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NASA NTRS2010

Application of the Tor Vergata Scattering Model to L Band Backscatter During the Corn Growth Cycle

At the USDA's Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) experimental site in Beltsville, Maryland, USA) a field campaign took place throughout the 2002 corn growth cycle from May 10th (emergence of corn crops) to October 2nd (harvest). One of the microwave instruments deployed was the multi-frequency (X-, C- and L-band) quad-polarized (HH, HV, VV, VH) NASA GSFC/George Washington University (GWU) truck mounted radar. During the field campaign, this radar system provided once a week fully polarized C- and L-band (4.75 and 1.6 GHz) backscatter measurements from incidence angle of 15, 35, and 55 degrees. In support of microwave observations, an extensive ground characterization took place, which included measurements of surface roughness, soil moisture, vegetation biomass and morphology. The field conditions during the campaign are characterized by several dry downs with a period of drought in the month of August. Peak biomass the corn canopies was reached on July 24th with a total biomass of approximately 6.5 kg/sq m. This dynamic range in both soil moisture and vegetation conditions within the data set is ideal for the validation of discrete medium vegetation scattering models. In this study, we compare the L band backscatter measurements with simulations by the Tor Vergata model (ferrazzoli and Guerriero 1996). The measured soil moisture, vegetation biomass and most reliably measured vegetation morphological parameters (e.g. number of leaves, number of stems and stem height) were used as input for the Tor Vergata model. The more uncertain model parameters (e.g. surface roughness, leaf thickness) and the stem diameter were optimized using a parameter estimation routine based on the Levenberg-Marquardt algorithm. As cost function for this optimization, the HH and VV polarized backscatter measured and stimulated by the TOR Vergata model for incidence angle of 15, 35, and 55 degrees were used (6 measurements in total). The calibrated Tor Vergata model simulations are in excellent agreement with the measurements of Root Mean Squared Differences (RMSD's) of 0.8, 0.9 and 1.4 dB for incidences of 15, 35 and 55 degrees, respectively. The results from this study that a physically based scattering model with the appropriate parameterization can accurately simulate backscatter measurements and, as such, have the potential of being used for the retrieval of biophysical variables (e.g. soil moisture and vegetation biomass).

Joseph, A. T.↗
NASA NTRS2017

Estimating Surface Soil Moisture from SMAP Observations Using a Neural Network Technique

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m(exp. 3)m(exp. -3), 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m(exp. 3)m(exp. -3), 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

Soil Moisture Remote Sensing↗
DOE OSTI2025

Cooperative On-Ramp Merging with Time-Varying Vehicle-to-Vehicle Communication Delay Compensation via a Model-Free Approach

Cooperative merging strategies enabled by vehicle-to-vehicle (V2V) communication have shown promise in addressing congestion, fuel inefficiency, and collision risks. However, their performance can be severely degraded by time-varying and uncertain communication delays-an issue often overlooked in existing research, which primarily focuses on merging sequence determination and trajectory planning. Furthermore, practical considerations such as heterogeneous vehicle dynamics, varying road conditions, and real-time implementation complexities are frequently neglected. This paper presents a model-free, online planning framework for cooperative on-ramp merging of connected and automated vehicles (CAVs), explicitly accounting for time-varying V2V communication delays. Without relying on detailed vehicle dynamics, the proposed method introduces a data-driven delay compensation scheme. A co-simulation platform integrating high-fidelity vehicle dynamics, traffic simulation (SUMO), and V2V communication within MATLAB/Simulink is developed to evaluate the proposed method. Simulation results demonstrate that unaddressed V2V communication delays significantly impair merging performance. In contrast, the proposed framework enhances intervehicle distance tracking and maintains low CO2 emissions and fuel consumption, under communication delay across different communication frequencies. In conclusion, its lightweight design also facilitates real-time implementation, making it well-suited for deployment in practical CAV systems.

Accounting↗
DOE OSTI2023

Assessing the nexus between groundwater and solar energy plants in a desert basin with a dual-model approach under uncertainty

Globally, many solar power plants and other types of renewable energy are being located in water-scarce regions. Many projects rely on groundwater resources whose sustainability is uncertain. In the Chuckwalla Basin in California, quantification of recharge and trans-valley underflow is needed to estimate the impacts of solar project withdrawals on the water table. However, such estimates are highly challenging due to data scarcity, heterogeneous soils and long residence times. Conventional assessment employs isolated groundwater models configured with crude and uniform estimates of recharge. Here, we employ a data-constrained surface subsurface processes model, PAWS+CLM, to provide an ensemble of recharges and underflows with perturbed parameters. Then, the Parameter Estimation (PEST) package is used to calibrate MODFLOW aquifer conductivity and filter out implausible recharges. The novel dual-model approach, potentially applicable in other arid regions, can effectively assimilate groundwater head observations, reject unrealistic parameters, and narrow the range of estimated drawdowns. Simulated recharge concentrates along alluvial fans at the mountain fronts and ephemeral washes where run-off water infiltrates. If an evenly distributed recharge was assumed, it resulted in under-estimated drawdown and larger uncertainty bounds. The withdrawals are approaching total inflow, suggesting the system will be nearing, if not exceeding, its sustainable groundwater production capacity, and a boom of such projects will not be sustainable. Especially, the cost/benefit of pumped-storage projects is called into question as the initial-fill phase depletes entire area’s recharge. Our study highlights the stress on groundwater resources of solar development, and that the speed of groundwater recovery does not indicate sustainability. Main point 1: A novel dual model approach, involving an integrated surface/subsurface model and a groundwater parameter-estimation model, was able to better constrain the model. Main point 2: The groundwater system may be nearing, if not exceeding, its sustainable groundwater production capacity and the speed of recovery is not indicative of sustainability. Main point 3: Results from using conventionally-assumed uniform recharge distort calibrated K fields and impacts assessment

14 SOLAR ENERGY↗
NASA NTRS2011

Developing Flexible Discrete Event Simulation Models in an Uncertain Policy Environment

On February 1st, 2010 U.S. President Barack Obama submitted to Congress his proposed budget request for Fiscal Year 2011. This budget included significant changes to the National Aeronautics and Space Administration (NASA), including the proposed cancellation of the Constellation Program. This change proved to be controversial and Congressional approval of the program's official cancellation would take many months to complete. During this same period an end-to-end discrete event simulation (DES) model of Constellation operations was being built through the joint efforts of Productivity Apex Inc. (PAl) and Science Applications International Corporation (SAIC) teams under the guidance of NASA. The uncertainty in regards to the Constellation program presented a major challenge to the DES team, as to: continue the development of this program-of-record simulation, while at the same time remain prepared for possible changes to the program. This required the team to rethink how it would develop it's model and make it flexible enough to support possible future vehicles while at the same time be specific enough to support the program-of-record. This challenge was compounded by the fact that this model was being developed through the traditional DES process-orientation which lacked the flexibility of object-oriented approaches. The team met this challenge through significant pre-planning that led to the "modularization" of the model's structure by identifying what was generic, finding natural logic break points, and the standardization of interlogic numbering system. The outcome of this work resulted in a model that not only was ready to be easily modified to support any future rocket programs, but also a model that was extremely structured and organized in a way that facilitated rapid verification. This paper discusses in detail the process the team followed to build this model and the many advantages this method provides builders of traditional process-oriented discrete event simulations.

Miranda, David J.↗
NASA NTRS2026

Tracing the Source of Carbon Oxides on the Large Moons of Uranus

The Uranian moons Ariel, Umbriel, Titania, and Oberon are enriched in CO 2 mixed with CO, but the origin(s) of these carbon oxides, be they primarily native or radiolytic, remain(s) uncertain. Using data collected by NIRSpec on the James Webb Space Telescope (JWST), we measured the spectral signature of CO 2 and other carbon oxides to help disentangle these hypotheses. Through comparison to laboratory data, we find that many of the detected spectral features are consistent with CO 2 ice, including 12 CO2 scattering peaks (4.15–4.26 μm), multilobe 13 CO 2 bands (4.35–4.43 μm), and CO 2 biphonon and triphonon modes (4.80–5.25 μm). Our measurements show that CO 2 and CO are concentrated on the trailing hemispheres of the inner moons Ariel and Umbriel, potentially supporting a radiolytic production hypothesis, consistent with prior ground-based results. However, many of the identified spectral features are only observed in thick crystalline ice deposits measured in the laboratory, which may be difficult to form via radiolysis of carbon-bearing material mixed in icy regoliths. Similarly, the data exhibit weak 4.02 and 4.40 μm bands, hinting at the presence of carbonate minerals and 13 CO 2 clathrates, respectively, possibly formed in the interiors of these moons. Furthermore, JWST has revealed that CO 2 is widespread at Uranus, present in its system of rings, ring moons, and irregular satellites, consistent with its largest moons accreting CO 2 and other carbon oxides from the Uranian subnebula. We conclude that exposed carbon oxides are potentially native, with their surface distributions shaped by charged particle irradiation and seasonal sublimation–condensation cycles.

Ice spectroscopy↗
DOE OSTI2022

Copy number variation in pituitary stalk interruption syndrome: A large case series of sporadic non‐syndromic patients and literature review

Abstract Abnormal hypothalamic/posterior pituitary development appears to be a major determinant of pituitary stalk interruption syndrome (PSIS). The observation of familial cases and associated congenital abnormalities suggests a genetic basis. Single‐gene mutations explain less than 5% of the cases, and whole exome sequencing has shown heterogeneous results. The present study aimed to assess copy number variation (CNV) using array‐based comparative genomic hybridization (aCGH) in patients with non‐syndromic PSIS and comprehensively review data from the literature on CNV analysis in congenital hypopituitarism (CH) patients. Twenty‐one patients with sporadic CH from our outpatient clinics presented with ectopic posterior pituitary (EPP) and no central nervous system abnormalities on magnetic resonance image (MRI) or any other malformations on physical examination at presentation were enrolled in the study. aCGH using a whole‐genome customized 400K oligonucleotide platform was performed in our patients. For the literature review, we searched for case reports of patients with CH and CNV detected by either karyotype or aCGH reported in PubMed up to November 2021. Thirty‐five distinct rare CNVs were observed in 18 patients (86%) and two of them (6%) were classified as pathogenic: one deletion of 1.8 Mb in chromosome 17 (17q12) and one deletion of 15 Mb in chromosome 18 (18p11.32p11.21), each one in a distinct patient. In the literature review, 67 pathogenic CNVs were published in 83 patients with CH, including the present study. Most of these patients had EPP (78% out of the 45 evaluated by sellar MRI) and were syndromic (70%). The most frequently affected chromosomes were X, 18, 20 and 1. Our study has found that CNV can be a mechanism of genetic abnormality in non‐syndromic patients with CH and EPP. In future studies, one or more genes in those CNVs, both pathogenic and variant of uncertain significance, may be considered as good candidate genes.

Correa‐Silva, Silvia R.↗
NASA NTRSDate not supplied

FluxSat: Long-term Earth Science Data Record (ESDR) for Terrestrial Gross Primary Production (GPP) based on satellite data calibrated with eddy covariance data

Gross primary production (GPP), the amount of carbon dioxide (CO 2 ) assimilated by plants through photosynthesis, is one of the most variable and uncertain components of the global carbon cycle. Global GPP has been estimated with a number of process-based models, data-driven, and hybrid approaches. Dynamic global vegetation models (DGVMs), driven by observed environmental changes, are used for global carbon budget assessments and long-term (climate) prediction. Benchmarking these and other models globally with data-driven GPP estimates is critical for understanding the land sink and ensuring accurate forecasts of the carbon cycle. In addition, global data-driven GPP estimates are crucial for studies of interannual variability, including trends that are linked to mechanisms with large uncertainties, such as the indirect CO 2 fertilization effect related to greening. In response to a community need for a GPP data set that well captures spatio-temporal variability, we developed FluxSat, a data-driven approach that optimizes the use of satellite reflectance data from the NASA MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites, calibrated using ground-based eddy covariance (EC) data. We are enhancing (spatially, higher resolution) and extending FluxSat (in time, with additional sensors) to create a high quality long term GPP Earth System Data Record (ESDR) for use in model benchmarking, carbon cycle modeling, and studies of trends and interannual variability. Our team’s objectives are to: 1. Update and document the current MODIS FluxSat GPP (daily, 0.05o and 0.5o resolutions) products with latest available MODIS and EC data sets; 2. Extend FluxSat GPP record forward in time with the Visible Infrared Imaging Radiometer Suite (VIIRS) on operational weather satellites going forward; 3. Extend FluxSat GPP record backward in time using the Advanced Very High Resolution Radiometer (AVHRR) on weather satellites dating back to 1981; 4. Provide higher spatial resolution MODIS and VIIRS GPP (0.0083o). 5. Thoroughly evaluate all FluxSat products with independent data; and 6. Create a homogenized long-term GPP record spanning 40+ years. We will discuss plans for this long-term data set that is supported through the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program.

gross Primary Production↗
DOE OSTI2022

EGS Stimulation Design with Uncertainty Quantification at the EGS Collab Site

Engineering a robust hydraulic connection between wells is one of the most difficult aspects of enhanced geothermal systems (EGS). Designing and constructing such hydraulic connections requires and understanding of the in situ state of stress and the heterogeneities and discontinuities that naturally exist and may control the stimulation. Even with comprehensive stress and formation characterization programs substantial uncertainty remains in these key parameters. This is especially the case in high-temperature EGS environments where drilling conditions are often difficult and a far fewer logging and testing options are available. This paper presents a new approach for explicitly quantifying the uncertainties in the state of stress using a Bayesian Markov Chain Monte Carlo method. This approach produces a probability distribution for the stress tensor, including a general 3D orientation, that reflects the uncertainties in all the observations or indicators used to constrain the stress state. This method is demonstrated on the characterization data for the EGS Collab Experiment 2 site. The output of the analysis is used to guide the design of the planned stimulations. In the case of research projects like EGS Collab, explicitly quantifying the uncertainties in the stress state allow for more rigorous hypothesis testing by allowing conclusions drawn from the experiments to be interpreted in the context of the uncertain knowledge about conditions in the test bed.

Burghardt, Jeffrey A.↗
DOE OSTI2022

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1993

Robust on-off pulse control of flexible space vehicles

The on-off reaction jet control system is often used for attitude and orbital maneuvering of various spacecraft. Future space vehicles such as the orbital transfer vehicles, orbital maneuvering vehicles, and space station will extensively use reaction jets for orbital maneuvering and attitude stabilization. The proposed robust fuel- and time-optimal control algorithm is used for a three-mass spacing model of flexible spacecraft. A fuel-efficient on-off control logic is developed for robust rest-to-rest maneuver of a flexible vehicle with minimum excitation of structural modes. The first part of this report is concerned with the problem of selecting a proper pair of jets for practical trade-offs among the maneuvering time, fuel consumption, structural mode excitation, and performance robustness. A time-optimal control problem subject to parameter robustness constraints is formulated and solved. The second part of this report deals with obtaining parameter insensitive fuel- and time- optimal control inputs by solving a constrained optimization problem subject to robustness constraints. It is shown that sensitivity to modeling errors can be significantly reduced by the proposed, robustified open-loop control approach. The final part of this report deals with sliding mode control design for uncertain flexible structures. The benchmark problem of a flexible structure is used as an example for the feedback sliding mode controller design with bounded control inputs and robustness to parameter variations is investigated.

Wie, Bong↗
DOE OSTI2025

The R -Process Alliance: Exploring the cosmic scatter among ten r -process sites with stellar abundances

Context. The astrophysical origin of the rapid neutron-capture process (r-process), responsible for producing roughly half of the elements heavier than iron, remains uncertain. Detailed chemical signatures from the oldest, most metal-poor stars, which act as fossil records of the earliest nucleosynthesis events, can be used to identify the dominant r-process sites. Aims. We present a homogeneous chemical abundance analysis of ten r-process element-enhanced stars. These old and metal-poor stars are strongly enriched in r-process elements with minimal contamination from other nucleosynthetic sources. By focusing on this chemically pure sample, we aim to investigate intrinsic variations in the r-process abundance patterns and explore their implications for the nature and potential diversity of r-process sites. Methods. We performed a detailed chemical abundance analysis of high-resolution, high-signal-to-noise spectra. For each star, we inspected over 1400 individual absorption lines using a combination of equivalent width measurements and spectral synthesis. The analysis was conducted under the assumption of 1D local thermodynamic equilibrium and employing the MOOG radiative transfer code. Results. We derived abundances for 54 chemical species, including 29 neutron-capture (n-capture) elements, covering the full mass range of the r-process abundance pattern. A kinematic analysis reveals that stars likely originated from ten kinematically distinct systems. Based on this assumption, we used the sample to probe the maximum variation expected from ten independent r-process nucleosynthesis events and computed the intrinsic dispersion of each element relative to Zr and Eu for the light and heavy r-process elements, respectively. This exercise resulted in a remarkably low cosmic scatter across the ten r-process sites enriching these stars; for the rare earth and third peak elements, for example, we find σ [La/Eu] = 0.08 and σ [Os/Eu] = 0.11 dex, while the scatter between light and heavy elements, σ [Zr/Eu] , is slightly higher at 0.18 dex. Conclusions. The elemental abundance patterns across the ten independent r-process sites show remarkably small cosmic dispersions. This minimal dispersion suggests a high degree of uniformity in r-process yields across diverse astrophysical environments.

Astronomy and AstroPhysics↗
DOE OSTI2024

A Photochemical Phosphorus-Hydrogen-Oxygen Network for Hydrogen-dominated Exoplanet Atmospheres

Due to the detection of phosphine (PH 3 ) in the solar system gas giants Jupiter and Saturn, PH 3 has long been suggested to be detectable in exosolar substellar atmospheres too. However, to date, direct detection of phosphine has proven to be elusive in exoplanet atmosphere surveys. We construct an updated phosphorus-hydrogen-oxygen (PHO) photochemical network suitable for the simulation of gas giant hydrogen-dominated atmospheres. Using this network, we examine PHO photochemistry in hot Jupiter and warm Neptune exoplanet atmospheres at solar and enriched metallicities. Our results show for HD 189733b-like hot Jupiters that HOPO, PO, and P 2 are typically the dominant P carriers at pressures important for transit and emission spectra, rather than PH 3 . For GJ1214b-like warm Neptune atmospheres our results suggest that at solar metallicity PH 3 is dominant in the absence of photochemistry, but is generally not in high abundance for all other chemical environments. At 10 and 100 times solar, small oxygenated phosphorus molecules such as HOPO and PO dominate for both thermochemical and photochemical simulations. The network is able to reproduce well the observed PH 3 abundances on Jupiter and Saturn. Despite progress in improving the accuracy of the PHO network, large portions of the reaction rate data remain with approximate, uncertain, or missing values, which could change the conclusions of the current study significantly. Improving understanding of the kinetics of phosphorus-bearing chemical reactions will be a key undertaking for astronomers aiming to detect phosphine and other phosphorus species in both rocky and gaseous exoplanetary atmospheres in the near future.

atmospheric composition↗
DOE OSTI2021

A deep learning hybrid predictive modeling (HPM) approach for estimating evapotranspiration and ecosystem respiration

Climate change is reshaping vulnerable ecosystems, leading to uncertain effects on ecosystem dynamics, including evapotranspiration (ET) and ecosystem respiration (R eco ). However, accurate estimation of ET and R eco still remains challenging at sparsely monitored watersheds, where data and field instrumentation are limited. In this study, we developed a hybrid predictive modeling approach (HPM) that integrates eddy covariance measurements, physically based model simulation results, meteorological forcings, and remote-sensing datasets to estimate ET and R eco in high space–time resolution. HPM relies on a deep learning algorithm and long short-term memory (LSTM) and requires only air temperature, precipitation, radiation, normalized difference vegetation index (NDVI), and soil temperature (when available) as input variables. We tested and validated HPM estimation results in different climate regions and developed four use cases to demonstrate the applicability and variability of HPM at various FLUXNET sites and Rocky Mountain SNOTEL sites in Western North America. To test the limitations and performance of the HPM approach in mountainous watersheds, an expanded use case focused on the East River Watershed, Colorado, USA. The results indicate HPM is capable of identifying complicated interactions among meteorological forcings, ET, and R eco variables, as well as providing reliable estimation of ET and R eco across relevant spatiotemporal scales, even in challenging mountainous systems. The study documents that HPM increases our capability to estimate ET and R eco and enhances process understanding at sparsely monitored watersheds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Bifurcation Analysis Using Rigorous Branch and Bound Methods

For the study of nonlinear dynamic systems, it is important to locate the equilibria and bifurcations occurring within a specified computational domain. This paper proposes a new approach for solving these problems and compares it to the numerical continuation method. The new approach is based upon branch and bound and utilizes rigorous enclosure techniques to yield outer bounding sets of both the equilibrium and local bifurcation manifolds. These sets, which comprise the union of hyper-rectangles, can be made to be as tight as desired. Sufficient conditions for the existence of equilibrium and bifurcation points taking the form of algebraic inequality constraints in the state-parameter space are used to calculate their enclosures directly. The enclosures for the bifurcation sets can be computed independently of the equilibrium manifold, and are guaranteed to contain all solutions within the computational domain. A further advantage of this method is the ability to compute a near-maximally sized hyper-rectangle of high dimension centered at a fixed parameter-state point whose elements are guaranteed to exclude all bifurcation points. This hyper-rectangle, which requires a global description of the bifurcation manifold within the computational domain, cannot be obtained otherwise. A test case, based on the dynamics of a UAV subject to uncertain center of gravity location, is used to illustrate the efficacy of the method by comparing it with numerical continuation and to evaluate its computational complexity.

Smith, Andrew P.↗
NASA NTRS1999

A Design Heritage-Based Forecasting Methodology for Risk Informed Management of Advanced Systems

The development of next generation systems often carries with it the promise of improved performance, greater reliability, and reduced operational costs. These expectations arise from the use of novel designs, new materials, advanced integration and production technologies intended for functionality replacing the previous generation. However, the novelty of these nascent technologies is accompanied by lack of operational experience and, in many cases, no actual testing as well. Therefore some of the enthusiasm surrounding most new technologies may be due to inflated aspirations from lack of knowledge rather than actual future expectations. This paper proposes a design heritage approach for improved reliability forecasting of advanced system components. The basis of the design heritage approach is to relate advanced system components to similar designs currently in operation. The demonstrated performance of these components could then be used to forecast the expected performance and reliability of comparable advanced technology components. In this approach the greater the divergence of the advanced component designs from the current systems the higher the uncertainty that accompanies the associated failure estimates. Designers of advanced systems are faced with many difficult decisions. One of the most common and more difficult types of these decisions are those related to the choice between design alternatives. In the past decision-makers have found these decisions to be extremely difficult to make because they often involve the trade-off between a known performing fielded design and a promising paper design. When it comes to expected reliability performance the paper design always looks better because it is on paper and it addresses all the know failure modes of the fielded design. On the other hand there is a long, and sometimes very difficult road, between the promise of a paper design and its fulfillment; with the possibility that sometimes the reliability promise is not fulfilled at all. Decision makers in advanced technology areas have always known to discount the performance claims of a design to a degree in proportion to its stage of development, and at times have preferred the more mature design over the one of lesser maturity even with the latter promising substantially better performance once fielded. As with the broader measures of performance this has also been true for projected reliability performance. Paper estimates of potential advances in design reliability are to a degree uncertain in proportion to the maturity of the features being proposed to secure those advances. This is especially true when performance-enhancing features in other areas are also planned to be part of the development program.

Maggio, Gaspare↗
DOE OSTI2026

Machine learning reveals strong grid-scale dependence in the satellite N d –LWP relationship

The relationship between cloud droplet number concentration ( N d ) and liquid water path (LWP) is highly uncertain yet crucial for determining the impact of aerosol-cloud interactions (ACI) on Earth's radiation budget. The N d -LWP relationship is examined using a machine learning (ML) random forest model applied to five years of satellite data at grid resolutions ranging from 10° to 0.05° in 12 distinct regions. In the subtropics, the shape of the N d -LWP relationship switches from an inverted-V at 1° grid-resolution to an “M” shape at 0.1° resolution with decreased $\frac{\textrm{dln⁡LWP}}{\textrm{dln⁡}N_d}$ sensitivity. Tropical and midlatitude regions generally show a more positive sensitivity. Cloud sampling and filtering also influence this slope, wherein the exclusion of thin clouds, as commonly performed to reduce retrieval uncertainty, leads to strongly negative sensitivity across all regions. Precipitation is primarily responsible for driving the strength of the sensitivity, with strong positive slopes in raining clouds and negative and/or neutral responses found in non-raining clouds. A new method to compute radiative forcing from the ML model shows a robust Twomey radiative forcing across all regions and grid resolutions. However, LWP and cloud fraction adjustments to the radiative forcing, which are ∼50 % or smaller than the Twomey effect, decrease to negligible values with higher spatial resolution data. As Earth system models move toward higher spatial resolutions in the future, evaluating the LWP and CF adjustment contributions to the radiative forcing budget at these finer resolutions will be essential for evaluation and model development.

Aerosol-Cloud Interactions↗
NASA NTRS2015

Results of Lunar Impact Observations During Geminid Meteor Shower Events

Meteoroids are natural particles with origins from comets, asteroids, and planets from within the solar system. On average, 33 metric tons (73,000 lb) of meteoroids hit Earth everyday with velocities ranging between 20 and 72 km/s. However, the vast majority of these meteoroids disintegrate in the atmosphere and never make it to the ground. The Moon also encounters the same meteoroid flux, but has no atmosphere to stop them from striking the surface. At such speeds even a small meteoroid has incredible energy. A meteoroid with a mass of only 5 kg can excavate a crater over 9 m across, hurling 75 metric tons (165,000 lb) of lunar soil and rock on ballistic trajectories above the lunar surface. Meteoroids with particle sizes as small as 100 micrometer (1 Microgram) can do considerable damage to spacecraft in Earth's orbit and beyond. Impacts can damage thermal protection systems, radiators, windows, and pressurized containers. Secondary effects might include partial penetration or pitting, local deformation, and surface degradation that can cause a failure upon reentry. The speed, mass, density, and flux of meteoroids are important factors for design considerations and mitigation during operations. Lunar operations (unmanned and manned) are also adversely affected by the meteoroid flux. Ejecta from meteoroid impacts is also part of the lunar environment and must be characterized. Understanding meteoroid fluxes and the associated risk of meteoroids impacting spacecraft traveling in and beyond Earth's orbit is the objective of the Meteoroid Environment Office (MEO) located at Marshall Space Flight Center (MSFC). One of the MEO's programs is meteoroid impact monitoring of the Moon. The large collecting area of the night side of the lunar disk provides statistically significant counts of meteoroids that can provide useful information about the flux of meteoroids in the hundreds of grams to kilograms size range. This information is not only important for characterizing the lunar environment associated with larger lunar impactors, but also provides statistical data for verification and improving meteoroid prediction models. Current meteoroid models indicate that the Moon is struck by a sporadic meteoroid with a mass greater than 1 kg over 260 times per year. This number is very uncertain since observations for objects in this mass range are few. Factors of several times, higher or lower, are easily possible. Meteor showers are also present to varying degrees at certain times of the year. The Earth experiences meteor showers when encountering the debris left behind by comets, which is also the case with 2 the Moon. During such times, the rate of shower meteoroids can greatly exceed that of the sporadic background rate for larger meteoroids. Looking for meteor shower impacts on the Moon at about the same time as they occur on Earth will yield important data that can be fed into meteor shower forecasting models, which can then be used to predict times of greater meteoroid hazard on the Moon. The Geminids are one such meteor shower of interest. The Geminids are a major meteor shower that occur in December with a peak intensity occurring usually during the 13th and 14th of the month and appearing to come from a radiant in the constellation Gemini. The Geminids are interesting in that the parent body of the debris stream is an asteroid, which along with the Quadrantids, are the only major meteor showers not originating from a comet. The Geminids parent body, 3200 Phaethon, is about 5 km in diameter and has an orbit that has a 22deg inclination which intersects the main asteroid belt and has a perihelion less than half of Mercury's perihelion distance. Thus, its orbit crosses those of Mars, Earth, Venus, and Mercury. The Geminid debris stream is by far the most massive as compared to the others. When the Earth passes through the stream in mid-December, a peak intensity of approx. equal 120 meteors per hour can be seen. Because of the Geminids' relatively large intensity and unique origin, it is important to monitor and gain information about the Geminids so as to improve their forecasts and understand their contribution to the meteoroid environment in Earth's orbit and at the Moon. It is the purpose of this Technical Memorandum (TM) to document two lunar observing periods coinciding with the Geminid meteor showers that occurred in 2006 and 2010.

Suggs, R. J.↗