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DOE OSTI2022

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series

Abstract. Improving the quantification of soil thermal and physical properties is key to achieving a better understanding and prediction of soil hydro-biogeochemical processes and their responses to changes in atmospheric forcing. Obtaining such information at numerous locations and/or over time with conventional soil sampling is challenging. The increasing availability of low-cost, vertically resolved temperature sensor arrays offers promise for improving the estimation of soil thermal properties from temperature time series, and the possible indirect estimation of physical properties. Still, the reliability and limitations of such an approach need to be assessed. In the present study, we develop a parameter estimation approach based on a combination of thermal modeling, sliding time windows, Bayesian inference, and Markov chain Monte Carlo simulation to estimate thermal diffusivity and its uncertainty over time, at numerous locations and at an unprecedented vertical spatial resolution (i.e., down to 5 to 10 cm vertical resolution) from soil temperature time series. We provide the necessary framework to assess under which environmental conditions (soil temperature gradient, fluctuations, and trend), temperature sensor characteristics (bias and level of noise), and deployment geometries (sensor number and position) soil thermal diffusivity can be reliably inferred. We validate the method with synthetic experiments and field studies. The synthetic experiments show that in the presence of median diurnal fluctuations ≥ 1.5 ∘C at 5 cm below the ground surface, temperature gradients > 2 ∘C m−1, and a sliding time window of at least 4 d the proposed method provides reliable depth-resolved thermal diffusivity estimates with percentage errors ≤ 10 % and posterior relative standard deviations ≤ 5 % up to 1 m depth. Reliable thermal diffusivity under such environmental conditions also requires temperature sensors to be spaced precisely (with accuracy to a few millimeters), with a level of noise ≤ 0.02 ∘C, and with a bias defined by a standard deviation ≤ 0.01 ∘C. Finally, the application of the developed approach to field data indicates significant repeatability in results and similarity with independent measurements, as well as promise in using a sliding time window to estimate temporal changes in soil thermal diffusivity, as needed to potentially capture changes in bulk density or water content.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

A Regional-Scale Assessment of Satellite Derived Precipitable Water Vapor Across The Amazon Basin

Atmospheric water vapor is widely recognized as a key climate variable, linking an assortment of poorly understood and complex processes. It is a major element of the hydrological cycle and provides a mechanism for energy exchange among many of the Earth system components. Reducing uncertainty in our current knowledge of water vapor and its role in the climate system requires accurate measurement, improved modeling techniques, and long-term prediction. Satellites have the potential to satisfy these criteria, as well as provide high resolution measurements that are not available from conventional sources. The focus of this paper is to examine the temporal and mesoscale variations of satellite derived precipitable water vapor (PW) across the Amazon Basin. This region is pivotal in the functioning of the global climate system through its abundant release of latent heat associated with heavy precipitation events. In addition, anthropogenic deforestation and biomass burning activities in recent decades are altering the conditions of the atmosphere, especially in the planetary boundary layer. A physical split-window (PSW) algorithm estimates PW using images from the GOES satellites along with the NCEP/NCAR Reanalysis data that provides the first guess information. Retrievals are made at a three-hourly time step during daylight hours in the Amazon Basin and surrounding areas for the months of June and October in 1988 (dry year) and 1995 (wet year). Spatially continuous fields are generated 5 times daily at 12Z, 15Z, 18Z, 21Z, and 00Z. These fields are then averaged to create monthly and 3 hourly monthly grids. Overall, the PSW estimates PW reasonable well in the Amazon with MAE ranging from 3.0 - 9.0 mm and MAE/observed mean around 20% in comparison to radiosonde observations. The distribution of PW generally mimics that of precipitation. Maximum values (42 - 52 mm) are located in the Northwest whereas minimum values (18 - 27 mm) are found along Brazil's East coast. Aside from the East coast, PW has a stronger north-south gradient than that of rainfall. As for the temporal variation of PW, June (1988 and 1995) experiences a peak about 1400 local time, corresponding to a maximum in air temperature. In contrast, October (1988 and 1995) experiences a maximum early in the day, 1100 local time, with a gradual decrease toward nighttime.

DeLiberty, Tracy↗

DOE OSTI2025

Thermodynamic assessment of the quaternary WTaCrV refractory high entropy alloy as a means to guide experimental approaches

The deployment of fusion energy poses challenges for materials in plasma facing components to withstand high temperatures and thermal gradients, particle implantation and neutron damage. The current material of choice is tungsten, although property degradation limits its consideration in future fusion reactors. Hence, materials with better resistance to harsh environments need to be developed for fusion energy to become a reality. High entropy alloys are being explored as potential candidates with some compositions showing good radiation resistance to defect cluster formation. One of these materials is the WTaCrV system, although only one composition has been tested under ion irradiation. In this work, we study the thermodynamic properties of the entire quaternary alloy composition range. Coupling first principles calculations, cluster expansion approaches, and Monte Carlo methods, we access the free energy functionals, short-range ordering as a function of temperature, and atomic configurations that can be compared to experimental observations. We use this data to inform experiments into compositions with higher propensity to form solid solutions, instead of phase separating. With this formalism we have developed thermodynamic database (TDB) files that can be used to plot quaternary phase diagrams.

Cluster Expansion↗

DOE OSTI2024

Investigation of acoustic waves under subsurface conditions to improve the predictions of rock mechanical properties and natural fracture characteristics

Mechanical properties and natural fracture characteristics are critical to investigate for subsurface engineering applications, including carbon storage, well drilling, and stimulation, as they govern rock stability, fluid flow, and mechanical behavior under stress. This dissertation integrates experimental and machine learning approaches to enhance the prediction and understanding of these properties by analyzing acoustic wave behavior under varied subsurface conditions. First, the influence of temperature, pore pressure, and supercritical CO2 (scCO2) saturation on poroelastic properties is examined using Gray Berea sandstone samples. The results show that temperature and pore pressure significantly affect the bulk modulus and Biot’s coefficient, while scCO2 saturation impacts rock compressibility, informing strategies for effective geological carbon storage. The study extends this understanding by experimentally evaluating the impact of reservoir depletion on the dynamic mechanical properties of the emerging Caney shale in South Oklahoma with the employment of unsupervised machine learning to predict static mechanical properties across the Caney shale. Integrating petrophysical data and chemostratigraphy, the workflow—featuring K-means clustering, principal component analysis (PCA), and inverse distance weighting (IDW)—improves stratigraphic characterization and the estimation of static-to-dynamic modulus ratios, which is vital for optimizing drilling and stimulation strategies. Finally, the work explores how natural fracture characteristics in shale influence acoustic waveforms and shear wave splitting (SWS) analysis. Experimental data on fractured samples under different stress and temperature conditions, combined with machine learning models such as K-nearest neighbors (KNN) and extreme gradient boosting (XGBoost), reveal key fracture properties impacting SWS and wave propagation. Together, these studies provide a comprehensive framework for linking acoustic wave behavior with rock properties, advancing the methods for monitoring and predicting geomechanical changes. The insights offered valuable implications for safer, more efficient CO2 injection, hydrocarbon extraction, and subsurface management.

Elkholy, Sherif↗

DOE OSTI2026

Historic climate, cosmogenic 10Be, denudation-rate, and geospatial datasets from the Pikes Peak region, Colorado, USA

This data package contains geographic information system (GIS) layers and tabular datasets associated with the study of elevation-dependent denudation rates on Pikes Peak in the Front Range of the Rocky Mountains, Colorado, USA. The package includes GIS layers used to produce the study-area map, including sample locations, sample watershed boundaries, the Pikes Peak batholith, Pleistocene glacier extent, weather station locations, and elevation and hillshade rasters, together with comma-separated value (CSV) tables and matching CSV data dictionaries. These mapped layers provide the geographic framework for interpreting denudation patterns across the Pikes Peak region and for relating sample locations to watershed geometry, bedrock setting, glacial history, and nearby climate stations. The first group of tables reports climate and geospatial context for the study area. These files include station-based temperature and precipitation data used to characterize elevational gradients in mean annual climate and monthly climate seasonality, sample locations, denudation-rate and topographic metrics, fixed frost-cracking model parameters, frost-cracking intensity and precipitation-frequency metrics, and stream-power inversion results. Together, these data provide the basis for evaluating how denudation varies with elevation, climate, and landscape form across sampled catchments on Pikes Peak. The second group of tables reports cosmogenic nuclide and erosion-model results used in the denudation analysis. Included files contain accelerator mass spectrometry (AMS) measurements for in situ-produced cosmogenic beryllium-10 (10Be), including sample identifiers, measured 10Be:9Be ratios, analytical uncertainties, carrier mass, quartz mass, blank corrections, blank-group statistics, and calculated 10Be concentrations and uncertainties. Additional tables summarize stream-power-law inversion results for sampled catchments, including optimized model parameters, predicted erosion rates, residual metrics, channel-pixel counts, and convergence status, as well as regression equations and summary statistics used to evaluate relationships among elevation, climate, frost cracking, precipitation forcing, and denudation rate. The package contains GIS files, comma-separated value files (.csv), Microsoft Excel files (.xlsx), CSV data dictionaries, a file-level metadata table, and a readme text file.

10Be cosmogenic nuclides↗

NASA NTRS1999

Improved Stratospheric Temperature Retrievals for Climate Reanalysis

The Data Assimilation Office (DAO) is embarking on plans to generate a twenty year reanalysis data set of climatic atmospheric variables. One of the focus points will be in the evaluation of the dynamics of the stratosphere. The Stratospheric Sounding Unit (SSU), flown as part of the TIROS Operational Vertical Sounder (TOVS), is one of the primary stratospheric temperature sensors flown consistently throughout the reanalysis period. Seven unique sensors made the measurements over time, with individual instrument characteristics that need to be addressed. The stratospheric temperatures being assimilated across satellite platforms will profoundly impact the reanalysis dynamical fields. To attempt to quantify aspects of instrument and retrieval bias we are carefully collecting and analyzing all available information on the sensors, their instrument anomalies, forward model errors and retrieval biases. For the retrieval of stratospheric temperatures, we adapted the minimum variance approach of Jazwinski (1970) and Rodgers (1976) and applied it to the SSU soundings. In our algorithm, the state vector contains an initial guess of temperature from a model six hour forecast provided by the Goddard EOS Data Assimilation System (GEOS/DAS). This is combined with an a priori covariance matrix, a forward model parameterization, and specifications of instrument noise characteristics. A quasi-Newtonian iteration is used to obtain convergence of the retrieved state to the measurement vector. This algorithm also enables us to analyze and address the systematic errors associated with the unique characteristics of the cell pressures on the individual SSU instruments and the resolving power of the instruments to vertical gradients in the stratosphere. The preliminary results of the improved retrievals and their assimilation as well as baseline calculations of bias and rms error between the NESDIS operational product and col-located ground measurements will be presented.

Rokke, L.↗

DOE OSTI2023

Three-Dimensional Reconstruction of Nb 3 Sn Films by Focused Ion Beam Cross Sectional Microscopy

Niobium has been the material of choice for SRF cavities for several decades due to its formability and superconducting properties. The accelerating gradient of niobium cavities is, however, rapidly approaching a theoretical limit. To achieve higher accelerating gradients a new material is needed that can sustain high fields. Nb 3 Sn is a promising competitor with a higher superconducting transition temperature and a higher critical field than pure niobium. However, Nb 3 Sn is very brittle and cannot be formed readily into a cavity. The main method for creating Nb 3 Sn cavities is to form a Nb 3 Sn film into a niobium surface using a tin vapor-diffusion method. This technique creates a microcrystalline Nb 3 Sn thin film on the inner surface of the cavity. Tin depleted regions are known to form in the film during this process. Previous studies have analyzed these regions using transmission electron microscopy on cross-sectional lamellae prepared by focused ion beam/scanning electron microscope (FIB/SEM). This method does not provide any three-dimensional (3-D) information about the distribution of tin-deficient regions. In this study we employ a focused ion beam tomographic technique to analyze the 3-D structure of the film. Electron dispersive X-ray spectroscopy is used to image the tin concentration of the film in 3-D. Tin-deficient regions are discovered close to the surface of the Nb 3 Sn film.

Viklund, E.↗

NASA NTRS2001

Dynamics and Morphology of Superfluid Helium Drops in a Microgravity Environment

We developed an apparatus that makes it possible to observe and study magnetically levitated drops of superfluid helium. The force on a diamagnetic substance in a magnetic field is proportional to the gradient of the square of the magnetic field B. For the magnetic force on helium to be equal to the gravitational force on Earth, it is necessary for the product of B with the field gradient dB/d z to be 21.5 T(exp 2)/cm. In addition, in order for the magnetic field to provide a stable trap, the value of B(exp 2) must increase in all directions in the horizontal plane that passes through the point where the field/field gradient product in the vertical direction has the critical value of 21.5 T(exp 2)/cm. A specially designed superconducting magnet that meets these specifications has been installed in a large helium dewar with optical access. Helium drops levitated by the magnet can be viewed along the axis of the solenoid. The sample chamber within the bore of the magnet is thermally isolated from the magnet and helium reservoir. Its temperature can be varied between 4 and 0.5 K, the lower part of the range being reached using a He-3 refrigerator. Liquid helium can be injected into the magnetic trap using a small capillary. Once a drop is contained in the trap it can be held there indefinitely. With this apparatus we have conducted a number of different types of experiments on helium drops so as to gain information necessary for performing experiments in space. With magnetically levitated drops we are limited to working with drops of 1 cm. or less in diameter. The shape of the drops larger than a few mm diameter can be distorted by the profile of the magnetic field. The study of phenomena such as the initial motion of the surfaces of two drops as they just make contact, requires the use large drops to resolve the behavior of interest. We have performed a detailed investigation of the shape oscillations of superfluid drops.

Seidel, George M.↗

DOE OSTI2022

Scientific Computational Imaging Code (SCICO)

Scientific Computational Imaging Code (SCICO) is a Python package for solving the inverse problems that arise in scientific imaging applications. Its primary focus is providing methods for solving ill-posed inverse problems by using an appropriate prior model of the reconstruction space. SCICO includes a growing suite of operators, cost functionals, regularizers, and optimization routines that may be combined to solve a wide range of problems, and is designed so that it is easy to add new building blocks. SCICO is built on top of JAX rather than NumPy, enabling GPU/TPU acceleration, just-in-time compilation, and automatic gradient functionality, which is used to automatically compute the adjoints of linear operators. An example of how to solve a multi-channel tomography problem with SCICO is shown in Figure 1. The SCICO source code is available from GitHub, and pre-built packages are available from PyPI. It has extensive online documentation, including API documentation and usage examples, which can be run online at Google Colab and binder.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1997

Regional Application of an Ecosystem Production Model for Studies of Biogeochemistry in the...

The degree to which primary production, soil carbon, and trace gas fluxes in tropical forests of the Amazon are limited by moisture availability and other environmental factors was examined using an ecosystem modeling application for the country of Brazil. A regional geographic information system (GIS) serves as the data source of climate drivers, satellite images, land cover, and soil properties for input to the NASA Ames-CASA (Carnegie-Ames-Stanford Approach) model over a 8-km grid resolution. Simulation results supports the hypothesis that net primary production (NPP) is limited by cloud interception of solar radiation over the humid northwestern portion of the region. Peak annual rates for NPP of nearly 1.4 kg C m-2yr -1are localized in the seasonally dry eastern Amazon in areas that we assume are primarily deep-rooted evergreen forest cover. Regional effects of forest conversion on NPP and soil carbon content are indicated in the model results, especially in seasonally dry areas. Comparison of model flux predictions along selected eco-climatic transects reveal moisture, soil, and land use controls on gradients of ecosystem production and soil trace gas emissions (CO2, N2O, and NO). These results are used to formulate a series of research hypotheses for testing in the next phase of regional modeling, which includes recalibration of the light-use efficiency term in CASA using field measurements of NPP, and refinements of vegetation index and soil property (texture and potential rooting depth) maps for the region.

Potter, C. S.↗

DOE OSTI2024

Recent Advances in Assessing Environmental Effects of Marine Renewable Energy Around the World

Marine renewable energy (MRE) is increasingly of interest to coastal nations as a source of renewable energy that can support climate change mitigation goals as well as provide secure locally-produced energy for coastal and island communities. MRE extracts power from tidal streams, waves, ocean currents, run of rivers, and gradients in the ocean, with specialized devices developed and tested for each energy resource. Alongside development of MRE technologies and systems, first in Europe and then in North America, Australia, Asia, and other regions, it has been universally recognized that there is also a need to examine potential effects on marine animals, habitats, ecosystem processes, local communities and other sea users, to ensure that the MRE industry can be developed in a responsible and sustainable manner. This paper looks at the status of assessment and monitoring for potential environmental effects associated with MRE projects around the world. Over 80 projects were identified worldwide as having been tested, demonstrated, or commercially deployed with associated environmental monitoring. Five of the projects that represent tidal stream, wave, and run of river projects are examined in more detail to determine the types of data and information collected for those projects, the outputs of the monitoring campaigns, and the actions taken as a result of the data collection and analysis. Recommendations are provided for standardization of the monitoring approaches, instruments, and analysis methods at MRE project sites worldwide.

marine renewable energy, environmental effects, ri↗

DOE OSTI2024

An ML-based terrestrial data fusion and augmentation framework to enable advanced understanding of the terrestrial carbon and water interactions

Soil moisture is essential to the terrestrial carbon and water cycles and land–atmosphere interactions. There are various types of soil moisture data, and each type has the distinct spatiotemporal strengths and limitations, depending on the diverse applications and retrieval methodologies of different data types (Li et al., in review; The PNNL-82151 FY23 Report). However, the limitations of different soil moisture data in terms of accuracy and spatiotemporal coverage hinder our ability to further understand the soil moisture dynamics across scales. To have a gap free soil moisture data product with a fine spatiotemporal coverage and vertical profiles, we train extreme gradient boosting (XGBoost) models by using (1) in-situ soil moisture measurements from the International Soil Moisture Network (ISMN), (2) soil moisture from the ECMWF reanalysis (ERA) at the 9 km and sub-daily spatiotemporal resolution, (3) the Daymet meteorological fields, and (4) data products that characterize surface conditions, including soil texture, organic content, topography, vegetation type, and rooting depth. We use the trained XGBoost models that have consistent performance across seven soil layers, i.e., 0–5 cm, 5–10 cm, 10–20 cm, 20–40 cm, 40–60 cm, 60–100 cm, and 100–200 cm, and the gridded model predictors to generate a soil moisture data at the 1 km and daily spatiotemporal resolution for the Continental United States (CONUS) from 2001–2020. This dataset can be broadly used for Earth system model benchmark, monitoring extreme weathers, making informed decisions regarding agriculture, water resource management, climate change mitigation, and ecosystem preservation.

58 GEOSCIENCES↗

NASA NTRS1995

Classification of rain regimes by the three-dimensional properties of reflectivity fields

An automated scheme to characterize precipitation echoes within small windows in the radar field is presented and applied to previously subjectively classified tropical rain cloud systems near Darwin, Australia. The classification parameters are (a) E(sub e), effective efficiency, as determined by cloud-top and cloud-base water vapor saturation mixing ratios; (b) BBF, brightband fraction, as determined by the fraction of the radar echo area in which the maximal reflectivity occurs within +/- 1.5 km of the 0 C isotherm level; and (c) del(sub r) Z, radial reflectivity gradients (dB/km). These classification criteria were applied to tropical rain cloud systems near Darwin, Australia, and to winter convective rain cloud systems in Israel. Both sets of measurements were made with nearly identical networks of C-band radars and rain gauge networks. The results of the application of these objective classification criteria to several independently predetermined rain regimes in Darwin have shown that better organized rain systems have smaller del(sub r) Z and larger BBF. Similarly, smaller del(sub r)Z and larger BBF were also observed from maritime rain cloud systems, as compared to continental rain cloud systems with the same degree of organization. Continental rain cloud system, regardless of their degree of organization, have larger depths, as expressed by E(sub e). The rainfall analyses presented in this study are based exclusively on rain gauge measurements, while radar information was used only to classify the individual gauge measurements.

Rosenfeld, Daniel↗

DOE OSTI2025

A data-driven method to estimate the antiproton background in the Mu2e experiment

The Mu2e experiment at Fermilab will search for the Charged Lepton Flavour Violating (CLFV) process of coherent, neutrinoless µ− → e − conversion in the field of an aluminum nucleus. The expected signal is a monochromatic electron with the energy of 104.97 MeV, slightly below the muon rest mass. Observation of a CLFV process would provide unambiguous evidence for Beyond the Standard Model (BSM) physics. Mu2e is sensitive to a wide range of BSM models and has the capability to distinguish between them, guiding us towards the most accurate models. The key features of the Mu2e experiment are: (1) a high intensity pulsed negative muon beam with about 1010 stopped µ −/s, and (2) a sophisticated superconducting solenoid system with a gradient magnetic field to form and guide the intense muon beam to the target. The Mu2e physics data taking is expected to begin in 2027. For Run I, the expected 5σ discovery sensitivity is Rµe = 1.2 × 10−15, with a total expected background of 0.11 ± 0.03 events. In the absence of a signal, the expected upper limit is Rµe < 6.2 × 10−16 at 90% CL. The success of this experiment hinges on the accurate estimation of the background from various SM processes that could provide signal-like electrons. One of the background processes is antiprotons annihilating in the stopping target to produce signal like electrons through π0 → γγ decays followed by γ conversions, and π− → µ−ν¯ decays followed by µ− decay. It is a relatively small background with large uncertainty (100%) due to the lack of antiproton production cross section information for the Mu2e proton beam energy of 8 GeV. We have developed a novel methodology to estimate the antiproton background in-situ. This forms the main theme of the thesis. We observed that at Mu2e energies, antiproton annihilation in the stopping target is the only source of events with multiple, simultaneous particle trajectories. From Geant4 simulations, only about 0.2% of the simulated antiproton annihilation events have a signal-like electron. Meanwhile, ∼ 5% of events have multiple reconstructible particle tracks per event. Therefore, we have devised a methodology to reconstruct the multi-track events and estimate the antiproton background by exploiting the large ratio of the production rates of the two final states.

Chithirasreemadam, Namitha [Pisa U.] (ORCID:000000↗

DOE OSTI2026

Optimization techniques in self-similar compressible flow

We investigate the one-dimensional (1D) inviscid compressible flow equations for an ideal gas through the lens of optimization techniques. It is the case that, to our knowledge, optimization analysis applied to the so-called “linear velocity” solutions of the Euler compressible flow equations has not been previously conducted. Through both gradient-based and variational techniques, new variants of well-studied flow scenarios, i.e., self-similar, 1D, linear velocity solution class to idealized inviscid compressible flow equations, are determined, as encoded in both the kinematic and thermodynamic properties of this self-similar solution class. With the kinematics of the said solutions being driven by a self-similar “scale radius” and the thermodynamics being driven separately through the appearance of an arbitrary function, a myriad of new solution classes is possible. Acting as a guide to more realistic physical circumstances as well as discovery, it is the hope that the presented cases serve as the framework for future investigations into the intersection of self-similarity and optimization techniques. Fields of study that may find this work to be of interest include aerodynamic design, flow control, inertial confinement fusion, physics-informed neural networks, and other related areas of interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Microfibril orientation and compositional heterogeneity in fiber and vessel cell walls of poplar xylem studied by AFM-IR and SFG spectroscopy

Understanding the structural organization of cellulose microfibrils (CMFs) within individual plant cell walls is essential for connecting cell wall architecture to its mechanical and physiological functions. However, due to the complex hierarchical structure and nanoscale heterogeneity of cell walls, it remains technically challenging to resolve detailed compositional and orientational information at subcellular levels of individual cell walls. This study investigates the internal 3D structure, chemical composition, and sublayer organization of fiber and vessel cell walls in the xylem tissue of a two-year-old field-grown hybrid poplar tree (Populus alba × P. glandulosa) using photothermal atomic force microscopy coupled with infrared spectroscopy (AFM-IR) and sum frequency generation (SFG) hyperspectral microscopy. AFM-IR provided nanoscale chemical imaging, revealing localized compositional heterogeneity, including variations between adjacent cell walls and transitional layers beyond the traditional S1, S2, and S3 sublayers. SFG microscopy revealed that CMFs in fiber walls are highly aligned along the stem axis, consistent with their role in mechanical support, while vessel cell walls exhibited slightly tilted CMFs, reflecting their function in hydraulic transport. Together, these results offer new insights into cell-type-specific CMF organization and compositional gradients in hybrid poplar xylem. These findings highlight the structural and chemical complexity of secondary cell walls in woody plants and demonstrate the value of AFM-IR and SFG spectroscopy in elucidating plant cell wall architecture.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1991

Modeling of the heat transfer in bypass transitional boundary-layer flows

A low Reynolds number k-epsilon turbulence model and conditioned momentum, energy and turbulence equations were used to predict bypass transition heat transfer on a flat plate in a high-disturbance environment with zero pressure gradient. The use of conditioned equations was demonstrated to be an improvement over the use of the global-time-averaged equations for the calculation of velocity profiles and turbulence intensity profiles in the transition region of a boundary layer. The approach of conditioned equations is extended to include heat transfer and a modeling of transition events is used to predict transition onset and the extent of transition on a flat plate. The events, which describe the boundary layer at the leading edge, result in boundary-layer regions consisting of: (1) the laminar, (2) pseudolaminar, (3) transitional, and (4) turbulent boundary layers. The modeled transition events were incorporated into the TEXSTAN 2-D boundary-layer code which is used to numerically predict the heat transfer. The numerical predictions in general compared well with the experimental data and revealed areas where additional experimental information is needed.

Simon, Frederick F.↗

NASA NTRS2003

High-Temperature Sprayable Phosphor Coating Developed for Measuring Surface Temperatures

The use of phosphor thermography for noncontact temperature measurements in harsh environments has been proven over the last decade, but it has suffered from difficult application procedures such as vapor deposition or sputtering techniques. We have developed a high-temperature-sensitive paint that is easily applied with commercially available paint-spraying equipment and have successfully demonstrated it to temperatures up to 1500 C. Selected phosphors have also shown measurable signals to 1700 C, thus allowing a combination of phosphors to be used in high-temperature binders to make surface temperature measurements from ambient to over 1500 C. Phosphor thermography is an optical technique that measures the time response of fluorescence light, which is a function of the phosphor temperature. The phosphors are excited with short wavelength light (ultraviolet or blue), and they emit light at a longer wavelength. This technique has a benefit over other temperature measurements, such as thermocouples and infrared thermography, in difficult environments such as high blackbody backgrounds, vibration, flames, high electromagnetic noise, or where special windows may be needed. In addition, the sprayable phosphor paints easily cover large or complicated structures, providing full-surface information with a single measurement. Oak Ridge National Laboratories developed and tested the high-temperature binders and phosphors under the direction of the NASA Glenn Research Center. Refractory materials doped with rare earth metals were selected for their performance at high temperature. Survivability, adhesion, and material compatibility tests were conducted at high temperatures in a small furnace while the fluorescent response from the phosphors was being measured. A painted sample in a furnace with a clearly visible fluorescing dot excited by a pulsed laser is shown. Measuring the decay time of this fluorescence yields the surface temperature. One new paint was recently tested in a rocket test stand at Glenn. The floor of a square duct nozzle was painted, and full-field lifetime decay measurements were acquired for multiple firings of the rocket. Good agreement with predicted results was obtained, matching temperature gradients along the length of the nozzle and clearly showing shock structures. These good results were very satisfactory given that the measurements were made looking through the combustion plume. Infrared pyrometry was incapable of making the surface measurements because of the interference from the rocket exhaust, which contaminated the infrared signature.

Bencic, Timothy J.↗