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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Inverse sequential detection of parameter changes in developing time series

Progressive values of two probabilities are obtained for parameter estimates derived from an existing set of values and from the same set enlarged by one or more new values, respectively. One probability is that of erroneously preferring the second of these estimates for the existing data ('type 1 error'), while the second probability is that of erroneously accepting their estimates for the enlarged test ('type 2 error'). A more stable combined 'no change' probability which always falls between 0.5 and 0 is derived from the (logarithmic) width of the uncertainty region of an equivalent 'inverted' sequential probability ratio test (SPRT, Wald 1945) in which the error probabilities are calculated rather than prescribed. A parameter change is indicated when the compound probability undergoes a progressive decrease. The test is explicitly formulated and exemplified for Gaussian samples.

Radok, Uwe↗
NASA NTRS1993

Geochemical evidences for two chondritic-like cometary or asteroidal impacts before and at the K/T boundary

A number of geological and palaeontological evidences support multiple impacts of cometary showers within a short time (approximately 1-3 Ma) and their connection with mass extinctions. Observations include clustered crater ages, stratigraphic horizons of impact ejecta closely spaced in time, and evidence for stepwise mass extinctions spanning intervals of 1-3 Ma. For the K/T boundary, three candidates, Popigai, Manson, and Yucatan, have been proposed as impact craters. Two distinct strata at the K/T boundary in western North America have been interpreted as evidence for two sequential impacts. If multiple impacts occurred within a time span of about 1 Ma then multiple Ir enrichments should be observed. DSDP Hole 577B on the Shatsky Plateau in the northern Pacific at K/T time is the first site. Samples contain approximately greater than 97 percent CaCO3, which exhibit clear chemical signals associated with asteroidal/cometary impact. Ir, Fe, and Cr data are presented. From the Th-normalized data, two satellite peaks below the major peak at 78 cm and 81 cm of 577B-1-4 are clearly shown. The major Ir peak (K/T boundary) is at 72 cm. Fe and Cr, from C1-like impactor ejecta fallout, also show two peaks at the same positions. For hole 738C on the southern Kerguelen Plateau, Ir values reach a peak concentration of 18 ppb in the clay layer at 96.0-96.2 cm in section 20R-5, and gradually tail off. In the sample 115 cm above the boundary, Ir concentrations have still not reached background levels. From the Ir peak downward to the lowermost sample analyzed at 102 cm, the Ir concentration is still as high as 1.7 ppb. From the Th-normalized data, we observe a small Ir/Th peak at 100-101 cm. Though this peak is within the error margin, the trend is clear. Fe and Cr exhibit the same pattern. The third case is Hole 690C on the Queen Maud Ridge. Again, the Ir/Th plot indicates the strong possibility of satellite peaks at approximately 52 cm. The main peak is at 39-40 cm. For the Stevns Klint K/T boundary layers, the stratification of trace elements appears threefold with peak concentrations in sublayers A1, A3, and B2 for different element groups, including Ir. C1 ratios for many siderophile elements found in combined layers III and IV, corresponding to layers A, B, C, and D, strongly support the impact hypothesis. Also, multiple Ir anomalies in the K/T section at Lattengebirge, Bavarian Alps are reported. Recent works on Ni-rich spinels and Ir at the K/T boundaries clearly establish cometary/asteroidal impacts at the K/T boundary. Lastly, cometary showers can explain the enhanced Ir contents over approximately a 1 Ma interval in Gubbio shales.

Liu, Y.-G.↗
NASA NTRS2000

Assessment of Countermeasure Efficacy for Long-Term Space Missions

One of the main functions of the upcoming International Space Station (ISS) will be to provide a venue for testing proposed countermeasures for their ability to protect humans from the debilitating effects of longterm space flight. However, several limiting factors preclude an evaluation process similar to that used in clinical trials which traditionally are implemented with large sample sizes of subjects, including control groups, and with blind or double-blind application of treatments according to factorial or other balanced experimental designs. In particular, only very limited numbers of human subjects will be available for actual field testing in the ISS With no more than 125 subjects planned to fly on all ISS missions over 10 years, it is not possible to test extensive combinations of some 15-20 proposed countermeasures. Furthermore because of safety concerns and operational considerations, it is unlikely that anything other than the current best guess at the most effective countermeasure package will ever be used on ISS. In particular, control or placebos will not be allowed. In view of these limitations, historical data and groundbased or animal studies will have to be used to compensate for small sample sizes and lack of controls in the field. As a result, statistical analysis methodology will have to be developed which allows for the integration of these disparate data types into a meaningful evaluation process. The process must be sequential, providing objective rules for deciding through time whether to reject or modify an ineffective countermeasure, or whether to certify one as effective. Additional output should include performance characteristics for all relevant physiological systems, including uncertainty analyses and estimates of accept/reject decision error rates.

Feiveson, Alan H.↗
DOE OSTI2018

Spatial distribution of organic functional groups supported on mesoporous silica nanoparticles (2): a study by 1 H triple-quantum fast-MAS solid-state NMR

The distribution of organic functional groups attached to the surface of mesoporous silica nanoparticles (MSNs) via co-condensation was scrutinized using 1D and 2D 1 H solid-state NMR, including the triple-quantum/single-quantum (TQ/SQ) homonuclear correlation technique. The excellent sensitivity of 1 H NMR and high resolution provided by fast magic angle spinning (MAS) allowed us to study surfaces with very low concentrations of aminopropyl functional groups. The sequential process, in which the injection of tetraethyl orthosilicate (TEOS) into the aqueous mother liquor was followed by dropwise addition of the organosilane precursor, resulted in deployment of organic groups on the surface, which were highly clustered even in a sample with a very low loading of ~0.1 mmol g -1 . The underlying mechanism responsible for clustering could involve fast aggregation of the aminopropyltrimethoxysilane (APTMS) precursor within the liquid phase, and/or co-condensation of the silica-bound molecules. Understanding the deposition process and the resulting topology of surface functionalities with atomic-scale resolution, can help to develop novel approaches to the synthesis of complex inorganic–organic hybrid materials.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Broadband multi-resonant strong field coherence breaking as a tool for single isomer microwave spectroscopy

Using standard hardware available in chirped-pulse Fourier transform microwave (CP-FTMW) spectroscopy, an experimental method is introduced to selectively extract from the microwave spectrum of an otherwise complicated multicomponent mixture a set of transitions due to a single component, thereby speeding spectral assignment. The method operates the broadband chirped-pulse used to excite the sample in the strong-field limit through a combination of high power and control of the sweep rate. A procedure is introduced that leads to selection of three transition frequencies that can be incorporated as a set of resonant sequential single-frequency microwave pulses that follow broadband chirped-pulse excitation, resulting in a reduction in the coherent signal from a set of transitions ascribable to the component of interest. The difference in the CP-FTMW spectrum with and without this set of multi-resonant single-frequency pulses produces a set of transitions that can confidently be assigned to a single component of the mixture, aiding the analysis of its spectrum. In conclusion, the scheme is applied to (i) selectively extract the spectrum of one of five singly 13 C-subsituted isotopologues of benzonitrile in natural abundance, (ii) obtain the microwave spectra of the two structural isomers (E)- and (Z)-phenylvinylnitrile, and (iii) obtain conformer-specific microwave spectra of methylbutyrate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Correlation of Advanced Accelerated Stress Testing with Polyamide-Based Photovoltaic Backsheet Field-Failures

Cracking of polyamide (PA)-based photovoltaic (PV) backsheet materials has been widely reported for field-aged modules. Failure was not detected by conventional accelerated stress tests (ASTs), which lacked the necessary combination of stress factors and/or factor sequences. PA-based AAA backsheet cracking has since been reproduced through combined and sequential stress testing. Planar- and cross-sectional-optical microscopy as well as Fourier-transform Infrared Spectroscopy (FTIR), have been used to elucidate the mechanical and chemical changes which lead to failure of the backsheet. Field-aged backsheet samples demonstrating failure in various climates (including locations in China and Italy) are also analyzed. Through the analysis, a comparison is made between the different stress testing protocols and the field-aged samples to validate relevance of the advanced stress tests. It is shown that the changes induced through combined-accelerated stress testing (C-AST) were most representative of changes induced by the field, supporting the relevance of C-AST and providing validity for the test protocol.

14 SOLAR ENERGY↗
DOE OSTI2015

MO-F-CAMPUS-J-02: Automatic Recognition of Patient Treatment Site in Portal Images Using Machine Learning

Purpose: To investigate the method to automatically recognize the treatment site in the X-Ray portal images. It could be useful to detect potential treatment errors, and to provide guidance to sequential tasks, e.g. automatically verify the patient daily setup. Methods: The portal images were exported from MOSAIQ as DICOM files, and were 1) processed with a threshold based intensity transformation algorithm to enhance contrast, and 2) where then down-sampled (from 1024×768 to 128×96) by using bi-cubic interpolation algorithm. An appearance-based vector space model (VSM) was used to rearrange the images into vectors. A principal component analysis (PCA) method was used to reduce the vector dimensions. A multi-class support vector machine (SVM), with radial basis function kernel, was used to build the treatment site recognition models. These models were then used to recognize the treatment sites in the portal image. Portal images of 120 patients were included in the study. The images were selected to cover six treatment sites: brain, head and neck, breast, lung, abdomen and pelvis. Each site had images of the twenty patients. Cross-validation experiments were performed to evaluate the performance. Results: MATLAB image processing Toolbox and scikit-learn (a machine learning library in python) were used to implement the proposed method. The average accuracies using the AP and RT images separately were 95% and 94% respectively. The average accuracy using AP and RT images together was 98%. Computation time was ∼0.16 seconds per patient with AP or RT image, ∼0.33 seconds per patient with both of AP and RT images. Conclusion: The proposed method of treatment site recognition is efficient and accurate. It is not sensitive to the differences of image intensity, size and positions of patients in the portal images. It could be useful for the patient safety assurance. The work was partially supported by a research grant from Varian Medical System.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1997

Lunar and Planetary Science XXVIII

The present conference discusses such topics as density crossovers in lunar picrites, the geology of the Cassini impact basin, Mars, nanobacteria in carbonates, the properties of shocked aerogels, a chemical model of Comet Halley, lunar mascons, the impact evolution of icy regoliths, the geology of the Venera 8 landing site, the photogeologic mapping of northern Venus, HST observations of Mars, observational constraints on the rotational dynamics of Mars, and primordial magnetic field measurements from the moon. Also discussed are models of the S2 fluorescence spectra of comets, Martian crater ejecta, the heights of Venusian steep-sided domes, cloud-climate interactions on Venus, the Humorum basin geology from Clementine data, an early Amazonian lake in the Gale crater of Mars, nebular fractionations and Mn-Cr systematics, the Rock Chipper planetary surface sample collection, Mariner 10 stereo images of Mercury, remote and local stresses and Calderas on Mars, the electrostatic charging of saltating particles, SO2 detected on Callisto, the Mars Explorer Planetary Data System, an assessment of explosive venting on Europa, the sequential faulting history of the Mars Valles Marineris, a search for Martian sediments, the composition and internal structure of Europa, long-term and 'diurnal' tidal stresses on Europa, and episodic greenhouse climates on Mars.

Source record↗
NASA NTRS2018

Dynamic Adjustment of Simulation Parameters for Efficient Vehicle Prognostics

Model-based diagnostics and prognostics rely on state estimation and uncertainty management algorithms to produce useful information for system operators and maintainers. This information enables more informed operational decisions, condition-based maintenance, and overall mission safety assurance. Typically, uncertainty is associated with vehicle state-of-health estimation and prediction results because of modeling errors, internal or external sources of noise, and sensor inaccuracy. Probabilistic uncertainty management methods including Sequential Monte Carlo simulation are commonly used to reason about state-of-health estimates and predictions in the presence of these sources of uncertainty. However, such algorithms can be computationally expensive as they require a very large number of samples to obtain a sufficiently accurate quantification of the end of life probability distribution. As a result, highly mobile autonomous systems that leverage the prognostic results for mission-level replanning are often constrained in their processing capability because of these computationally expensive simulation approaches. Therefore, in this paper, we investigate algorithmic methods for dynamically adjusting simulation time step as well as number of samples to achieve highly efficient prognostic results while maintaining results accuracy. Results obtained from simulated flight experiments of an electric unmanned aerial vehicle are presented to verify the efficacy of such algorithms.

Prognostics↗
NASA NTRS2008

Preliminary Examination of the Interstellar Collector of Stardust

The findings of the Stardust spacecraft mission returned to earth in January 2006 are discussed. The spacecraft returned two unprecedented and independent extraterrestrial samples: the first sample of a comet and the first samples of contemporary interstellar dust. An important lesson from the cometary Preliminary Examination (PE) was that the Stardust cometary samples in aerogel presented a technical challenge. Captured particles often separate into multiple fragments, intimately mix with aerogel and are typically buried hundreds of microns to millimeters deep in the aerogel collectors. The interstellar dust samples are likely much more challenging since they are expected to be orders of magnitudes smaller in mass, and their fluence is two orders of magnitude smaller than that of the cometary particles. The goal of the Stardust Interstellar Preliminary Examination (ISPE) is to answer several broad questions, including: which features in the interstellar collector aerogel were generated by hypervelocity impact and how much morphological and trajectory information may be gained?; how well resolved are the trajectories of probable interstellar particles from those of interplanetary origin?; and, by comparison to impacts by known particle dimensions in laboratory experiments, what was the mass distribution of the impacting particles? To answer these questions, and others, non-destructive, sequential, non-invasive analyses of interstellar dust candidates extracted from the Stardust interstellar tray will be performed. The total duration of the ISPE will be three years and will differ from the Stardust cometary PE in that data acquisition for the initial characterization stage will be prolonged and will continue simultaneously and parallel with data publications and release of the first samples for further investigation.

Westphal, A. J.↗
DOE OSTI2021

Low soil phosphorus availability triggers maize growth stage specific rhizosphere processes leading to mineralization of organic P

Phosphorus (P) is one of the essential nutrients for all living organisms. High-quality mineral P fertilizer is a finite resource with only an estimated 80-100 years of reserves remaining globally. Both plants and microbes have developed several mechanisms such as secretion of organic acids, acidification of the rhizosphere, and production of extracellular enzymes to enhance the acquisition of P from soils. Increased activity of phosphatase occurs in response to P deficiency as part of P starvation responses which catalyze the hydrolysis of P o from soil organic matter (SOM) and release inorganic P (P i ). However, the specific interactions between plants and microbial communities in the rhizosphere soil triggered by P deficiency are largely unknown. In a greenhouse study we grew maize plants in low and high P containing soils and examined the role of rhizosphere processes on mineralization of organic P (P o ) in soils with low and high P availability and different P speciation 23 (Po dominated versus P i dominated) and determine its effect on plant growth. Plant biomass was determined and rhizosphere soils, and soil samples from pots with and without plants were collected at key vegetative growth stages (VGS). A variety of biogeochemical parameters (e.g. microbial biomass C and P, potential phosphatase activities, plant biomass P, soil P species etc.) were determined using both conventional (sequential chemical extraction) and advanced (e.g. high resolution mass spectrometry (FTICR-MS) and 3129 P solution NMR) techniques. Here, we used phospholipid fatty acid (PLFA) and DNA based microbial community analysis to track changes in microbial community structure and diversity. Low P availability induced changes in biogeochemical processes and microbial community composition in the rhizosphere soils of plants grown in low P containing soil. At early VGS, the plants in low P soil were visually struggling which correlated with greater rhizosphere potential acid phosphatase activity and a reduction in P o fractions. At late VGS, the plants appeared to recover which correlated with a decrease in Meh (III) extractable P, an increase in microbial biomass C and P and greater total P in the plant biomass (roots, shoots and leaves). In high P containing soil, on the other hand, greater P availability masked these rhizosphere processes. Our results confirmed the degradation of SOM and Po mineralization in rhizosphere soils driven by microbe and plant need for P. P deficiency may have favored the abundance of fungi which utilized easily degradable root exudates for the production of extracellular enzymes responsible for the mineralize of SOM P o . This study highlights the intertwined mechanisms involved, and emphasizes the importance of, P o sources for plant nutrition and survival in marginal soils.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Characterization of Modern Spacecraft Materials under Space-simulated Environment

External spacecraft materials play an important role in satellite protection from the harsh space environment. Research has shown that the physical, chemical, and optical properties of matter change continuously as a result of exposure to solar radiation and aggressive chemical species produced in Earth’s upper atmosphere. Thorough knowledge of the material properties evolution throughout a planned mission lifetime helps to improve the reliability of spacecraft. Moreover, the establishment of correlation factors between true space exposure and accelerated space weather experiments at ground facilities enables accurate prediction of on-orbit material performance based on laboratory-based testing. The presented work aims to evaluate the radiation effects of low Earth orbit (LEO) environment, namely, exposure to the high-energy electrons, atomic oxygen (AO), and vacuum ultraviolet (VUV), of several modern spacecraft materials. The studied materials represent the “flight duplicates” of samples that will be launched as a part of the Materials International Space Station Experiment Flight Facility (MISSE-FF) mission in 2022. MISSE-FF flight sample collection comprises different classes of polymers, including polyimides from the Kapton family, manufactured by E.I du Pont de Nemours and Co., Polyethylene terephthalate (PET) materials, liquid crystal polymers, PI/Polyhedral Oligomeric Silsesquioxanes (POSS), and carbon and glass fiber reinforced polymers. A sequential exposure approach was undertaken to allow monitoring of degradation induced by each environmental component (electrons, AO, and VUV) separately. Surface morphology, optical, and charge transport properties of selected materials were characterized using different techniques, namely, atomic force and scanning electron microscopy, ultraviolet visible (UV/Vis) transmission, reflectance, Bidirectional Reflectance Distribution Function (BRDF), and surface potential decay measurements.

Elena Plis↗
DOE OSTI2016

Isotopic determination of uranium in soil by laser induced breakdown spectroscopy

Laser-induced breakdown spectroscopy (LIBS) operated under ambient pressure has been evaluated for isotopic analysis of uranium in real-world samples such as soil, with U concentrations in the single digit percentage levels. The study addresses the requirements for spectral decomposition of 235 U and 238 U atomic emission peaks that are only partially resolved. Although non-linear least-square fitting algorithms are typically able to locate the optimal combination of fitting parameters that best describes the experimental spectrum even when all fitting parameters are treated as free independent variables, the analytical results of such an unconstrained free-parameter approach are ambiguous. In this work, five spectral decomposition algorithms were examined, with different known physical properties (e.g., isotopic splitting, hyperfine structure) of the spectral lines sequentially incorporated into the candidate algorithms as constraints. It was found that incorporation of such spectral-line constraints into the decomposition algorithm is essential for the best isotopic analysis. The isotopic abundance of 235 U was determined from a simple two-component Lorentzian fit on the U II 424.437 nm spectral profile. For six replicate measurements, each with only fifteen laser shots, on a soil sample with U concentration at 1.1% w/w, the determined 235 U isotopic abundance was (64.6 ± 4.8)%, and agreed well with the certified value of 64.4%. Another studied U line - U I 682.691 nm possesses hyperfine structure that is comparatively broad and at a significant fraction as the isotopic shift. Thus, 235 U isotopic analysis with this U I line was performed with spectral decomposition involving individual hyperfine components. For the soil sample with 1.1% w/w U, the determined 235 U isotopic abundance was (60.9 ± 2.0)%, which exhibited a relative bias about 6% from the certified value. The bias was attributed to the spectral resolution of our measurement system - the measured line width for this U I line was larger than its isotopic splitting. In conclusion, although not the best emission line for isotopic analysis, this U I emission line is sensitive for element analysis with a detection limit of 500 ppm U in the soil matrix; the detection limit for the U II 424.437 nm line was 2000 ppm.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Using Flory–Huggins-informed human-in-the-loop Bayesian optimization to map the phase diagram of polymer blends

Mapping the phase diagram of polymer blends is an essential step in controlling the structure–property relationship of polymer-based materials. However, traditional grid-based approaches are inefficient and rely on subjective judgements for terminating the experimental campaign. Artificial intelligence-guided experimentation offers a compelling alternative, especially when data-driven decision-making is interfaced with established polymer thermodynamics to improve efficiency and interpretability. Here, we introduce a physics-informed Bayesian optimization approach to guide the mapping of the phase diagram of a model blend containing poly(methyl methacrylate) and poly(styrene-ran-acrylonitrile). Physical information is derived from a Flory–Huggins representation of the spinodal curve, which is integrated into the Bayesian optimization process as a structured prior mean that acts as a soft constraint. Implemented as a human-in-the-loop workflow, the approach leverages optical imaging of film cloudiness with iterative Gaussian process surrogate modeling and a parameter selection decision policy to identify the composition-temperature conditions for sequential iterations. Convergence of kernel and Flory–Huggins-based hyperparameters provided a stopping criterion, ensuring an objective and interpretable termination of the experimental campaign. The framework recovered the known lower critical solution temperature (∼160 °C), while increasing material efficiency through targeted sampling. This work establishes a proof-of-concept for the application of Bayesian optimization workflows to study polymer blend miscibility.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Electrically driven photon emission from individual atomic defects in monolayer WS 2

Quantum dot–like single-photon sources in transition metal dichalcogenides (TMDs) exhibit appealing quantum optical properties but lack a well-defined atomic structure and are subject to large spectral variability. Here, we demonstrate electrically stimulated photon emission from individual atomic defects in monolayer WS 2 and directly correlate the emission with the local atomic and electronic structure. Radiative transitions are locally excited by sequential inelastic electron tunneling from a metallic tip into selected discrete defect states in the WS 2 bandgap. Coupling to the optical far field is mediated by tip plasmons, which transduce the excess energy into a single photon. The applied tip-sample voltage determines the transition energy. Atomically resolved emission maps of individual point defects closely resemble electronic defect orbitals, the final states of the optical transitions. Inelastic charge carrier injection into localized defect states of two-dimensional materials provides a powerful platform for electrically driven, broadly tunable, atomic-scale single-photon sources.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Machine learning-based inversion for acoustic impedance with large synthetic training data: Workflow and data characterization

Where wells are sparse or training data are difficult to label with high-quality wireline-derived impedance logs, machine learning (ML)-based inversion of acoustic impedance typically depends on small training data sets, leading to biased prediction. We have advanced a novel workflow that applies large synthetic seismic training data to reduce facies-related bias. Using a geologically realistic model as the truth model, we randomly select sparse seed wells to perform sequential Gaussian simulation (SGS) for impedance models of the same geometry and simulate facies variability. We implement random forest regression on 30 features extracted from the synthetic volume. We observe that more seed wells tend to reduce facies-induced bias by sampling more types of facies, resulting in a better prediction. We then focus on the responses of SGS models to facies changes, the number of seed wells necessary for a useful synthetic model, and how much a synthetic model can help ML-based inversion. Here, we observe that the SGS synthetic training model outperforms well-direct training in general. For modeled clastic shore-zone systems in Miocene Gulf of Mexico, two or more seed wells are necessary for a significant reduction of root-mean-square error and outliners, and improvement of facies imaging. In a field-data test, we apply a similar workflow to quantitatively predict acoustic impedance, which is then converted to a sand-volume map at a high-frequency sequence (10–100 m), revealing detailed facies and sandstone patterns. Such results are valuable in many geologic and engineering applications, such as hydrocarbon and CO 2 reservoir prospecting, reserve estimation, simulation, etc.

3D seismic↗
DOE OSTI2017

Speciation of mercury in sludge solids: washed sludge

The objective of this applied research task was to study the type and concentration of mercury compounds found within the contaminated Savannah River Site Liquid Waste System (SRS LWS). A method of selective sequential extraction (SSE), developed by Eurofins Frontier Global Sciences1,2 and adapted by SRNL, utilizes an extraction procedure divided into seven separate tests for different species of mercury. In the SRNL’s modified procedure four of these tests were applied to a washed sample of high level radioactive waste sludge.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗