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DOE OSTI2019

Delayed Gamma-ray Assay for Nuclear Materials Safeguards. Comprehensive Technology Readiness Assessment

Spectroscopic analysis of beta-delayed gamma-rays emitted from fission products following active interrogation was investigated as a non-destructive assay technique for detection and characterization of nuclear materials in shielded and complex configurations. This measurement technique is expected to be applicable to a variety of applications within the nuclear material safeguards, arms control, and emergency response areas, where active neutron interrogation is acceptable. Potential applications of the delayed gamma-ray assay in the nuclear material safeguards area include characterization of U and Pu isotopic content in spent and unirradiated nuclear fuel, enrichment measurements, verification of bulk material in containers, and the characterization of nuclear wastes. In the arms control area, this method can be used as a part of warhead dismantlement measurements to confirm separation of components, and may be applicable in warhead confirmation. In the context of emergency response, it can be used for detailed diagnostics of an unknown item. At present, the delayed gamma-ray assay technology reliably qualifies for the Technical Readiness Level 3 (TRL 3). The R&D work completed under this project has successfully demonstrated the empirical proof-of-concept for this active interrogation technology for a variety of measurement configurations, neutron sources, and nuclear material samples. A robust first-principles analytical signature modeling methodology was developed, experimentally validated, and can be easily extrapolated to a range of realistic measurement scenarios. Several response analysis methodologies have been implemented and deemed reliable for a variety of active interrogation applications in the areas of nuclear material safeguards, arms control, and emergency response. The initial readiness level before the start of this project was assessed at TRL 0, since only fragmentary records of the signature observations and speculative statements of the relevant non-destructive assay applications existed at that time. The delayed gamma-ray technology readiness can be easily advanced to TRL 4 in a short period, if a certain measurement application is specified and set for a demonstration in a laboratory environment. The critical hardware components of the delayed gamma-ray measurement technology (neutron generators, gamma-ray spectrometers) are readily available as COTS and can be configured for a specific deployment configuration. The primary risk of the delayed gamma-ray assay methodology is defined by the applicationspecific uncertainties. Evaluation of the system performance can be effectively completed once the expected measurement purpose, nuclear material characteristics, dimensions, and radiation exposure constraints are specified. A minor risk can be associated with the delayed gamma-ray response analysis techniques. Several approaches were proposed and demonstrated primarily using the modeled signatures. The observed performance may not be easily transferrable to the conditions of a real measurement setup, and some additional R&D may be required. Overall, the delayed gamma-ray assay technology can be recommended for follow-up demonstrations addressing relevant measurement applications in the areas of nuclear material safeguards, arms control, and emergency response.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Predicting transport of intra-articularly injected growth factor fusion proteins into human knee joint cartilage

There are no drugs or treatment methods known to prevent the development of post-traumatic osteoarthritis (PTOA), a type of osteoarthritis (OA) that is triggered by traumatic joint injuries and accounts for ~12% of the nearly 600 million OA cases worldwide. Lack of effective drug delivery techniques remains a major challenge in developing clinically effective treatments, but cationic delivery carriers can help overcome this challenge. Scaling up treatments that are effective in in vitro models to achieve success in preclinical in vivo models and clinical trials is also a challenging problem in the field. Here we use a cationic green fluorescent protein (GFP) as a carrier to deliver Insulin-Like Growth Factor 1 (IGF-1), a drug considered as a potential therapeutic for PTOA. GFP-IGF-1 conjugates were first synthesized as fusion proteins with different polypeptide linkers, and their transport properties were characterized in human cartilage explants. In vitro experimental data were used to develop a predictive mathematical transport model that was validated using an independent in vitro experimental data set. In this study, the model was used to predict the transport of these fusion proteins upon intra-articular injection into human knee joints. The predictions included results for the rate and extent of fusion protein penetration into cartilage, and the maximum levels of fusion proteins that would escape into systemic circulation through the joint capsule. Together, our transport measurements and model set the stage for translation of such explant culture studies to in vivo preclinical studies and potentially clinical application.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Dynamics of a relativistic jet through magnetized media

The merger of two neutron stars (NSs) produces the emission of gravitational waves, the formation of a compact object surrounded by a dense and magnetized environment. If the binary undergoes delayed collapse a collimated and relativistic jet, which will eventually produce a short gamma-ray burst (SGRB), may be launched. The interaction of the jet with the environment has been shown to play a major role in shaping the structure of the outflow that eventually powers the gamma-ray emission. In this paper, we present a set of 2.5D RMHD simulations that follow the evolution of a relativistic non-magnetized jet through a medium with different magnetization levels, as produced after the merger of two NSs. We find that the predominant consequence of a magnetized ambient medium is that of suppressing instabilities within the jet and preventing the formation of a series of collimation shocks. One implication of this is that internal shocks lose efficiency, causing bursts with low-luminosity prompt emission. On the other hand, the jet-head velocity and the induced magnetization within the jet are fairly independent of the magnetization of the ambient medium. Future numerical studies with a larger domain are necessary to obtain light curves and spectra in order to better understand the role of magnetized media.

(magnetohydrodynamics) MHD↗

DOE OSTI2022

Process-oriented stochastic perturbations applied to the parametrization of turbulence and shallow convection for ensemble prediction

Weather forecasting nowadays often requires some estimation of uncertainties associated with the output of meteorological models, in order to better inform decision making, especially in the context of intense weather events. Ensemble prediction systems provide such information through sets of possible scenarios which are designed to represent various uncertainty sources, including model uncertainties. A wide variety of methods have been proposed to estimate model uncertainties, among which perturbation methods targeting uncertain processes are a promising research field. Here, we focus on the representation of small-scale variability by process-oriented perturbation schemes applied to two key physical processes, namely turbulence and shallow convection. The perturbations are applied to a single-column version of the convection-permitting AROME model, in three idealized boundary-layer cases. Large-eddy simulations (LESs) of the same cases serve as a reference for the subgrid variability that has to be represented, and the results are also compared to those given by the Stochastically Perturbed Parametrization Tendencies (SPPT) method, which is a method commonly used by weather forecast centres to represent model uncertainty. The spread produced by our process-oriented perturbations of turbulence and shallow convection does not represent all the small-scale variability implied by the LESs for temperature and humidity. However, it is of a similar order of magnitude for the wind, thanks to perturbations generated by the stochastic turbulence scheme. The dispersion is structurally different from what is obtained with SPPT. It is non-negligible in the lower levels, where SPPT perturbations are usually suppressed because of numerical instabilities, indicating a possible complementarity between the schemes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

WE-AB-209-07: Explicit and Convex Optimization of Plan Quality Metrics in Intensity-Modulated Radiation Therapy Treatment Planning

Purpose: To formulate objective functions of a multicriteria fluence map optimization model that correlate well with plan quality metrics, and to solve this multicriteria model by convex approximation. Methods: In this study, objectives of a multicriteria model are formulated to explicitly either minimize or maximize a dose-at-volume measure. Given the widespread agreement that dose-at-volume levels play important roles in plan quality assessment, these objectives correlate well with plan quality metrics. This is in contrast to the conventional objectives, which are to maximize clinical goal achievement by relating to deviations from given dose-at-volume thresholds: while balancing the new objectives means explicitly balancing dose-at-volume levels, balancing the conventional objectives effectively means balancing deviations. Constituted by the inherently non-convex dose-at-volume measure, the new objectives are approximated by the convex mean-tail-dose measure (CVaR measure), yielding a convex approximation of the multicriteria model. Results: Advantages of using the convex approximation are investigated through juxtaposition with the conventional objectives in a computational study of two patient cases. Clinical goals of each case respectively point out three ROI dose-at-volume measures to be considered for plan quality assessment. This is translated in the convex approximation into minimizing three mean-tail-dose measures. Evaluations of the three ROI dose-at-volume measures on Pareto optimal plans are used to represent plan quality of the Pareto sets. Besides providing increased accuracy in terms of feasibility of solutions, the convex approximation generates Pareto sets with overall improved plan quality. In one case, the Pareto set generated by the convex approximation entirely dominates that generated with the conventional objectives. Conclusion: The initial computational study indicates that the convex approximation outperforms the conventional objectives in aspects of accuracy and plan quality.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Availability and Performance Loss Factors for U.S. PV Fleet Systems

In the PV Fleet Performance Data Initiative, we partner with photovoltaic (PV) fleet owners to collect time-series PV production data and publish aggregated, anonymized results. This report is an update of our previous publications, specifically a FY 2021 performance index publication and a FY 2022 fleet degradation analysis. In this analysis, we have increased our data participants and system totals by around 10% to 8.5 GW and 24,000 separate inverter data channels. Four major analysis topics are considered in this report: Performance Index (PI) trends, PV system availability, soiling losses, and PV system degradation. Performance Index and inverter availability are assessed on a larger set of data from our FY 2021 report: 1,128 systems compared with 200 systems from before. The increased number of systems is due to an improved data quality methodology, as well as introducing new systems to the analysis. Overall results are similar to previously published values - overall inverter availability is low in the first six months of system performance before reaching steady-state by the end of the first year. Excluding this six-month startup period, system-level aggregated data shows a median (P50) system availability of 0.99 and a lower 10th percentile (P90) value of 0.95 (Figure ES-1). A dependence on system size is also demonstrated, with worse inverter availability results for larger PV systems. Causes of this effect are under investigation, but may be impacted by inverter size, which also show lower availability for larger inverter sizes. This report also investigates PI, correcting for degradation, soiling, snow, and availability. Following these corrections, the median system PI over its entire lifetime is 0.95. PI values reported here are approximately 3% lower than what we presented in our previous FY 2021 report. Soiling loss is assessed in a comprehensive way for the first time in this report. Results are presented using the COmbined Degradation and Soiling (CODS) method, as implemented in RdTools (v3.0.0a4). Soiling values are presented for 255 systems, which indicated irradiance-weighted soiling loss greater than 1%. The values have been published in an updated NREL soiling map at nrel.gov/pv/soiling.html. Finally, we investigated system degradation using three different data analysis techniques: conventional RdTools (year-on-year (YOY)), CODS, and Performance Loss Rate (PLR) analysis. Overall degradation results are consistent with our previous publications. Rerunning conventional RdTools on our updated fleet shows that some data partners have systematically fallen below the median system degradation rate (change over time) of -0.75 %/year. A comparison with PLR analysis, which looks at change in annual PI over time, shows that median system degradation is consistent with -0.5% to -0.75% per year change. However, at the P90 value, system degradation is substantially faster. These two results are consistent and indicate that resulting degradation statistics depend to a great degree on the population of PV systems making up the analysis cohort and whether soiling impacts the systems. The use of CODS for degradation analysis provides a different method for degradation assessment, which explicitly excludes the impact of recoverable soiling on degradation analysis. Excluding soiling effects yields an annual system degradation around -0.5% per year on average. This indicates that a portion of system performance loss may be attributed to periodic soiling that is not fully recovered. This report provides PV system owners/operators with background and methods to analyze PV system performance, give guidance for expected cohort performance, and performance loss values for use in pro-forma financial models, which guide new-build system design and bankability reports.

14 SOLAR ENERGY↗

DOE OSTI2018

Well Design, Operation and Maintenance and Proactive Rehabilitation to Optimize Remediation Well Performance - 18605

Optimizing performance of extraction, injection and monitoring wells, which are integral components of groundwater remediation systems, result in lower life cycle costs and a higher probability of meeting project objectives. These wells provide the means to extract contaminated groundwater, inject reagents, treated water and clean water to create groundwater reaction/flushing zones, and to provide groundwater level, contaminant concentration and geochemical data. Initial costs associated with well installation and associated pipelines and treatment systems are significant project expenditures related to site remediation. However, the life cycle costs for wells are dominated by the long-term operation and maintenance (O and M) expenditures. Remediation wells are particularly susceptible to various types of fouling that impact well performance and, therefore, drive up operating costs. Simply defined, fouling is the result of any biological, geochemical or physical process that negatively impacts the intended performance of a remediation well. Fouling decreases well performance by effectively reducing hydraulic communication between the well and the surrounding formation. Oftentimes this occurs via clogging screens and/or gravel pack/formation pore space by bacterial or chemical byproducts and gases, which can lead to corrosion of metal components and spreading fouling deposits to pipelines and surface treatment systems. Ultimately, this results in reduced hydraulic performance in extraction and injection wells and result in erroneous water level and chemical parameter concentration measurements in monitoring wells. Remediation well fouling cannot be eliminated, and natural fouling processes are exacerbated by the installation and operation of remedial systems. Steps required to extend the life of remediation wells and to lower life cycle costs are discussed in this paper in order to establish the required approach to effective system management. These optimization approaches have been developed through years of operation and maintenance of complex large-scale plume remediation systems utilizing a variety of subsurface in-situ and ex-situ technologies. Remediation well performance can be improved by: - careful site characterization, - appropriate well design, - proper well installation and development, - thoughtful and adaptable operation and maintenance, - well performance maintenance tracking and, - proactive well rehabilitation. Clear understanding of the site hydro-stratigraphy and geochemical settings places constraints on the compatibility of well materials and the configurations of well screens. Proper well design, including collection and analysis (sieve/grain-size) of screen zone formation samples, assures that wells can be optimally installed, developed and redeveloped during well rehabilitation. Design considerations should include proper sizing of filter packs and well screens, casing/screen diameter, well material selection/compatibility, expected life/use, and well head configuration to allow for future access. Applying appropriate and effective well installation and development methods are of paramount importance and rely on a good understanding of site characteristics (e.g., geologic setting) as well as local drilling company expertise and experience. Different approaches to operation and maintenance can greatly affect the degree of fouling, these include limiting reagent concentrations, maintaining submerged well screens and filtering injection water to prevent the introduction of fouling enhancing constituents. Tracking well performance by monitoring changes in system operation and metrics such as specific capacity or injectivity for extraction and injection wells, respectively, or turbidity and chemical analyses for monitoring wells is key to identifying well maintenance issues early when well rehabilitation can be most effective. Proactive well rehabilitation can include mechanical brushing, surging and jetting, chemical treatment or other specialized approaches; however, the approach needs to be based on a site-specific understanding of the predominant fouling mechanisms. Collection and analyses of fouling deposits can provide guidance for selection of rehabilitation methods and chemicals that will be most effective. Application of these approaches have led to extended operational life for reagent injection wells, which can foul quickly, from months to years. Additionally, proper maintenance will often lead to increased and extended productivity of the well. For extraction wells, this translates to a higher sustainable yield, which means shorter cleanup times. Similarly, for injection wells, proper maintenance allows for the introduction of a greater volume of reagents over a shorter period, thus, shorter cleanup times that reduce overall project costs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Natural Gas Drilling near the Underground Nuclear Test Site of Rulison, Colorado - 19571

In 1969, the Project Rulison test was conducted in western Colorado using a nuclear device to stimulate natural gas production by fracturing low-permeability, gas-bearing rock. The presence of radionuclides (specifically tritium) in the produced gas persisted above acceptable levels, and the test was abandoned. Advances in hydrofracturing technology over the past 10-15 years have revolutionized the extraction of hydrocarbons from low-permeability formations, leading to a significant increase of drilling in the Rulison area. Drilling activity nearing the Rulison site has raised concerns that remnant radioactivity might be encountered. The site, now under the care of the US Department of Energy (DOE), is protected by a 16-hectare (40 acre) institutional control boundary (Lot 11) that prohibits drilling or extraction of materials below 1830 meters (6000 feet) within the lot boundary. Drilling within 0.8 kilometer (0.5 mile) of the site requires a hearing before the Colorado Oil and Gas Conservation Commission. DOE recommends that gas developers adopt a conservative, staged drilling approach, allowing gas reserves near the Rulison site to be recovered in a manner that minimizes the likelihood of encountering contamination. The staged approach calls for collecting data from wells away from the site before drilling closer. For instance, the wells 1.2 kilometer (0.75 mile) west of the site did not encounter any unexpected geologic conditions and now have 8 years of production without encountering any detonation-related radionuclides. The next set of wells would be 0.8 kilometer (0.5 mile) west of the site. This sequential method drills first at locations with a low probability of encountering contamination and then moves closer. This process protects public safety while allowing the collection of additional data to confirm that contamination has not migrated beyond the 16-hectare (40-acre) institutional control boundary. The staged drilling approach was simulated with a modeling effort that estimates the current extent of contamination and the potential for production-induced contaminant migration to nearby wells. The model incorporates geologic data from nearby wells and was calibrated to production data from both the reentry well production testing (1970-1971) and the wells 1.2 kilometer (0.75 mile) from the site that began producing in 2010. The geologic data include both sand/shale distribution statistics as well as the tendency of hydrofractures to preferentially propagate east and west due to the regional stress field. The model results indicate that it is unlikely that wells near the site would ever encounter site-related radionuclides. (authors)

03 NATURAL GAS↗

DOE OSTI2019

A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems

Presently the training of neural networks relies on data of comparable accuracy but in real applications only a very small set of high-fidelity data is available while inexpensive lower fidelity data may be plentiful. We propose a new composite neural network (NN) that can be trained based on multi-fidelity data. It is comprised of three NNs, with the first NN trained using the low-fidelity data and coupled to two high-fidelity NNs, one with activation functions and another one without, in order to discover and exploit nonlinear and linear correlations, respectively, between the low-fidelity and the high-fidelity data. We first demonstrate the accuracy of the new multi-fidelity NN for approximating some standard benchmark functions but also a 20-dimensional function that is not easy to approximate with other methods, e.g. Gaussian process regression. Subsequently, we extend the recently developed physics-informed neural networks (PINNs) to be trained with multi-fidelity data sets (MPINNs). MPINNs contain four fully-connected neural networks, where the first one approximates the low-fidelity data, while the second and third construct the correlation between the low- and high-fidelity data and produce the multi-fidelity approximation, which is then used in the last NN that encodes the partial differential equations (PDEs). Specifically, by decomposing the correlation into a linear and nonlinear part, the present model is capable of learning both the linear and complex nonlinear correlations between the low- and high-fidelity data adaptively. By training the MPINNs, we can: (1) obtain the correlation between the low- and high-fidelity data, (2) infer the quantities of interest based on a few scattered data, and (3) identify the unknown parameters in the PDEs. In particular, we employ the MPINNs to learn the hydraulic conductivity field for unsaturated flows as well as the reactive models for reactive transport. The results demonstrate that MPINNs can achieve relatively high accuracy based on a very small set of high-fidelity data. Despite the relatively low dimension and limited number of fidelities (two-fidelity levels) for the benchmark problems in the present study, the proposed model can be readily extended to very high-dimensional regression and classification problems involving multi-fidelity data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Multilevel Spectral Coarsening for Graph Laplacian Problems with Application to Reservoir Simulation

We extend previously developed two-level coarsening procedures for graph Laplacian problems written in a mixed saddle point form to the fully recursive multilevel case. The resulting hierarchy of discretizations gives rise to a hierarchy of upscaled models, in the sense that they provide approximation in the natural norms (in the mixed setting). This property enables us to utilize them in three applications: (i) as an accurate reduced model, (ii) as a tool in multilevel Monte Carlo simulations (in application to finite volume discretizations), and (iii) for providing a sequence of nonlinear operators in a full approximation scheme for solving nonlinear pressure equations discretized by the conservative two-point flux approximation. Finally, we illustrate the potential of the proposed multilevel technique in all three applications on a number of popular benchmark problems used in reservoir simulation.

multilevel Monte Carlo↗

DOE OSTI2020

Major Revisions in Arthropod Phylogeny Through Improved Supermatrix, With Support for Two Possible Waves of Land Invasion by Chelicerates

Deep phylogeny involving arthropod lineages is difficult to recover because the erosion of phylogenetic signals over time leads to unreliable multiple sequence alignment (MSA) and subsequent phylogenetic reconstruction. One way to alleviate the problem is to assemble a large number of gene sequences to compensate for the weakness in each individual gene. Such an approach has led to many robustly supported but contradictory phylogenies. A close examination shows that the supermatrix approach often suffers from two shortcomings. The first is that MSA is rarely checked for reliability and, as will be illustrated, can be poor. The second is that, to alleviate the problem of homoplasy at the third codon position of protein-coding genes due to convergent evolution of nucleotide frequencies, phylogeneticists may remove or degenerate the third codon position but may do it improperly and introduce new biases. We performed extensive reanalysis of one of such “big data” sets to highlight these two problems, and demonstrated the power and benefits of correcting or alleviating these problems. Our results support a new group with Xiphosura and Arachnopulmonata (Tetrapulmonata + Scorpiones) as sister taxa. This favors a new hypothesis in which the ancestor of Xiphosura and the extinct Eurypterida (sea scorpions, of which many later forms lived in brackish or freshwater) returned to the sea after the initial chelicerate invasion of land. Our phylogeny is supported even with the original data but processed with a new “principled” codon degeneration. We also show that removing the 1673 codon sites with both AGN and UCN codons (encoding serine) in our alignment can partially reconcile discrepancies between nucleotide-based and AA-based tree, partly because two sequences, one with AGN and the other with UCN, would be identical at the amino acid level but quite different at the nucleotide level.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Forecasting constraints on the mean free path of ionizing photons at z ≥ 5.4 from the Lyman-α forest flux autocorrelation function

ABSTRACT Fluctuations in Lyman-α (Ly α) forest transmission towards high-z quasars are partially sourced from spatial fluctuations in the ultraviolet background, the level of which are set by the mean free path of ionizing photons (λmfp). The autocorrelation function of Ly α forest flux characterizes the strength and scale of transmission fluctuations and, as we show, is thus sensitive to λmfp. Recent measurements at z ∼ 6 suggest a rapid evolution of λmfp at z > 5.0 which would leave a signature in the evolution of the autocorrelation function. For this forecast, we model mock Ly α forest data with properties similar to the XQR-30 extended data set at 5.4 ≤ z ≤ 6.0. At each z, we investigate 100 mock data sets and an ideal case where mock data matches model values of the autocorrelation function. For ideal data with λmfp = 9.0 cMpc at z = 6.0, we recover $\lambda _{\text{mfp}}=12^{+6}_{-3}$ cMpc. This precision is comparable to direct measurements of λmfp from the stacking of quasar spectra beyond the Lyman limit. Hypothetical high-resolution data leads to a $\sim 40~{{\ \rm per\ cent}}$ reduction in the error bars over all z. The distribution of mock values of the autocorrelation function in this work is highly non-Gaussian for high-z, which should caution work with other statistics of the high-z Ly α forest against making this assumption. We use a rigorous statistical method to pass an inference test, however future work on non-Gaussian methods will enable higher precision measurements.

Astronomy & Astrophysics↗

DOE OSTI2015

Structure of the ordered hydration of amino acids in proteins: analysis of crystal structures

The hydration of protein crystal structures was studied at the level of individual amino acids. The dependence of the number of water molecules and their preferred spatial localization on various parameters, such as solvent accessibility, secondary structure and side-chain conformation, was determined. Crystallography provides unique information about the arrangement of water molecules near protein surfaces. Using a nonredundant set of 2818 protein crystal structures with a resolution of better than 1.8 Å, the extent and structure of the hydration shell of all 20 standard amino-acid residues were analyzed as function of the residue conformation, secondary structure and solvent accessibility. The results show how hydration depends on the amino-acid conformation and the environment in which it occurs. After conformational clustering of individual residues, the density distribution of water molecules was compiled and the preferred hydration sites were determined as maxima in the pseudo-electron-density representation of water distributions. Many hydration sites interact with both main-chain and side-chain amino-acid atoms, and several occurrences of hydration sites with less canonical contacts, such as carbon–donor hydrogen bonds, OH–π interactions and off-plane interactions with aromatic heteroatoms, are also reported. Information about the location and relative importance of the empirically determined preferred hydration sites in proteins has applications in improving the current methods of hydration-site prediction in molecular replacement, ab initio protein structure prediction and the set-up of molecular-dynamics simulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

TH-AB-209-02: Gadolinium Measurements in Human Bone Using in Vivo K X-Ray Fluorescence (KXRF) Technique

Purpose: Improvement in an in vivo K x-ray fluorescence system, based on 109Cd source, for the detection of gadolinium (Gd) in bone has been investigated. Series of improvements to the method is described. Gd is of interest because of the extensive use of Gd-based contrast agents in MR imaging and the potential toxicity of Gd exposure. Methods: A set of seven bone equivalent phantoms with different amount of Gd concentrations (from 0–100 ppm) has been developed. Soft tissue equivalent plastic plates were used to simulate the soft tissue overlaying the tibia bone in an in vivo measurement. A new 5 GBq 109Cd source was used to improve the source activity in comparison to the previous study (0.17 GBq). An improved spectral fitting program was utilized for data analysis. Results: The previous published minimum detection limit (MDL) for Gd doped phantom measurements using KXRF system was 3.3 ppm. In this study the MDL for bare bone phantoms was found to be 0.8 ppm. Our previous study used only three layers of plastic (0.32, 0.64 and 0.96 mm) as soft tissue equivalent materials and obtained the MDL of 4–4.8 ppm. In this study the plastic plates with more realistic thicknesses to simulate the soft tissue covering tibia bone (nine thicknesses ranging from 0.61–6.13 mm) were used. The MDLs for phantoms were determined to be 1.8–3.5 ppm. Conclusion: With the improvements made to the technology (stronger source, improved data analysis algorithm, realistic soft tissue thicknesses), the MDL of the KXRF system to measure Gd in bare bone was improved by a factor of 4.1. The MDL is at the level of the bone Gd concentration reported in literature. Hence, the system is ready to be tested on human subjects to investigate the use of bone Gd as a biomarker for Gd toxicity.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

An Orthogonal Recursive Bisection (ORB) Based Time Advancement Algorithm for CFD-DEM Solvers

The time integration of the granular phase in coupled computational fluid dynamics (CFD) – discrete element method (DEM) simulations presents a unique computational challenge brought about by the large variations in particle collisional time scales. Particles in the dilute regions of the computational domain can be advanced with large time steps while dense regions require much smaller time increments. However, the time step size in most solvers is globally set as the limit for accuracy and stability imposed by the collisions and is typically orders of magnitude less than that required away from collisions. This work addresses this precise issue and provides a strategy to avoid the use of a global conservative small time step size for the entire set of particles.A novel time stepping algorithm for CFD-DEM solvers using a partitioning approach using orthogonal recursive bisection (ORB) that allows for variable time steps among particles is described and its computational performance is compared against baseline explicit methods, typically used in several CFD-DEM solvers. ORB has advantages of being relatively quick and easy to update incrementally and has the required heuristic behavior (i.e., it will split the region in half with a cluster on each side) when groups of particles are well separated (clustered). The algorithm presented in this work uses a local time stepping approach to resolve collisional time scales for subsets of particles that are present at the leaves of the ORB, thereby resulting in substantial reduction of computational cost. The parallel implementation of this method where a ``knapsack” algorithm is used in tandem with ORB for effective load-balancing is also presented, where a best possible partitioning is obtained based on number of particles and local time-stepping costs. The algorithm is tested against benchmark problems with varying particle distributions that include fluidized bed and riser flow scenarios. Preliminary results indicate that the approach is 2-3X faster than traditional explicit methods for problems that involve both dense and dilute regions, while maintaining the same level of accuracy.

adaptive timestepping↗

DOE OSTI2016

SU-C-204-03: DFT Calculations of the Stability of DOTA-Based-Radiopharmaceuticals

Purpose: Application of the density function theory (DFT) to investigate the structural stability of complexes applied in cancer therapy consisting of the 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) chelated to Ac225, Fr221, At217, Bi213, and Gd68 radio-nuclei. Methods: The possibility to deliver a toxic payload directly to tumor cells is a highly desirable aim in targeted alpha particle therapy. The estimation of bond stability between radioactive atoms and the DOTA chelating agent is the key element in understanding the foundations of this delivery process. Thus, we adapted the Vienna Ab-initio Simulation Package (VASP) with the projector-augmented wave method and a plane-wave basis set in order to study the stability and electronic properties of DOTA ligand chelated to radioactive isotopes. In order to count for the relativistic effect of radioactive isotopes we included Spin-Orbit Coupling (SOC) in the DFT calculations. Five DOTA complex structures were represented as unit cells, each containing 58 atoms. The energy optimization was performed for all structures prior to calculations of electronic properties. Binding energies, electron localization functions as well as bond lengths between atoms were estimated. Results: Calculated binding energies for DOTA-radioactive atom systems were −17.792, −5.784, −8.872, −13.305, −18.467 eV for Ac, Fr, At, Bi and Gd complexes respectively. The displacements of isotopes in DOTA cages were estimated from the variations in bond lengths, which were within 2.32–3.75 angstroms. The detailed representation of chemical bonding in all complexes was obtained with the Electron Localization Function (ELF). Conclusion: DOTA-Gd, DOTA-Ac and DOTA-Bi were the most stable structures in the group. Inclusion of SOC had a significant role in the improvement of DFT calculation accuracy for heavy radioactive atoms. Our approach is found to be proper for the investigation of structures with DOTA-based-radiopharmaceuticals and will enhance our understanding of processes occurring at subatomic levels.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

RISK-INFORMED EXTERNAL HAZARDS ANALYSIS BY EEVE TOOLKIT

Introducing risk-informed safety analyses for external events can bring sensible benefits to the nuclear power industry easing the regulatory burden introduced in the aftermath of the Fukushima accident. In the framework of the US-DOE Light-Water Reactor Sustainability program, Risk-Informed Margin Characterization project (LWRS-RISMC), research activities were conducted at INL for developing and applying a toolkit for performing risk-informed external hazards analysis. The “EEVE” (External EVEnts) toolkit, a chain of INL and state-of-the-art codes, was set-up and applied for simulating earthquake-induced transients with internal flooding in a PWR. This was done using methodology set-up for evaluating new data and determining critical areas that would benefit most from advanced analysis methods. The methodology is agnostic and it can be applied to other external hazards than just seismic and flooding (e.g., high winds, intense precipitation, etc.). The first step was the deterministic calculations for evaluating the propagation of a set of earthquakes and for determining the effects on a fire suppression system in an auxiliary building. These deterministic calculations were performed using the LS-DYNA and the OPENSEE structural mechanics codes. Probability failures and event trees of a generic 3-loops Westinghouse PWR were derived from a generic SAPHIRE model. Seismically induced Loss of Offsite Power, Station Blackout, and fire suppression piping failure events were considered. SAPHIRE code allowed a pre-screening of all possible branches of the event tree and a selection of those with the largest Core Damage Frequency increase for further analysis using dynamic PRA methods. INL's EMRALD code performed dynamic PRA calculations of the identified sequences, integrating risk analysis with on-line deterministic safety analysis results (seismically-induced internal flooding calculations by NEUTRINO code and system analysis by RELAP5-3D code). RELAP5-3D Best-Estimate calculations coupled with RAVEN statistical code were used for deriving limit surfaces as function of relevant transient parameters. This data was used by EMRALD for determining the final core status (core damage/core safe). Finally, the coupling of seismic, flooding, system thermal-hydraulic, uncertainty quantification and probabilistic risk analysis for an advanced risk-informed external hazards analysis was demonstrated. Results showed the sensible decrease in the level of conservatism achieved using the developed risk-informed methodology, which allowed also improving the evaluation of the failure modes and failure probabilities of different components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

OECD/NEA EGMPEBV Activities in Multi-Physics Verification and Validation

The Expert Group on Multi-Physics Experimental Data, Benchmarks and Validation (EGMPEBV) was established in 2014 by the Nuclear Energy Agency (NEA) at the Organization for Economic Co-operation and Development (OECD) to establish processes for certification of experimental data and development of benchmark models for validation of Multi-Physics (MP) Modeling and Simulation (M and S) computational systems. The aim of the group is to provide member countries with guidelines and recommendations for validating and improving their novel multi-physics simulations, and with an access to key experimental data. To be used to their full potential, these novel tools will require a more complex suite of validation experiments due to the multiple energy, spatial and temporal scales, as well as the number of physical phenomena being simulated. They will also require accurate measurements of all terms, including coupling terms representing the feedback effects, in situations where the appropriate experimental techniques and facilities might not exist today. However, the ability to conduct validation experiments has for certain applications progressed at a slower pace than for computational methods, or in some cases it has significantly regressed (through shutdown of facilities, or through retirement of experts). In addition, as modelling capabilities are reaching deeper levels in single physics phenomena and in coupled behaviors, appropriate experimental techniques may not yet exist. Validation of multiple physics models requires a wide variety of experimental data, which emphasizes the importance of maximizing the use of historically accumulated data to avoid the significant cost of performing similar experiments today. Moreover, the pedigree and quality of this data as it pertains to modern day simulation methods may be insufficient for rigorous validation of high fidelity modeling and simulation tools. Thus, these data can often exhibit limitations including a lack of measurement accuracy or a lack of knowledge of the measurement uncertainty in the experimental techniques; an absence of measurements for some critical parameters; an obscuring of relationships between individual physics phenomena owing to the output data resolution; or simply an inability to allow for a detailed reinterpretation of the experiments based on the documented information. The organization of the EGMPEBV relies on three Task Forces, focused on 1) Experimental Data Qualification and Benchmark Evaluation; 2) Methods and Standards, and 3) Specific Applications. Task Force 1 is focused on providing better and more accurate experimental datasets, which support validation of high-fidelity multi-physics modelling and simulation (M and S) tools. At the same time it has to consider the incompleteness of past experimental data sets (in terms of data, documentation, or uncertainties) and with the limited number of available multi-physics experimental facilities. Task Force 2 is designed to develop validation methods and guidelines, and uncertainty qualification for the new family of multi-physics, multi-scale codes in the context of emerging demands such as longer fuel cycles and power uprate. Task Force 3 is focused on applications of validation experiments and has the objective to organize multi-physics M and S benchmarks involving validation experiments.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗