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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 19 records

Design, scaling and cost evaluations of circulating fluidized-bed systems for biomass pyrolysis

To generate updated and transparent capital cost estimates for biomass fast pyrolysis equipment, refinery fluidized catalytic cracking design and sizing principles are examined and extended to pyrolysis of woody biomass. Capital costs for the sized equipment are estimated with process-industry software. A one-dimensional flow simulation with pyrolysis kinetics is leveraged to validate the fluidization conditions and thermal energy balance. After successful sizing and a system cost estimate of $\$$2.8 M (in 2016 US$\$$) at the biorefinery scale of 1000 metric tons per day (MTD), these methods were exercised for even smaller equipment at the distributed pyrolysis scale with modifications to the process design constraints, and not directly comparable with the 1000 MTD case, arriving at capital cost estimates of $\$$1.2 M for a 500 ton/day system and $\$$0.9 M for a 200 ton/day system. Here in this work, It is noted that this work only estimates purchased equipment costs at the ±50% accuracy level; there are significant other custom factors applicable to each installation based on location, maturity, scale, complexities during installation, engineering and licensing costs, etc. that need to be added on to these estimates to derive investment costs.

09 BIOMASS FUELS↗

Integrated State Estimation and Contingency Analysis Software Implementation using High Performance Computing Techniques

Power system simulation tools are traditionally developed in sequential mode and codes are optimized for single core computing only. However, the increasing complexity in the power grid models requires more intensive computation. The traditional simulation tools will soon not be able to meet the grid operation requirements. Therefore, power system simulation tools need to evolve accordingly to provide faster and better results for grid operations. This paper presents an integrated state estimation and contingency analysis software implementation using high performance computing techniques. The software is able to solve large size state estimation problems within one second and achieve a near-linear speedup of 9,800 with 10,000 cores for contingency analysis application. The performance evaluation is presented to show its effectiveness.

Chen, Yousu↗

Dielectric relaxation in 0-3 PVDF-Ba(Fe{sub 1/2}Nb{sub 1/2})O{sub 3} composites

(1-x)PVDF-xBa(Fe{sub 1/2}Nb{sub 1/2})O{sub 3} ceramic-polymer composites with x = 0.025, 0.05, 0.10, 0.15 were prepared using melt-mixing technique. The crystal symmetry, space group and unit cell dimensions were determined from the XRD data of Ba(Fe{sub 1/2}Nb{sub 1/2})O{sub 3} using FullProf software, whereas crystallite size and lattice strain were estimated using Williamson-Hall approach. The distribution of Ba(Fe{sub 1/2}Nb{sub 1/2})O{sub 3} particles in the PVDF matrix were examined on the cryo-fractured surfaces using a scanning electron microscope. Cole-Cole and pseudo Cole-Cole analysis suggested the dielectric relaxation in this system to be of non-Debye type. Filler concentration dependent real and imaginary parts of dielectric constant as well as ac conductivity data followed definite trends of exponential growth types of variation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Automated Estimation of the DARHT Radiographic Spot Size from Spatially Modulated Images

We wrote a software routine to find local extrema and calculate the contrast in the image for each feature set. The input is a KTO image in the standard DARHT orientation, pre-processed by flat-fielding, dark frame subtraction and de-warping. Table 1 shows contrast results for five contemporaneous DARHT images of the KTO. For some very dense feature sets, contrast measurements are not possible due to a lack of local extrema, and in this case no contrast value is given in the table. Highlighted in bold are the contrast values for each image that bound the threshold C = 0.01. The contrast is varying rapidly enough with spatial frequency that we can interpolate between these values to find an estimate of the spatial frequency at the threshold value.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Metrological characterization of X-ray diffraction methods at different acquisition geometries for determination of crystallite size in nano-scale materials

Crystallite size values were determined by X-ray diffraction methods for 183 powder samples. The tested size range was from a few to about several hundred nanometers. Crystallite size was calculated with direct use of the Scherrer equation, the Williamson–Hall method and the Rietveld procedure via the application of a series of commercial and free software. The results were statistically treated to estimate the significance of the difference in size resulting from these methods. We also estimated effect of acquisition conditions (Bragg–Brentano, parallel-beam geometry, step size, counting time) and data processing on the calculated crystallite size values. On the basis of the obtained results it is possible to conclude that direct use of the Scherrer equation, Williamson–Hall method and the Rietveld refinement employed by a series of software (EVA, PCW and TOPAS respectively) yield very close results for crystallite sizes less than 60 nm for parallel beam geometry and less than 100 nm for Bragg–Brentano geometry. However, we found that despite the fact that the differences between the crystallite sizes, which were calculated by various methods, are small by absolute values, they are statistically significant in some cases. The values of crystallite size determined from XRD were compared with those obtained by imaging in a transmission (TEM) and scanning electron microscopes (SEM). It was found that there was a good correlation in size only for crystallites smaller than 50 – 60 nm. Highlights: • The crystallite sizes for 183 nanopowders were calculated using different XRD methods • Obtained results were subject to statistical treatment • Results obtained with Bragg-Brentano and parallel beam geometries were compared • Influence of conditions of XRD pattern acquisition on results was estimated • Calculated by XRD crystallite sizes were compared with same obtained by TEM and SEM.

36 MATERIALS SCIENCE↗

Design and analysis of magnetic coil for relativistic magnetron

This paper presents the design of magnetic coil for relativistic magnetron (RM) for LIA (Linear Induction Accelerator)-400 systems. Vacuum improves the efficiency of RM for HPM generation. Magnetic field in RM is very critical parameter and should be nearly constant in the active region. Typical coils are helical in nature, which have multi turns of varying radius. Magnetic field calculation of such coils with basic equations of Helmholtz coils or solenoid with mean radius can only give estimation. Field computational softwares like CST require small mesh size and boundary at very far so consume large memory and take very much time. Helical coils are simplified such that the basic law of magnetic field calculation i.e. Bio-Savart law can be applied with less complexity. Pairs of spiral coils have been analyzed for magnetic field and Lorenz's force. The approach is field experimentally validated. (author)

43 PARTICLE ACCELERATORS↗

Usage of Parameterized Fatigue Spectra and Physics-Based Systems Engineering Models for Wind Turbine Component Sizing: Preprint

Software models that use design-level input variables and physics-based engineering analysis for estimating the mass and geometrical properties of components in large-scale machinery can be very useful for analyzing design trade-offs in complex systems. This study uses DriveSE, an OpenMDAO-based drivetrain model that uses stress and deflection criteria to size drivetrain components within a geared, upwind wind turbine. Because a full lifetime fatigue load spectrum can only be defined using computationally-expensive simulations in programs such as FAST, a parameterized fatigue loads spectrum that depends on wind conditions, rotor diameter, and turbine design life has been implemented. The parameterized fatigue spectrum is only used in this paper to demonstrate the proposed fatigue analysis approach. This paper details a three-part investigation of the parameterized approach and a comparison of the DriveSE model with and without fatigue analysis on the main shaft system. It compares loads from three turbines of varying size and determines if and when fatigue governs drivetrain sizing compared to extreme load-driven design. It also investigates the model's sensitivity to shaft material parameters. The intent of this paper is to demonstrate how fatigue considerations in addition to extreme loads can be brought into a system engineering optimization.

17 WIND ENERGY↗

Development of a bayesian belief network model for the software reliability assessment of nuclear digital I and C safety systems - 206

Since the digital instrumentation and control systems are expected to play an important role for the safety systems in nuclear power plants (NPPs), the need has emerged to not only establish a basis for incorporating software behavior into digital I and C system reliability models, but also to quantify the failure probability of the software used in NPP digital protection systems. In this study, a Bayesian belief network (BBN) model is developed to quantitatively assess software reliability by estimating the number of faults in a software program considering its software development life cycle (SDLC). The model structure and parameters are established based on the information applicable to NPP safety-related systems and the evidence used to construct and quantify the BBN model was collected from three stages of expert elicitation. The software failure probability is estimated from the number of residual defects in a software program at the end of SDLC phase. As a case study, the BBN model was applied to quantify the software reliability of a typical digital protection software having the size of 50 function points and having the Medium development and validation and verification (V and V) qualities. The developed model can be applied to estimate the failure probability for both developing and deployed safety-related NPP software, and such results can be used to evaluate the quality of the digital I and C systems in addition to estimating potential reactor risk due to software failure. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SU-E-I-25: Determining Tube Current, Tube Voltage and Pitch Suitable for Low- Dose Lung Screening CT

Purpose: The quality of a computed tomography (CT) image and the dose delivered during its acquisition depend upon the acquisition parameters used. Tube current, tube voltage, and pitch are acquisition parameters that potentially affect image quality and dose. This study investigated physicians' abilities to characterize small, solid nodules in low-dose CT images for combinations of current, voltage and pitch, for three CT scanner models. Methods: Lung CT images was acquired of a Data Spectrum anthropomorphic torso phantom with various combinations of pitch, tube current, and tube voltage; this phantom was used because acrylic beads of various sizes could be placed within the lung compartments to simulate nodules. The phantom was imaged on two 16-slice scanners and a 64-slice scanner. The acquisition parameters spanned a range of estimated CTDI levels; the CTDI estimates from the acquisition software were verified by measurement. Several experienced radiologists viewed the phantom lung CT images and noted nodule location, size and shape, as well as the acceptability of overall image quality. Results: Image quality for assessment of nodules was deemed unsatisfactory for all scanners at 80 kV (any tube current) and at 35 mA (any tube voltage). Tube current of 50 mA or more at 120 kV resulted in similar assessments from all three scanners. Physician-measured sphere diameters were closer to actual diameters for larger spheres, higher tube current, and higher kV. Pitch influenced size measurements less for larger spheres than for smaller spheres. CTDI was typically overestimated by the scanner software compared to measurement. Conclusion: Based on this survey of acquisition parameters, a low-dose CT protocol of 120 kV, 50 mA, and pitch of 1.4 is recommended to balance patient dose and acceptable image quality. For three models of scanners, this protocol resulted in estimated CTDIs from 2.9–3.6 mGy.

60 APPLIED LIFE SCIENCES↗

Hiperclust

This software leverages transfer learning to analyze atom probe tomography (APT) data. It is trained on synthetic data and then applies this knowledge to predict the optimal number of clusters for a given APT dataset. Initially, the software used preliminary clustering to estimate the general structure of the data. Based on this, it provides suggestions for key parameters like minimum cluster size and minimum number of points. These parameters are critical for algorithms like HDBSCAN, ensuring accurate cluster formation without the need for trial-and-error testing. The software runs on High-Performance computing (HPC) systems, enabling fast, scalable analysis of large APT datasets, ultimately saving time and improving the reliability of clustering outcomes.

Tang, Yalei [Idaho National Laboratory (INL), Idah↗

Unlock Expert Energy Analysis with REopt Lite

NREL’s REopt Lite software is a free online tool designed to help building owners, developers, utilities, and researchers find the most cost-effective and resilient energy solution for a specific site. REopt Lite evaluates the economic viability of solar PV, battery storage, and wind energy at a site, identifies system sizes and battery dispatch strategies to minimize energy costs, and estimates how long a system can sustain a site’s critical load during a grid outage. The software delivers powerful insights with as few as three site-specific inputs, allowing users to evaluate the tradeoffs between initial capital expenditures and reduced utility costs over the project lifetime.

97 MATHEMATICS AND COMPUTING↗

Accuracy of Length of Virtual Stents in Treatment of Intracranial Wide-Necked Aneurysms

Background and Purpose: Precise stent deployment is important for successful treatment of intracranial aneurysms by stent-assisted coiling (SAC). We evaluated the accuracy of virtual stents generated using commercial stent planning software by comparing the length of virtual and actually deployed intracranial laser cut stents on three-dimensional digital subtraction angiography (3D-DSA) images. Methods: We retrospectively analyzed the data of 75 consecutive cases of intracranial wide-necked aneurysms treated with the SAC technique using laser cut stents. Based on 3D-DSA images acquired by C-arm CT, stent sizing and placement were intraoperatively simulated by a commercial software application. The difference in length of the stents was estimated by measuring proximal discrepancies between the end points of the virtual and actually deployed stents on fused pre-procedural and post-procedural 3D-DSA images. Discrepancies between distal stent end points were manually minimized. The Kruskal–Wallis test was applied to test whether stent location, type, and length had an effect on difference in length between virtual and real stent. Results: The median difference in length between virtual and real stents was 1.58 mm with interquartile range 1.12–2.12 mm. There was no evidence for an effect of stent location (p = 0.23), stent type (p = 0.33), or stent length (p = 0.53) on difference in length between virtual and real stents. Conclusions: Stent planning software allows 3D simulation of laser cut stents overlain on 3D-DSA images of vessels and may thus be useful for stent selection and deployment of laser cut stents during stent-assisted coiling of intracranial aneurysms.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Absorption Correction for Reliable Pair Distribution Functions from Low Energy X-ray Sources

This paper explores the development and testing of a simple absorption correction model for processing powder X-ray diffraction data from Debye−Scherrer geometry laboratory X-ray experiments. This may be used as a preprocessing step before using PDFGETX3 to obtain reliable pair distribution functions (PDFs). Various experimental and theoretical methods for estimating μR were explored, and the most appropriate μR values for correction were identified for different capillary diameters and X-ray beam sizes. We identify operational ranges of μR where a reasonable signal-to-noise ratio is possible after correction. A user-friendly software package, DIFFPY.LABPDFPROC, is presented that can help estimate μR and perform absorption corrections with a rapid calculation for efficient processing.

Absorption↗

Nitrogen expander cycles for large capacity liquefaction of natural gas

Thermodynamic study is performed on nitrogen expander cycles for large capacity liquefaction of natural gas. In order to substantially increase the capacity, a Brayton refrigeration cycle with nitrogen expander was recently added to the cold end of the reputable propane pre-cooled mixed-refrigerant (C3-MR) process. Similar modifications with a nitrogen expander cycle are extensively investigated on a variety of cycle configurations. The existing and modified cycles are simulated with commercial process software (Aspen HYSYS) based on selected specifications. The results are compared in terms of thermodynamic efficiency, liquefaction capacity, and estimated size of heat exchangers. The combination of C3-MR with partial regeneration and pre-cooling of nitrogen expander cycle is recommended to have a great potential for high efficiency and large capacity.

42 ENGINEERING↗

Bayesian Integration of multiscale environmental data

The software is designed for efficiently integrating large-size of multi-scale environmental data using the Bayesian framework. Suppose we need to estimate the spatial distribution of variable X with high spatial resolution. The available data include (1) direct measurements Z of the unknowns with high resolution in a subset of the spatial domain (small spatial coverage), (2) measurements C of the unknowns at the median scale, and (3) measurements A of the unknowns at the coarsest scale but with large spatial coverage. The goal is to estimate the unknowns at the fine grids by conditioning to all the available data. We first consider all the unknowns as random variables and estimate conditional probability distribution of those variables by conditioning to the limited high-resolution observations (Z). We then treat the estimated probability distribution as the prior distribution. Within the Bayesian framework, we combine the median and large-scale measurements (C and A) through likelihood functions. Since we assume that all the relevant multivariate distributions are Gaussian, the resulting posterior distribution is a multivariate Gaussian distribution. The developed software provides numerical solutions of the posterior probability distribution. The software can be extended in several different ways to solve more general multi-scale data integration problems.

CHEN, JINSONG↗

Bayesian Integration of multiscale environmental data

The software is designed for efficiently integrating large-size of multi-scale environmental data using the Bayesian framework. Suppose we need to estimate the spatial distribution of variable X with high spatial resolution. The available data include (1) direct measurements Z of the unknowns with high resolution in a subset of the spatial domain (small spatial coverage), (2) measurements C of the unknowns at the median scale, and (3) measurements A of the unknowns at the coarsest scale but with large spatial coverage. The goal is to estimate the unknowns at the fine grids by conditioning to all the available data. We first consider all the unknowns as random variables and estimate conditional probability distribution of those variables by conditioning to the limited high-resolution observations (Z). We then treat the estimated probability distribution as the prior distribution. Within the Bayesian framework, we combine the median and large-scale measurements (C and A) through likelihood functions. Since we assume that all the relevant multivariate distributions are Gaussian, the resulting posterior distribution is a multivariate Gaussian distribution. The developed software provides numerical solutions of the posterior probability distribution. The software can be extended in several different ways to solve more general multi-scale data integration problems.

CHEN, JINSONG↗

The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation

Here, this work explores the effect of the ill-posed problem on uncertainty quantification for motion estimation using digital image correlation (DIC) (Sutton et al. 2009). We develop a correction factor for standard uncertainty estimates based on the cosine of the angle between the true motion and the image gradients, in an integral sense over a subregion of the image. This correction factor accounts for variability in the DIC solution previously unaccounted for when considering only image noise, interpolation bias, contrast, and the software settings such as subset size and spacing.

97 MATHEMATICS AND COMPUTING↗

Quantifying uncertainty in Pareto estimates of global lake area

This software contains the code for Bayesian uncertainty analysis of global lake area. Computed uncertainties are compared against more conventional estimation using lake size-abundance distributions. Routines are included to explore sensitivity to observational errors and ad-hoc "censoring" strategies.

Stachelek, Jemma↗