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At least 253 records · Page 14

TRUST Sensors in Environments: Fiber Optic Displacement (SE-FOD)

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to the development, on-target assessment, and qualification of current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Under the TRUST work package, engineers use and provide feedback on analysis tools and experimental results and create databases for efficient and responsive engineering which are currently under development.

42 ENGINEERING↗

TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY25

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments [1]. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline collaboration to provide engineers with experience in both numerical simulations and experimental methods. This work uses and provides feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development.

42 ENGINEERING↗

Using Ultrasound Image Augmentation and Ensemble Predictions to Prevent Machine-Learning Model Overfitting

Deep learning predictive models have the potential to simplify and automate medical imaging diagnostics by lowering the skill threshold for image interpretation. However, this requires predictive models that are generalized to handle subject variability as seen clinically. Here, we highlight methods to improve test accuracy of an image classifier model for shrapnel identification using tissue phantom image sets. Using a previously developed image classifier neural network—termed ShrapML—blind test accuracy was less than 70% and was variable depending on the training/test data setup, as determined by a leave one subject out (LOSO) holdout methodology. Introduction of affine transformations for image augmentation or MixUp methodologies to generate additional training sets improved model performance and overall accuracy improved to 75%. Further improvements were made by aggregating predictions across five LOSO holdouts. This was done by bagging confidences or predictions from all LOSOs or the top-3 LOSO confidence models for each image prediction. Top-3 LOSO confidence bagging performed best, with test accuracy improved to greater than 85% accuracy for two different blind tissue phantoms. This was confirmed by gradient-weighted class activation mapping to highlight that the image classifier was tracking shrapnel in the image sets. Overall, data augmentation and ensemble prediction approaches were suitable for creating more generalized predictive models for ultrasound image analysis, a critical step for real-time diagnostic deployment.

60 APPLIED LIFE SCIENCES↗

Overview of the Tolerance Limit Calculations with Application to TSURFER

To establish confidence in the results of computerized physics models, a key regulatory requirement is to develop a scientifically defendable process. The methods employed for confidence, characterization, and consolidation, or C3, are statistically involved and are often accessible only to avid statisticians. This manuscript serves as a pedagogical presentation of the C3 process to all stakeholders—including researchers, industrial practitioners, and regulators—to impart an intuitive understanding of the key concepts and mathematical methods entailed by C3. The primary focus is on calculation of tolerance limits, which is the overall goal of the C3 process. Tolerance limits encode the confidence in the calculation results as communicated to the regulator. Understanding the C3 process is especially critical today, as the nuclear industry is considering more innovative ways to assess new technologies, including new reactor and fuel concepts, via an integrated approach that optimally combines modeling and simulation and minimal targeted validation experiments. This manuscript employs intuitive, analytical, numerical, and visual representations to explain how tolerance limits may be calculated for a wide range of configurations, and it also describes how their values may be interpreted. Various verification tests have been developed to test the calculated tolerance limits and to help delineate their values. The manuscript demonstrates the calculation of tolerance limits for TSURFER, a computer code developed by the Oak Ridge National Laboratory for criticality safety applications. The goal is to evaluate the tolerance limit for TSURFER-determined criticality biases to support the determination of upper, subcritical limits for regulatory purposes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Characterization of the Atmosphere of Super-Earth 55 Cancri e Using High-resolution Ground-based Spectroscopy

The nearby super-Earth 55 Cnc e orbits a bright (V = 5.95 mag) star with a period of -18 hr and a mass of -8M {sub ⊕}. Its atmosphere may be water-rich and have a large-scale height; though, attempts to characterize it have yielded ambiguous results. Here we present a sensitive search for water and TiO in its atmosphere at high spectral resolution using the Gemini North telescope and the GRACES spectrograph. We combine observations with previous observations from Subaru and CFHT, improving the constraints on the presence of water vapor. We adopt parametric models with an updated planet radius based on recent measurements, and use a cross-correlation technique to maximize sensitivity. Our results are consistent with atmospheres that are cloudy or contain minimal amounts of water and TiO. Using these parametric models, we rule out a water-rich atmosphere (VMR ≥ 0.1%) with a mean molecular weight of ≤ 15 g mol{sup -1} at a 3σ confidence level, improving on the previous limit by a significant margin. For TiO, we rule out a mean molecular weight of ≤ 5 g mol{sup -1} with a 3σ confidence level for a VMR greater than 10{sup -8}; for a VMR of greater than 10{sup -7}, the limit rises to a mean molecular weight of ≤ 10 g mol{sup -1}. We can rule out low mean-molecular-weight chemical equilibrium models both including and excluding TiO/VO at very high confidence levels (>10σ). Overall, our results are consistent with an atmosphere with a high mean molecular weight and/or clouds, or no atmosphere.

79 ASTRONOMY AND ASTROPHYSICS↗

Radial Segregation between Red Giant Populations in the Globular Cluster NGC 3201: Tentative Role of Varying Mass among the Progenitors

In the globular cluster NGC 3201, we study subpopulations (SPs) of red giants (RGs) distinguished by their characteristics. In its central part, we make use of multicolor Hubble Space Telescope (HST) photometry coupled with spectroscopy of RGs spread out over a larger cluster face. In the color index CI = (m{sub F275W}−m{sub F336W}) −(m{sub F336W}−m{sub F439W}), RGs commonly referred to as first generation, SPI, are separated from the counterparts of the second generation, SPII. The latter are more concentrated than the former at a confidence level of P = 93%, within the field covered by the HST photometry. Their minor portion (∼28%, SPIIm) located in the middle of the δCI range spanned across the split RG branch relative to the splitting edge is more centrally concentrated at a higher confidence level of 96%. We found, from the [Na/Fe]−δCI plot for RGs in common between the photometry and spectroscopy, that SPI and SPII are mostly overlapped within 0.0 < [Na/Fe] < 0.3. RGs with [Na/Fe] < 0.0 (mostly SPI) keep their lower concentration to the cluster center over larger radial distance as compared to SPII RGs with [Na/Fe] > 0.3 at a confidence level of P = 88%. It is increased up to 95% if a restriction on [O/Fe] is imposed. The obtained result, particularly in the central part, is a clue that SPIIm RGs are the descendants of more massive progenitors. Of these RGs approximately one-third probably originate from recent (within the past 1.5 Gyr) blue stragglers with M {sub BS} > 1.1M {sub ☉}, and the other two-thirds could be accounted for by older collision products of primordial MS stars.

47 OTHER INSTRUMENTATION↗

Data from: Comparing traditional and Bayesian approaches to ecological meta-analysis

Despite the wide application of meta-analysis in ecology, some of the traditional methods used for meta-analysis may not perform well given the type of data characteristic of ecological meta-analyses. We reviewed published meta-analyses on the ecological impacts of global climate change, evaluating the number of replicates used in the primary studies (ni) and the number of studies or records (k) that were aggregated to calculate a mean effect size. We used the results of the review in a simulation experiment to assess the performance of conventional frequentist and Bayesian meta-analysis methods for estimating a mean effect size and its uncertainty interval. Our literature review showed that ni and k were highly variable, distributions were right-skewed, and were generally small (median ni =5, median k=44). Our simulations show that the choice of method for calculating uncertainty intervals was critical for obtaining appropriate coverage (close to the nominal value of 0.95). When k was low (<40), 95% coverage was achieved by a confidence interval based on the t-distribution that uses an adjusted standard error (the Hartung-Knapp-Sidik-Jonkman, HKSJ), or by a Bayesian credible interval, whereas bootstrap or z-distribution confidence intervals had lower coverage. Despite the importance of the method to calculate the uncertainty interval, 39% of the meta-analyses reviewed did not report the method used, and of the 61% that did, 94% used a potentially problematic method, which may be a consequence of software defaults. In general, for a simple random-effects meta-analysis, the performance of the best frequentist and Bayesian methods were similar for the same combinations of factors (k and mean replication), though the Bayesian approaches had higher than nominal (>95%) coverage for the mean effect when k was very low (k<15). Our literature review suggests that many meta-analyses that used z-distribution or bootstrapping confidence intervals may have over-estimated the statistical significance of their results when the number of studies was low; more appropriate methods need to be adopted in ecological meta-analyses.

54 ENVIRONMENTAL SCIENCES↗

A comprehensive and synthetic dataset for global, regional, and national greenhouse gas emissions by sector 1970–2018 with an extension to 2019

To track progress towards keeping global warming well below 2 °C or even 1.5 °C, as agreed in the Paris Agreement, comprehensive up-to-date and reliable information on anthropogenic emissions and removals of greenhouse gas (GHG) emissions is required. Here we compile a new synthetic dataset on anthropogenic GHG emissions for 1970–2018 with a fast-track extension to 2019. Our dataset is global in coverage and includes CO 2 emissions, CH 4 emissions, N 2 O emissions, as well as those from fluorinated gases (F-gases: HFCs, PFCs, SF 6 , NF 3 ) and provides country and sector details. We build this dataset from the version 6 release of the Emissions Database for Global Atmospheric Research (EDGAR v6) and three bookkeeping models for CO 2 emissions from land use, land-use change, and forestry (LULUCF). We assess the uncertainties of global greenhouse gases at the 90 % confidence interval (5th–95th percentile range) by combining statistical analysis and comparisons of global emissions inventories and top-down atmospheric measurements with an expert judgement informed by the relevant scientific literature. We identify important data gaps for F-gas emissions. The agreement between our bottom-up inventory estimates and top-down atmospheric-based emissions estimates is relatively close for some F-gas species (~ 10 % or less), but estimates can differ by an order of magnitude or more for others. Our aggregated F-gas estimate is about 10 % lower than top-down estimates in recent years. However, emissions from excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are cumulatively larger than the sum of the reported species. Using global warming potential values with a 100-year time horizon from the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), global GHG emissions in 2018 amounted to 58 ± 6.1 GtCO 2 eq. consisting of CO 2 from fossil fuel combustion and industry (FFI) 38 ± 3.0 GtCO 2 , CO 2 -LULUCF 5.7 ± 4.0 GtCO 2 , CH 4 10 ± 3.1 GtCO 2 eq., N2O 2.6 ± 1.6 GtCO 2 eq., and F-gases 1.3 ± 0.40 GtCO 2 eq. Initial estimates suggest further growth of 1.3 GtCO 2 eq. in GHG emissions to reach 59 ± 6.6 GtCO 2 eq. by 2019. Our analysis of global trends in anthropogenic GHG emissions over the past 5 decades (1970–2018) highlights a pattern of varied but sustained emissions growth. There is high confidence that global anthropogenic GHG emissions have increased every decade, and emissions growth has been persistent across the different (groups of) gases. There is also high confidence that global anthropogenic GHG emissions levels were higher in 2009–2018 than in any previous decade and that GHG emissions levels grew throughout the most recent decade. While the average annual GHG emissions growth rate slowed between 2009 and 2018 (1.2 % yr –1 ) compared to 2000–2009 (2.4 % yr –1 ), the absolute increase in average annual GHG emissions by decade was never larger than between 2000–2009 and 2009–2018. Our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. There are a number of countries that have reduced GHG emissions over the past decade, but these reductions are comparatively modest and outgrown by much larger emissions growth in some developing countries such as China, India, and Indonesia. There is a need to further develop independent, robust, and timely emissions estimates across all gases. As such, tracking progress in climate policy requires substantial investments in independent GHG emissions accounting and monitoring as well as in national and international statistical infrastructures. The data associated with this article (Minx et al., 2021) can be found at https://doi.org/10.5281/zenodo.5566761.

54 ENVIRONMENTAL SCIENCES↗

Screening and Brief Interventions for Alcohol Use During Pregnancy: Practices Among US Primary Care Clinicians, DocStyles 2019

Alcohol use during pregnancy can cause birth defects and developmental disabilities. From 2018 through 2020, 13.5% of pregnant women reported current drinking. The US Preventive Services Task Force recommends evidence-based tools (eg, AUDIT-C and SASQ) for implementing screening and brief interventions to reduce excessive alcohol use among adults, including pregnant people, for whom any alcohol use is considered excessive. We used DocStyles 2019 data to conduct a cross-sectional analysis to examine current screening and brief intervention practices that primary care clinicians conduct among pregnant patients; clinicians’ confidence levels in conducting screening, brief interventions, and referral to treatment; and the documentation of brief interventions in the medical record. A total of 1,500 US adult medicine clinicians completed the entire survey. Among the respondents who conduct screening (N = 1,373) and brief interventions (N = 1,357) in their practice, nearly all reported implementing screening (94.6%) and brief interventions (94.9%) with their pregnant patients for alcohol use, but fewer than half felt confident about conducting their screening practices (46.5%). Two-thirds (64%) reported using a tool that met the criteria recommended by the US Preventive Services Task Force (USPSTF). Over half documented brief interventions in electronic health record notes (51.7%) or designated space (50.7%). Pregnancy presents a unique opportunity for clinicians to incorporate screening into routine obstetric care and encourage behavior change among patients. Most providers reported always screening their pregnant patients for alcohol use, but fewer used evidence-based USPSTF-recommended screening tools. Increased clinician confidence in screening and brief intervention, the use of standardized screening tools tailored to pregnant people, and maximal use of electronic health record technology may enhance the benefits of their application to alcohol use, which ultimately can reduce adverse outcomes associated with alcohol use during pregnancy.

60 APPLIED LIFE SCIENCES↗

Determining Normal-Distribution Tolerance Bounds Graphically

Graphical method requires calculations and table lookup. Distribution established from only three points: mean upper and lower confidence bounds and lower confidence bound of standard deviation. Method requires only few calculations with simple equations. Graphical procedure establishes best-fit line for measured data and bounds for selected confidence level and any distribution percentile.

Mezzacappa, M. A.↗

Forced convection heat transfer to air/water vapor mixtures

Heat transfer coefficients were measured using both dry and humid air in the same forced convection cooling scheme and were compared using appropriate nondimensional parameters (Nusselt, Prandtl and Reynolds numbers). A forced convection scheme with a complex flow field, two dimensional arrays of circular jets with crossflow, was utilized with humidity ratios (mass ratio of water vapor to air) up to 0.23. The dynamic viscosity, thermal conductivity and specific heat of air, steam and air/steam mixtures are examined. Methods for determining gaseous mixture properties from the properties of their pure components are reviewed as well as methods for determining these properties with good confidence. The need for more experimentally determined property data for humid air is discussed. It is concluded that dimensionless forms of forced convection heat transfer data and empirical correlations based on measurements with dry air may be applied to conditions involving humid air with the same confidence as for the dry air case itself, provided that the thermophysical properties of the humid air mixtures are known with the same confidence as their dry air counterparts.

Richards, D. R.↗

A modified VAPEPS method for predicting vibroacoustic response of unreinforced mass loaded honeycomb panels

VAPEPS (VibroAcoustic Payload Environment Prediction System) is a computer program used to predict the vibroacoustic response of a structure. An alternate VAPEPS modeling technique, the Modified NASA Lewis Method, is an improvement for modeling unreinforced mass loaded honeycomb panels. The Modified NASA Lewis Method prediction is compared to the standard ASMS VAPEPS prediction, and the acoustic test data for three spacecraft panels. An analytical method of computing variance is presented and used to compute 95 percent confidence levels. These levels are compared to the standard VAPEPS confidence levels and to the envelope of the test data. As a result of using the new methodology suggested in the paper, both the mean prediction and the 95 percent confidence level prediction agree well with the test data in both spectral shape and magnitude. Therefore, the Modified NASA Lewis Method prediction methodology may be used to define more realistic random vibration test levels.

Mcnelis, Mark E.↗

Pivotal-Function Assessment Of Reliability Of Software

Approach developed to establish utility of pivotal functions for estimation and prediction of reliability of software. Improved estimates of reliability with statistical confidence obtained when relatively few testing data available. Pivotal functions effective tools for determination of confidence limits for reliability of software and prediction limits for time to next failure. Provides exact confidence and prediction limits regardless of how many bugs found in software.

Hayhurst, Kelly J.↗

A modified VAPEPS method for predicting vibroacoustic response of unreinforced mass loaded honeycomb panels

VAPEPS (vibroAcoustic Payload Environment Prediction System) is a computer program used to predict the vibroacoustic response of a structure. An alternate VAPEPS modeling technique, the Modified NASA Lewis Method, is an improvement for modeling unreinforced mass loaded honeycomb panels. The Modified NASA Lewis Method prediction is compared to the standard ASMS VAPEPS prediction, and the acoustic test data for three spacecraft panels. An analytical method of computing variance is presented and used to compute 95 percent confidence levels. These levels are compared to the standard VAPEPS confidence levels and to the envelope of the test data. As a result of using the new methodology suggested in the paper, both the mean prediction and the 95 percent confidence level prediction agree well with the test data in both spectral shape and magnitude. Therefore, the Modified NASA Lewis Method prediction methodology may be used to define more realistic random vibration test levels.

Mcnelis, Mark E.↗

A classification of the galaxy groups

A statistical criterion has been proposed to reveal the random and physical clusterings among stars, galaxies and other objects. This criterion has been applied to the galaxy triples of the list by Karachentseva, Karaschentsev and Scherbanovsky, and the double galaxies of the list by Dahari where the primary components are the Seyfert galaxies. The confident physical, probable physical, probable optical and confident optical groups have been identified. The limit difference of radial velocities of components for the confident physical multiple galaxies has also been estimated.

Anosova, Joanna P.↗

A comment on the suspected solar neutrino -- solar activity connection

Recently, it has been proposed that there exists a highly statistically significant (at greater than or equal to 98% level of confidence) relationship between Ar-37 production rate (namely, solar neutrinos) and the Ap geomagnetic index (namely, solar particles), based on the chi-square goodness-of-fit test and correlation analysis, for the interval 1970-1990. While a relationship between the two parameters, indeed, seems to be discernible, the strength of the relationship has been overstated. Instead of being significant at the afore-mentioned level of confidence, the relationship is found to be significant at only greater than or equal to 95% level of confidence, based on Yates' modification to the chi-square test for 2 x 2 contingency tables. Likewise, while correlation analysis yields a value of r = 0.2691, it is important to note that such a value suggests that only about 7% of the variance can be 'explained' by the inferred correlation and that the remaining 93% of the variance must be attributed to other sources.

Wilson, Robert M.↗

Absorption in X-ray spectra of high-redshift quasars

We present evidence that X-ray absorption is common in high-redshift quasars. We have studied six high-redshift (z approximately 3) quasars with the ROSAT Position Sensitive Proportional Counter (PSPC) of which four are in directions of low Galactic N(sub H). Three out of these four show excess absorption, while only three in approximately 50 z approximately less than 0.4 quasars do, indicating that such absorption must be common, but not ubiquitous, at high redshifts, and that the absorbers must lie at z greater than 0.4. The six quasars were: S5 0014+81, Q0420-388, PKS 0438-436, S4 0636+680. PKS 2000-330, PKS 2126-158, which have redshifts between 2.85 and 3.78. PKS 0438-436 and PKS 2126-158 show evidence for absorption above the local Galactic value at better than 99.999% confidence level. If the absorber is at the redshift of the quasar, then values of N(sub H) = (0.86(+0.49, -0.28)) x 10(exp 22) atoms/sq cm for PKS 0438-436, and N(sub H) = (1.45(+1.20, -0.64)) x 10(exp 22) atoms/ sq cm for PKS 2126-158, are implied, assuming solar abundances. The spectrum of S4 0636+680 also suggests the presence of a similarly large absorption column density at the 98% confidence level. This absorption reverses the trend for the most luminous active galactic nuclei (AGN) to have the least X-ray absorption, so a new mechanism is likely to be responsible. Intervening absorption due to damped Lyman(alpha) systems is a plausible cause. We also suggest, as an intrinsic model, that intracluster material, e.g., a cooling flow, around the quasar could account for both the X-ray spectrum and other properties of these quasars. All the quasars are radio-loud and three are gigahertz peaked (two of the three showing absorption). No excess absorption above the Galactic value is seen toward Q0420-388. This quasar has two damped Lyman(alpha) systems at z = 3.08. The limit on the X-ray column density implies a low ionization fraction, N(H I)/N(H) approximately greater than 4 x 10(exp -3) (3 (sigma)), for solar abundances, for these systems, and can set a weak limit on the size of the absorber. In the emitted frame these PSPC spectra cover the band approximately 0.5-10 keV, which has been well observed for low-redshift quasars and AGN. Comparison of high and low-redshift spectra in this emitted band shows no change of mean spectral index greater than Delta alpha(sub E) greater than 0.3 (99% confidence) with either redshift or luminosity, for radio-loud quasars.

Elvis, Martin↗

A Comment on the Suspected Solar Neutrino-Solar Activity Connection

Recently, it has been proposed that there exists a highly statistically significant (at greater than or equal to 98% level of confidence) relationship between Ar-37 production rate (viz., solar neutrinos) and the Ap geomagnetic index (viz., solar particles), based on the (chi)-square goodness-of-fit test and correlation analysis, for the interval 1970-1990. While a relationship between the two parameters, indeed, seems to be discernible, the strength of the relationship has been overstated. Instead of being significant at the afore-mentioned level of confidence, the relationship is found to be significant at only greater than or equal to 95% level of confidence, based on Yates' modification to the (chi)-square test for 2 x 2 contingency tables. Likewise, while correlation analysis yields a value of r = 0.2691, it is important to note that such a value suggests that only about 7% of the variance can be 'explained' by the inferred correlation and that the remaining 93% of the variance must be attributed to other sources.

Wilson, Robert M.↗