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At least 379 records · Page 21

Analysis of gas membrane ultra-high purification of small quantities of mono-isotopic silane

A small quantity of high-value, crude, mono-isotopic silane is a prospective gas for a small-scale, high-recovery, ultra-high membrane purification process. This is an unusual application of gas membrane separation for which we provide a comprehensive analysis of a simple purification model. The goal is to develop direct analytic expressions for estimating the feasibility and efficiency of the method, and guide process design; this is only possible for binary mixtures of silane in the dilute limit which is a somewhat realistic case. In addition, analytic solutions are invaluable to verify numerical solutions obtained from computer-aided methods. Hence, in this paper we provide new analytic solutions for the purification loops proposed. Among the common impurities in crude silane, methane poses a special membrane separation challenge since it is chemically similar to silane. Other potential problematic compounds are: ethylene, diborane and ethane (in this order). Nevertheless, we demonstrate, theoretically, that a carefully designed membrane system may be able to purify mono-isotopic, crude silane to electronics-grade level in a reasonable amount of time and expenses. We advocate a combination of membrane materials that preferentially reject heavy impurities based on mobility selectivity, and light impurities based on solubility selectivity. We provide estimates for the purification of significant contaminants of interest. In this study, we suggest cellulose acetate and polydimethylsiloxane as examples of membrane materials on the basis of limited permeability data found in the open literature. We provide estimates on the membrane area needed and priming volume of the cell enclosure for fabrication purposes when using the suggested membrane materials. These estimates are largely theoretical in view of the absence of reliable experimental data for the permeability of silane. And finally, future extension of this work to the non-dilute limit may apply to the recovery of silane from rejected streams of natural silicon semi-conductor processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of Gas Membrane Ultra-High Purification of Small Quantities of Mono-Isotopic Silane

A small quantity of high-value, crude, mono-isotopic silane is a prospective gas for a small-scale, high-recovery, ultra-high membrane purification process. This is an unusual application of gas membrane separation for which we provide a comprehensive analysis of a simple purification model. The goal is to develop direct analytic expressions for estimating the feasibility and efficiency of the method, and guide process design; this is only possible for binary mixtures of silane in the dilute limit which is a somewhat realistic case. Among the common impurities in crude silane, methane poses a special membrane separation challenge since it is chemically similar to silane. Other potential problematic surprises are: ethylene, diborane and ethane (in this order). Nevertheless, we demonstrate, theoretically, that a carefully designed membrane system may be able to purify mono-isotopic, crude silane to electronics-grade level in a reasonable amount of time and expenses. We advocate a combination of membrane materials that preferentially reject heavy impurities based on mobility selectivity, and light impurities based on solubility selectivity. We provide estimates for the purification of significant contaminants of interest. To improve the separation selectivity, it is advantageous to use a permeate chamber under vacuum, however this also requires greater control of in-leakage of impurities in the system. In this study, we suggest cellulose acetate and polydimethylsiloxane as examples of membrane materials on the basis of limited permeability data found in the open literature. We provide estimates on the membrane area needed and priming volume of the cell enclosure for fabrication purposes when using the suggested membrane materials. These estimates are largely theoretical in view of the absence of reliable experimental data for the permeability of silane. Last but not least, future extension of this work to the non-dilute limit may apply to the recovery of silane from rejected streams of natural silicon semi-conductor processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Acquisition and analysis of angle-beam wavefield data

Angle-beam ultrasonic testing is a common practical technique used for nondestructive evaluation to detect, locate, and characterize a variety of material defects and damage. Greater understanding of the both the incident wavefield produced by an angle-beam transducer and the subsequent scattering from a variety of defects and geometrical features is anticipated to increase the reliability of data interpretation. The focus of this paper is on acquiring and analyzing propagating waves from angle-beam transducers in simple, defect-free plates as a first step in the development of methods for flaw characterization. Unlike guided waves, which excite the plate throughout its thickness, angle-beam bulk waves bounce back and forth between the plate surfaces, resulting in the well-known multiple “skips” or “V-paths.” The experimental setup consists of a laser vibrometer mounted on an XYZ scanning stage, which is programmed to move point-to-point on a rectilinear grid to acquire waveform data. Although laser vibrometry is now routinely used to record guided waves for which the frequency content is below 1 MHz, it is more challenging to acquire higher frequency bulk waves in the 1–10 MHz range. Signals are recorded on the surface of an aluminum plate that were generated from a 5 MHz, 65° refracted angle, shear wave transducer-wedge combination. Data are analyzed directly in the x-t domain, via a slant stack Radon transform in the τ-p (offset time-slowness) domain, and via a 2-D Fourier transform in the ω-k domain, thereby enabling identification of specific arrivals and modes. Results compare well to those expected from a simple ray tracing analysis except for the unexpected presence of a strong Rayleigh wave.

42 ENGINEERING↗

Initial Characterization of the NREL Large-Amplitude Motion Platform

The Large Amplitude Motion Platform (LAMP) at NREL represents a significant advancement in the controlled testing of Wave Energy Converters (WECs) under laboratory conditions. Originally designed by E2M as a six-degree-of-freedom (DOF) Stewart platform for flight simulation, LAMP has been adapted by NREL to facilitate the mounting and evaluation of WECs. This adaptation enables dry testing of WECs using motion profiles similar to the ocean, facilitating the iterative design, testing, and validation of WEC performance prior to ocean deployments. This report presents the initial work completed to characterize LAMP, with particular emphasis on its stability and operational capabilities across various single and multi-degree-of-freedom (DOF) motion profiles. The report includes planned comparisons at three distinct mass payloads, aimed at assessing the platform's positional accuracy, frequency response, and endurance over extended runtime periods. These experimental tests are critical for establishing the platform's limitations and ensuring that the data generated during WEC validation is both accurate and reproducible. The outcomes of this study not only contribute to a deeper understanding of LAMP's capabilities but also lay the groundwork for future advancements in WEC testing methodologies. By providing robust and reliable performance data within a controlled laboratory setting, the findings are expected to significantly enhance the development and commercialization of marine energy technologies. This report presents the initial findings of the LAMP Characterization work and proposed steps to further understand and characterize LAMP. Data collected during this work can be found on MHKDR at: https://mhkdr.openei.org/submissions/602 Note that this report shares the measured/found instantaneous maximum operating range of LAMP. For most applications the maximum operating range cannot be used for system health and longevity. The operating range and capabilities of LAMP will be evaluated on a case-by-case basis, single-DOF position, velocity, and acceleration values presented in Table 4a-c, and Table 5 should be taken as instantaneous absolute maximum values. Future use of LAMP will likely be limited to smaller values.

16 TIDAL AND WAVE POWER↗

Data on photoneutron reactions from various experiments for {sup 133}Cs, {sup 138}Ba and {sup 209}Bi nuclei

Basic methods for determining cross sections for photoneutron partial reactions are examined. They are obtained directly in experiments with quasimonoeneregetic annihilation photons or from the cross section for the (γ, xn) = (γ, 1n) + 2(γ, 2n) + 3(γ, 3n) +... neutron-yield reaction in experiments with bremsstrahlung photons by introducing corrections based on statistical nuclear-reaction theory. The difference in the conditions of these experiments, which leads to discrepancies between their results because of sizable systematic errors, is analyzed. Physical criteria are used to study the reliability of data on the photodisintegration of {sup 133}Cs, {sup 138}Ba, and {sup 209}Bi nuclei. The cross sections for partial and total reactions satisfying the reliability criteria are evaluated within the experimental–theoretical method (σ{sup eval}(γ, in) = F{sub i}{sup theor} × σ{sup expt}(γ, xn)) on the basis of the experimental cross sections σ{sup expt}(γ, xn) and the results of the calculations within the combined model of photonuclear reactions.

74 ATOMIC AND MOLECULAR PHYSICS↗

Re-evaluation of Spent Nuclear Fuel Assay Data for the Three Mile Island Unit 1 Reactor and Application to Code Validation

Destructive radiochemical assay measurements of spent nuclear fuel rod segments from an assembly irradiated in the Three Mile Island unit 1 (TMI-1) pressurized water reactor have been performed at Oak Ridge National Laboratory (ORNL). Assay data are reported for five samples from two fuel rods of the same assembly. The TMI-1 assembly was a 15 X 15 design with an initial enrichment of 4.013 wt% 235 U, and the measured samples achieved burnups between 45.5 and 54.5 gigawatt days per metric ton of initial uranium (GWd/t). Measurements were performed mainly using inductively coupled plasma mass spectrometry after elemental separation via high performance liquid chromatography. High precision measurements were achieved using isotope dilution techniques for many of the lanthanides, uranium, and plutonium isotopes. Measurements are reported for more than 50 different isotopes and 16 elements. One of the two TMI-1 fuel rods measured in this work had been measured previously by Argonne National Laboratory (ANL), and these data have been widely used to support code and nuclear data validation. Recently, ORNL provided an important opportunity to independently cross check results against previous measurements performed at ANL. The measured nuclide concentrations are used to validate burnup calculations using the SCALE nuclear systems modeling and simulation code suite. These results show that the new measurements provide reliable benchmark data for computer code validation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Data Files for Runoff Evaluation in an Earth System Land Model for Permafrost Regions

Modeling of hydrological runoff is essential for accurately capturing spatiotemporal feedbacks within the land–atmosphere system, particularly in sensitive regions such as permafrost landscapes. However, substantial uncertainties persist in the terrestrial runoff parameterization schemes used in Earth system and land surface models. This is particularly true in permafrost regions, where landscape heterogeneity is high and reliable observational data are scarce.This data set includes all files that were produced and applied in the paper Runoff Evaluation in an Earth System Land Model for Permafrost Regions [Xiang et al. in review]. The paper is in review as of July 1 2025 in Geoscientific Model Development (GMD). In this study, we evaluate the performance of runoff parameterization schemes in the Energy Exascale Earth System Model (E3SM) land model (ELM). Our proposed framework leverages simulation results from the Advanced Terrestrial Simulator (ATS), which is a physics-rich integrated surface/subsurface hydrologic model that has been successfully evaluated previously in Arctic tundra regions. We used ATS to simulate runoff from 22 representative hillslopes in the Sagavanirktok River basin, located on the North Slope of Alaska, then compared the output with ELM’s parameterized representation of total runoff. This dataset contains 2 figure image files (*.png, *jpg) that describe the study site and methods, as well as folders (Figure*.zip) that contain the associated data files (*.csv, *.dat) and python code notebooks (*.ipynb) for figures 3-7 in the paper. Jupyter notebook (*.ipynb) files that produce the figure files using the associated data files will run within a python environment configured with Jupyter Lab or Notebook packages.

54 ENVIRONMENTAL SCIENCES↗

Experimental investigation and thermodynamic modeling of the binary Pt–Sn system

Here, the thermodynamics of the Pt–Sn system is revisited with attention to phase equilibria involving PtSn 4 , a topological quantum material with interesting physical properties. The phase relationship in the Sn-rich region of the Pt–Sn binary system was investigated by a combination of differential scanning calorimetry and equilibration experiments. Based on the present experiments and a critical evaluation of the available thermodynamic and phase diagram data reported in the literature, thermodynamic assessments of the entire Pt–Sn system were performed using the CALPHAD approach. Two sets of thermodynamic parameters were optimized, where the liquid phase was described using the Bragg-Williams random mixing model and the associate solution model, respectively. The modeling results are compared with the reliable experimental data and are shown to provide good representations of the phase equilibria and thermodynamic properties in this system.

36 MATERIALS SCIENCE↗

Cyber security best practices for the nuclear industry

When deploying software based systems, such as, digital instrumentation and controls for the nuclear industry, it is vital to include cyber security assessment as part of architecture and development process. When integrating and delivering software-intensive systems for the nuclear industry, engineering teams should make use of a secure, requirements driven, software development life cycle, ensuring security compliance and optimum return on investment. Reliability protections, data loss prevention, and privacy enforcement provide a strong case for installing strict cyber security policies. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Use of Covariances in a Consistent Data Assimilation for Improvement of Basic Nuclear Parameters in Nuclear Reactor Applications: From Meters to Femtometers

Recognition of the key role physics plays in innovative reactor design was already made clear by E. Wigner in his warning: “It has been a bit forgotten that in all really creative thinking in reactor design, a working knowledge of nuclear reaction theory is required.” More recently, extensive sensitivity and uncertainty studies and the availability of new covariance data have allowed preliminary quantification of the impact of current nuclear data uncertainties on the design parameters of the Generation-IV systems (both fast neutron and thermal neutron systems). Similar quantifications can be done for the parameters that characterize the associated innovative fuel cycle to insure sustainability, waste minimization and drastic reduction of the proliferation risks. In parallel, there has been a growing and very significant trend to develop a new generation of reactor simulation tools that rely more and more on first principles. It is safe to say that the next generation of innovative nuclear systems will be assessed with a completely new set of tools, more science based, in sharp contrast with what has been done in the past. However, the studies mentioned above point out that the present uncertainties in nuclear data should be significantly reduced in order to fully benefit from advances in modeling and simulation. Only a parallel effort in advanced simulation and nuclear data improvement will be able to provide designers with more general and well validated calculational tools to meet new design target accuracies. One further consideration related to the development of new advanced simulation tools is that there should be a more explicit link with the more fundamental physics parameters underlying the models used to describe cross sections that would avoid the use of processed, application-oriented, data (like multigroup cross sections). Finally, current methodologies for reducing uncertainties coming from nuclear data, which rely on the use of integral experiment information to perform statistical multigroup (i.e., energy spectrum weighted) cross section data assimilation should evolve to embrace new frontiers in advanced simulation. One of the drawbacks of the classical methodologies is related to the energy group structure and the type of neutron energy spectrum that are adopted in the assimilation (adjustment). In fact, after such an adjustment is performed, neutronic designers are then tied to this energy group structure and neutron energy spectrum when carrying out further calculations. In reality, this can be quite a limiting factor in view of the complex spectral issues that are involved in most reactor physics. This work combines novel, but proven, methodologies for overcoming these limitations. In fact, this is the first attempt to build up a link between the wealth of precise integral experiments and a basic theory of nuclear reactions. Essential ingredients of such a procedure, denominated here as assimilation, are covariances for model parameters and sensitivity matrices. The latter provide direct link between reaction theory and integral experiments. The result is a consistent data assimilation performed directly on the basic nuclear physics parameters that are being used in a variety of nuclear reaction mechanisms. The resulting improvement in their performance will consequently reduce related uncertainties when employed in reactor calculations. By using integral reactor physics experiments (meter scale), information is propagated back to the nuclear physics level (femtometers) covering a range of more than 13 orders of magnitude. The assimilation procedure should result in more accurate and more reliable evaluated data files of universal validity rather than tailored to a particular application. In fact, after data assimilation is carried out, the basic nuclear data file can be processed by a dedicated code into any energy group structure that the reactor physicist deems to be useful. On the other hand, integral experiments used in the assimilation should provide additional, possibly quite strict, constraints on the parameters entering nuclear reaction modeling, as well as the reaction models themselves. This report describes three years of combined research by Brookhaben National Lab (BNL) and Idaho National Lab (INL) on establishing viable assimilation methodology. The emphasis of this paper is on the empire code calculations to prepare the priors, sensitivity matrices and covariances for the model parameters. For completeness, we also include a short summary of the assimilation results produced by INL and reported earlier in annual reports [6], [7], [8].

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Communication: Electron ionization of DNA bases

No reliable experimental data exist for the partial and total electron ionization cross sections for DNA bases, which are very crucial for modeling radiation damage in genetic material of living cell. We have measured a complete set of absolute partial electron ionization cross sections up to 500 eV for DNA bases for the first time by using the relative flow technique. These partial cross sections are summed to obtain total ion cross sections for all the four bases and are compared with the existing theoretical calculations and the only set of measured absolute cross sections. Our measurements clearly resolve the existing discrepancy between the theoretical and experimental results, thereby providing for the first time reliable numbers for partial and total ion cross sections for these molecules. The results on fragmentation analysis of adenine supports the theory of its formation in space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine-Learning-Based Predictive Modeling of Glass Transition Temperatures: A Case of Polyhydroxyalkanoate Homopolymers and Copolymers

Polyhydroxyalkanoate-based polymers—being ecofriendly, biosynthesizable, and economically viable and possessing a broad range of tunable properties—are currently being actively pursued as promising alternatives for petroleum-based plastics. The vast chemical complexity accessible within this class of polymers gives rise to challenges in the rational discovery of novel polymer chemistries for specific applications. Here, the burgeoning field of polymer informatics addresses this challenge via providing tools and strategies for accelerated property prediction and materials design via surrogate machine-learning models built on reliable past data. In this contribution, we use glass transition temperature T g as an example target property to demonstrate promise of the data-enabled route to accelerated learning of accurate structure–property mappings in PHA-based polymers. Our analysis uses a data set of experimentally measured T g values, polymer molecular weights, and a polydispersity index for PHA-based homo- and copolymers that was carefully assembled from the literature. A fingerprinting scheme that captures key properties based on topology, shape, and charge/polarity of specific chemical units or motifs forming the polymer backbone was devised to numerically represent the polymers. A validated statistical learning model is then developed to allow for a mapping of the polymer fingerprints onto the property space in a physically meaningful and reliable manner. Once developed, the model can not only rapidly predict the property of new PHA polymers but also provide uncertainties underlying the predictions. The model is further combined with an evolutionary-algorithm-based search strategy to efficiently identify multicomponent polymer compositions with a prespecified T g . While the present contribution is focused specifically on T g , the surrogate model development approach put forward here is general and can, in principle, be extended to a range of other properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Critical mineral source potential from oil & gas produced waters in the United States

The volume of produced water, a by-product of oil & gas operations and other energy processes, has been growing across the United States (U.S.) along with the need to manage or recycle this wastewater. Produced water contains many naturally occurring elements of varying concentrations, including critical minerals which are essential to the clean energy transition. However, the current understanding of critical mineral concentrations in produced water and the associated volumes across the U.S. is limited. This study has assessed available databases and literature to gain insight into the presence and concentration of five high priority critical minerals, namely cobalt, lithium, magnesium, manganese, and nickel. The U.S. Geological Survey's National Produced Waters Geochemical Database was the main data source used for determining average critical mineral concentrations in produced water from the major oil and gas reservoirs in the U.S. The volumes of produced water for these major reservoirs were coupled with these concentrations to provide insights into where critical minerals are likely to have high abundance and therefore more recovery options. The analysis indicated the highest recovery potential for lithium and magnesium from produced water in the Permian basin and the Marcellus shale region. However, these assessments should be considered conservative due to the limited availability of reliable concentration data. Finally, it is expected more critical mineral recovery options could emerge with comprehensive characterization data from more recent and representative sources of produced water.

54 ENVIRONMENTAL SCIENCES↗

Chapter 15: Reliability of Wind Turbines

The global wind industry has witnessed exciting developments in recent years. The future will be even brighter with further reductions in capital and operation and maintenance costs, which can be accomplished with improved turbine reliability, especially when turbines are installed offshore. One opportunity for the industry to improve wind turbine reliability is through the exploration of reliability engineering life data analysis based on readily available data or maintenance records collected at typical wind plants. If adopted and conducted appropriately, these analyses can quickly save operation and maintenance costs in a potentially impactful manner. This chapter discusses wind turbine reliability by highlighting the methodology of reliability engineering life data analysis. It first briefly discusses fundamentals for wind turbine reliability and the current industry status. Then, the reliability engineering method for life analysis, including data collection, model development, and forecasting, is presented in detail and illustrated through two case studies. The chapter concludes with some remarks on potential opportunities to improve wind turbine reliability. An owner and operator's perspective is taken and mechanical components are used to exemplify the potential benefits of reliability engineering analysis to improve wind turbine reliability and availability.

17 WIND ENERGY↗

Overview of the forthcoming AAPM TG-158 Report, 'Measurements and calculations of doses outside the treatment volume from External Beam Radiation Therapy' - Paper 85

The evolution of techniques and technology in radiotherapy has greatly improved our ability to deliver higher tumor doses while minimizing the dose to the adjacent organs at risk. However, this improved conformality has not removed the problem of doses to normal tissues outside the target volume. Whether these out-of-field doses arise from photons, electrons, protons or neutrons, there are unique challenges that many medical physicists may have limited knowledge about or experience with. With modern treatment planning systems, high dose regions and areas within the primary beam path are typically well described. However, their accuracy beyond a few centimeters outside the treatment field edge are usually poor. In these cases, alternate methods are required to assess the out-of-field dose. Such assessments require additional care to avoid potentially large errors associated with a variety of unique complications in performing dosimetry outside the treatment field. Furthermore, physicists will not always have an a priori estimate of the expected dose, and, as a result, large dosimetric errors are more easily missed. Low radiation doses outside the treatment volume are a concern because they can cause deleterious effects to the patient. The risk of late effects from the secondary radiation may be more evident today because of the success of cancer screening and modern therapies that have increased the number of cancer patients who survive and live long enough for the adverse radiation effects on healthy tissues to manifest. Simultaneously, radiotherapy procedures have become more complex, making the estimation of low out-of-field doses even more challenging. Over the past 30 years, numerous studies have been published detailing non-target doses from various radiotherapy treatments (for a detailed review see Xu et al. However, dosimetry data were obtained using a variety of measurement or computational techniques. An overview of dosimetry techniques for measuring low-level non-target doses is not available. Improved, or at least valid, dosimetry is important for several reasons. In clinical care (e.g. fetal dose estimates), large dose errors can lead to inappropriate or unnecessary treatment decisions, with potentially serious consequences to the patient. In a broader sense of somatic effects, more accurate dosimetry will improve patient risk assessment, understanding of dose responses, treatment planning, and design of the radiation delivery machines. Once reliable dosimetry data are available, it is then the clinician's responsibility to assess the risk vs. benefit of the radiotherapy treatment to make a sound and informed assessment of all possible treatment outcomes. (author)

61 RADIATION PROTECTION AND DOSIMETRY↗

A combined experimental and computational analysis of failure mechanisms in open-hole cross-ply laminates under flexural loading

In this work, integrated experimental tests and computational modeling are proposed to investigate the failure mechanisms of open-hole cross-ply carbon fiber reinforced polymer (CFRP) laminated composites. In particular, we propose two effective methods, which include width-tapered double cantilever beam (WTDCB) and fixed-ratio mixed-mode end load split (FRMMELS) tests, to obtain the experimental data more reliably. We then calibrate the traction-separation laws of cohesive zone model (CZM) used among laminas of the composites by leveraging these two methods. The experimental results of fracture energy, i.e. G Ic and G Tc , obtained from WTDCB and FRMMELS tests are generally insensitive to the crack length thus requiring no effort to accurately measure the crack tip. Moreover, FRMMELS sample contains a fixed mixed-mode ratio of G IIc /G Tc depending on the width taper ratio. Examining comparisons between experimental results of FRMMELS tests and failure surface of B–K failure criterion predicted from a curve fitting, good agreement between the predictions and experimental data has been found, indicating that FRMMELS tests are an effective method to determine mixed-mode fracture criterion. In addition, a coupled experimental-computational modeling of WTDCB, edge notched flexure, and FRMMELS tests are adopted to calibrate and validate the interfacial strengths. Finally, failure mechanisms of open-hole cross-ply CFRP laminates under flexural loading have been studied systematically using experimental and multi-scale computational analyses based on the developed CZM model. The initiation and propagation of delamination, the failure of laminated layers as well as load-displacement curves predicted from computational analyses are in good agreement with what we have observed experimentally.

36 MATERIALS SCIENCE↗

Tracking seasonal variability in plant traits from spaceborne PRISMA and NEON AOP across forest types and ecoregions

Plant traits serve as critical indicators of how plants adapt to environmental changes and influence ecosystem functions. While airborne hyperspectral remote sensing effectively maps plant traits through detailed reflectance properties, it is limited by cost and scale, making large-scale and temporal studies challenging. The recently launched spaceborne hyperspectral imager, PRecursore IperSpettrale della Missione Applicativa (PRISMA), offers frequent, large scale and high-fidelity observations on a spatial resolution of 30 m and a revisit time of around 29 days, making it suitable for large-scale seasonal trait mapping. However, their potential remains largely unexplored. This study developed a multi-stage framework by leveraging the PRISMA spaceborne hyperspectral data and National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) hyperspectral data to investigate the seasonal dynamics of four key plant traits — chlorophyll content, carotenoid content, equivalent water thickness, and nitrogen content — across eleven NEON sites representing diverse forest types and ecoregions in the contiguous U.S. Our results demonstrated that PRISMA hyperspectral data can reliably track seasonal variability in plant traits, achieving overall R 2 values ranging from 0.78 to 0.88 and normalized root mean square error (NRMSE) values ranging from 5.4% to 8.4% for the four traits. Seasonal patterns revealed bell-shaped trajectories for chlorophyll and carotenoids, while equivalent water thickness decreased steadily across most sites, driven by structural changes during leaf maturation and senescence. Nitrogen content exhibited less pronounced seasonal variation but followed expected nutrient resorption patterns. Analysis of environmental drivers showed that seasonal variability is primarily controlled by solar radiation and day length in northern sites, vapor pressure in semi-arid regions, and temperature in mid-southeastern sites. Spatial variability, meanwhile, was primarily driven by soil properties, particularly during the peak growing season. However, the influence of soil variables slightly declines toward the end of the season at several sites, as climatic factors become more prominent. This study highlights the capability of PRISMA, and potentially other similar spaceborne hyperspectral data for large-scale, time-series plant trait mapping and provides valuable insights into the interactions between plant traits and environmental factors. In conclusion, these findings contribute to advancing our understanding of plant functional ecology and improving predictions of ecosystem responses to environmental changes.

Environmental drivers↗

Integration of Data Analytics with Plant System Health Program

This report summarizes the R&D activities of the Plant Health Management (PHM) project during fiscal year 2020 (FY20). This project focuses on the development of methods that integrate component health data and propagate such information at the system level to evaluate system sources of risk. This project development lives in cooperation with the Risk Informed Asset Management (RIAM) project. The RIAM project, in fact, uses the reliability models and data generated by the PHM project to optimize plant operations (e.g., maintenance/replacement schedule, optimal maintenance posture). This year’s activities for the PHM project focused mainly on the development of two classes of models. The first one includes a series of component reliability models which include aging, testing and maintenance. The second class includes a series of system reliability models which focus on the secondary side of exiting U.S. reactors. These models are based on fault tree logic structures such that they can be used by existing plant PRA software. We also started to focus on the management of health data and we tackled this issue in two directions. The first one focuses on the integration of monitor data with simulation models to assess component health. This approach is moving from a classical data based to a model+data based approach with the goal of improving higher component health information. The second direction focuses on linking equipment reliability data (e.g., maintenance/failure reports, component monitoring data) directly to system reliability models using a safety margin based language rather than a probability based language. The main advantage of a safety margin based language is that it can provide to system engineers more tangible information on system/component health and how it propagates to the system level.

97 MATHEMATICS AND COMPUTING↗