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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 OSTI2023

Enhanced Hanford Low-Activity Waste Glass Property Data Development: Phase 5 and Phase 6

This report summarizes the data collected on two test matrices of low-activity waste (LAW) glass compositions intended to expand the composition-property database: Low-Activity Waste (LAW) Phase 5: Expansion of LAW Glass Composition Boundaries and LAW Phase 6: High PCT and VHT Response Glass Matrix. Both matrix glass compositions were statistically designed to expand the LAW glass composition region. The analyses performed on these glasses include chemical composition (for target compositional verification), density, viscosity, electrical conductivity, crystal fraction, container centerline cooling with crystal identification, the product consistency test (PCT) response, the vapor hydration test (VHT) response, and sulfur solubility. Because of the slightly different scope of the two matrices, not all methods were applied to both matrices. Specifically, the following measurements were taken only on the LAW Phase 5: Expansion of LAW Glass Composition Boundaries glasses: crystal fraction as a function of temperature, density (ρ), viscosity (η), and electrical conductivity (EC, e). Combined, these data contribute a significant amount, 51 glasses, to the database for high LAW loaded enhanced waste glasses. Most of these data are focused near the boundaries of acceptable PCT and VHT responses, where prediction uncertainties are most impactful.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Multifunctional Fiber-Reinforced Polymer Composites for Damage Detection and Memory

Self-structural health monitoring (SHM) functionalities for fiber-reinforced polymer composites have become highly sought after to ensure the structural safety of newly advancing components in the automotive, civil, mechanical, and aerospace industries. This paper introduces a self-damage detection and memory (SDDM) hybrid composite material, where the structural carbon fiber tow is transformed into a piezoresistive sensor network, and the structural glass fiber operates as electrical insulation. In this study, SDDM specimens were fabricated, and tensile and impact tests were performed. The tensile tests of SDDM specimens find two distinct loading peaks: first where the carbon fiber fails, and second where the glass fiber fails. A linear correlation was observed between the carbon fiber resistance and composite strain up to a threshold, beyond which a sharp nonlinear increase in resistance occurred. The resistance then approached infinity, coinciding with the first loading peak and failure of the carbon fiber elements. This demonstrates the potential for a damage early warning threshold. Additionally, the effect of stitching the sensor tow in a zig-zag pattern over a large area was investigated using tailored fiber placement (TFP) of 1-loop, 3-loop, and 5-loop specimens. Tensile testing found that increasing the number of loops improved the sensor’s accuracy for strain sensing. Furthermore, impact tests were conducted, and as the impact energy progressively increased, the sensor resistance permanently increased. This illustrates a capability for self-memory of microdamage throughout the life cycle of the structure, potentially useful for predicting the remaining life of the composite.

Demo, Luke B. (ORCID:0000000208806522)↗
DOE OSTI2017

Review of CTF’s Fuel Rod Modeling Using FRAPCON-4.0’s Centerline Temperature Predictions

Coolant Boiling in Rod Arrays–Two Fluid (COBRA-TF), or CTF1 [1], is a nuclear thermal hydraulic subchannel code used throughout academia and industry. CTF’s fuel rod modeling is originally developed for VIPRE code [2]. Its methodology is based on GAPCON [3] and FRAP [4] fuel performance codes, and material properties are included from MATPRO handbook [5]. This work focuses on review of CTF’s fuel rod modeling to address shortcomings in CTF’s temperaturepredictions. CTF is compared to FRAPCON which is U.S. NRC’s steady-state fuel performance code for light-water reactor fuel rods. FRAPCON calculates the changes in fuel rod variables and temperatures including the eects of cladding hoop strain, cladding oxidation, hydriding, fuel irradiation swelling, densification, fission gas release and rod internal gas pressure. It uses fuel, clad and gap material properties from MATPRO. Additionally, it has its own models for fission gas release, cladding corrosion and cladding hydrogen pickup. It allows finite dierence or finite element approaches for its mechanical model.In this study, FRAPCON-4.0 [6] is used as a reference fuel performance code. In comparison, Halden Reactor Data for IFA432 Rod 1 and Rod 3. CTF simulations are performed in two ways; informing CTF with gap conductance value from FRAPCON, and using CTF’s dynamic gap conductance model.First case is chosen to show temperature is predicted correctly with CTF’s models for thermal and cladding conductivities once gap conductance is provided. Latter is to review CTF’s dynamic gap conductance model. These Halden test cases are selected to be representative of cases with and without any physical contact between fuel-pellet and clad while reviewing functionality of CTF’s dynamic gap conductance model. Improving the CTF’s dynamic gap conductance model will allowprediction of fuel and cladding thermo-mechanical behavior under irradiation, and better temperature feedbacks from CTF in transient calculations.

Toptan, Aysenur↗
DOE OSTI2026

A Physics-Based Digital Twin for Wave Elevation and Seabed Moment Estimation of Offshore Monopiles: Preprint

In this work, we present a proof of concept of a physics-based digital twin for a monopile structure (with overhead inertia) subjected to wave loading. The digital twin is formulated using reduced-order models derived from first principles and combined with a Kalman filter for state estimation. The proposed framework estimates the monopile top motion, the wave elevation, and the section forces and moments along the pile using primarily acceleration measurements at the monopile top. Key innovations include the use of a hydrodynamic shape function to represent distributed wave loading in a compact and computationally efficient manner, and the introduction of a shaping filter to augment the state-space with wave kinematics. Synthetic measurement data are generated using OpenFAST and used as a reference to assess the performance of the digital twin. Results demonstrate that the wave elevation can be accurately reconstructed without direct sea-state measurements as long as the wave regime is inertia-dominated. Under the ideal tested conditions, the total hydrodynamic force and sea-bed bending moment are estimated with relative errors on the order of 1% and correlation coefficients exceeding 96%. Future work will evaluate the estimator's performance under operational uncertainties and more complex loading conditions.

17 WIND ENERGY↗
DOE OSTI2019

Molecular Engineering of Hydroxide Conducting Polymers for Anion Exchange Membranes in Electrochemical Energy Conversion Technology

Anion exchange membranes (AEMs) based on hydroxide-conducting polymers (HCPs) are a key component for anion-based electrochemical energy technology such as fuel cells, electrolyzers, and advanced batteries. Although these alkaline electrochemical applications offer a promising alternative to acidic proton exchange membrane electrochemical devices, access to alkaline-stable and high-performing polymer electrolyte materials has remained elusive until now. Despite vigorous research of AEM polymer design, literature examples of high-performance polymers with good alkaline stability at an elevated temperature are uncommon. Traditional aromatic polymers used in AEM applications contain a heteroatomic backbone linkage, such as an aryl ether bond, which is prone to degradation via nucleophilic attack by hydroxide ion. In this Account, we highlight some of the progress our group has made in the development of advanced HCPs for applications in AEMs and electrode ionomers. Here, we propose that a synthetic polymer design with an all C−C bond backbone and a flexible chain-tethered quaternary ammonium group provides an effective solution to the problem of alkaline stability. Because of the critical demand for such a polymer system, we have established new synthetic strategies for polymer functionalization and polycondensation using an acid catalyst. The first approach is to graft a cationic tethered alkyl group to pre-existing, commercially available styrene-based block copolymers. The second approach is to synthesize high-molecular-weight aromatic backbone polymers using acid-catalyzed polycondensation of arene monomers and a functionalized trifluoromethyl ketone substrate. Both strategies involve a simple two-step reaction process and avoid the use of expensive metal-based catalysts and toxic chemicals, thereby making the synthetic processes easily scalable to large industrial quantities. Both polymer systems were found to have excellent alkaline stability, confirmed by the preservation of ion exchange capacity and ion conductivity of the membrane after an alkaline test under conditions of 1 M NaOH at 80−95 °C. In addition, the advantage of good solvent processability and convenient scalability of the reaction process generates considerable interest in these polymers as commercial standard AEM candidates. AEM fuel cell and electrolyzer tests of some of the developed polymer membranes showed excellent performance, suggesting that this new class of HCPs opens a new avenue to electrochemical devices with real-world applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Consideration for the application of artificial neural networks to criticality code validation - 14270

The artificial neural network (ANN) is a consistent example for non-parametric parameter estimation and regression, with powerful universal approximation properties, that is distribution independent. ANN application to criticality code validation centers on aligning mathematical relationships between code validation parameters and neural network prediction for those parameter values. Two specific goals are: (1) an appropriate ANN architecture to determine validation parameter values, and (2) bootstrapping individual ANNs as a 'Prediction Interval' (PI) technique to estimate the Calculation Margin and Upper Subcritical Limit. The individual ANN workflow is segregated into Training, Validation (network), and Testing Sets, where the network predictive properties and performance are expressed in the latter set. The Bootstrap ANN replicates a large set of individual ANNs (taken from the original data distribution) where (1-α/2)100% PI estimates can be determined. Results from the ANN method are compared to a variety of validation examples: a 'toy example' from ANSI/ANS-8.24, Appendix D, a variety of methods noted in a Nuclear Criticality Safety Division 2009 paper, and several validation campaigns for highly enriched uranium and plutonium systems. The ANN method is robust and can be applied to single or multivariate inputs. A trained ANN can provide both an average estimate (e.g., single value) and an estimate over a range of independent variable values where the kUSL can be formed in a regression relationship suitable for extrapolation. The input dependence has been tested, ranging from 15 to over 400 sample size distributions. An expanded Shapiro-Wilk test (for sample sizes up to 5000) was implemented to confirm that the ANN method is transparent to distribution function. The Principle Component Analysis method was applied as an input preprocessing step embedded within the ANN in order to reduce dimensionality and correlation for multivariable inputs. This can potentially aid in determining accurate margins over applying arbitrary margins. The automatic optimization of the Bootstrap ANN PI is left for future consideration. (authors)

42 ENGINEERING↗
DOE OSTI2018

Temperature and Humidity Stable Alkali/Alkaline-Earth Metal Carbonates as Electron Heterocontacts for Silicon Photovoltaics

Nanometer scale interfacial layers between the metal cathode and the n-type semiconductor play a critical role in enhancing the transport of charge carriers in and out of optoelectronic devices. In this research, a range of nanoscale alkali and alkaline earth metal carbonates (i.e., potassium, rubidium, caesium, calcium, strontium, and barium) are shown to function effectively as electron heterocontacts to lightly doped n-type crystalline silicon (c-Si), which is particularly challenging to contact with common metals. These carbonate interlayers are shown to enhance the performance of n-type c-Si proof-of-concept solar cells up to a power conversion efficiency of ≈19%. Furthermore, these devices are thermally stable up to 350 °C and both the caesium and barium carbonates pass a standard 1000 h damp heat test, with >95% of their initial performance maintained. The temperature and humidity stable electron heterocontacts based on alkali and alkaline earth metal carbonates show a high potential for industrial feasibility and longevity for deployment in the field.

36 MATERIALS SCIENCE↗
DOE OSTI2015

p53-Based Strategy for Protection of Bone Marrow From Y-90 Ibritumomab Tiuxetan

Purpose: The main drawbacks of radioimmunotherapy have been severe hematological toxicity and potential development of myelodysplastic syndrome and secondary leukemia. Activation of p53 follows a major pathway by which normal tissues respond to DNA-damaging agents, such as chemotherapy and radiation therapy, that result in injuries and pathological consequences. This pathway is separate from the tumor suppressor pathway of p53. We have previously reported that use of low-dose arsenic (LDA) temporarily and reversibly suppresses p53 activation, thereby ameliorating normal tissue toxicity from exposure to 5-fluorouracil and X rays. We have also demonstrated that LDA-mediated protection requires functional p53 and thus is selective to normal tissues, as essentially every cancer cell has dysfunctional p53. Here we tested the protective efficacy of LDA for bone marrow tissue against radioimmunotherapy through animal experiments. Methods and Materials: Mice were subjected to LDA pretreatment for 3 days, followed by treatment with Y-90 ibritumomab tiuxetan. Both dose course (10, 25, 50, 100, and 200 μCi) and time course (6, 24, and 72 hours and 1 and 2 weeks) experiments were performed. The response of bone marrow cells to LDA was determined by examining the expression of NFκB, Glut1, and Glut3. Staining with hematoxylin and eosin, γ-H2AX, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) was used to examine morphology, DNA damage response, and apoptotic cell populations. Results: Elevated levels of NFκB, Glut1, and Glut3 were observed in bone marrow cells after LDA treatment. Bone marrow damage levels induced by Y-90 ibritumomab tiuxetan were greatly reduced by LDA pretreatment. Consistent with this observation, significantly less DNA damage and fewer apoptotic cells were accumulated after Y-90 ibritumomab tiuxetan treatment in LDA-pretreated mice. Furthermore, in the mouse xenograft model implanted with human Karpas-422 lymphoma cells, LDA pretreatment did not have any detectable effect on either tumor growth or Y-90 ibritumomab tiuxetan (200 μCi)-induced tumor suppression. Conclusions: LDA pretreatment protected bone marrow without compromising tumor control caused by Y-90 ibritumomab tiuxetan.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

ENDF/B-VIII.1: Updated Nuclear Reaction Data Library for Science and Applications

The ENDF/B-VIII.1 library is the newest recommended evaluated nuclear data file by the Cross Section Evaluation Working Group (CSEWG) for use in nuclear science and technology applications, and incorporates advances made in the six years since the release of ENDF/B-VIII.0. Among key advances made are that the 239 Pu file was reevaluated by a joint international effort and that updated 16,18 O, 19 F, 28–30 Si, 50–54 Cr, 55 Mn, 54,56,57 Fe, 63,65 Cu, 139 La, 233,235,238 U, and 240,241 Pu neutron nuclear data from the IAEA coordinated INDEN collaboration were adopted. Over 60 neutron dosimetry cross sections were adopted from the IAEA's IRDFF-II library. In addition, the new library includes significant changes for 3 He, 6 Li, 9 Be, 51 V, 88 Sr, 103 Rh, 140,142 Ce, Dy, 181 Ta, Pt, 206–208 Pb, and 234,236 U neutron data, and new nuclear data for the photonuclear, charged-particle and atomic sublibraries. Numerous thermal neutron scattering kernels were reevaluated or provided for the very first time. On the covariance side, work was undertaken to introduce better uncertainty quantification standards and testing for nuclear data covariances. The significant effort to reevaluate important nuclides has reduced bias in the simulations of many integral experiments with particular progress noted for fluorine, copper, and stainless steel containing benchmarks. Data issues hindered the successful deployment of the previous ENDF/B-VIII.0 for commercial nuclear power applications in high burnup situations. These issues were addressed by improving the 238 U and 239,240,241 Pu evaluated data in the resonance region. The new library performance as a function of burnup is similar to the reference ENDF/B-VII.1 library.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Arrays of Functionalized Graphene Chemiresistors for Selective Sensing of Volatile Organic Compounds

Real-time detection of volatile organic compounds (VOCs) is being spotlighted for its importance in environmental monitoring and disease detection from the breath. However, the selective detection of VOCs in a small form factor gas sensor remains a challenge. Here, we present the VOC sensing performance of phthalocyanine (Pc)-functionalized graphene chemiresistors supported by the theoretical prediction of Pc's VOC interactions. Pc functionalization, with and without metalation, was studied parametrically with varying deposition parameters to explore impacts on the gas sensing response toward VOCs as a function of substrate coverage. Sensing data were collected to establish fingerprint signatures for a variety of VOCs. In conclusion, improvement in selectivity is shown by successfully differentiating the VOCs from each other when combined into a gas sensor array tested with acetone, ethanol, formaldehyde, and toluene.

2D materials↗
DOE OSTI2021

NENCI-2021. I. A large benchmark database of non-equilibrium non-covalent interactions emphasizing close intermolecular contacts

In this work, we present NENCI-2021, a benchmark database of ~8000 Non-Equilibirum Non-Covalent Interaction energies for a large and diverse selection of intermolecular complexes of biological and chemical relevance. To meet the growing demand for large and high-quality quantum mechanical data in the chemical sciences, NENCI-2021 starts with the 101 molecular dimers in the widely used S66 and S101 databases and extends the scope of these works by (i) including 40 cation–π and anion–π complexes, a fundamentally important class of non-covalent interactions that are found throughout nature and pose a substantial challenge to theory, and (ii) systematically sampling all 141 intermolecular potential energy surfaces (PESs) by simultaneously varying the intermolecular distance and intermolecular angle in each dimer. Designed with an emphasis on close contacts, the complexes in NENCI-2021 were generated by sampling seven intermolecular distances along each PES (ranging from 0.7× to 1.1× the equilibrium separation) and nine intermolecular angles per distance (five for each ion–π complex), yielding an extensive database of 7763 benchmark intermolecular interaction energies (E int ) obtained at the coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory. The E int values in NENCI-2021 span a total of 225.3 kcal/mol, ranging from -38.5 to +186.8 kcal/mol, with a mean (median) E int value of -1.06 kcal/mol (-2.39 kcal/mol). In addition, a wide range of intermolecular atom-pair distances are also present in NENCI-2021, where close intermolecular contacts involving atoms that are located within the so-called van der Waals envelope are prevalent—these interactions, in particular, pose an enormous challenge for molecular modeling and are observed in many important chemical and biological systems. A detailed symmetry-adapted perturbation theory (SAPT)- based energy decomposition analysis also confirms the diverse and comprehensive nature of the intermolecular binding motifs present in NENCI-2021, which now includes a significant number of primarily induction-bound dimers (e.g., cation–π complexes). NENCI-2021 thus spans all regions of the SAPT ternary diagram, thereby warranting a new four-category classification scheme that includes complexes primarily bound by electrostatics (3499), induction (700), dispersion (1372), or mixtures thereof (2192). A critical error analysis performed on a representative set of intermolecular complexes in NENCI-2021 demonstrates that the E int values provided herein have an average error of ±0.1 kcal/mol, even for complexes with strongly repulsive E int values, and maximum errors of ±0.2–0.3 kcal/mol (i.e., ~±1.0 kJ/mol) for the most challenging cases. For these reasons, we expect that NENCI-2021 will play an important role in the testing, training, and development of next-generation classical and polarizable force fields, density functional theory approximations, wavefunction theory methods, and machine learning based intra- and inter-molecular potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Synchronverter-based Control of Multi-Port Autonomous Reconfigurable Solar Plants (MARS)

Control of integrated photovoltaic (PV) plants with energy storage systems (ESSs) has become an important research and development topic in recent times. In this context, a Multi-port Autonomous Reconfigurable Solar (MARS) plant that integrates PV and ESS to alternating current transmission grid and high-voltage direct current (HVdc) link is studied in this paper. With penetration of power electronic based resources in the grid, the grid’s capability to recover from frequency or voltage disturbances are reduced. Therefore, one of the vital objectives of any new grid integrated power electronic resource is to provide advanced control functions like voltage and frequency support to the grid during disturbances. In this research work, a detailed implementation of a synchronverter-based control algorithm of MARS is presented. The proposed control algorithm and the MARS control architecture are evaluated through simulations on PSCAD/EMTDC simulation platform to showcase the performance in different operating conditions. In addition, they are evaluated in Opal-RT offline simulation models which can also be used to perform control-hardware-in-the-loop (cHIL) tests.

Marthi, Phani Ratna Vanamali↗
DOE OSTI2016

TU-FG-209-12: Treatment Site and View Recognition in X-Ray Images with Hierarchical Multiclass Recognition Models

Purpose: To investigate an approach of automatically recognizing anatomical sites and imaging views (the orientation of the image acquisition) in 2D X-ray images. Methods: A hierarchical (binary tree) multiclass recognition model was developed to recognize the treatment sites and views in x-ray images. From top to bottom of the tree, the treatment sites are grouped hierarchically from more general to more specific. Each node in the hierarchical model was designed to assign images to one of two categories of anatomical sites. The binary image classification function of each node in the hierarchical model is implemented by using a PCA transformation and a support vector machine (SVM) model. The optimal PCA transformation matrices and SVM models are obtained by learning from a set of sample images. Alternatives of the hierarchical model were developed to support three scenarios of site recognition that may happen in radiotherapy clinics, including two or one X-ray images with or without view information. The performance of the approach was tested with images of 120 patients from six treatment sites – brain, head-neck, breast, lung, abdomen and pelvis – with 20 patients per site and two views (AP and RT) per patient. Results: Given two images in known orthogonal views (AP and RT), the hierarchical model achieved a 99% average F1 score to recognize the six sites. Site specific view recognition models have 100 percent accuracy. The computation time to process a new patient case (preprocessing, site and view recognition) is 0.02 seconds. Conclusion: The proposed hierarchical model of site and view recognition is effective and computationally efficient. It could be useful to automatically and independently confirm the treatment sites and views in daily setup x-ray 2D images. It could also be applied to guide subsequent image processing tasks, e.g. site and view dependent contrast enhancement and image registration. The senior author received research grants from ViewRay Inc. and Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Evaluation of Subgrid-scale Hydrometeor Transport Schemes using a High-resolution Cloud-resolving Model

Potential ways of parameterizing vertical turbulent fluxes of hydrometeors are examined using a high-resolution cloud-resolving model. The cloud-resolving model uses the Morrison microphysics scheme, which contains prognostic variables for rain, graupel, ice, and snow. A benchmark simulation with a horizontal grid spacing of 250 m of a deep convection case carried out to evaluate three different ways of parameterizing the turbulent vertical fluxes of hydrometeors: an eddy-diffusion approximation, a quadrant-based decomposition, and a scaling method that accounts for within-quadrant (subplume) correlations. Results show that the down-gradient nature of the eddy-diffusion approximation tends to transport mass away from concentrated regions, whereas the benchmark simulation indicates that the vertical transport tends to transport mass from below the level of maximum to aloft. Unlike the eddy-diffusion approach, the quadri-modal decomposition is able to capture the signs of the flux gradient but underestimates the magnitudes. The scaling approach is shown to perform the best by accounting for within-quadrant correlations, and improves the results for all hydrometeors except for snow. A sensitivity study is performed to examine how vertical transport may affect the microphysics of the hydrometeors. The vertical transport of each hydrometeor type is artificially suppressed in each test. Results from the sensitivity tests show that cloud-droplet-related processes are most sensitive to suppressed rain or graupel transport. In particular, suppressing rain or graupel transport has a strong impact on the production of snow and ice aloft. Lastly, a viable subgrid-scale hydrometeor transport scheme in an assumed probability density function parameterization is discussed.

cloud-resolving model↗
DOE OSTI2019

An Improved Double-Gaussian Closure for the Subgrid Vertical Velocity Probability Distribution Function

Abstract The vertical velocity probability distribution function (PDF) is analyzed throughout the depth of the lower atmosphere, including the subcloud and cloud layers, in four large-eddy simulation (LES) cases of shallow cumulus and stratocumulus. Double-Gaussian PDF closures are examined to test their ability to represent a wide range of turbulence statistics, from stratocumulus cloud layers characterized by Gaussian turbulence to shallow cumulus cloud layers displaying strongly non-Gaussian turbulence statistics. While the majority of the model closures are found to perform well in the former case, the latter presents a considerable challenge. A new model closure is suggested that accounts for high skewness and kurtosis seen in shallow cumulus cloud layers. The well-established parabolic relationship between skewness and kurtosis is examined, with results in agreement with previous studies for the subcloud layer. In cumulus cloud layers, however, a modified relationship is necessary to improve performance. The new closure significantly improves the estimation of the vertical velocity PDF for shallow cumulus cloud layers, in addition to performing well for stratocumulus. In particular, the long updraft tail representing the bulk of cloudy points is much better represented and higher-order moments diagnosed from the PDF are also greatly improved. However, some deficiencies remain owing to fundamental limitations of representing highly non-Gaussian turbulence statistics with a double-Gaussian PDF.

Fitch, A. C.↗
DOE OSTI2022

Performance improvements of the windowed multipole formalism using a rational fraction approximation of the Faddeeva function

The windowed multipole (WMP) formalism was introduced as a way to calculate Doppler broadened cross sections on the fly during Monte Carlo simulations. While more arithmetic is needed compared to point-wise cross section look-ups, performance remained competitive from the large memory reductions and sequential data access. The single most expensive function call in a depleted fuel assembly problem using WMP comes from the evaluation of the Faddeeva function, which previously relied on a highly accurate, highly-branching algorithm. This paper explores the use of rational fraction approximations tailored to the domain interest of reactor physics applications and the development of lower accuracy approximations sufficient for our application. The rational approximations were implemented and tested in OpenMC on an infinite medium problem to stress the cross section calculation routine and a PWR assembly problem. In both cases, the rational approximation nearly eliminated the ∼ 20% penalty previously observed when comparing to point-wise libraries. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

ZND Verification Tests for Reactive Burn Models in FLAG

The ZND theory, named after Zeldovich, von Neumann, and Doering, provides a simple model for one-dimensional ideal steady-state detonation. It assumes that the detonation wave front starts with a shock that is a discontinuous jump and is followed by a finite-length reaction zone. Reactive burn (also called reactive flow) models are based on ZND theory, as they model the shock initiation and detonation process with a finite reaction rate. The ZND wave propagation test is essentially the only available test case where an analytic solution exists for verification of reactive burn models in numerical codes. However, there are extensions and variants of the ZND test that have been devised for verification of multidimensional flows. The objective of this work is to provide verification of the reactive burn models currently implemented in the Lagrangian hydrocode FLAG and investigate the influence of mesh resolution, artificial viscosity models, and the Arbitrary Lagrangian-Eulerian (ALE) Euler relaxer on the simulation results. The burn models of interest are the Wescott-Stewart-Davis (WSD) model, the Scaled Uniform Reactive Flow (SURF) model (specifically with the SURFplus model extension), and the Arrhenius shock temperature state dependent WSD (AWSD) model. Previously, Ralph Menikoff has used ZND tests for verification of the SURF and SURFplus models in the Eulerian hydrocode xRAGE. The ZND tests here are somewhat different than the approach by Menikoff. In particular, we use a piston-driven ZND detonation wave (via a prescribed constant velocity boundary condition) in a Lagrangian framework whereas Menikoff had a ZND wave followed by a invariant rarefaction wave. The xRAGE simulations were carried out on uniform grids and adaptive mesh refinement (AMR) grids. Although AMR was recently implemented in FLAG and now fully functional for 2D simulations, it will not be evaluated with ZND tests at this time. Some work has been done previously for validating the reactive burn models in FLAG. For example, the validation studies of SURF with shock-to-detonation (SDT) tests, cylinder tests, and gap-stick tests. Further validation of the AWSD, WSD, and SURF models is described in for SDT, multi-shock, cylinder, and corner-turning tests. Recently, a large parameter study with approximately twenty SDT tests was performed to validate the AWSD, WSD, SURF, and SURFplus models while also investigating mesh resolution and artificial viscosity settings. To the best of our knowledge, the current work represents the first documented verification of these burn models in FLAG. The reader should note that many of the tables and figures in this report use units of cm/g/µs, which are the default units for FLAG. However, some lengths and velocities are expressed in µm and mm/µs, respectively, which are typical units for detonation analyses.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Water Vapor Resistant SiC/SiC Composite for Hydrogen-Based Turbines (Final Scientific Technical Report)

New material innovations are needed for the extreme environments of next generation, hydrogen-fueled turbine engines. Ceramic matrix composites (CMCs) offer high-temperature capability but are susceptible to degradation in high-temperature water vapor. Pratt & Whitney’s (P&W) baseline silicon carbide (SiC)/SiC CMC was initially applied to design a component in a hydrogen-fueled engine, verifying the existence of a design space and extracting boundary conditions to inform testing parameters. Several material innovations, including two fibers, interface coatings (IFC), and self-healing matrices (SHM), were investigated to improve high-temperature performance in water vapor. A boron-doped pyrocarbon (B-PyC) IFC and a SHM matrix with layers of zirconium nitride (ZrN) or zirconium diboride (ZrB 2 ) were developed to fabricate minicomposites with either standard Hi-Nicalon™ Type S (HNS) fibers or new Tyranno® SA4 fibers (SA4). The B-PyC IFC is functional but lacks in providing improved durability. A matrix consisting of thick layers of SiC and thin layers of ZrB 2 shows promise as a SHM that can effectively seal matrix cracks in this extreme environment. Minicomposites with HNS fibers generally outperform those with SA4 fibers.

08 HYDROGEN↗