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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Evaluation of Composite Airframe Dynamic Impact Modeling Using Hawker 4000 Fuselage Drop Test Data

Two drop tests of partial Hawker 4000 fuselage sections were conducted at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) to characterize the response of representative composite aerospace structure to dynamic impact loads. Test conditions were selected to induce damage into the composite structure in order to study material failure within a composite fuselage and evaluate the capability of finite element (FE) model analysis to predict that failure. The tests were simulated using FE models which were generated to isolate the effect of developmental data availability on predictive capability. FE Models of the tested fuselage sections were generated using two limited data sets. The first model configuration was reverse engineered from the test article with no information related to design or fabrication details which would be known only by the manufacturer. The second model was generated from data provided by the manufacturer but without additional material characterization test data. Models were developed using these methodologies for both fuselage sections tested. Correlation of each model to the tests conducted was evaluated in terms of damage, deformation, and cabin acceleration measurements. Correlation between the developed models and the tested fuselage sections showed that the reverse engineered model predicted the composite damage and cabin acceleration measured during test though it was limited due to lack of detail in the composite layup changes through the structure. The model developed using manufacturer specifications did not predict damage, due to limited material and component model characterization data, but it did predict acceleration on par with the reverse engineered model. Model capability and limitation sources identified were verified through correlation of a final model which was developed by combining the individual data sets. The combined model demonstrated that the addition of calibrated composite material models to accurate composite layup definitions and detailed geometry led to improved correlation of damage and acceleration response within the composite fuselage structures.

Crashworthiness↗
NASA NTRS2017

Multi-Model Impacts of Climate Change on Pollution Transport from Global Emission Source Regions

The impacts of climate change on tropospheric transport, diagnosed from a carbon monoxide (CO)-like tracer species emitted from global CO sources, are evaluated from an ensemble of four chemistry-climate model (CCMs) contributing to the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Model time-slice simulations for present-day and end of the 21st century conditions were performed under the Representative Concentrations Pathways (RCP) climate scenario RCP 8.5. All simulations reveal a strong seasonality in transport, especially over the tropics. The highest CO-tracer mixing ratios aloft occur during boreal winter when strong vertical transport is co-located with biomass burning emission source regions. A consistent and robust decrease in future CO-tracer mixing ratios throughout most of the troposphere, especially in the tropics, and an increase around the tropopause is found across the four CCMs in both winter and summer. Decreases in CO-tracer mixing ratios in the tropical troposphere are associated with reduced convective mass fluxes in this region, which in turn may reflect a weaker Hadley Cell circulation in the future climate. Increases in CO-tracer mixing ratios near the tropopause are largely attributable to a rise in tropopause height, although a poleward shift in the midlatitude jets may also play an important role in the extra-tropical upper troposphere. An increase in CO-tracer mixing ratios also occurs near the Equator, centred over EquatorialCentral Africa, extending from the surface to the mid troposphere which is most likely related to localised decreases in convection in the vicinity of the Intertropical Convergence Zone, resulting in larger CO-tracer mixing ratios over biomass burning regions and smaller mixing ratios downwind.

Tropospheric Transport↗
NASA NTRS2000

Application of a Reduced Order Kalman Filter to Initialize a Coupled Atmosphere-Ocean Model: Impact on the Prediction of El Nino

A reduced order Kalman Filter, based on a simplification of the Singular Evolutive Extended Kalman (SEEK) filter equations, is used to assimilate observed fields of the surface wind stress, sea surface temperature and sea level into the nonlinear coupled ocean-atmosphere model. The SEEK filter projects the Kalman Filter equations onto a subspace defined by the eigenvalue decomposition of the error forecast matrix, allowing its application to high dimensional systems. The Zebiak and Cane model couples a linear reduced gravity ocean model with a single vertical mode atmospheric model of Zebiak. The compatibility between the simplified physics of the model and each observed variable is studied separately and together. The results show the ability of the model to represent the simultaneous value of the wind stress, SST and sea level, when the fields are limited to the latitude band 10 deg S - 10 deg N. In this first application of the Kalman Filter to a coupled ocean-atmosphere prediction model, the sea level fields are assimilated in terms of the Kelvin and Rossby modes of the thermocline depth anomaly. An estimation of the error of these modes is derived from the projection of an estimation of the sea level error over such modes. This method gives a value of 12 for the error of the Kelvin amplitude, and 6 m of error for the Rossby component of the thermocline depth. The ability of the method to reconstruct the state of the equatorial Pacific and predict its time evolution is demonstrated. The method is shown to be quite robust for predictions I up to six months, and able to predict the onset of the 1997 warm event fifteen months before its occurrence.

Ballabrera-Poy, Joaquim↗
NASA NTRS2000

Application of a Reduced Order Kalman Filter to Initialize a Coupled Atmosphere-Ocean Model: Impact on the Prediction of El Nino

A reduced order Kalman Filter, based on a simplification of the Singular Evolutive Extended Kalman (SEEK) filter equations, is used to assimilate observed fields of the surface wind stress, sea surface temperature and sea level into the nonlinear coupled ocean-atmosphere model of Zebiak and Cane. The SEEK filter projects the Kalman Filter equations onto a subspace defined by the eigenvalue decomposition of the error forecast matrix, allowing its application to high dimensional systems. The Zebiak and Cane model couples a linear reduced gravity ocean model with a single vertical mode atmospheric model of Zebiak. The compatibility between the simplified physics of the model and each observed variable is studied separately and together. The results show the ability of the model to represent the simultaneous value of the wind stress, SST and sea level, when the fields are limited to the latitude band 10 deg S - 10 deg N In this first application of the Kalman Filter to a coupled ocean-atmosphere prediction model, the sea level fields are assimilated in terms of the Kelvin and Rossby modes of the thermocline depth anomaly. An estimation of the error of these modes is derived from the projection of an estimation of the sea level error over such modes. This method gives a value of 12 for the error of the Kelvin amplitude, and 6 m of error for the Rossby component of the thermocline depth. The ability of the method to reconstruct the state of the equatorial Pacific and predict its time evolution is demonstrated. The method is shown to be quite robust for predictions up to six months, and able to predict the onset of the 1997 warm event fifteen months before its occurrence.

Ballabrera-Poy, J.↗
NASA NTRS1991

Clouds-radiation interactions in a general circulation model - Impact upon the planetary radiation balance

Simultaneously conducted observations of the earth radiation budget and the cloud amount estimates, taken during the June 1979 - May 1980 Nimbus 7 mission were used to show interactions between the cloud amount and raidation and to verify a long-term climate simulation obtained with the latest version of the NCAR Community Climate Model (CCM). The parameterization of the radiative, dynamic, and thermodynamic processes produced the mean radiation and cloud quantities that were in reasonable agreement with satellite observations, but at the expense of simulating their short-term fluctuations. The results support the assumption that the inclusion of the cloud liquid water (ice) variable would be the best mean to reduce the blinking of clouds in NCAR CCM.

Smith, Laura D.↗
NASA NTRS1999

Modeled Impact of Cirrus Cloud Increases Along Aircraft Flight Paths

The potential impact of contrails and alterations in the lifetime of background cirrus due to subsonic airplane water and aerosol emissions has been investigated in a set of experiments using the GISS GCM connected to a q-flux ocean. Cirrus clouds at a height of 12-15km, with an optical thickness of 0.33, were input to the model "x" percentage of clear-sky occasions along subsonic aircraft flight paths, where x is varied from .05% to 6%. Two types of experiments were performed: one with the percentage cirrus cloud increase independent of flight density, as long as a certain minimum density was exceeded; the other with the percentage related to the density of fuel expenditure. The overall climate impact was similar with the two approaches, due to the feedbacks of the climate system. Fifty years were run for eight such experiments, with the following conclusions based on the stable results from years 30-50 for each. The experiments show that adding cirrus to the upper troposphere results in a stabilization of the atmosphere, which leads to some decrease in cloud cover at levels below the insertion altitude. Considering then the total effect on upper level cloud cover (above 5 km altitude), the equilibrium global mean temperature response shows that altering high level clouds by 1% changes the global mean temperature by 0.43C. The response is highly linear (linear correlation coefficient of 0.996) for high cloud cover changes between 0. 1% and 5%. The effect is amplified in the Northern Hemisphere, more so with greater cloud cover change. The temperature effect maximizes around 10 km (at greater than 40C warming with a 4.8% increase in upper level clouds), again more so with greater warming. The high cloud cover change shows the flight path influence most clearly with the smallest warming magnitudes; with greater warming, the model feedbacks introduce a strong tropical response. Similarly, the surface temperature response is dominated by the feedbacks, and shows little geographical relationship to the high cloud input. Considering whether these effects would be observable, changing upper level cloud cover by as little as 0.4% produces warming greater than 2 standard deviations in the Microwave Sounding Unit (MSU) channels 4, 2 and 2r, in flight path regions and in the subtropics. Despite the simplified nature of these experiments, the results emphasize the sensitivity of the modeled climate to high level cloud cover changes, and thus the potential ability of aircraft to influence climate by altering clouds in the upper troposphere.

Rind, David↗
NASA NTRSDate not supplied

Modeled Impacts of LULC and Climate Change Predictions on Water Quality in Belize

Land use and land cover (LULC) change can have detrimental effects on water quality. In Belize, agricultural expansion creates the risk of increased sediment load and excess nutrients in runoff water, while deforestation removes potential infiltration sites for this outflow. Climate change and evolving precipitation rates can intensify the quantity of runoff, further enabling the flow of sediments and excess nutrients out to the lagoon surrounding the Belize Barrier Reef Reserve System (BBRRS). This study estimated future water quality in Belize by projecting LULC change through 2090 across Belize’s major watersheds based on observed trends from 2008-2018. Those LULC projections were subsequently combined with soil type data, elevation, and precipitation rates into a hydrologic model to produce runoff estimates as a proxy for water quality. The two Coupled Model Intercomparison Project phase 6 (CMIP-6) scenarios employed in the study represented bookend climate change scenarios, and both predicted lower precipitation rates in Belize over the next century due to climate change. When holding LULC change constant, these climate scenarios projected a decrease in runoff, suggesting a positive relationship between precipitation and runoff. The southern watersheds in particular are projected to experience greater decreases in annual rainfall and runoff by 2090. When holding climate constant, runoff increased by approximately 2.8% in the Conservation-focused LULC scenario by 2090, which was 28% lower than the Business as Usual scenario and 42% lower than the Development scenario.

water resources↗
NASA NTRSDate not supplied

Sensitivity Analysis of the Human Research Program’s Impact 1.0 Model

Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Leave One Out (LOO) are methods of conducting sensitivity analysis on non-linear simulation models like the IMPACT Model. The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The “partial” part is due to the adjustments made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. LOO removes a medical condition from test suite and calculates the change in the outcome. This is used to identify the influence of the condition input in the model The inputs to the sensitivity procedures include the number of occurrences of each of the one hundred plus IMPACT medical conditions generated over the simulations, and the IMPACT outputs from the MEDPRAT mathematical model. The outputs total task time lost (TTL), number of return to definitive care (RTDC), and number of loss of crew lives (LOCL). The IMPACT team will report the results of using PRCC and LOO on IMPACT 1.0. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty, and input values could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMPACT 1.0.

Sensitivity Anaylsis↗
NASA NTRS2009

Developing Soil Models for Dynamic Impact Simulations

This paper describes fundamental soils characterization work performed at NASA Langley Research Center in support of the Subsonic Rotary Wing (SRW) Aeronautics Program and the Orion Landing System (LS) Advanced Development Program (ADP). LS-DYNA(Registered TradeMark)1 soil impact model development and test-analysis correlation results are presented for: (1) a 38-ft/s vertical drop test of a composite fuselage section, outfitted with four blocks of deployable energy absorbers (DEA), onto sand, and (2) a series of impact tests of a 1/2-scale geometric boilerplate Orion capsule onto soil. In addition, the paper will discuss LS-DYNA contact analysis at the soil/structure interface, methods used to estimate frictional forces, and the sensitivity of the model to density, moisture, and compaction.

Fasanella, Edwin L.↗
NASA NTRS2012

Foam-on-Tile Damage Model

An impact model was developed to predict how three specific foam types would damage the Space Shuttle Orbiter insulating tiles. The inputs needed for the model are the foam type, the foam mass, the foam impact velocity, the foam impact incident angle, the type being impacted, and whether the tile is new or aged (has flown at least one mission). The model will determine if the foam impact will cause damage to the tile. If it can cause damage, the model will output the damage cavity dimensions (length, depth, entry angle, exit angle, and sidewall angles). It makes the calculations as soon as the inputs are entered (less than 1 second). The model allows for the rapid calculation of numerous scenarios in a short time. The model was developed from engineering principles coupled with significant impact testing (over 800 foam impact tests). This model is applicable to masses ranging from 0.0002 up to 0.4 pound (0.09 up to 181 g). A prior tool performed a similar function, but was limited to the assessment of a small range of masses and did not have the large test database for verification. In addition, the prior model did not provide outputs of the cavity damage length, entry angle, exit angle, or sidewall angles.

Koharchik, Michael↗
NASA NTRS2017

Validation Testing of a Peridynamic Impact Damage Model Using NASA's Micro-Particle Gun

Through a collaborative effort between the Virginia Commonwealth University and Raytheon, a peridynamic model for sand impact damage has been developed1-3. Model development has focused on simulating impacts of sand particles on ZnS traveling at velocities consistent with aircraft take-off and landing speeds. The model reproduces common features of impact damage including pit and radial cracks, and, under some conditions, lateral cracks. This study focuses on a preliminary validation exercise in which simulation results from the peridynamic model are compared to a limited experimental data set generated by NASA's recently developed micro-particle gun (MPG). The MPG facility measures the dimensions and incoming and rebound velocities of the impact particles. It also links each particle to a specific impact site and its associated damage. In this validation exercise parameters of the peridynamic model are adjusted to fit the experimentally observed pit diameter, average length of radial cracks and rebound velocities for 4 impacts of 300 μm glass beads on ZnS. Results indicate that a reasonable fit of these impact characteristics can be obtained by suitable adjustment of the peridynamic input parameters, demonstrating that the MPG can be used effectively as a validation tool for impact modeling and that the peridynamic sand impact model described herein possesses not only a qualitative but also a quantitative ability to simulate sand impact events.

Baber, Forrest E.↗
NASA NTRS2024

Crew State and Risk Model (CSRM) - Medication Impacts on Physiologic Models for Exploration Class EVA Predictive Modeling and Operations

EVA and Environmental Physiology Laboratory (EEPL) wanted to expand upon the previous CSRM Physiologic Map to visually demonstrate the impact of medications on various modeling inputs that map to the seven physiologic models. It is acknowledged various physiologic states present during EVA could impact drug pharmacokinetics (i.e. pressure changes, core body temperature), which could impact pharmacodynamics. However, that is outside the scope of this document. The medications below represent the authors’ assumption of what medications will be available and able to impact an Artemis EVA and do not include the full ISS formulary, a final Artemis medical kit, or additional personal medications for individual crewmember’s chronic medical conditions.

Emma Ives↗
NASA NTRS2021

Land Surface Modeling Over the Dry Chaco: The Impact of Model Structures, and Soil, Vegetation and Land Cover Parameters

In this study, we tested the impact of a revised set of soil, vegetation and land cover parameters on the performance of three different state-of-the-art land surface models (LSMs) within the NASA Land Information System (LIS). The impact of this revision was tested over the South American Dry Chaco, an ecoregion characterized by deforestation and forest degradation since the 1980s. Most large-scale LSMs may lack the ability to correctly represent the ongoing deforestation processes in this region, because most LSMs use climatological vegetation indices and static land cover information. The default LIS parameters were revised with improved soil parameters, satellite-based interannually varying vegetation indices (leaf area index and green vegetation fraction) instead of climatological vegetation indices, and yearly land cover information instead of static land cover. A relative comparison in terms of water budget components and “efficiency space” for various baseline and revised experiments showed that large regional and long-term differences in the simulated water budget partitioning relate to different LSM structures, whereas smaller local differences resulted from updated soil, vegetation and land cover parameters. Furthermore, the different LSM structures redistributed water differently in response to these parameter updates. A time-series comparison of the simulations to independent satellite-based estimates of evapotranspiration and brightness temperature (Tb) showed that no LSM setup significantly outperformed another for the entire region and that not all LSM simulations improved with updated parameter values. However, the revised soil parameters generally reduced the bias between simulated surface soil moisture and pixel-scale in situ observations and the bias between simulated Tb and regional Soil Moisture Ocean Salinity (SMOS) observations. Our results suggest that the different hydrological responses of various LSMs to vegetation changes may need further attention to gain benefits from vegetation data assimilation.

Michiel Maertens↗
NASA NTRS2011

Multi-Dimensional Calibration of Impact Dynamic Models

NASA Langley, under the Subsonic Rotary Wing Program, recently completed two helicopter tests in support of an in-house effort to study crashworthiness. As part of this effort, work is on-going to investigate model calibration approaches and calibration metrics for impact dynamics models. Model calibration of impact dynamics problems has traditionally assessed model adequacy by comparing time histories from analytical predictions to test at only a few critical locations. Although this approach provides for a direct measure of the model predictive capability, overall system behavior is only qualitatively assessed using full vehicle animations. In order to understand the spatial and temporal relationships of impact loads as they migrate throughout the structure, a more quantitative approach is needed. In this work impact shapes derived from simulated time history data are used to recommend sensor placement and to assess model adequacy using time based metrics and orthogonality multi-dimensional metrics. An approach for model calibration is presented that includes metric definitions, uncertainty bounds, parameter sensitivity, and numerical optimization to estimate parameters to reconcile test with analysis. The process is illustrated using simulated experiment data.

Horta, Lucas G.↗