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DOE OSTI2020

Linking Hydrology and Dissolved Organic Matter Characteristics in a Subtropical Wetland: A Long-Term Study of the Florida Everglades

Dissolved organic matter (DOM) acts as an important biogeochemical component of aquatic ecosystems that controls nutrient cycling, influences water quality, and links terrestrial and oceanic carbon pools, yet long-term studies of how changing environmental drivers alter its abundance and composition are rare. Using a ten-year, spatially explicit dataset from Everglades National Park (ENP), a globally significant wetland, we investigated the relationships between DOM quality/quantity and hydrologic/climatic drivers along two contrasting marsh-estuarine transects based on generalized linear modeling and a cumulative sums analysis. Analyses revealed distinct spatial, seasonal, and interannual patterns in variability of DOC and optical properties. Landscape-scale seasonal patterns showed an enrichment in microbial-like and protein-like DOM during the dry season relative to the wet season. We found that, while some compositional constituents varied with the solar calendar, responsive to temperature and photoperiod, others varied with the hydrologic calendar. Independent water level and discharge effects indicated strong hydrologic control on DOM quality that differed between the two transects, evidencing differences in their connectivity to areas of high agricultural activity. Across all sites, a significant long-term increasing trend in the fluorescence index was observed, associated with a positive correlation with precipitation and also potential changes in agricultural inputs, with other features associated with drought and hurricanes. Lastly, the cumulative sums analysis revealed differences between the two transects in the sensitivity of DOM composition to decreased water levels associated with 30-year climate scenarios, with the less hydrologically dynamic transect exhibiting greater potential sensitivity.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2014

Missing Data and Multiple Imputation: An Unbiased Approach

The default method of dealing with missing data in statistical analyses is to only use the complete observations (complete case analysis), which can lead to unexpected bias when data do not meet the assumption of missing completely at random (MCAR). For the assumption of MCAR to be met, missingness cannot be related to either the observed or unobserved variables. A less stringent assumption, missing at random (MAR), requires that missingness not be associated with the value of the missing variable itself, but can be associated with the other observed variables. When data are truly MAR as opposed to MCAR, the default complete case analysis method can lead to biased results. There are statistical options available to adjust for data that are MAR, including multiple imputation (MI) which is consistent and efficient at estimating effects. Multiple imputation uses informing variables to determine statistical distributions for each piece of missing data. Then multiple datasets are created by randomly drawing on the distributions for each piece of missing data. Since MI is efficient, only a limited number, usually less than 20, of imputed datasets are required to get stable estimates. Each imputed dataset is analyzed using standard statistical techniques, and then results are combined to get overall estimates of effect. A simulation study will be demonstrated to show the results of using the default complete case analysis, and MI in a linear regression of MCAR and MAR simulated data. Further, MI was successfully applied to the association study of CO2 levels and headaches when initial analysis showed there may be an underlying association between missing CO2 levels and reported headaches. Through MI, we were able to show that there is a strong association between average CO2 levels and the risk of headaches. Each unit increase in CO2 (mmHg) resulted in a doubling in the odds of reported headaches.

Foy, M.↗

NASA NTRS2015

Chlorophyll Variability in the Oligotrophic Gyres: Mechanisms, Seasonality and Trends

A 16-year (1998-2013) analysis of trends and seasonal patterns was conducted for the 5 subtropical ocean gyres using chlorophyll-a (Chl-a) retrievals from ocean color satellite data, sea surface temperature (SST) obtained from optimally interpolated Advanced Very High Resolution Radiometer (AVHRR) data, and sea-level anomaly (SLA) from Aviso multi-sensor altimetry data. Trend analysis was also performed on mixed-layer data derived from gridded temperature and salinity profiles (1998-2010) from the Simple Ocean Data Assimilation (SODA) model. The Chl-a monthly composites were constructed from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate-resolution Imaging Spectroradiometer (MODIS) on Aqua using two different algorithms: the standard algorithm (STD) that has been in use since the start of the SeaWiFS mission in 1997, and a more recently developed Ocean Color Index (OCI) algorithm that is purported to provide improved accuracy in low chlorophyll waters such as the oligotrophic regions of the subtropical gyres. Trends were obtained for all gyres using both STD and OCI algorithms, which demonstrated generally consistent results. The North Pacific, Indian Ocean, North Atlantic and South Atlantic gyres showed significant downward trends in Chl-a, while the South Pacific gyre has a much weaker upward trend with no statistical significance. Time series of satellite-derived net primary production (NPP) showed downward trends for all the gyres, while all 5 gyres exhibited positive trends in SST and SLA. The seasonal variability of Chl-a in each gyre is tightly coupled to the variability in mixed layer depth (MLD) with peak values in winter in both hemispheres when vertical mixing is more vigorous, reaching depths approaching the nutricline (ZNO3, here defined as the depth of the 0.2 micron nitrate concentration). On a seasonal basis, Chl-a concentrations increase when the MLD approaches or is deeper than the nutricline depth, in agreement with the concept that vertical mixing is the major driving mechanism for phytoplankton photosynthesis in the interior of the gyres. In addition, MLD and SST seasonal changes are well correlated indicating that SST is a reasonable index of vertical mixing in the gyres. The combination of surface warming trends and biomass reduction over the 16-year period has the potential to reduce atmospheric CO2 uptake by the gyres and therefore influence the global carbon cycle.

Long-term trends↗

NASA NTRS2014

The Variable Hard X-Ray Emission of NGC4945 as Observed by NuSTAR

We present a broadband (approx. 0.5 - 79 keV) spectral and temporal analysis of multiple NuSTAR observations combined with archival Suzaku and Chandra data of NGC4945, the brightest extragalactic source at 100 keV. We observe hard X-ray (> 10 keV) flux and spectral variability, with flux variations of a factor 2 on timescales of 20 ksec. A variable primary continuum dominates the high energy spectrum (> 10 keV) in all the states, while the reflected/scattered flux which dominates at E< 10 keV stays approximately constant. From modelling the complex reflection/transmission spectrum we derive a Compton depth along the line of sight of Thomson approx.2.9, and a global covering factor for the circumnuclear gas of approx. 0.15. This agrees with the constraints derived from the high energy variability, which implies that most of the high energy flux is transmitted, rather that Compton-scattered. This demonstrates the effectiveness of spectral analysis in constraining the geometric properties of the circumnuclear gas, and validates similar methods used for analyzing the spectra of other bright, Compton-thick AGN. The lower limits on the e-folding energy are between 200 − 300 keV, consistent with previous BeppoSAX, Suzaku and Swift BAT observations. The accretion rate, estimated from the X-ray luminosity and assuming a bolometric correction typical of type 2 AGN, is in the range approx. 0.1 − 0.3 lambda(sub Edd) depending on the flux state. The substantial observed X-ray luminosity variability of NGC4945 implies that large errors can arise from using single-epoch X-ray data to derive L/L(sub Edd) values for obscured AGNs.

galaxies: active aEuro" galaxies: individual (NGC4↗

NASA NTRS1992

Optimizing tuning masses for helicopter rotor blade vibration reduction including computed airloads and comparison with test data

The development and validation of an optimization procedure to systematically place tuning masses along a rotor blade span to minimize vibratory loads are described. The masses and their corresponding locations are the design variables that are manipulated to reduce the harmonics of hub shear for a four-bladed rotor system without adding a large mass penalty. The procedure incorporates a comprehensive helicopter analysis to calculate the airloads. Predicting changes in airloads due to changes in design variables is an important feature of this research. The procedure was applied to a one-sixth, Mach-scaled rotor blade model to place three masses and then again to place six masses. In both cases the added mass was able to achieve significant reductions in the hub shear. In addition, the procedure was applied to place a single mass of fixed value on a blade model to reduce the hub shear for three flight conditions. The analytical results were compared to experimental data from a wind tunnel test performed in the Langley Transonic Dynamics Tunnel. The correlation of the mass location was good and the trend of the mass location with respect to flight speed was predicted fairly well. However, it was noted that the analysis was not entirely successful at predicting the absolute magnitudes of the fixed system loads.

Pritchard, Jocelyn I.↗

DOE OSTI2026

Uncertainty quantification for competing failure mechanisms in unidirectionally reinforced carbon–carbon composites

Microstructure-informed finite element models play a key role in the carbon–carbon composite design process. Variability in manufacturing process parameters and experimental limitations introduce model parameter uncertainty. This study quantifies the effect of model parameter uncertainty on transverse tensile fracture behavior and proposes a methodology to predict the failure mode based on competing microscale damage mechanisms. Finite element simulations incorporate fiber–matrix interface debonding with cohesive zones and matrix damage with a smeared crack band approach in a unidirectional carbon–carbon composite. Results from a variance-based global sensitivity analysis identifies interfacial and matrix damage parameters as the primary source of variability in fracture behavior. Sobol’ indices indicate that matrix and cohesive zone strengths contribute 94% of the variance in the effective ultimate stress. A local analysis elucidates the relationship between these constituent strength parameters and failure mode by estimating the probability of cohesive, matrix, and mixed-mode dominated failure. Based on the results for 4000 simulations, 93% exhibit mixed-mode or interfacial dominated failure, which underscores the crucial role of fiber–matrix interface debonding in the transverse tensile failure of carbon–carbon composites. These uncertainty quantification results facilitate more efficient model calibration and provide a framework for microstructure-informed failure predictions in the face of manufacturing-induced uncertainty.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Analysis of the microphysical properties of snowfall using scanning polarimetric and vertically pointing multi-frequency Doppler radars

Radar dual-wavelength ratio (DWR) measurements from the Stony Brook Radar Observatory Ka-band scanning polarimetric radar (KASPR, 35 GHz), a W-band profiling radar (94 GHz), and a next-generation K-band (24 GHz) micro rain radar (MRRPro) were exploited for ice particle identification using triple-frequency approaches. The results indicated that two of the radar frequencies (K and Ka band) are not sufficiently separated; thus, the triple-frequency radar approaches had limited success. On the other hand, a joint analysis of DWR, mean Doppler velocity (MDV), and polarimetric radar variables indicated potential in identifying ice particle types and distinguishing among different ice growth processes and even in revealing additional microphysical details. We investigated all DWR pairs in conjunction with MDV from the KASPR profiling measurements and differential reflectivity (Z DR ) and specific differential phase (K DP ) from the KASPR quasi-vertical profiles. The DWR-versus-MDV diagrams coupled with the polarimetric observables exhibited distinct separations of particle populations attributed to different rime degrees and particle growth processes. In fallstreaks, the 35–94 GHz DWR pair increased with the magnitude of MDV corresponding to the scattering calculations for aggregates with lower degrees of riming. The DWR values further increased at lower altitudes while Z DR slightly decreased, indicating further aggregation. Particle populations with higher rime degrees had a similar increase in DWR but a 1–1.5 m s –1 larger magnitude of MDV and rapid decreases in K DP and Z DR . The analysis also depicted the early stage of riming where Z DR increased with the MDV magnitude collocated with small increases in DWR. This approach will improve quantitative estimations of snow amount and microphysical quantities such as rime mass fraction. The study suggests that triple-frequency measurements are not always necessary for in-depth ice microphysical studies and that dual-frequency polarimetric and Doppler measurements can successfully be used to gain insights into ice hydrometeor microphysics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Subgrid-scale horizontal and vertical variation of cloud water in stratocumulus clouds: a case study based on LES and comparisons with in situ observations

Abstract. Stratocumulus clouds in the marine boundary layer cover a large fraction of ocean surface and play an important role in the radiative energy balance of the Earth system. Simulating these clouds in Earth system models (ESMs) has proven to be extremely challenging, in part because cloud microphysical processes such as the autoconversion of cloud water into precipitation occur at scales much smaller than typical ESM grid sizes. An accurate autoconversion parameterization needs to account for not only the local microphysical process (e.g., the dependence on cloud water content qc and cloud droplet number concentration Nc) but also the subgrid-scale variability of the cloud properties that determine the process rate. Accounting for subgrid-scale variability is often achieved by the introduction of a so-called enhancement factor E. Previous studies of E for autoconversion have focused more on its dependence on cloud regime and ESM grid size, but they have largely overlooked the vertical dependence of E within the cloud. In this study, we use a large-eddy simulation (LES) model, initialized and constrained with in situ and surface-based measurements from a recent airborne field campaign, to characterize the vertical dependence of the horizontal variation of qc in stratocumulus clouds and the implications for E. Similar to our recent observational study (Zhang et al., 2021), we found that the inverse relative variance of qc, an index of horizontal homogeneity, generally increases from cloud base upward through the lower two-thirds of the cloud and then decreases in the uppermost one-third of the cloud. As a result, E decreases from cloud base upward and then increases towards the cloud top. We apply a decomposition analysis to the LES cloud water field to understand the relative roles of the mean and variances of qc in determining the vertical dependence of E. Our analysis reveals that the vertical dependence of the horizontal qc variability and enhancement factor E is a combined result of condensational growth throughout the lower portion of the cloud and entrainment mixing at cloud top. The findings of this study indicate that a vertically dependent E should be used in ESM autoconversion parameterizations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2018

High-Fidelity Multidisciplinary Design Optimization Methodology with Application to Rotor Blades

A multidisciplinary design optimization procedure has been developed and applied to rotorcraft simulations involving tightly-coupled, high-fidelity computational fluid dynamics and comprehensive analysis. A discretely-consistent, adjoint-based sensitivity analysis available in the fluid dynamics solver provides sensitivities arising from unsteady turbulent flows on unstructured, dynamic, overset meshes, while a complex-variable approach is used to compute structural sensitivities with respect to aerodynamic loads. The multidisciplinary sensitivity analysis is conducted through integrating the sensitivity components from each discipline of the coupled system. Accuracy of the coupled system for high-fidelity rotorcraft analysis is verified; simulation results exhibit good agreement with established solutions. A constrained gradient-based design optimization for a HART-II rotorcraft configuration is demonstrated. The computational cost for individual components of the multidisciplinary sensitivity analysis is assessed and improved.

Wang, Li↗

DOE OSTI2022

Evaluation of a quasi-steady-state approximation of the cloud droplet growth equation (QDGE) scheme for aerosol activation in global models using multiple aircraft data over both continental and marine environments

This research introduces a numerically efficient aerosol activation scheme and evaluates it by using stratus and stratocumulus cloud data sampled during multiple aircraft campaigns in Canada, Chile, Brazil, and China. The scheme employs a quasi-steady-state approximation of the cloud droplet growth equation (QDGE) to efficiently simulate aerosol activation, the vertical profile of supersaturation, and the activated cloud droplet number concentration (CDNC) near the cloud base. The calculated maximum supersaturation values using the QDGE scheme were compared with multiple parcel model simulations under various aerosol and environmental conditions. The differences are all below 0.18 %, indicating good performance and accuracy of the QDGE scheme. We evaluated the QDGE scheme by specifying observed environmental thermodynamic variables and aerosol information from 31 cloud cases as input and comparing the simulated CDNC with cloud observations. The average of mean relative error ($\overline{MRE}$) of the simulated CDNC for cloud cases in each campaign ranges from 17.30 % in Brazil to 25.90 % in China, indicating that the QDGE scheme successfully reproduces observed variations in CDNC over a wide range of different meteorological conditions and aerosol regimes. Additionally, we carried out an error analysis by calculating the maximum information coefficient (MIC) between the MRE and input variables for the individual campaigns and all cloud cases. MIC values were then sorted by aerosol properties, pollution level, environmental humidity, and dynamic condition according to their relative importance to MRE. Based on the error analysis, we found that the magnitude of MRE is more relevant to the specification of input aerosol pollution level in marine regions and aerosol hygroscopicity in continental regions than to other variables in the simulation.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Statistical Analysis of Risk Factors in the Prebreathe Reduction Protocol

The 165 exposures from four 2-hour protocols were analyzed for correlations or trends between decompression sickness (DCS) or venous gas emboli (VGE), and variables that affect risk in the subject and astronaut populations. The assumption in this global survey is that the distributions of gender, age, body mass index, etc., are equally represented in all four tested procedures. We used Student t-test for comparisons between means and chi-square test between comparisons of proportions with p<0.05 defining a significant level. The type and distribution of the 19 cases of DCS were similar to historical cases. There was no correlation of age, gender, body mass index or fitness level with greater incidence of DCS or VGE. However increased age was associated with more Grade IV VGE in males. The duration and quantity of exercise during prebreathe is inversely related to risk of DCS and VGE. The latency time for VGE was longer (103 min +/- 56 SD, n = 15) when the ergometry was done approximately 15 min into the prebreathe than when done at the start of the prebreathe (53 min +/- 31, n = 13). The order of the ergometry did not influence the overall DCS and VGE incidence. We identified variables other than those of the prebreathe procedures that influence the DCS and VGE outcome. The analysis suggests that males over 40 years have a high incidence of Grade IV VGE.

Gerth, Wayne A.↗

DOE OSTI2023

Collaborative Research: Understanding air‐sea feedbacks to the MJO through process evaluation of observations and E3SM experiments (Final Technical Report)

This project explored the role of tropical oceans in regulating cloud populations within the Madden-Julian oscillation (MJO)–a large-scale tropical weather disturbance that influences extreme weather events across the globe by affecting the position of the jet stream and patterns of moisture transport. Our project sought to 1) document ocean feedback strength to the MJO in climate models, 2) understand how air-sea interactions affect the intensity, organization, and propagation of MJO convection, 3) utilize existing observations to identify sources of model bias for tropical air-sea interactions, and 4) better understand the effects of slow and fast ocean variability on MJO cloudiness. We found that transfers of heat and moisture across the air-sea interface (i.e., surface fluxes) in most climate models are over-supportive in maintaining MJO convection and under-supportive in propagating MJO convection. This can lead to misrepresentations in the frequency of extreme weather events across the globe through erroneous MJO feedbacks to jet stream position and moisture transport. Furthermore, using observations collected by ocean moorings across the tropical oceans, we showed that most models greatly overestimate surface evaporation in the subtropics, and that this bias is likely one contributor to a pervasive bias among climate models in their ability to simulate the mean state of rainfall over the tropical oceans (i.e., the “double ITCZ bias”). Replacing the default surface flux algorithm in two climate models with a state-of-the-art surface flux algorithm modestly reduced the double ITCZ bias in those models. Our work produced two model diagnostics packages that are now publicly available through DOE and NOAA model diagnostics archives. The first, the Analysis of Scales of Precipitation (ASoP) diagnoses scales of precipitation variability across space and time, with temporal resolution as fine as the model integration timestep. The second, the air-sea flux diagnostic diagnoses model surface fluxes and allows direct comparison of model fluxes to observations without having to recompute fluxes using model output and a state-of-the-art flux algorithm. These diagnostics, which were developed using climate models, can be readily applied to regional and global forecast model output to improve forecasts for the benefit of society.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

Analysis of precracking parameters for ceramic single-edge-precracked-beam specimens

The single-edge-precracked-beam (SEPB) method involves creation of a straight-through crack from an indentation crack. The straight-through crack is developed by applying a controlled bending load to a specimen via a precracking fixture. The fixture induces the following sequence: (1) stable growth of the indentation crack; (2) pop-in; and finally, (3) arrest - thereby forming a straight-through precrack. The effects of indentation load on precracking load as well as precrack size were studied for experimental variables such as specimen width, fixture span, and material. Finite element analysis was used to obtain the stress distribution and stress intensity factor, thus providing a quantitative prediction of the precracking load and precrack size for silicon nitride, alumina, silicon carbide, and two SiC whisker-reinforced silicon nitrides. Fracture toughness values obtained from the SEPB method were compared with those obtained from other methods.

Choi, Sung R.↗

NASA NTRSDate not supplied

High Latitude Atmospheric Rivers: Teleconnections and Impacts

Atmospheric rivers (ARs) are long, narrow synoptic scale features that act as moisture transport vehicles by moving water vapor poleward. They are typically found in storm tracks and often have profound implications for regional hydroclimate. For high latitude locales such as Antarctica and the Arctic, ARs are fewer in number but often have an outsized impact by either producing significant snow accumulation events, or, depending on their thermal characteristics, initiating melt events on ice sheets, ice shelves, and sea ice. In this study, we apply both reanalysis and climate model data to evaluate high latitude ARs for both the Arctic and Antarctic in the context of teleconnections and modes of variability. Specifically, we fold in both MERRA-2 and ERA5 reanalysis as well as historical and climate change simulations from the CESM2 (Community Earth System Model, Version 2) and E3SMv2 (Energy Exascale Earth System Model, v2) with multiple ensemble members to better understand natural variability versus climate change signals. An overview of AR climatology and impacts will be presented, including a baseline uncertainty quantification analysis using data from ARTMIP (the Atmospheric River Tracking Method Intercomparison Project). AR impacts during specific modes of variability will be characterized by diagnosing precipitation and boundary layer temperature associated with Ars influencing the cryosphere. Modes of variability investigated include the SAM (Southern Annular Mode), PDO (Pacific Decadal Oscillation), PSA2 (Pacific South American Mode 2), the IOD (Indian Ocean Dipole), and the AO (Arctic Oscillation).

Atmospheric Rivers↗

NASA NTRS2018

Vortex Shedding Characteristics of the Wake of a Thin Flat Plate with a Circular Trailing Edge

The near and very near wake of a thin flat plate with a circular trailing edge are investigated with direct numerical simulations (DNS). Data obtained for two different Reynolds numbers (based on plate thickness, D) are the main focus of this study. The separating boundary layers are turbulent in both cases. An earlier investigation of one of the cases (Case F) showed shed vortices in the wake that were about 1.0 D to 4.0 D in spanwise length. Considerable variation in both the strength and frequency of these shed vortices was observed. One objective of the present investigation is to determine the important contributors to this variability in strength and frequency of shed vortices and their finite spanwise extent. Analysis of the data shows that streamwise vortices in the separating boundary layer play an important role in strengthening/weakening of the shed vortices and that high/low-speed streaks in the boundary layer are important contributors to variability in shedding frequency. Both these features of the boundary layer contribute to the finite extent of the vortices in the spanwise direction. The second plate DNS (Case G, with 40 percent of the plate thickness of Case F) shows that while shedding intensity is weaker than obtained in Case F, many of the wake features are similar to that of Case F. This is important in understanding the path to the wake of the thin plate with a sharp trailing edge where shedding is absent. Here we also test the efficacy of a functional relationship between the shedding frequency and the Reynolds numbers based on the boundary layer momentum thickness (Re (sub theta) and D (Re (sub D)); data for developing this behavioral model is from Cases F & G and five earlier DNSs of the flat plate wake.

Turbulent wakes↗

DOE OSTI2023

A Monte-Carlo Method for Evaluating the Economic Performance of Plastics Recycling Systems Using Historical Pricing

The management of plastic waste is a considerable emerging global concern. Conventional plastics recycling rates range from 5–10% in the US, which results in considerable material being sent to landfill. New sorting technologies using artificial intelligence have the potential to dramatically increase the ability of waste management companies to sort out valuable fractions of plastic waste and create high-purity streams for secondary markets. However, several fractions of the plastics recycling stream, i.e., low-density polyethylene, polypropylene, and polystyrene, do not have well-developed markets. These materials may be sent to pyrolysis facilities for thermal recycling, but the economics of the pyrolysis industry are currently uncertain. This work aims to identify the breakeven price of the plastic fractions that would be sent to pyrolysis in order to determine the economic viability of the sorting facility. The work will use Monte Carlo analysis to evaluate several scenarios and understand how compositional variation, price variability, and facility attributes affect the breakeven price. Here, the presorting conditions in Materials Recovery Facilities strongly affects the profitability of the sorting facility. High residual high density polyethylene (HDPE) and polyethylene terephthalate (PET) content in presorted bales are important revenue drivers for the facility, even in presorted 3-7 bales. Key variables that lead to profitability include a high sale price of polyethylene terephthalate, a high sale price of high-density polyethylene, and if polypropylene can be sold to recycling markets (as opposed to pyrolysis facilities).

Plastics↗

NASA NTRS2018

A Benchmark Example for Delamination Propagation Predictions Based on the Single Leg Bending Specimen Under Quasi-Static and Fatigue Loading

Benchmark examples based on Single Leg Bending (SLB) specimens with equal and unequal bending arm thicknesses were used to assess the performance of delamination prediction capabilities in finite element codes. First, the development of the quasi-static benchmark cases using the Virtual Crack Closure Technique (VCCT) is discussed in detail. Second, based on the quasi-static benchmark results, additional benchmark cases to assess delamination propagation under fatigue loading are created. Third, the application is demonstrated for the commercial finite element code Abaqus Standard 2018. The benchmark cases are compared to results obtained from VCCT-based, automated quasi-static propagation analysis. A comparison with results from automated fatigue propagation analysis was not performed at this point since the current version of Abaqus does not include this capability under variable mixed-mode conditions. In general, good agreement between the results obtained from the quasi-static propagation analysis and the benchmark results were achieved. Overall, the benchmarking procedure proved valuable for analysis verification.

Krueger, Ronald↗

NASA NTRSDate not supplied

A Benchmark Example for Delamination Propagation Predictions Based on the Single Leg Bending Specimen under Quasi-static and Fatigue Loading

Ronald Krueger↗