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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Real-time Ridesharing for Transportation Hubs with Demand and Supply Uncertainty

Transportation hubs in major cities generate a significant amount of trips by taxis and for-hail vehicles (FHV), with many of the trips sharing similar destinations. This suggests promising opportunities to leverage the collective travel needs with dedicated ridesharing solutions to reduce the externalities of excessive traffic at transportation hubs. In this study, we develop a novel dynamic ridesharing approach to serve trips from the transportation hub by considering (1) demand (new passengers) and supply (newly available vehicles) in the near future and (2) the uncertainty of future predictions. Our approach consists of two stages. In the first stage, we develop a data structure called hub mobility tree to generate potential combinations of shareable trips as candidate schedules efficiently. Then the generated schedules are used in the second stage to formulate the stochastic hub-based ridesharing problem (SHRP), which is a stochastic integer programming problem with the objective to maximize the total expected ridesharing profit over time. Due to the prohibitive number of shareable trips, we then approximately solve SHRP by the sample average approximate method (SAA), and a dual Lagrangian technique is implemented to further improve the scalability of the solution approach. We demonstrate the performances of the proposed method by simulating the ridesharing service at JFK airport using NYC taxi and FHV data. The results indicate that the proposed method outperforms the myopic ridesharing (maximize profit for a single time step) and the rolling horizon method with point estimation of future demand and supply.

dynamic ridesharing↗
DOE OSTI2016

Equation of State for Technetium Metal up to 153 GPa

The transition metal, technetium, is a major fission product with a fission yield greater the 6 % for {sup 235}U and as such is found in large quantities in nuclear waste. However, few studies have investigated the behavior of technetium under extreme conditions. Previously, three studies have reported bulk moduli values for technetium metal determined by experimental methods: ultrasonic techniques at ambient pressure, estimated from elastic constants determined from experimental phonon dispersion curves and by high pressure X-ray diffraction. Numerous estimates have been made from computational methods - . The bulk moduli of transition metals is used as a benchmark for validating computation methods. With so little experimental data on technetium, it cannot serve as a useful benchmark. In our previous study the equation of state was measured up to 67 GPa using a 4:1 mixture of methanol-ethanol as the pressure transmitting medium. The non-hydrostatic data produced there resulted in an equation of state defined by B{sub 0} = 288 GPa, and B' = 5.9. Reported here is the high pressure X-ray diffraction measurements made on technetium metal up to a maximum pressure of 153 GPa (1.53 Mbar) and the resulting equation of state. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2017

Generation of an Activation Map for Decommissioning Planning of the Berlin Experimental Reactor-II

The BER-II is an experimental facility with 10 MW that was operated since 1974. Its operation will end in 2019. To support the decommissioning planning, a map with the overall distribution of relevant radionuclides has to be created according to the state of the art. The activation analysis comprises all load periods until the planned shutdown. A procedure for an activation calculation of the pool structure of the BER-II research reactor including the concrete shielding is presented. With the combination of the options offered by MCNP6 and PARTISN, an effective method to compute the neutron flux for a reactor geometry model with 2,790,000 cells could be achieved. The fact that for calculations with PARTISN some extra effort to generate the XS is needed is more than compensated by the fact that for all volumes of the model, neutron fluxes are produced that can be subsequently used for the activation calculation. With the power history provided together with the material compositions, an activation map was created for the whole structure, even for the most remote parts. The activity can be calculated for all nuclides of the FISPACT library. Depending on material and irradiation history, however, only a limited number of nuclides must be regarded to reduce the size of activation data base. The results for the activation at calibration points give an example that the use of detailed calculation methods allows reliable estimation of the activity of relevant nuclides. The mean and the maximum activity can be determined. For a more detailed analysis, it is desirable to provide some more calibration points and realistic material specifications including impurities where the results of the activation can be validated, especially for more remote regions of the concrete structures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Diffractometric method for determining the degree of crystallinity of materials

A new method for determining the degree of crystallinity of a material from X-ray diffraction data has been developed. The method is based on estimating the rate of change in function I = f(2θ) in the entire range of scattering angles. A calculation is performed using the ratio of the integral modulus of the first derivative of intensity with respect to angle 2θ to the integral area under the diffraction pattern curve. The method was tested on two substances with known amorphous and crystalline components. A linear relationship is revealed between the specified ratio of crystalline and amorphous parts and the calculated crystallinity index. The proposed method allows one to estimate impartially and compare the degree of crystallinity for samples of different nature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Estimation of Qualitative and Quantitative Parameters of Air Cleaning by a Pulsed Corona Discharge Using Multicomponent Standard Mixtures

The efficiency of removal of volatile organic impurities in air by a pulsed corona discharge is investigated using model mixtures. Based on the method of competing reactions, an approach to estimating the qualitative and quantitative parameters of the employed electrophysical technique is proposed. The concept of the “toluene coefficient” characterizing the relative reactivity of a component as compared to toluene is introduced. It is proposed that the energy efficiency of the electrophysical method be estimated using the concept of diversified yield of the removal process. Such an approach makes it possible to substantially intensify the determination of energy parameters of removal of impurities and can also serve as a criterion for estimating the effectiveness of various methods in which a nonequilibrium plasma is used for air cleaning from volatile impurities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. Furthermore, the combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The estimation of Poisson’s ratio by time-averaging and Cornu’s method for isotropic beams

Prior research suggests that direct static (e.g., uniaxial testing) and dynamic (e.g., ultrasonic wave propagation analysis) measurements differ in the estimation of Poisson’s ratio because anisotropies and heterogeneities in the sample material affect the two types of tests differently. Even assuming isotropic and homogeneous material properties, prior research further suggests that discrepancies between static/dynamic test results will exist because the error of the diagnostic techniques for the measurand are inherently different. Finally, thermodynamic effects are not present in static tests but can significantly affect dynamic test results. Given the potential for all these variables to produce discrepancies, it would be helpful to have the measurement of Poisson’s ratio obtainable from the same theory and experimental measurements by either static or dynamic testing methods. Our finite element calculations show that by combining time-averaged scanning digital holography with Cornu’s method, it is theoretically possible to estimate the effective Poisson’s ratio from the anticlastic contours at the antinode of the first out-of-plane bending mode shape. This is true regardless of frequency and therefore applicable for both static and dynamic measurements. Our results show that the estimate of Poisson’s ratio by Cornu’s method using data from simulations of mode shapes approaches the true value of Poisson’s ratio. Additionally, our research suggests that beam geometry and boundary conditions are fundamental factors limiting the convergence of the estimate of Poisson’s ratio to the true value of Poisson’s ratio regardless of performing a static or dynamic test.

42 ENGINEERING↗
DOE OSTI2017

NETL CO 2 Storage prospeCtive Resource Estimation Excel aNalysis (CO 2 -SCREEN) User’s Manual

This user’s manual guides the use of the National Energy Technology Laboratory’s (NETL) CO 2 Storage prospeCtive Resource Estimation Excel aNalysis (CO 2 -SCREEN) tool, which was developed to aid users screening saline formations for prospective CO 2 storage resources. CO 2 -SCREEN applies U.S. Department of Energy (DOE) methods and equations for estimating prospective CO 2 storage resources for saline formations. CO 2 -SCREEN was developed to be substantive and user-friendly. It also provides a consistent method for calculating prospective CO 2 storage resources that allows for consistent comparison of results between different research efforts, such as the Regional Carbon Sequestration Partnerships (RCSP). CO 2 -SCREEN consists of an Excel spreadsheet containing geologic inputs and outputs, linked to a GoldSim Player model that calculates prospective CO 2 storage resources via Monte Carlo simulation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Estimation of Syringyl Units in Wood Lignins by FT-Raman Spectroscopy

Syringyl (S) lignin content and the syringyl-to-guaiacyl (S/G) lignin ratio are important characteristics of wood and lignocellulosic biomass. While numerous methods are available for estimating S lignin units and the S/G ratio, in this work, a new method based on Raman spectroscopy that uses the 370 cm –1 Raman band-area intensity (370-area) was developed. The reliability of the Raman method for determining S content was first tested by the quantitative analysis of three syringyl lignin models by sampling them, separately, in dioxane and in Avicel. Good linear correlations between the 370 cm –1 intensity and model concentrations were obtained. Next, the percent syringyl (%S) lignin units in various woods were measured by correlating the 370 cm –1 Raman intensity data with values of S units in lignin determined by three regularly used methods, namely, thioacidolysis, DFRC, and 2D-HSQC NMR. The former two methods take into account only the monomers cleaved from β–O–4-linked lignin units, whereas the NMR method reports S content on the whole cell wall lignin. When the 370-area intensities and %S values from the regularly used methods were correlated, good linear correlations were obtained (R 2 = 0.767, 0.731, and 0.804, respectively, for the three methods). The correlation with the highest R 2 , i.e., with the 2D NMR approach, is introduced for estimating S units in wood lignins by Raman spectroscopy as, in principle, both represent the whole cell wall lignin and not just the portion of lignin that gets cleaved to release monomers. The Raman analysis method is quick, uses minimal harmful chemicals, is carried out nondestructively, and is insensitive to the wet or dry state of the sample. The only limitations are that the sample of wood contains at least 30% S and not be significantly fluorescent, although the latter can be mitigated in some cases.

09 BIOMASS FUELS↗
DOE OSTI2018

Combined Mini-Cylex & Disk Acceleration Tests in Type K Copper

In this work, we combined the miniature cylinder expansion test (Mini-Cylex), with the Disk Acceleration Test (DAX) using Type K copper, Picatinny Liquid Explosive, and photonic Doppler velocimetry. We estimated the CJ state using plate reverberation methods at the test cap. We extracted velocities at 2, 7, and 10 volume expansions to fit Jones-Wilkins-Lee Equation of State and estimated Gurney velocity at the tube wall. The test also provides an additional method to estimate reaction products Hugoniot through knowledge of the copper test cap. Our experiments and simulations are within expected uncertainty. Lastly, the test and the analysis effectively reduce costs while keeping or increasing fidelity.

42 ENGINEERING↗
DOE OSTI2021

Mortality among individuals exposed to atomic bomb radiation in utero: 1950–2012

We examined the mortality risks among 2463 individuals who were exposed in utero to atomic bomb radiation in Hiroshima or Nagasaki in August 1945 and were followed from October 1950 through 2012. Individual estimates of mother’s weighted absorbed uterine dose (DS02R1) were used. Poisson regression method was used to estimate the radiation-associated excess relative risk per Gy (ERR/Gy) and 95% confidence intervals (CI) for cause-specific mortality. Head size, birth weight, and parents’ survival status were evaluated as potential mediators of radiation effect. There were 339 deaths (216 males and 123 females) including deaths from solid cancer (n = 137), lymphohematopoietic cancer (n = 8), noncancer disease (n = 134), external cause (n = 56), and unknown cause (n = 4). Among males, the unadjusted ERR/Gy (95% CI) was increased for noncancer disease mortality (1.22, 0.10–3.14), but not for solid cancer mortality (-0.18,< -0.77–0.95); the unadjusted ERR/Gy for external cause mortality was not statistically significant (0.28, < -0.60–2.36). Among females, the unadjusted ERRs/Gy were increased for solid cancer (2.24, 0.44–5.58), noncancer (2.86, 0.56–7.64), and external cause mortality (2.57, 0.20–9.19). The ERRs/Gy adjusted for potential mediators did not change appreciably for solid cancer mortality, but decreased notably for noncancer mortality (0.39, < -0.43–1.91 for males; 1.48, - 0.046–4.55 for females) and external cause mortality (0.10, < -0.57–1.96 for males; 1.38, < -0.46–5.95 for females). In conclusion, antenatal radiation exposure is a consistent risk factor for increased solid cancer mortality among females, but not among males. The effect of exposure to atomic bomb radiation on noncancer disease and external cause mortality among individuals exposed in utero was mediated through small head size, low birth weight, and parental loss.

Public, Environmental & Occupational Health↗
DOE OSTI2022

Inference, Prediction, & Entropy-Rate Estimation of Continuous-Time, Discrete-Event Processes

Inferring models, predicting the future, and estimating the entropy rate of discrete-time, discrete-event processes is well-worn ground. However, a much broader class of discrete-event processes operates in continuous-time. Here, we provide new methods for inferring, predicting, and estimating them. The methods rely on an extension of Bayesian structural inference that takes advantage of neural network’s universal approximation power. Based on experiments with complex synthetic data, the methods are competitive with the state-of-the-art for prediction and entropy-rate estimation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Centrifuge modeling and numerical analysis on lateral performance of mono-bucket foundation for offshore wind turbines

The lateral loading performance of the mono-bucket foundation for offshore wind turbines is investigated in this study through a series of centrifuge tests and numerical analysis. Six mono-bucket models are considered to assess the influences of aspect ratio under the ultimate condition. The FE model is validated against the centrifuge test results, and the failure mechanism of the foundation is revealed. The parametric study and sensitivity analysis of the soil parameters are performed in the numerical simulations. A modified theoretical calculation method is proposed to estimate the ultimate lateral capacity of the suction bucket foundation by solving the limit equilibrium equations. A correction term is added in the calculation using the “m” method. The position of the rotation center is calculated, demonstrating a better accuracy compared to the previously reported geometric method. The modified calculation method is verified against the field test, the centrifuge test, and the laboratory test. The method is proved to be applicable in estimating the lateral performance of the mono-bucket foundation in a general form. Finally, this study aims to provide well-documented data and design references for practical engineers.

17 WIND ENERGY↗
DOE OSTI2016

Further Investigation of Employing Binomial Small-Sample Estimator in M-LROM

Reduced Order Modeling (ROM) is essential to enable the identification of the so-called active parameter subspace for high-fidelity models that are employed in computationally intensive analyses such as uncertainty characterization and data assimilation. Given the complexity of models for real-world application, brute force methods to identify the active subspace may not be computationally efficient to realize the value of reduction, since in realistic problems, the full scale model must be executed few hundred times, which may be computationally taxing. Earlier work has introduced a new approach, which represents a further development of our previous work on ROM, referred to as multi-level ROM (M-LROM). In M-LROM, approximate models are employed to identify the active subspace instead of the full scale model. In this summary, we present our recent results on M-LROM, specifically in regard to the construction of reliable error metrics that can bound the errors resulting from the reduction. The idea is to employ a lower fidelity model, i.e., an approximation of the full scale or high fidelity model, to build the active subspace, and via the proposed error bound, the quality of the active subspace can be determined by calculating an upper bound on the errors resulting from the reduction. For this approach to be practical, the error bound must be realistic, implying that it should be close to the actual errors expected, and not much higher. Therefore, an important goal of this summary is to compare different error bounds in terms of the relation between their estimated bounds to the actual errors. In particular, we compare the proposed error bound which numerically construct an estimator using binomial distribution to the widely used small-sample norm estimators. Unlike most probabilistic error estimation methods, the proposed bound employs a binomial distribution to construct the estimator whereas in other conventional methods, the distribution employed is typically the standard Gaussian, normalized over a unit hypersphere as initially proposed by the seminal paper of J. Dixon on random matrix theory. Previous publications provided evidence that the binomial distribution calculates more realistic bounds as compared to the Gaussian distribution, which tends to be conservative, implying that the bound is much bigger than the actual errors, which diminishes the value of the reduction, as now must increase the size of the active subspace to reach the desired upper bound on the reduction errors. This work has provided a rigorous approach by which error bounds on the reduction errors can be established without having to execute the high fidelity model during the construction of the active subspace. The high fidelity model is only need to test the error bound using small number of executions. This methodology paves the way for a more efficient application of ROM to complex engineering models, where standard ROM techniques may be too taxing to optimally realize their value in practical situations. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Improved accuracy of quantitative parameter estimates in dynamic contrast-enhanced CT study with low temporal resolution

Purpose: A previously proposed method to reduce radiation dose to patient in dynamic contrast-enhanced (DCE) CT is enhanced by principal component analysis (PCA) filtering which improves the signal-to-noise ratio (SNR) of time-concentration curves in the DCE-CT study. The efficacy of the combined method to maintain the accuracy of kinetic parameter estimates at low temporal resolution is investigated with pixel-by-pixel kinetic analysis of DCE-CT data. Methods: The method is based on DCE-CT scanning performed with low temporal resolution to reduce the radiation dose to the patient. The arterial input function (AIF) with high temporal resolution can be generated with a coarsely sampled AIF through a previously published method of AIF estimation. To increase the SNR of time-concentration curves (tissue curves), first, a region-of-interest is segmented into squares composed of 3 × 3 pixels in size. Subsequently, the PCA filtering combined with a fraction of residual information criterion is applied to all the segmented squares for further improvement of their SNRs. The proposed method was applied to each DCE-CT data set of a cohort of 14 patients at varying levels of down-sampling. The kinetic analyses using the modified Tofts’ model and singular value decomposition method, then, were carried out for each of the down-sampling schemes between the intervals from 2 to 15 s. The results were compared with analyses done with the measured data in high temporal resolution (i.e., original scanning frequency) as the reference. Results: The patients’ AIFs were estimated to high accuracy based on the 11 orthonormal bases of arterial impulse responses established in the previous paper. In addition, noise in the images was effectively reduced by using five principal components of the tissue curves for filtering. Kinetic analyses using the proposed method showed superior results compared to those with down-sampling alone; they were able to maintain the accuracy in the quantitative histogram parameters of volume transfer constant [standard deviation (SD), 98th percentile, and range], rate constant (SD), blood volume fraction (mean, SD, 98th percentile, and range), and blood flow (mean, SD, median, 98th percentile, and range) for sampling intervals between 10 and 15 s. Conclusions: The proposed method of PCA filtering combined with the AIF estimation technique allows low frequency scanning for DCE-CT study to reduce patient radiation dose. The results indicate that the method is useful in pixel-by-pixel kinetic analysis of DCE-CT data for patients with cervical cancer.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Security Analysis of a Class of Spread Spectrum Systems Presentation

A method of adding physical layer security to a class of spread spectrum systems has been recently proposed. In this paper, we look into the rate at which an eavesdropper may gain information about the system to decipher the data symbols. The Shannon mutual information is used to measure the rate of information that may be gained by an eavesdropper. The k-nearest neighbors (k-NN) method is used to obtain estimates of relevant entropy values, which will then be used to quantify the rate of information recovery as more data is transmitted. It turns out that such information recovery requires the adoption of special methods that avoid any destructive bias in the estimates. Details of these methods are also presented.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Multiclass Classification Using Bayesian Multivariate Adaptive Regression Splines

We present a new Bayesian model for the problem of multiclass classification. In this model, the probabilities of class membership of a given observation are determined by the mean of a latent Gaussian distribution. The mean functions of this latent distribution consist of combinations of highly flexible basis functions of the inputs: multivariate adaptive regression splines (MARS), first developed for multiple regression. We use reversible jump Markov chain Monte Carlo to make inference on the classification model, including the number of basis functions. We compare the probabilistic classification performance of our proposed approach to existing methods on simulated and benchmark data, and compare uncertainty estimates on simulated data. Our proposed method compares favorably with existing Bayesian and frequentist multiclass classification methods in out-of-sample probabilistic classification, and uncertainty estimation of these probabilistic classifications. We examine the fit of the proposed method to a data set of hurricane storm surge levels near Delaware Bay, US, and conclude that sea level rise is a key contributor to damage delivered by storm surge.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Regional Input-Output Tables and Trade Flows: an Integrated and Interregional Non-survey Approach

Regional input–output tables and trade flows: an integrated and interregional non-survey approach. Regional Studies. Regional analyses require detailed and accurate information about dynamics happening within and between regional economies. However, regional input–output tables and trade flows are rarely observed and they must be estimated using up-to-date information. Common estimation approaches vary widely but consider tables and flows independently. Here, by using commonly used economic assumptions and available economic information, this paper presents a method that integrates the estimation of regional input–output tables and trade flows across regions. Examples of the method implementation are presented and compared with other approaches, suggesting that the integrated approach provides advantages in terms of estimation accuracy and analytical capabilities.

99 GENERAL AND MISCELLANEOUS↗