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DOE OSTI2024

Qualitative and Quantitative Evaluation for Representative Human Reliability Analysis Methods

The Korea Institute of Nuclear Safety (KINS) is the regulatory expert organization established by the Korean government to strengthen the nation’s technical capabilities relating to nuclear safety regulation. KINS oversees the technical aspects of nuclear safety regulation, including safety reviews, inspections, education, and safety research—all conducted based on technical knowledge and accumulated regulatory experience. In 2023, KINS requested that Idaho National Laboratory (INL) validates representative human reliability analysis (HRA) methods used throughout the world, thus affording KINS with a basis for determining an HRA method adequate for its domestic regulatory purposes. The present paper mainly examines INL’s efforts in this regard. The resulting INL study covered four representative HRA methods widely used by nuclear utilities and regulatory institutes. These methods were qualitatively evaluated by applying specific evaluation criteria and determining how well each method reflected critical HRA issues. For this assessment, INL benchmarked the Halden International HRA Empirical Study. Using the Halden empirical data, along with information on human failure events (HFEs), the present study employed the selected HRA methods to estimate human error probabilities (HEPs) for the HFEs. It also performed statistical analyses to compare the HEPs predicted via the HRA methods against those from the Halden empirical data.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2020

High Temperature Additive Architectures for 65% Efficiency (Final Report)

GE Power (GEP) proposed a development program that targets advanced high temperature additive components that contribute towards the DOE’s goal for advanced gas turbines that are capable of 65%, or greater, efficiency in combined cycle application. GEP proposed to leverage state-of-the-art additive manufacturing to develop novel and innovative component airfoil and end wall architectures that provide cooling flow savings while maintaining the component durability expected in today’s gas turbines. The objective of this program was to develop advanced component designs and architectures enabled by additive manufacturing, and the materials systems and additive manufacturing technology required for these designs. This Phase I program leveraged existing design and analysis knowledge and techniques for additive materials and methods and utilized extensive analytical evaluations to develop and refine designs for advanced turbine hot gas path (HGP) components. The design will be the basis for development and testing in a potential Phase II program. The goal of this Phase I program was to establish a feasible conceptual design for advanced additive turbine hot section components along with a technology maturation plan involving testing to address risk areas and needed validation. It was approached through two primary elements: 1) conceptual design and analysis of wall architectures, advanced airfoil cooling concepts, and advanced system-level concepts, and 2) investigation of additive modalities and associated materials systems. The Phase I program has concluded with the down-select of a primary design concept for a potential Phase II program.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Spent Nuclear Fuel Mechanical Loads in the General Package Drop Scenario

The US Department of Energy Spent Fuel and Waste Science and Technology program is performing research to determine the mechanical loading conditions applied to spent nuclear fuel (SNF) during normal conditions of transportation to inform mechanical tests of SNF and close an important knowledge gap related to the practical disposition of SNF in the US. A recent multi-national collaborative test campaign measured SNF assembly impact response to the 30 cm horizontal package drop scenario, which is a common regulatory basis test of SNF package design. Researchers at Pacific Northwest National Laboratory (PNNL) are using the test data to validate explicit finite element models to calculate the mechanical loads and structural response of spent nuclear fuel assemblies in the as-tested 30 cm horizontal package drop scenario. Once the as-tested package drop model is validated, the next step is to apply the model to the general 30 cm drop scenario, which includes all impact angles, all fuel assembly types, and all burnup conditions. PNNL is developing a damage model that will incorporate the results of finite element parametric studies to establish trends in SNF mechanical loading to various input parameters, like impact orientation and burnup. The damage model will have the capability to estimate mechanical loads for any single set of input parameters, but it will first be used to describe the upper bounds of potential SNF loading in the 30 cm drop scenario. This paper describes PNNL’s progress toward developing the general solution to the problem of spent nuclear fuel mechanical loads in the 30 cm package drop scenario and it describes the next steps in closing the knowledge gap.

Klymyshyn, Nicholas A.↗

DOE OSTI2024

Your Clean Graphene is Still Not Clean

Researchers working with thin samples, such as monolayer graphene, are consistently struggling against contamination. Indeed, the problem of hydrocarbon contamination is known from the earliest days of electron microscopy and efforts to reduce this problem are ubiquitous to almost all high-vacuum experiments. Accurate knowledge of the behavior of such contamination is essential for electron beam (e-beam) based atomic fabrication, where it is aspired to select and control matter on an atom-by-atom basis. Here, the vexing question of hydrocarbon contamination on graphene is taken up. Image intensity is used to directly reveal the presence of diffusing hydrocarbons on ostensibly clean graphene. These diffusing hydrocarbons are previously inferred but not directly observed. Surprising dynamic variations of the concentration of these hydrocarbons impels questions about their origin. Here, some possible explanations are presented and some tentative conclusions are drawn. This work updates the conceptual model of “clean graphene” and offers refinements to the description of e-beam induced hydrocarbon deposition.

atomic fabrication↗

DOE OSTI2023

Microalgae Hydrothermal Liquefaction and Biocrude Upgrading: 2022 State of Technology

A preliminary techno-economic analysis (TEA) was developed for the fiscal year (FY) 2022 state of technology (SOT) assessment to evaluate the benefits and risks of using demonstrated, high-productivity algae strains for fuels generation, including sustainable aviation fuel (SAF). In 2022, the marine algal strain, Picochlorum celeri, which demonstrated the highest outdoor biomass productivities reported to date in the DOE-funded open-pond raceway testbed at the Arizona Center for Algae Technology and Innovation (AzCATI), was tested for continuous hydrothermal liquefaction (HTL) processing at PNNL. HTL testing results demonstrated a biocrude yield of 0.33 g/g algae on an ash-free dry weight (AFDW) basis from P. celeri. The hydrotreatment testing of the HTL biocrude from P. celeri was also conducted to investigate the production of jet fuel from marine algal biomass. To the best of our knowledge, this is the first report of jet fuel production from autotrophically grown marine algal biomass. The current hydrotreating testing demonstrated approximately 22.7 wt% of the hydrotreated oil within the typical boiling-point range of jet fuel (150–250 °C). Initial testing of the jet fuel cut (JFC) showed that the physical properties under investigation were within typical ranges for petroleum-based jet fuels. The experimental work of this study closes the gap between outdoor algae cultivation and algae conversion to critical transportation fuels using the same algae strain for both cultivation and conversion testing. The continuous HTL and the upgrading testing described herein demonstrate the potential of producing sustainable aviation fuel (SAF) from algae cultivated in open-pond systems using the primary inputs of sunlight and carbon dioxide.

09 BIOMASS FUELS↗

DOE OSTI2021

Application of the FaMUS Methodology to the NSUF Research Outputs Through End of 2019

The Nuclear Science User Facilities (NSUF) is one of a diverse group of DOE user facilities. It is focused on advancing the understanding of radiation effects in nuclear fuels and materials in support of nuclear energy applications. The NSUF has been operating since 2007 and has developed a significant portfolio of supported research. Therefore, it is appropriate to consider its achievements and to determine its successes and shortfalls. As part of this analysis of the NSUF research program, the NSUF has developed a novel and elegant formalism for assessing the current level of understanding of nuclear fuels and materials for use in nuclear environments: the NSUF Fuels and Materials Understanding Scale (FaMUS). The FaMUS methodology is being applied to the NSUF portfolio on an ongoing basis to quantify the progress made. This report summarizes the status of the assessment exercise and highlights general lessons learned. This examination will facilitate capability balancing of future research by identifying gaps in knowledge, understanding, testing, and demonstration allowing the NSUF program office in conjunction with DOE-NE to direct resources to important aspects of the DOE-NE mission using “emphasize & enhance”, “maintain”, and “encourage excellence” classifications as well as providing increased transparency to researchers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Canonical and noncanonical Hamiltonian operator inference

Here, a method for the nonintrusive and structure-preserving model reduction of canonical and noncanonical Hamiltonian systems is presented. Based on the idea of operator inference, this technique is provably convergent and reduces to a straightforward linear solve given snapshot data and gray-box knowledge of the system Hamiltonian. Examples involving several hyperbolic partial differential equations show that the proposed method yields reduced models which, in addition to being accurate and stable with respect to the addition of basis modes, preserve conserved quantities well outside the range of their training data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

The Remarkable I 2 O 3 Molecule: A New View from Theory

Atmospheric iodine chemistry has garnered increasing attention as a result of increased iodine emissions. A key subset of this chemistry involves iodine oxides (I 2 O 2–5 ), which serve as precursors to particle formation. Among these, I 2 O 3 is the simplest iodine oxide involved in particle formation, but it has remained undetected in the atmosphere. Previous theoretical studies have characterized this peculiar molecule, primarily using energies to refine geometries obtained at low levels of theory. Due to the reemerging interest in I 2 O 3 , this study presents geometries optimized at the CCSD(T)/aug-cc-pwCVTZ-PP level of theory─marking the first instance, to the best of our knowledge, where this system has been studied exclusively with CCSD(T). Harmonic vibrational frequencies were computed at the same level of theory. Final energetics were obtained using the very high level CCSDT(Q) method with basis sets up to quintuple-zeta cardinality (aug-cc-pwCV5Z-PP) and extrapolated to the CBS limit to yield CCSDT(Q)/CBS//CCSD(T)/aug-cc-pwCVTZ-PP energies. These energies include harmonic zero-point vibrational energy corrections and scalar relativistic energy corrections. Additionally, this study discovers new isomers along the I 2 O 3 potential energy surface, a novel contribution to the field. The performance of different computational methods and DFT functionals commonly used in atmospheric chemistry is also assessed relative to high-level theoretical methods.

basis sets↗

DOE OSTI2026

Active space selection with self-healing diffusion Monte Carlo algorithms for periodic solids

Multideterminant Diffusion Monte Carlo (DMC) displays improved accuracy over single determinant DMC. Self-Healing Diffusion Monte Carlo (SHDMC) is a DMC based method that iteratively improves a multideterminant trial wavefunction. Although configuration interaction or complete active space (CAS) methods are very accurate and computationally feasible for many systems, they are not optimal for application to solids. SHDMC is accurate and designed for application to solids, so developing SHDMC based active space selection algorithms is a worthy endeavor. Here, we present and compare active space selection algorithms that are designed for use in conjunction with SHDMC, without relying on external approaches. For benchmarking, we calculated the ground state energy of a small unit cell of graphene and compared the results with a complete basis set extrapolated selected CI and a reference SHDMC trajectory. We found that systematically expanding the active space using an “auto-branching” algorithm optimally balances accuracy with computational practicality. To the best of our knowledge, this is the first work that demonstrates completely self-contained DMC-based active space selection algorithms that do not depend on external methods for determinant selection.

Spanedda, Nicole [ORNL]↗

DOE OSTI2023

3D Source Reconstruction Using Coded Aperture Gamma-Ray Imaging

Recent measurements with coded-aperture imagers demonstrate material mass determination in a holdup setting to an accuracy within a few percent. This capability is of particular interest to the Surplus Plutonium Disposition (SPD) project, which aims to dilute and dispose of surplus plutonium oxide. Gamma-ray imagers can be used to determine holdup without interrupting normal operations. In this work, we examine techniques for 3D source localization and mass determination using gamma-ray imagers. Coded-aperture imagers provide excellent source localization within the 2D image plane; however, multiple imagers operating in tandem are necessary to identify source location in 3D space. A Maximum Likelihood Expectation-Maximization (MLEM) method for fitting detector mappings is a powerful tool for accomplishing this task. MLEM allows 3D source localization to be simultaneously constrained using multiple gamma-ray imagers by constructing the basis for the MLEM fit using detector mappings from different detector locations stitched together. Each of these basis points represents a singular response from a source in 3D space and is generated using Monte Carlo simulations of sources placed individually at different locations throughout the imager’s field of view. Additionally, implementing knowledge of the physical equipment in the simulations of the glovebox used for the SPD project incorporates attenuation effects that are needed to calculate material holdup.

Laminack, Alex↗

DOE OSTI2021

Ecological stoichiometry as a foundation for omics-enabled biogeochemical models of soil organic matter decomposition

Coupled biogeochemical cycles drive ecosystem ecology by influencing individual-to-community scale behaviors; yet the development of process-based models that accurately capture these dynamics remains elusive. Soil organic matter (SOM) decomposition in particular is influenced by resource stoichiometry that dictates microbial nutrient acquisition (‘ecological stoichiometry’). Despite its basis in biogeochemical modeling, ecological stoichiometry is only implicitly considered in high-resolution microbial investigations and the metabolic models they inform. State-of-science SOM decomposition models in both fields have advanced largely separately, but they agree on a need to move beyond seminal pool-based models. This presents an opportunity and a challenge to maximize the strengths of various models across different scales and environmental contexts. To address this challenge, we contend that ecological stoichiometry provides a framework for merging biogeochemical and microbiological models, as both explicitly consider substrate chemistries that are the basis of ecological stoichiometry as applied to SOM decomposition. We highlight two gaps that limit our understanding of SOM decomposition: (1) understanding how individual microorganisms alter metabolic strategies in response to substrate stoichiometry and (2) translating this knowledge to the scale of biogeochemical models. We suggest iterative information exchange to refine the objectives of high-resolution investigations and to specify limited dynamics for representation in large-scale models, resulting in a new class of omics-enabled biogeochemical models. Assimilating theoretical and modelling frameworks from different scientific domains is the next frontier in SOM decomposition modelling; advancing technologies in the context of stoichiometric theory provides a consistent framework for interpreting molecular data, and further distilling this information into tractable SOM decomposition models.

Carbon cycling↗

DOE OSTI2024

Structural basis for C-degron selectivity across KLHDCX family E3 ubiquitin ligases

Abstract Specificity of the ubiquitin-proteasome system depends on E3 ligase-substrate interactions. Many such pairings depend on E3 ligases binding to peptide-like sequences - termed N- or C-degrons - at the termini of substrates. However, our knowledge of structural features distinguishing closely related C-degron substrate-E3 pairings is limited. Here, by systematically comparing ubiquitylation activities towards a suite of common model substrates, and defining interactions by biochemistry, crystallography, and cryo-EM, we reveal principles of C-degron recognition across the KLHDCX family of Cullin-RING ligases (CRLs). First, a motif common across these E3 ligases anchors a substrate’s C-terminus. However, distinct locations of this C-terminus anchor motif in different blades of the KLHDC2, KLHDC3, and KLHDC10 β-propellers establishes distinct relative positioning and molecular environments for substrate C-termini. Second, our structural data show KLHDC3 has a pre-formed pocket establishing preference for an Arg or Gln preceding a C-terminal Gly, whereas conformational malleability contributes to KLHDC10’s recognition of varying features adjacent to substrate C-termini. Finally, additional non-consensus interactions, mediated by C-degron binding grooves and/or by distal propeller surfaces and substrate globular domains, can substantially impact substrate binding and ubiquitylatability. Overall, the data reveal combinatorial mechanisms determining specificity and plasticity of substrate recognition by KLDCX-family C-degron E3 ligases.

Science & Technology - Other Topics↗

DOE OSTI2021

The Average Shape of Sea Ice Ridge Keels

Through analysis of over 64,000 ridge profiles identified from moored upward-looking sonars, we identify a well-defined average shape of pressure ridge keels that is concave or cusped, not triangular as widely assumed in other literature. On the basis of this average shape, we put forward a new, dimensional-definition, of a pressure ridge cross-section that follows a negative exponential form and allows an average pressure ridge cross section to be constructed with knowledge or choice of a single parameter. The horizonal asymptote of the profile represents the draft of the “background” ice in which the ridge is embedded. The draft of this background ice scales with keel depth and is typically greater than can be accounted through thermodynamic growth, indicating that ridges tend to be embedded in fields of mechanically thickened rubble. Using a variational ridge model we simulated keel shapes for a range of ridge building conditions. Here, the model results agree well with the observations and indicate the cusped shape of an average ridge profile arises from the varying angle of horizontal shear in the ice cover when ridges form. The modeling results also explain the elongated tail of the area draft distribution of the pack.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Open-Source Tidal Energy Converter (OSTEC) Testbed: Design Basis Report

This report describes the design basis and design details for an instrumented marine turbine system intended to serve as the DOE’s marine tidal turbine test bed for foundational open-source R&D and data generation to advance our understanding and to identify knowledge gaps on the techno-economic performance of tidal energy converters (TEC) under real tidal flow conditions and at sufficiently large scale to enable upscaling of fluid-structure-interactions and component and material load responses

16 TIDAL AND WAVE POWER↗

DOE OSTI2026

Converting methoxy groups on lignin-derived aromatics from a toxic hurdle to a useful resource: a systems-driven approach

Lignin conversion to bioproducts is challenging for several reasons, including the toxicity generated from the abundant methoxy groups released as formaldehyde. Consequently, our project used the best understood methylotroph – for which there is growing knowledge of formaldehyde stress responses – to explore how genetic factors and single-cell phenotypic heterogeneity contribute to growth and production. Our major goals were to (1) understand the fundamentals of Methylobacterium growth on aromatics, (2) identify and understand the basis of physiological basis of single-cell heterogeneity, and (3) develop quantitative models that relate heterogeneity to physiological and evolutionary outcomes.

Source record↗

DOE OSTI2022

Developing an Undergraduate Research Laboratory for Experimental Physical Chemistry [Book Chapter]

Embarking on a faculty career in physical chemistry at a primarily undergraduate institution (PUI) is exciting, but also overwhelming. Becoming both an effective teacher and a productive researcher requires a good plan, hard work and support from others who understand what it takes to be successful. The phrase, “building a laboratory,” calls to mind the physical construction of a research instrument, but beginning a career at a PUI involves much more than assembling equipment. Funding for the lab must be secured, students must be recruited and mentored, and the lab must be overseen to keep things running on a daily basis. While many of these tasks would also be part of starting a career at a doctoral level institution, there are many special considerations that must be taken into account when working with undergraduate students because their laboratory experience and chemical knowledge are still within those beautiful but nascent stages. Here, this unique aspect makes building a research program challenging, but also very rewarding. Exposing young minds to the wonders of physical chemistry and building personal relationships through the mentoring process can be immensely gratifying. This chapter is a compilation of holistic advice for building an experimental physical chemistry research laboratory for undergraduates, reflecting a typical experience found in the United States.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Development of phenomena identification and ranking table for Westinghouse lead fast reactor’s safety

The Westinghouse Lead-cooled Fast Reactor (LFR) is a medium-size, passively safe, economic, Gen-IV nuclear reactor. An important effort within the Westinghouse LFR program is the development of the safety analysis methodology, which comprises computer code development, model development, and experimental testing. A key initial task associated with the development of the safety analysis methodology is the identification of processes and phenomena that affect the plant's capability to meet selected safety performance indicators. This is accomplished through the development of a Phenomena Identification and Ranking Table (PIRT) for selected accident scenarios which, for this specific PIRT effort, included selected postulated design basis accidents and hypothetical beyond design basis accidents in LFRs. This paper describes the role of PIRT in the development of the Westinghouse LFR safety analysis methodology and the process used in the PIRT development. Specifically, the Westinghouse LFR PIRT assessed importance of pertinent phenomena and identified gaps in their knowledge-base by evaluating current modeling capabilities and data available for validation. The ultimate goal was to provide guidance on computer code development and validation efforts and to prioritize testing to support LFR design and licensing. The key phenomena and processes that are deemed highly important for the safety performance indicators, but for which the state of knowledge is low, are presented. The testing program and analyses development are planned to address significant phenomena in the PIRT.

Lead fast reactor↗

DOE OSTI2023

Electrophysiological Signatures of Visual Recognition Memory across All Layers of Mouse V1

In mouse primary visual cortex (V1), familiar stimuli evoke significantly altered responses when compared with novel stimuli. This stimulus-selective response plasticity (SRP) was described originally as an increase in the magnitude of visual evoked potentials (VEPs) elicited in layer 4 (L4) by familiar phase-reversing grating stimuli. SRP is dependent on NMDA receptors (NMDARs) and has been hypothesized to reflect potentiation of thalamocortical (TC) synapses in L4. However, recent evidence indicates that the synaptic modifications that manifest as SRP do not occur on L4 principal cells. To shed light on where and how SRP is induced and expressed in male and female mice, the present study had three related aims: (1) to confirm that NMDAR are required specifically in glutamatergic principal neurons of V1, (2) to investigate the consequences of deleting NMDAR specifically in L6, and (3) to use translaminar electrophysiological recordings to characterize SRP expression in different layers of V1. We find that knock-out (KO) of NMDAR in L6 principal neurons disrupts SRP. Current-source density (CSD) analysis of the VEP depth profile shows augmentation of short latency current sinks in layers 3, 4, and 6 in response to phase reversals of familiar stimuli. Multiunit recordings demonstrate that increased peak firing occurs in response to phase reversals of familiar stimuli across all layers, but that activity between phase reversals is suppressed. Together, these data reveal important aspects of the underlying phenomenology of SRP and generate new hypotheses for the expression of experience-dependent plasticity in V1. SIGNIFICANCE STATEMENT Repeated exposure to stimuli that portend neither reward nor punishment leads to behavioral habituation, enabling organisms to dedicate attention to novel or otherwise significant features of the environment. The neural basis of this process, which is so often dysregulated in neurologic and psychiatric disorders, remains poorly understood. Learning and memory of stimulus familiarity can be studied in mouse visual cortex by measuring electrophysiological responses to simple phase-reversing grating stimuli. The current study advances knowledge of this process by documenting changes in visual evoked potentials (VEPs), neuronal spiking activity, and oscillations in the local field potentials (LFPs) across all layers of mouse visual cortex. In addition, we identify a key contribution of a specific population of neurons in layer 6 (L6) of visual cortex.

60 APPLIED LIFE SCIENCES↗