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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.

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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cuprate superconductors as viewed through a striped lens

Understanding the electron pairing in hole-doped cuprate superconductors has been a challenge, in particular because the “normal” state from which it evolves is unprecedented. Now, after three and a half decades of research, involving a wide range of experimental characterizations, it is possible to delineate a clear and consistent cuprate story. It starts with doping holes into a charge-transfer insulator, resulting in in-gap states. Furthermore, these states exhibit a pseudogap resulting from the competition between antiferromagnetic superexchange J between nearest-neighbor Cu atoms (a real-space interaction) and the kinetic energy of the doped holes, which, in the absence of interactions, would lead to extended Bloch-wave states whose occupancy is characterized in reciprocal space. To develop some degree of coherence on cooling, the spin and charge correlations must self-organize in a cooperative fashion.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Physics-guided machine learning approaches to predict the ideal stability properties of fusion plasmas

One of the biggest challenges to achieve the goal of producing fusion energy in tokamak devices is the necessity of avoiding disruptions of the plasma current due to instabilities. The disruption event characterization and forecasting (DECAF) framework has been developed in this purpose, integrating physics models of many causal events that can lead to a disruption. Two different machine learning approaches are proposed to improve the ideal magnetohydrodynamic (MHD) no-wall limit component of the kinetic stability model included in DECAF. First, a random forest regressor (RFR), was adopted to reproduce the DCON computed change in plasma potential energy without wall effects for a large database of equilibria from the national spherical torus experiment (NSTX). This tree-based method provides an analysis of the importance of each input feature, giving an insight into the underlying physics phenomena. Secondly, a fully-connected neural network has been trained on sets of calculations with the DCON code, to get an improved closed form equation of the no-wall β limit as a function of the relevant plasma parameters indicated by the RFR. The neural network has been guided by physics theory of ideal MHD in its extension outside the domain of the NSTX experimental data. The estimated value has been incorporated into the DECAF kinetic stability model and tested against a set of experimentally stable and unstable discharges. Moreover, the neural network results were used to simulate a real-time stability assessment using only quantities available in real-time. Finally, the portability of the model was investigated, showing encouraging results by testing the NSTX-trained algorithm on the mega ampere spherical tokamak (MAST).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Characterization of Si particles in additively manufactured AlSi10Mg using synchrotron transmission X-ray nanotomography

In AlSi10Mg samples manufactured by Laser Powder Bed Fusion, distinguishing the Si eutectic network/Si particles from the Al matrix by X-ray imaging is challenging due to the low absorption contrast between the Al and Si. This work investigates the possibility of overcoming this obstacle in synchrotron transmission X-ray microscopy. Effects of both different defocusing conditions and X-ray beam energies are evaluated and optimal conditions are identified for imaging a sample annealed post-print for 2h at 520°C. It is shown that both large particles (e.g. 4μm) and particles as small as 0.5 μm, can be imaged with reasonable precision in 3D non-destructively.

Defer, M.↗
DOE OSTI2022

High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean ( Glycine max ) nested association mapping population

We report photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping photosynthetic traits by traditional approaches is slow and destructive. There is proof-of-concept for leaf hyperspectral reflectance as a rapid method to model photosynthetic traits. However, the crucial step of demonstrating that hyperspectral approaches can be used to advance understanding of the genetic architecture of photosynthetic traits is untested. To address this challenge, we used full-range (500–2,400 nm) leaf reflectance spectroscopy to build partial least squares regression models to estimate leaf traits, including the rate-limiting processes of photosynthesis, maximum Rubisco carboxylation rate, and maximum electron transport. In total, 11 models were produced from a diverse population of soybean sampled over multiple field seasons to estimate photosynthetic parameters, chlorophyll content, leaf carbon and leaf nitrogen percentage, and specific leaf area (with R 2 from 0.56 to 0.96 and root mean square error approximately <10% of the range of calibration data). We explore the utility of these models by applying them to the soybean nested association mapping population, which showed variability in photosynthetic and leaf traits. Genetic mapping provided insights into the underlying genetic architecture of photosynthetic traits and potential improvement in soybean. Notably, the maximum Rubisco carboxylation rate mapped to a region of chromosome 19 containing genes encoding multiple small subunits of Rubisco. We also mapped the maximum electron transport rate to a region of chromosome 10 containing a fructose 1,6-bisphosphatase gene, encoding an important enzyme in the regeneration of ribulose 1,5-bisphosphate and the sucrose biosynthetic pathway. The estimated rate-limiting steps of photosynthesis were low or negatively correlated with yield suggesting that these traits are not influenced by the same genetic mechanisms and are not limiting yield in the soybean NAM population. Leaf carbon percentage, leaf nitrogen percentage, and specific leaf area showed strong correlations with yield and may be of interest in breeding programs as a proxy for yield. This work is among the first to use hyperspectral reflectance to model and map the genetic architecture of the rate-limiting steps of photosynthesis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An Iterative Response-Surface-Based Approach for Chance-Constrained AC Optimal Power Flow Considering Dependent Uncertainty

A modern power system is characterized by a stochastic variation of the loads and an increasing penetration of renewable energy generation, which results in large uncertainties in its states. These uncertainties bring formidable challenges to the power system planning and operation process. To address these challenges, we propose a cost-effective, iterative response-surface-based approach for the chance-constrained AC optimal power-flow problem that aims to ensure the secure operation of the power systems considering dependent uncertainties. Starting from a stochastic-sampling-based framework, we first utilize the copula theory to simulate the dependence among multivariate uncertain inputs. Then, to reduce the prohibitive computational time required in the traditional Monte-Carlo method, we propose, instead of using the original complicated power-system model, to rely on a polynomial-chaos-based response surface. This response surface allows us to efficiently evaluate the time-consuming power-system model at arbitrary distributed sampled values with a negligible computational cost. This further enables us to efficiently conduct an online stochastic testing for the system states that not only screens out the statistical active constraints, but also assists in a better design of the tightened bounds without using any Gaussian or symmetric assumption. Finally, an iterative procedure is executed to fine-tune the optimal solution that better satisfies a predefined probability. The simulations conducted in multiple test systems demonstrate the excellent performance of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types

Leaf trait relationships are widely used to predict ecosystem function in Terrestrial Biosphere Models (TBMs), in which leaf maximum carboxylation capacity (V c,max ), an important trait for modelling photosynthesis, can be inferred from other easier- to-measure traits. However, whether trait-V c,max relationships are robust across different forest types remains unclear. Here we used measurements of leaf traits, including one morphological trait (leaf mass per area), three biochemical traits (leaf water content, area-based leaf nitrogen content, and leaf chlorophyll content), one physiological trait (V c,max ), as well as leaf reflectance spectra, and explored their relationships within and across three contrasting forest types in China. We found weak and forest type-specific relationships between V c,max and the four morphological and biochemical traits (R 2 ≤ 0.15), indicated by significantly changing slopes and intercepts across forest types. In contrast, reflectance spectroscopy effectively collapsed the differences in the trait-V c,max relationships across three forest biomes into a single robust model for V c,max (R 2 = 0.77), and also accurately estimated the four traits (R 2 = 0.75-0.94). Furthermore, these findings challenge the traditional use of empirical trait-V c,max relationships in TBMs for estimating terrestrial plant photosynthesis, but also highlight spectroscopy as an efficient alternative for characterizing V c,max and multi-trait variability, with critical insights into ecosystem modeling and functional trait ecology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Growth of ultrathin Bi 2 Se 3 films by molecular beam epitaxy

Bi 2 Se 3 is a widely studied 3D topological insulator having potential applications in optics, electronics, and spintronics. When the thickness of these films decreases to less than approximately 6 nm, the top and bottom surface states couple, resulting in the opening of a small gap at the Dirac point. In the 2D limit, Bi 2 Se 3 may exhibit quantum spin Hall states. However, growing coalesced ultrathin Bi 2 Se 3 films with a controllable thickness and typical triangular domain morphology in the few nanometer range is challenging. Here, we explore the growth of Bi 2 Se 3 films having thicknesses down to 4 nm on sapphire substrates using molecular beam epitaxy that were then characterized with Hall measurements, atomic force microscopy, and Raman imaging. We find that substrate pretreatment—growing and decomposing a few layers of Bi 2 Se 3 before the actual deposition—is critical to obtaining a completely coalesced film. In addition, higher growth rates and lower substrate temperatures led to improvement in surface roughness, in contrast to what is observed for conventional epitaxy. Altogether, coalesced ultrathin Bi 2 Se 3 films with lower surface roughness enable thickness-dependent studies across the transition from a 3D-topological insulator to one with gapped surface states in the 2D regime.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A miniaturized feedstocks-to-fuels pipeline for screening the efficiency of deconstruction and microbial conversion of lignocellulosic biomass

Sustainably grown biomass is a promising alternative to produce fuels and chemicals and reduce the dependency on fossil energy sources. However, the efficient conversion of lignocellulosic biomass into biofuels and bioproducts often requires extensive testing of components and reaction conditions used in the pretreatment, saccharification, and bioconversion steps. This restriction can result in a significant and unwieldy number of combinations of biomass types, solvents, microbial strains, and operational parameters that need to be characterized, turning these efforts into a daunting and time-consuming task. Here we developed a high-throughput feedstocks-to-fuels screening platform to address these challenges. The result is a miniaturized semi-automated platform that leverages the capabilities of a solid handling robot, a liquid handling robot, analytical instruments, and a centralized data repository, adapted to operate as an ionic-liquid-based biomass conversion pipeline. The pipeline was tested by using sorghum as feedstock, the biocompatible ionic liquid cholinium phosphate as pretreatment solvent, a “one-pot” process configuration that does not require ionic liquid removal after pretreatment, and an engineered strain of the yeast Rhodosporidium toruloides that produces the jet-fuel precursor bisabolene as a conversion microbe. By the simultaneous processing of 48 samples, we show that this configuration and reaction conditions result in sugar yields (~70%) and bisabolene titers (~1500 mg/L) that are comparable to the efficiencies observed at larger scales but require only a fraction of the time. We expect that this Feedstocks-to-Fuels pipeline will become an effective tool to screen thousands of bioenergy crop and feedstock samples and assist process optimization efforts and the development of predictive deconstruction approaches.

09 BIOMASS FUELS↗
DOE OSTI2020

Novel Membrane and Electrodeposition-Based Separation and Recovery of Rare Earth Elements from Coal Combustion Residues (Final Report)

This project developed a hydrometallurgical-based technology to extract and concentrate rare earth elements (REEs) from a representative group of coal combustion residuals (CCRs) from major coal sources in the United States. The approach for REE recovery comprises two general components: (1) Leaching of REEs from CCRs and (2) Separation of REEs from other major ions in the CCR leachate. The leaching step entails acid leaching with nitric or hydrochloric acid, and in some cases, pretreatment of CCRs with alkaline roasting prior to acid leaching. The follow-up REE recovery steps involve a series of membrane-based methods to separate and concentrate rare earth ions from other major ions in acid leachates of CCRs. These methods include liquid emulsion membranes, supported liquid membranes and electrodeposition with carbon nanotube electrochemical filters. The advantage of these separation approaches (relative to conventional approaches such as solvent extraction) is a reduction in the usage of solvents and other costly chemicals and a reduction of hazardous waste products that are challenges in conventional REE separation methods. In the testing of our process, we selected a representative set of CCR samples from our collection and performed a suite of characterization measurements (total REE content and major mineralogy). The major results of this work demonstrated that heated acid leaching could efficiently extract REEs from PRB-based coal fly ashes while the Appalachian and Illinois Basin CCRs required alkaline roasting with NaOH prior to acid leaching at room temperature. The supported liquid membrane (SLM) configuration and electrochemical deposition (ED) system yielded the most promising methods of REE recovery from the acid leachates of fly ash. Our most concentrated product to date comprised 1 wt.% (dry basis) REEs produced from an Appalachian-based fly ash leached and purified by SLM. The SLM separation process was more selective for heavy REEs over the light REEs. When SLM was combined with ED, preliminary results demonstrated that a final product of >2 wt.% REEs was possible.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Nonlinear Characterization of a Joint Exhibiting a Reduction in Damping at High Energy

Even with the advent of additive manufacturing, the vast majority of complex structures are comprised of individual components held together with bolted joints. However, bolted joints present a challenge for mechanical design as they are a source of nonlinearity and increase the uncertainty in the overall behavior of the system in a dynamic environment. While many advances have been made in the ability to accurately model and test bolted joints, it is still an open area of research. Modes of vibration that exercise bolted joints typically exhibit nonlinear behavior where, with increased excitation level, the natural frequency decreases (i.e. softens) and the damping increases. However, the system under study for this work has an axial mode which does not follow this trend; it does soften as expected, but, after an initial increase, the apparent damping decreases with excitation amplitude. At the highest excitation level, the frequency of the mode decreases to that of a nearby bending mode and the response is amplified nearly 500% above that at lower levels. It is unclear whether the decrease in damping is due to the coupling of the two modes or if it is a characteristic of the axial mode. Therefore, the objective of this project is to investigate the coupling between the axial and bending modes and the dynamics leading to the decrease in damping.

42 ENGINEERING↗
DOE OSTI2020

High-Temperature Particle Heat Exchanger for sCO2 Power Cycles [Award 30342]

This report describes the design, development, and testing of a prototype 100 kWt particle-to-supercritical CO 2 (sCO2) heat exchanger. An analytic hierarchy process was implemented to compare and evaluate alternative heat-exchanger designs (fluidized bed, shell-and-plate moving packed bed, and shell-and-tube moving packed bed) that could meet the high pressure (≥ 20 MPa) and high temperature (≥ 700 °C) operational requirements associated with sCO2 power cycles. Cost, heat-transfer coefficient, structural reliability, manufacturability, parasitics and heat losses, scalability, compatibility, erosion and corrosion, transient operation, and inspection ease were considered in the evaluation. A 100 kWt shell-and-plate design was selected for construction and integration with Sandia’s falling particle receiver system that heats the particles using concentrated sunlight. Sandia worked with industry to design and construct the moving packed-bed shell-and-plate heat exchanger. Tests were performed to evaluate its performance using both electrical heating and concentrated sunlight to heat the particles. Overall heat transfer coefficients at off-design conditions (reduced operating temperatures and only three stainless steel banks in the counter-crossflow heat exchanger) were measured to be approximately ~25 - 70 W/m 2 -K, significantly lower than simulated values of >100 W/m 2 -K. Tests using the falling particle receiver to heat the particles with concentrated sunlight yielded overall heat transfer coefficients of ~35 – 80 W/m 2 -K with four banks (including a nickel-alloy bank above the three stainless steel banks). The overall heat transfer coefficient was observed to decrease with increasing particle inlet temperatures, which contrasted the results of simulations that showed an increase in heat transfer coefficient with temperature due to increased effective particle-bed thermal conductivity from radiation. The likely cause of the discrepancy was particle-flow maldistributions and funnel flow within the heat exchanger caused by internal ledges and cross-bracing, which could have been exacerbated by increased particle-wall friction at higher temperatures. Additional heat loss at higher temperatures may also contribute to a lower overall heat-transfer coefficient. Design challenges including pressure drop, particle and sCO2 flow maldistribution, and reduced heat transfer coefficient are discussed with approaches for mitigation in future designs. Lessons learned regarding instrumentation, performance characterization, and operation of particle components and sCO2 flow loops are also discussed. Finally, a 200 MWt commercial-scale shell-and-plate heat-exchanger design based on the concepts investigated in this report is proposed.

14 SOLAR ENERGY↗
DOE OSTI2021

Measurement of Volatile Compounds for Real-Time Analysis of Soil Microbial Metabolic Response to Simulated Snowmelt

Snowmelt dynamics are a significant determinant of microbial metabolism in soil and regulate global biogeochemical cycles of carbon and nutrients by creating seasonal variations in soil redox and nutrient pools. With an increasing concern that climate change accelerates both snowmelt timing and rate, obtaining an accurate characterization of microbial response to snowmelt is important for understanding biogeochemical cycles intertwined with soil. However, observing microbial metabolism and its dynamics non-destructively remains a major challenge for systems such as soil. Microbial volatile compounds (mVCs) emitted from soil represent information-dense signatures and when assayed non-destructively using state-of-the-art instrumentation such as Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-TOF-MS) provide time resolved insights into the metabolism of active microbiomes. In this study, we used PTR-TOF-MS to investigate the metabolic trajectory of microbiomes from a subalpine forest soil, and their response to a simulated wet-up event akin to snowmelt. Using an information theory approach based on the partitioning of mutual information, we identified mVC metabolite pairs with robust interactions, including those that were non-linear and with time lags. The biological context for these mVC interactions was evaluated by projecting the connections onto the Kyoto Encyclopedia of Genes and Genomes (KEGG) network of known metabolic pathways. Simulated snowmelt resulted in a rapid increase in the production of trimethylamine (TMA) suggesting that anaerobic degradation of quaternary amine osmo/cryoprotectants, such as glycine betaine, may be important contributors to this resource pulse. Unique and synergistic connections between intermediates of methylotrophic pathways such as dimethylamine, formaldehyde and methanol were observed upon wet-up and indicate that the initial pulse of TMA was likely transformed into these intermediates by methylotrophs. Increases in ammonia oxidation signatures (transformation of hydroxylamine to nitrite) were observed in parallel, and while the relative role of nitrifiers or methylotrophs cannot be confirmed, the inferred connection to TMA oxidation suggests either a direct or indirect coupling between these processes. Overall, it appears that such mVC time-series from PTR-TOF-MS combined with causal inference represents an attractive approach to non-destructively observe soil microbial metabolism and its response to environmental perturbation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Hubble WFC3 Spectroscopy of the Habitable-zone Super-Earth LHS 1140 b

Atmospheric characterization of temperate, rocky planets is the holy grail of exoplanet studies. These worlds are at the limits of our capabilities with current instrumentation in transmission spectroscopy and challenge our state-of-the-art statistical techniques. Here we present the transmission spectrum of the temperate super-Earth LHS 1140b using the Hubble Space Telescope (HST). The Wide Field Camera 3 (WFC3) G141 grism data of this habitable-zone (T {sub eq} = 235 K) super-Earth (R = 1.7 R {sub ⊕}) shows tentative evidence of water. However, the signal-to-noise ratio, and thus the significance of the detection, is low and stellar contamination models can cause modulation over the spectral band probed. We attempt to correct for contamination using these models and find that, while many still lead to evidence for water, some could provide reasonable fits to the data without the need for molecular absorption although most of these cause features in the visible ground-based data which are nonphysical. Future observations with the James Webb Space Telescope would be capable of confirming, or refuting, this atmospheric detection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

WASP-107b’s Density Is Even Lower: A Case Study for the Physics of Planetary Gas Envelope Accretion and Orbital Migration

With a mass in the Neptune regime and a radius of Jupiter, WASP-107b presents a challenge to planet formation theories. Meanwhile, the planet’s low surface gravity and the star’s brightness also make it one of the most favorable targets for atmospheric characterization. Here, we present the results of an extensive 4 yr Keck/HIRES radial-velocity (RV) follow-up program of the WASP-107 system and provide a detailed study of the physics governing the accretion of the gas envelope of WASP-107b. We reveal that WASP-107b’s mass is only 1.8 Neptune masses (M {sub b} = 30.5 ± 1.7 M {sub ⊕}). The resulting extraordinarily low density suggests that WASP-107b has a H/He envelope mass fraction of >85% unless it is substantially inflated. The corresponding core mass of <4.6 M {sub ⊕} at 3σ is significantly lower than what is traditionally assumed to be necessary to trigger massive gas envelope accretion. We demonstrate that this large gas-to-core mass ratio most plausibly results from the onset of accretion at ≳1 au onto a low-opacity, dust-free atmosphere and subsequent migration to the present-day a {sub b} = 0.0566 ± 0.0017 au. Beyond WASP-107b, we also detect a second, more massive planet (M{sub c}sin i=0.36±0.04M{sub J}) on a wide eccentric orbit (e {sub c} = 0.28 ± 0.07) that may have influenced the orbital migration and spin–orbit misalignment of WASP-107b. Overall, our new RV observations and envelope accretion modeling provide crucial insights into the intriguing nature of WASP-107b and the system’s formation history. Looking ahead, WASP-107b will be a keystone planet to understand the physics of gas envelope accretion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

The LSST AGN Data Challenge: Selection Methods

Abstract Development of the Rubin Observatory Legacy Survey of Space and Time (LSST) includes a series of Data Challenges (DCs) arranged by various LSST Scientific Collaborations that are taking place during the project's preoperational phase. The AGN Science Collaboration Data Challenge (AGNSC-DC) is a partial prototype of the expected LSST data on active galactic nuclei (AGNs), aimed at validating machine learning approaches for AGN selection and characterization in large surveys like LSST. The AGNSC-DC took place in 2021, focusing on accuracy, robustness, and scalability. The training and the blinded data sets were constructed to mimic the future LSST release catalogs using the data from the Sloan Digital Sky Survey Stripe 82 region and the XMM-Newton Large Scale Structure Survey region. Data features were divided into astrometry, photometry, color, morphology, redshift, and class label with the addition of variability features and images. We present the results of four submitted solutions to DCs using both classical and machine learning methods. We systematically test the performance of supervised models (support vector machine, random forest, extreme gradient boosting, artificial neural network, convolutional neural network) and unsupervised ones (deep embedding clustering) when applied to the problem of classifying/clustering sources as stars, galaxies, or AGNs. We obtained classification accuracy of 97.5% for supervised models and clustering accuracy of 96.0% for unsupervised ones and 95.0% with a classic approach for a blinded data set. We find that variability features significantly improve the accuracy of the trained models, and correlation analysis among different bands enables a fast and inexpensive first-order selection of quasar candidates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1993

Nonlinear optical thin films

A focused approach to development and evaluation of organic polymer films for use in optoelectronics is presented. The issues and challenges that are addressed include: (1) material synthesis, purification, and the tailoring of the material properties; (2) deposition of uniform thin films by a variety of methods; (3) characterization of material physical properties (thermal, electrical, optical, and electro-optical); and (4) device fabrication and testing. Photonic materials, devices, and systems were identified as critical technology areas by the Department of Commerce and the Department of Defense. This approach offers strong integration of basic material issues through engineering applications by the development of materials that can be exploited as the active unit in a variety of polymeric thin film devices. Improved materials were developed with unprecedented purity and stability. The absorptive properties can be tailored and controlled to provide significant improvement in propagation losses and nonlinear performance. Furthermore, the materials were incorporated into polymers that are highly compatible with fabrication and patterning processes for integrated optical devices and circuits. By simultaneously addressing the issues of materials development and characterization, keeping device design and fabrication in mind, many obstacles were overcome for implementation of these polymeric materials and devices into systems. We intend to considerably improve the upper use temperature, poling stability, and compatibility with silicon based devices. The principal device application that was targeted is a linear electro-optic modulation etalon. Organic polymers need to be properly designed and coupled with existing integrated circuit technology to create new photonic devices for optical communication, image processing, other laser applications such as harmonic generation, and eventually optical computing. The progression from microscopic sample to a suitable film-forming material in a working device is a complex, multifaceted endeavor. It requires close attention to maintaining the optical properties of the electro-optic active portion of the polymer while manipulating the polymer structure to obtain the desired secondary polymer properties.

Leslie, Thomas M.↗
NASA NTRS1998

Development of a Satellite Systems for Measuring Soil Moisture

The science need for remotely sensed soil moisture has been well established in the hydrologic, climate change and weather forecasting communities. There also have been a number of programs that have demonstrated the feasibility of using long wave microwave sensors for estimating soil moisture. These have ranged from truck mounted sensors, to intensive airborne campaigns with science objectives. Based on this history of truck and aircraft experiments, the science community has settled on a soil moisture product that meets the following criteria: a two day global repeat, a measured layer of 5 cm of soil, a footprint of 20 to 30 km, and an absolute accuracy of +/- 4% volumetric soil moisture. The principal sensor to accomplish this is an L-band passive microwave radiometer. A soil moisture mission is being proposed for the NASA Earth Systems Science Pathfinder (ESSP) mission which has very real constraints of a limited budget which includes the launch vehicle, and a three year award to launch time schedule. This paper describes ways to solve the very large antenna challenge, and the criteria used to choose the final design for an ESSP proposal. The paper also discusses the alternatives considered to obtain the necessary ancillary data for characterizing the surface roughness, the surface temperature and the attenuation affects of vegetation.

Engman, Edwin T.↗
NASA NTRS2009

Characterization of Damage in Triaxial Braid Composites Under Tensile Loading

Carbon fiber composites utilizing flattened, large tow yarns in woven or braided forms are being used in many aerospace applications. Their complex fiber architecture and large unit cell size present challenges in both understanding deformation processes and measuring reliable material properties. This report examines composites made using flattened 12k and 24k standard modulus carbon fiber yarns in a 0 /+60 /-60 triaxial braid architecture. Standard straight-sided tensile coupons are tested with the 0 axial braid fibers either parallel with or perpendicular to the applied tensile load (axial or transverse tensile test, respectively). Nonuniform surface strain resulting from the triaxial braid architecture is examined using photogrammetry. Local regions of high strain concentration are examined to identify where failure initiates and to determine the local strain at the time of initiation. Splitting within fiber bundles is the first failure mode observed at low to intermediate strains. For axial tensile tests splitting is primarily in the 60 bias fibers, which were oriented 60 to the applied load. At higher strains, out-of-plane deformation associated with localized delamination between fiber bundles or damage within fiber bundles is observed. For transverse tensile tests, the splitting is primarily in the 0 axial fibers, which were oriented transverse to the applied load. The initiation and accumulation of local damage causes the global transverse stress-strain curves to become nonlinear and causes failure to occur at a reduced ultimate strain. Extensive delamination at the specimen edges is also observed.

Littell, Justin D.↗