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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

United States Department of Energy severe accident research following the Fukushima Daiichi accidents

The U.S. Department of Energy (DOE) has played a major role in the U.S. response to the events at Fukushima Daiichi. During the first several weeks following the accident, U.S. assistance efforts were guided by results from a significant and diverse set of analyses. In the months that followed, a coordinated analysis activity aimed at gaining a more thorough understanding of the accident sequence was completed using laboratory-developed, system-level best-estimate accident analysis codes, while a parallel analysis was conducted by U.S. industry. A comparison of predictions for Unit 1 from these two studies indicated significant differences between MAAP and MELCOR results for key plant parameters, such as in-core hydrogen production. On that basis, a crosswalk was completed to determine the key modeling variations that led to these differences. In parallel with these activities, it became clear that there was a need to perform a technology gap evaluation on accident-tolerant components and severe accident analysis methodologies with the goal of identifying any data and/or knowledge gaps that may exist given the current state of light water reactor (LWR) severe accident research and augmented by insights from Fukushima. In addition, there is growing international recognition that data from Fukushima could significantly reduce uncertainties related to severe accident progression, particularly for boiling water reactors. On these bases, a group of U. S. experts in LWR safety and plant operations was convened by the DOE Office of Nuclear Energy (DOE-NE) to complete technology gap analysis and Fukushima forensics data needs identification activities. The results from these activities were used as the basis for refining DOE-NE's severe accident research and development (R&D) plan. Finally, this paper provides a high-level review of DOE-sponsored R&D efforts in these areas, including planned activities on accident-tolerant components and accident analysis methods.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Modeling Photovoltaics Innovation and Deployment Dynamics

PV’s historically rapid cost reduction is exceptional among technologies. Further cost reductions could play a major role in increasing deployment in the future. To enable such cost reductions, new modeling frameworks are needed to understand the determinants of innovation in PV. In this project, we study the mechanisms driving PV module and system cost reductions, delving deeply into the specific technological innovations that have occurred in the past and the policies that encouraged them, and also opportunities for future cost reduction and widespread deployment. The project contributes new fundamental insight on the determinants of technological innovation by developing novel methods and insights that are generalizable and can therefore be applied to other technologies. The results will allow policy makers, engineers, and other stakeholders to better prioritize their efforts and investments in the future. The project is organized around four journal articles as described below. The first article [1] identifies ‘low-level’ (e.g. conversion efficiency improvement) and ‘high- level’ (e.g. R&D efforts) mechanisms of cost reduction in PV systems (Tasks 1-4). This work builds on a previous DOE grant, where we developed a framework for technological innovation leading to PV module cost reduction [2]. We advance a method to disentangle the contributions of physical (‘hardware’) and non-physical (‘soft technology’) changes. Our results uncover reasons behind the relatively slow evolution of soft technology and can inform new innovation approaches to these technologies. The second article [3] identifies specific engineering or institutional innovations that enabled the low-level mechanisms of cost reduction in PV module and balance-of-systems (BOS) (Tasks 5, 9, 10). We identify 85 innovations and connect them to the cost variables they affected. By developing an innovations typology, this study shows the differences between the types of innovations affecting PV modules and BOS components. Finally, by analyzing the industry origins of innovations, this study also finds that PV was well-positioned within an ecosystem of continuously advancing technologies. The third article [4] studies prospective cost reduction opportunities (Task 10). We explore how design approaches that emphasize standardization and automation, such as plug-and-play PV systems, can create cost reduction opportunities by reducing interactions and speeding up activities with high process costs. We show that this can lead to cost reduction in cost components with the most untapped opportunity for improvement such as installation labor, overhead, electrical BOS, and customer acquisition. The fourth article [5] analyzes how various policies supporting PV deployment and R&D contributed to PV’s cost improvement by enabling high-level mechanisms, specific innovations, and ultimately low-level mechanisms of cost reduction (Tasks 8, 13, 14). We investigate examples from different countries and connect these policies to quantifiable cost change mechanisms. Our study sheds light on the roles that different nations played over time, through a diverse set of policy approaches.

14 SOLAR ENERGY↗
DOE OSTI2015

Single Vocal Cord Irradiation: Image Guided Intensity Modulated Hypofractionated Radiation Therapy for T1a Glottic Cancer: Early Clinical Results

Purpose: To report, from a retrospective analysis of prospectively collected data, on the feasibility, outcome, toxicity, and voice-handicap index (VHI) of patients with T1a glottic cancer treated by a novel intensity modulated radiation therapy technique developed at our institution to treat only the involved vocal cord: single vocal cord irradiation (SVCI). Methods and Materials: Thirty patients with T1a glottic cancer were treated by means of SVCI. Dose prescription was set to 16 × 3.63 Gy (total dose 58.08 Gy). The clinical target volume was the entire vocal cord. Setup verification was done by means of an online correction protocol using cone beam computed tomography. Data for voice quality assessment were collected prospectively at baseline, end of treatment, and 4, 6, and 12 weeks and 6, 12, and 18 months after treatment using VHI questionnaires. Results: After a median follow-up of 30 months (range, 7-50 months), the 2-year local control and overall survival rates were 100% and 90% because no single local recurrence was reported and 3 patients died because of comorbidity. All patients have completed the intended treatment schedule; no treatment interruptions and no grade 3 acute toxicity were reported. Grade 2 acute dermatitis or dysphagia was reported in only 5 patients (17%). No serious late toxicity was reported; only 1 patient developed temporary grade 2 laryngeal edema, and responded to a short-course of corticosteroid. The VHI improved significantly, from 33.5 at baseline to 9.5 and 10 at 6 weeks and 18 months, respectively (P<.001). The control group, treated to the whole larynx, had comparable local control rates (92.2% vs 100%, P=.24) but more acute toxicity (66% vs 17%, P<.0001) and higher VHI scores (23.8 and 16.7 at 6 weeks and 18 months, respectively, P<.0001). Conclusion: Single vocal cord irradiation is feasible and resulted in maximal local control rate at 2 years. The deterioration in VHI scores was slight and temporary and subsequently improved to normal levels. Long-term follow-up is needed to consolidate these promising results.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

SAM Plug-in Development (Phase I Final Report)

The DOE Office of Nuclear Energy (NE) has created an extensive set of advanced modeling and simulation tools for nuclear engineering analysis. The advanced capabilities of these newer analysis codes require more in-depth training, skills, and knowledge in order to effectively utilize them for the design, analysis, and licensing of advanced nuclear systems and experiments. A high learning curve for inexperienced users may deter organizations from incorporating these tools into their internal processes. This project involved development of a plug-in to the Symbolic Nuclear Analysis Package (SNAP) for the System Analysis Module (SAM) tool. SAM is an advanced system analysis tool for reactor transient analyses being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SNAP provides a highly flexible framework for creating, modifying and documenting input for engineering analysis codes such as SAM as well as extensive functionality for submitting, monitoring, and interacting with the codes through an intuitive graphical user interface (GUI). The common user interface provided by SNAP minimizes the learning curve for engineers starting with a new analysis code and provides an intuitive framework for transitioning between different analysis codes. SNAP provides a powerful but intuitive interface to facilitate access to advanced modeling and simulation tools for inexperienced users. Unlike many “form based” GUI’s, SNAP maps each engineering code’s component input to an internal database which manages all component input parameters along with component interconnections. This level of abstraction permits SNAP to support several advanced capabilities such as renodalization, model validation and consistency checks, embedded documentation, model notebook generation, data ownership and reviewer tracking, and variable assignment for inputs to name a few. SNAP includes a built-in Python interpreter and is interfaced to several commercial and open source packages including CPython, MATLAB/OCTAVE, Microsoft Office, Open Office, and SANDIA’s DAKOTA package which provides Uncertainty Quantification analysis through the SNAP plug-ins. Phase I of this project involved development a fully functional basic SAM plug-in to SNAP. This plug-in provides the ability to import existing models, graphically construct, edit and submit models using SNAP’s extensive functionality.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Assessing heterogeneity of patient and health system delay among TB in a population with internal migrants in China

Backgrounds The diagnostic delay of tuberculosis (TB) contributes to further transmission and impedes the implementation of the End TB Strategy. Therefore, we aimed to describe the characteristics of patient delay, health system delay, and total delay among TB patients in Shanghai, identify areas at high risk for delay, and explore the potential factors of long delay at individual and spatial levels. Method The study included TB patients among migrants and residents in Shanghai between January 2010 and December 2018. Patient and health system delays exceeding 14 days and total delays exceeding 28 days were defined as long delays. Time trends of long delays were evaluated by Joinpoint regression. Multivariable logistic regression analysis was employed to analyze influencing factors of long delays. Spatial analysis of delays was conducted using ArcGIS, and the hierarchical Bayesian spatial model was utilized to explore associated spatial factors. Results Overall, 61,050 TB patients were notified during the study period. Median patient, health system, and total delays were 12 days (IQR: 3–26), 9 days (IQR: 4–18), and 27 days (IQR: 15–43), respectively. Migrants, females, older adults, symptomatic visits to TB-designated facilities, and pathogen-positive were associated with longer patient delays, while pathogen-negative, active case findings and symptomatic visits to non-TB-designated facilities were associated with long health system delays (LHD). Spatial analysis revealed Chongming Island was a hotspot for patient delay, while western areas of Shanghai, with a high proportion of internal migrants and industrial parks, were at high risk for LHD. The application of rapid molecular diagnostic methods was associated with reduced health system delays. Conclusion Despite a relatively shorter diagnostic delay of TB than in the other regions in China, there was vital social-demographic and spatial heterogeneity in the occurrence of long delays in Shanghai. While the active case finding and rapid molecular diagnosis reduced the delay, novel targeted interventions are still required to address the challenges of TB diagnosis among both migrants and residents in this urban setting.

Sun, Ruoyao↗
DOE OSTI2019

Risk-informed Physical Security Using Dynamic Force-on-Force Modelling Tools (ABSTRACT)

Physical security requirement of nuclear power plants (NPPs) in the US is regulated in a mainly prescriptive manner. This “one size fits all” approach may consequently overlook plant-specific characteristics which are beneficial for the inherent safety and security of the plant. Although a performance-based security measure has been promulgated in 10 CFR 73.55(r), current evaluation methods generally emphasize static and conservative assumptions on physical security uncertainties. This conservatism contributes to the overall operational and maintenance costs, which account to 70% of total operating expenditures for an NPP. This paper describes an ongoing work at the Idaho National Laboratory within the Light Water Reactor Sustainability pathway, which aims to optimize physical protection system with regards to system effectiveness and dollar costs. To achieve this goal, a risk-informed approach to physical security is proposed. This approach leverages the Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool to model facility infiltration and Force-on-Force (FoF) engagement in a dynamic manner. The dynamic FoF analysis was conducted by coupling human performance uncertainties modeled in EMRALD to existing commercial 3-dimensional FoF software, i.e. SCRIBE3D, AVERT and Simajin. Meanwhile, risk analysis was accomplished by coupling the attack outcomes to existing plant Probabilistic Risk Assessment (PRA) model with FLEX strategy. This approach reduces the conservatisms in security modeling and further acknowledges the possibility for plant operators to mitigate the attack outcomes. A sabotage attack on a hypothetical NPP facility was devised to demonstrate the proposed methodology. Dynamic FoF rules were implemented in EMRALD coupled to SCRIBE3D. This dynamic evaluation revealed an additional 21% system effectiveness in protecting the target set relative to the static modelling approach. Furthermore, the conditional core damage probability could be reduced by up to 46% by crediting operator actions in mitigating the sabotage outcomes. We evaluated the relative importance of each component of the physical security posture included in the model and assessed tradeoffs between components to identify potential opportunities for cost reduction while maintaining a specific level of system effectiveness. Results of the cost analysis will be presented in the conference. This study is expected to help NPP operators in allocating resources optimally to satisfy the security requirements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Describing patterns of familial cancer risk in subfertile men using population pedigree data

STUDY QUESTION Can we simultaneously assess risk for multiple cancers to identify familial multicancer patterns in families of azoospermic and severely oligozoospermic men? SUMMARY ANSWER Here, distinct familial cancer patterns were observed in the azoospermia and severe oligozoospermia cohorts, suggesting heterogeneity in familial cancer risk by both type of subfertility and within subfertility type. WHAT IS KNOWN ALREADY Subfertile men and their relatives show increased risk for certain cancers including testicular, thyroid, and pediatric. STUDY DESIGN, SIZE, DURATION A retrospective cohort of subfertile men (N = 786) was identified and matched to fertile population controls (N = 5674). Family members out to third-degree relatives were identified for both subfertile men and fertile population controls (N = 337 754). The study period was 1966–2017. Individuals were censored at death or loss to follow-up, loss to follow-up occurred if they left Utah during the study period. PARTICIPANTS/MATERIALS, SETTING, METHODS Azoospermic (0 × 10 6 /mL) and severely oligozoospermic (<1.5 × 10 6 /mL) men were identified in the Subfertility Health and Assisted Reproduction and the Environment cohort (SHARE). Subfertile men were age- and sex-matched 5:1 to fertile population controls and family members out to third-degree relatives were identified using the Utah Population Database (UPDB). Cancer diagnoses were identified through the Utah Cancer Registry. Families containing ≥10 members with ≥1 year of follow-up 1966–2017 were included (azoospermic: N = 426 families, 21 361 individuals; oligozoospermic: N = 360 families, 18 818 individuals). Unsupervised clustering based on standardized incidence ratios for 34 cancer phenotypes in the families was used to identify familial multicancer patterns; azoospermia and severe oligospermia families were assessed separately. MAIN RESULTS AND THE ROLE OF CHANCE Compared to control families, significant increases in cancer risks were observed in the azoospermia cohort for five cancer types: bone and joint cancers hazard ratio (HR) = 2.56 (95% CI = 1.48–4.42), soft tissue cancers HR = 1.56 (95% CI = 1.01–2.39), uterine cancers HR = 1.27 (95% CI = 1.03–1.56), Hodgkin lymphomas HR = 1.60 (95% CI = 1.07–2.39), and thyroid cancer HR = 1.54 (95% CI = 1.21–1.97). Among severe oligozoospermia families, increased risk was seen for three cancer types: colon cancer HR = 1.16 (95% CI = 1.01–1.32), bone and joint cancers HR = 2.43 (95% CI = 1.30–4.54), and testis cancer HR = 2.34 (95% CI = 1.60–3.42) along with a significant decrease in esophageal cancer risk HR = 0.39 (95% CI = 0.16–0.97). Thirteen clusters of familial multicancer patterns were identified in families of azoospermic men, 66% of families in the azoospermia cohort showed population-level cancer risks, however, the remaining 12 clusters showed elevated risk for 2-7 cancer types. Several of the clusters with elevated cancer risks also showed increased odds of cancer diagnoses at young ages with six clusters showing increased odds of adolescent and young adult (AYA) diagnosis [odds ratio (OR) = 1.96–2.88] and two clusters showing increased odds of pediatric cancer diagnosis (OR = 3.64–12.63). Within the severe oligozoospermia cohort, 12 distinct familial multicancer clusters were identified. All 12 clusters showed elevated risk for 1–3 cancer types. An increase in odds of cancer diagnoses at young ages was also seen in five of the severe oligozoospermia familial multicancer clusters, three clusters showed increased odds of AYA diagnosis (OR = 2.19–2.78) with an additional two clusters showing increased odds of a pediatric diagnosis (OR = 3.84–9.32). LIMITATIONS, REASONS FOR CAUTION Although this study has many strengths, including population data for family structure, cancer diagnoses and subfertility, there are limitations. First, semen measures are not available for the sample of fertile men. Second, there is no information on medical comorbidities or lifestyle risk factors such as smoking status, BMI, or environmental exposures. Third, all of the subfertile men included in this study were seen at a fertility clinic for evaluation. These men were therefore a subset of the overall population experiencing fertility problems and likely represent those with the socioeconomic means for evaluation by a physician. WIDER IMPLICATIONS OF THE FINDINGS This analysis leveraged unique population-level data resources, SHARE and the UPDB, to describe novel multicancer clusters among the families of azoospermic and severely oligozoospermic men. Distinct overall multicancer risk and familial multicancer patterns were observed in the azoospermia and severe oligozoospermia cohorts, suggesting heterogeneity in cancer risk by type of subfertility and within subfertility type. Describing families with similar cancer risk patterns provides a new avenue to increase homogeneity for focused gene discovery and environmental risk factor studies. Such discoveries will lead to more accurate risk predictions and improved counseling for patients and their families. STUDY FUNDING/COMPETING INTEREST(S) This work was funded by GEMS: Genomic approach to connecting Elevated germline Mutation rates with male infertility and Somatic health (Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): R01 HD106112). The authors have no conflicts of interest relevant to this work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Spectrotemporal CT data acquisition and reconstruction at low dose

Purpose: X-ray computed tomography (CT) is widely used, both clinically and preclinically, for fast, high-resolution anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. The authors propose and demonstrate a projection acquisition and reconstruction strategy for 5D CT (3D + dual energy + time) which recovers spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols. Methods: The authors approach the 5D reconstruction problem within the framework of low-rank and sparse matrix decomposition. Unlike previous work on rank-sparsity constrained CT reconstruction, the authors establish an explicit rank-sparse signal model to describe the spectral and temporal dimensions. The spectral dimension is represented as a well-sampled time and energy averaged image plus regularly undersampled principal components describing the spectral contrast. The temporal dimension is represented as the same time and energy averaged reconstruction plus contiguous, spatially sparse, and irregularly sampled temporal contrast images. Using a nonlinear, image domain filtration approach, the authors refer to as rank-sparse kernel regression, the authors transfer image structure from the well-sampled time and energy averaged reconstruction to the spectral and temporal contrast images. This regularization strategy strictly constrains the reconstruction problem while approximately separating the temporal and spectral dimensions. Separability results in a highly compressed representation for the 5D data in which projections are shared between the temporal and spectral reconstruction subproblems, enabling substantial undersampling. The authors solved the 5D reconstruction problem using the split Bregman method and GPU-based implementations of backprojection, reprojection, and kernel regression. Using a preclinical mouse model, the authors apply the proposed algorithm to study myocardial injury following radiation treatment of breast cancer. Results: Quantitative 5D simulations are performed using the MOBY mouse phantom. Twenty data sets (ten cardiac phases, two energies) are reconstructed with 88 μm, isotropic voxels from 450 total projections acquired over a single 360° rotation. In vivo 5D myocardial injury data sets acquired in two mice injected with gold and iodine nanoparticles are also reconstructed with 20 data sets per mouse using the same acquisition parameters (dose: ∼60 mGy). For both the simulations and the in vivo data, the reconstruction quality is sufficient to perform material decomposition into gold and iodine maps to localize the extent of myocardial injury (gold accumulation) and to measure cardiac functional metrics (vascular iodine). Their 5D CT imaging protocol represents a 95% reduction in radiation dose per cardiac phase and energy and a 40-fold decrease in projection sampling time relative to their standard imaging protocol. Conclusions: Their 5D CT data acquisition and reconstruction protocol efficiently exploits the rank-sparse nature of spectral and temporal CT data to provide high-fidelity reconstruction results without increased radiation dose or sampling time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Benchmarking the completely renormalised equation-of-motion coupled-cluster approaches for vertical excitation energies

When vertical energies are excited for a comprehensive test set of about 150 singlet excited states of 28 medium-sized organic molecules computed using two variants of the completely renormalised (CR) equation-of-motion (EOM) coupled-cluster (CC) method with singles, doubles, and non-iterative triples, abbreviated as δ-CR-EOMCCSD(T), and the analogous two variants of the newer, left-eigenstate δ-CR-EOMCC(2,3) approach are benchmarked against the previously published CASPT2, CC3, and EOMCCSDT-3 results, as well as the suggested theoretical best estimate (TBE) values. The δ-CR-EOMCC approaches are also used to identify and characterise about 50 additional excited states, including several states having substantial two-electron excitation components, which have not been found in the previous work and which can be used in future benchmark studies. We demonstrated that the non-iterative triples corrections to the EOMCCSD excitation energies defining the relatively inexpensive, single-reference, black-box δ-CR-EOMCC approaches provide significant improvements in the EOMCCSD data, while closely matching the results of the iterative and considerably more expensive CC3 and EOMCCSDT-3 calculations and their CASPT2 and TBE counterparts. It is also shown that the δ-CR-EOMCC methods, especially δ-CR-EOMCC(2,3), are capable of bringing the results of the CC3 and EOMCCSDT-3 calculations to a closer agreement with the CASPT2 and TBE data, demonstrating the utility of the cost-effective δ-CR-EOMCC methods in applications involving molecular electronic spectra. Finally, we show that there may exist a relationship between the magnitude of the triples corrections defining δ-CR-EOMCC approaches and the reduced excitation level diagnostic resulting from EOMCCSD.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Understanding the Hierarchy of Dense Subgraphs in Stationary and Temporally Varying Setting

Graphs are widely used to model relationships in a wide variety of domains such as sociology, bioinformatics, infrastructure, the WWW, to name a few. One of the key observations is that while real-world graphs are often globally sparse, they are locally dense. In other words, the average degree is often quite small (say at most 10 in a million vertex graph), but vertex neighborhoods are often dense. Finding dense subgraphs is a critical aspect of graph mining It has been used for finding communities and spam link farms in web graphs, graph visualization, real-time story identification, DNA motif detection in biological networks, finding correlated genes, epilepsy prediction, finding price value motifs in financial data, graph compression, distance query indexing, and increasing the throughput of social networking site servers. However, most standard formulations of this problem (like clique, quasi-clique, k-densest subgraph) are NP-hard. Furthermore, current dense subgraph finding algorithms usually optimize some objective, and only find a few such subgraphs without providing any structural relations, whereas the goal is rarely to find the "true optimum," but to identify many (if not all) dense substructures, understand their distribution in the graph, and ideally determine relationships among them. In this project, we first aim to devise algorithms and provide 3 implementations with nice visualizations to find the hierarchy between dense subgraphs, and then understand the structure of the hierarchy to gain more insight on the hidden patterns in real-world networks. Another important aspects in graph analysis is the temporal nature of networks. Networks evolve over time and in many applications data arrives at a high velocity, and thus it is important to design algorithms that can process data efficiently. We report three main results towards identifying dense structures in large evolving graphs. First, we will show how the hierarchical connectedness structure can be maintained efficiently, where connectedness is defined by increasing levels of connectivity strength. Next, we present dense structure can be identified in bipartite graphs without building projection graphs. And finally, we present a new method for peeling algorithms This new approach avoids sequential nature of peeling algorithms and is amenable to parallelization, which is crucial for processing high velocity data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Transition Core Planning and Safety Analyses in Support of LEU Fuel Conversion of the University of Missouri Research Reactor (MURR)

The University of Missouri Research Reactor (MURR®) is one of six U.S. High Performance Research Reactors (USHPRR), including one critical facility, that is working with the National Nuclear Security Administration (NNSA) Office of Material Management and Minimization (M3) Reactor Conversion Program to convert from highly enriched uranium (HEU) to low-enriched uranium (LEU) fuel. The M3 Reactor Conversion USHPRR Project objectives include the development of LEU fuel element designs that will ensure safe reactor operations and to maintain the existing experimental performance of each facility. The work is being conducted through many inter-related activities being completed by four Project Pillars: Fuel Qualification (FQ), Fuel Fabrication (FF), Reactor Conversion (RC), and Cross Cutting (CC). A new type of LEU fuel based on an alloy of uranium-10 wt% molybdenum (U-10Mo) is expected to allow the conversion of those USHPRR, like MURR, requiring higher density fuels. The very-high-density LEU U-10Mo monolithic fuel is currently undergoing irradiation testing and post-irradiation examination under a planned and documented fuel qualification effort. The FQ Pillar will document fuel property and fuel performance data and qualify the fuel for use in these reactors. The FF Pillar is fabricating fuel for ongoing and future irradiation tests, as well as conducting fabrication demonstrations to validate or update preliminary fabrication assumptions. The FF Pillar is also working to develop and install commercial manufacturing capacity with the U-10Mo monolithic fuel to produce prototypic fuel. Working with the RC Pillar at Argonne, MURR has progressed through a preliminary fuel element design using preliminary data for the proposed monolithic alloy of U-10Mo. Analyses were completed in previous work that found for typical equilibrium operations with the preliminary LEU fuel element design, in conjunction with a power uprate to 12 MW and appropriate changes to the MURR Limiting safety system settings (LSSS), MURR will have adequate margins to safety for steady-state operations and postulated transient accidents and will have experimental performance in key locations that meets or exceeds current operations with HEU fuel. The purpose of this work is to develop a sequence of transition cycles that will enable MURR to transition from operation with the reactor core loaded with fresh LEU fuel elements only to typical equilibrium operations with mixed-burnup cores following conversion while meeting operational requirements on safety and experimental performance. It is expected that the use of fresh LEU fuel at conversion and subsequent low burnup of the LEU fuel elements that will initially be available for use following conversion will result in critical control blade positions that will substantially change the axial power distribution in the core and the neutron flux available in key experimental locations relative to equilibrium LEU operations. Given the constraints of MURR safety margins, operational practices, and production and research, a novel method has been developed to identify a transition sequence that minimizes the time MURR operates atypically compared to the current prototypic cycles using HEU fuel. The proposed transition sequence moves quickly to the same sort of equilibrium cycles for the LEU fuel that have already been evaluated in documented preliminary safety analyses. Although shifting the neutron flux peak to the lower half of the core during initial cycles with LEU at 12 MW reduces the experiment performance in some key locations relative to current HEU operations at 10 MW, all LEU cores provide an average performance that meets or exceeds that of HEU. An LEU cycle is reached that meets or exceeds the level of experimental performance predicted for current HEU and equilibrium LEU operations in more than 450 key locations identified by a reactor specialist at MURR by the 23rd cycle following conversion and that afterwards will enable MURR to consistently meet its experimental performance requirements. The proposed transition sequence only requires the fabrication of 34 fresh LEU elements in the first year of operation and does not exceed the anticipated availability of fresh elements that can be produced by the fuel fabricator. By the third year after conversion, 22 fresh LEU elements will be required each year, which is the same as expected for equilibrium LEU operations and the same as current operations with HEU fuel. The proposed transition sequence thus combines a relatively short time period before equilibrium burnup is achieved, a temporary increase of fuel elements needed annually relative to typical operations that are within the production capabilities of the fuel fabricator, and demonstrates comparable experimental performance of the LEU cores relative to current HEU operations. Further measures may be taken to reduce any initial experimental performance penalty even further, where possible, by repositioning certain experiments to leverage the increased performance in the lower axial experimental positions in the initial cycles following conversion or leaving the experiments in the irradiation facilities longer in order to achieve the required neutron fluence. This analysis may require refinement depending on the experimental facilities in use at the time of conversion. Nonetheless, the results presented here, including the experimental performance, core burnup, and critical control blade positions throughout the transition cycles, show that the proposed transition cycle fuel management patterns are consistent with what is expected and desired for MURR operation with LEU U-10Mo fuel. Detailed core power distributions from the neutronics models were also used to evaluate safety margins during steady-state operations for the selected transition cycles and the equilibrium LEU core. It is shown that there are adequate safety margins for both steady-state operations and postulated accident scenarios. For the steady-state operations with the preliminary LEU fuel element design the analysis predicts at least 2.49 MW margin to the onset of flow instability at the LSSS power of 15 MW. Considering the LSSS power is 125% of full license power, the margin to OFI is sufficient. In addition, the critical heat flux ratio at LSSS power is well above the requirement of CHFR > 2.0 from NUREG-1537 for all considered cases. For postulated transient accidents, the minimum margin to the fuel temperature safety limit is at least 109 °C. In summary, the proposed sequence of core loadings for MURR operations following conversion to LEU fuel and a power uprate to 12 MW provides sufficient safety margins for both steady-state operations and postulated transient accidents during a proposed sequence of transition cycles to equilibrium operations. Analysis has shown that there are some local experimental performance penalties during the initial cycles. Although there are local shifts in the experimental performance, on average all LEU cores at 12 MW have equal or higher performance than HEU at 10 MW. Temporary adjustments are being planned that will produce suitable experimental performance during these cycles. The results indicate that for the equilibrium LEU core the experimental performance exceeds that of current HEU operations in all key locations while also demonstrating sufficient safety margins.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Application of High Performance Computing for Simulating Cycle-to-Cycle Variation in Dual-Fuel Combustion Engines

Interest in operational cost reduction is driving engine manufacturers to consider lower-cost fuel substitution in heavy-duty diesel engines. These dual-fuel (DF) engines could be operated either in diesel-only mode or operated with premixed natural gas (NG) ignited by a pilot flame of compression-ignited direct-injected diesel fuel. One promising application is that of large-bore, medium-speed engines such as those used in locomotives. With realistic natural gas substitution levels in the fleet of locomotives currently in service, such fuel substitution could result in billions of dollars of savings annually in the US alone. However, under certain conditions, dual-fuel operation can result in increased cycle-to-cycle variability (CCV) during combustion, resulting in variations in cylinder pressure and work extraction. In certain situations, the CCV of dual-fuel operation can be notably higher than that of diesel-only combustion under similar operating conditions. Excessive CCV can limit the NG substitution rate and operating range of a dual-fuel engine by increasing emissions and reducing engine stability, reliability and fuel efficiency via incomplete natural-gas combustion. Running multiple engine cycles in series to simulate CCV can be quite time consuming. Hence innovative modelling techniques and large computing resources are needed to investigate the factors affecting CCV in dual-fuel engines. This paper discusses the use of the High Performance Computing resource Titan, at the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, to investigate cycle-to-cycle combustion variability of a dual-fuel engine. The CONVERGE CFD software was used to simulate multiple, parallel single cycles of dual-fuel combustion with perturbed operating parameters and boundary conditions. These perturbations are imposed according to a sparse grids sampling of the parameter space. The sampling scheme chosen is similar to a design of experiments method but uses functions designed to minimize the number of samples required to achieve a desired degree of accuracy. The perturbed input parameters were connected to engine performance output over a large parameter space. Additionally, the same methodology was used to perform a set of diesel-only simulations at similar operating conditions to assess the numerical capability of capturing relatively low combustion variation. Lastly, this technique is expected to be useful to understand and predict combustion stability limits (knock and misfire) which are important for designing dual-fuel engines with improved operability and reliability.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

SU-F-J-159: Influence of the Elevated Posterior Position by Using the Customized Vacuum-Bag On the Abdominal MR Image Quality: A Quantitative Phantom Study

Purpose: Signal-to-noise ratio(SNR) of MR abdominal imaging in diagnostic radiology is maximized by minimizing the coil-to-patient distance. However, for radiotherapy applications, customized vacuum-bag is needed for abdominal immobilization at the cost of the increasing distance to the posterior spine coil. This sub-optimized coil setting for RT applications may compromise image quality, such as SNR and homogeneity, thus potentially affect tissue delineation. In this study, we quantitatively evaluate the effect of the vertical position change on SNR and image quality change using an ACR MR phantom. Methods: An ACR MR phantom was placed on the flat couch top. Images were acquired using an 18-channel body array coil and spine coil on a dedicated 1.5T MR-simulator. The scan was repeated three times with the ACR phantom elevated up to 7.5cm from the couch top, with a step size of 2.5cm. All images were acquired using standard ACR test sequence protocol of 2D spin-echo T1-weighted(TR/TE=500/200ms) and T2-weighted(TR/TE1/TE2=2000/20/80) sequences. For all scans, pre-scan normalization was turned on, and the distance between the phantom and the anterior 18-channel body array coil was kept constant. SNR was calculated using the slice with a large water-only region of the phantom. Percent intensity uniformity(PIU) and low contrast object detectability(LCD) were assessed by following ACR test guidelines. Results: The decrease in image SNR(from 335.8 to 169.3) and LCD(T1: from 31 to 19 spokes, T2: 26 to 16 spokes) were observed with increasing vertical distance. After elevating the phantom by 2.5cm(approximately the thickness of standard vacuum-bag), SNR change(from 335.8 to 275.5) and LCD(T1: 31 to 26 spokes, T2: 26 to 21 spokes) change were noted. However, similar PIU was obtained for all choices of vertical distance (T1: 94.5%–95.0%, T2: 94.4%–96.8%). Conclusion: After elevating the scan object, reduction in SNR level and contrast detectability but no change in image homogeneity was observed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Enhancements to the RAVEN code in FY16

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies. RAVEN has currently reached a good level of maturity in terms of deployed state-of-art and advanced capabilities. The main subject of this report is to show the activities that have been recently accomplished: • Implementation of ensemble modeling for time-series, and • initial implementation of model validation for surrogate models, and • advanced visualization capability for topology based data analysis The development of ensemble modeling for time-series has been performed in order to begin tackling the needs of those RISMC applications that need to communicate 1-Dimensional information (e.g. power histories, etc.) among different models. In this document the implementation details and an application example is reported. The second subject of this report is about the initial development of methods, within the RAVEN framework, to assess the validity of the predictive capabilities of surrogate models. Indeed, after the construction of a surrogate tight to a certain physical model, it is crucial to assess the goodness of its representation, in order to be confident with its prediction. In this initial activity, a cross-validation technique has been employed. This report will highlight the implementation details and proof its correct implementation by an application example. The final subject of this report is about the implementation of advanced visualization capability in RAVEN, for interactive data analysis. Indeed, RAVEN offers several post-processing capabilities that can structurally decompose data extracted from experimental results offering both data clustering/partitioning and dimensionality reduction techniques. A disadvantage of the workflow available in RAVEN is that it treats these as black box operations and the user is expected to know specific information about their data including the number of partitions to expect in some cases or the “correct” parameter settings for a particular algorithm. In order to overcome this limitation, it has been added an interactive user interface that can be run in RAVEN to explore different parameter settings on the fly specifically for the topological post-processor and allows the user to explore the data interactively. The design of this user interface is generalizable to other algorithms and can be used as a model to generate more dynamic and user-friendly visualization capabilities within RAVEN.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Assessment of Multiple Monitoring Methods for Detection of Brine and CO2 Leakage

We assess the effectiveness of four surface-based geophysical methods and in situ monitoring of pressure and chemical changes for detecting brine and CO2 leakage from legacy wells into underground sources of drinking water (USDW) overlying a CO2 storage reservoir. This is the first such effort to evaluate and compare six monitoring methods for detection of CO2 leakage. This assessment, conducted in support of the USDOE National Risk Assessment Partnership (NRAP), utilizes 3000 synthetic data sets, generated in an uncertainty quantification (UQ) model framework. This framework combines the results of (1) a CO2 storage reservoir model of a hypothetical storage operation of 5 MT/yr for 50 years into the 1700-m deep Vedder Fm. at a site near Kimberlina, California with (2) wellbore leakage models of a legacy well and (3) multi-phase flow and reactive transport models of brine and CO2 plume migration in aquifer layers overlying the storage reservoir. Leakage drives subsurface changes, quantified by pressure plumes, CO2-saturation plumes, and total dissolved solids (TDS) plumes, the latter being related to changes in pH and species concentrations. Depending on the depth of leakage, aquifer permeability, and regional groundwater gradient, pressure plume volumes can become larger than the CO2 and TDS plumes; however, reaching detectable thresholds may take too long to be useful. For a single monitoring well located 500 m downgradient of a leaky legacy well, a depth of 570 m is found to be optimal for sampling pressure and chemical changes. We assess four surface-based geophysical monitoring methods: electrical resistivity tomography (ERT), magnetotellurics (MT), gravity, and seismic methods. Sensors cover a 4-km × 2-km area. Both ERT and MT methods are sensitive to changes in CO2 saturation and TDS concentration, whereas gravity and seismic methods detect changes in CO2 saturation. The six monitoring methods complement each other in space and time, and we find that a minimum of 20 kT of CO2 leakage is required for the leakage plume to be detected. Of the four surface-based geophysical methods, gravity monitoring appears to be the most sensitive to CO2 leaks, while the usefulness of in situ pressure and chemical monitoring will depend on the level of unfilterable background noise. Geophysical monitoring methods may detect a leak anywhere in a large area and in a large depth range, but the effectiveness of pressure and chemical monitoring depends on the number of monitoring wells, where those wells are located, and the depth of sampling. Surface-based geophysical monitoring methods are cost-effective alternatives to in situ pressure and chemical monitoring methods.

NRAP, CCS, monitoring, geophysical methods, gravit↗
DOE OSTI2015

On the validity of the basis set superposition error and complete basis set limit extrapolations for the binding energy of the formic acid dimer

We report the variation of the binding energy of the Formic Acid Dimer with the size of the basis set at the Coupled Cluster with iterative Singles, Doubles and perturbatively connected Triple replacements [CCSD(T)] level of theory, estimate the Complete Basis Set (CBS) limit, and examine the validity of the Basis Set Superposition Error (BSSE)-correction for this quantity that was previously challenged by Kalescky, Kraka, and Cremer (KKC) [J. Chem. Phys. 140, 084315 (2014)]. Our results indicate that the BSSE correction, including terms that account for the substantial geometry change of the monomers due to the formation of two strong hydrogen bonds in the dimer, is indeed valid for obtaining accurate estimates for the binding energy of this system as it exhibits the expected decrease with increasing basis set size. We attribute the discrepancy between our current results and those of KKC to their use of a valence basis set in conjunction with the correlation of all electrons (i.e., including the 1s of C and O). We further show that the use of a core-valence set in conjunction with all electron correlation converges faster to the CBS limit as the BSSE correction is less than half than the valence electron/valence basis set case. The uncorrected and BSSE-corrected binding energies were found to produce the same (within 0.1 kcal/mol) CBS limits. We obtain CCSD(T)/CBS best estimates for D{sub e} = − 16.1 ± 0.1 kcal/mol and for D{sub 0} = − 14.3 ± 0.1 kcal/mol, the later in excellent agreement with the experimental value of −14.22 ± 0.12 kcal/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Demonstration of Wide Area Radiological Decontamination and Mitigation Technologies for Building Structures and Vehicles - 16508

Researchers at the U.S. Environmental Protection Agency in collaboration with the Department of Homeland Security conducted the 'Wide-Area Urban Radiological Contaminant, Mitigation, and Clean-Up Technology Demonstration' in Columbus, Ohio on June 22-25, 2015. EPA's National Homeland Security Research Center (NHSRC) demonstrated five wide-area radiological decontamination technologies (including strippable coatings, gels, and chemical foam technologies) on an urban building. Decontamination technologies were applied to remove the contaminants from the building's surfaces by physical, chemical, or other methods, which in practice could reduce radiation exposure level. In addition, NHSRC teamed with the Department of Homeland Security (DHS) to demonstrate several radiological contaminant mitigation technologies including building and vehicle wash technologies, as well as several approaches to contain wash water and radioactive particles. 'Radiological contaminant mitigation' technologies are measures taken to reduce adverse impacts of radiological contamination on people and the environment, and facilitate such purposes as restoration of first responder services and critical infrastructure. Radiological contaminant mitigation technologies are designed for containing and removing radiological contamination on the surface in the first hours or days following a radiological event (early phase response). Such technologies include 'radiological particle containment', which is design to prevent the spread of particles which might result from vehicle or foot traffic. Radiological particle containment technologies are applicable for early phase response to contain the radionuclides and to reduce radiation dose to responders and the public. Mitigation also includes 'gross decontamination' technologies, which perform a type of decontamination that is conducted with the goal of reducing contamination levels. This reduction may not meet final cleanup levels, but may be useful to mitigate some public hazard or contain contamination. The purpose of the demonstrations was to educate potential end-users and stakeholders of this technology about a 'Toolbox of Options' for radiological decontamination, as well as radiological contaminant mitigation. Both demonstrations were conducted using a 75-year old brick building and the surrounding area (including parking lots) in Columbus, OH. No radioactive contaminants were applied during either demonstration, as the objective was to duplicate and implement realistic operational conditions for these technologies. Surrogate contaminants such as particle tracers were used in several demonstrations. The decontamination technologies were used in a scaled-up setting with application to the building. Contaminant mitigation technologies were demonstrated on the building as well as on vehicles. Example technology application techniques/accessories included an articulating boom lift, repelling boatswain chair, stand-alone surface material structures, high-volume foam applicators, fire truck foam applicator, a vehicle wash tent for vehicles, particle tracers to simulate radiological contaminants, and high- and low-technology liquid containment approaches. Results and stakeholder observations from the demonstration are now publically in a report entitled 'Technical Report for the Demonstration of Radiological Decontamination and Mitigation Technologies for Building Structures and Vehicles' available at http://www.epa.gov/hsresearch Example information that was obtained included decontamination rate, contaminant mitigation and containment capacity, user friendliness of each technology, the required utilities (electric, water, etc.) for each technology, skill of worker required, and the cost. The condition (color, texture, integrity, etc.) of each building material present on the structure along with all structural components such as gutters, windows, doors, etc. were carefully examined and documented. All demonstrations were open to individuals, organizations, and local, state, federal, tribal, and international governments who may be involved with implementing or planning radiological incident response. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗