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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A ModEx Framework for Watershed Subsurface Investigation With Limited Geophysical Data Using Machine Learning and Hydrologic Modeling

Abstract Subsurface heterogeneity influences watershed hydrology strongly but remains difficult to characterize at catchment scales with sparse and costly field data. Geophysical surveys such as electromagnetic induction (EMI) provide local spatial subsurface images yet scaling them to watershed scales and converting EMI‐derived resistivity into hydraulic properties remains a challenge. We present a Model–Experiment (ModEx) framework that integrates limited EMI data with machine learning (ML) and hydrologic modeling to improve process representation and guide field investigations. Sparse EMI surveys were scaled to the catchment scale using a Random Forest model, and the resulting resistivity fields were combined with nearby borehole constraints to parameterize a hydrologic model. The EMI‐informed hydrological simulations improved predictions of streamflow sustained by subsurface flow and shallow saturation patterns. By combining EMI data and ML with hydrologic modeling, the ModEx framework guides future subsurface surveys, providing a transferable and efficient strategy for data–model integration across diverse watersheds. Plain Language Summary Mapping the underground network of soil and rock that controls water is essential for predicting floods and droughts, but seeing underground is difficult and expensive. We cannot drill everywhere, so scientists use geophysical tools to scan broad areas. There are two key challenges: these geophysical scans are often sparse across the whole watershed, and the geophysical data is hard to translate into water‐related properties. We used artificial intelligence to solve these problems. We taught a computer to find patterns linking the limited geophysical data to the land surface properties. This allowed it to fill in the gaps and create a complete, useful subsurface map for the entire watershed. This new map improves hydrologic simulations, leading to more accurate predictions of water movement in the watershed. It also helps scientists build better models with less data and generates a priority map showing where to measure next, making future investigations more efficient. Key Points Limited EMI scaled with ML improves catchment‐scale subsurface parameterization for hydrologic models The framework integrates hydrologic modeling with limited geophysical data to support subsurface investigation design ModEx framework offers a transferable data–model integration strategy that quantifies and reduces uncertainty guiding watershed studies

Chen, Hang↗
DOE OSTI2025

Meso-scale modeling of UO2 nuclear fuel to high burnup

To improve the economics of light water reactors for commercial nuclear energy generation, utility operators are seeking to obtain regulatory approval to run UO2 fuel to higher levels of burnup. One potential impediment to obtaining this approval is the phenomenon of fuel fragmentation, relocation, and dispersal (FFRD). FFRD can result when fuel experiences a rapid temperature transient, such as that occurring during a Loss Of Coolant Accident (LOCA). FFRD has historically been most associated with the rim region in UO2 fuel pellets, where the phenomenon of fragmentation is also referred to as pulverization due to the small size of the fragments. More recent evidence suggests that the so-called “dark zone” (due to its appearance in micrographs) that can be observed in the mid-radial regions of high burnup fuel is also susceptible to FFRD. Although empirical fuel performance models have been developed that can adequately predict pulverization in the rim region under typical LWR conditions, a scientific understanding of what underlies fuel restructuring and subsequent FFRD is lacking even in the rim region, and no models are currently available for the behavior the dark zone. To address these challenges, the U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has employed a multi-scale modeling approach to improve scientific understanding and develop new fuel performance models. In this talk, I will focus on meso-scale efforts, which form a crucial link between atomic-scale and engineering-scale models. Phase-field modeling combined with cluster dynamics is used to predict the restructuring process in the rim region. Phase-field fracture modeling, informed by atomistic simulations, is used to predict the onset of pulverization in the rim region. Combining these techniques together allows the extent of rim pulverization to be predicted. The formation and evolution of the dark zone has also been simulated with the phase-field method, using an improved approach to vacancy source term parameterization. The work shows the important impact of microstructure on fuel performance.

fracture↗
NASA NTRS2002

Mystery of Foil Air Bearings for Oil-free Turbomachinery Unlocked: Load Capacity Rule-of-thumb Allows Simple Estimation of Performance

The Oil-Free Turbomachinery team at the NASA Glenn Research Center has unlocked one of the mysteries surrounding foil air bearing performance. Foil air bearings are self-acting hydrodynamic bearings that use ambient air, or any fluid, as their lubricant. In operation, the motion of the shaft's surface drags fluid into the bearing by viscous action, creating a pressurized lubricant film. This lubricating film separates the stationary foil bearing surface from the moving shaft and supports load. Foil bearings have been around for decades and are widely employed in the air cycle machines used for cabin pressurization and cooling aboard commercial jetliners. The Oil-Free Turbomachinery team is fostering the maturation of this technology for integration into advanced Oil-Free aircraft engines. Elimination of the engine oil system can significantly reduce weight and cost and could enable revolutionary new engine designs. Foil bearings, however, have complex elastic support structures (spring packs) that make the prediction of bearing performance, such as load capacity, difficult if not impossible. Researchers at Glenn recently found a link between foil bearing design and load capacity performance. The results have led to a simple rule-of-thumb that relates a bearing's size, speed, and design to its load capacity. Early simple designs (Generation I) had simple elastic (spring) support elements, and performance was limited. More advanced bearings (Generation III) with elastic supports, in which the stiffness is varied locally to optimize gas film pressures, exhibit load capacities that are more than double those of the best previous designs. This is shown graphically in the figure. These more advanced bearings have enabled industry to introduce commercial Oil-Free gas-turbine-based electrical generators and are allowing the aeropropulsion industry to incorporate the technology into aircraft engines. The rule-of-thumb enables engine and bearing designers to easily size and select bearing technology for a new application and determine the level of complexity required in the bearings. This new understanding enables industry to assess the feasibility of new engine designs and provides critical guidance toward the future development of Oil-Free turbomachinery propulsion systems.

DellaCorte, Christopher↗
NASA NTRS1998

Contributions of Nimbus 7 TOMS Data to Volcanic Study and Hazard Mitigation

Nimbus TOMS data have led to advancements among many volcano-related scientific disciplines, from the initial ability to quantify SO2 clouds leading to derivations of eruptive S budgets and fluxes, to tracking of individual clouds, assessing global volcanism and atmospheric impacts. Some of the major aspects of TOMS-related research, listed below, will be reviewed and updated: (1) Measurement of volcanic SO2 clouds: Nimbus TOMS observed over 100 individual SO2 clouds during its mission lifetime; large explosive eruptions are now routinely and reliably measured by satellite. (2) Eruption processes: quantification of SO2 emissions have allowed assessments of eruption sulfur budgets, the evaluation of "excess" sulfur, and inferences of H2S emissions. (3) Detection of ash: TOMS data are now used to detect volcanic particulates in the atmosphere, providing complementary analyses to infrared methods of detection. Paired TOMS and AVHRR studies have provided invaluable information on volcanic cloud compositions and processes. (4) Cloud tracking and hazard mitigation: volcanic clouds can be considered gigantic tracers in the atmosphere, and studies of the fates of these clouds have led to new knowledge of their physical and chemical dispersion in the atmosphere for predictive models. (5) Global trends: the long term data set has provided researchers an unparalleled record of explosive volcanism, and forms a key component in assessing annual to decadal trends in global S emissions. (6) Atmospheric impacts: TOMS data have been linked to independent records of atmospheric change, in order to compare cause and effect processes following a massive injection of SO2 into the atmosphere. (7) Future TOMS instruments and applications: Nimbus TOMS has given way to new satellite platforms, with several wavelength and resolution modifications. New efforts to launch a geostationary TOMS could provide unprecedented observations of volcanic activity.

Krueger, Arlin J.↗
DOE OSTI2025

Root genetics in the field to understand drought adaptation and carbon sequestration (Final Scientific/Technical Report)

For all crop plants, roots play a critical role in growth. Roots anchor the plants, and are the primary site of nutrient and water uptake. Roots are also the main source of C to soil in the form of root tissues and exudates, and thus greatly influence SOM stocks. To perform these functions, primary roots extend into soil, producing a network of branching roots of characteristic form, known as its root system architecture (RSA). RSA varies among species, and among varieties within a species that are adapted to different environments. Root traits are major targets for the second green revolution because of their potential to improve crop productivity, increase drought tolerance and nutrient acquisition, and increase C capture of soil. Improving the quality of roots in maize will be particularly valuable, since this crop is planted on over 92 million acres annually in the US. The future sustainability of agricultural systems relies on their ability to enhance soil organic matter (SOM) storage and reduce GHG emissions, while maintaining or enhancing productivity. This program had two components, Sensors and Models. For the first component, we designed and built a high-throughput phenotyping platform for root pulling of maize plants. This eliminated the physical labor of manually pulling up plants and reduced the number of personnel required down to one. The standardized pulling mechanism allowed recording force curves during the pulling process, providing additional information. We validated that the maximum force for pulling the root system was well-correlated with the root system mass and provided root crowns for further RSA analysis. These root crowns identified significant correlations with 2D root area and root depth, along with 3D root volume, total root length and number of root tips. We then used this system for field-based studies in maize on the genetics of root system architecture and its relation to nitrogen-use efficiency (NUE), including using lines relevant to the Corteva breeding program. Varieties were also evaluated at Corteva sites in the cornbelt and Danforth farm in Missouri, to establish responses across sites. From these studies we have identified genetic loci associated with root traits and created mutant lines for these loci and correlations of root traits with NUE. For the Models component, we worked to incorporate root and soil characteristics into the MEMS 2.0 soil and ecosystem biogeochemical model. Existing soil C models, such as Century, are unable to represent specific root trait interactions with the soil environment and therefore to accurately forecast the potential C sequestration benefits of root breeding under different climatic and soil type conditions. We have developed the MEMS 2.0 ecosystem biogeochemical model to improve quantification of farm-scale soil carbon and greenhouse gas emissions. The new knowledge and large datasets produced by this project will be used to develop and drive an innovative model capable of forecasting the impacts on soil C stocks and nutrient dynamics. An innovation was to use the empirical data from the field studies (in 1, above) to model genetic variation in nitrogen use efficiencies and soil C input. Our work demonstrated that maize root-derived C rapidly replaces existing soil C and after 3 years of continuous maize, up to 20% of soil organic C in the topsoil (0-15cm) and 3% in the subsoil (15-30cm) was contributed by maize. However, this contribution did not entirely represent a net increase. Root C contribution to soil was affected by maize genetics. We have analyzed soils derived from the CSU field trials for C and N stocks, in the different soil physical fractions represented by the MEMS model, using both physical fractionation with elemental analyses, and Fourier transformed infrared spectroscopy. Data will be used to link crop nitrogen use efficiencies with soil C sequestration and provide data to bridge the field trials with the model development, for verification of model predictions. The project had a number of successful outcomes: we have used the new phenotyping platform to identify new genetic loci that can enhance root phenotypes; we have partnered with multiple maize seed companies phenotype varieties in their breeding programs; we have developed the MEMS model that can help inform industry on the potential for carbon sequestration in the agricultural sector, and which is now available at the CSU Soil Carbon Solutions Center for use.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Image-based time series analysis to establish differential disease progression for two Fusarium head blight pathogens in oat spikelets with variable resistance

Oat-based value-added products have increased their value as healthy foodstuff. Fusarium head blight (FHB) infections and the mycotoxins accumulated to the oat seeds, however, pose a challenge to oat production. The FHB infections are predicted to become more prevalent in the future changing climates and under more limited use of fungicides. Both these factors increase the pressure for breeding new resistant cultivars. Until now, however, genetic links in oats against FHB infection have been difficult to identify. Therefore, there is a great need for more effective breeding efforts, including improved phenotyping methods allowing time series analysis and the identification of molecular markers during disease progression. To these ends, dissected spikelets of several oat genotypes with different resistance profiles were studied by image-based methods during disease progression by Fusarium culmorum or F. langsethiae species. The chlorophyll fluorescence of each pixel in the spikelets was recorded after inoculation by the two Fusarium spp., and the progression of the infections was analyzed by calculating the mean maximum quantum yield of PSII (F v /F m ) values for each spikelet. The recorded values were (i) the change in the photosynthetically active area of the spikelet as percentage of its initial size, and (ii) the mean of F v /F m values of all fluorescent pixels per spikelet post inoculation, both indicative of the progression of the FHB disease. The disease progression was successfully monitored, and different stages of the infection could be defined along the time series. The data also confirmed the differential rate of disease progression by the two FHB causal agents. In addition, oat varieties with variable responses to the infections were indicated.

oats↗
NASA NTRS1994

Topography and tectonics of the central New Madrid seismic zone: Results of numerical experiements using a three-dimensional boundary element program

We present results of a series of numerical experiments designed to test hypothetical mechanisms that derive deformation in the New Madrid seismic zone. Experiments are constrained by subtle topography and the distribution of seismicity in the region. We use a new boundary element algorithm that permits calcuation of the three-dimensional deformation field. Surface displacement fields are calculated for the New Madrid zone under both far-field (plate tectonics scale) and locally derived driving strains. Results demonstrate that surface displacement fields cannot distinguish between either a far-field simple or pure shear strain field or one that involves a deep shear zone beneath the upper crustal faults. Thus, neither geomorphic nor geodetic studies alone are expected to reveal the ultimate driving mechanism behind the present-day deformation. We have also tested hypotheses about strain accommodation within the New Madrid contractional step-over by including linking faults, two southwest dipping and one vertical, recently inferred from microearthquake data. Only those models with step-over faults are able to predict the observed topography. Surface displacement fields for long-term, relaxed deformation predict the distribution of uplift and subsidence in the contractional step-over remarkably well. Generation of these displacement fields appear to require slip on both the two northeast trending vertical faults and the two dipping faults in the step-over region, with very minor displacements occurring during the interseismic period when the northeast trending vertical faults are locked. These models suggest that the gently dippling central step-over fault is a reverse fault and that the steeper fault, extending to the southeast of the step-over, acts as a normal fault over the long term.

Gomberg, Joan↗
NASA NTRS2012

GPM Mission Overview and U.S. Science Status

The Global Precipitation Measurement (GPM) Mission is an international satellite mission to unify and advance precipitation measurements from a constellation of research and operational sensors to provide "next-generation" precipitation products [1-2]. Water is fundamental to life on Earth. Knowing where and how much rain and snow falls globally is vital to understanding how weather and climate impact both our environment and Earth's water and energy cycles, including effects on agriculture, fresh water availability, and responses to natural disasters. Since rainfall and snowfall vary greatly from place to place and over time, satellites can provide more uniform observations of rain and snow around the globe than ground instruments, especially in areas where surface measurements are difficult. Relative to current global rainfall products, GPM data products will be characterized by: (l) more accurate instantaneous precipitation measurements (especially for light rain and cold-season solid precipitation), (2) more frequent sampling by an expanded constellation of domestic and international microwave radiometers including operational humidity sounders, (3) intercalibrated microwave brightness temperatures from constellation radiometers within a unified framework, and (4) physical-based precipitation retrievals from constellation radiometers using a common a priori cloud/hydrometeor database derived from GPM Core sensor measurements. The cornerstone of the GPM mission is the deployment of a Core Observatory in a unique 65 non-Sun-synchronous orbit to serve as a physics observatory and a reference standard to unify precipitation measurements by a constellation of dedicated and operational passive microwave sensors. The design of the GPM Core Observatory is an advancement of the Tropical Rainfall Measuring Mission (TRMM)'s highly successful rain-sensing package. The Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a multichannel (l0-183 GHz) GPM Microwave Radiometer (GMI). Since light rain and falling snow account for a significant fraction of precipitation occurrence in middle and high latitudes, the GPM instruments extend the capabilities of the TRMM sensors to detect falling snow, measure light rain, and provide, for the first time, quantitative estimates of microphysical properties of precipitation particles. The combined use of DPR and GMI measurements will place greater constraints on possible solutions to radiometer retrievals to improve the accuracy and consistency of precipitation retrievals from all constellation radiometers. The GMI uses 13 different microwave channels to observe energy from the different types of precipitation through clouds for estimating everything from heavy to light rain and for detecting falling snow. As the satellite passes over Earth, the GMI constantly scans a region 885 kilometers across. The Ball Aerospace and Technology Corporation built the GMI under contract with NASA Goddard Space Flight Center. The DPR provides three-dimensional information about precipitation particles derived from reflected energy by these particles at different heights within the cloud system. The two frequencies of the DPR also allow the radar to infer the sizes of precipitation particles and offer insights into a storm's physical characteristics. The Ka-band frequen~y scans across a region of 125 kilometers and is nested within the wider scan of the Ku-band frequency of 245 kilometers. The Japan Aerospace and Exploration Agency (JAXA) and Japan's National Institute of Information and Communications Technology (NICT) built the DPR. The Core Observatory satellite will fly at an altitude of 253 miles (407 kilometers) in a non-Sun-synchronous orbit that covers the Earth from 65 S to 65 N - from about the Antarctic Circle to the Arctic Circle. The GPM Core Observatory is being developed and tested at NASA Goddard Space Flight Center. Once complete, a Japanese H-lIA rocket will carry thPM Core Observatory into orbit from Tanegashima Island, Japan in 2014. The GPM constellation is envisioned to comprise 8 or more microwave sensors provided by partners, including both conical imagers and cross-track sounders. GPM is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA). Additional partnerships are under development to include microwave radiometers on the French-Indian Megha-Tropiques satellite and U.S. Defense Meteorological Satellite Program (DMSP) satellites, as well as humidity sounders or precipitation sensors on operational satellites such as the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), NOAA-NASA Joint Polar Satellite System (JPSS) satellites, European MetOp satellites, and DMSP follow-on sensors. In addition, data from Chinese and Russian microwave radiometers may be available through international cooperation under the auspices of the Committee on Earth Observation Satellites (CEOS) and Group on Earth Observations (GEO). GPM's next-generation global precipitation data will lead to scientific advances and societal benefits in the following areas: (1) Improved knowledge of the Earth's water cycle and its link to climate change (2) New insights into precipitation microphysics, storm structures and large-scale atmospheric processes (3) Better understanding of climate sensitivity and feedback processes (4) Extended capabilities in monitoring and predicting hurricanes and other extreme weather events (5) Improved forecasting capabilities for natural hazards, including floods, droughts and landslides. (6) Enhanced numerical prediction skills for weather and climate (7) Better agricultural crop forecasting and monitoring of freshwater resources. An overview of the GPM mission concept and science activities in the United States, together with an update on international collaborations in radiometer intercalibration and ground validation, will be presented.

Hou, Arthur Y.↗
DOE OSTI2022

Evaluated 238 U(n,f) Average Prompt Fission Neutron Multiplicities Including the CGMF Model

This report documents an evaluation of the average prompt fission neutron multiplicity, $\overline{v}_p$, of 238 U from 800 keV to MeV. This evaluation had to be re-done from “scratch” as the input to previous $\overline{v}_p$ evaluations, specifically ENDF/B-VIII.0, was not found. That means that all available experimental data were re-analyzed and uncertainties were re-estimated. The new evaluated 238 U $\overline{v}_p$ based on only experimental data differs distinctly from ENDF/B-VIII.0 $\overline{v}_p$ from 2 to 4.5 MeV, and from 6 to 7 MeV, and is otherwise similar. The difference from 2 to 4.5 MeV stems from the fact that ENDF/B-VIII.0 was tweaked in this energy range to data of Frehaut, while two other, equally trustworthy, data sets would indicate an evaluated 238 U $\overline{v}_p$ that is up to 2% higher. Also, second chance fission in ENDF/B-VIII.0 was smoothed over from 6–7 MeV. Another major difference to ENDF/B-VIII.0 is that one of the evaluations presented here includes model information from the Hauser-Feshbach fission fragment decay code CGMF, while ENDF/B-VIII.0 is based purely on experimental data. CGMF links several fission quantities with each other; $\overline{v}_p$ is predicted by assumptions made on, e.g., pre-neutron emission yields as a function of mass, the total kinetic energy, or spin and parity of fission fragments. This allows to validate the new 238 U $\overline{v}_p$ by using CGMF parameters obtained from fitting to experimental 238 U $\overline{v}_p$ to predict yields as a function of mass, the average total kinetic energy, or the mean energy of the prompt fission neutron spectrum. These model-predicted values can then be compared to experimental and evaluated data. The model-predicted fission-observable values using evaluated parameters obtained here are reasonably close to experimental data for some observables, but are farther away from experimental data related to TKE observables. In addition to that, the evaluated 238 U(n,f) $\overline{v}_p$ shows similar deviations from ENDF/B-VIII.0 as for the evaluation with only experimental data. This difference is expected to lead to changes in simulated effective neutron multiplication factor, $k_{eff}$ of ICSBEP critical assemblies that are sensitive to 238 U in the fast range (BigTen, Flattop, Flattop-Pu). These changes in $k_{eff}$ need to be counter-balanced. Chi-Nu PFNS experimental data are expected to be released in the next few months that might lead to the needed changes in the PFNS. Until then, we hold off in benchmarking the new 238 U(n,f) $\overline{v}_p$ as well as submitting it to ENDF/B-VIII.1. Also, new high-precision 238 U $\overline{v}_p$ are expected to be measured by the CEA in the next two years that will shed further light on question on 238 U $\overline{v}_p$ from 2–4.5 and 6–7 MeV.

238U↗
NASA NTRS2009

Data-Link and Surface Map Traffic Intent Displays for NextGen 4DT and Equivalent Visual Surface Operations

By 2025, U.S. air traffic is predicted to increase 3-fold and may strain the current air traffic management system, which may not be able to accommodate this growth. In response to this challenge, a consortium of industry, academia and government agencies have proposed a revolutionary new concept for U.S. aviation operations, termed the Next Generation Air Transportation System or "NextGen". Many key capabilities are being identified to enable NextGen, including the concept of "net-centric" operations whereby each aircraft and air services provider shares information to allow real-time adaptability to ever-changing factors such as weather, traffic, flight trajectories, and security. Data-link is likely to be the primary source of communication in NextGen. Because NextGen represents a radically different approach to air traffic management and requires a dramatic shift in the tasks, roles, and responsibilities for the flight deck, there are numerous research issues and challenges that must be overcome to ensure a safe, sustainable air transportation system. Flight deck display and crew-vehicle interaction concepts are being developed that proactively investigate and overcome potential technology and safety barriers that might otherwise constrain the full realization of NextGen.

Shelton, Kevin J.↗
DOE OSTI2023

Rapid Computational Identification of Therapeutic Targets for Pathogens

Biological threats continue to persist and evolve as an important challenge to national security. There are multiple ways in which novel viral pathogens could emerge to pose a serious threat to human health. This project developed a pathogen target identification tool that can rapidly respond to a novel or emerging viral biological threat. A set of computational tools were developed that provide detailed information on the newly sequenced genes, their protein products and the drug target sites for the proteins that are best suited for biological countermeasure development. Three key innovations were developed in the project. 1) Development of a new extensive database of protein pocket structures with structure-based search algorithms to rapidly link novel protein targets with the complete collection of previously experimentally solved protein structures. 2) A novel clustering pipeline was introduced to group matching structures and associated small-molecule binding ligands into a consensus protein pocket with the associated small-molecule chemotypes predicted to fit in the pocket site. The matching experimentally solved structures were used to inform the value of different target sites. 3) Where there are viral protein targets with pockets structurally matched to similar human proteins, a biological knowledge graph, which links molecular interactions with human disease, was used to further assess the potential negative impact of a viral protein target with similarities to human proteins that could have important off target side effects. In total, the project produced a new resource for rapid and detailed assessment of promising targets for countermeasures, reflecting the ongoing wet lab, clinical, and computational data being collected. These capabilities will improve the ability to respond to a biological threat in multiple domains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Elevated nocturnal respiratory rates in the mitochondria of CAM plants: current knowledge and unanswered questions

Abstract Crassulacean acid metabolism (CAM) is a metabolic adaptation that has evolved convergently in 38 plant families to aid survival in water-limited niches. Whilst primarily considered a photosynthetic adaptation, CAM also has substantial consequences for nocturnal respiratory metabolism. Here, we outline the history, current state and future of nocturnal respiration research in CAM plants, with a particular focus on the energetics of nocturnal respiratory oxygen consumption. Throughout the 20th century, research interest in nocturnal respiration occurred alongside initial discoveries of CAM, although the energetic and mechanistic implications of nocturnal oxygen consumption and links to the operation of the CAM cycle were not fully understood. Recent flux balance analysis (FBA) models have provided new insights into the role that mitochondria play in the CAM cycle. Several FBA models have predicted that CAM requires elevated nocturnal respiratory rates, compared to C3 species, to power vacuolar malic acid accumulation. We provide physiological data, from the genus Clusia, to corroborate these modelling predictions, thereby reinforcing the importance of elevated nocturnal respiratory rates for CAM. Finally, we outline five unanswered questions pertaining to nocturnal respiration which must be addressed if we are to fully understand and utilize CAM plants in a hotter, drier world.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1990

Optimum structural design of robotic manipulators with fiber reinforced composite materials

High-speed robotic arms with advanced structural characteristics can be fabricated from optimally tailored fiber reinforced composites. An integrated design methodology is presented for the optimal structural synthesis of composite robotic manipulators. Optimum configurations of ply angles and ply thicknesses are predicted for maximum structural end-effector stiffness and maximum end-effector load carrying capacity, without altering the geometric dimensions of the links. Multiple posture finite element-based static performance criteria are implemented. A new finite element has been developed for the modeling of tubular composite links. Unique features are the inclusion of shear effects and coupling between stretching and flexure. Numerical solutions are obtained via an efficient optimization algorithm. Applications to an existing SCARA-class manipulator illustrate the effectiveness of the method and demonstrate the dramatic influence of the multi-postural design criteria on the optimal design. For a filament wound structure using a high strength carbon fiber in a thermoplastic matrix, the resultant optimum ply configurations have increased the specific stiffness and specific load capacity by factors of 1.5 and 16, respectively, in comparison to identically sized aluminum links.

Saravanos, D. A.↗
NASA NTRS2001

Spectroscopic diagnostics of organic chemistry in the protostellar environment

A combination of astronomical observations, laboratory studies, and theoretical modelling is necessary to determine the organic chemistry of dense molecular clouds. We present spectroscopic evidence for the composition and evolution of organic molecules in protostellar environments. The principal reaction pathways to complex molecule formation by catalysis on dust grains and by reactions in the interstellar gas are described. Protostellar cores, where warming of dust has induced evaporation of icy grain mantles, are excellent sites in which to study the interaction between gas phase and grain-surface chemistries. We investigate the link between organics that are observed as direct products of grain surface reactions and those which are formed by secondary gas phase reactions of evaporated surface products. Theory predicts observable correlations between specific interstellar molecules, and also which new organics are viable for detection. We discuss recent infrared observations obtained with the Infrared Space Observatory, laboratory studies of organic molecules, theories of molecule formation, and summarise recent radioastronomical searches for various complex molecules such as ethers, azaheterocyclic compounds, and amino acids.

Ethers/analysis/chemical synthesis/chemistry↗
DOE OSTI2021

Impact of Precipitation Parameters on the Specific Surface Area of PuO 2

Controlling the properties of PuO 2 through processing is of vital importance to environmental transport and fate, production of nuclear fuels, nuclear forensic analyses, stockpile stewardship, and storage of nuclear wastes applications. A number of processing conditions have been identified to control final product properties, including specific surface area (SSA), residual carbon content, adsorption of volatile species, morphology, and particle size. In this paper, a novel approach is developed for the prediction of PuO 2 SSA via the synthetic route of Pu(IV) oxalate precipitation followed by calcination. The proposed model utilizes multivariate regression methodology and leave one out formalism to link Savannah River Site (SRS) precipitation and calcination production data to the SSA of the final product. A comparison among the models provides insight into the accuracy and ability to identify variations amongst the processing data. Additionally, the models may also be used to fit new data outside of the parameters explored in a production facility. Finally, the trained model was compared to a similarly trained conventional model form to illustrate the influence of precipitation parameters on the prediction of the final SSA. The models presented here attempt to provide new methods for more accurate prediction of the PuO 2 product properties in a production scale environment for key environmental and nuclear applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS1993

General-Purpose Time-Accurate Adaptive-Grid Method

Adaptive-grid method provides for generation of time-accurate grids used to solve wide variety of problems numerically. Intended use in computation of compressible flows. Part of solution method including algebraic grid-movement scheme; algorithm solving, by use of explicit numerical-integration scheme, Euler equations of unsteady flow; and temporal coupling routine utilizing grid-prediction/correction method to link dynamic grid with Euler-equation-solving algorithm. Improves ability to adapt grid to multiple features of solution and involves use of coarse grid in prediction stage of temporal coupling reducing central-processing-unit cost of obtaining new grid.

Bockelie, Michael J.↗
NASA NTRS2008

A Semi-Empirical Model for Forecasting Relativistic Electrons at Geostationary Orbit

We developed a new prediction model for forecasting relativistic (>2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/Interplanetary Magnetic Field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is about 0.9. The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible. The correlation coefficient between predicted and actual electron fluxes is stable and incredibly high.

Lyatsky, Wladislaw↗