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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Application of IR imaging for free-surface velocity measurement in liquid-metal systems

Measuring free-surface, liquid-metal flow velocity is challenging to do in a reliable and accurate manner. This paper presents a non-invasive, easily calibrated method of measuring the surface velocities of open-channel liquid-metal flows using an IR camera. Unlike other spatially limited methods, this IR camera particle tracking technique provides full field-of-view data that can be used to better understand open-channel flows and determine surface boundary conditions. Lastly, this method could be implemented and automated for a wide range of liquid-metal experiments, even if they operate at high-temperatures or within strong magnetic fields.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Network Models of Active Degradation Mechanisms and Pathways for Service Life Prediction of Indoor and Outdoor PV Modules

ct: PV service lifetime prediction (SLP) enables accurate calculation of levelized cost of energy (LCOE), which is crucial to rationalizing PV investment and installation. However, SLP is challeging since PV reliability in the field is affected by many combined factors, including various environmental stresses and module quality. In order to map out the active degradation mechanisms and pathways that best resemble real world conditions, we introduce the framework of a study protocol and use network models fitted to data, to enable analysis and SLP of complex PV systems with multiple active degradation mechanisms. The study protocol is the experimental design, including module variants and different exposure conditions, selection of evaluation methods, time-series data acquisition and training of network models to these data. We present SLP of minimodules in the lab and PV systems in the field. For lab SLP, minimodules with 8 variants based on manufacturer, architecture, and encapsulation were prepared and aged in modified damp heat with or without full spectrum light exposure. Stepwise I-V and Suns-Voc data acquisition tracks changes in electrical properties including Rs,IV, Isc,IV, Vmp,PIV providing insights into power loss of minimodules. Network structural equation modeling (netSEM) was utilized to construct degradation pathway models that identify active degradation mechanisms and predict power loss over time. For field SLP, datastreams of Pmp values and I-V curve datastreams of two types of modules installed in three distinctly different Köppen-Geiger climate zones for 9 years were acquired. With power loss modes corresponding to uniform current loss (ΔPIsc), recombination (ΔPVoc), series resistance (ΔPRs), and current mismatch (ΔPImis) determined, the performance loss rates (PLR) were determined using PVplr. We show how to establish a study protocol framework to ensure appropriate parametric variations and valid data collection from the variants of your complex systems. Then the data-driven netSEM model fitting provides a comprehensive mapping of multiple active degradation mechanisms, and accurate service life prediction.

network model, degradation, photovoltaic, solar↗
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 NTRS1993

Structure of turbulence in three-dimensional boundary layers

This report provides an overview of the three dimensional turbulent boundary layer concepts and of the currently available experimental information for their turbulence modeling. It is found that more reliable turbulence data, especially of the Reynolds stress transport terms, is needed to improve the existing modeling capabilities. An experiment is proposed to study the three dimensional boundary layer formed by a 'sink flow' in a fully developed two dimensional turbulent boundary layer. Also, the mean and turbulence field measurement procedure using a three component laser Doppler velocimeter is described.

Subramanian, Chelakara S.↗
NASA NTRS1994

Innovation and application of ANN in Europe demonstrated by Kohonen maps

One of the most important contributions to neural networks comes from Kohonen, Helsinki/Espoo, Finland, who had the idea of self-organizating maps in 1981. He verified his idea by an algorithm of which many applications make use of. The impetus for this idea came from biology, a field where the Europeans have always been very active at several research laboratories. The challenge was to model the self-organization found in the brain. Today one goal is the development of more sophisticated neurons which model the biological neurons more exactly. They should come to a better performance of neural nets with only a few complex neurons instead of many simple ones. A lot of application concepts arise from this idea: Kohonen himself applied it to speech recognition, but the project did not overcome much more than the recognition of the numerals one to ten at that time. A more promising application for self-organizing maps is process control and process monitoring. Several proposals were made which concern parameter classification of semiconductor technologies, design of integrated circuits, and control of chemical processes. Self-organizing maps were applied to robotics. The neural concept was introduced into electric power systems. At Dortmund we are working on a system which has to monitor the quality and the reliability of gears and electrical motors in equipment installed in coal mines. The results are promising and the probability to apply the system in the field is very high. A special feature of the system is that linguistic rules which are embedded in a fuzzy controller analyze the data of the self-organizing map in regard to life expectation of the gears. It seems that the fuzzy technique will introduce the technology of neural networks in a tandem mode. These technologies together with the genetic algorithms start to form the attractive field of computational intelligence.

Goser, Karl↗
NASA NTRS2003

An Introduction to Atmospheric Radiation: Review for the Bulletin of AMS

Whether you like a certain geophysical book or not, largely depends on your background. The field of radiative transfer and atmospheric radiation, in particular, combines people with a wide range of mathematical skills: from theoretical astrophysicists and nuclear physicists to meteorologists and ecologists. There is always a delicate balance between physical explanations and their mathematical interpretations. This balance is very personal and is based on your background. I came to the field of atmospheric radiative transfer as a mathematician with little knowledge of atmospheric physics. After being in the field for more than a decade, I still have gaps in my atmospheric science education. Thus I assess a radiative transfer book fi-om two main criteria: how well does it describe the material that is familiar to me (the radiative transfer equation and its numerical solutions) and how well does it help me to fill the gaps in my personal knowledge. So I present this review fi-om the perspective of a former mathematician working in the field of atmospheric radiation. . After being asked to review the book, my first intention was to compare the new edition with the previous one (Liou, 1980). In doing so, you can clearly follow the progress made in the field of atmospheric radiation over the past two decades. If there are few changes (as in Fundamental Radiative Transfer) or no changes at all (as in the Maxwell s equations), then the field has not seen much development. To the contrary, many differences between the two editions illustrate areas of major progress in the field, such as evidenced in Thermal Ineared Radiative Transfer and even in the creations of completely new fields like Three-Dimensional Radiative Transfer or Light Scattering by Nonspherical Particles. Obviously, the major changes happened not in the theory, which is at least half a century old, but in data quality and completely new measurements (mostly due to new satellite data) with higher accuracy and more reliability. The new edition illustrates this progress well.

Marshak, Alexander↗
NASA NTRS2020

Exploring the Limits of the Data-Model-Theory Synergy: “Hot” MW Transitions for Rovibrational IR Studies

In order to further improve the accuracy of rovibrational IR line lists generated from the “Best Theory +Reliable High-resolution Experiment” (BTRHE) strategy from 0.01-0.05 cm-1, or 300-1500 MHz, to ~10 MHz, we explore the current limits of the Data-Model-Theory synergy by examining the accuracy and consistency of existing data, then propose that “hot” bands in microwave (MW) spectra is the solution we need for future enhancements. The Ames SO2 J=0-20 rovibrational energy levels computed on the semi-empirically refined Ames-2 potential energy surface (PES) are fit to the Effective Hamiltonian (EH) model regularly used in the experimental infrared (IR) analysis for SO2 isotopologues. In the fitted EH(Ames) model, the rotational constants A/B/C and all 5 quartic centrifugal distortion constants display clear, systematic, and consistent patterns along the vibrational state energy or quanta. Such consistent patterns may facilitate the vibrational assignments for MW hot bands and extract more information from high temperature MW spectra. Some EH(Expt) analyses were carried out with the lowest order Coriolis Coupling term, C1. Their constants should not be directly compared with other EH(Expt) and EH(Ames) results. After excluding them, our  = EH(Ames)- EH(Expt) analyses for 5 isotopologues (626, 636, 646, 628 and 828) indicates some loss of accuracy and consistency starting from vibrational states as low as 22 or 1000 cm-1. Some EH parameters, e.g. K, may have relative deviations as large as 50-100% and totally lose any recognizable patterns. This simply means that current EH(Expt) models do not have the system-wide consistency we need to further refine the EH(Ames) and Ames rovibrational IR line lists. A large part of such defects are probably inherited from the limited precision of experimental line positions, i.e. 1E-3 ~ 1E-4 cm-1, or 3-30 MHz. This is confirmed in a series of truncation tests using the Ames data. Although the EH(Ames) consistency may help identify unreliable rovibrational EH(Expt) parameters, and make reliable predictions for minor isotopologues and unobserved vibrational bands, we believe only the highly accurate “hot” MW transitions can provide real enhancements for EH(Expt) accuracy and consistency. “Hot” MW spectra should play a more significant role in the future synergy of Data, Model, and Theory in the field of rovibrational IR studies.

Xinchuan Huang↗
DOE OSTI2012

RELIABLE IDENTIFICATIONS OF ACTIVE GALACTIC NUCLEI FROM THE WISE, 2MASS, AND ROSAT ALL-SKY SURVEYS

We have developed the ''S{sub IX}'' statistic to identify bright, highly likely active galactic nucleus (AGN) candidates solely on the basis of Wide-field Infrared Survey Explorer (WISE), Two Micron All-Sky Survey (2MASS), and ROSAT all-sky survey (RASS) data. This statistic was optimized with data from the preliminary WISE survey and the Sloan Digital Sky Survey, and tested with Lick 3 m Kast spectroscopy. We find that sources with S{sub IX} < 0 have a {approx}>95% likelihood of being an AGN (defined in this paper as a Seyfert 1, quasar, or blazar). This statistic was then applied to the full WISE/2MASS/RASS dataset, including the final WISE data release, to yield the ''W2R'' sample of 4316 sources with S{sub IX} < 0. Only 2209 of these sources are currently in the Veron-Cetty and Veron (VCV) catalog of spectroscopically confirmed AGNs, indicating that the W2R sample contains nearly 2000 new, relatively bright (J {approx}< 16) AGNs. We utilize the W2R sample to quantify biases and incompleteness in the VCV catalog. We find that it is highly complete for bright (J < 14), northern AGNs, but the completeness drops below 50% for fainter, southern samples and for sources near the Galactic plane. This approach also led to the spectroscopic identification of 10 new AGNs in the Kepler field, more than doubling the number of AGNs being monitored by Kepler. The W2R sample contains better than 1 bright AGN every 10 deg{sup 2}, permitting construction of AGN samples in any sufficiently large region of sky.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Machine Learning and Data Science to Advance Laboratory Earthquake Prediction and Illuminate the Mechanics of Precursors to Failure

Earthquakes represent one of our greatest natural hazards and in recent years human induced seismicity is adding to the threat. Even a modest improvement in the ability to forecast devastating large earthquakes or smaller shallow events associated with fluid injection could save thousands of lives and billions of dollars. Current efforts to forecast earthquakes are limited by knowledge of earthquake physics and hampered by a lack of reliable lab or field observations. However, recent work has provided a critical opportunity for advancement. We have found: 1) clear and consistent precursors prior to earthquake-like failure in the laboratory and 2) that lab earthquakes can be predicted using machine learning (ML). These works show that stick-slip failure events –the lab equivalent of earthquakes– are preceded by a cascade of micro-failure events that radiate elastic energy in a manner that foretells catastrophic failure. Remarkably, ML predicts the fault zone stress state, the failure time and in some cases the magnitude of lab earthquakes. In addition, the observations include clear precursors to failure in the form of changes in fault zone properties prior to lab earthquakes. Precursors have been observed in previous laboratory studies but their origin is poorly understood and their possible connection to ML based earthquake prediction is unknown. The work conducted under our project has dramatically expanded these efforts. We have developed an integrated data science approach to illuminate the physics of earthquake precursors and lab earthquake prediction. Our work has accelerated the development of ML, artificial intelligence (AI), and related data science approaches by providing massive data sets that are tightly connected to critical scientific problems and by bringing together leading subject matter experts and data scientists. Earthquake physics involves phenomena that are far from equilibrium. Our work has leveraged data science methods to illuminate these phenomena and investigate how they relate to earthquake prediction. In addition to a large database with many types of labeled events that is available to everyone, our work has advanced the fundamental understanding of seismic forecasting, earthquake physics, and fault rheology

58 GEOSCIENCES↗
DOE OSTI2018

Pressure-Based Inversion and Data Assimilation System (PIDAS) for CO 2 Leakage Detection (Final Report)

This project aims to develop a Pressure-based Inversion and Data Assimilation System (PIDAS) for detecting CO 2 leakage from storage formations. Carbon capture, utilization, and sequestration (CCUS) has the potential to enable deep reductions in global carbon emissions if high storage efficiency can be achieved. A major hurdle to industrial-scale implementation of geological carbon sequestration (GCS) projects is the potential migration of fluids (either brine or injected CO 2 ) from the storage formations and the resulting legal and financial liabilities. The capability to accurately identify leakage pathways by which stored CO 2 could leak, has leaked, or is leaking from the targeted storage zone is thus of paramount importance to site licensees and regulators. Although many MVA techniques have been devised, pressure-based monitoring technology remains the most sensitive and reliable technique for early detection. Pressure-based monitoring has consistently received the highest score in terms of benefit/cost ratio and it provides the greatest potential for leakage detection with broad areal coverage. Under this project we have (a) demonstrated the utility of the proposed well testing technique for leakage detection through integrated theoretical and numerical analysis, laboratory experiments, and field tests; (b) developed effective data analysis and inversion algorithms for identifying leakage pathways by fusing data generated during well testing; (c) provided a designing tool for maximizing the utility of the developed PIDAS tool for early leakage detection.

02 PETROLEUM↗
DOE OSTI2015

Long Island Smart Energy Corridor

The Long Island Power Authority (LIPA) has teamed with Stony Brook University (Stony Brook or SBU) and Farmingdale State College (Farmingdale or FSC), two branches of the State University of New York (SUNY), to create a “Smart Energy Corridor.” The project, located along the Route 110 business corridor on Long Island, New York, demonstrated the integration of a suite of Smart Grid technologies from substations to end-use loads. The Smart Energy Corridor Project included the following key features: -TECHNOLOGY: Demonstrated a full range of smart energy technologies, including substations and distribution feeder automation, fiber and radio communications backbone, advanced metering infrastructure (AM”), meter data management (MDM) system (which LIPA implemented outside of this project), field tools automation, customer-level energy management including automated energy management systems, and integration with distributed generation and plug-in hybrid electric vehicles. -MARKETING: A rigorous market test that identified customer response to an alternative time-of-use pricing plan and varying levels of information and analytical support. -CYBER SECURITY: Tested cyber security vulnerabilities in Smart Grid hardware, network, and application layers. Developed recommendations for policies, procedures, and technical controls to prevent or foil cyber-attacks and to harden the Smart Grid infrastructure. -RELIABILITY: Leveraged new Smart Grid-enabled data to increase system efficiency and reliability. Developed enhanced load forecasting, phase balancing, and voltage control techniques designed to work hand-in-hand with the Smart Grid technologies. -OUTREACH: Implemented public outreach and educational initiatives that were linked directly to the demonstration of Smart Grid technologies, tools, techniques, and system configurations. This included creation of full-scale operating models demonstrating application of Smart Grid technologies in business and residential settings. Farmingdale State College held three international conferences on energy and sustainability and Smart Grid related technologies and policies. These conferences, in addition to public seminars increased understanding and acceptance of Smart Grid transformation by the general public, business, industry, and municipalities in the Long Island and greater New York region. - JOB CREATION: Provided training for the Smart Grid and clean energy jobs of the future at both Farmingdale and Stony Brook. Stony Brook focused its “Cradle to Fortune 500” suite of economic development resources on the opportunities emerging from the project, helping to create new technologies, new businesses, and new jobs. To achieve these features, LIPA and its sub-recipients, FSC and SBU, each have separate but complementary objectives. At LIPA, the Smart Energy Corridor (1) meant validating Smart Grid technologies; (2) quantifying Smart Grid costs and benefits; and (3) providing insights into how Smart Grid applications can be better implemented, readily adapted, and replicated in individual homes and businesses. LIPA installed 2,550 AMI meters (exceeding the 500 AMI meters in the original plan), created three “smart” substations serving the Corridor, and installed additional distribution automation elements including two-way communications and digital controls over various feeders and capacitor banks. It gathered and analyzed customer behavior information on how they responded to a new “smart” TOU rate and to various levels of information and analytical tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2017

Data Assimilation and Uncertainties in Early Solar Cycle Predictions

Stochastic nature of solar activity variations together with our limited knowledge of the dynamo mechanism and subsurface dynamics causes uncertainty in predictions of the solar cycle. For improving the physics-­‐based predictions we can take advantage of the mathematical data assimilation approach that allows us to take into account both, observational errors and model uncertainties, and provide estimates of the next solar cycle along with prediction uncertainties. In this study we use the Parker's migratory dynamo model together with the equation of magnetic helicity balance, which reproduces main properties of the sunspot cycles and allow us to minimize discrepancies between the observed global activity variations and the model solution. The test simulation runs show that a reliable prediction can be obtained for two phases of preceding solar cycle: 1) if the polar field reversals shortly after the solar maxima (strong toroidal field and weak poloidal field), and 2) during the solar minima (strongest poloidal and weak toroidal fields). The early estimate of Cycle 25 obtained by this method shows that this cycle will start in 2019 – 2020, reach the maximum in 2023 – 2024, and that the mean sunspot number at the maximum will be about 90 (for the v2.0 sunspot number series).

Data Assimilation↗
DOE OSTI2017

Low irradiance losses of photovoltaic modules

Here, the efficiency of a photovoltaic cell/module changes, as the intensity of incident irradiance decreases, in a non linear way and these changes are referred to as low irradiance losses. In this study data from field experiments, developed and organized by the National Renewable Energy Laboratory, are used to evaluate the low irradiance losses for a variety of module technologies. The results demonstrate that the ratio of the normalized power divided by the normalized short circuit current provide a good measure of the module's low light efficiency losses after both the maximum power and the short circuit current are adjusted for temperature effects. The normalized efficiencies determined through the field data, spanning for several months, are in good agreement with those determined under controlled conditions in a solar simulator. An analytical relation for the normalized efficiency is proposed based on existing formulation for the fill factor. Despite the approximate nature of the fill factor relation, this approach produces reliable results. It will be shown that a normalized efficiency curve can be used to extract information on the series and shunt resistances of the PV module and that the shunt resistance as a function of solar irradiance can be studied. Alternately, this formulation can be used to study the low irradiance losses of a module when the internal resistances are known.

14 SOLAR ENERGY↗
DOE OSTI2020

Planck intermediate results

In this work, we describe an extension of the most recent version of the Planck Catalogue of Compact Sources (PCCS2), produced using a new multi-band Bayesian Extraction and Estimation Package (BeeP). BeeP assumes that the compact sources present in PCCS2 at 857 GHz have a dust-like spectral energy distribution (SED), which leads to emission at both lower and higher frequencies, and adjusts the parameters of the source and its SED to fit the emission observed in Planck’s three highest frequency channels at 353, 545, and 857 GHz, as well as the IRIS map at 3000 GHz. In order to reduce confusion regarding diffuse cirrus emission, BeeP’s data model includes a description of the background emission surrounding each source, and it adjusts the confidence in the source parameter extraction based on the statistical properties of the spatial distribution of the background emission. BeeP produces the following three new sets of parameters for each source: (a) fits to a modified blackbody (MBB) thermal emission model of the source; (b) SED-independent source flux densities at each frequency considered; and (c) fits to an MBB model of the background in which the source is embedded. BeeP also calculates, for each source, a reliability parameter, which takes into account confusion due to the surrounding cirrus. This parameter can be used to extract sub-samples of high-frequency sources with statistically well-understood properties. We define a high-reliability subset (BeeP/base), containing 26 083 sources (54.1% of the total PCCS2 catalogue), the majority of which have no information on reliability in the PCCS2. We describe the characteristics of this specific high-quality subset of PCCS2 and its validation against other data sets, specifically for: the sub-sample of PCCS2 located in low-cirrus areas; the Planck Catalogue of Galactic Cold Clumps; the Herschel GAMA15-field catalogue; and the temperature- and spectral-index-reconstructed dust maps obtained with Planck’s Generalized Needlet Internal Linear Combination method. The results of the BeeP extension of PCCS2, which are made publicly available via the Planck Legacy Archive, will enable the study of the thermal properties of well-defined samples of compact Galactic and extragalactic dusty sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Theoretical modeling of the linear and nonlinear optical properties of organic crystals within the rigorous local field theory (RLFT)

This contribution summarizes our current findings in the field of calculating and predicting the linear and second-order nonlinear electric susceptibility tensor components of organic crystals. The methodology used for this purpose is based on a combination of the electrostatic interaction scheme developed by Munn and his coworkers (RLFT) with high-level electronic structure calculations. We compare the results of calculations with available experimental data for several examples of molecular crystals. We show the quality of the final results is influenced by i) the chromophore geometry, ii) the method used for molecular properties calculations and iii) the partitioning scheme used. In conclusion we summarize further plans to improve the reliability and predictability of the method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Time-sliced perturbation theory II: baryon acoustic oscillations and infrared resummation

We use time-sliced perturbation theory (TSPT) to give an accurate description of the infrared non-linear effects affecting the baryonic acoustic oscillations (BAO) present in the distribution of matter at very large scales. In TSPT this can be done via a systematic resummation that has a simple diagrammatic representation and does not involve uncontrollable approximations. We discuss the power counting rules and derive explicit expressions for the resummed matter power spectrum up to next-to leading order and the bispectrum at the leading order. The two-point correlation function agrees well with N -body data at BAO scales. The systematic approach also allows to reliably assess the shift of the baryon acoustic peak due to non-linear effects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Using leaf and stomatal traits to predict biomass production and water use efficiency in Populus

Climate change is reshaping ecosystems, driving plants to adapt through leaf-trait plasticity that reflects strategies for growth and water use. Predicting biomass production and intrinsic water use efficiency (iWUE) remains challenging because of genetic, taxonomic, and environmental variability. Here, we used eastern cottonwood and Populus hybrids as a model system to test whether easily measurable leaf traits can serve as reliable predictors of performance, and whether adding stomatal and biochemical traits improves predictive power. Across two field sites in Mississippi, leaf mass per area (LMA), biomass production, iWUE, leaf area, and foliar nitrogen ( N %) differed significantly among taxa and sites, while other traits were conserved. Factorial analysis of mixed data (FAMD) revealed distinct clustering of taxa and sites, indicating coordinated variation among leaf and stomatal traits. Pairwise correlations highlighted fundamental trade-offs, with biomass positively related to LMA and petiole length but negatively associated with iWUE, N %, and carbon isotopic ratios (δ 13 C). Leaf temperature and leaf angle varied among taxa and were significantly correlated with LMA and petiole length, suggesting mechanisms of heat dissipation and leaf movability that link simple traits to gas exchange and productivity. Weighted multiple linear regression models explained 80%–91% of variation in biomass production and iWUE. Models using only LMA, petiole length, and stomatal metrics performed nearly as well as those incorporating N %, and δ 13 C, with complex traits adding approximately 10% explanatory power. These results demonstrate that simple morphological traits capture integrated functional trade-offs, while complex traits refine predictions. This tiered approach provides an efficient framework for selecting high-yielding, water-efficient genotypes of Populus and other hardwood species, offering practical pathways to enhance carbon uptake and iWUE under climate change.

biomass production↗
NASA NTRS1975

Improved ultrasonic standard reference blocks

A program to improve the quality, reproducibility and reliability of nondestructive testing through the development of improved ASTM-type ultrasonic reference standards is described. Reference blocks of aluminum, steel, and titanium alloys were considered. Equipment representing the state-of-the-art in laboratory and field ultrasonic equipment was obtained and evaluated. Some RF and spectral data on ten sets of ultrasonic reference blocks were taken as part of a task to quantify the variability in response from nominally identical blocks. Techniques for residual stress, preferred orientation, and microstructural measurements were refined and are applied to a reference block rejected by the manufacturer during fabrication in order to evaluate the effect of metallurgical condition on block response.

Eitzen, D. G.↗