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DOE OSTI2026

Impact of vertical and seasonal variation in leaf traits on simulating soybean canopy photosynthesis via 1D and 3D modeling

Accurate modeling of photosynthesis is crucial for predicting crop productivity and quantifying the carbon cycle in agroecosystems. Leaf traits are essential inputs for modeling canopy photosynthesis. Yet, many existing models still use fixed plant functional type (PTF)-based values to parameterize leaf traits under a big-leaf or two-big-leaf assumption, neglecting their vertical profiles and seasonal changes. This simplification may introduce significant uncertainties in estimating gross primary productivity (GPP). In this study, we simulated soybean GPP and tested the effects of vertical and seasonal variation in three key leaf photosynthetic traits: the maximum carboxylation rate at 25 °C (Vcmax 25 ), leaf chlorophyll content (LCC), and leaf mass per area (LMA) in the 1D-SCOPE and 3D-Helios models. Weekly field measurements were conducted during the growing season of 2024 to support the simulation. We designed ten leaf trait parameterization schemes by incorporating different combinations of vertical profiles and seasonal changes, while assuming homogeneous canopy architecture in both models. Our results revealed that Vcmax 25 vertical and seasonal variation had the strongest influence on simulated GPP in both 1D and 3D models, while LCC and LMA effects were minimal. Particularly, the scheme with an empirically parameterized Vcmax 25 profile achieved comparable performance to the scheme with the measured Vcmax 25 profile. Both 1D-SCOPE and 3D-Helios accurately modeled GPP (SCOPE: R 2 = 0.87, Bias = 0.55 µmol m⁻² s⁻¹; Helios: R 2 = 0.9, Bias = 0.22 µmol m⁻² s⁻¹) under the most complex scheme, and their responses to vertical and seasonal variation in leaf traits were consistent, demonstrating the robustness of our findings. Based on our findings, we propose a scalable framework for parameterizing leaf traits to improve GPP simulations. This study contributes to improving the representation of leaf trait dynamics in canopy-level photosynthesis models, potentially enhancing our ability to predict crop productivity and understand agroecosystem carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Status of the Jefferson Lab Eta Factory (JEF) experiment

The Jefferson Lab Eta Factory (JEF) experiment is an experiment running in Hall D at Jefferson Lab that focuses on studying the decays of the ¿ meson. These decays provide a rich laboratory for searching for new charge conjugation violating / parity conserving (CVPC) processes, looking for hints of Beyond Standard Model physics, and probing higher order terms in Chiral Perturbation Theory. The flagship channel is the rare decay ¿ ¿ p0¿¿, the measurement of which required an upgrade to the existing equipment in Hall D. The experiment uses the GlueX detector, a fixed-target large acceptance spectrometer based on a solenoid magnet containing drift chambers for tracking charged particles and a lead-scintillator barrel calorimeter in the central region and an array of 4 × 4 × 45 cm3 lead glass blocks in the forward region for detecting neutral particles. During the last two years the inner 80×80 cm2 region of the forward calorimeter has been replaced by an array of 2 × 2 × 20 cm3 lead tungstate crystals, which provide factors of two improvement in energy and position resolution. The first round of data taking with this configuration took place this year. A first look at the data will be presented.

Taylor, Simon [Thomas Jefferson National Accelerat↗

DOE OSTI2026

Synthesis of ARM User Facility Surface Rainfall Datasets to Construct a Best Estimate Value Added Product (PrecipBE)

Surface precipitation measurements are essential for Earth system model (ESM) evaluation and understanding cloud processes. An ever-growing need for robust, temporally evolving, and easy-to-use statistical datasets provides motivation for a baseline ground-based precipitation properties data product. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility operates an extensive suite of precipitation instruments with various sensitivities and operating mechanisms, which render the decision of which instrument to use based on one or more fixed thresholds challenging and prone to errors and bias. Using a long-term instrument inter-comparison from a unique per-precipitation event perspective, rather than instantaneous sample comparison, we demonstrate that ARM rainfall-measuring instruments are generally consistent with each other at the statistical level. Inter-instrument deviations at the single event level can be large, especially for specific rainfall event properties such as maximum precipitation rates. A machine-learning (ML) analysis using a random forest regressor indicates that in some cases, depending on instrument, local site climatology, and/or specific deployment configuration, certain atmospheric state variables influence the measured quantities in an unpredictable manner. Thus, a-priori weighting of different instruments does not necessarily lead to more accurate and less biased synthesis of instrument data. These results motivate the design of the ARM precipitation best-estimate (PrecipBE) value-added product, which incorporates all valid precipitation data while considering data quality and other instrument limitations. PrecipBE consists of time series and tabular statistics datasets in an easy-to-use and insightful per-precipitation event format. It provides a large set of precipitation event properties supplemented with ancillary data from ARM datasets that correspond to the detected precipitation events. We describe the PrecipBE algorithm and demonstrate its use via the examination of a single-day output as well as a long-term trend analysis of precipitation events at the ARM Southern Great Plains (SGP) site, covering more than 30 years of data. The trend analysis tentatively suggests a long-term temporal tendency for mainly shorter and less intense precipitation events at the SGP site, but a long-term increase in annual rainfall by more than 36 mm (5 %) per decade. This rainfall trend is catalyzed primarily by more extreme event properties of relatively rare, intense precipitation events, with event total and 1 min maximum precipitation rate at a 1 year timeframe increasing up to 5 mm and 9 mm h −1 (several percent) per decade, respectively. While the currently available PrecipBE datasets (at https://adc.arm.gov/discovery/, last access: 8 December 2025) cover rainfall from multiple ARM deployments up to March 2025, PrecipBE is planned to be expanded to include solid-phase precipitation and will soon become an operational product with a several-day lag from real-time. We invite the ARM user community to leverage this new product and welcome user feedback to further enhance the dataset.

Silber, Israel [Pacific Northwest National Laborat↗

NASA NTRS1976

Hydrogen use projections and supply options

Two projections of future hydrogen demand, based on the Ford technical fix and the Westinghouse nuclear electric economy energy supply and demand scenarios, are analyzed. It is suggested that hydrogen use will increase during the remainder of this century by at least a factor of five, and perhaps by a factor of twenty. Primary energy sources for producing hydrogen are discussed in terms of the transition from low to high demand for hydrogen.

Manvi, R.↗

NASA NTRS1977

Remote-area health care delivery through space technology - STARPAHC

A joint NASA/HEW project called Space Technology Applied to Rural Papage Advanced Health Care (STARPAHC) has been developed to deliver quality health care to inhabitants of remote geographical areas. The system consists of a hospital-based support control center, a fixed clinic, a mobile clinic, and a referral center with access to specialists via television links to the control center. A strategically located relay station routes television, voice, and data transmissions between system elements. A model system has been installed on the Papage Indian Reservation in Arizona, and is undergoing a 2-year evaluation. The system has been shown to be both effective and cost-efficient, and applications of the concept are planned for future manned spacecraft flights.

Belasco, N.↗

NASA NTRS1984

Structure of particle-laden jets - Measurements and predictions

Measurements of mean and fluctuating velocities of both phases as well as particle mass fluxes were completed in turbulent, particle-laden jets containing monodisperse particles with well-defined initial and boundary conditions. The new measurements were used to evaluate a stochastic separated flow model of the process which treated effects of interphase slip and turbulent dispersion using random-walk computations for particle motion. The continuous phase was treated using a modified k-epsilon model allowing for direct contributions of interphase transport to both mean and turbulence properties. The model performed reasonably well over the new data base, with all empirical parameters fixed from earlier work. In contrast, simplified models ignoring either interphase slip or turbulent dispersion yielded poor agreement with the measurements.

Shuen, J.-S.↗

NASA NTRS1986

Local flow management/profile descent algorithm. Fuel-efficient, time-controlled profiles for the NASA TSRV airplane

The Local Flow Management/Profile Descent (LFM/PD) algorithm designed for the NASA Transport System Research Vehicle program is described. The algorithm provides fuel-efficient altitude and airspeed profiles consistent with ATC restrictions in a time-based metering environment over a fixed ground track. The model design constraints include accommodation of both published profile descent procedures and unpublished profile descents, incorporation of fuel efficiency as a flight profile criterion, operation within the performance capabilities of the Boeing 737-100 airplane with JT8D-7 engines, and conformity to standard air traffic navigation and control procedures. Holding and path stretching capabilities are included for long delay situations.

Groce, J. L.↗

NASA NTRS1988

Research on output feedback control

A summary is presented of the main results obtained during the course of research on output feedback control. The term output feedback is used to denote a controller design approach which does not rely on an observer to estimate the states of the system. Thus, the order of the controller is fixed, and can even be zero order, which amounts to constant gain ouput feedback. The emphasis has been on optimal output feedback. That is, a fixed order controller is designed based on minimizing a suitably chosen quadratic performance index. A number of problem areas that arise in this context have been addressed. These include developing suitable methods for selecting an index of performance, both time domain and frequency domain methods for achieving robustness of the closed loop system, developing canonical forms to achieve a minimal parameterization for the controller, two time scale design formulations for ill-conditioned systems, and the development of convergent numerical algorithms for solving the output feedback problem.

Calise, Anthony J.↗

NASA NTRS1989

Effects of cumulus entrainment and multiple cloud types on a January global climate model simulation

An improved version of the GISS Model II cumulus parameterization designed for long-term climate integrations is used to study the effects of entrainment and multiple cloud types on the January climate simulation. Instead of prescribing convective mass as a fixed fraction of the cloud base grid-box mass, it is calculated based on the closure assumption that the cumulus convection restores the atmosphere to a neutral moist convective state at cloud base. This change alone significantly improves the distribution of precipitation, convective mass exchanges, and frequencies in the January climate. The vertical structure of the tropical atmosphere exhibits quasi-equilibrium behavior when this closure is used, even though there is no explicit constraint applied above cloud base.

Yao, Mao-Sung↗

NASA NTRS1992

Future benefits and applications of intelligent on-board processing to VSAT services

The trends and roles of VSAT services in the year 2010 time frame are examined based on an overall network and service model for that period. An estimate of the VSAT traffic is then made and the service and general network requirements are identified. In order to accommodate these traffic needs, four satellite VSAT architectures based on the use of fixed or scanning multibeam antennas in conjunction with IF switching or onboard regeneration and baseband processing are suggested. The performance of each of these architectures is assessed and the key enabling technologies are identified.

Price, Kent M.↗

NASA NTRS1992

Technology requirements for mesh VSAT applications

This paper first examines the trends and the roles of VSAT services in the year 2010 time frame based on an overall network and service model for that period. An estimate of the VSAT traffic is then made and the service and general network requirements are identified. In order to accommodate these traffic needs, four satellite VSAT architectures based on the use of fixed or scanning multibeam antennas in conjunction with IF switching or onboard regeneration and baseband processing are suggested. The performance of each of these architectures is assessed and the key enabling technologies are identified.

Kwan, R. K.↗

NASA NTRS1992

Bayesian classification of polarimetric SAR images using adaptive a priori probabilities

The problem of classifying earth terrain by observed polarimetric scattering properties is tackled with an iterative Bayesian scheme using a priori probabilities adaptively. The first classification is based on the use of fixed and not necessarily equal a priori probabilities, and successive iterations change the a priori probabilities adaptively. The approach is applied to an SAR image in which a single water body covers 10 percent of the image area. The classification accuracy for ocean, urban, vegetated, and total area increase, and the percentage of reclassified pixels decreases greatly as the iteration number increases. The iterative scheme is found to improve the a posteriori classification accuracy of maximum likelihood classifiers by iteratively using the local homogeneity in polarimetric SAR images. A few iterations can improve the classification accuracy significantly without sacrificing key high-frequency detail or edges in the image.

Van Zyl, J. J.↗

NASA NTRS1992

ROM/RMF control of the flexible, articulated-truss space crane

The large size and extreme flexibility of an articulated space crane entail great difficulties in precision positioning. Control strategies for the flexible multibody system are here developed using a Timoshenko-beam finite-element model (FEM) which captures the system's low frequency characteristics. From the FEM, a reduced-order model (ROM) controller is designed which rotates the fixed shape crane about the base alpha joint to actuate positioning control. Eigenvalue analysis of the closed-loop system shows the destabilizing effect of controller-structure interaction (CSI). Making use of a parallel bank of residual mode filters (RMFs) compensated for CSI, restoring system stability and performance. The linear control law is simulated in closed-loop with the beam model. The ROM-based control law with RMF compensation is an effective, low-order controller.

Reisenauer, Brian T.↗

NASA NTRS1991

Space Shuttle processing - A case study in artificial intelligence

A scheduling system incorporating AI is described and applied to the automated processing of the Space Shuttle. The unique problem of addressing the temporal, resource, and orbiter-configuration requirements of shuttle processing is described with comparisons to traditional project management for manufacturing processes. The present scheduling system is developed to handle the late inputs and complex programs that characterize shuttle processing by incorporating fixed preemptive scheduling, constraint-based simulated annealing, and the characteristics of an 'anytime' algorithm. The Space-Shuttle processing environment is modeled with 500 activities broken down into 4000 subtasks and with 1600 temporal constraints, 8000 resource constraints, and 3900 state requirements. The algorithm is shown to scale to very large problems and maintain anytime characteristics suggesting that an automated scheduling process is achievable and potentially cost-effective.

Mollikarimi, Cindy↗

NASA NTRS1992

Constant-Frequency Pulsed Phase-Locked-Loop Measuring Device

Constant-frequency pulsed phase-locked-loop measuring device is sensitive to small changes in phase velocity and easily automated. Based on use of fixed-frequency oscillator in measuring small changes in ultrasonic phase velocity when sample exposed to such changes in environment as changes in pressure and temperature. Automatically balances electrical phase shifts against acoustical phase shifts to obtain accurate measurements of acoustical phase shifts.

Yost, William T.↗

NASA NTRS1993

Dynamically reconfigurable optical morphological processor and its applications

An innovative optically implemented morphological processor is introduced. With the use of a large space-bandwidth-product Dammann grating and a high-speed shutter spatial light modulator, effective structuring element with large size and arbitrary shape can be constructed with dynamic reconfigurability. This reconfigurability is a major improvement over the conventional correlator-based morphological processor in which fixed holographic filters are used as structuring elements (Casasent and Botha, 1988). A novel two-dimensional thresholding photodetector array, capable of performing parallel thresholding and feedback, is utilized in this system and makes possible the implementation of many complex morphological operations requiring iterative feedbacks and full programmability. The optical architecture and the principle of operation are presented. Experimental demonstration of binary image morphological erosion, dilation, opening, and closing are also demonstrated. A technique for extending this technique to gray-scale image using thresholding decomposition technique is also discussed.

Chao, Tien-Hsin↗

NASA NTRS1994

A Planar Approximation for the Least Reliable Bit Log-likelihood Ratio of 8-PSK Modulation

The optimum decoding of component codes in block coded modulation (BCM) schemes requires the use of the log-likelihood ratio (LLR) as the signal metric. An approximation to the LLR for the least reliable bit (LRB) in an 8-PSK modulation based on planar equations with fixed point arithmetic is developed that is both accurate and easily realizable for practical BCM schemes. Through an error power analysis and an example simulation it is shown that the approximation results in 0.06 dB in degradation over the exact expression at an E(sub s)/N(sub o) of 10 dB. It is also shown that the approximation can be realized in combinatorial logic using roughly 7300 transistors. This compares favorably to a look up table approach in typical systems.

Thesling, William H.↗

NASA NTRS2002

The GEOS Retrospective Data Assimilation System: The 6-hour lag case

The fixed-lag Kalman smoother (FLKS) has been proposed as a framework to construct data assimilation procedures capable of producing high-quality climate research datasets. Fixed-lag Kalman smoother-based systems, referred to as retrospective data assimilation systems, are an extension to three-dimensional filtering procedures with the added capability of incorporating observations not only in the past and present time of the estimate, but also at future times. A variety of simplifications are necessary to render retrospective assimilation procedures practical. In this article, we present an FLKS-based retrospective data assimilation system implementation for the Goddard Earth Observing System (GOES) Data Assimilation System (DAS). The practicality of this implementation comes from the practicality of its underlying (filter) analysis system, i.e., the physical-space statistical analysis system (PSAS). The behavior of two schemes is studied here. The first retrospective analysis (RA) scheme is designed simply to update the regular PSAS analyses with observations available at times ahead of the regular analysis times. Although our GEOS DAS implementation is general, results are only presented for when observations 6-hours ahead of the analysis time are used to update the PSAS analyses and thereby to calculate the so-called lag-1 retrospective analyses. Consistency tests for this RA scheme show that the lag-1 retrospective analyses indeed have better 6-hour predictive skills than the predictions from the regular analyses. This motivates the introduction of the second retrospective analysis scheme which, at each analysis time, uses the 6-hour retrospective analysis to replace the first-guess normally used in the PSAS analysis, and therefore allows the calculation of a revised (filter) PSAS analysis. Since in this scheme the lag-1 retrospective analyses influence the filter results, this procedure is referred to as the retrospective-based iterative analysis (RIA) scheme. Results from the RIA scheme indicate its potential for improving the overall quality of the assimilation.

Zhu, Yan-Qiu↗