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At least 163 records · Page 9

The Postshock Chemical Lifetimes of Outflow Tracers and a Possible New Mechanism to Produce Water Ice Mantles

We have used a coupled time-dependent chemical and dynamical model to investigate the lifetime of the chemical legacy in the wake of C-type shocks. We concentrate this study on the chemistry of H2O and O2, two molecules which are predicted to have abundances that are significantly affected in shock-heated gas. Two models are presented: (1) a three-stage model of preshock, shocked, and postshock gas; and (2) a Monte Carlo cloud simulation where we explore the effects of stochastic shock activity on molecular gas over a cloud lifetime. For both models we separately examine the pure gas-phase chemistry as well as the chemistry including the interactions of molecules with grain surfaces. In agreement with previous studies, we find that shock velocities in excess of 10 km/s are required to convert all of the oxygen not locked in CO into H2O before the gas has an opportunity to cool. For pure gas phase models the lifetime of the high water abundances, or "H2O legacy," in the postshock gas is approximately (4-7) x 10(exp 5) yr, independent of the gas density. A density dependence for the lifetime of H2O is found in gas-grain models as the water molecules deplete onto grains at the depletion timescale. Through the Monte Carlo cloud simulation we demonstrate that the time-average abundance of H2O, the weighted average of the amount of time gas spends in preshock, shock, and postshock stages, is a sensitive function of the frequency of shocks. Thus we predict that the abundance of H2O, and to a lesser extent O2, can be used to trace the history of shock activity in molecular gas. We use previous large-scale surveys of molecular outflows to constrain the frequency of 10 km/s shocks in regions with varying star formation properties and discuss the observations required to test these results. We discuss the postshock lifetimes for other possible outflow tracers (e.g., SiO and CH3OH) and show that the differences between the lifetimes for various tracers can produce potentially observable chemical variations between younger and older outflows. For gas-grain models we find that the abundance of water-ice on grain surfaces can be quite large and is comparable to that observed in molecular clouds. This offers a possible alternative method to create water mantles without resorting to grain surface chemistry: gas heating and chemical modification due to a C-type shock and subsequent depletion of the gas-phase species onto grain mantles.

Bergin, Edwin A.↗

Simulation of etch pit formation through active sites in carbon fiber micro-structures

Erosion of carbon due to oxidation does not occur uniformly but through localized etch pit formation as a result of active surface sites. In this work we demonstrate a newly developed capability to capture pitting of carbon fiber microstructures such as FiberForm, which is commonly used as the base material for NASA’s spacecraft ablative thermal protection systems (TPS). The simulations are performed at the meso-scale in order to capture the pit formation and growth using direct simulation Monte Carlo (DSMC), specifically using the Stochastic PArallel Rarefied-gas Time-accurate Analyzer (SPARTA) code. Legacy and latest models both assume uniform reactivity of carbon surface sites with oxygen even at the meso-scale level. However, in reality the carbon surface has locally different reaction rates due to the presence of defects at the atomic scale. The defective nature of these sites enhances their reactivity with atmospheric gases compared to the non-defective sites (2-3 orders of magnitude) and are termed as “active sites”. Thus, these sites tend to be the first to react and eventually get removed through the formation of gasses such as CO, CO2, and CN. Their removal results in all the neighboring atoms becoming defective, thus leading to chain reaction of localized carbon removal and formation of etch pits. Capturing the formation of pits during the ablation simulation of carbon micro-structures is critical to predicting their structural failure. Recently a detailed surface chemistry framework was developed in SPARTA, capable of incorporating various reaction mechanisms such as adsorption, desorption, Eley-Rideal (ER) and Langmuir-Hinshelwood (LH) mechanisms. We have implemented the capability of a single surface having multiple site sets with different reactivities within this framework. We have used this feature to model the presence of active sites on carbon surfaces, whose reactivity is orders of magnitude higher than that of the passive sites due to the presence of defects. The active site fraction is a property of surface elements within SPARTA and is directly proportional to the local reactivity of each surface element. By introducing an initial distribution of the active site fraction across the carbon surface and propagating it in a manner that mimics the evolution of real reacting carbon surfaces, we can capture the formation and growth of etch pits as a result of surface consumption reactions such as oxidation.

DSMC↗

Simulation of Etch Pit Formation in DSMC Through Active Sites in Carbon Fiber Micro-Structures

Erosion of carbon due to oxidation does not occur uniformly but through localized etch pit formation because of active surface sites. In this work we demonstrate a newly developed capability to capture pitting of carbon fiber microstructures such as FiberForm, which is commonly used as the base material for NASA’s spacecraft ablative thermal protection systems (TPS). The simulations are performed at the meso-scale in order to capture the pit formation and growth using direct simulation Monte Carlo (DSMC), specifically using the Stochastic PArallel Rarefied-gas Time-accurate Analyzer (SPARTA) code. Legacy and latest models both assume uniform reactivity of carbon surface sites with oxygen even at the meso-scale level. However, in reality the carbon surface has locally different reaction rates due to the presence of defects at the atomic scale. The defective nature of these sites enhances their reactivity with atmospheric gases compared to the non-defective sites (2-3 orders of magnitude) and are termed as “active sites”. Thus, these sites tend to be the first to react and eventually get removed through the formation of gases such as CO, CO2, and CN. Their removal results in all the neighboring atoms becoming defective, thus leading to chain reaction of localized carbon removal and formation of etch pits. Capturing the formation of pits during the ablation simulation of carbon micro-structures is critical to predicting their structural failure. Recently a detailed surface chemistry framework was developed in SPARTA, capable of incorporating various detailed surface reaction mechanisms. We have implemented the capability of a single surface having multiple site sets with different reactivities within this framework. We have used this feature to model the presence of active sites on carbon surfaces, whose reactivity is orders of magnitude higher than that of the passive sites due to the presence of defects. The active site fraction is a property of surface elements within SPARTA and is directly proportional to the local reactivity of each surface element. By introducing an initial distribution of the active site fraction across the carbon surface and propagating it in a manner that mimics the evolution of real reacting carbon surfaces, we can capture the formation and growth of etch pits as a result of surface consumption reactions such as oxidation.

DSMC↗

DSMC Simulation of Etch Pit Formation Through Active Sites in Carbon Fiber Micro-Structures

Erosion of carbon due to oxidation does not occur uniformly but through localized etch pit formation because of active surface sites. In this work we demonstrate a newly developed capability to capture pitting of carbon fiber microstructures such as FiberForm, which is commonly used as the base material for NASA’s spacecraft ablative thermal protection systems (TPS). The simulations are performed at the meso-scale in order to capture the pit formation and growth using direct simulation Monte Carlo (DSMC), specifically using the Stochastic PArallel Rarefied-gas Time-accurate Analyzer (SPARTA) code. Legacy and latest models both assume uniform reactivity of carbon surface sites with oxygen even at the meso-scale level. However, in reality the carbon surface has locally different reaction rates due to the presence of defects at the atomic scale. The defective nature of these sites enhances their reactivity with atmospheric gases compared to the non-defective sites (2-3 orders of magnitude) and are termed as “active sites”. Thus, these sites tend to be the first to react and eventually get removed through the formation of gases such as CO, CO2, and CN. Their removal results in all the neighboring atoms becoming defective, thus leading to chain reaction of localized carbon removal and formation of etch pits. Capturing the formation of pits during the ablation simulation of carbon micro-structures is critical to predicting their structural failure. Recently a detailed surface chemistry framework was developed in SPARTA, capable of incorporating various detailed surface reaction mechanisms. We have implemented the capability of a single surface having multiple site sets with different reactivities within this framework. We have used this feature to model the presence of active sites on carbon surfaces, whose reactivity is orders of magnitude higher than that of the passive sites due to the presence of defects. The active site fraction is a property of surface elements within SPARTA and is directly proportional to the local reactivity of each surface element. By introducing an initial distribution of the active site fraction across the carbon surface and propagating it in a manner that mimics the evolution of real reacting carbon surfaces, we can capture the formation and growth of etch pits as a result of surface consumption reactions such as oxidation.

DSMC↗

The cost of conservative synchronization in parallel discrete event simulations

The performance of a synchronous conservative parallel discrete-event simulation protocol is analyzed. The class of simulation models considered is oriented around a physical domain and possesses a limited ability to predict future behavior. A stochastic model is used to show that as the volume of simulation activity in the model increases relative to a fixed architecture, the complexity of the average per-event overhead due to synchronization, event list manipulation, lookahead calculations, and processor idle time approach the complexity of the average per-event overhead of a serial simulation. The method is therefore within a constant factor of optimal. The analysis demonstrates that on large problems--those for which parallel processing is ideally suited--there is often enough parallel workload so that processors are not usually idle. The viability of the method is also demonstrated empirically, showing how good performance is achieved on large problems using a thirty-two node Intel iPSC/2 distributed memory multiprocessor.

Nicol, David M.↗

Influence of maneuverability on helicopter combat effectiveness

A computational procedure employing a stochastic learning method in conjunction with dynamic simulation of helicopter flight and weapon system operation was used to derive helicopter maneuvering strategies. The derived strategies maximize either survival or kill probability and are in the form of a feedback control based upon threat visual or warning system cues. Maneuverability parameters implicit in the strategy development include maximum longitudinal acceleration and deceleration, maximum sustained and transient load factor turn rate at forward speed, and maximum pedal turn rate and lateral acceleration at hover. Results are presented in terms of probability of skill for all combat initial conditions for two threat categories.

Falco, M.↗

An identification algorithm for linear stochastic systems with time delays

Linear discrete stochastic control systems containing unknown multiple time delays, plant parameters and noise variances are considered. An algorithm is established which uses the maximum-likelihood technique to identify the unknown parameters. An estimated likelihood function is evaluated based on the previous parameter estimates, which in turn generates a new descent direction vector to update the unknown parameters. The delays and plant parameters are identified in their respective parameter spaces. An example of a second-order stochastic system has been implemented by digital simulation to demonstrate the applicability of the algorithm.

Leondes, C. T.↗

Technology programs and related policies - Impacts on communications satellite business ventures

The DOMSAT II stochastic communication satellite business venture financial planning simulation model is described. The specification of business scenarios and the results of several analyses are presented. In particular, the impacts of NASA on-orbit propulsion and power technology programs are described. The effects of insurance rates and self-insurance and of the use of the Space Shuttle and Ariane transportation systems on a typical fixed satellite service business venture are discussed.

Greenberg, J. S.↗

Stochastic prediction techniques for wind shear hazard assessment

The threat of low-altitude wind shear has prompted development of aircraft-based sensors that measure winds directly on the aircraft's intended flight path. Measurements from these devices are subject to turbulence inputs and measurement error, as well as to the underlying wind profile. Stochastic estimators are developed to process on-board Doppler sensor measurements, producing optimal estimates of the winds along the path. A stochastic prediction technique is described to predict the hazard to the aircraft from the estimates as well as the level of uncertainty of the hazard prediction. The stochastic prediction technique is demonstrated in a simulated microburst wind shear environment. Use of the technique in a decision-making process is discussed.

Stratton, D. A.↗

Stochastic Evolutionary Algorithms for Planning Robot Paths

A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.

Fink, Wolfgang↗

Cost and Throughput Analysis for the NASA Ames Arc Jet Modernization Program

NASA Ames Center is currently evaluating alternatives to modernize the Arc Jet Complex, a critical part of testing for NASA’s planetary missions. NASA’s Arc Jet Complex facilities “are used to simulate the aerothermodynamic heating that a spacecraft endures throughout hypersonic atmospheric entry, and to test candidate thermal protection system (TPS) materials and systems. “Because planetary mission schedules often have tight windows due to planetary alignment constraints, a small increase in schedule could result in a two-year delay. Such a delay could increase the cost of a $1billionmissionbyhundreds of millions of dollars due to project personnel pay and clean room storage. To avoid these costs, the authors support NASA Ames in evaluating return on investment (ROI) and effectiveness of alternatives for modernizing the complex. The first input into the ROI is the deconstruction and construction cost estimates, which are developed using independent research on highly specialized subsystems, vendor quotes, and Unified Facilities Criteria (UFC), depending on the facility and work package. One of the measures of effectiveness is throughput analysis of the test bays, as a main goal of the modernization is to increase the number of possible test runs per year. This analysis is conducted via a probabilistic simulation and accounts for a variety of stochastic factors that influence the sequence of test runs, such as the facility availability; test complexity; the need to pause to assess test results; test failure; and the possibility of a system failure. The methodologies for both these analyses are discussed, along with the challenges presented due to the unique nature of the highly specialized test equipment.

Jennifer Scheel↗

Controlled Parametric Forcing During Directional Solidification of a Bulk Organic Alloy Under Microgravity

The response of dendritic microstructures to step-like pulling velocity conditions is investigated using microgravity directional solidification experiments conducted on DECLIC-DSI combined with phase-field simulations. Under a constant pulling velocity of 1.5 µm/s, the evolution toward steady-state growth is characterized in terms of primary spacing, dendrite drift, and tip dynamics. For the first time, side-view observations enabled direct measurement of tip radius and sidebranching frequency. When step-like oscillations of the pulling velocity are imposed, the dendritic array exhibits a strongly period-dependent response: short periods lead to rapid tip adaptation, whereas longer periods induce a phase lag between tip position and morphology, resulting in progressive tip flattening and, above a critical period, interface destabilization and dendrite splitting. Quantitative phase-field simulations, including a realistic thermal field and stochastic noise, reproduce the experimental observations and provide insight into the governing mechanisms, highlighting the role of characteristic relaxation times, sequence-dependent effects, and the irreversible reorganization of the microstructure following splitting.

Microgravity↗

Megadroughts in Southwestern North America in ECHO-G Millennial Simulations and Their Comparison to Proxy Drought Reconstructions

Simulated hydroclimate variability in millennium-length forced transient and control simulations from the ECHAM and the global Hamburg Ocean Primitive Equation (ECHO-G) coupled atmosphere-ocean general circulation model (AOGCM) is analyzed and compared to 1000 years of reconstructed Palmer drought severity index (PDSI) variability from the North American Drought Atlas (NADA). The ability of the model to simulate megadroughts in the North American southwest is evaluated. (NASW: 25deg42.5degN, 125deg-105degW). Megadroughts in the ECHO-G AOGCM are found to be similar in duration and magnitude to those estimated from the NADA. The droughts in the forced simulation are not, however, temporally synchronous with those in the paleoclimate record, nor are there significant differences between the drought features simulated in the forced and control runs. These results indicate that model-simulated megadroughts can result from internal variability of the modeled climate system rather than as a response to changes in exogenous forcings. Although the ECHO-G AOGCM is capable of simulating megadroughts through persistent La Nina-like conditions in the tropical Pacific, other mechanisms can produce similarly extreme NASW moisture anomalies in the model. In particular, the lack of low-frequency coherence between NASW soil moisture and simulated modes of climate variability like the El Nino-Southern Oscillation, Pacific decadal oscillation, and Atlantic multidecadal oscillation during identified drought periods suggests that stochastic atmospheric variability can contribute significantly to the occurrence of simulated megadroughts in the NASW. These findings indicate that either an expanded paradigm is needed to understand multidecadal hydroclimate variability in the NASW or AOGCMs may incorrectly simulate the strength and/or dynamics of the connection between NASW hydroclimate variability and the tropical Pacific.

variability↗

Stochastic solution to quantum dynamics

The quantum Liouville equation in the Wigner representation is solved numerically by using Monte Carlo methods. For incremental time steps, the propagation is implemented as a classical evolution in phase space modified by a quantum correction. The correction, which is a momentum jump function, is simulated in the quasi-classical approximation via a stochastic process. The technique, which is developed and validated in two- and three- dimensional momentum space, extends an earlier one-dimensional work. Also, by developing a new algorithm, the application to bound state motion in an anharmonic quartic potential shows better agreement with exact solutions in two-dimensional phase space.

John, Sarah↗

Accumulation of the terrestrial planets and implications concerning lunar origin

In order to provide a context for understanding lunar formation, 28 new three-dimensional simulations of terrestrial planet formation from a gas-free planetesimal swarm have been carried out. The natural orbital and collisional evolution of 500 initial planetesimals ranging in mass from 5.7 x 10 to the 24th g to 1.1 x 10 to the 26th g is followed until only final planets in noncrossing orbits remain. The results are in general agreement with the number, size, and orbits of the observed terrestrial planets, but also show considerable variation of stochastic origin. These results are combined with 11 simulations using 500 bodies of equal initial mass presented earlier, as well as with some other numerical studies, to conclude that for a wide range of initial conditions, terrestrial planet accumulation was characterized by giant impacts, ranging in mass up to 3 times the mass of Mars, at typical impact velocities of about 9 km/sec. These large planetesimals and the impacts they produce are sufficient to explain the unexpectedly large angular momentum of the earth-moon system.

Wetherill, G. W.↗

A simulation to study the feasibility of improving the temporal resolution of LAGEOS geodynamic solutions by using a sequential process noise filter

A key drawback to estimating geodetic and geodynamic parameters over time based on satellite laser ranging (SLR) observations is the inability to accurately model all the forces acting on the satellite. Errors associated with the observations and the measurement model can detract from the estimates as well. These 'model errors' corrupt the solutions obtained from the satellite orbit determination process. Dynamical models for satellite motion utilize known geophysical parameters to mathematically detail the forces acting on the satellite. However, these parameters, while estimated as constants, vary over time. These temporal variations must be accounted for in some fashion to maintain meaningful solutions. The primary goal of this study is to analyze the feasibility of using a sequential process noise filter for estimating geodynamic parameters over time from the Laser Geodynamics Satellite (LAGEOS) SLR data. This evaluation is achieved by first simulating a sequence of realistic LAGEOS laser ranging observations. These observations are generated using models with known temporal variations in several geodynamic parameters (along track drag and the J(sub 2), J(sub 3), J(sub 4), and J(sub 5) geopotential coefficients). A standard (non-stochastic) filter and a stochastic process noise filter are then utilized to estimate the model parameters from the simulated observations. The standard non-stochastic filter estimates these parameters as constants over consecutive fixed time intervals. Thus, the resulting solutions contain constant estimates of parameters that vary in time which limits the temporal resolution and accuracy of the solution. The stochastic process noise filter estimates these parameters as correlated process noise variables. As a result, the stochastic process noise filter has the potential to estimate the temporal variations more accurately since the constraint of estimating the parameters as constants is eliminated. A comparison of the temporal resolution of solutions obtained from standard sequential filtering methods and process noise sequential filtering methods shows that the accuracy is significantly improved using process noise. The results show that the positional accuracy of the orbit is improved as well. The temporal resolution of the resulting solutions are detailed, and conclusions drawn about the results. Benefits and drawbacks of using process noise filtering in this type of scenario are also identified.

Hartman, Brian Davis↗

A dynamic localization model with stochastic backscatter

The modeling of subgrid scales in large-eddy simulation (LES) has been rationalized by the introduction of the dynamic localization procedure. This method allows one to compute rather than prescribe the unknown coefficients in the subgrid-scale model. Formally, the LES equations are supposed to be obtained by applying to the Navier-Stokes equations a 'grid filter' operation. Though the subgrid stress itself is unknown, an identity between subgrid stresses generated by different filters has been derived. Although preliminary tests of the Dynamic Localization Model (DLM) with k-equation have been satisfactory, the use of a negative eddy viscosity to describe backscatter is probably a crude representation of the physics of reverse transfer of energy. Indeed, the model is fully deterministic. Knowing the filtered velocity field and the subgrid-scale energy, the subgrid stress is automatically determined. We know that the LES equations cannot be fully deterministic since the small scales are not resolved. This stems from an important distinction between equilibrium hydrodynamics and turbulence. In equilibrium hydrodynamics, the molecular motions are also not resolved. However, there is a clear separation of scale between these unresolved motions and the relevant hydrodynamic scales. The result of molecular motions can then be separated into an average effect (the molecular viscosity) and some fluctuations. Due to the large number of molecules present in a box with size of the order of the hydrodynamic scale, the ratio between fluctuations and the average effect should be very small (as a result of the 'law of large numbers'). For that reason, the hydrodynamic balance equations are usually purely deterministic. In turbulence, however, there is no clear separation of scale between small and large eddies. In that case, the fluctuations around a deterministic eddy viscosity term could be significant. An eddy noise would then appear through a stochastic term in the subgrid-scale model and could be the source of backscatter.

Carati, Daniele↗

Simulation of Galactic Cosmic Rays and Dose-Rate Effects in RITRACKS

The NASA Space Radiation Laboratory (NSRL) facility has been used successfully for many years to generate ion beams for radiation research experiments by NASA investigators. Recently, modifications were made to the beam lines to allow rapid switching between different types of ions and energies, with the aim to simulate the Galactic Cosmic Rays (GCR) environment. As this will be a focus of space radiation research for upcoming years, the stochastic radiation track structure code RITRACKS (Relativistic Ion Tracks) was modified to simulate beams of various ion types and energies during time intervals specified by the user at the microscopic and nanoscopic scales. For example, particle distributions of a mixed 344.1-MeV protons (18.04 cGy) and 950-MeV/n iron (5.64 cGy) beam behind a 20 g/cm(exp 2) aluminum followed by a 10 g/cm(exp 2) polyethylene shield as calculated by the code GEANT4 were used as an input field in RITRACKS. Similarly, modifications were also made to simulate a realistic radiation environment in a spacecraft exposed to GCR by sampling the ion types and energies from particle spectra pre-calculated by the code HZETRN. The newly implemented features allows RITRACKS to generate time-dependent differential and cumulative 3D dose voxel maps. These new capabilities of RITRACKS will be used to investigate dose-rate effects and synergistic interactions of various types of radiations for many end points at the microscopic and nanoscopic scales such as DNA damage and chromosome aberrations.

Plante, Ianik↗