. The errors generally do not continue to decrease. Rather, a balance is reached between the gain of information from new measurements and the loss of information during propagation. The errors can be further reduced, however, by a second pass through the data with an optimal smoother. This algorithm obtains the optimally weighted average of forward and backward propagating Kalman filters. It roughly halves the error covariance by including future as well as past measurements in each estimate. This paper investigates whether such benefits actually accrue in the application of an optimal smoother to spacecraft attitude determination. Tests are performed both with actual spacecraft data from the Extreme Ultraviolet Explorer (EUVE) and with simulated data for which the true state vector and noise statistics are exactly known.

Sedlak, J.↗

A Computational Approach for Probabilistic Analysis of LS-DYNA Water Impact Simulations

NASA s development of new concepts for the Crew Exploration Vehicle Orion presents many similar challenges to those worked in the sixties during the Apollo program. However, with improved modeling capabilities, new challenges arise. For example, the use of the commercial code LS-DYNA, although widely used and accepted in the technical community, often involves high-dimensional, time consuming, and computationally intensive simulations. Because of the computational cost, these tools are often used to evaluate specific conditions and rarely used for statistical analysis. The challenge is to capture what is learned from a limited number of LS-DYNA simulations to develop models that allow users to conduct interpolation of solutions at a fraction of the computational time. For this problem, response surface models are used to predict the system time responses to a water landing as a function of capsule speed, direction, attitude, water speed, and water direction. Furthermore, these models can also be used to ascertain the adequacy of the design in terms of probability measures. This paper presents a description of the LS-DYNA model, a brief summary of the response surface techniques, the analysis of variance approach used in the sensitivity studies, equations used to estimate impact parameters, results showing conditions that might cause injuries, and concluding remarks.

Horta, Lucas G.↗