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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Chemical Composition and PCT Data for the Initial Set of Hanford Enhanced Waste Loading Glasses

In this report, the Savannah River National Laboratory provides chemical analyses and Product Consistency Test results for 20 simulated high level waste glasses fabricated by the Pacific Northwest National Laboratory. The results of these analyses will be used as part of efforts to revise or extend the validation ranges of the current Hanford Waste Treatment and Immobilization Plant glass property models to cover a broader span of waste compositions. The measured chemical composition data are reported and compared with the targeted values for each component for each glass. Two components of the study glasses, fluorine and silver, were not measured since each of these species would have required the use of an additional preparation method and their measured values were likely to be near or below analytical detection limits. Some of the glasses were difficult to prepare for chemical analysis. A sodium peroxide fusion dissolution method was successful in completely dissolving the glasses. Components present in the glasses in minor concentrations can be difficult to measure using this dissolution method due to dilution requirements. The use of a lithium metaborate preparation method for the minor components (planned for use since it is typically successful in digesting Defense Waste Processing Facility HLW glasses) resulted in an unacceptable amount of undissolved solids remaining in the sample solutions. An acid dissolution method was used instead, which provided more thorough dissolution of the glasses, although a small amount of undissolved material remained for some of the study glasses. The undissolved material was analyzed to determine those components of the glasses that did not fully dissolve. These components (e.g., calcium and chromium) were present in sufficient quantities to be reported from the measurements resulting from the sodium peroxide fusion preparation method, which did not leave undissolved material. Overall, the analyses resulted in sums of oxides that ranged from about 98 to 101.5 wt % for the study glasses, indicating excellent recovery of all the components in the chemical composition analyses. Comparisons of the targeted and measured chemical compositions indicated that, in general, the measured values for the glasses met the targeted concentrations. Exceptions were Cr 2 O 3 , MgO, and P 2 O 5 . The measured values for Cr 2 O 3 were somewhat low when compared to the targeted values for all of the study glasses targeting Cr 2 O 3 concentrations above 0.5 wt %. Many of the measured MgO and P 2 O 5 values were below the targeted values for those glasses that contained these components. Two of the study glasses exhibited differences from the targeted compositions that may indicate a batching error. Glasses EWG-HAI-Centroid-2 and EWG-OL-1672 had measured values for Al 2 O 3 and SiO 2 that were lower than the targeted values, and measured values for B 2 O 3 that were higher than the targeted values. Glass EWG-HAI-Centroid-2 also had a measured value for Fe 2 O 3 that was lower than the targeted value. A review of the PCT data, including standards and blanks, revealed no issues with the performance of the tests. The PCT results were normalized to both the targeted and measured compositions of the study glasses. Comparisons of the normalized PCT results for both the quenched and Canister Centerline Cooled versions of the study glasses are made with the Environmental Assessment benchmark glass for reference.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Final Technical Report: Moving ASR Cloud Microphysical Retrievals Beyond the Vertical Column

Clouds of all types play important roles in atmospheric heating, surface heating and emission of radiation, hence energy, to space. Clouds not only affect atmospheric heating via their impacts on solar and terrestrial radiation, they also release kinetic energy to the atmosphere when they form and they extract kinetic energy from the atmosphere when they evaporate. To understand the impacts of clouds on weather and climate, one must be able to make accurate observations of the amount of water associated with them and the impact of this water on atmospheric and surface heating rates. One important cloud type is liquid water clouds. Liquid clouds are often found in the boundary layers of Earth at altitudes from just above the surface to approximately 2000 m above it, at a variety of temperatures, including temperatures below the freezing point of liquid water (0 °C). As a result, they are important constituents over the world’s oceans as well as over cold, ice-covered surfaces such as in the Arctic. Observationally estimating the total amount of liquid contained in a column through a liquid water cloud can now be accomplished to acceptable accuracies (except for the thinnest, lowest liquid containing clouds) using instruments called passive microwave radiometers. However, observationally determining the spatial distribution of liquid within these columns has proven to be difficult. The focus of this project was on the application of two radars operating at two different frequencies to retrieve the distribution of liquid water within columns passing through liquid water clouds. Motivation in this project for using two different radars operating at different frequencies is that as overlapping (in space) beams from the two radars pass through the same column of liquid water cloud absorption of power from one beam (the 94-GHz beam) is greater than absorption of power from the other beam (the 35-GHz beam). Therefore, the difference in returned powers between the two radar beams with distance from the radars is proportional to the amount of liquid water that the two beams have passed through. Therefore, one can use the differences in power between the two beams with distance through a liquid water cloud to determine the distribution of liquid water throughout the cloud. The two radars used in this study are the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program Ka-band Scanning ARM Cloud Radar (Ka-SACR) and the W-band Scanning ARM Cloud Radar (W-SACR). When this projected started in 2013, the Ka- and W-band SACRs were new technology, state-of-the-art sensors. To put together a sufficiently diverse and big set of test cases for the study, data from the SACRs deployed to NSA, SGP, TCAP and MAGIC were used, leading to a test set composed of 65 hours of suitable data spread over approximately 17 case study days. Using the Ka- and W-band SACR data from the case study periods, vertical distributions of liquid water content through liquid water clouds were retrieved. Because there are no other data sets with which to compare the retrievals, distributions of liquid water through a column were summed and compared to the total amounts of liquid water obtained by retrievals applied to passive microwave radiometer observations. The total amounts of liquid water (in units of millimeters, or the thickness in millimeters of the total liquid water in a vertical column if allowed to pool at the bottom of the column) between the two retrievals agreed to within 0.060 mm with a standard deviation of 0.31 mm, or to within 0.016 mm with a standard deviation of 0.12 mm once outliers were removed. The standard deviation of 0.12 mm was fairly independent of the total amount of liquid water in the clouds, indicating that retrieval errors were larger for clouds with smaller amounts of liquid in them. Errors in the retrieved total amounts of liquid were also found to be sensitive to the a priori information that was fed into the retrieval approach. Overall, standard deviations of 0.12 mm are sufficient for some cloud studies but for radiation studies standard deviations on the order of 0.02 mm need to be achieved for clouds with the lowest amounts of liquid water. Many modifications to the retrieval approach were tested subsequently in an attempt to reduce the standard deviations relative to the radiometer retrievals below 0.12 mm but none of them worked reliably. We decided to wait until the DOE ARM Program deployed its second generation SACR2s to its NSA and ENA sites for further retrieval evaluation. The SACR2s were engineered to better synchronize data between the Ka- and W-band radars, reducing potential sources of noise for radar retrieval of liquid water distributions within clouds. The SACR2s have improved in reliability recently and the system deployed to ENA is best positioned to provide the data to advance research on this path. This will be an ongoing research activity beyond the project because of the promise in SACR2 data from the DOE ARM ENA Facility.

58 GEOSCIENCES↗
DOE OSTI2023

Electrodynamic Shaker Capability Estimation Through Experimental Dynamic Substructuring [Thesis]

Electrodynamic shaker systems are an essential tool in shock and vibration testing of dynamic environments. However, the specific performance capability of these systems is difficult to characterize. The dynamics of the shaker itself, the device under test and the specific test configuration used all couple to create a dynamic response unique to each test. Poorly predicted limitations in shaker capability affect the ability to achieve test specifications, delay testing schedules, and create difficulties for choosing test equipment. To predict shaker capability for a specific test configuration prior to setup, a lumped parameter model of the shaker system and a modal model of a device under test was developed. These models were then analytically coupled using LaGrange multiplier frequency based substructuring to estimate their coupled frequency response functions. The coupled frequency response functions were used to predict electrical inputs required to meet a given test specification. These input requirements were finally compared to a validation test using the specification and setup. Input requirements estimated using the substructuring estimated frequency response functions showed significant error. However, results using an ideal frequency response function showed very little error. These results indicate that with a better method of experimental dynamic substructuring employed it would be possible to accurately predict shaker capability for a given test configuration prior to setup.

42 ENGINEERING↗
DOE OSTI2023

Modeling and Simulation of Xe-100-type Pebble Bed Gas-Cooled Reactor with SCALE

The US Department of Energy (DOE) announced the Advanced Reactor Demonstration Program (ARDP) to accelerate the deployment of advanced reactor concepts. Awardees of ARDP funds are expected to demonstrate the operation of an advanced reactor within 7 years of receiving the award. X-Energy’s advanced reactor concept, the Xe-100, was selected as one of two advanced reactor concepts to receive funding to demonstrate the operation of its high-temperature gas-cooled pebble-bed reactor before the end of this decade. As a result of this push to bring advanced reactors to maturation and commercialization, transition and deployment scenario studies are being performed under the Systems Analysis and Integration (SA&I) campaign within the DOE Office of Nuclear Energy (DOE-NE) to evaluate the transition of the current US commercial fleet of light-water reactors (LWRs) to a future fleet of advanced reactors consisting of a mix of ARDP type reactor concepts and advanced LWRs. To accurately evaluate the front- and back-end resource requirements, it is important to perform reactor physics calculations to determine the discharge burnup and isotopic content, fuel residence time, as well as other parameters. For this purpose, a summer project funded by the SA&I campaign allowed for the setup of SCALE models for full-core Xe-100 type high-temperature gas-cooled pebble-bed reactor and a Xe-100 type slice using publicly available information. The core-averaged equilibrium compositions and zone-wise equilibrium compositions for the slice and 3D models, respectively, were obtained following an iterative depletion method developed by Bostelmann et al. using SCALE’s reactor physics sequence TRITON. The slice model was used with TRITON to generate burnup-dependent cross section libraries at different temperatures which can be used with SCALE’s ORIGAMI code to rapidly determine fuel inventory and therefore to perform quick sensitivity studies on parameters such as the pebble location in the core. The SCALE/TRITON transport and depletion calculation for the Xe-100 type slice model indicates that the isotopic concentrations are in good agreement at 1,300 effective full power days (EFPD) for 235 U. An analysis of 236 U results match 239 Pu results would seem to indicate a typographical error in Mulder and Boyes wherein the reported results of 236 U and 239 Pu are reversed. In addition to SCALE/TRITON calculations, a new capability within SCALE/ORIGAMI for the simulation of pebble-bed reactors was used to study the burnup sensitivity with respect to the pebble pathway through the core. The SCALE/ORIGAMI results show that pebbles that travel closer to the reflector for the entire depletion history have a higher burnup than pebbles that travel through the middle of the core because of the higher thermal to fast flux ratio near the reflector. Consequently, a pebble’s burnup is strongly affected by the pebble’s pathway for each pass. Additional phenomena such as temperature distributions in the core and different travel times of the pebbles in the individual radial zones further affect the burnup distribution. The sensitivity of the discharge vector to the pebble pathways taken during each pass can be evaluated in the future using SCALE/ORIGAMI now that the SCALE inputs have been established.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Validation of Weather Forecasting Products

Meteorological modeling plays a pivotal role in operational safety and emergency response at the Savannah River Site (SRS). This study focuses on verifying the Regional Atmospheric Modelling System (RAMS) Version 4.3 through Mean Bias Error (MBE) and Root Mean Square Error (RMSE) analyses of temperature, dew point, and wind speed over a decade. Using observed data from SRS, we assessed RAMS' accuracy, revealing seasonal biases and error trends. Results indicate RAMS' strengths in mild weather conditions but challenges during seasonal extremes and wind speed predictions due to measurement disparities. Future research aims to expand verification to other models and parameters, advocating for enhanced forecasting accuracy crucial for safeguarding personnel and community well-being.

42 ENGINEERING↗
DOE OSTI2015

Stillwater Hybrid Geo-Solar Power Plant Optimization Analyses

The Stillwater Power Plant is the first hybrid plant in the world able to bring together a medium-enthalpy geothermal unit with solar thermal and solar photovoltaic systems. Solar field and power plant models have been developed to predict the performance of the Stillwater geothermal / solar-thermal hybrid power plant. The models have been validated using operational data from the Stillwater plant. A preliminary effort to optimize performance of the Stillwater hybrid plant using optical characterization of the solar field has been completed. The Stillwater solar field optical characterization involved measurement of mirror reflectance, mirror slope error, and receiver position error. The measurements indicate that the solar field may generate 9% less energy than the design value if an appropriate tracking offset is not employed. A perfect tracking offset algorithm may be able to boost the solar field performance by about 15%. The validated Stillwater hybrid plant models were used to evaluate hybrid plant operating strategies including turbine IGV position optimization, ACC fan speed and turbine IGV position optimization, turbine inlet entropy control using optimization of multiple process variables, and mixed working fluid substitution. The hybrid plant models predict that each of these operating strategies could increase net power generation relative to the baseline Stillwater hybrid plant operations.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

The limits and challenges of error field correction for ITER

Significant progress has been made in interpreting the effects of non-axisymmetric 'error' fields on a plasma through ideal MHD stability and a dominant 'least stable' ideal mode through which the fields couple to the tearing resonant surface. However, in contrast to expectations from such theories, experiments have found limited success in correcting error fields, with single correction coil arrays giving benefits of between 0% and {approx}50% correction (in terms of improvement to a low density locked mode limit), dependent on the structure of the error and correcting fields. With additional coils up to {approx}70% is possible. It was unclear whether this represented an intrinsic stability or control limit, or higher order toroidal or poloidal harmonic effects. Thus, studies on the DIII-D tokamak explored correction of a proxy error field, using two differently structured coil arrays. This enabled the principles of error correction to be tested at high amplitudes and operational densities, with known pure n=1 fields. Results showed substantial residual effects from the corrected n=1 field, with improvements of only {approx}50% in the low density locked mode limit. This suggests that n=1 error fields must couple to more than one surface in the plasma, and this is conjectured to be through more than one ideal mode, thereby requiring precise correction. For ITER, updated predictions of field error have been obtained and compared with revised scalings for tearing mode thresholds, indicating 50% or better error field correction will be needed. This will likely require more than one well coupled correction coil array and sets a challenge for theory to model the behavior, in order to clarify the plasma response and braking mechanisms, and so the effectiveness of ITER's correction coils and the possible need for support from its edge localized mode control coils.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

TU-C-BRE-01: KEYNOTE PRESENTATION - Emerging Frontiers in IMRT QA

As IMRT treatment processes advance and mature, so must the quality assurance processes being used to validate their delivery. In some respects, treatment delivery advancements (e.g. VMAT) have out-paced QA advancements. The purpose of this session is to describe new processes that are being implemented to bring IMRT QA up-to-date with the treatment delivery advances. It would explore emerging IMRT QA paradigms, including requirements-based IMRT QA which necessitates definition of delivery errors (e.g. patient dose error, leaf positioning error) and development of processes to ensure reliable error detection. Engineeringbased QA approaches, including use of IMRT treatment delivery process trees, fault tree analysis and failure modes effects analysis would be described. Approaches to detect errors such as (1) during treatment delivery validation using exit fluence detectors (e.g. EPIDs); (2) analysis of treatment delivery via use of machine parameter log files; (3) dose recalculation using (3a) treatment planning system; (3b) record-and-verify; or (3c) entrance and exit fluence measurement parameters would be explained. The relative advantages and disadvantages of each method would be discussed. Schemes for error classification and root cause analysis would be described – steps which are essential for future error prevention. For each QA method, testing procedures and results would be presented indicating the types of errors that can be detected, those that cannot be detected, and the reliability of the error detection method (for example determined via ROC analysis). For speakers, we are seeking to engage non-commercially biased experts. Those listed below are a sub-sample of possible qualified individuals.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Modeling forest site productivity using mapped geospatial attributes within a South Carolina Landscape, USA

Spatially explicit mapping of forest productivity is important to assess many forest management alternatives. We assessed the relationship between mapped variables and site index of forests ranging from southern pine plantations to natural hardwoods on a 74,000-ha landscape in South Carolina, USA. Mapped features used in the analysis were soil association, land use condition in 1951, depth to groundwater, slope and aspect. Basal area, species composition, age and height were the tree variables measured. Linear modelling identified that plot basal area, depth to groundwater, soils association and the interactions between depth to groundwater and forest group, and between land use in 1951 and forest group were related to site index (SI) (R 2 =0.37), but this model had regression attenuation. We then used structural equation modeling to incorporate error-in-measurement corrections for basal area and groundwater to remove bias in the model. We validated this model using 89 independent observations and found the 95% confidence intervals for the slope and intercept of an observed vs. predicted site index error-corrected regression included zero and one, respectively, indicating a good fit. With error in measurement incorporated, only basal area, soil association, and the interaction between forest groups and land use were important predictors (R2 =0.57). Thus, we were able to develop an unbiased model of SI that could be applied to create a spatially explicit map based primarily on soils as modified by past (land use and forest type) and recent forest management (basal area).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Evidence for Reduced, Carbon-rich Regions in the Solar Nebula from an Unusual Cometary Dust Particle

Geochemical indicators in meteorites imply that most formed under relatively oxidizing conditions. However, some planetary materials, such as the enstatite chondrites, aubrite achondrites, and Mercury, were produced in reduced nebular environments. Because of large-scale radial nebular mixing, comets and other Kuiper Belt objects likely contain some primitive material related to these reduced planetary bodies. Here, we describe an unusual assemblage in a dust particle from comet 81P/Wild 2 captured in silica aerogel by the NASA Stardust spacecraft. The bulk of this ∼20 μ m particle is comprised of an aggregate of nanoparticulate Cr-rich magnetite, containing opaque sub-domains composed of poorly graphitized carbon (PGC). The PGC forms conformal shells around tiny 5–15 nm core grains of Fe carbide. The C, N, and O isotopic compositions of these components are identical within errors to terrestrial standards, indicating a formation inside the solar system. Magnetite compositions are consistent with oxidation of reduced metal, similar to that seen in enstatite chondrites. Similarly, the core–shell structure of the carbide + PGC inclusions suggests a formation via FTT reactions on the surface of metal or carbide grains in warm, reduced regions of the solar nebula. Together, the nanoscale assemblage in the cometary particle is most consistent with the alteration of primary solids condensed from a C-rich, reduced nebular gas. The nanoparticulate components in the cometary particle provide the first direct evidence from comets of reduced, carbon-rich regions that were present in the solar nebula.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Quality assurance for online adapted treatment plans: Benchmarking and delivery monitoring simulation

Purpose: An important challenge facing online adaptive radiation therapy is the development of feasible and efficient quality assurance (QA). This project aimed to validate the deliverability of online adapted plans and develop a proof-of-concept online delivery monitoring system for online adaptive radiation therapy QA. Methods: The first part of this project benchmarked automatically online adapted prostate treatment plans using traditional portal dosimetry IMRT QA. The portal dosimetry QA results of online adapted plans were compared to original (unadapted) plans as well as randomly selected prostate IMRT plans from our clinic. In the second part, an online delivery monitoring system was designed and validated via a simulated treatment with intentional multileaf collimator (MLC) errors. This system was based on inputs from the dynamic machine information (DMI), which continuously reports actual MLC positions and machine monitor units (MUs) at intervals of 50 ms or less during delivery. Based on the DMI, the system performed two levels of monitoring/verification during the delivery: (1) dynamic monitoring of cumulative fluence errors resulting from leaf position deviations and visualization using fluence error maps (FEMs); and (2) verification of MLC positions against the treatment plan for potential errors in MLC motion and data transfer at each control point. Validation of the online delivery monitoring system was performed by introducing intentional systematic MLC errors (ranging from 0.5 to 2 mm) to the DMI files for both leaf banks. These DMI files were analyzed by the proposed system to evaluate the system’s performance in quantifying errors and revealing the source of errors, as well as to understand patterns in the FEMs. In addition, FEMs from 210 actual prostate IMRT beams were analyzed using the proposed system to further validate its ability to catch and identify errors, as well as establish error magnitude baselines for prostate IMRT delivery. Results: Online adapted plans were found to have similar delivery accuracy in comparison to clinical IMRT plans when validated with portal dosimetry IMRT QA. FEMs for the simulated deliveries with intentional MLC errors exhibited distinct patterns for different MLC error magnitudes and directions, indicating that the proposed delivery monitoring system is highly specific in detecting the source of errors. Implementing the proposed QA system for online adapted plans revealed excellent delivery accuracy: over 99% of leaf position differences were within 0.5 mm, and >99% of pixels in the FEMs had fluence errors within 0.5 MU. Patterns present in the FEMs and MLC control point analysis for actual patient cases agreed with the error pattern analysis results, further validating the system’s ability to reveal and differentiate MLC deviations. Calculation of the fluence map based on the DMI was performed within 2 ms after receiving each DMI input. Conclusions: The proposed online delivery monitoring system requires minimal additional resources and time commitment to the current clinical workflow while still maintaining high sensitivity to leaf position errors and specificity to error types. The presented online delivery monitoring system therefore represents a promising QA system candidate for online adaptive radiation therapy.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

Evaluating probabilistic deep learning methods for uncertainty quantification of temperature downscaling

Deep learning (DL) has emerged as a promising tool for downscaling coarse-resolution climate data to high-resolution outputs, enabling improved regional climate predictions. A critical aspect of DL-based downscaling is the incorporation of uncertainty quantification (UQ), which enhances the interpretability and reliability of predictions—key factors for climate risk assessment and decision-making. This study develops a DL model to downscale 2 m temperature across the contiguous United States using reanalysis datasets. We systematically evaluate three epistemic UQ methods—deep ensembles (DEns), Monte Carlo dropout (MCD), and Flipout—based on their probabilistic accuracy, downscaling performance, sensitivity to geographical features, and computational efficiency. Results indicate that MCD generally outperforms Flipout and DEns in terms of calibration and downscaling accuracy. However, DEns demonstrate lower calibration errors in coastal regions, indicating its higher confidence within these areas. Flipout, in contrast, is more sensitive to elevation gradients and exhibits higher calibration errors in mountainous regions. Hence, the choice of UQ method for this task depends on the specific requirements of the application. For applications that prioritize overall calibration, downscaling accuracy, and computational efficiency, MCD is a strong candidate. These findings highlight the importance of selecting UQ methods based on application-specific requirements, such as geographical context and computational constraints. By addressing the trade-offs between UQ methods, this study provides actionable insights for improving the reliability, scalability, and utility of DL-based downscaling in climate science.

Environmental sciences↗
DOE OSTI2017

Quantifying the Accuracy and Uncertainty of Diurnal Thermodynamic Profiles and Convection Indices Derived from the Atmospheric Emitted Radiance Interferometer

Abstract While radiosondes have provided atmospheric scientists an accurate high-vertical-resolution profile of the troposphere for decades, they are unable to provide high-temporal-resolution observations without significant recurring expenses. Remote sensing technology, however, has the ability to monitor the evolution of the atmosphere in unprecedented detail. One particularly promising tool is the Atmospheric Emitted Radiance Interferometer (AERI), a passive ground-based infrared radiometer. Through a physical retrieval, the AERI can retrieve the vertical profile of temperature and humidity at a temporal resolution on the order of minutes. The synthesis of these two instruments may provide an improved diagnosis of the processes occurring in the atmosphere. This study provides a better understanding of the capabilities of the AERI in environments supportive of deep, moist convection. Using 3-hourly radiosonde launches and thermodynamic profiles retrieved from collocated AERIs, this study evaluates the accuracy of AERI-derived profiles over the diurnal cycle by analyzing AERI profiles in both the convective and stable boundary layers. Monte Carlo sampling is used to calculate the distribution of convection indices and compare the impact of measurement errors from each instrument platform on indices. This study indicates that the nonintegrated indices (e.g., lifted index) derived from AERI retrievals are more accurate than integrated indices (e.g., CAPE). While the AERI retrieval’s vertical resolution can inhibit precise diagnoses of capping inversions, the high-temporal-resolution nature of the AERI profiles overall helps in detecting rapid temporal changes in stability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Toward a systematic improvement of the fixed-node approximation in diffusion Monte Carlo for solids—A case study in diamond

While Diffusion Monte Carlo (DMC) is in principle an exact stochastic method for ab initio electronic structure calculations, in practice, the fermionic sign problem necessitates the use of the fixed-node approximation and trial wavefunctions with approximate nodes (or zeros). This approximation introduces a variational error in the energy that potentially can be tested and systematically improved. Here, we present a computational method that produces trial wavefunctions with systematically improvable nodes for DMC calculations of periodic solids. These trial wavefunctions are efficiently generated with the configuration interaction using a perturbative selection made iteratively (CIPSI) method. A simple protocol in which both exact and approximate results for finite supercells are used to extrapolate to the thermodynamic limit is introduced. This approach is illustrated in the case of the carbon diamond using Slater–Jastrow trial wavefunctions including up to one million Slater determinants. Fixed-node DMC energies obtained with such large expansions are much improved, and the fixed-node error is found to decrease monotonically and smoothly as a function of the number of determinants in the trial wavefunction, a property opening the way to a better control of this error. The cohesive energy extrapolated to the thermodynamic limit is in close agreement with the estimated experimental value. Interestingly, this is also the case at the single-determinant level, thus, indicating a very good error cancellation in carbon diamond between the bulk and atomic total fixed-node energies when using single-determinant nodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Towards Realistic and High Fidelity Models for Nuclear Reactor Power Synthesis Simulation with Self-Powered Neutron Detectors

As presented in this report, a weighting function–based inferencing method is being applied to synthesize the power distribution in next-generation and university research reactors based on simulated self power neutron detector (SPND) responses. The overall goal is to assess the impacts of sensor uncertainty and true power distribution perturbations on the error in the synthesized power distribution. Regarding sensor uncertainty, the NuScale Small Modular Reactor (SMR) and the Westinghouse AP1000 serve as testbeds for analyzing the impact of varying the sensor uncertainty, as well as varying the number of sensors per sensor string in the reactor core. The reactor models are informed by Monte Carlo N-Particle (MCNP) neutron flux tallies. For the NuScale SMR and Westinghouse AP1000, the SPND response functions (i.e., the response of the SPNDs to individual segments of fuel) were determined homogeneously. Regarding an analysis of power distribution perturbation detection, the Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor was used as a demonstration case with one particular arrangement of SPNDs; the response functions for this reactor model were determined heterogeneously, making this a uniquely high-fidelity demonstration of perturbation detection. Finally, SPND models generated in the Geometry and Tracking 4 (Geant4) code have been generated and tested for comparison with traditionally implemented analytical SPND models, with the intent for Geant4 integration with the full methodological framework. SPND current outputs as a function of distance from some fuel assembly segment in the NuScale SMR are compared with the analytically determined currents. Results from the sensor uncertainty simulations for the NuScale SMR and AP1000 indicate that the average error in the inferred power distribution on the fuel assembly segment level is reasonably low, being slightly less than the random uncertainty applied to all respective SPNDs in both cores. For example, if all SPNDs in the core have a random uncertainty of 5%, then the corresponding fuel assembly segment level error (i.e. difference between the true and inferred local power) is ~2–3%. However, the maximum error in the inferred power distribution on the fuel assembly segment level can be considerably high (>15%) when SPND random uncertainties start to exceed ~3%. In general, the average and maximum errors in the inferred power distribution were slightly higher in the AP1000 as opposed to the NuScale SMR for the sensor string configurations considered herein. Another result determined from analysis of the sensor uncertainty simulations was that increasing the number of SPNDs per string does not clearly reduce inferred power distribution error and can in fact make the error large in some cases; however, this assessment may skewed due to imposed iteration limits. Results from the perturbation detection demonstration using the high-fidelity TAMU TRIGA model indicate that, given the arrangement of 17 SPND strings and 4 SPNDs per string considered herein, there is a clear, provable ability to infer a localized Gaussian-type peak perturbation in the 3D power distribution. Such a perturbation was detected with an average fuel assembly segment level error of 0.19%, and the general visualization of the detected perturbation clearly indicates that the magnitude and shape were appropriately resolved. Finally, the electrical current output generated by the Geant4 modeled SPND indicates significant magnitude differences than the analytically modeled SPND, demonstrating the need for accurate SPND models which account for finite sensor geometry effects to inform the power synthesis work described herein.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Effects of error, chimera, bias, and GC content on the accuracy of amplicon sequencing

ABSTRACT Targeted amplicon sequencing is widely used in microbial ecology studies. However, sequencing artifacts and amplification biases are of great concern. To identify sources of these artifacts, a systematic analysis was performed using mock communities comprised of 16S rRNA genes from 33 bacterial strains. Our results indicated that while sequencing errors were generally isolated to low-abundance operational taxonomic units, chimeric sequences were a major source of artifacts. Singleton and doubleton sequences were primarily chimeras. Formation of chimeric sequences was significantly correlated with the GC content of the targeted sequences. Low-GC-content mock community members exhibited lower rates of chimeric sequence formation. GC content also had a large impact on sequence recovery. The quantitative capacity was notably limited, with substantial recovery variations and weak correlation between anticipated and observed strain abundances. The mock community strains with higher GC content had higher recovery rates than strains with lower GC content. Amplification bias was also observed due to the differences in primer affinity. A two-step PCR strategy reduced the number of chimeric sequences by half. In addition, comparative analyses based on the mock communities showed that several widely used sequence processing pipelines/methods, including DADA2, Deblur, UCLUST, UNOISE, and UPARSE, had different advantages and disadvantages in artifact removal and rare species detection. These results are important for improving sequencing quality and reliability and developing new algorithms to process targeted amplicon sequences. IMPORTANCE Amplicon sequencing of targeted genes is the predominant approach to estimate the membership and structure of microbial communities. However, accurate reconstruction of community composition is difficult due to sequencing errors, and other methodological biases and effective approaches to overcome these challenges are essential. Using a mock community of 33 phylogenetically diverse strains, this study evaluated the effect of GC content on sequencing results and tested different approaches to improve overall sequencing accuracy while characterizing the pros and cons of popular amplicon sequence data processing approaches. The sequencing results from this study can serve as a benchmarking data set for future algorithmic improvements. Furthermore, the new insights on sequencing error, chimera formation, and GC bias from this study will help enhance the quality of amplicon sequencing studies and support the development of new data analysis approaches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Measuring qubit stability in a gate-based NISQ hardware processor

Some of the most problematic issues that limit the implementation of applications on Noisy Intermediate Scale Quantum (NISQ) machines are the adverse impacts of both incoherent and coherent errors. We conducted an in-depth study of coherent errors on a quantum hardware platform using a transverse field Ising model Hamiltonian as a sample user application. We report here on the results from these computations using several error mitigation protocols that profile these errors and provide an indication of the hardware qubit stability. Through a detailed set of measurements we identify inter-day and intra-day qubit calibration drift and the impacts of quantum circuit placement on groups of qubits in different physical locations on the processor. This paper also discusses how these measurements can provide a better understanding of these types of errors and how they may improve efforts to validate the accuracy of quantum computations.

Yeter-Aydeniz, Kübra↗
DOE OSTI2014

WE-E-18A-09: Application of a Channelized Hotelling Observer Model to Evaluate Angiographic Imaging Equipment

Purpose: To develop and apply an observer model to objectively evaluate and compare the performance of different angiographic imaging equipment and acquisition variables. Methods: Image Acquisition— Iodine-based phantoms were created with target diameters: 0.5, 1, 2, and 4 mm. The phantoms were imaged using both planes of a bi-plane angiography system with detector pixel dimensions 0.1542 mm{sup 2} and 0.1842 mm{sup 2}, respectively. All four phantoms were imaged with magnification factors 1.5, 1.25 and 1 and with the large and small focal spots. Phantom position and the dose per frame (0.12– 0.24 μ Gy/frame) were varied for a single phantom size, magnification and focal spot. Observer Model— For each experimental condition, 1200 signal-present and signal-absent images were acquired and a detectability index (d') was calculated with a Gabor-channelized Hotelling observer (CHO) model. Detectability indices were evaluated as a function of dose, phantom size, and magnification. The model was then applied to compare d' of the two imaging planes and focal spots. Uncertainty in d' was estimated by bootstrapping the data and by examining the shift-variance of systems. Results: Detectability indices varied linearly with magnification and the square root of dose. For the 2 and 4 mm phantoms, d' varied linearly with diameter. For the 0.5 and 1 mm phantoms, d' expectedly deviated from this linear relationship due to substantial detector and focal spot blurring of the phantoms. The small focal spot yielded up to 50% greater d' values than the large focal spot. For the two detectors, differences in d' did not exceed the estimated ∼7% error. Conclusions: The detectability indices predictably scaled with dose, diameter, magnification, and focal spot size and serve to validate the model. Results demonstrate statistically similar target detectability for both investigated detectors, despite differences in pixel dimensions. This CHO model provides a framework to evaluate angiographic system performance.

60 APPLIED LIFE SCIENCES↗