Search NASA⌕ Search

SEARCH · Search NASA

Results for “soil strength”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

83 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The impact of multi-sensor land data assimilation on river discharge estimation

River discharge is one of the most critical renewable water resources. Accurately estimating river discharge with land surface models (LSMs) remains challenging due to the difficulty in estimating land water storages such as snow, soil moisture, and groundwater. While data assimilation (DA) ingesting optical, microwave, and gravity measurements from space can help constrain theses storage states, its impacts on runoff and eventually river discharge are not fully understood. In this study, by taking advantage of recently published land DA results that jointly assimilate eight different combinations of observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), Gravity Recovery and Climate Experiment (GRACE), and Advanced Microwave Scanning Radiometer for EOS (AMSR-E), we quantify to what degree multi-sensor land DA improves the river discharge simulation skills over 40 global river basins, and investigate the complementary strengths of different satellite measurements on river discharge. To be more specific, river discharge is updated by feeding gridded runoff from the eight multi-sensor DA simulations into a vector-based river routing model named the Routing Application for Parallel computatIon of Discharge (RAPID). Our modeling results, including 7-year simulations at 177,458 river reaches globally, are used to study the seasonal to interannual variability of river discharge. It is found that assimilating GRACE has the greatest impact on global runoff patterns, leading to the most pronounced improvements in spatial river discharge in the middle and high latitudes with the R 2 increased by 0.16. The seasonal variation of spatial discharge is most skillful during the boreal summer. However, our evaluation also shows model and DA still struggle to generate reasonable variability and averaged discharge over permafrost regions. Finally, by assessing how different satellites add value to discharge forecasts, this study paves the way for more advanced multi-sensor satellite data assimilation to predict the terrestrial hydrological cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Investigating the quaternary structure of a homomultimeric catechol 1,2-dioxygenase: An integrative structural biology study

The structural analysis of catechol 1,2 dioxygenase from Stutzerimonas frequens GOM2, SfC12DO, was conducted using various structural techniques. SEC-SAXS experiments revealed that SfC12DO, after lyophilization and reconstitution processes, can form multiple enzymatically active oligomers, including dimers, tetramers, and octamers. These findings differ from previous studies, which reported active dimers in homologous counterparts with available crystallographic structures, or trimers observed exclusively in solution for SfC12DO and its homologous isoA C12DO from Acinetobacter radioresistens under low ionic strength conditions. In some cases, tetramers were also reported, such as for the Rodococcus erythropolis C12DO. The combined results of Small-Angle X-ray Scattering, Dynamic Light Scattering, and Transmission Electron Microscopy experiments provided additional insights into these active oligomers’ shape and molecular organization in an aqueous solution. These results highlight the oligomeric structural plasticity of SfC12DO, proving that it can exist in different oligomeric forms depending on the physicochemical characteristics of the solutions in which the experiments were performed. Remarkably, regardless of its oligomeric state, SfC12DO maintains its enzymatic activity even after prior lyophilization. All these characteristics make SfC12DO a putative candidate for bioremediation applications in polluted soils or waters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Numerical study of the chemo-mechanical behavior of FEBEX bentonite in nuclear waste disposal based on the Barcelona expansive model

Experimental studies show that compacted bentonite used as a backfill material for nuclear waste repository experiences strong coupling between chemical and mechanical processes. Here, we use a dual-structure expansive soil model, referred to as the Barcelona Expansive Model (BExM), to predict the behavior of bentonite buffer in subsurface emplacement tunnels for high-level radioactive waste. After emplacement, the bentonite is subjected to complex and coupled Thermal-Hydraulic-Mechanical-Chemical (THMC) processes. The BExM constitutive model is implemented in a multi-phase reactive transport and geomechanics simulator, TOUGHREACT-FLAC3D, and the model is verified with one benchmark test on FEBEX bentonite. We utilize a one-way Chemo-Mechanical (C-M) coupling approach, in which chemical changes affect the mechanical behavior of bentonite through the BExM linked with the evolution of mass fraction of smectite, exchangeable cation concentration, and ionic strength via osmotic suction. The parameters of the new coupled model for FEBEX bentonite are calibrated against a series of laboratory experiments with various salinity solutions. Finally, coupled THMC modeling is conducted for a generic argillite repository with bentonite buffer under high temperature, focusing on the long-term chemical change and its effect on the mechanical process.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Modeling Interfaces to Support Low-Level Waste Disposal System Performance Assessments - 20366

In low-level waste (LLW) disposal sites, interfaces between cementitious materials, used as waste forms and/or engineered barriers, and the surrounding soil or backfill material are often encountered. Reactions across these interfaces may lead to chemical and structural alteration of the cementitious and backfill materials that may ultimately affect long-term performance. For example, the ingress of carbon dioxide from soil gas into a waste tank concrete shell at the Hanford Site or Savannah River Site (SRS) or a low-level waste disposal vault at SRS leads to carbonation of cement hydration products (e.g. portlandite, calcium-silicate hydrate or C-S-H, and ettringite). The result of carbonation is a decrease in pH in the cement paste portion of the tank wall or vault concrete structure that could ultimately lead to de-passivation of the embedded structural steel and, eventually, to cracking. Cracking can lead to increased ingress of water into the structure, corresponding increased release of constituents of concern, and to subsequent increased transport of these constituents to the surrounding environment. The mobility of trace constituents (e.g., radionuclides of concern) in waste forms may increase in response to changes in pH, pore structure, and mineralogical gradients. Depletion of portlandite results in subsequent decalcification of C-S-H that leads to changes in the cement strength and may lead to structural failure. At the boundary between waste forms and concrete vaults, the migration of sulfate ions from the salt waste form (e.g., the saltstone waste form used for LLW disposal at the Savannah River Site in Saltstone Disposal Units, or SDUs) into the barrier or vault concrete has been predicted to result in expansive mineral phase formation (or 'sulfate attack'). Expansive mineral formation could result in cracking and potential loss of structural integrity in the vault concrete. In the performance assessment (PA) for the SRS SDUs, prediction of both the carbonation and sulfate attack fronts are critical to assessing the long-term performance of these LLW disposal vaults. A general purpose geochemical reactive transport model has been developed in LeachXS/ORCHESTRA to evaluate typical interfaces for LLW disposal environments, including SDUs at SRS. The model may be used to predict the long-term performance of interfaces between cementitious materials and saltstone or backfill materials with respect to primary phases by considering mass transport, cement chemistry, geochemical speciation, and multi-ionic diffusion over interfaces between different materials. The present study compares the performance and interactions between vault concrete and saltstone waste form for a representative SDU scenario. The materials were characterized using pH-dependence leaching test (EPA 1313) and semi-dynamic transport tests (EPA 1315) with test results used to parameterize the interface model. The development of a credible inter model provides an important basis for supporting future PAs where carbonation and sulfate attack are important aging and degradation mechanisms. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Fully Distributed Multi-Material Magnetic Sensing Structures for Multiparameter DAS Applications

This dissertation demonstrates the first of its kind distributed magnetic field sensor based on a fiber optic distributed acoustic sensing (DAS) scheme. Ferromagnetic nickel and Metglas® were dispersed internally within a fiber optic preform and then drawn on an in-house fiber optic draw tower to lengths in the kilometers. Due to the close proximity of the ferromagnetic metals and fiber optic core, the magnetostrictive strain response of the ferromagnetic materials when exposed to a magnetic field would perturbate within the fiber cladding and transfer that strain, internally, to the fiber optic core. Strain resulting from the magnetostrictive effect allows the DAS based sensor to accurately translate strain into readable magnetic field data. Due to the high sensitivity seen in this sensor design, multiparameter sources, acoustic and magnetic fields, were tested and validated and a three dimensional magnetic-field vector sensor was proposed. Numerical analysis of the novel sensor design was first implemented using COMSOL Multiphysics, where inputs such as magnetostrictive element shape, size, distance, and number were first investigated. Upon optimizing system constraints, the sensor design was further modified such that single mode operation was consistent across multiple fiber draws while retaining high strain transfer from the ferromagnetic elements to the fiber optic core. Ferromagnetic material selection was evaluated as a function of the saturation magnetostriction constants and a total of 4 modules were used to fully characterize the complex physics involved in this sensor design. All fabrication and testing were performed in-house using a full scale 3-story fiber draw tower and custom environmental testing stations to imitate naturally occurring events such as magnetic or acoustic point sources. A unique stacking method was used to embed ferromagnetic nickel and Metglas® into a fiber optic preform which when combined with a custom fiber draw process resulted in consistent multi-material fibers drawn to lengths of 1-km. In-house testing facilities included different types of electromagnetic generators, in addition to a soil test bed, and an outdoor test bed which allowed 100 meters of fiber to be tested simultaneously. All tested sensors demonstrated high strain transfer capabilities on the order of 0.01-10 μϵ depending on the materials used, ferromagnetic rod number, and core to metal spacing. Due to the sensitivity of the system the difference between AC and DC was distinct, and directional magnetostriction was studied. Transverse and longitudinal magnetic wave propagation was controlled through a solenoid and rectangular Helmholtz coil, both built in-house. A three-dimensional magnetic field vector sensor was proposed due to the success of the magnetic field sensor, and a design was proposed and initially tested to validate direction as a function of field strength and distance. To summarize, this dissertation explores the first fully distributed magnetic field sensor using DAS based techniques and one of the first multi-material fiber draw processes which can produce consistent single mode fiber up to 1-km. Due to extensive FEA modeling, multiple iterations of the magnetic sensor were fully characterized and an equation describing the relationship between sensor design and strain transfer has been created and validated experimentally. Multi-parameter tests including acoustic and magnetic fields were implemented and an algorithm was developed to separate the mixed signals. Finally, a test was performed to demonstrate the feasibility of sensing magnetic fields directionally. Cumulative results demonstrate a high-quality sensor alternative to current designs which may surpass other magnetic sensors due to innate multi-parameter capabilities, in addition to the inexpensive production cost and extremely long operating lengths.

02 PETROLEUM↗
DOE OSTI2024

Monitoring the impact of confinement on hyphal penetration and fungal behavior

Through their expansive mycelium network, soil fungi alter the physical arrangement and chemical composition of their local environment. This can significantly impact bacterial distribution and nutrient transport and can play a dramatic role in shaping the rhizosphere around a developing plant. However, direct observation and quantitation of such behaviors is extremely difficult due to the opacity and complex porosity of the soil microenvironment. In this study, we demonstrate the development and use of an engineered microhabitat to visualize fungal growth in response to varied levels of confinement. Microfluidics were fabricated using photolithography and conventional soft lithography, assembled onto glass slides, and prepared to accommodate fungal cultures. Selected fungal strains across three phyla (Ascomycota: Morchella sextalata , Fusarium falciforme ; Mucoromycota: Linnemannia elongata , Podila minutissima , Benniella ; Basidiomycota: Laccaria bicolor , and Serendipita sp.) were cultured within microhabitats and imaged using time-lapse microscopy to visualize development at the mycelial level. Fungal hyphae of each strain were imaged as they penetrated through microchannels with well-defined pore dimensions. The hyphal penetration rates through the microchannels were quantified via image analysis. Other behaviors, including differences in the degree of branching, peer movement, and tip strength were also recorded for each strain. Our results provide a repeatable and easy-to-use approach for culturing fungi within a microfluidics platform and for visualizing the impact of confinement on hyphal growth and other fungal behaviors pertinent to their remodeling of the underground environment.

Guo, Yi-Syuan (ORCID:0000000340142225)↗
DOE OSTI2021

Eight Metagenome-Assembled Genomes Provide Evidence for Microbial Adaptation in 20,000- to 1,000,000-Year-Old Siberian Permafrost

Permafrost microbes may be metabolically active in microscopic layers of liquid brines, even in ancient soil. Metagenomics can help discern whether permafrost microbes show adaptations to this environment. Thirty-three metagenome-assembled genomes (MAGs) were obtained from six depths (3.5 m to 20 m) of freshly cored permafrost from the Siberian Kolyma-Indigirka Lowland region. These soils have been continuously frozen for ~20,000 to 1,000,000 years. Eight of these MAGs were ≥80% complete with <10% contamination and were taxonomically identified as Aminicenantes, Atribacteria, Chloroflexi, and Actinobacteria within bacteria and Thermoprofundales within archaea. MAGs from these taxa have been obtained previously from nonpermafrost environments and have been suggested to show adaptations to long-term energy starvation, but they have never been explored in ancient permafrost. The permafrost MAGs had greater proportions in the Clusters of Orthologous Groups (COGs) categories of energy production and conversion and carbohydrate transport and metabolism than did their nonpermafrost counterparts. They also contained genes for trehalose synthesis, thymine metabolism, mevalonate biosynthesis, and cellulose degradation, which were less prevalent in nonpermafrost genomes. Furthermore, many of these genes are involved in membrane stabilization and osmotic stress responses, consistent with adaptation to the anoxic, high-ionic-strength, cold environments of permafrost brine films. Our results suggest that this ancient permafrost contains DNA of high enough quality to assemble MAGs from microorganisms with adaptations to survive long-term freezing in this extreme environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon

The Weather Research and Forecasting (WRF) model can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations but subjected to uncertainties associated with model physical parameterizations. In this study, we propose a framework to quantify and reduce model physical parameterization uncertainties associated with surface fluxes and L-A coupling. An ensemble of WRF simulations with different physical schemes is used to simulate surface fluxes and land-atmosphere coupling strength over the Amazon region. The physical parameterizations investigated include cloud microphysics (MP), land surface processes (LSM), planetary boundary layer (PBL), surface layer (SL), and cumulus (CU). We perform 120 ensemble simulations using the WRF model and different combinations of six MPs, three LSMs, six PBLs and SLs and three CUs. The measurements from the GoAMAZON field campaign and satellite data are used to evaluate model performance. A Multi-way analysis of variance (ANOVA) approach is applied to quantify the relative importance of different physics processes on L-A coupling. The Tukey’s test is used to sort schemes that have no significant differences into one group. The suite of physics that result in the best simulations of the corresponding variables are selected based on the Taylor skill score. Results show that the relative importance of processes and their interaction vary with the variables of interest. For example, CU was the most important process in modulating soil moisture, 2 m-humidity, latent heat, and net radiation. LSM showed dominant effects on 2 m-temperature and also has the largest impact on sensible heat and the lifting condensation level. The best physical parameterization ensembles show much narrower ranges of the variables of interest than the priori ensemble. Results of this study show the roles of different physical processes in modulating L-A interactions, quantify model uncertainties from physical processes, and provide insights for improving the model physics parameterizations.

Wang, Chen↗
DOE OSTI2022

Airborne hyperspectral imaging of cover crops through radiative transfer process-guided machine learning

Cover cropping between cash crop growing seasons is a multifunctional conservation practice. Timely and accurate monitoring of cover crop traits, notably aboveground biomass and nutrient content, is beneficial to agricultural stakeholders to improve management and understand outcomes. Currently, there is a scarcity of spatially and temporally resolved information for assessing cover crop growth. Remote sensing has a high potential to fill this need, but conventional empirical regression operated with coarse-resolution multispectral data has large uncertainties. Therefore, this study utilized airborne hyperspectral imaging techniques and developed new process-guided machine learning approaches (PGML) for cover crop monitoring. Specifically, we deployed an airborne hyperspectral system covering visible to shortwave-infrared wavelengths (400–2400 nm) to acquire high spatial (0.5 m) and spectral (3–5 nm) resolution reflectance over 23 cover crop fields across Central Illinois in March and April of 2021. Airborne hyperspectral surface reflectance with high spectral and spatial resolution can be well matched with field data to quantify cover crop traits. Furthermore, the PGML models were pre-trained by synthetic data from soil-vegetation radiative transfer modeling (one million records), and then fine-tuned with field data of cover crop biomass and nutrient content. Results show that airborne hyperspectral data with PGML can achieve high accuracy to predict cover crop aboveground biomass (R 2 = 0.72, relative RMSE = 15.16%) and nitrogen content (R 2 = 0.69, relative RMSE = 16.59%) through leave-one-field-out cross-validation. Unlike the pure data-driven approach (e.g., partial least-squares regression), PGML incorporated radiative transfer knowledge and obtained higher predictive performance with fewer field data. Meanwhile, with field data for model fine-tuning, PGML predicted biomass more accurately than the inversion of radiative transfer models. Here we also found that the red edge has a high contribution in quantifying aboveground biomass and nitrogen content, followed by green and shortwave spectra. This study demonstrated the first attempt of utilizing hyperspectral remote sensing to accurately quantify cover crop traits. We highlight the strength of PGML in exploiting sensing data to quantify ecosystem variables to advance agroecosystem monitoring for sustainable agricultural management.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics

Mounting evidence indicates dryland ecosystems play an important role in driving the interannual variability and trend of the terrestrial carbon sink. Nevertheless, our understanding of the seasonal dynamics of dryland ecosystem carbon uptake through photosynthesis [gross primary productivity (GPP)] remains relatively limited due in part to the limited availability of long-term data and unique challenges associated with satellite remote sensing across dryland ecosystems. Here, we comprehensively evaluated longstanding and emerging satellite vegetation proxies in their ability to capture seasonal dryland GPP dynamics. Specifically, we evaluated: 1) reflectance-based proxies normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), near infrared reflectance index (NIR v ), and kernel NDVI (kNDVI) from the MODerate resolution Imaging Spectroradiometer (MODIS); and 2) newly available physiologically-based proxy solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI). As a performance benchmark, we used GPP estimates from a robust network of 21 western United States eddy covariance tower sites that span representative gradients in dryland ecosystem climate and functional composition. We found that NIR v and SIF were the best performing GPP proxies and captured complementary aspects of seasonal GPP dynamics across dryland ecosystem types. NIR v offered better performance than the other proxies across relatively low-productivity, sparsely non-evergreen vegetated sites (R 2 = 0.59 ± 0.13); whereas SIF best captured seasonal dynamics across relatively high-productivity sites, including evergreen-dominated sites (R 2 = 0.74 ± 0.07). Notably, across grass-dominated sites, all reflectance-based proxies (NDVI, SAVI, NIRv and kNDVI) showed significant seasonal bias (hysteresis) that strengthened with the total fraction of woody vegetation cover, likely due to seasonal patterns in woody vegetation reflectance that are unrelated to or decoupled from GPP. In conclusion, future efforts to fully integrate the complementary strengths of NIR v and SIF could significantly improve our understanding and representation of dryland GPP dynamics in satellite-based models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Local adaptation of both plant and pathogen: an arms‐race compromise in switchgrass rust

In coevolving species, parasites locally adapt to host populations as hosts locally adapt to resist parasites. Parasites often outpace host local adaptation since they have rapid life cycles, but host diversity, the strength of selection, and external environmental influence can result in complex outcomes. To better understand local adaptation in host–parasite systems, we examined locally adapted switchgrass (Panicum virgatum), and its leaf rust pathogen (Puccinia novopanici) across a latitudinal range in North America. We grew switchgrass genotypes in 10 replicated multiyear common gardens, measuring rust severity from natural infection in a ‘host reciprocal transplant’ framework for testing local adaptation. We conducted genome-wide association mapping to identify genetic loci associated with rust severity. Genetically differentiated rust populations were locally adapted to northern and southern switchgrass, despite host local adaptation to environmental conditions in the same regions. Rust resistance was polygenic, and distinct loci were associated with rust severity in the north and south. We narrowed a previously identified large-effect quantitative trait locus for rust severity to a candidate YELLOW STRIPE-LIKE gene and linked numerous other loci to defense-related genes. Overall, our results suggest that both hosts and parasites can be simultaneously locally adapted, especially when parasites impose less selection than other environmental factors.

59 BASIC BIOLOGICAL SCIENCES↗