Evaluation of a Simple UQ Approach to Compensate for Sparse Stress-Strain Curve Data in Solid Mechanics Applications.
Abstract not provided.
Romero, Vicente J.↗
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Generation and evaluation of synthetic patient data
Background: Machine learning (ML) has made a significant impact in medicine and cancer research; however, its impact in these areas has been undeniably slower and more limited than in other application domains. A major reason for this has been the lack of availability of patient data to the broader ML research community, in large part due to patient privacy protection concerns. High-quality, realistic, synthetic datasets can be leveraged to accelerate methodological developments in medicine. By and large, medical data is high dimensional and often categorical. These characteristics pose multiple modeling challenges. Methods: In this paper, we evaluate three classes of synthetic data generation approaches; probabilistic models, classification-based imputation models, and generative adversarial neural networks. Metrics for evaluating the quality of the generated synthetic datasets are presented and discussed. Results: While the results and discussions are broadly applicable to medical data, for demonstration purposes we generate synthetic datasets for cancer based on the publicly available cancer registry data from the Surveillance Epidemiology and End Results (SEER) program. Specifically, our cohort consists of breast, respiratory, and non-solid cancer cases diagnosed between 2010 and 2015, which includes over 360,000 individual cases. Conclusions: We discuss the trade-offs of the different methods and metrics, providing guidance on considerations for the generation and usage of medical synthetic data.
59 BASIC BIOLOGICAL SCIENCES↗
Implementation of the direct S ( α , β ) method in the KENO Monte Carlo code
The Monte Carlo code KENO contains thermal scattering data for a wide variety of thermal moderators. These data are processed from Evaluated Nuclear Data Files (ENDF) by AMPX and stored as double differential probability distribution functions. The method examined in this study uses S(α,β) probability distribution functions derived from the ENDF data files directly instead of being converted to double differential cross sections. This allows the size of the cross section data on the disk to be reduced substantially amount. KENO has also been updated to allow interpolation in temperature on these data so that problems can be run at any temperature. Results are shown for several simplified problems for a variety of moderators. In addition, benchmark models based on the KRITZ reactor in Sweden were run, and the results are compared with the previous versions of KENO without the direct S(α,β) method. Results from the direct S(α,β) method compare favorably with the original results obtained using the double differential cross sections. Finally, sampling the data increases the run-time of the Monte Carlo calculation, but memory usage is decreased substantially.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Delayed Neutron Precursor Group Parameter and Spectra Generation from Fast Fission of 235U in SCALE
Delayed neutron precursor (DNP) group data are important for modeling reactor dynamics. Although the data for individual DNPs have been developed over time, the DNP group data present in the Evaluated Nuclear Data Files (ENDF) have not been updated in the past 20 years. In this work, we use SCALE to recreate the Godiva experiment that was used to generate the original DNP group structure for fast fission of 235U. However, each DNP is modeled using up-to-date data, and the results are then converted into a newly updated group structure. This conversion uses an iterative linear least squares solver to minimize chi-squared. The approaches used in this work also enable energy spectrum generation and uncertainty tracking. The method used in this paper for fast 235U fission DNP group structure updating can be applied to different energies and fissile nuclides. Demonstration of the uncertainty tracking in reactor kinetics and dynamics simulations is shown using point reactor kinetics simulations. Results show that there are data discrepancies between the International Atomic Energy Agency database and data used in ORIGEN, which are currently being fixed. Results also show that the proposed method for group spectra generation performs well.
Seifert, Luke [University of Illinois]↗
MaDaTS: Managing Data on Tiered Storage for Scientific Workflows
Scientific workflows are increasingly used in High Performance Computing (HPC) environments to manage complex simulation and analyses, often consuming and generating large amounts of data. However, workflow tools have limited support for managing the input, output and intermediate data. The data elements of a workflow are often managed by the user through scripts or other ad-hoc mechanisms. Technology advances for future HPC systems is redefining the memory and storage subsystem by introducing additional tiers to improve the I/O performance of data-intensive applications. These architectural changes introduce additional complexities to managing data for scientific workflows. Thus, we need to manage the scientific workflow data across the tiered storage system on HPC machines. In this paper, we present the design and implementation of MaDaTS (Managing Data on Tiered Storage for Scientific Workflows), a software architecture that manages data for scientific workflows. We introduce Virtual Data Space (VDS), an abstraction of the data in a workflow that hides the complexities of the underlying storage system while allowing users to control data management strategies. We evaluate the data management strategies with real scientific and synthetic workflows, and demonstrate the capabilities of MaDaTS. Our experiments demonstrate the flexibility, performance and scalability gains of MaDaTS as compared to the traditional approach of managing data in scientific workflows.
Ghoshal, Devarshi↗
Evaluation of land cover change detection techniques using Landsat MSS data
Four techniques for detecting land cover change with Landsat MSS data were evaluated for a test site in east central Louisiana where forestland is being converted to cropland and pasture. The four techniques were: (1) post-classification differencing, (2) composite classification, (3) radiance value shift, and (4) regression modeling. Three of the techniques gave acceptable accuracies. The main differences were the amount of computer time and the level of complexity.
Burns, G. S.↗
System Safety Hazards Assessment in Conceptual Program Trade Studies
Providing a program in the concept development phase with a method of determining system safety benefits of potential concepts has always been a challenge. Lockheed Martin Space and Strategic Missiles has developed a methodology for developing a relative system safety ranking using the potential hazards of each concept. The resulting output supports program decisions with system safety as an evaluation criterion with supporting data for evaluation. This approach begins with a generic hazards list that has been tailored for the program being studied and augmented with an initial hazard analysis. Each proposed concept is assessed against the list of program hazards and ranked in three derived areas. The hazards can be weighted to show those that are of more concern to the program. Sensitivities can be also be determined to test the robustness of the conclusions
Eben, Dennis M.↗
Status of Validation Program for Tropical Rainfall Measuring Mission (TRMM)
The Tropical Rainfall Measuring Mission (TRMM) is in its sixth year of operation. This successful research mission, a joint U.S./Japan effort, has become-a key element in the routine monitoring of global precipitation. The package of rain measuring instrumentation, including the first meteorological radar in space, continues to function perfectly, and with the increase in orbital altitude (from 350 km to 400 km) the mission will hopefully continue for a number of years. The validation effort has been a combination of routine use of 1) ground-based radar and raingauge measurements for comparison with the satellite-based estimates, 2) the use of field experiment data for evaluation of the satellite data products and investigation of some of the assumptions in the satellite retrievals, and 3) use of other comparison data sets, including atoll and buoy gauges over ocean and research and operational gauge data sets over land. The status of the program will be described along with "lessons learned". Near term plans for improved validation products and new thrusts related to validation of TRMM-based multi-satellite products that extend into middle latitudes will be outlined.
Adler, Robert↗
Continuing Development of the Nuclear Data Processing Code AMPX [Abstract]
The AMPX nuclear data processing code reads evaluated nuclear data files and prepares libraries in continuous energy (CE) and multigroup (MG) formats. These libraries are used by the transport and depletion codes in the SCALE code system.
AMPX↗
Monthly Oceanic Rainfall from TRMM Microwave Imager (TMI) Data
We evaluated the performance of the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) at-launch algorithm for monthly oceanic rain rate using two years (January 1998 - December 1999) of TMI data. The TMI at-launch algorithm is based on Wilheit et al.'s technique for estimating monthly oceanic rainfall that relies on histograms of multichannel microwave measurements. Comparisons with oceanic monthly rain rates derived from the Defense Meteorological Satellite Program (DMSP) F-13 and F-14 Special Sensor Microwave Imager (SSM/I) data show the average rain rates over the TRMM region (between 400S and 40N) are 3.0, 2.85 and 2.89 mm/day, respectively for F-13, F-14 and TMI. Based on the latest version of TB data (version 5), both rainrate and freezing height derived from TMI are similar to those from the F-13 and F-14 SSM/I data. However, regionally the differences are statistically significant at the 95% confidence. Three hourly monthly rainrates are also computed from 3-hourly TB histograms to examine the diurnal cycle of precipitation. Over most of the oceanic TRMM area, a distinct early morning rainfall peak is found. A harmonic analysis shows that the amplitude of the 12h harmonic is significant and comparable to that of the 24h harmonic.
Chang, Alfred T. C.↗
Nuclear Data Sheets for A=24
Here, evaluated spectroscopic data and level schemes from radioactive decay and nuclear reaction studies are presented for 24 N, 24 O, 24 F, 24 Ne, 24 Na, 24 Mg, 24 Al, and 24 Si. This evaluation for A=24 supersedes the earlier one by R. B. Firestone (2007Fi14). Highlights of this evaluation are the following: In 24 O, the 7.4- and 7.65-MeV groups reported in 1 H( 24 O,p') (2012Ts03) and 9 Be( 26 F,nX) (2011Ho05), respectively, are considered as separate states in this evaluation, since the former one was observed to decay by only one neutron emission to 23 O, while the latter one by two sequential neutrons to 22 O. Based on assigned configurations, the 7.4- and 7.6-MeV groups are tentatively assigned negative and positive parities, respectively. Additional study would be useful to determine if these states are same or different. In 24 Na, 2014Fi01 (n,γ) proposed Jπ=(0,1,2) - for 4048.8 keV level based on weaker population from the capture state (J π =1 + ,2 + ) and mentioned to reexamine the J π =0 + assignment, suggested in earlier evaluations (1990En08, 2007Fi02). This evaluation includes the first observation of E0 transition, strength ρ 2 (E0)=0.380 70, for the 6432 keV transition from 0 + state at 6432 to 0 + g.s. in 24 Mg reported in 2020Do10. Authors proposed the first-excited 0+ state of 24 Mg to be superdeformed. In 24 Al, the excited level energies deduced from ( 3 He,t) measurements reported by different research groups vary significantly and it was not clear if some of those levels were same or different. Additional measurements are needed.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Decade-Long Ozone Profile Record from Suomi NPP OMPS Limb Profiler: Assessment of Version 2.6 Data
We evaluate a decadal ozone profile record derived from the Suomi National Polar-orbiting Partnership (SNPP) Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) satellite instrument. In 2023, the OMPS LP data were re-processed with the new version 2.6 retrieval algorithm that combines measurements from the ultraviolet (UV) and visible (VIS) parts of the spectra and employs the second order Tikhonov regularization to retrieve a single vertical ozone profile between 12.5 km (or cloud tops) and 57.5 km with the vertical resolution of about 1.9 - 2.5 km between 20-55 km. The algorithm uses radiances measured at six UV ozone-sensitive wavelengths (295, 302, 306, 312, 317 and 322 nm) paired with 353 nm, and one VIS wavelength at 606 nm combined with 510 nm and 675 nm to form a triplet. Each wavelength pair or triplet is used over a limited range of tangent altitudes where the sensitivity to ozone changes are strongest. A new implemented aerosol correction scheme is based on a gamma-function particle size distribution. Numerous calibration changes that affected ozone retrievals were also applied to measured LP radiances, including updates in altitude registration, radiometric calibration, stray light, and spectral registration. The key version 2.6 improvement is the reduction in relative drifts between LP ozone and correlative measurements, linked previously to a drift in the version 2.5 LP altitude registration. We compare LP ozone profiles with those from Aura Microwave Limb Sensor (MLS) to quantify ozone changes in version 2.6.
Limb scattering↗
Evaluating the 238 U PFNS Including Chi-Nu Experimental Data
This report documents an evaluation of 238 U prompt fission neutron spectra (PFNS) which is a deliverable for a FY2024 Q4 NCSP (Nuclear Criticality Safety Program) milestone. This evaluation is new; its prior input is based on extended Los Alamos and exciton models implemented in the code CoH. Experimental covariances were estimated for five experimental data sets. One of these data sets that was measured by the Chi-Nu team of LANL and LLNL. It covers the 238 U PFNS for continuous incident-neutron energies of 1–20 MeV and outgoing-neutron energies from 10 keV– 10 MeV with high precision. Contrary to Chi-Nu data, previous data sets were measured in a limited energy range. The resulting evaluated data correspond well to the experimental PFNS taken into account for the evaluation. The evaluated PFNS also produce average mean energies in agreement with associated Chi-Nu data. If one uses the new evaluated data to predict the neutron multiplication factor, k eff , of the Flattop, Flattop-Pu and BigTen ICSBEP critical assemblies (which all have thick reflectors with high percentages of 238 U), the differences of simulated values compared to those using ENDF/B-VIII.1β3 is modest (less than 25 pcm). In addition to that, the new PFNS predict on average 238 U LLNL pulsed-sphere neutron-leakage spectra slightly better than ENDF/BVIIII.0 and ENDF/B-VIII.1β3 PFNS. The differences are, however, well within the experimental uncertainties.
238U↗
Evaluation of aircraft microwave data for locating zones for well stimulation and enhanced gas recovery
Imaging radar was evaluated as an adjunct to conventional petroleum exploration techniques, especially linear mapping. Linear features were mapped from several remote sensor data sources including stereo photography, enhanced LANDSAT imagery, SLAR radar imagery, enhanced SAR radar imagery, and SAR radar/LANDSAT combinations. Linear feature maps were compared with surface joint data, subsurface and geophysical data, and gas production in the Arkansas part of the Arkoma basin. The best LANDSAT enhanced product for linear detection was found to be a winter scene, band 7, uniform distribution stretch. Of the individual SAR data products, the VH (cross polarized) SAR radar mosaic provides for detection of most linears; however, none of the SAR enhancements is significantly better than the others. Radar/LANDSAT merges may provide better linear detection than a single sensor mapping mode, but because of operator variability, the results are inconclusive. Radar/LANDSAT combinations appear promising as an optimum linear mapping technique, if the advantages and disadvantages of each remote sensor are considered.
Macdonald, H.↗
Nuclear Data Sheets for A=100
Here, evaluated experimental data are presented for 15 known nuclides of mass 100 (Kr, Rb, Sr, Y, Zr, Nb, Mo, Tc, Ru, Rh, Pd, Ag, Cd, In, Sn). Recommended values are given for level parameters, γ and β radiations, and other spectroscopic information. No excited states are known in 100 Rb and 100 Sn. Except for isotopic identification, no information is available for the decay of the 100 Kr isotope, and limited information is known about the decay properties of the 100 Sn isotope. According to Fig. 2 (A/Q versus counts plot) and as mentioned in the text in 2021Su01, 100 Br isotope was not observed, although, discovery of 101 Br was claimed in this work. In the case of 100 Pd, the agreement in the orderings of the γ-ray cascades and γ-ray inventory between various studies of high-spin structures remains poor at high excitation energies (>9 MeV). For 100 Y, the assignments of the two previously known half-lives to the respective states (g.s. and the 145-keV isomer) remain to be established. Here, this work supersedes earlier full evaluations of A=100 by 2008Si01, 1997Si09, 1990Si05 and 1974Ko37.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Machine-Learned Manifold-Based Models for Large Eddy Simulation of Turbulent Combustion
Reduced-order manifold combustion models are commonly used to lower the cost of reacting Large Eddy Simulations (LES) and may be derived either from physical principles as in flamelet models or from data-driven methods like Principal Component Analysis (PCA). In either case, neural networks are increasingly used as part of these models to provide a nonlinear mapping between a small set of pre-defined variables that parameterize the manifold and outputs of interest, such as reaction rates. In this work, we propose a new manifold-based modeling approach that combines the definition of the manifold-parameterizing variables (linear combinations of species), the nonlinear mapping to the outputs, and closure of filtered quantities for LES into the structure of a single neural network. This allows the process used to train the neural network to simultaneously optimize both the functional form of the model and the identities of the inputs to the model. The new approach can flexibly incorporate thermochemical data from any combustion system; if trained on data from 1D flames it can be interpreted as an optimized flamelet model, but it can also be used to learn models from data from more complex configurations. This work presents a priori evaluations of the new approach in both contexts. Evaluation using data from 1D premixed flames demonstrates the physical interpretability of the manifold variables generated by the new approach. Evaluation using data from direct numerical simulations of turbulent flames shows improved predictions relative to either flamelet or PCA-based models in a more complex configuration.
47 OTHER INSTRUMENTATION↗
Fast neutron leakage spectra of the EUCLID experiment
Special nuclear material in sub-critical and critical configurations measured in integral experiments are important for validation and adjustment of nuclear data. Many different evaluations of nuclear data exist, and these different evaluations can provide different values for individual cross sections that vary due to the uncertainties in differential experiments or lack of such data. For integral experiments, differences in these individual cross sections can have compensating errors, which lead to the same answer. One example of this is the Jezebel critical assembly, where k eff of the system is correctly computed by both ENDF/B-VIII.0 and JEFF-3.3, despite having substantially different underlying evaluated values for specific reactions (such as elastic and inelastic cross sections). To reduce compensating errors in nuclear data, the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project has utilized machine learning to design a set of sub-critical and critical experiments. These experiments include slab- and cube-like configurations of 239 Pu in the form of the ZPPR plates. Six different responses were measured on a total of thirteen different configurations. One of these responses, the neutron leakage spectrum, was measured using an EJ301D detector. Finally, the results of the neutron leakage spectra show good agreement (within 1–2 σ ) with the expected spectrum from simulations and will be used in the subsequent nuclear data adjustment done by the EUCLID team.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗