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DOE OSTI2022

Using artificial intelligence to detect human errors in nuclear power plants: A case in operation and maintenance

Human error (HE) is an important concern in safety-critical systems such as nuclear power plants (NPPs). HE has played a role in many accidents and outage incidents in NPPs. Despite the increased automation in NPPs, HE remains unavoidable. Hence, the need for HE detection is as important as HE prevention efforts. In NPPs, HE is rather rare. Hence, anomaly detection, a widely used machine learning technique for detecting rare anomalous instances, can be repurposed to detect potential HE. In this study, we develop an unsupervised anomaly detection technique based on generative adversarial networks (GANs) to detect anomalies in manually collected surveillance data in NPPs. More specifically, our GAN is trained to detect mismatches between automatically recorded sensor data and manually collected surveillance data, and hence, identify anomalous instances that can be attributed to HE. We test our GAN on both a real-world dataset and an external dataset obtained from a testbed, and we benchmark our results against state-of-the-art unsupervised anomaly detection algorithms, including one-class support vector machine and isolation forest. Our results show that the proposed GAN provides improved anomaly detection performance. Our study is promising for the future development of artificial intelligence based HE detection systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2007

Renal Stone Risk During Space Flight: Assessment and Countermeasure Validation

NASA has focused its future on exploration class missions including the goal of returning to the moon and landing on Mars. With these objectives, humans will experience an extended exposure to the harsh environment of microgravity and the associated negative effects on all the physiological systems of the body. Exposure to microgravity affects human physiology and results in changes to the urinary chemical composition during and after space flight. These changes are associated with an increased risk of renal stone formation. The development of a renal stone would have health consequences for the crewmember and negatively impact the success of the mission. As of January 2007, 15 known symptomatic medical events consistent with urinary calculi have been experienced by 13 U.S. astronauts and Russian cosmonauts. Previous results from both MIR and Shuttle missions have demonstrated an increased risk for renal stone formation. These data have shown decreased urine volume, urinary pH and citrate levels and increased urinary calcium. Citrate, an important urinary inhibitor of calcium-containing renal stones binds with calcium in the urine, thereby reducing the amount of calcium available to form calcium oxalate stones. Urinary citrate also prevents calcium oxalate crystals from aggregating into larger crystals and into renal stones. In addition, citrate makes the urine less acidic which inhibits the development of uric acid stones. Potassium citrate supplementation has been successfully used to treat patients who have formed renal stones. The evaluation of potassium citrate as a countermeasure has been performed during the ISS Expeditions 3-6, 8, 11-13 and is currently in progress during the ISS Expedition 14 mission. Together with the assessment of stone risk and the evaluation of a countermeasure, this investigation provides an educational opportunity to all crewmembers. Individual urinary biochemical profiles are generated and the risk of stone formation is estimated. Increasing fluid intake is recommended to all crewmembers. These results can be used to lower the risk for stone formation through lifestyle, diet changes or therapeutic administration to minimize the risk for stone development. With human presence in microgravity a continuing presence and exploration class missions being planned, maintaining the health and welfare of all crewmembers is critical to the exploration of space.

Whitson, P. A.↗

DOE OSTI2016

Distillation of secret-key from a class of compound memoryless quantum sources

We consider secret-key distillation from tripartite compound classical-quantum-quantum (cqq) sources with free forward public communication under strong security criterion. We design protocols which are universally reliable and secure in this scenario. These are shown to achieve asymptotically optimal rates as long as a certain regularity condition is fulfilled by the set of its generating density matrices. We derive a multi-letter formula which describes the optimal forward secret-key capacity for all compound cqq sources being regular in this sense. We also determine the forward secret-key distillation capacity for situations where the legitimate sending party has perfect knowledge of his/her marginal state deriving from the source statistics. In this case regularity conditions can be dropped. Our results show that the capacities with and without the mentioned kind of state knowledge are equal as long as the source is generated by a regular set of density matrices. We demonstrate that regularity of cqq sources is not only a technical but also an operational issue. For this reason, we give an example of a source which has zero secret-key distillation capacity without sender knowledge, while achieving positive rates is possible if sender marginal knowledge is provided.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1978

FASOR - A second generation shell of revolution code

An integrated computer program entitled Field Analysis of Shells of Revolution (FASOR) currently under development for NASA is described. When completed, this code will treat prebuckling, buckling, initial postbuckling and vibrations under axisymmetric static loads as well as linear response and bifurcation under asymmetric static loads. Although these modes of response are treated by existing programs, FASOR extends the class of problems treated to include general anisotropy and transverse shear deformations of stiffened laminated shells. At the same time, a primary goal is to develop a program which is free of the usual problems of modeling, numerical convergence and ill-conditioning, laborious problem setup, limitations on problem size and interpretation of output. The field method is briefly described, the shell differential equations are cast in a suitable form for solution by this method and essential aspects of the input format are presented. Numerical results are given for both unstiffened and stiffened anisotropic cylindrical shells and compared with previously published analytical solutions.

Cohen, G. A.↗

DOE OSTI2021

The great escape: tunneling out of microstate geometries

We compute the quasi-normal frequencies of scalars in asymptotically-flat microstate geometries that have the same charge as a D1-D5-P black hole, but whose long BTZ-like throat ends in a smooth cap. In general the wave equation is not separable, but we find a class of geometries in which the non-separable term is negligible and we can compute the quasi-normal frequencies using WKB methods. We argue that our results are a universal property of all microstate geometries with deeply-capped BTZ throats. These throats generate large redshifts, which lead to exceptionally-low-energy states with extremely long decay times, set by the central charge of the dual CFT to the power of twice the dimension of the operator dual to the mode. While these decay times are extremely long, we also argue that the energy decay is bounded, at large t , by (log( t )) – 2 and is comparable with the behavior of ultracompact stars, as one should expect for microstate geometries.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Self-Destructing Dark Matter

We present Self-Destructing Dark Matter (SDDM), a new class of dark matter models which are detectable in large neutrino detectors. In this class of models, a component of dark matter can transition from a long-lived state to a short-lived one by scattering off of a nucleus or an electron in the Earth. The short-lived state then decays to Standard Model particles, generating a dark matter signal with a visible energy of order the dark matter mass rather than just its recoil. This leads to striking signals in large detectors with high energy thresholds. We present a few examples of models which exhibit self destruction, all inspired by bound state dynamics in the Standard Model. The models under consideration exhibit a rich phenomenology, possibly featuring events with one, two, or even three lepton pairs, each with a fixed invariant mass and a fixed energy, as well as non-trivial directional distributions. This motivates dedicated searches for dark matter in large underground detectors such as Super-K, Borexino, SNO+, and DUNE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

P450-Mediated Non-natural Cyclopropanation of Dehydroalanine-Containing Thiopeptides

Thiopeptides are a growing class of ribosomally synthesized and post-translationally modified peptide (RiPP) natural products. Many biosynthetic enzymes for RiPPs, especially thiopeptides, are promiscuous and can accept a wide range of peptide substrates with different amino acid sequences; thus, these enzymes have been used as tools to generate new natural product derivatives. In this work, we explore an alternative route to molecular complexity by engineering thiopeptide tailoring enzymes to do new or non-native chemistry. We explore cytochrome P450 enzymes as biocatalysts for cyclopropanation of dehydroalanines, chemical motifs found widely in thiopeptides and other RiPP-based natural products. We find that P450 TbtJ1 and P450 TbtJ2 selectively cyclopropanate dehydroalanines in a number of complex thiopeptide-based substrates and convert them into 1-amino-2-cyclopropane carboxylic acids (ACCAs), which are important pharmacophores. This chemistry takes advantage of the innate affinity of these biosynthetic enzymes for their substrates and enables incorporation of new pharmacophores into thiopeptide architectures. This work also presents a strategy for diversification of natural products through rationally repurposing biosynthetic enzymes as non-natural biocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Immunogenicity and therapeutic targeting of a public neoantigen derived from mutated PIK3CA

Public neoantigens (NeoAgs) represent an elite class of shared cancer-specific epitopes derived from recurrently mutated driver genes. Here we describe a high-throughput platform combining single-cell transcriptomic and T cell receptor (TCR) sequencing to establish whether mutant PIK3CA, among the most frequently genomically altered driver oncogenes, generates an immunogenic public NeoAg. Using this strategy, we developed a panel of TCRs that recognize an endogenously processed neopeptide encompassing a common PIK3CA hotspot mutation restricted by the prevalent human leukocyte antigen (HLA)-A*03:01 allele. Mechanistically, immunogenicity to this public NeoAg arises from enhanced neopeptide/HLA complex stability caused by a preferred HLA anchor substitution. Structural studies indicated that the HLA-bound neopeptide presents a comparatively ‘featureless’ surface dominated by the peptide’s backbone. To bind this epitope with high specificity and affinity, we discovered that a lead TCR clinical candidate engages the neopeptide through an extended interface facilitated by an unusually long CDR3β loop. In patients with diverse malignancies, we observed NeoAg clonal conservation and spontaneous immunogenicity to the neoepitope. Finally, adoptive transfer of TCR-engineered T cells led to tumor regression in vivo in mice bearing PIK3CA-mutant tumors but not wild-type PIK3CA tumors. Together, these findings establish the immunogenicity and therapeutic potential of a mutant PIK3CA-derived public NeoAg.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Dynamic Morphologies of Microscale Droplet Interface Bilayers

Droplet interface bilayers (DIBs) are a powerful platform for studying the dynamics of synthetic cellular membranes; however, very little has been done to exploit the unique dynamical features of DIBs. Here, we generate microscale droplet interface bilayers ( DIBs) by bringing together femtoliter-volume water droplets in a microfluidic oil channel, and characterize morphological changes of the DIBs as the droplets shrink due to evaporation. By varying the initial conditions of the system, we identify three distinct classes of dynamic morphology. (1) Buckling and Fission: When forming DIBs using the lipid-out method (lipids in oil phase), lipids in the shrinking monolayers continually pair together and slide into the bilayer to conserve their mass. As the bilayer continues to grow, it becomes confined, buckles, and eventually fissions one or more vesicles. (2) Uniform Shrinking: When using the lipid-in method (lipids in water phase) to form DIBs, lipids uniformly transfer from the monolayers and bilayer into vesicles contained inside the water droplets. (3) Stretching and Unzipping: Finally, when the droplets are pinned to the wall(s) of the microfluidic channel, the droplets become stretched during evaporation, culminating in the unzipping of the bilayer and droplet separation. These findings offer a better understanding of the dynamics of coupled lipid interfaces.

Mruetusatorn, Prachya↗

DOE OSTI2016

Robustness of magnetic and electric domains against charge carrier doping in multiferroic hexagonal ErMnO 3

We investigate the effect of chemical doping on the electric and magnetic domain pattern in multiferroic hexagonal ErMnO 3 . Hole- and electron doping are achieved through the growth of Er 1-x Ca x MnO 3 and Er 1-x Zr x MnO 3 single crystals, which allows for a controlled introduction of divalent and tetravalent ions, respectively. Using conductance measurements, piezoresponse force microscopy and nonlinear optics we study doping-related variations in the electronic transport and image the corrsponding ferroelectric and antiferromagnetic domains. We find that moderate doping levels allow for adjusting the electronic conduction properties of ErMnO 3 without destroying its characteristic domain patterns. Our findings demonstrate the feasibility of chemical doping for nonperturbative property-engineering of intrinsic domain states in this important class of multiferroics.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Energy and momentum conservation in the Euler–Poincaré formulation of local Vlasov–Maxwell-type systems

The action principle by Low for the classic Vlasov–Maxwell system contains a mix of Eulerian and Lagrangian variables. This renders the Noether analysis of reparametrization symmetries inconvenient, especially since the well-known energy- and momentum-conservation laws for the system are expressed in terms of Eulerian variables only. While an Euler–Poincaré formulation of Vlasov–Maxwell-type systems, effectively starting with Low's action and using constrained variations for the Eulerian description of particle motion, has been known for a while Cendra et al, it is hard to come by a documented derivation of the related energy- and momentum-conservation laws in the spirit of the Euler–Poincaré machinery. To our knowledge only one such derivation exists in the literature so far, dealing with the so-called guiding-center Vlasov–Darwin system Sugama et al. The present exposition discusses a generic class of local Vlasov–Maxwell-type systems, with a conscious choice of adopting the language of differential geometry to exploit the Euler–Poincaré framework to its full extent. After reviewing the transition from a Lagrangian picture to an Eulerian one, we demonstrate how symmetries generated by isometries in space lead to conservation laws for linear- and angular-momentum density and how symmetry by time translation produces a conservation law for energy density. Here, we also discuss what happens if no symmetries exist. Finally, two explicit examples will be given—the classic Vlasov–Maxwell and the drift-kinetic Vlasov–Maxwell—and the results expressed in the language of regular vector calculus for familiarity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Temporally quasiperiodic data, propagating in the laboratory frame, can be rendered periodic by Galilean transformation

For a broad class of distributions of temperature, concentration, or another quantity propagating rectilinearly, we show that temporally quasiperiodic behavior in the laboratory frame can be rendered periodic by Galilean transformation. The approach is illustrated analytically and numerically using as an example a closed-form model distribution generated from a one-dimensional partial differential equation, and a detailed process is developed to determine frame speed from more general quasiperiodic, one-dimensional, temporally- and spatially-discretized data. Furthermore, the approach is extended to two- and three-dimensional rectilinear propagation, and its application to nonrectilinear propagation, along with implications for interpreting noise-corrupted data, are also discussed.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Nanoscale magnetic phase competition throughout the Ni 50– x Co x Mn 40 Sn 10 phase diagram: Insights from small-angle neutron scattering

The Ni 2 MnSn-derived Ni 50– x Co x Mn 25+ y Sn 25– y alloys are premier examples of a class of off-stoichiometric Heusler alloys recently discovered to exhibit attractive magnetic properties in tandem with extraordinarily reversible martensitic phase transformations. Multiferroicity, magnetic phase competition and separation, field-induced martensitic transformations, magnetic shape memory behavior, and sizable magneto-, elasto-, and barocaloric effects result, generating substantial interest and application potential. In this work we expand on a prior small-angle neutron scattering (SANS) study at a single composition (Ni 44 Co 6 Mn 40 Sn 10 ) by exploring all three main regions of the recently established Ni 50–x Co x Mn 40 Sn 10 phase diagram, i.e., at the representative y = 15 composition. Wide temperature and scattering wave-vector range (20–500K, 0.004–0.2Å –1 ) SANS data on x = 2, 6, and 14 polycrystals provide a detailed picture of the evolution in magnetic order and inhomogeneity. Consistent with recent studies with a variety of techniques, phase separation into short-range coexisting ferromagnetic and antiferromagnetic regions is deduced below the martensitic transformation at x = 2 and 6, with average ferromagnetic cluster spacing of ~13 nm. Remarkably, at x = 14, where the martensitic transformation is suppressed and ferromagnetic austenite is stabilized to low temperatures, nanoscopic magnetic inhomogeneity nevertheless persists. Further, distinct ferromagnetic clusters (~36-nm average spacing) in a ferromagnetic matrix are observed at intermediate temperatures, homogenizing into a uniform long-range ordered ferromagnet only at low temperatures. This unusual ferromagnet cluster/ferromagnet matrix inhomogeneity, as well as x -dependent subtleties of the superparamagnetic freezing of ferromagnetic clusters, are discussed in light of 55 Mn nuclear magnetic resonance data, and the recent observation of annealing-induced core/shell nanoprecipitates. The origins of nanoscalemagnetic inhomogeneity are discussed in terms of statistical variations in local composition and structure, tendency to chemical phase separation, and other forms of disorder.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

An Introduction to Word Embeddings and Language Models

Language models have advanced at a phenomenal pace over the past decade. This document provides a short introduction to terminology, word embeddings (aka low-dimensional representations), and popular large-scale language models (LMs). Word embeddings are used to represent words as numerical vectors and are context-independent, meaning a word can only have a single representation (e.g., club can only be club sandwich, not golf club ). Language models can determine the probability of a given sequence of words occurring in a sentence and can provide context to distinguish between words and phrases that sound similar. LMs are context-dependent (e.g., club can be club sandwich or golf club ) and largely fall in two main classes – autoregressive and autoencoding models. Autoregressive models are pretrained on the classic language modeling task: guess the next token having read all the previous ones. Those models can be fine-tuned and achieve great results on many tasks, the most natural application is text generation. A typical example of such models is GPT, but others include GPT-2, GPT-3, CTLR, TRANSFORMER-XL, REFORMER, XLNET. Autoencoding models are pretrained by corrupting the input tokens in some way and trying to reconstruct the original sentence. They can be fine-tuned and achieve great results on many tasks such as text generation, but their most natural application is sentence classification or token classification. A typical example of such models is BERT, but others include ROBERTA, ALBERT, XML, XML-ROBERTA, FLAUBERT AND LONGFORMER.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Thermal & Electrochemical Power Plant Design and Cost Estimation

Public textbook for "Thermal & Electrochemical Power Plant Design and Cost Estimation: Version#1" This public textbook is an extension of class notes from Carnegie Mellon University courses: Energy System Modeling (24-722) and Fuel Cell Systems (24-262), taught by Dr. Nicholas Siefert between 2010-2021. Textbook includes some references to class notes from Dr. Shawn Litster, Department of Mechanical Engineering, Carnegie Mellon University. Textbook covers the equilibrium and nonequilibrium thermodynamics of power systems as well as an overview of system and economic modeling of these systems. There is in-depth coverage of (a) entropy generation, (b) exergy and (c) the redox state of molecules in equilibrium with the natural environment. This textbook is integrated with other materials (such as lecture slides, solved homeworks, and solved exams) that will be posted to the PowerShare: Energy Systems Modeling group on EDX. Publication Number: DOE/NETL-2023/3913

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2024

Component-to-Optimization Workflow Demonstration

This report aims to demonstrate workflow-generating algorithms for optimizing dispatch across a broad range of Integrated Energy System applications using the Framework for Optimization of Resources and Economics (FORCE) tool suite. The optimization is performed at two different time scales. In the coarse time scale, the optimization focuses on a class of energy sources and consumers and aims to find the optimal combinations and flows of energy based on real-time price data information. In the fine time scale, the optimization focuses on a specific thermal energy delivery system and aims to find the optimal setpoints of components in order to meet the energy demands from coarse-time-scale optimizations. In this demonstration, the coarse-scale optimization is implemented using the newly developed Dispatch Optimization Variable Engine (DOVE), while the fine-scale optimization used Optimization of Real-Time Capacity Allocation (ORCA).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Analysis of Electric Heavy-Duty Driving and Infrastructure Requirements

The analysis discussed in this report was performed as part of DOE award DE-EE0009232 to model the effects of charging Heavy Duty Battery Electric Trucks (HDBETs) on the grid. This project combines best in class freight modeling by the National Renewable Energy Laboratory (NREL) with advanced distribution modeling by EPRI using detailed data from Xcel Energy and Salt River Project to analyze the effects of depot charging and utility-grade transmission modeling by Tri-State Transmission and Generation Association Inc. to analyze the effects of en-route charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1976

Exploration for porphyry copper deposits in Pakistan using digital processing of Landsat-1 data

Rock-type classification by digital-computer processing of Landsat-1 multispectral scanner data has been used to select 23 prospecting targets in the Chagai District, Pakistan, five of which have proved to be large areas of hydrothermally altered porphyry containing pyrite. Empirical maximum and minimum apparent reflectance limits were selected for each multispectral scanner band in each rock type classified, and a relatively unrefined classification table was prepared. Where the values for all four bands fitted within the limits designated for a particular class, a symbol for the presumed rock type was printed by the computer at the appropriate location. Drainage channels, areas of mineralized quartz diorite, areas of pyrite-rich rock, and the approximate limit of propylitic alteration were very well delineated on the computer-generated map of the test area. The classification method was used to evaluate 2,100 sq km in the Mashki Chah region. The results of the experiment show that outcrops of hydrothermally altered and mineralized rock can be identified from Landsat-1 data under favorable conditions.

Schmidt, R. G.↗