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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

User Guide to the Advanced Dimensional Depletion for Engineering of Reactors (ADDER) Software (V.1.01)

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) software is being developed in the Research and Test Reactor (RTR) Program at Argonne National Laboratory to meet the reactor design and analysis needs of the Conversion Program. ADDER is a flexible tool that (1) provides a depletion capability through coupling external neutronics codes with a built-in CRAM solver or external depletion code and (2) provides a user-friendly interface to perform fuel management and criticality search operations. The ADDER software is a Python 3 application written using modern software development practices subject to a compliant implementation of NQA-1 and applicable Department of Energy software quality assurance standards. This report is the user guide for the software release referred to as ADDER v1.0.1. The motivation for a software to have flexible capabilities that ADDER possesses is the need to support a wide variety of geometries that are commonly required in analysis of research and test reactors. These reactors can have complex fuel, experiment, or control material shuffling patterns that persist over several years with many fuel management and partial refueling intervals. The scale of fuel management analysis can require tracking of an inventory that is multiple times the core loading. Many reactors, both power and non-power reactors of various types, will find the features of ADDER useful to facilitate key tasks that a fuel or core design engineer must perform with the convenience of concise input and validated functionality.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

AMMT FY23 HFIR Irradiation Test Matrix – Supported by the Design of a Miniature Bend Bar Irradiation Vehicle

With the continued advancement of additive manufacturing (AM) techniques, interest has grown in the development and qualification of steels produced via these methods for use in the structural components of advanced nuclear reactors. Therefore, it is crucial that the properties of these materials such as the tensile strength and fracture toughness be investigated following neutron irradiation to support their use in industry. To that end, a test plan to irradiate several tensile and bend bar specimens in the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory was proposed, along with the development of a new “MINBEN” capsule design that features MBS-1 bend bar specimens that have a larger cross-sectional area than those of previous designs, which allows for higher temperature out-of-pile testing. The specimens include AM 316H stainless steel with wrought 316H and A709 stainless steels for reference, and they will be irradiated at 2 dpa and 10 dpa—corresponding to roughly 1 and 5 cycles at the HFIR midplane—at temperatures of 400°C and 600°C. The MINBEN design was found to be capable of providing specimen test plane average temperatures in the range of 220–660°C for six specimens, with a min-max spread in this temperature of ~40°C and a 95% confidence interval of ~24°C. This analysis shows that the capsule provides an effective vehicle for gathering needed high-temperature fracture toughness data.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) Software for Depletion and Fuel Management

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) software is being developed in the Research and Test Reactor (RTR) Program at Argonne National Laboratory to meet the reactor design and analysis needs of the Conversion Program. ADDER is a flexible tool that (1) provides a depletion capability through coupling external neutronics codes with a built-in CRAM solver or external depletion code and (2) provides a user-friendly interface to perform fuel management and criticality search operations. The ADDER software is a Python 3 application written using modern software development practices subject to a compliant implementation of NQA-1 and applicable Department of Energy software quality assurance standards. This report is the user guide for the software release referred to as ADDER v1.1.0. The motivation for a software to have flexible capabilities that ADDER possesses is the need to support a wide variety of geometries that are commonly required in analysis of research and test reactors. These reactors can have complex fuel, experiment, or control material shuffling patterns that persist over several years with many fuel management and partial refueling intervals. The scale of fuel management analysis can require tracking of an inventory that is multiple times the core loading. Many reactors, both power and non-power reactors of various types, will find the features of ADDER useful to facilitate key tasks that a fuel or core design engineer must perform with the convenience of concise input and validated functionality.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) Software for Depletion and Fuel Management

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) software is being developed in the Research and Test Reactor (RTR) Program at Argonne National Laboratory to meet the reactor design and analysis needs of the Conversion Program. ADDER is a flexible tool that (1) provides a depletion capability through coupling external neutronics codes with a built-in CRAM solver or external depletion code and (2) provides a user-friendly interface to perform fuel management and criticality search operations. The ADDER software is a Python 3 application written using modern software development practices subject to a compliant implementation of NQA-1 and applicable Department of Energy software quality assurance standards. This report is the user guide for the software release referred to as ADDER v1.1.0. The motivation for a software to have flexible capabilities that ADDER possesses is the need to support a wide variety of geometries that are commonly required in analysis of research and test reactors. These reactors can have complex fuel, experiment, or control material shuffling patterns that persist over several years with many fuel management and partial refueling intervals. The scale of fuel management analysis can require tracking of an inventory that is multiple times the core loading. Many reactors, both power and non-power reactors of various types, will find the features of ADDER useful to facilitate key tasks that a fuel or core design engineer must perform with the convenience of concise input and validated functionality.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1988

High degree interpolation polynomial in Newton form

Polynomial interpolation is an essential subject in numerical analysis. Dealing with a real interval, it is well known that even if f(x) is an analytic function, interpolating at equally spaced points can diverge. On the other hand, interpolating at the zeroes of the corresponding Chebyshev polynomial will converge. Using the Newton formula, this result of convergence is true only on the theoretical level. It is shown that the algorithm which computes the divided differences is numerically stable only if: (1) the interpolating points are arranged in a different order, and (2) the size of the interval is 4.

Tal-Ezer, Hillel↗
NASA NTRS1987

Expert systems tools for Hubble Space Telescope observation scheduling

This paper discusses the utility of expert systems techniques for Hubble Space Telescope (HST) planning and scheduling and describes a plan for development of expert system tools which will augment the existing ground system. Additional capabilities provided by these tools will include graphics-oriented plan evaluation, long-range analysis of the observation pool, analysis of optimal scheduling time intervals, constructing sequences of spacecraft activities which minimize operational overhead, and optimization of linkages between observations. Initial prototyping of a scheduler used the Automated Reasoning Tool running on a LISP workstation.

Miller, Glenn↗
NASA NTRS1987

Expert systems tools for Hubble Space Telescope observation scheduling

The utility of expert systems techniques for the Hubble Space Telescope (HST) planning and scheduling is discussed and a plan for development of expert system tools which will augment the existing ground system is described. Additional capabilities provided by these tools will include graphics-oriented plan evaluation, long-range analysis of the observation pool, analysis of optimal scheduling time intervals, constructing sequences of spacecraft activities which minimize operational overhead, and optimization of linkages between observations. Initial prototyping of a scheduler used the Automated Reasoning Tool running on a LISP workstation.

Miller, Glenn↗
NASA NTRS1986

Laser wavemeter/spectrometer operating manual

The Laser Wavemeter/Spectrometer is a compact, rugged instrument using a unique combination of an uncoated (Snyder) wedge interferometer and a coated (Fizeau) wedge interferometer to simultaneously measure the wavelength centroid and spectral characteristics of pulsed or CW lasers. Wavelength centroid measurement accuracies are in the range of 1 part in 1,000,000 using the Snyder stage alone. The Fizeau wedge section is capable of resolving spectral details to 0.002/cm and of locating the position of a fringe to 0.0005/cm. Because the Snyder wedge is uncoated, wavelength centroid measurements are possible over the entire detector range of from about 300 nm to greater than 1.0 micron. The coatings of the Fizeau wedge limit spectral analysis to a 200 nm interval in that range. The instrument is currently configured to operate from 600 nm to 800 nm.

Cotnoir, Leo J.↗
NASA NTRS1999

Experimental Studies of Mars-Analog Brines

Evaporite deposits may represent significant sinks of mobile cations (e.g., those of Ca, N, Mg, and Fe) and anions (e.g., those of C, N, S, and Cl) among the materials composing the Martian surface and upper crust. Carbon and nitrogen are especially interesting because of their role as atmospheric gases which can become incorporated into crustal rocks. However, the nature of evaporite precursor brines formed under Martian conditions is poorly understood. To date, only a very limited number of laboratory investigations have been reported which have any bearing on a better understanding of various processes related to brine or evaporite formation on Mars. Here we report on preliminary laboratory experiments that exposed igneous minerals analogous to those in Martian (Shergottites, Nakhlites, and Chassigny (SNC) group) meteorites to a simulated Martian atmosphere and pure, deoxygenated water. Analysis of the water over intervals of time approaching 1 year showed that atmospheric gases dissolved to form carbonate and nitrate ions while minerals dissolved to form sulfate and chloride along with various cations. On an annual basis, ion formation gave a carbonate/sulfate ratio that is comparable to the ratio found among salts in SNC meteorites. The sulfate/chloride ratio of the experimental brines is higher than in SNC meteorites but lower than in surface soils measured at the Viking and Pathfinder landing sites.

Moore, Jeffrey M.↗
NASA NTRS2005

High Frequency QRS ECG Accurately Detects Cardiomyopathy

High frequency (HF, 150-250 Hz) analysis over the entire QRS interval of the ECG is more sensitive than conventional ECG for detecting myocardial ischemia. However, the accuracy of HF QRS ECG for detecting cardiomyopathy is unknown. We obtained simultaneous resting conventional and HF QRS 12-lead ECGs in 66 patients with cardiomyopathy (EF = 23.2 plus or minus 6.l%, mean plus or minus SD) and in 66 age- and gender-matched healthy controls using PC-based ECG software recently developed at NASA. The single most accurate ECG parameter for detecting cardiomyopathy was an HF QRS morphological score that takes into consideration the total number and severity of reduced amplitude zones (RAZs) present plus the clustering of RAZs together in contiguous leads. This RAZ score had an area under the receiver operator curve (ROC) of 0.91, and was 88% sensitive, 82% specific and 85% accurate for identifying cardiomyopathy at optimum score cut-off of 140 points. Although conventional ECG parameters such as the QRS and QTc intervals were also significantly longer in patients than controls (P less than 0.001, BBBs excluded), these conventional parameters were less accurate (area under the ROC = 0.77 and 0.77, respectively) than HF QRS morphological parameters for identifying underlying cardiomyopathy. The total amplitude of the HF QRS complexes, as measured by summed root mean square voltages (RMSVs), also differed between patients and controls (33.8 plus or minus 11.5 vs. 41.5 plus or minus 13.6 mV, respectively, P less than 0.003), but this parameter was even less accurate in distinguishing the two groups (area under ROC = 0.67) than the HF QRS morphologic and conventional ECG parameters. Diagnostic accuracy was optimal (86%) when the RAZ score from the HF QRS ECG and the QTc interval from the conventional ECG were used simultaneously with cut-offs of greater than or equal to 40 points and greater than or equal to 445 ms, respectively. In conclusion 12-lead HF QRS ECG employing RAZ scoring is a simple, accurate and inexpensive screening technique for cardiomyopathy. Although HF QRS ECG is highly sensitive for cardiomyopathy, its specificity may be compromised in patients with cardiac pathologies other than cardiomyopathy, such as uncomplicated coronary artery disease or multiple coronary disease risk factors. Further studies are required to determine whether HF QRS might be useful for monitoring cardiomyopathy severity or the efficacy of therapy in a longitudinal fashion.

Schlegel, Todd T.↗
NASA NTRS2006

An Examination of Selected Geomagnetic Indices in Relation to the Sunspot Cycle

Previous studies have shown geomagnetic indices to be useful for providing early estimates for the size of the following sunspot cycle several years in advance. Examined this study are various precursor methods for predicting the minimum and maximum amplitude of the following sunspot cycle, these precursors based on the aa and Ap geomagnetic indices and the number of disturbed days (NDD), days when the daily Ap index equaled or exceeded 25. Also examined is the yearly peak of the daily Ap index (Apmax), the number of days when Ap greater than or equal to 100, cyclic averages of sunspot number R, aa, Ap, NDD, and the number of sudden storm commencements (NSSC), as well the cyclic sums of NDD and NSSC. The analysis yields 90-percent prediction intervals for both the minimum and maximum amplitudes for cycle 24, the next sunspot cycle. In terms of yearly averages, the best regressions give Rmin = 9.8+/-2.9 and Rmax = 153.8+/-24.7, equivalent to Rm = 8.8+/-2.8 and RM = 159+/-5.5, based on the 12-mo moving average (or smoothed monthly mean sunspot number). Hence, cycle 24 is expected to be above average in size, similar to cycles 21 and 22, producing more than 300 sudden storm commencements and more than 560 disturbed days, of which about 25 will be Ap greater than or equal to 100. On the basis of annual averages, the sunspot minimum year for cycle 24 will be either 2006 or 2007.

Wilson, Robert M.↗
NASA NTRSDate not supplied

Uncertainty Quantification Methodology for Sonic Boom Loudness of a Low-Boom Supersonic Concept

This paper presents a comprehensive analysis of uncertainty quantification for sonic boom loudness metrics associated with the X-59 aircraft during its acoustic validation phase. The study focuses on employing advanced methodologies to characterize uncertainties in key sonic boom parameters predicted from a database derived from a computational fluid dynamics (CFD) solver. These methodologies include creating a polynomial chaos expansion (PCE) surrogate model, which is then used to run a Monte Carlo analysis to obtain 95% uncertainty intervals for sonic boom loudness parameters across the full carpet. Atmospheric uncertainties are rigorously considered, leveraging weather models based on historical data near Edwards Air Force Base to simulate potential flight conditions. The findings include preliminary uncertainty results for the full carpet during the validation phase of the Quesst mission. Additionally, a sensitivity study reveals that the primary sources of uncertainty are humidity and cruise weight.

Laura M. White↗
DOE OSTI2024

A Measurement of νe Appearance and νµ Disappearance Using 10 Years of Data from the NOvA Experiment

NOvA is a long baseline neutrino experiment with an 810 km baseline, using the NuMIbeam at Fermilab, and a functionally identical near and far detector operating at an angle14 mrad off axis from the beam. NOvA jointly measures muon neutrino (and antineutrino)disappearance and electron neutrino (and antineutrino) appearance to make a measurementof sin2θ23, δCP, and ∆m232, including its sign, the mass ordering.This dissertation reports a new measurement from NOvA, using 10 years of data, with a totalexposure of 26.6 ×1020 POT of neutrino beam and 12.5 ×1020 POT of antineutrino beam.This represents 95.6% more neutrino beam exposure since the last NOvA analysis. Aspects ofthe analysis are discussed in detail, including neutrino energy estimation, analysis systematicuncertainties, including the implementation of systematics new to the NOvA analysis, andthe Bayesian fit infrastructure using Markov Chain Monte Carlo (MCMC).The analysis yields the following credible intervals for the oscillation parameters assumingthe normal ordering: δCP = 0.930+0.210−0.290 π ∪0.150+0.150−0.110 π,∆m232 = 2.424+0.035−0.040 × 10−3eV2,and sin2θ23 = 0.55+0.02−0.06, with a 76% preference for normal ordering using a prior for sin2(2θ13)using Daya Bay’s measurement. If the Daya Bay sin2(2θ13) vs ∆m232 constraint is used as aprior instead, an 87% preference for normal ordering emerges.

43 PARTICLE ACCELERATORS↗
NASA NTRS1994

Spectroscopy of Solid State Laser Materials

We retrieved the vertical distribution of ozone from a series 0.005-0.013/cm resolution infrared solar spectra recorded with the McMath Fourier Transform spectrometer at the Kitt Peak National Solar Observatory. The analysis is based on a multi-layer line-by-line forward model and a semi-empirical version of the optimal estimation inversion method by Rodgers. The 1002.6-1003.2/cm spectral interval has been selected for the analysis on the basis of synthetic spectrum calculations. The characterization and error analysis of the method have been performed. It was shown that for the Kitt Peak spectral resolution and typical signal-to-noise ratio (greater than or equal to 100) the retrieval is stable, with the vertical resolution of approximately 5 km attainable near the surface degrading to approximately 10 km in the stratosphere. Spectra recorded from 1980 through 1993 have been analyzed. The retrieved total ozone and vertical profiles have been compared with total ozone mapping spectrometer (TOMS) satellite total columns for the location and dates of the Kitt Peak Measurements and about 100 ozone ozonesoundings and Brewer total column measurements from Palestine, Texas, from 1979 to 1985. The total ozone measurements agree to +/- 2%. The retrieved profiles reproduce the seasonally averaged variations with altitude, including the ozone spring maximum and fall minimum measured by Palestine sondes, but up to 15% differences in the absolute values are obtained.

Buoncristiani, A. M.↗
NASA NTRS1990

Review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials

A review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials is presented. Initially, a semi-empirical model is developed showing the origin of the linear relationship between ultrasonic velocity and porosity fraction. Then, from a compilation of data produced by many researchers, scatter plots of velocity versus percent porosity data are shown for Al2O3, MgO, porcelain-based ceramics, PZT, SiC, Si3N4, steel, tungsten, UO2,(U0.30Pu0.70)C, and YBa2Cu3O(7-x). Linear regression analysis produced predicted slope, intercept, correlation coefficient, level of significance, and confidence interval statistics for the data. Velocity values predicted from regression analysis for fully-dense materials are in good agreement with those calculated from elastic properties.

Roth, D. J.↗
NASA NTRS1991

Review and statistical analysis of the use of ultrasonic velocity for estimating the porosity fraction in polycrystalline materials

A review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials is presented. Initially, a semiempirical model is developed showing the origin of the linear relationship between ultrasonic velocity and porosity fraction. Then, from a compilation of data produced by many researchers, scatter plots of velocity versus percent porosity data are shown for Al2O3, MgO, porcelain-based ceramics, PZT, SiC, Si3N4, steel, tungsten, UO2,(U0.30Pu0.70)C, and YBa2Cu3O(7-x). Linear regression analysis produces predicted slope, intercept, correlation coefficient, level of significance, and confidence interval statistics for the data. Velocity values predicted from regression analysis of fully-dense materials are in good agreement with those calculated from elastic properties.

Roth, D. J.↗
DOE OSTI2023

Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis

Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. As a result, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.

15 GEOTHERMAL ENERGY↗
NASA NTRS2002

Predicting Motion Sickness During Parabolic Flight

Background: There are large individual differences in susceptibility to motion sickness. Attempts to predict who will become motion sick have had limited success. In the present study we examined gender differences in resting levels of salivary amylase and total protein, cardiac interbeat intervals (R-R intervals), and a sympathovagal index and evaluated their potential to correctly classify individuals into two motion sickness severity groups. Methods: Sixteen subjects (10 men and 6 women) flew 4 sets of 10 parabolas aboard NASA's KC-135 aircraft. Saliva samples for amylase and total protein were collected preflight on the day of the flight and motion sickness symptoms were recorded during each parabola. Cardiovascular parameters were collected in the supine position 1-5 days prior to the flight. Results: There were no significant gender differences in sickness severity or any of the other variables mentioned above. Discriminant analysis using salivary amylase, R-R intervals and the sympathovagal index produced a significant Wilks' lambda coefficient of 0.36, p= 0.006. The analysis correctly classified 87% of the subjects into the none-mild sickness or the moderate-severe sickness group. Conclusions: The linear combination of resting levels of salivary amylase, high frequency R-R interval levels, and a sympathovagal index may be useful in predicting motion sickness severity.

Harm, Deborah L.↗