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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Understanding the Durability of SiC Based Ceramic Matrix Composites (CMCs) for Gas Turbine Engine Hot Section Components

Silicon carbide fiber reinforced silicon carbide ceramic matrix composites (SiCf/SiC-CMCs) are being used in the fabrication of gas turbine engine hot section components due to their light weight and excellent thermal and chemical stabilities at high-temperature. These superior properties enable significant enhancements in engine efficiency and reduced fuel burn, emissions, and cooling requirements. In support of NASA’s Aeronautics Mission under various programs at Glenn Research Center, different types of composites have been developed and assessed for a high temperature (2700 °F) SiCf/SiC CMC system for turbine engine applications. These composites have creep-resistant SiC fibers, advanced 3D weaves, 2700 °F-capable hybrid SiC matrices, and durable environmental barrier coatings (EBCs). These efforts have resulted in improvements in the overall CMC thermomechanical and environmental durability. In order to study the role of different constituents and processing variables, a single fiber tow CVI (chemical vapor infiltration) SiC/SiC mini-composite can be considered the basic architectural feature of woven and laminate SiC/SiC CMCs. Moreover, the mini-composite mechanical and tensile creep damage behavior represents the creep behavior of 0° fiber tows in the axial loading direction of a macro-composite or component. In addition, a large number of mini-composite samples can be fabricated at relatively low cost within a short time, which makes them attractive for obtaining a robust set of experimental data and studying constituent behavior. In this presentation, the mini-composite approach to study damage mechanisms that limit CMC life in extreme environments including exposure to steam will be presented. The effects of constituent type and volume fraction on the CMC durability, which will help influence CMC design, will be discussed.

Ceramic Matrix Composites (CMCs)↗
NASA NTRS2020

How Satellite Soil Moisture Data Can Help to Monitor the Impacts of Climate Change: SMAP Case Studies

Socially and economically costly extreme weather events have become more prevalent in the last decade. Monitoring and early warning systems could help mitigate the impact of such events by allowing people to better prepare themselves to manage their responses to these events. One significant element of an effective warning system is soil moisture because it is a key determinant of the exchange of water and heat energy between the land and atmosphere, the partitioning of precipitation between infiltration and runoff, and therefore has an influence on weather patterns and streamflow. In addition, soil moisture governs plant water availability - the key to crop yield forecasting. For these reasons, a wide range of organizations use soil moisture information to better predict and monitor climate and weather phenomena such as floods and droughts. By improving soil moisture estimates, it may be possible to improve the monitoring and early warning systems upon which these organizations rely, and hence better mitigate the impacts of extreme weather events. Through case studies, this article discusses several uses of soil moisture data products from NASA's Soil Moisture Active Passive (SMAP) mission to help improve soil moisture-related monitoring and early warning systems.

agriculture↗
NASA NTRS2020

Evidence for Multiple Diagenetic Episodes in Ancient Fluvial‐Lacustrine Sedimentary Rocks in Gale Crater, Mars

The Curiosity rover's exploration of rocks and soils in Gale crater has provided diverse geochemical and mineralogical data sets, underscoring the complex geological history of the region. We report the crystalline, clay mineral, and amorphous phase distributions of four Gale crater rocks from an 80‐m stratigraphic interval. The mineralogy of the four samples is strongly influenced by aqueous alteration processes, including variations in water chemistries, redox, pH, and temperature. Localized hydrothermal events are evidenced by gray hematite and maturation of amorphous SiO 2 to opal‐CT. Low‐temperature diagenetic events are associated with fluctuating lake levels, evaporative events, and ground water infiltration. Among all mudstones analyzed in Gale crater, the diversity in diagenetic processes is primarily captured by the mineralogy and X‐ray amorphous chemistry of the drilled rocks. Variations indicate a transition from magnetite to hematite and an increase in matrix‐associated sulfates suggesting intensifying influence from oxic, diagenetic fluids up section. Furthermore, diagenetic fluid pathways are shown to be strongly affected by unconformities and sedimentary transitions, as evidenced by the intensity of alteration inferred from the mineralogy of sediments sampled adjacent to stratigraphic contacts.

C N Achilles↗
NASA NTRSDate not supplied

Multi-Scale Analysis of Effective Mechanical Properties of 3D Woven Composite Materials

This work aims to compute and analyze the mechanical properties of 3D woven composite materials that share the same yarn structure but differ in their matrix porosity and fiber volume fraction. Assuming linear elastic behavior, the software PuMA, developed at NASA, was used to characterize the different composites from their constituents' data averaging their elastic properties in three main directions to obtain their effective orthotropic mechanical properties. This was performed in three steps: firstly, the different phases (yarns/matrix) were analyzed as anisotropic materials separately at the micro-scale; then, the results from these analyses were homogenized and used to obtain the anisotropic elasticity tensor at the meso-scale for the different woven materials; and finally, assuming orthotropic mechanical behavior for the unit cell the mechanical properties were obtained at the macro-scale. The 3D woven composite materials selected for this study are made of phenolic resin with porosity values between 0 and 0.6, and resin infiltrated carbon fiber with volume fractions between 0.5 and 0.9 for the yarns. Results from PuMA were validated with external FEA simulations for the non-porous 3D woven material with a fiber volume fraction of 0.9 in the yarns. Results will be included in the final paper after completing the study detailed in Section II.

Sergio Fraile Izquierdo↗
NASA NTRSDate not supplied

Evaluation of Materials and Surfaces for Lunar Regolith Adherence Characterization (RAC) Payload Samples

As the quest for long term lunar exploration and habitation comes closer to reality, widespread efforts are ongoing to effectively mitigate lunar dust surface contamination and infiltration. This dust is hazardous to humans and tends to adhere tenaciously to all exposed surfaces, causing performance issues and ultimately failure. While several active and passive technologies have been developed to address this challenge, assessing the performance of these technologies in the actual lunar environment is extremely important. The regolith adherence characterization (RAC) experiment payload provides an important opportunity for this evaluation. The RAC payload is designed by Alpha Space for the National Aeronautics and Space Administration (NASA)and scheduled to be flown to the moon in 2023 on the Firefly Aerospace Blue Ghost lander. As there were a limited number of slots available for materials to be chosen for this mission, it was critical to make an informed selection. Two polymers, a carbon fiber reinforced composite and a metal alloy were chosen to be a diverse selection of structural materials from NASA Langley Research Center. Each material was topographically modified using laser ablation patterning. This article briefly describes the selection and testing procedure and some of the results obtained for the passive dust mitigating materials and surfaces selected for this lunar surface experiment.

Lunar Dust↗
NASA NTRSDate not supplied

Multi-Scale Analysis of Effective Mechanical Properties of Porous 3D Woven Composite Materials

This work aims to compute and analyze the mechanical properties of 3D woven composite materials that share the same yarn structure but differ in their matrix porosity and yarn's fiber volume fraction. Assuming linear elastic behavior, NASA's PuMA software was used to characterize the different composites from their constituents' data, averaging their elastic properties in three main directions to obtain their effective orthotropic mechanical properties. This was performed in three steps: firstly, the porous matrix phase was analyzed at the micro-scale; then, these results were used, along with the mechanical properties of the fibers, to model the yarns at the meso-scale; finally, results from the constituents were homogenized and used to model the mechanical behavior of the unit cell at the macro-scale. The 3D woven composite materials selected for this study are made of a mixture of phenolic resin with porosity values between 0 and 0.6, and infiltrated carbon fiber yarns with fiber volume fractions between 0.5 and 0.8. Results from this study show the effect of different matrix porosities and fiber volume fractions on the macro-scale mechanical properties, and were validated through theoretical and semi-empirical expressions found in the literature.

3D woven materials↗
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 NTRS2022

Thermochemical Degradation of HfSiO4 by Molten CMAS

The thermochemical degradation of hafnium silicate (HfSiO4) was investigated with a molten calcium-magnesium-aluminosilicate (CMAS) glass relevant to gas turbine engine applications. Sintered HfSiO4 coupons were fabricated, within which wells were drilled and filled with CMAS glass powder at a loading of ~35 mg/cm2. Samples were heat treated at1200°C, 1300°C, 1400°C, and 1500°C for 1 hour, 10 hours, and 50 hours. At 1200°C and1300°C, slow formation of a Ca2HfSi4O12 cyclosilicate phase was observed at the HfSiO4-CMASinterface. At 1300°C and higher, rapid infiltration of CMAS into the material along the grain boundaries was observed. Initial conjecture into CMAS degradation mechanisms of HfSiO4 are presented herein.

CMAS↗
NASA NTRS2022

Thermal Hydraulic Disaggregation of SMAP Soil Moisture Over the Continental United States

Thermal Hydraulic disaggregation of Soil Moisture (THySM) algorithm was implemented to downscale NASA’s Soil Moisture Active Passive (SMAP) Enhanced soil moisture (SM) product to 1 km over the continental United States (CONUS). This algorithm was developed by combining thermal inertia theory with a soil hydraulic-based approach that considers fine-scale SM spatial distribution driven by both heat fluxes and hydraulic conductivity in soils. Relative soil wetness values were estimated using land surface temperature and normalized difference vegetation index for the thermal inertia model and using soil properties for the hydraulic model. The relative soil wetness values at 1 km from both models were then combined by using weighting functions whereby the spatial distribution of SM was governed more by thermal fluxes during times of strong heat transport and infiltration during moisture abundant soil conditions. THySM values were evaluated using in situ SM measurements from SMAP Core Validation Sites (CVS), the USDA Soil Climate Analysis Network, and the NOAA Climate Reference Network over CONUS. THySM shows higher accuracy than the SMAP / Sentinel-1 (SPL2SMAP_S) 1 km SM product when compared to in situ measurements. The accuracy of THySM is 0.048 m3/m3 based on unbiased root mean square error (ubRMSE), outperforming SPL2SMAP_S by 0.01-0.02 m3/m3. The ubRMSE of THySM 1km SM over the SMAP grassland/rangeland-dominated CVS sites is better than 0.04 m3/m3, which meets the SMAP mission SM accuracy requirement applied at 9 and 36 km.

SMAP↗
NASA NTRS2022

Building and Breaking Carbon Composites with REACTER

Carbon-based composites have become indispensable materials in aerospace and other high-performance applications, yet obtaining a detailed, nanoscale understanding of their morphology and failure mechanisms using only experimental methods remains a difficult challenge. REACTER is a versatile computational modeling tool for atomistic molecular dynamics simulations designed to model chemical reactions at the speed and length scales of classical force fields. In this work, several recent features of REACTER were applied to the creation and subsequent mechanical testing of two classes of carbon composites: carbon nanotube (CNT) composites and carbon fiber reinforced polymers (CFRP). A network of CNTs was grown dynamically using the new ‘create atoms’ feature of REACTER. The CNT filler was embedded into a polyarylacetylene (PAA) matrix by simulated in situ polymerization to obtain the final composite model. To generate the second class of carbon composite, fully carbonized (graphitic) carbon fiber morphologies were created by the method of Desai et al. [1], but using the advanced reaction constraints framework of REACTER. Two fiber models were created, representing a circular carbon fiber core and a flat surface, and similarly infiltrated with resin to obtain the final CFRP structure. Failure mechanisms were elucidated by simulating mechanically induced bond breaking, as characterized by third order DFT-based tight-binding simulations, via a reaction constraint on the total potential energy of the involved atoms.

Polymer↗
NASA NTRS2022

Leveraging Pre-storm Soil Moisture Estimates for Enhanced Land Surface Model Calibration in Ungauged Hydrologic Basins

Despite long-standing efforts, hydrologists still lack robust tools for calibrating land surface model (LSM) streamflow estimates within ungauged basins. Using surface soil moisture estimates from the Soil Moisture Active Passive Level 4 Soil Moisture (L4_SM) product, precipitation observations, and streamflow gauge measurements for 617 medium-scale (200-10,000 km2) basins in the contiguous United States, we measure the temporal (Spearman) rank correlation between antecedent (i.e., pre-storm) surface soil moisture (ASM) and the storm-scale runoff coefficient (RC; the fraction of storm-scale precipitation accumulation converted into streamflow). In humid and semi-humid basins, this rank correlation is shown to be sufficiently strong to allow for the substitution of storm-scale RC observations (available only in basins that are both lightly regulated and gauged) with high-quality ASM values (available quasi-globally from L4_SM) in streamflow calibration procedures. Using this principle, we define a new, basin-wise LSM streamflow calibration approach based on L4_SM alone and successfully apply it to identify LSM configurations that produce a high rank correlation with observed RC. However, since the approach cannot detect RC bias, it is less successful in identifying LSM configurations with low mean-absolute error. Plain Text Summary Accurately forecasting the fraction of rainfall that runs off into streams, as opposed to infiltrates into the soil, is critical for flash-flood prediction, water-resource monitoring, and tracking the transport of nutrients from agricultural fields into local waterways. Such forecasting is typically performed by hydrologic models that attempt to represent the physical processes responsible for surface runoff generation. However, to provide accurate streamflow forecasts, these models typically need to be calibrated against actual streamflow observations. This is problematic given the relatively poor, and declining, global availability of stream gauges. This paper presents a novel model calibration strategy that uses soil moisture from remote sensing and numerical modeling in place of streamflow observations during calibration. This transition has significant practical advantages because, unlike streamflow observations, the soil moisture data are continuously available across space. Our results demonstrate that this new approach can significantly improve hydrologic models within humid and semi-humid basins lacking sufficient ground-based instrumentation for traditional streamflow calibration.

hydrologic models↗
NASA NTRS2022

Analyzing Recharge Dynamics and Storage in a Thick, Karstic Vadose Zone

Karst vadose zone heterogeneity creates complex transmission and storage dynamics that affect the timing and magnitude of aquifer recharge. Young, high-matrix permeability eogenetic karst aquifers may have significantly higher matrix storage than older, lower matrix permeability counterparts. In vulnerable and water-limited karst regions, the timescales of storage may be important for seasonal and sub-seasonal water resource management. We create a framework to quantify storage dynamics in karst aquifers using high-resolution precipitation and groundwater levels from the Northern Guam Lens Aquifer in the US territory of Guam. We estimate recharge using the Water Table Fluctuation method, and then develop transfer functions between precipitation and recharge to quantify storage and release of water from the vadose zone. The transfer functions are partitioned into different flow pathways including conduit, conduit/matrix, and slowly draining matrix. Probability distributions are fit to each pathway to determine the average travel times of infiltrated waters. The results show that aquifer recharge through secondary porosity features typically occurs within a few hours of a rainfall event, but this rapid recharge accounts for only 12%–28% of total recharge. The majority of aquifer recharge (>70%) occurs within a month of a contributing storm event. An additional 10% of recharge, on average, took longer than a month to reach the water table. The framework established can help improve the hydrological modeling and freshwater management for karst aquifers.

Patricia Spellman↗
NASA NTRSDate not supplied

Building and Breaking Carbon Composites with REACTER

Carbon composites have become indispensable for aerospace and other high-performance applications, and a detailed picture of their morphology and failure mechanisms remains difficult to obtain through experiment. REACTER is a versatile computational modeling tool for atomistic molecular dynamics designed to model chemical reactions at the speed and length scales of classical force fields.1 In this work, several recent features of REACTER were applied to the creation and subsequent mechanical testing of two classes of carbon composites, carbon-fiber reinforced polymers (CFRP) and carbon nanotube (CNT) composites. Carbon fiber core morphologies were created by the method of Desai et al.,2 but using the advanced reaction constraints framework of REACTER, their proposed multistep procedure was reduced to a single uninterrupted molecular dynamics simulation. The carbon fiber filler was embedded into a polymer matrix by simulated in situ polymerization of several thermosetting resins, including bismaleimide and polyarylacetylene, to obtain the final CFRP model. To generate the second class of carbon composite, CNT networks were grown dynamically using the new ‘create atoms’ feature of REACTER, and similarly infiltrated with resin to obtain CNT composites. The resulting models were compared directly to experiment using simulated high resolution transmission electron microscopy and x-ray diffraction. Failure mechanisms were elucidated by simulating mechanically induced bond breaking, as characterized by third-order DFT-based tight-binding (DFTB3) simulations, via a reaction constraint on the total potential energy of the involved atoms.

Molecular Dynamics↗
NASA NTRSDate not supplied

Neurovascular Responses to Simulated Deep Space Radiation in a Human Organ-on-a-Chip Model

A major health risk for human deep space exploration is central nervous system (CNS) damage by galactic cosmic ray radiation. Simulated galactic cosmic rays or their components, especially the high-linear energy transfer (LET) particles such as 56Fe ions, have been shown to cause CNS damage, neuroinflammation and cognitive dysfunction in rodent models, but their effects on human CNS remain to be investigated. CNS damage from any insult, including ionizing radiation, is partially mediated by the blood-brain barrier (BBB), which regulates interactions between CNS and the rest of the body. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuroinflammation. However, there have been few studies on BBB and astrocyte functions in regulating CNS responses, especially in human tissue analogs. Therefore, we utilized a high-throughput 3D organ-on-a-chip system, seeded with human induced pluripotent stem cell-derived astrocytes and brain endothelial cells, or brain endothelial cells alone, to study human neurovascular responses to simulated deep space radiation. We investigated the permeability and morphology of vascular structures formed by endothelial cells, as well as oxidative stress and secreted cytokines and chemokine levels over 1-7 days after irradiation with 0.25 – 0.5 Gy 5-ion simplified simulated galactic cosmic rays or 0.3 – 0.8 Gy high-LET 600 MeV/n 56Fe particles, and compared the outcomes to low-LET X-ray irradiation. We observed that simulated deep space radiation caused delayed astrocyte activation in a pattern resembling CNS responses to brain injury, caused oxidative stress and the production of inflammatory cytokines, and compromised BBB integrity by damaging tight junctions, thus increasing vascular permeability. Furthermore, our results indicate that astrocytes have a dual role in regulating radiation responses: they exacerbate blood-brain barrier permeability early after irradiation, followed by switching to a more protective scar-like phenotype by reducing oxidative stress and pro-inflammatory cytokine and chemokine secretion. In a follow-up study using the same platform, we investigated the dose-rate effects of ionizing radiation, by exposing our model to chronic, low dose-rate, gamma radiation. Our model was significantly improved by adding additional cell types composing the BBB, modelling immune cell infiltration into the brain, and studying the effect of an antioxidant, to measure more complex outcomes and model more closely the effect of deep space radiation on the human BBB. In summary, our results present a human neurovascular model for space radiation studies and potential future automated payload adaptation, and suggest astrocyte regulatory mechanisms as targets for countermeasures to mitigate human neurovascular impairments during deep space exploration.

Ionizing radiation↗
NASA NTRS2022

Simulations of Firn Processes Over the Greenland and Antarctic Ice Sheets: 1980-2021

Conversion of altimetry-derived ice-sheet volume change to mass requires an understanding of the evolution of the combined ice and air content within the firn column. In the absence of suitable techniques to observe the changes to the firn column across the entirety of an ice sheet, the firn column processes are typically modeled. Here, we present new simulations of firn processes over the Greenland and Antarctic ice sheets (GrIS and AIS) using the Community Firn Model and atmospheric reanalysis variables for more than four decades. A data set of more than 250 measured depth–density profiles from both ice sheets provides the basis of the calibration of the dry-snow densification scheme. The resulting scheme results in a reduction in the rate of densification, relative to a commonly used semi-empirical model, through a decreased dependence on the accumulation rate, a proxy for overburden stress. The 1980–2020 modeled firn column runoff, when combined with atmospheric variables from MERRA-2, generates realistic mean integrated surface mass balance values for the Greenland (+390 Gt yr(exp −1)) and Antarctic (+2612 Gt yr(exp −1)) ice sheets when compared to published model-ensemble means. We find that seasonal volume changes associated with firn air content are on average approximately 2.5 times larger than those associated with mass fluxes from surface processes for the AIS and 1.5 times larger for the GrIS; however, when averaged over multiple years, ice and air-volume fluctuations within the firn column are of comparable magnitudes. Between 1996 and 2019, the Greenland Ice Sheet lost nearly 5% of its firn air content, indicating a reduction in the total meltwater retention capability. Nearly all (94 %) of the meltwater produced over the Antarctic Ice Sheet is retained within the firn column through infiltration and refreezing.

Greenland↗
NASA NTRS2023

Lunar Dust Mitigation: A Guide and Reference: First Edition (2021)

On the surface of the Moon, lunar dust specifically presents unique challenges to operations long-term due to regolith particles’ ubiquitous presence in the lunar environment, potential to electrostatically charge and possible chemical reactivity. Whether to avoid exposure, try to remove or simply to tolerate lunar dust infiltrating a system becomes a complex question involving length of required service life, dust effects and critical risks, mass and complexity trades for the entire system. This publication provides a snapshot of advice from topical experts for specific areas of concern to systems targeted for deployment on the lunar surface. Following introductory overview commentary, dust mitigation approaches appropriate to the lunar surface are first addressed for typically static structures such as optical surfaces, radiators, and other thermal control surfaces, followed by regolith exposure concerns for communications equipment and non-optical sensors. The broad topic of mechanisms and mechanical assemblies is broken down to address relevant component level concerns, such as for bearings and for seals. “Soft goods” components of space suits (fabric) specific concerns are discussed, followed finally by brief coverage of human health issues and concerns, though the emphasis of this publication remains with components directly exposed to the harsh lunar surface environment. A description of some lunar surface hazard details, in particular characteristics of lunar surface dust, follows in Appendix A, and more detailed explanations of quantification issues for particulates are in Appendix B. The simple inertial removal of particles from a surface is discussed in Appendix C, followed by a summary of terrestrial best practices for dust mitigation recommended within select industries in Appendix D. The aggregated bibliography of references, while extensive and very useful, should not be construed to be exhaustive and can serve as a constructive start.

dust↗
NASA NTRSDate not supplied

Medium-Range River Flood Forecasts Using a Long Short-Term Memory Network

River flooding and the impacts are a concern for decision makers throughout the United States. Accurate medium-range forecasts (~3-7 days) are critical for providing advanced outlooks to emergency management officials. Unfortunately, accurately forecasting rainfall-runoff and the subsequent rise and fall within rivers remain a challenge in hydrological modeling. While complex physical modeling systems are the standard for representing the hydrological processes, they are computationally demanding and can require extensive calibration. Further, uncertainties remain in the model parameters and input data. The use of machine learning can reduce some of the computational demand while maintaining high accuracy. Therefore, this project makes use of a Long Short-Term Memory (LSTM) network which explicitly accounts for the time-dependent nature of rainfall-runoff modeling. The developed LSTM was trained to predict river gauge height, or stage height, based on time-lagged input features which include: gauge height to initialize the model, the NASA Short-term Prediction Research and Transition Center’s instance of the Land Information System (SPoRT-LIS) relative soil moisture to describe the rainfall infiltration rate, and 6-hr Multi-Radar Multi-Sensor quantitative precipitation estimate (MRMS QPE). The developed LSTM based system is then used to produce 7-day forecasts with a 6-hr temporal resolution using three different quantitative precipitation forecasts (QPF) from the NWS’s Weather Prediction Center (WPC), the NCEP Global Forecast System (GFS) model and the National Blend of Models (NBM). This trained modeling system has been implemented as an experimental product at over 100 different rivers in collaboration with at multiple National Weather Service (NWS) Forecast Offices and River Forecast Centers (RFC) across the eastern half of the United States. The developed LSTM model achieved average Nash-Sutcliffe efficiency (NSE) 0.89 higher than the equivalent medium-range National Water Model ensemble member forecast over a 7-day forecast. In addition to the initial development and evaluation, this project has continued to expand. While the initial model was developed for precipitation dominated basins, expansion of the project has taken it to basins effected by snow melt. This presentation will provide an overview of the project with focus on recent developments on incorporating snow melt processes into the model.

Andrew T. White↗
NASA NTRSDate not supplied

Thermochemical/Thermomechanical Synergies in High Temperature Solid Particle Erosion of CMAS-Exposed EBCs

Environmental barrier coatings (EBCs) are an enabling technology for the use of SiC-based ceramic matrix composites in next generation gas turbine engines. In the extreme engine environment, EBCs must be able to withstand a variety of individual damage mechanisms and their interactions with each other. Ingested particulates/debris can cause both thermochemical and thermomechanical degradation of EBCs. Siliceous debris primarily based on calcium magnesium aluminosilicates (CMAS) can melt and infiltrate and/or react with EBCs above >1200°C. Similarly, ingested debris can lead to mechanical damage and recession of coatings due to particulate erosion. Both modes of degradation can occur simultaneously during engine operation, and it is crucial to comprehensively understand the mechanisms of coating failure due to high-temperature particulate interactions. This study assesses the erosion durability of Yb2Si2O7-based EBCs exposed to CMAS of various loads in NASA Glenn’s Erosion Burner Rig Facility. CMAS exposures and erosion testing were carried out at 1316°C. The effects of CMAS loading and exposure time on EBC erosion durability were evaluated using Al2O3 as an erodent material.

EBC↗