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NASA NTRS2003

Estimation of Model Error Variances During Data Assimilation

Data assimilation is all about understanding the error characteristics of the data and models that are used in the assimilation process. Reliable error estimates are needed to implement observational quality control, bias correction of observations and model fields, and intelligent data selection. Meaningful covariance specifications are obviously required for the analysis as well, since the impact of any single observation strongly depends on the assumed structure of the background errors. Operational atmospheric data assimilation systems still rely primarily on climatological background error covariances. To obtain error estimates that reflect both the character of the flow and the current state of the observing system, it is necessary to solve three problems: (1) how to account for the short-term evolution of errors in the initial conditions; (2) how to estimate the additional component of error caused by model defects; and (3) how to compute the error reduction in the analysis due to observational information. Various approaches are now available that provide approximate solutions to the first and third of these problems. However, the useful accuracy of these solutions very much depends on the size and character of the model errors and the ability to account for them. Model errors represent the real-world forcing of the error evolution in a data assimilation system. Clearly, meaningful model error estimates and/or statistics must be based on information external to the model itself. The most obvious information source is observational, and since the volume of available geophysical data is growing rapidly, there is some hope that a purely statistical approach to model error estimation can be viable. This requires that the observation errors themselves are well understood and quantifiable. We will discuss some of these challenges and present a new sequential scheme for estimating model error variances from observations in the context of an atmospheric data assimilation system.

Dee, Dick↗

DOE OSTI2022

Solving the structure of “single-atom” catalysts using machine learning – assisted XANES analysis

We show that "single-atom” catalysts (SACs) have demonstrated excellent activity and selectivity in challenging chemical transformations such as photocatalytic CO 2 reduction. For heterogeneous photocatalytic SAC systems, it is essential to obtain sufficient information of their structure at the atomic level in order to understand reaction mechanisms. In this work, a SAC was prepared by grafting a molecular cobalt catalyst on a light-absorbing carbon nitride surface. Due to the sensitivity of the X-ray absorption near edge structure (XANES) spectra to subtle variances in the Co SAC structure in reaction conditions, different machine learning (ML) methods, including principal component analysis, K-means clustering, and neural network (NN), were utilized for in situ Co XANES data analysis. As a result, we obtained quantitative structural information of the SAC nearest atomic environment thereby extending the NN-XANES approach previously demonstrated for nanoparticles and size-selective clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Characterization of zirconium carbide microspheres synthesized via internal gelation

Microspheres of zirconium carbide with grain size 40-320 nm were synthesized using internal gelation techniques and characterized by scanning electron microscopy, synchrotron X-ray diffraction, and neutron total scattering. Compared with a polycrystalline benchmark ZrC sample prepared by plasma vapor phase deposition, the microspheres display lower variance in grain size and considerably lower microstrain representative of a more homogenous internal microstructure. However, excess carbon was present in the microspheres, evident in both the X-ray and neutron diffraction data as well as a corresponding hypostoichiometric ZrC phase. Furthermore, the excess carbon phase is assumed to be pockets of carbon that remained unreacted through the combined internal gelation and subsequent carbothermic reduction synthesis process. Atomic-scale structural characterization with neutron PDF analysis confirmed the presence of localized nano-sized domains of graphite-like carbon material.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Understanding Diverse Model Projections of Future Extreme El Niño

The majority of future projections in the Coupled Model Intercomparison Project (CMIP5) show more frequent exceedances of the 5 mm day -1 rainfall threshold in the eastern equatorial Pacific rainfall during El Niño, previously described in the literature as an increase in “extreme El Niño events”; however, these exceedance frequencies vary widely across models, and in some projections actually decrease. Here we combine single-model large ensemble simulations with phase 5 of the Coupled Model Intercomparison Project (CMIP5) to diagnose the mechanisms for these differences. The sensitivity of precipitation to local SST anomalies increases consistently across CMIP-class models, tending to amplify extreme El Niño occurrence; however, changes to the magnitude of ENSO-related SST variability can drastically influence the results, indicating that understanding changes to SST variability remains imperative. Future El Niño rainfall intensifies most in models with 1) larger historical cold SST biases in the central equatorial Pacific, which inhibit future increases in local convective cloud shading, enabling more local warming; and 2) smaller historical warm SST biases in the far eastern equatorial Pacific, which enhance future reductions in stratus cloud, enabling more local warming. Additionally, these competing mechanisms complicate efforts to determine whether CMIP5 models under- or overestimate the future impacts of climate change on El Niño rainfall and its global impacts. However, the relation between future projections and historical biases suggests the possibility of using observable metrics as “emergent constraints” on future extreme El Niño, and a proof of concept using SSTA variance, precipitation sensitivity to SST, and regional SST trends is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Mapping the Binary Covalent Alloy Space to Pursue Superior Nitrogen Reduction Reaction Catalysts

The electrochemical nitrogen reduction reaction (NRR) has the potential to decarbonize industrial ammonia production. However, NRR has poor activity and selectivity versus the competing hydrogen evolution reaction for catalysts that adhere to scaling relations. Overcoming the limitations imposed by scaling relations requires more complex catalyst materials, however, evaluating materials beyond simple metal systems is a large combinatorial problem that requires an improved understanding of the electrocatalyst surface to rationally guide the discovery of superior catalysts. The study uses grand canonical density functional theory to uncover NRR trends on a large and disparate set of binary covalent alloys (BCA) with variable compositions and active-site geometries. The studied BCAs generally follow scaling relations, albeit with larger variance and several systems that significantly break scaling. BCAs with early- to mid-transition metals tend to lie near the volcano peak and activate the N 2 triple bond via a side-on binding configuration. Trends in the BCA space cannot be readily predicted using simple electronic descriptors, which is ascribed to the large geometric variability of the BCA surfaces. Furthermore, it is anticipated that these findings will provide a foundation for the rational design of superior NRR electrocatalysts with increasing material complexity.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Stability-Constrained Learning for Frequency Regulation in Power Grids With Variable Inertia

The increasing penetration of converter-based renewable generation has resulted in faster frequency dynamics, and low and variable inertia. As a result, there is a need for frequency control methods that are able to stabilize a disturbance in the power system at timescales comparable to the fast converter dynamics. This paper proposes a combined linear and neural network controller for inverter-based primary frequency control that is stable at time-varying levels of inertia. We model the time-variance in inertia via a switched affine hybrid system model. We derive stability certificates for the proposed controller via a quadratic candidate Lyapunov function. We test the proposed control on a 12-bus 3-area test network, and compare its performance with a base case linear controller, optimized linear controller, and finite-horizon Linear Quadratic Regulator (LQR). Our proposed controller achieves faster mean settling time and over 50% reduction in average control cost across 100 inertia scenarios compared to the optimized linear controller. Unlike LQR which requires complete knowledge of the inertia trajectories and system dynamics over the entire control time horizon, our proposed controller is real-time tractable, and achieves comparable performance to LQR.

data-driven control↗

DOE OSTI2023

Challenges in practical button cell testing for hydrogen production from high temperature electrolysis of water

High temperature electrolysis of water using solid oxide electrochemical cells (SOEC) is a promising technology for hydrogen production with high energy efficiency and may promote decarbonization when coupled with renewable energy sources and excess heat from nuclear reactors. Over the past several decades there have been extensive scientific and engineering studies on cell materials and degradation behaviors that have greatly improved current density, decreased total resistance, and lowered degradation rates. Although the technology is now at a near-commercial level, maintaining consistency in cell testing and minimizing variance in practical testing environments is an often overlooked but crucial topic. To promote high quality data collection, testing procedures and balance of plant component details are extremely important to consider. This work discusses some key factors affecting the reproducibility of practical SOEC testing on the button cell level, namely, current collection layers, cell sealing procedures, the reliability of steam and hydrogen delivery systems, cell testing fixture design, and reduction procedures. To provide a baseline and a level of standardization for the SOEC community, this work also discloses details of the standard operating procedure and techniques adopted for o-SOEC testing at Idaho National Laboratory (INL).

08 HYDROGEN↗

NASA NTRS1988

Improved Tracking Of Square-Wave Subcarrier

Variance of phase error reduced. Report discusses application of "windowing" concept to improve ability of telemetry receiver to track phase of square-wave phase-modulation subcarrier signal. Concept based on setting phase-tracking signal at zero outside narrow time "windows", reducing noise energy in processed signal. Result is increase in signal-to-noise ratio in tracking loop with consequent increase in accuracy of tracking and reduction in number of errors in telemetric data.

Hurd, William J.↗

NASA NTRS1984

Quick Look Analysis of TM Data of the Washington, District of Columbia Area

A fixed factor analysis-of-variance (ANOVA) approach was used to quantify the impact of each TM sensor characteristic (spectral, spatial, and radiometric resolutions) on classification accuracy. All assessments were made relative to MSS sensor characteristics, and the impact of each characteristic was assessed individually, and in all possible combinations. Thematic Mapper data acquired over the Washington, D.C. area on November 2, 1982 were utilized to conduct the experiment. The following results were obtained: the reduction of quantization level from eight bits to six bits caused a decrease in overall accuracy (7%); the use of only three bands (TM 2, 3 and 4) covering the isible and near infrared portion of the spectrum caused a decrease in overall accuracy (7%); and the decrease in spatial resolution resulted in an increase in overall accuracy (4%). Results indicate that the increased radiometric and spectral resolution of the TM instrument do provide increased information content. The result of the spatial resolution degradation is somewhat misleading, in that the result is more a function of spatial resolution.

Williams, D. L.↗

DOE OSTI2025

BEACON—automated aberration correction for scanning transmission electron microscopy using Bayesian optimization

Aberration correction is an important aspect of modern high-resolution scanning transmission electron microscopy. Most methods of aligning aberration correctors require specialized sample regions and are unsuitable for fine-tuning aberrations without interrupting on-going experiments. Here, we present an automated method of correcting first- and second-order aberrations called BEACON, which uses Bayesian optimization of the normalized image variance to efficiently determine the optimal corrector settings. We demonstrate its use on gold nanoparticles and a hafnium dioxide thin film showing its versatility in nano- and atomic-scale experiments. BEACON can correct all first- and second-order aberrations simultaneously to achieve an initial alignment and first- and second-order aberrations independently for fine alignment. Ptychographic reconstructions are used to demonstrate an improvement in probe shape and a reduction in the target aberration.

techniques and instrumentation↗

NASA NTRS2016

Evaluation of the Effect of Surface Finish on High-Cycle Fatigue of SLM-IN718

The surface finish of parts produced by additive manufacturing processes is much rougher than the surface finish generated by machining processes, and a rougher surface can reduce the fatigue strength of a part. This paper discusses an effort to quantify that reduction of strength in high-cycle fatigue for selective laser melt (SLM) coupons. A high-cycle fatigue (HCF) knockdown factor was estimated for Inconel 718, manufactured with the SLM process. This factor is the percentage reduction from the maximum stress in fatigue for low-stress ground (LSG) specimens to the maximum stress of those left with the original surface condition at the same fatigue life. Specimens were provided by a number of vendors, free to use their "best practice"; only one heat treat condition was considered; and several test temperatures were characterized, including room temperature, 800F, 1000F, and 1200F. The 1000F data had a large variance, and was omitted from consideration in this document. A first method used linear approximations extracted from the graphs, and only where data was available for both. A recommended knockdown factor of the as-built surface condition (average roughness of approximately 245 micro-inches/inch) versus low-stress ground condition (roughness no more than 4 micro-inches/inch) was established at approximately 1/3 or 33%. This is to say that for the as-built surface condition, a maximum stress of 2/3 of the stress for LSG can be expected to produce a similar life in the as-built surface condition. In this first evaluation, the knockdown factor did not appear to be a function of temperature. A second approach, the "KP method", incorporated the surface finish measure into a new parameter termed the pseudo-stress intensity factor, Kp, which was formulated to be similar to the fracture mechanics stress intensity factor. Using Kp, the variance seemed to be reduced across all sources, and knockdown factors were estimated using Kp over the range where data occurred. A plot of the results suggests that the knockdown factor is a function of temperature, and that for low lives the knockdown might be lower than the knockdown observed above about one million cycles, where it tended to stabilize. This was not universal for all temperatures tested. The higher temperature tests are thought to be influenced by the test temperature, which perhaps continued the aging process. Further evaluation of the method is suggested.

Lambert, D. M.↗

NASA NTRS1976

Analytical and experimental design and analysis of an optimal processor for image registration

The author has identified the following significant results. A quantitative measure of the registration processor accuracy in terms of the variance of the registration error was derived. With the appropriate assumptions, the variance was shown to be inversely proportional to the square of the effective bandwidth times the signal to noise ratio. The final expressions were presented to emphasize both the form and simplicity of their representation. In the situation where relative spatial distortions exist between images to be registered, expressions were derived for estimating the loss in output signal to noise ratio due to these spatial distortions. These results are in terms of a reduction factor.

Mcgillem, C. D.↗

NASA NTRS1992

Importance of Geosat orbit and tidal errors in the estimation of large-scale Indian Ocean variations

To improve the estimate accuracy of large-scale meridional sea-level variations, Geosat ERM data on the Indian Ocean for a 26-month period were processed using two different techniques of orbit error reduction. The first technique removes an along-track polynomial of degree 1 over about 5000 km and the second technique removes an along-track once-per-revolution sine wave about 40,000 km. Results obtained show that the polynomial technique produces stronger attenuation of both the tidal error and the large-scale oceanic signal. After filtering, the residual difference between the two methods represents 44 percent of the total variance and 23 percent of the annual variance. The sine-wave method yields a larger estimate of annual and interannual meridional variations.

Perigaud, Claire↗

NASA NTRS2001

The First SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-1)

Four laboratories, which had contributed to various aspects of SeaWiFS calibration and validation activities, participated in the first SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-1): Horn Point Laboratory (USA), the Joint Research Centre (Italy), the Laboratoire de Physique et Chimie Marines (France), and the Marine and Coastal Management group (South Africa). The analyses of the data are presented in Chapter 1 and the individual methods of the four groups are presented in Chapters 2-5. The average (or overall) conclusions of the round-robin are derived from 12 in situ stations occupied during a cruise in the Mediterranean Sea, although, only 11 stations are used in the analyses. The data set is composed of 12 replicates taken during each sampling opportunity with 3 replicates going to each of the 4 laboratories. The average (or overall) results from the intercomparison of 15 pigments or pigment associations are as follows (in some cases, data subsets that exclude pigments which were not analyzed by all the laboratories, or that had unusually large variances, are used to exclude a variety of problematic pigments): a) the accuracy of the four methods in determining the concentration of total chlorophyll a is 7.9%, (one method did not separate mono- and divinyl chlorophyll a, and if the samples containing significant divinyl chlorophyll a concentrations are ignored, the four methods have an accuracy of 6.7%); b) the accuracy in determining the full set of pigments is 19.1%; c) there is a reduction in accuracy of approximately - 12.2% for every decade (factor of 10) decrease in concentration (based on a data subset); d) the precision of the four methods using a subset data is 8.617( 6.2% for an edited subset); e) the repeatability of the four methods using the subset data is 9.2% (7.2%; for an edited subset, and f) the reproducibility of the four methods using the subset data is 21.31% (15.0% for an edited subset).

Hooker, Stanford B.↗

NASA NTRS2016

Simulated Space Radiation: Murine Skeletal Responses During Recovery and with Mechanical Stimulation

Simulated space radiation at doses similar to those of solar particle events or a round-trip sojourn to Mars (1-2Gy) may cause skeletal tissue degradation and deplete stem/progenitor cell pools throughout the body. We hypothesized that simulated space radiation (SSR) causes late, time-dependent deficits in bone structure and bone cell function reflected by changes in gene expression in response to anabolic stimuli. We used a unique sequential dual ion exposure (proton and iron) for SSR to investigate time-dependence of responses in gene expression, cell function, and microarchitecture with respect to radiation and an anabolic stimulus of axial loading (AL). Male 16-wk C57BL6/J mice (n=120 total) were exposed to 0Gy (Sham, n=10), 56Fe (2Gy, positive control dose, n=10), or sequential ions for SSR (1Gy 1H/56Fe/1H, n=10) by total body irradiation (IR), and the tissues were harvested 2 or 6 mo. later. Further, to assess the response to anabolic stimuli, we subjected additional Sham-AL (n=15) and SSR-AL (n=15) groups to rest-inserted tibial axial loading (AL) starting at 1 and 5 months post-IR (-9N, 60 cycles/day, 3 days/wk, 4 wks). Exposure to 56Fe caused a significant reduction in cancellous bone volume fraction (BV/TV) compared to Sham (-34%) and SSR (-20%) in the proximal tibia metaphysis at 2-months post-IR; however BV/TV for SSR group was not different than Sham. Both 56Fe and SSR caused significant reduction in trabecular number (Tb.N) compared to Sham (-33% and -16%, respectively). Further, Tb.N for 56Fe (2Gy) was significantly lower than SSR (-21%). Ex vivo culture of marrow cells to assess growth and differentiation of osteoblast lineage cells 6 months post-IR showed that both 56Fe and SSR exposures significantly impaired colony formation compared to Sham (-66% and -54%, respectively), as well as nodule mineralization (-90% and -51%, respectively). Two-way analysis of variance showed that both mechanical loading and radiation reduced BV/TV, mechanical loading reduced trabecular thickness (Tb.Th), and radiation reduced Tb.N, at both time points. To assess acute response to mechanical stimuli, samples were harvested from a subset of Sham-AL (n=5) and SSR-AL (n=5) to measure changes in gene expression levels. Preliminary results indicate that axial loading increased expression of the antioxidant response gene Nfe2l2 and the osteoprogenitor-associated marker Runx2 in the bone marrow cells, and there was an interaction effect between axial loading and radiation at 2-months post-IR. Additional analyses of gene expression levels in the mineralized tissue are in progress. Results indicate that SSR caused persistent impairment of osteoblast colony formation and nodule mineralization 6-mo post-IR. Contrary to our hypothesis, simulated space radiation did not impair the ability of cancellous bone to respond to a mechanical anabolic stimulus, consistent with our previous findings [1]. Hence, compressive loading may be a potential countermeasure against spaceflight-induced bone loss.

Bone Loss↗

NASA NTRS2016

Simulated Space Radiation: Murine Skeletal Responses During Recovery and with Mechanical Stimulation

Simulated space radiation at doses similar to those of solar particle events or a round-trip sojourn to Mars (1-2Gy) may cause skeletal tissue degradation and deplete stem/progenitor cell pools throughout the body. We hypothesized that simulated space radiation (SSR) causes late, time-dependent deficits in bone structure and bone cell function reflected by changes in gene expression in response to anabolic stimuli. We used a unique sequential dual ion exposure (proton and iron) for SSR to investigate time-dependence of responses in gene expression, cell function, and microarchitecture with respect to radiation and an anabolic stimulus of axial loading (AL). Male 16-wk C57BL6/J mice (n=120 total) were exposed to 0Gy (Sham, n=10), 56Fe (2Gy, positive control dose, n=10), or sequential ions for SSR (1Gy 1H/56Fe/1H, n=10) by total body irradiation (IR), and the tissues were harvested 2 or 6 mo. later. Further, to assess the response to anabolic stimuli, we subjected additional Sham-AL (n=15) and SSR-AL (n=15) groups to rest-inserted tibial axial loading (AL) starting at 1 and 5 months post-IR (-9N, 60 cycles/day, 3 days/wk, 4 wks). Exposure to 56Fe caused a significant reduction in cancellous bone volume fraction (BV/TV) compared to Sham (-34%) and SSR (-20%) in the proximal tibia metaphysis at 2-months post-IR; however BV/TV for SSR group was not different than Sham. Both 56Fe and SSR caused significant reduction in trabecular number (Tb.N) compared to Sham (-33% and -16%, respectively). Further, Tb.N for 56Fe (2Gy) was significantly lower than SSR (-21%). Ex vivo culture of marrow cells to assess growth and differentiation of osteoblast lineage cells 6 months post-IR showed that both 56Fe and SSR exposures significantly impaired colony formation compared to Sham (-66% and -54%, respectively), as well as nodule mineralization (-90% and -51%, respectively). Two-way analysis of variance showed that both mechanical loading and radiation reduced BV/TV, mechanical loading reduced trabecular thickness (Tb.Th), and radiation reduced Tb.N, at both time points. To assess acute response to mechanical stimuli, samples were harvested from a subset of Sham-AL (n=5) and SSR-AL (n=5) to measure changes in gene expression levels. Preliminary results indicate that axial loading increased expression of the antioxidant response gene Nfe2l2 and the osteoprogenitor-associated marker Runx2 in the bone marrow cells, and there was an interaction effect between axial loading and radiation at 2-months post-IR. Additional analyses of gene expression levels in the mineralized tissue are in progress. Results indicate that SSR caused persistent impairment of osteoblast colony formation and nodule mineralization 6-mo post-IR. Contrary to our hypothesis, simulated space radiation did not impair the ability of cancellous bone to respond to a mechanical anabolic stimulus, consistent with our previous findings. Hence, compressive loading may be a potential countermeasure against spaceflight-induced bone loss.

MURINE SKELETAL↗

NASA NTRS2002

Mountain-Top-to-Mountain-Top Optical Link Demonstration

A mountain-top-to-mountain-top optical link was demonstrated between JPL's Table Mountain Facility (TMF), Wrightwood, California, and Strawberry Peak (SP), Lake Arrowhead, California, during the months of June, August, and September of 2000. The bidirectional laser link was nearly horizontal at an altitude of 2 km and spanned a range of 46.8 km. The 780-nm beacon laser transmitted from TMF comprised eight co-propagating mutually incoherent laser beams. The normalized variance or scintillation index (SI) of the individual beacon lasers measured by recording the signal received through 8.50-cm-diameter spotting telescopes on three different nights (June 28-30, 2000) was 1.05 +/- 0.2, 1.76 +/- 0.6, and 0.96 +/- 0.24, respectively. These measurements agreed with values predicted by a heuristic model. The SI of the signal received at SP was found to decrease progressively with an increasing number of beams, and a factor of 3 to 3.5 reduction was achieved for all eight beams. The beam divergence determined by mapping out the point spread function of a few of the individual laser footprints received at SP was 85 to 150 microrad, compared to a design goal of 120 microrad. The 852-nm communications laser beam received at TMF through a 60-cm-diameter telescope on the nights of August 4 and September 14 and 15, 2000, yielded SI values of 0.23 +/- 0.04, 0.32 +/- 0.01, and 0.49 +/- 0.18, respectively, where the reduction was attributed to aperture averaging. The probability distribution functions of the received signal at either end, mitigated by multi-beam averaging in one direction and by aperture averaging in the other direction, displayed lognormal behavior. Consequently, the measured fade statistics showed good agreement with a lognormal model.

Biswas, A.↗

DOE OSTI2022

Monitoring the propagation of mechanical discontinuity using data-driven causal discovery and supervised learning

Mechanical wave transmission through a material is influenced by the mechanical discontinuity in the material. The propagation of embedded discontinuities can be monitored by analyzing the wave-transmission measurements recorded by a multipoint sensor system placed on the surface of the material. The proposed workflow monitors the propagation of mechanical discontinuity through three stages, namely initial, intermediate, and final stages, by using supervised learning followed by data-driven causal discovery. To the end, the workflow processes the multipoint waveform measurements resulting from a single impulse source, while considering the effects of wave attenuation, dispersion and multiple wave-propagation modes due to the discontinuity and material boundaries. Among various feature reduction techniques ranging from decomposition methods to manifold approximation methods, the features derived based on statistical parameterizations of the measured waveforms lead to reliable monitoring that is robust to changes in precision, resolution, and signal-to-noise ratio of the multipoint sensor measurements. The numbers of zero-crossing, negative-turning, and positive turning in the waveforms are the strongest causal signatures of the propagation of mechanical discontinuity. Higher order moments of the waveforms, such as variance, skewness and kurtosis, are also strong causal signatures of the propagation. Finally, the newly discovered causal signatures confirm that the statistical correlations and conventional feature rankings are not always statistically significant indicators of causality.

42 ENGINEERING↗