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Toward Improving the Assimilation of IASI and CrIS Radiances Over Land Into the NASA GEOS: LST Inversion and Validation

Assimilating surface-sensitive radiances over land is still challenging for both infrared (IR) and microwave (WV) essentially because of the large uncertainties of the land physical surface emissivity model used in the CRTM and the uncertainties of land surface state properties. Currently very few IR radiances are assimilated over land in the NASA Goddard Earth Observing System (GEOS). Large number of radiances are rejected by the emissivity sensitivity check as well as the Cloud detection check. This study focuses on enhancing the assimilation of Infrared Atmospheric Sounding Interferometer (IASI) and Cross-track Infrared Sounder (CrIS) over land in the GEOS forecasting and data assimilation framework. To reach this goal, the Land surface Temperature (LST) is first inverted using IR radiances from IASI and CrIS selected channels to use it as surface boundary parameter for the assimilation of the rest of IASI and CrIS surface-sensitive channels. This work will present a full assessment of the quality of this LST by comparing it and its spatio-temporal variability to LST predicted by the GEOS model. The impacts on the quality of the resulting analysis and subsequent forecast will also be discussed.

Niama Boukachaba↗

NASA NTRS1987

Application of a sensitivity analysis technique to high-order digital flight control systems

A sensitivity analysis technique for multiloop flight control systems is studied. This technique uses the scaled singular values of the return difference matrix as a measure of the relative stability of a control system. It then uses the gradients of these singular values with respect to system and controller parameters to judge sensitivity. The sensitivity analysis technique is first reviewed; then it is extended to include digital systems, through the derivation of singular-value gradient equations. Gradients with respect to parameters which do not appear explicitly as control-system matrix elements are also derived, so that high-order systems can be studied. A complete review of the integrated technique is given by way of a simple example: the inverted pendulum problem. The technique is then demonstrated on the X-29 control laws. Results show linear models of real systems can be analyzed by this sensitivity technique, if it is applied with care. A computer program called SVA was written to accomplish the singular-value sensitivity analysis techniques. Thus computational methods and considerations form an integral part of many of the discussions. A user's guide to the program is included. The SVA is a fully public domain program, running on the NASA/Dryden Elxsi computer.

Paduano, James D.↗

DOE OSTI2020

Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities

Increased penetration levels of distributed variable renewable generation can cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But because of the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network are needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69-node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time-series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Inter-IBR Oscillation Modes

This research addresses the following question: For a weak grid with multiple-IBRs, what is the nature of oscillation modes? The analysis of a system consisting of two identical IBRs offers a glimpse of the picture. It shows that the system has a weak-grid mode and an inter-IBR mode. For the weak-grid mode, two IBRs work as an aggregated one to interact with the grid. Furthermore, this mode is sensitive to IBR exporting power level and grid strength. For the inter-IBR mode, two IBRs oscillate against each other. This mode is less sensitive to grid strength and power level.

14 SOLAR ENERGY↗

DOE OSTI2021

A Zonal Volt/VAR Control Mechanism for High PV Penetration Distribution Systems

This paper presents a zonal Volt/VAR control scheme for regulating voltage in unbalanced 3-phase distribution systems using inverter-based resources (IBR). First, the dependency between nodal voltage changes and IBR reactive power injections is derived via voltage sensitivity studies. Then, a fast-incremental clustering method is used to divide the distribution circuit into weakly-coupled zones based on correlations between nodal voltage sensitivities. The weak-coupling allows the voltage to be regulated independently within each zone using a rule-based voltage controller to dispatch IBR for voltage corrections. Simulation results on actual distribution feeder show that the proposed zone-based Volt/VAR control method maintains system voltages within their operational limits while reducing the runtime of the Volt/VAR controller from tens of second to a couple of milliseconds compared with centralized, optimization-based Volt/VAR control methods.

Alrushoud, Asmaa↗

NASA NTRS1984

Sensitivities of projected 1980 photovoltaic system costs to major system cost drivers

The sensitivity of projected 1990 photovoltaic (PV) system costs to major system cost drivers was examined. It includes: (1) module costs and module efficiencies; (2) area related balance of system (BOS) costs; (3) inverter costs and efficiencies; and (4) module marketing and distribution markups and system integration fees. Recent PV system cost experiences and the high costs of electricity from the systems are reviewed. The 1990 system costs are projected for five classes of PV systems, including four ground mounted 5-MWp systems and one residential 5-kWp system. System cost projections are derived by first projecting costs and efficiencies for all subsystems and components. Sensitivity analyses reveal that reductions in module cost and engineering and system integration fees seem to have the greatest potential for contributing to system cost reduction. Although module cost is clearly the prime candidate for fruitful PV research and development activities, engineering and system integration fees seem to be more amenable to reduction through appropriate choice of system size and market strategy. Increases in inverter and module efficiency yield significant benefits, especially for systems with high area related costs.

Zimmerman, L. W.↗

NASA NTRS1986

The control of apical dominance: localization of the growth region of the Pharbitis nil shoot

The growing region of the upright Pharbitis nil shoot extends over a distance 13 cm basipetal to the shoot apex. When the shoot is inverted, ethylene production in this region is greatly enhanced whereas stem elongation is significantly inhibited. This growth region is ethylene-sensitive and the restriction of its growth by shoot inversion-induced ethylene may mediate the release of apical dominance.

NASA Discipline Plant Biology↗

DOE OSTI2021

Representing DC-Coupled PV+Battery Hybrids in a Capacity Expansion Model

Recent technology cost and performance improvements and the federal investment tax credit (ITC) have driven growing interest in coupling solar photovoltaic (PV) and battery systems. Combining these technologies into co-located or hybridized PV+battery systems has the potential to lower costs and increase energy output relative to multiple independent systems. In this work, we provide an overview of PV+battery systems and demonstrate methods for incorporating them into NREL’s Regional Energy Deployment System (ReEDS) capacity expansion model. Although the methods are applied to a specific model, we anticipate that the approaches used here can be useful for informing PV+battery method development for other capacity expansion models. The implemented method relies heavily on the native representations of PV and battery technologies; therefore, the focus of this work is on capturing and parameterizing the interactions between them for a configuration in which the PV and battery technologies share a single bi-directional inverter. This work also demonstrates the impacts of including PV+battery systems in the ReEDS optimization for the conterminous United States through 2050. In particular, we perform parametric sensitivities for input assumptions that are uncertain and expected to influence PV+battery deployment levels, including (a) the cost of PV+battery systems relative to independent PV and battery systems, (b) the battery component’s qualification for the ITC, and (c) future cost trajectories for PV and battery systems. We find that PV+battery deployment could occur throughout the conterminous United States if there are cost savings associated with DC coupling PV and battery technologies. If even modest (5%) cost savings can be achieved (through a shared inverter and balance-of-system costs), then approximately one-third of utility-scale PV deployment through 2050 adopts the DC-coupled hybrid configuration, resulting in total PV+battery deployment that exceeds the magnitude of PV+battery projects in U.S. interconnection queues in 2020. If greater cost savings can be achieved through DC coupling (e.g., due to a growing amount of shared balance-of-system costs, reduced financial risk, or modularity) or more rapid cost and performance improvements are realized for PV and battery technologies, then total PV+battery deployment and the share of PV and battery deployment that adopts the hybrid configuration grows (to >50%). In all cases, growing PV+battery deployment primarily displaces independent PV and battery technologies, indicating the strong competition between the hybrid and independent configurations comprising technologies with similar performance characteristics.

14 SOLAR ENERGY↗

DOE OSTI2025

Structure of the Ecuadorian Upper Plate From a Joint Seismic‐Gravity Inversion

The Ecuadorian portion of the South American subduction zone presents an interesting case study in the structure and complex evolution of an upper plate. There are outstanding questions about its tectonic history, composition, and magmatic processes. While previous studies have employed ambient noise tomography to image the Ecuadorian upper plate, surface wave inversions alone often lack sensitivity at relevant shallow depths. This limitation can be overcome with an independent, complementary data set, such as gravity. We have jointly inverted Rayleigh wave phase velocities and Bouguer gravity anomalies to provide a more detailed seismic velocity model of the Ecuadorian upper plate. Our joint inversion has yielded several key improvements from previous models. First, we observe much shallower slow velocities beneath major basins (the Manabí, Progreso, and Gulf of Guayaquil), better aligning with expected basin structure. Second, we identify a high-velocity block beneath the entire forearc, corresponding to the Piñon Terrane, with velocities suggesting the presence of ultramafic material. Third, we highlight a new narrow swath of slow velocities beneath the Ecuadorian Andes, which closely follows the active volcanoes along the Eastern Cordillera. The extent of these slow velocities coincides with the termination of active arc volcanism and the predicted location of the subducted Carnegie Ridge. The predicted compositions for the mid to lower crust in the region preclude a purely compositional explanation for these velocities, suggesting that some level of partial melt is necessary.

Birkey, Andrew [Univ. of Delaware, Newark, DE (Uni↗

NASA NTRS2016

First Image Products from EcoSAR - Osa Peninsula, Costa Rica

Designed especially for forest ecosystem studies, EcoSAR employs state-of-the-art digital beamforming technology to generate wide-swath, high-resolution imagery. EcoSARs dual antenna single-pass imaging capability eliminates temporal decorrelation from polarimetric and interferometric analysis, increasing the signal strength and simplifying models used to invert forest structure parameters. Antennae are physically separated by 25 meters providing single pass interferometry. In this mode the radar is most sensitive to topography. With 32 active transmit and receive channels, EcoSARs digital beamforming is an order of magnitude more versatile than the digital beamforming employed on the upcoming NISAR mission. EcoSARs long wavelength (P-band, 435 MHz, 69 cm) measurements can be used to simulate data products for ESAs future BIOMASS mission, allowing scientists to develop algorithms before the launch of the satellite. EcoSAR can also be deployed to collect much needed data where BIOMASS satellite wont be allowed to collect data (North America, Europe and Arctic), filling in the gaps to keep a watchful eye on the global carbon cycle. EcoSAR can play a vital role in monitoring, reporting and verification schemes of internationals programs such as UN-REDD (United Nations Reducing Emissions from Deforestation and Degradation) benefiting global society. EcoSAR was developed and flown with support from NASA Earth Sciences Technology Offices Instrument Incubator Program.

InSAR↗

NASA NTRS1991

Backscattering by nonspherical particles - A review of methods and suggested new approaches

Scattering of electromagnetic radiation near the backward direction is more sensitive to particle shape than scattering near the forward direction. Mie theory is therefore of dubious applicability to predicting backscattering by atmospheric particles known to be irregular or to inverting measurements on such particles. An irregular particle is one with an uncertain shape. In the face of uncertainty one must adopt a statistical approach in which scattering properties of ensembles are determined. To obtain ensemble averages, a basis is needed for averaging over a set of electromagnetic microstates. Ensemble averages based on the Rayleigh theory for small ellipsoids and on the T matrix method for spheroids agree better with measurements than Mie theory does. The coupled-dipole method also provides a basis for ensemble averaging. This method also leads to a simple physical interpretation of why backscattering is so sensitive to particle shape and can be used to calculate scattering by one- and two-dimensional analogs to three-dimensional irregular particles.

Bohren, Craig F.↗

DOE OSTI2021

nEXO: neutrinoless double beta decay search beyond 10 28 year half-life sensitivity

The nEXO neutrinoless double beta (0νββ) decay experiment is designed to use a time projection chamber and 5000 kg of isotopically enriched liquid xenon to search for the decay in 136 Xe. Progress in the detector design, paired with higher fidelity in its simulation and an advanced data analysis, based on the one used for the final results of EXO-200, produce a sensitivity prediction that exceeds the half-life of 10 28 years. Specifically, improvements have been made in the understanding of production of scintillation photons and charge as well as of their transport and reconstruction in the detector. The more detailed knowledge of the detector construction has been paired with more assays for trace radioactivity in different materials. In particular, the use of custom electroformed copper is now incorporated in the design, leading to a substantial reduction in backgrounds from the intrinsic radioactivity of detector materials. Furthermore, a number of assumptions from previous sensitivity projections have gained further support from interim work validating the nEXO experiment concept. Together these improvements and updates suggest that the nEXO experiment will reach a half-life sensitivity of 1.35 × 10 28 yr at 90% confidence level in 10 years of data taking, covering the parameter space associated with the inverted neutrino mass ordering, along with a significant portion of the parameter space for the normal ordering scenario, for almost all nuclear matrix elements. Furthermore, the effects of backgrounds deviating from the nominal values used for the projections are also illustrated, concluding that the nEXO design is robust against a number of imperfections of the model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Regime-based aerosol–cloud interactions from CALIPSO-MODIS and the Energy Exascale Earth System Model version 2 (E3SMv2) over the Eastern North Atlantic

This study investigates aerosol-cloud interactions in marine boundary layer (MBL) clouds using an advanced deep-learning-driven synoptic-regime-based framework, combining satellite data (CALIPSO vertically resolved aerosol extinction and MODIS cloud properties) with 1° nudged Energy Exascale Earth System Model version 2 (E3SMv2) simulation over the Eastern North Atlantic (ENA; ∼10°×10°, 2006–2014). The E3SMv2 captures observed seasonal variations in cloud droplet number concentrations (N d ) and liquid water path (LWP), though it systematically underestimates N d . We then partition ENA meteorology into four synoptic regimes (Pre-Trough, Post-Trough, Ridge, Trough) via a deep-learning clustering of ERA5 reanalysis fields, enabling regime-dependent aerosol-cloud interactions analyses. Both satellite and E3SMv2 exhibit an inverted-V LWP-N d relationship. In Post-Trough and Ridge regimes, the satellite shows stronger negative LWP-N d sensitivities than in Pre-Trough regime. The Trough regime displays a muted satellite LWP response. In comparison, the model predicts more exaggerated LWP responses across regimes, with LWP increasing too quickly at low N d and decreasing more sharply at high N d , especially in Pre-Trough and Trough regimes. These exaggerated model LWP sensitivities may stem from uncertainties in representing drizzle processes, entrainment, and turbulent mixing. As for N d susceptibility to aerosols, N d increases with MBL aerosol extinction in both datasets, but the simulated aerosol-cloud interactions appear oversensitive to meteorological conditions. Overall, E3SMv2 better captures aerosol effects under regimes that favor stratiform clouds (Post-Trough, Ridge), but performance deteriorates for regimes with deeper, dynamically complex clouds (Trough), highlighting the need for improved representations of those cloud processes in climate models.

Environmental sciences↗

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 NTRS2010

Comparison of Traditional Design Nonlinear Programming Optimization and Stochastic Methods for Structural Design

Structural design generated by traditional method, optimization method and the stochastic design concept are compared. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the merit function with constraints imposed on failure modes and an optimization algorithm is used to generate the solution. Stochastic design concept accounts for uncertainties in loads, material properties, and other parameters and solution is obtained by solving a design optimization problem for a specified reliability. Acceptable solutions were produced by all the three methods. The variation in the weight calculated by the methods was modest. Some variation was noticed in designs calculated by the methods. The variation may be attributed to structural indeterminacy. It is prudent to develop design by all three methods prior to its fabrication. The traditional design method can be improved when the simplified sensitivities of the behavior constraint is used. Such sensitivity can reduce design calculations and may have a potential to unify the traditional and optimization methods. Weight versus reliabilitytraced out an inverted-S-shaped graph. The center of the graph corresponded to mean valued design. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure. Weight can be reduced to a small value for a most failure-prone design. Probabilistic modeling of load and material properties remained a challenge.

Patnaik, Surya N.↗

DOE OSTI2024

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

Abstract Nanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well‐established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal‐organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high‐throughput, non‐destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

Fricke, Sophia N.↗

DOE OSTI2024

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1988

Dynamic structural correlation via nonlinear programming techniques

A solution to the correlation between structural dynamic test results and finite element analyses of the same components is presented in this paper. Basically, the method can be categorized as a Levenberg-Marquardt type Gauss-Newton method which requires only the differences between FE modal analyses and test results and their first derivatives with respect to preassigned design variables. With proper variable normalization and equation scaling, the method has been made numerically better-conditioned and the inclusion of the Levenberg-Marquardt technique overcomes any remaining difficulty encountered in inverting singular or near-singular matrices. An important feature is that each iteration requires only one function evaluation along with the associated design sensitivity analysis and so the procedure is computationally efficient.

Ting, T.↗