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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Pruning of Discrete Dynamic Event Trees Using Density Peaks and Dynamic Time Warping

Discrete Dynamic Event Trees (DDETs) are used in probabilistic risk assessment (PRA) to determine the risk associated with complex systems, such as nuclear power plants, where accident scenarios need to be realistically modeled. One of the most challenging aspects of the DDET method is that a large number of branches are produced for each initiating event. This can result in data that is difficult to organize and time consuming to analyze. As the number of uncertain parameters increases, so does the complexity of the event tree. An event tree often has nodes that do not contribute to the overall results and predictive capabilities; therefore, we suggest a pre-pruning algorithm that can work to remove these nodes, and consequently, reduce the complexity of the tree. Sandia National Laboratories (SNL) is currently working on a two year dynamic cyber-risk informed project to assess cyber failure in a nuclear power plant. This will be achieved by coupling SNL's dynamic scheduler known as Analysis of Dynamic Accident Progression Trees (ADAPT) with MELCOR, a reactor accident simulator, and a System for Circuit Evaluation and Prediction of Transient Radiation Effects (SCEPTRE), a cyber Emulytics code. This paper will discuss the preliminary results of a feasibility study for using density peaks (DP) clustering with dynamic time warping (DTW) to prune branches that are formed from large DDETs, like the ones that will be produced throughout SNL's project. Papers from the project that are submitted to this conference discuss the following: - The MELCOR model for a Pressurized Water Reactor that uses a digital instrumentation and control system. - Proposed generic cyber exploits for the above reactor. - Modifications to ADAPT to extend the framework for multiple simulators, incorporate importance measures into DDET analysis, as well as sort and reduce DDETs based on inputs to or outputs from the tree. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Topographic controls on a phreatomagmatic maar-diatreme eruption: field and numerical results from the Holocene Dotsero volcano (Colorado, USA)

We analyzed the eruptive products of Holocene Dotsero volcano (Colorado, USA; ~4.15 ka), which recorded evidence of a progression from effusive magmatic activity through explosive phreatomagmatic maar-forming activity to a final explosive magmatic phase. The nature of the deposits suggests that the irregular and mountainous pre-eruptive topography strongly influenced the formation of directed pyroclastic density currents (PDCs) during the phreatomagmatic phase, where the topographically high northern crater rim acted as a barrier and promoted transport to the south. Furthermore, the crater shape strongly controlled the grain size of the final deposits, providing further evidence that deposit grain size can be a misleading proxy for fragmentation or explosion intensity. We test these hypotheses, as gleaned from fieldwork, by implementing a multiphase numerical model to simulate discrete explosions and their resulting PDCs at maar-diatreme volcanoes. We confirm that a crater shape where one rim is higher than the other promotes multiple pulses of particle transport in the direction of the lower rim. The initial PDCs contain both coarse and fine particles, whereas PDCs generated by later pulses contain, predominately, finer particles. This mechanism provides an alternative explanation to the formation of lapilli tuff/tuff couplets often found at maar-diatreme tephra rings (including Dotsero volcano). Additional modeling shows how the crater depth can control grain size of the resulting PDC deposits. In the case of a deep crater and a relatively weak explosion, it is possible that only the fine particles escape following collapse of the eruptive column, resulting in a fine-grained deposit. This work allows us to improve models developed to describe emplacement of PDCs for different crater geometries and informs on the dynamics of maar-diatreme eruptions, but also highlights the limitations of our knowledge of key parameters, especially those related to the processes of magma-water interaction and syn-eruptive hydrogeology, during such events.

58 GEOSCIENCES↗
DOE OSTI2017

Modeling of Hydraulic Fracture Propagation at the kISMET Site Using a Fully Coupled 3D Network-Flow and Quasi- Static Discrete Element Model

Aimed at supporting the design of hydraulic fracturing experiments at the kISMET site, ~1500 m below ground in a deep mine, we performed pre-experimental hydraulic fracturing simulations in order to estimate the breakdown pressure, propagation pressure, fracture geometry, and the magnitude of induced seismicity using a newly developed fully coupled three-dimensional (3D) network flow and quasi-static discrete element model (DEM). The quasi-static DEM model, which is constructed by Delaunay tessellation of the rock volume, considers rock fabric heterogeneities by using the “disordered” DEM mesh and adding random perturbations to the stiffness and tensile/shear strengths of individual DEM elements and the elastic beams between them. A conjugate 3D flow network based on the DEM lattice is constructed to calculate the fluid flow in both the fracture and porous matrix. One distinctive advantage of the model is that fracturing is naturally described by the breakage of elastic beams between DEM elements. It is also extremely convenient to introduce mechanical anisotropy into the model by simply assigning orientation-dependent tensile/shear strengths to the elastic beams. In this paper, the 3D hydraulic fracturing model was verified against the analytic solution for a penny-shaped crack model. We applied the model to simulate fracture propagation from a vertical open borehole based on initial estimates of rock mechanical properties and in-situ stress conditions. The breakdown pressure and propagation pressure are directly obtained from the simulation. In addition, the released elastic strain energies of individual fracturing events were calculated and used as a conservative estimate for the magnitudes of the potential induced seismic activities associated with fracturing. The comparisons between model predictions and experimental results are still ongoing.

15 GEOTHERMAL ENERGY↗
DOE OSTI2014

WE-A-17A-04: Development of An Ultra-Fast Monte Carlo Dose Engine for High Dose Rate Brachytherapy

Purpose: Current clinical brachytherapy dose calculations are based on AAPM TG43 guidelines, which approximate the patient geometry as a large water phantom. This ignores heterogeneities and tends to overestimate skin dose. Although Monte Carlo (MC) dose calculations have been recognized as the most accurate method, its associated long computational time is a major bottleneck for routine clinical applications. This work aims to develop a GPU-based ultra-fast MC dose engine (gBMC) for HDR brachytherapy to provide clinical users with accurate sub-minute dose calculations. Methods: Standard photon transport with discrete events including: Compton scattering, Rayleigh scattering and Photoelectric effect, was implemented. Secondary electrons were transported under the continuous slowing down approximation. To reduce the GPU thread divergence, photons and electrons were separately transported. Transport of photons was grouped according to energy. The source model in gBMC can be either a phase-space file generated using Geant4 or a parameterized source model. This dose engine was validated against TG43 in a water phantom and against Geant4 calculations in heterogeneous patient geometries. Results: A phase space file was generated for the Varian VS2000 Ir-192 source. In a water phantom, the calculated radial dose function was within 0.6% of the TG43 calculations for radial distances from 1 cm to 20 cm. The anisotropy functions were within 1% for radial distances from 1 cm to 20 cm except for polar angles larger than 173°. Local point-dose differences were within 2%. In a Mammosite breast cancer case with 22 dwell locations, gBMC and Geant4 isodose lines compared well. The computation time was about 28 seconds using the phase-space file source and 20 seconds using the parameterized source to simulate 1 billion particles, yielding less than 1% statistical uncertainty. Conclusion: The gBMC dose engine makes it possible to use fast and accurate MC dose calculations for clinical work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Development of an MC&A toolbox for liquid-fueled molten salt reactors with online reprocessing (Final Report)

A critical barrier to the deployment of MSRs is the absence of a well-defined nuclear material control and accounting (MC&A) approach, a vital prerequisite to meet NRC licensing requirements as well as facilitating future international exports. Liquid-fueled MSR variants (especially those incorporating online refueling or reprocessing) present a unique set of challenges to traditional nuclear material control and accountancy. Unlike solid-fueled light-water reactors, traditional item-counting methods cannot be applied as an accountancy strategy. Rather, MC&A approaches to MSR variants (including both uranium and thorium fueled designs) are more analogous to bulk material handling facilities (e.g., enrichment and reprocessing); yet further complicating matters is the fact that fuel medium is also highly radioactive. Meanwhile, the space of MSRs covers a broad range of design parameters, including thermal and fast spectra designs; operation in actinide breeder or burner modes, choice of actinide fuel used (e.g., 235 U, 232 Th / 233 U, denatured 233 U, etc.), pool or loop-type configuration, and even different salt chemistry. Each of these design choices introduce significant challenges to MC&A approaches within MSR facilities. We propose to bridge this gap for liquid-fueled MSRs by developing a modular, component-based test framework for evaluating viable process monitoring and MC&A techniques specifically suited to liquid-fueled MSR system variants employing online refueling or reprocessing. This test platform will consist of a toolbox of independent process modules representing discrete physical units (such as the reactor core, off-gas processing, decay tanks, and actinide separation units), each with its own self-contained physics responsive to the input mass flow, along with appropriate measurement models that can be coupled to key flow points. These dynamic physical signatures thus afford the ability to test the viability and efficacy of potential accountancy techniques under the full range of reactor operating conditions. As process modules are connected via mass flows, the result is a reconfigurable, generic MSR mass flow model capable of serving as an MC&A test platform for a broad spectrum of possible MSR configurations. The resulting MSR MC&A toolbox will enable robust assessment of accountancy strategies for this unique facility type, including analysis of physical feedbacks arising both from depletion of the fuel over time as well as from potential off-normal events, including those introduced by equipment failures (e.g., a pump failure) as well as by malicious action (i.e., attempts to divert material). The proposed toolbox both addresses a critical needs area for the MPACT analysis toolkit while leveraging existing MPACT-sponsored tools, especially with respect to simulation of measurement and accountancy techniques for advanced fuel cycle facilities. Beyond enabling new analysis capabilities for MSR systems, the design of this toolbox will be to such to maximize compatibility with existing MPACT tools, such to enhance existing facility MC&A analysis capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗
DOE OSTI2020

Detection of DoS Attacks Using ARFIMA Modeling of GOOSE Communication in IEC 61850 Substations

Integration of Information and Communication Technology (ICT) in modern smart grids (SGs) offers many advantages including the use of renewables and an effective way to protect, control and monitor the energy transmission and distribution. To reach an optimal operation of future energy systems, availability, integrity and confidentiality of data should be guaranteed. Research on the cyber-physical security of electrical substations based on IEC 61850 is still at an early stage. In the present work, we first model the network traffic data in electrical substations, then, we present a statistical Anomaly Detection (AD) method to detect Denial of Service (DoS) attacks against the Generic Object Oriented Substation Event (GOOSE) network communication. According to interpretations on the self-similarity and the Long-Range Dependency (LRD) of the data, an Auto-Regressive Fractionally Integrated Moving Average (ARFIMA) model was shown to describe well the GOOSE communication in the substation process network. Based on this ARFIMA-model and in view of cyber-physical security, an effective model-based AD method is developed and analyzed. Two variants of the statistical AD considering statistical hypothesis testing based on the Generalized Likelihood Ratio Test (GLRT) and the cumulative sum (CUSUM) are presented to detect flooding attacks that might affect the availability of the data. Our work presents a novel AD method, with two different variants, tailored to the specific features of the GOOSE traffic in IEC 61850 substations. The statistical AD is capable of detecting anomalies at unknown change times under the realistic assumption of unknown model parameters. The performance of both variants of the AD method is validated and assessed using data collected from a simulation case study. We perform several Monte-Carlo simulations under different noise variances. The detection delay is provided for each detector and it represents the number of discrete time samples after which an anomaly is detected. In fact, our statistical AD method with both variants (CUSUM and GLRT) has around half the false positive rate and a smaller detection delay when compared with two of the closest works found in the literature. Our AD approach based on the GLRT detector has the smallest false positive rate among all considered approaches. Whereas, our AD approach based on the CUSUM test has the lowest false negative rate thus the best detection rate. Depending on the requirements as well as the costs of false alarms or missed anomalies, both variants of our statistical detection method can be used and are further analyzed using composite detection metrics.

IEC 61850 electrical substations↗
DOE OSTI2014

Application of the GBFP Method to Electron Partial-Wave Expansion Elastic Scattering Differential Cross Sections Within the Geant4 Toolkit - Paper 69

Analog Monte Carlo simulation of electrons in complex material geometries is generally impractical because the long range Coulomb interactions result in highly peaked differential cross sections (DCS) for scattering and energy-loss and extremely small collision mean free paths (mfp). The condensed history (CH) Monte Carlo method attempts to alleviate this limitation by advancing electrons in fixed steps and sampling angular deflections and energy losses from precomputed distributions obtained from approximate solutions to the underlying transport equation that are valid only for thin layers. Though CH is efficient and is widely employed in production codes (ITS, MCNP, EGS, Geant), step size restrictions and inconsistent handling of material and free surface boundaries limit the ultimate accuracy possible with this approach, especially in applications to highly heterogeneous media. Recently proposed alternatives to the CH method, such as the Generalized Boltzmann Fokker-Planck (GBFP) method, restore the correct transport mechanics by simulating single events based on a Boltzmann transport equation but with efficiency and accuracy achieved through the use of reduced-physics interaction models. Motivated by Lewis theory, various moment-preserving strategies are employed in the GBFP approach to construct DCSs that are less singular, and with mfps shorter than analog. Specifically, the approximate cross sections are constructed to rigorously preserve a finite number of angular and energy-loss moments of the analog DCSs while all higher moments are approximated in terms of the exact lower moments. By systematically increasing the number of moments retained, any desired accuracy can be obtained for integrated quantities, such as dose, reflection and transmission yields, as well as distributed quantities such as energy and angular distributions. For relativistic Rutherford cross section models, the GBFP method has been demonstrated in Monte Carlo simulation to yield accuracy comparable to analog but at a fraction of the cost. One advantage of the GBFP approach is that angular deflection and energy-loss interactions depend only on Legendre moments and energy-loss moments and not the detailed form of the analog DCSs. This feature allows moment-preservation to be enforced through DCSs expressed as a superposition of discrete (i.e., using delta-functions) angular deflections and discrete energy losses. This promotes extremely efficient computation when compared to analog and completely continuous or hybrid discrete-continuous moment-based DCS reconstructions, while yielding highly accurate results for integrated and distributed quantities. In this paper, we demonstrate that the moment-preserving algorithms central to our fully discrete GBFP method can be readily extended to apply to tabulated DCS data, specifically to the partial-wave expansion (PWE) elastic scattering DCSs. Since data libraries for the PWE DCSs for energy and material combinations of interest can be prohibitively large, the GBFP method provides a means to reduce data storage requirements. We implemented our algorithm in the Geant4 Monte Carlo code and all numerical results are obtained using this implementation. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Fish Passage though Hydropower Turbines: Simulating Blade Strike using the Discrete Element Method

mong the hazardous hydraulic conditions affecting anadromous and resident fish during their passage though turbine flows, two are believed to cause considerable injury and mortality: collision on moving blades and decompression. Several methods are currently available to evaluate these stressors in installed turbines, i.e. using live fish or autonomous sensor devices, and in reduced-scale physical models, i.e. registering collisions from plastic beads. However, a priori estimates with computational modeling approaches applied early in the process of turbine design can facilitate the development of fish-friendly turbines. In the present study, we evaluated the frequency of blade strike and nadir pressure environment by modeling potential fish trajectories with the Discrete Element Method (DEM) applied to fish-like composite particles. In the DEM approach, particles are subjected to realistic hydraulic conditions simulated with computational fluid dynamics (CFD), and particle-structure interactions—representing fish collisions with turbine blades—are explicitly recorded and accounted for in the calculation of particle trajectories. We conducted transient CFD simulations by setting the runner in motion and allowing for better turbulence resolution, a modeling improvement over the conventional practice of simulating the system in steady state which was also done here. While both schemes yielded comparable bulk hydraulic performance, transient conditions exhibited a visual improvement in describing flow variability. We released streamtraces (steady flow solution) and DEM particles (transient solution) at the same location from where sensor fish (SF) have been released in field studies of the modeled turbine unit. The streamtrace-based results showed a better agreement with SF data than the DEM-based nadir pressures did because the former accounted for the turbulent dispersion at the intake but the latter did not. However, the DEM-based strike frequency is more representative of blade-strike probability than the steady solution is, mainly because DEM particles accounted for the full fish length, thus resolving (instead of modeling) the collision event.

CFD↗
DOE OSTI2014

DISCRETE ELEMENT MODELING OF BLADE–STRIKE FREQUENCY AND SURVIVAL OF FISH PASSING THROUGH HYDROKINETIC TURBINES

Evaluating the consequences from blade-strike of fish on marine hydrokinetic (MHK) turbine blades is essential for incorporating environmental objectives into the integral optimization of machine performance. For instance, experience with conventional hydroelectric turbines has shown that innovative shaping of the blade and other machine components can lead to improved designs that generate more power without increased impacts to fish and other aquatic life. In this work, we used unsteady computational fluid dynamics (CFD) simulations of turbine flow and discrete element modeling (DEM) of particle motion to estimate the frequency and severity of collisions between a horizontal axis MHK tidal energy device and drifting aquatic organisms or debris. Two metrics are determined with the method: the strike frequency and survival rate estimate. To illustrate the procedure step-by-step, an exemplary case of a simple runner model was run and compared against a probabilistic model widely used for strike frequency evaluation. The results for the exemplary case showed a strong correlation between the two approaches. In the application case of the MHK turbine flow, turbulent flow was modeled using detached eddy simulation (DES) in conjunction with a full moving rotor at full scale. The CFD simulated power and thrust were satisfactorily comparable to experimental results conducted in a water tunnel on a reduced scaled (1:8.7) version of the turbine design. A cloud of DEM particles was injected into the domain to simulate fish or debris that were entrained into the turbine flow. The strike frequency was the ratio of the count of colliding particles to the crossing sample size. The fish length and approaching velocity were test conditions in the simulations of the MHK turbine. Comparisons showed that DEM-based frequencies tend to be greater than previous results from Lagrangian particles and probabilistic models, mostly because the DEM scheme accounts for both the geometric aspects of the passage event ---which the probabilistic method does--- as well as the fluid-particle interactions ---which the Lagrangian particle method does. The DEM-based survival rates were comparable to laboratory results for small fish but not for mid-size fish because of the considerably different turbine diameters. The modeling framework can be used for applications that aim at evaluating the biological performance of MHK turbine units during the design phase and to provide information to regulatory agencies needed for the environmental permitting process.

blade strike↗
DOE OSTI2017

On-the-fly Doppler broadening of unresolved resonance region cross sections

In this paper, two methods for computing temperature-dependent unresolved resonance region cross sections on-the-fly within continuous-energy Monte Carlo neutron transport simulations are presented. The first method calculates Doppler broadened cross sections directly from zero-temperature average resonance parameters. In a simulation, at each event that requires cross section values, a realization of unresolved resonance parameters is generated about the desired energy and temperature-dependent single-level Breit-Wigner resonance cross sections are computed directly via the analytical Ψ-x Doppler integrals. The second method relies on the generation of equiprobable cross section magnitude bands on an energy-temperature mesh. Within a simulation, the bands are sampled and interpolated in energy and temperature to obtain cross section values on-the-fly. Both of the methods, as well as their underlying calculation procedures, are verified numerically in extensive code-to-code comparisons. Energy-dependent pointwise cross sections calculated with the newly-implemented procedures are shown to be in excellent agreement with those calculated by a widely-used nuclear data processing code. Relative differences at or below 0.1% are observed. Integral criticality benchmark results computed with the proposed methods are shown to reproduce those computed with a state-of-the-art processed nuclear data library very well. In simulations of fast spectrum systems which are highly-sensitive to the representation of cross section data in the unresolved region, k-eigenvalue and neutron flux spectra differences of <10 pcm and <1.0% are observed, respectively. The direct method is demonstrated to be well-suited to the calculation of reference solutions — against which results obtained with a discretized representation may be assessed — as a result of its treatment of the energy, temperature, and cross section magnitude variables as continuous. Also, because there is no pre-processed data to store (only temperature-independent average resonance parameters) the direct method is very memory-efficient. Typically, only a few kB of memory are needed to store all required unresolved region data for a single nuclide. However, depending on the details of a particular simulation, performing URR cross section calculations on-the-fly can significantly increase simulation times. Alternatively, the method of interpolating equiprobable probability bands is demonstrated to produce results that are as accurate as the direct reference solutions, to within arbitrary precision, with high computational efficiency in terms of memory requirements and simulation time. Analyses of a fast spectrum system show that interpolation on a coarse energy-temperature mesh can be used to reproduce reference k-eigenvalue results obtained with cross sections calculated continuously in energy and directly at an exact temperature to within <10 pcm. Probability band data on a mesh encompassing the range of temperatures relevant to reactor analysis usually require around 100 kB of memory per nuclide. Finally, relative to the case in which probability table data generated at a single, desired temperature are used, minor increases in simulation times are observed when probability band interpolation is employed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Accurate chemical master equation solution using multi-finite buffers

Here, the discrete chemical master equation (dCME) provides a fundamental framework for studying stochasticity in mesoscopic networks. Because of the multiscale nature of many networks where reaction rates have a large disparity, directly solving dCMEs is intractable due to the exploding size of the state space. It is important to truncate the state space effectively with quantified errors, so accurate solutions can be computed. It is also important to know if all major probabilistic peaks have been computed. Here we introduce the accurate CME (ACME) algorithm for obtaining direct solutions to dCMEs. With multifinite buffers for reducing the state space by $O(n!)$, exact steady-state and time-evolving network probability landscapes can be computed. We further describe a theoretical framework of aggregating microstates into a smaller number of macrostates by decomposing a network into independent aggregated birth and death processes and give an a priori method for rapidly determining steady-state truncation errors. The maximal sizes of the finite buffers for a given error tolerance can also be precomputed without costly trial solutions of dCMEs. We show exactly computed probability landscapes of three multiscale networks, namely, a 6-node toggle switch, 11-node phage-lambda epigenetic circuit, and 16-node MAPK cascade network, the latter two with no known solutions. We also show how probabilities of rare events can be computed from first-passage times, another class of unsolved problems challenging for simulation-based techniques due to large separations in time scales. Overall, the ACME method enables accurate and efficient solutions of the dCME for a large class of networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Breaking Computational Barriers: Real-time Analysis and Optimization with Large-scale Nonlinear Models via Model Reduction

Model reduction for dynamical systems is a promising approach for reducing the computational cost of large-scale physics-based simulations to enable high-fidelity models to be used in many- query (e.g., Bayesian inference) and near-real-time (e.g., fast-turnaround simulation) contexts. While model reduction works well for specialized problems such as linear time-invariant systems, it is much more difficult to obtain accurate, stable, and efficient reduced-order models (ROMs) for systems with general nonlinearities. This report describes several advances that enable nonlinear reduced-order models (ROMs) to be deployed in a variety of time-critical settings. First, we present an error bound for the Gauss-Newton with Approximated Tensors (GNAT) nonlinear model reduction technique. This bound allows the state-space error for the GNAT method to be quantified when applied with the backward Euler time-integration scheme. Second, we present a methodology for preserving classical Lagrangian structure in nonlinear model reduction. This technique guarantees that important properties--such as energy conservation and symplectic time-evolution maps--are preserved when performing model reduction for models described by a Lagrangian formalism (e.g., molecular dynamics, structural dynamics). Third, we present a novel technique for decreasing the temporal complexity --defined as the number of Newton-like iterations performed over the course of the simulation--by exploiting time-domain data. Fourth, we describe a novel method for refining projection-based reduced-order models a posteriori using a goal-oriented framework similar to mesh-adaptive h -refinement in finite elements. The technique allows the ROM to generate arbitrarily accurate solutions, thereby providing the ROM with a 'failsafe' mechanism in the event of insufficient training data. Finally, we present the reduced-order model error surrogate (ROMES) method for statistically quantifying reduced- order-model errors. This enables ROMs to be rigorously incorporated in uncertainty-quantification settings, as the error model can be treated as a source of epistemic uncertainty. This work was completed as part of a Truman Fellowship appointment. We note that much additional work was performed as part of the Fellowship. One salient project is the development of the Trilinos-based model-reduction software module Razor , which is currently bundled with the Albany PDE code and currently allows nonlinear reduced-order models to be constructed for any application supported in Albany. Other important projects include the following: 1. ROMES-equipped ROMs for Bayesian inference: K. Carlberg, M. Drohmann, F. Lu (Lawrence Berkeley National Laboratory), M. Morzfeld (Lawrence Berkeley National Laboratory). 2. ROM-enabled Krylov-subspace recycling: K. Carlberg, V. Forstall (University of Maryland), P. Tsuji, R. Tuminaro. 3. A pseudo balanced POD method using only dual snapshots: K. Carlberg, M. Sarovar. 4. An analysis of discrete v. continuous optimality in nonlinear model reduction: K. Carlberg, M. Barone, H. Antil (George Mason University). Journal articles for these projects are in progress at the time of this writing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Mechanism of Tyrosine-Driven Deprotonation in Photosystem II Revealed by Multiscale Simulations

Photosystem II (PSII) drives light-induced water oxidation via stepwise redox transitions of its oxygen-evolving complex (OEC), a Mn 4 Ca cluster advancing through five intermediate S-states (S 0 –S 4 ). The S 2 → S 3 transition involves a redox event in which a Mn ion donates an electron to the redox-active tyrosine YZ, coupled to deprotonation of an OEC-bound water ligand─yet the underlying coupling mechanism remains unresolved. Time-resolved serial femtosecond crystallography (TR-SFX) has revealed transient electron density shifts near the redox-active tyrosine Y Z , interpreted as sequential oxidation and reduction, with reduction initiating ∼1 μs after excitation and substantially progressed by 30 μs. However, this interpretation conflicts with kinetics from photothermal beam deflection (PBD), time-resolved X-ray absorption spectroscopy (TR-XAS), and electron paramagnetic resonance (EPR), which place electron transfer at 190–400 μs and proton transfer around 30 μs. Here, we reconcile these discrepancies using quantum mechanics/molecular mechanics (QM/MM) and molecular dynamics (MD) simulations. We show that oxidation of P680 and Y Z breaks the symmetry of the nearby hydrogen bonds involving water molecule W4, displacing Y Z and replicating the TR-SFX features of Y Z and Q165 observed at 1 μs. This local perturbation propagates through a hydrogen-bond network, transmitting the electrostatic signal from Y Z to the E65-E312 dyad and triggering redox-coupled deprotonation via the Cl1 channel. By 30 μs, the hydrogen-bond symmetry is restored through deprotonation of W2 (or alternatively W1), reproducing the disappearance of TR-SFX density differences around Y Z and Q165 without requiring Y Z reduction. Our proposed mechanism also gives molecular insights into the O6* density, assigning it to water reorganization rather than a discrete Ca-bound hydroxide species. Here, our results reveal a detailed atomistic mechanism linking Y Z oxidation to long-range proton release and suggest a functional role for the nearby Cl – ion in proton transfer. More broadly, this study underscores the importance of hydrogen-bond dynamics in mediating redox-driven proton transport and demonstrates how integrative simulations can resolve mechanistic ambiguities.

Deprotonation↗
DOE OSTI2014

A New On-the-Fly Sampling Method for Incoherent Inelastic Thermal Neutron Scattering Data in MCNP6

At thermal energies, the scattering of neutrons in a system is complicated by the comparable velocities of the neutron and target, resulting in competing upscattering and downscattering events. The neutron wavelength is also similar in size to the target's interatomic spacing making the scattering process a quantum mechanical problem. Because of the complicated nature of scattering at low energies, the thermal data files in ACE format used in continuous-energy Monte Carlo codes are quite large { on the order of megabytes for a single temperature and material. In this paper, a new storage and sampling method is introduced that is orders of magnitude less in size and is used to sample scattering parameters at any temperature on-the-fly. In addition to the reduction in storage, the need to pre-generate thermal scattering data tables at fine temperatures has been eliminated. This is advantageous for multiphysics simulations which may involve temperatures not known in advance. A new module was written for MCNP6 that bypasses the current S(α,β) table lookup in favor of the new format. The new on-the-fly sampling method was tested for graphite for two benchmark problems at ten temperatures: 1) an eigenvalue test with a fuel compact of uranium oxycarbide fuel homogenized into a graphite matrix, 2) a surface current test with a \broomstick" problem with a monoenergetic point source. The largest eigenvalue difference was 152pcm for T= 1200K. For the temperatures and incident energies chosen for the broomstick problem, the secondary neutron spectrum showed good agreement with the traditional S(α,β) sampling method. These preliminary results show that sampling thermal scattering data on-the-fly is a viable option to eliminate both the storage burden of keeping thermal data at discrete temperatures and the need to know temperatures before simulation runtime.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

DR Argillite Disposal R&D at LBNL

Within the Natural Barrier System (NBS) group of the Used Fuel Disposition (UFD) Campaign at the Department of Energy’s (DOE) Office of Nuclear Energy, LBNL’s research activities have focused on understanding and modeling EDZ evolution and the associated coupled processes and impacts of high temperature on parameters and processes relevant to performance of a clay repository to establish the technical base for the maximum allowable temperature. This report documents results from some of these activities. These activities address key Features, Events, and Processes (FEPs), which have been ranked in importance from medium to high, as listed in Table 7 of the Used Fuel Disposition Campaign Disposal Research and Development Roadmap (FCR&D-USED-2011-000065 REV0) (Nutt, 2011). Specifically, they address FEP 2.2.01, Excavation Disturbed Zone, for clay/shale, by investigating how coupled processes affect EDZ evolution; FEP 2.2.05, Flow and Transport Pathways; and FEP 2.2.08, Hydrologic Processes, and FEP 2.2.07, Mechanical Processes, and FEP 2.2.09, Chemical Process—Transport, by studying near-field coupled THMC processes in clay/shale repositories. The activities documented in this report also address a number of research topics identified in Research & Development (R&D) Plan for Used Fuel Disposition Campaign (UFDC) Natural System Evaluation and Tool Development (Wang 2011), including Topics S3, Disposal system modeling – Natural System; P1, Development of discrete fracture network (DFN) model; P14, Technical basis for thermal loading limits; and P15 Modeling of disturbed rock zone (DRZ) evolution (clay repository).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Radioactive Source Localization via Bayesian Particle Filter

In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

Mixed Convection in the VHTR in the Event of a LOFA

The US Department of Energy, Office of Nuclear Energy (DOE-NE) is supporting the development of a very high temperature reactor (VHTR) concept as the primary focus of it next generation nuclear power plant (NGNP) program. The VHTR is cooled by forcing helium downwards through the core into the lower plenum and out the hot duct. In the event that the coolant circulators are lost, the driving pressure drop across the core will reduce to zero and there will be the opportunity for natural circulation to occur. During the time that the circulators are powering down, the heat transfer in the core from the graphite blocks to the helium coolant will transform from turbulent forced convection to mixed convection, where buoyancy effects become important, to free or natural convection, where buoyancy is dominant. Analysis of the nature of the forced, mixed and free convection is best done using computational fluid dynamic (CFD) software that can provide fine details of the flow and heat transfer. However, CFD analysis involves approximations in the results because of the finite nature of the spatial and temporal discretizations required, the inexact nature of the turbulence models that are used and the finite precision of the computers employed. Therefore, it is necessary to validate the CFD computations. Validation is accomplished by comparing results from specific CFD computations to experimental data that have been taken specifically for the purpose of validation and that are related to the physical phenomena in question. The present report examines the flow and heat transfer parameters (dimensionless numbers) that characterize the flow and reports ranges for their values based on specific CFD studies performed for the VHTR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗