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At least 865 records · Page 48

A fresh look at crater scaling laws for normal and oblique hypervelocity impacts

With the concomitant increase in the amount of man-made debris and an ever increasing use of space satellites, the issue of accidental collisions with particles becomes more severe. While the natural micrometeoroid population is unavoidable and assumed constant, continued launches increase the debris population at a steady rate. Debris currently includes items ranging in size from microns to meters which originated from spent satellites and rocket cases. To understand and model these environments, impact damage in the form of craters and perforations must be analyzed. Returned spacecraft materials such as those from LDEF and Solar Max have provided such a testbed. From these space-aged samples various impact parameters (i.e., particle size, particle and target material, particle shape, relative impact speed, etc.) may be determined. These types of analyses require the use of generic analytic scaling laws which can adequately describe the impact effects. Currently, most existing analytic scaling laws are little more than curve-fits to limited data and are not based on physics, and thus are not generically applicable over a wide range of impact parameters. During this study, a series of physics-based scaling laws for normal and oblique crater and perforation formation has been generated into two types of materials: aluminum and Teflon.

Watts, A. J.↗

Uncertainty in Simulating Wheat Yields Under Climate Change

Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1,3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking.

exhaust gases↗

Planetary and Primitive Object Strength Measurement and Sampling Apparatus

Support is requested for continuation of a program of dynamic impact (harpoon) coring of planetary, comet, or asteroid surface materials. We have previously demonstrated that good quality cores are obtainable for planetary materials with compressive strengths less than 200 MPa. Since the dynamics of penetration are observable on a Discovery class spacecraft, which images the sampling operation, these data can be used with a model developed under this project, to measure in-situ strength and frictional strength of the crust of the object. During the last year we have developed a detailed analytic model of penetrator mechanics. Progress is reported for the solid penetrators experiments, the CIT penetrator model, and the impact spall sampling apparatus.

Ahrens, Thomas J.↗

AgMIP Training in Multiple Crop Models and Tools

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has the goal of using multiple crop models to evaluate climate impacts on agricultural production and food security in developed and developing countries. There are several major limitations that must be overcome to achieve this goal, including the need to train AgMIP regional research team (RRT) crop modelers to use models other than the ones they are currently familiar with, plus the need to harmonize and interconvert the disparate input file formats used for the various models. Two activities were followed to address these shortcomings among AgMIP RRTs to enable them to use multiple models to evaluate climate impacts on crop production and food security. We designed and conducted courses in which participants trained on two different sets of crop models, with emphasis on the model of least experience. In a second activity, the AgMIP IT group created templates for inputting data on soils, management, weather, and crops into AgMIP harmonized databases, and developed translation tools for converting the harmonized data into files that are ready for multiple crop model simulations. The strategies for creating and conducting the multi-model course and developing entry and translation tools are reviewed in this chapter.

farm crops↗

Adiabatic Gravitational Waveform Model for Compact Objects Undergoing Quasi-Circular Inspirals Into Rotating Massive Black Holes

We present bhpwave: a new python-based, open-source tool for generating the gravitational waveforms of stellar-mass compact objects undergoing quasicircular inspirals into rotating massive black holes. These binaries, known as extreme-mass-ratio inspirals (EMRIs), are exciting mHz gravitational wave sources for future space-based detectors such as the Laser Interferometer Space Antenna (LISA). Relativistic models of EMRI gravitational wave signals are necessary to unlock the full scientific potential of mHz detectors, yet few open-source EMRI waveform models exist. Thus we built bhpwave, which uses the adiabatic approximation from black hole perturbation theory to rapidly construct gravitational waveforms based on the leading-order inspiral dynamics of the binary. In this work, we present the theoretical and numerical foundations underpinning bhpwave. We also demonstrate how bhpwave can be used to assess the impact of EMRI modeling errors on LISA gravitational wave data analysis. In particular, we find that for retrograde orbits and slowly spinning black holes we can mismodel the gravitational wave phasing by as much as ∼10 radians without significantly biasing EMRI parameter estimation.

Zachary Nasipak↗

The Role of Model and Initial Condition Error in Numerical Weather Forecasting Investigated with an Observing System Simulation Experiment

A series of experiments that explore the roles of model and initial condition error in numerical weather prediction are performed using an observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO). The use of an OSSE allows the analysis and forecast errors to be explicitly calculated, and different hypothetical observing networks can be tested with ease. In these experiments, both a full global OSSE framework and an 'identical twin' OSSE setup are utilized to compare the behavior of the data assimilation system and evolution of forecast skill with and without model error. The initial condition error is manipulated by varying the distribution and quality of the observing network and the magnitude of observation errors. The results show that model error has a strong impact on both the quality of the analysis field and the evolution of forecast skill, including both systematic and unsystematic model error components. With a realistic observing network, the analysis state retains a significant quantity of error due to systematic model error. If errors of the analysis state are minimized, model error acts to rapidly degrade forecast skill during the first 24-48 hours of forward integration. In the presence of model error, the impact of observation errors on forecast skill is small, but in the absence of model error, observation errors cause a substantial degradation of the skill of medium range forecasts.

Model Error↗

The NASA JSC Hypervelocity Impact Test Facility (HIT-F)

The NASA Johnson Space Center Hypervelocity Impact Test Facility was created in 1980 to study the hypervelocity impact characteristics of composite materials. The facility consists of the Hypervelocity Impact Laboratory (HIRL) and the Hypervelocity Analysis Laboratory (HAL). The HIRL supports three different-size light-gas gun ranges which provide the capability of launching particle sizes from 100 micron spheres to 12.7 mm cylinders. The HAL performs three functions: (1) the analysis of data collected from shots in the HIRL, (2) numerical and analytical modeling to predict impact response beyond test conditions, and (3) risk and damage assessments for spacecraft exposed to the meteoroid and orbital debris environments.

Crews, Jeanne L.↗

Scaling effects in the impact response of graphite-epoxy composite beams

In support of crashworthiness studies on composite airframes and substructure, an experimental and analytical study was conducted to characterize size effects in the large deflection response of scale model graphite-epoxy beams subjected to impact. Scale model beams of 1/2, 2/3, 3/4, 5/6, and full scale were constructed of four different laminate stacking sequences including unidirectional, angle ply, cross ply, and quasi-isotropic. The beam specimens were subjected to eccentric axial impact loads which were scaled to provide homologous beam responses. Comparisons of the load and strain time histories between the scale model beams and the prototype should verify the scale law and demonstrate the use of scale model testing for determining impact behavior of composite structures. The nonlinear structural analysis finite element program DYCAST (DYnamic Crash Analysis of STructures) was used to model the beam response. DYCAST analysis predictions of beam strain response are compared to experimental data and the results are presented.

Jackson, Karen E.↗

A Linearized Prognostic Cloud Scheme in NASAs Goddard Earth Observing System Data Assimilation Tools

A linearized prognostic cloud scheme has been developed to accompany the linearized convection scheme recently implemented in NASA's Goddard Earth Observing System data assimilation tools. The linearization, developed from the nonlinear cloud scheme, treats cloud variables prognostically so they are subject to linearized advection, diffusion, generation, and evaporation. Four linearized cloud variables are modeled, the ice and water phases of clouds generated by large-scale condensation and, separately, by detraining convection. For each species the scheme models their sources, sublimation, evaporation, and autoconversion. Large-scale, anvil and convective species of precipitation are modeled and evaporated. The cloud scheme exhibits linearity and realistic perturbation growth, except around the generation of clouds through large-scale condensation. Discontinuities and steep gradients are widely used here and severe problems occur in the calculation of cloud fraction. For data assimilation applications this poor behavior is controlled by replacing this part of the scheme with a perturbation model. For observation impacts, where efficiency is less of a concern, a filtering is developed that examines the Jacobian. The replacement scheme is only invoked if Jacobian elements or eigenvalues violate a series of tuned constants. The linearized prognostic cloud scheme is tested by comparing the linear and nonlinear perturbation trajectories for 6-, 12-, and 24-h forecast times. The tangent linear model performs well and perturbations of clouds are well captured for the lead times of interest.

Precipitation↗

Optimal ride control for the Twin Otter, STOL aircraft

An aircraft with low wing loading, such as the deHavilland, Twin Otter, exhibits a relatively large acceleration sensitivity to wind gusts. These undesirable aircraft motions can be reduced using an automatic ride control system. In this paper, the techniques of quadratic optimal control theory are utilized to investigate the capabilities of such a ride control system. The effects of the wind gusts on the aircraft can be modeled by a vector stochastic process containing seven states. The impact of this disturbance model on the optimal control system structure is assessed and comparison is made to a system without gust feedback.

Holley, W. E.↗

The effect of matrix properties and fiber properties on impact failure mechanics

The low-velocity impact problem in graphite/epoxy composite sheets must be solved before large amounts of that material can be used in commercial aircraft. Many of the low-velocity impacts that affect aircraft parts occur during normal ground operations and maintenance. Service equipment and tools have masses above 1 kg, and at velocities of less than 3 m/s can impact structural parts with energies higher than composites can endure without degradation of stiffness or strength. Simple solutions were developed for large-mass, low-velocity impacts which can be modeled as quasi-static events. Static test data and impact data show that the fiber properties control the impact energy which can be absorbed before penetration. Matrix shear strength and peel resistance control the extent of delamination. Comparison of results from tough matrix and brittle matrix composites show that although tough matrices reduce the extent of delamination, they lead to more fiber damage in the contact area.

Elber, W.↗

Impact of increased TOVS signal on the NMC global spectral model - A tropical-plume case study

Temperature and moisture signals are extracted from operationally available TOVS channel radiances for a tropical plume that developed over the North Pacific in January 1989, and are inserted into the NMC's operational medium-range forecast model. Several 48-h forecasts are made to test the impact of the additional information. It is shown, at least within a single tropical plume event, that there is still unutilized information within operational TOVS satellite observations. This information resides in the moisture channels and within small-amplitude, but horiontally coherent, thermal features. Perturbed upper-tropospheric relative humidity patterns are smoother and more consistent with satellite imagery than is the historical forecast.

Mcguirk, James P.↗

The 3-Dimensional Inner and Outer Structure of Ejecta Around Eta Carinae as Detected by the STIS

The HST/STIS instrument was used successfully to perform a complete mapping of the Homunculus nebula at two wavelength ranges including H-alpha and H-beta with a spectral resolving power of about 5000 and a spatial resolution of 0.1". The individual spectra were merged to synthesize three-dimensional data cubes that contain a set of images of Eta Car with spatial resolution of 0.10 to 0.251, sliced at velocity increment of 10 -- 30 km/s. For the first time this unique method allows us to diagnose the origin of intrinsic narrow emission structure of the nebula with high spatial and velocity resolution. Our initial analysis revealed the inner emission structure appeared to trace an elongated bipolar shell (possibly other shells as well) with a scale size of an arcsecond (i.e., "little homunculus in the Homunculus"). Furthermore, the mapping data cube revealed that the "fan" or "paddle" -- often referred as the source of peculiar blue-shifted intrinsic emissions including the Strontium cloud -- is not the source of intrinsic emissions. The fan is not even a part of the equatorial disk, but is spatially separated from the peculiar emission structure. Indeed we suggest that the fan is a surface of the Northwest lobe, possibly revealed by a blowout of the equatorial disk. We will use a number of visualization techniques (tomographic animations and simple 3-D models) to show these structures. These new results have strong impact upon future numerical modelings of the Homunculus nebula and of understanding of the evolution of the ejecta powered by the central source(s).

Ishibashi, Kazunori↗

Experimental Methods in Materials for Structural Impact Dynamics

Over the past two decades significant technological advances have completely changed the way in which experimental testing is conducted in Structural Impact Dynamics applications. Probably the two most significant advances have been the advent of high speed digital video cameras and the use of Digital Image Correlation techniques to measure deformations and strains at high rates. These advances have led to significantly more accurate measurements of material and structural response under high rate loading, which has also led to advances in computational modeling techniques for Impact Dynamics. In this address we will review the past, present and what the future may hold for experimental methods in the field of Structural Impact Dynamics.

Structural Impact Dynamics↗

Robustness and Behavior of Adjoint Calculations of Observation Impacts in Numerical Weather Prediction

Adjoint models are powerful tools that can be used to estimate the impact of observations on a chosen norm for numerical weather prediction forecasts. In this study, the Global Modeling and Assimilation Office (NASA/GMAO) Observing System Simulation Experiment framework is employed to investigate the behavior of the adjoint tool in an environment where the 'true' state of the atmosphere is fully known. This allows for the calculation of adjoint estimates of observation impact for very short forecast times including the zero-hour analysis state. The adjoint calculations using self-analysis verification can also be compared to adjoint calculations using the 'truth' as verification in order to characterize the robustness of adjoint estimations in the operational setting. Results from a experiments exploring various aspects of performance of the adjoint tool will be presented.

Prive, Nikki C.↗

Cross correlations between the radiation and atmospheric variables in a general circulation model and satellite data

The classical picture of the influence of midlatitude troughs on cloud patterns is studied in a GCM and in satellite and NMC data, by comparing the cross correlation of the poleward component of the wind and the outgoing longwave radiation (OLR). Over storm tracks, the variance of the OLR is explained by a correlation with the poleward component of the horizontal wind, forced by stronger correlations with the vertical velocity through the cloud and humidity fields. It is found that stratiform clouds have a dominant impact on the model OLR fluctuations, even over much of the tropics.

Charlock, Thomas P.↗

Seasonal Soil Freeze/Thaw Variability Across North America via Ensemble Land Surface Modeling

Land surface modeling provides the opportunity to investigate winter soil processes such as soil freezing and thawing over large domains. However, the variability in simulated winter soil characteristics among land surface models and forcing datasets is not well understood. In this study, a nine-member ensemble was employed to characterize the spatial and inter-annual variability of three winter soil characteristics, annual number of frozen days, annual minimum temperature and annual number of freeze-thaw cycles over North America during the water years 2010–2016. The ensemble, including three land surface model (JULES, Noah2.7.1 and Noah-MP) and three forcing datasets (ECMWF, GDAS and MERRA2), was developed through the Snow Ensemble Uncertainty Project (SEUP). In many regions, there was remarkably good agreement across the ensemble for the winter soil temperatures. However, the variability among the ensemble's annual number of frozen days, as quantified with standard deviation, exceeded 150 days at the northern Pacific coastline. While the differences among the ensemble members' annual minimum temperature were typically <3 °C, the differences exceeded 6 °C north of 50°N. The ensemble members generally agreed within one to three freeze-thaw cycles in mid latitude regions, Alaska, and the south and west coasts of the USA. High variability among the ensemble, more than six freeze-thaw cycles, occurred in the Great Plains, northern Pacific coastline, and along the Appalachian Mountains. Differences in winter soil temperature characteristics were more apparent among the LSMs rather than the meteorological forcing datasets. Except for maritime regions, the Noah2.7.1 members had the fewest annual number of frozen days and the least number of freeze-thaw cycles. Noah2.7.1 also had the coldest annual minimum temperatures except for ephemeral regions. Comparisons between in-situ observations and the SEUP estimates of winter soil characteristics revealed that the modeled frozen period was much longer than observed, that the modeled annual minimum temperatures were much colder than observed, and the modeled freeze-thaw cycles occurred more frequently than observed. Excluding the high latitude sites, the observed frozen period is less than two months with the minimum temperature above − 5 °C at most of the studied sites, while the ensemble members simulated, on average, a four month frozen period with − 10 °C minimum temperature. Errors in capturing snow during the accumulation period appear to impact differences in modeled versus observed soil temperature throughout the entire winter.

Soil freeze/thaw↗