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Critical biogeochemical functions in the subsurface are associated with bacteria from new phyla and little studied lineages

Nitrogen, sulfur and carbon fluxes in the terrestrial subsurface are determined by the intersecting activities of microbial community members, yet the organisms responsible are largely unknown. Metagenomic methods can identify organisms and functions, but genome recovery is often precluded by data complexity. To address this limitation, we developed subsampling assembly methods to re-construct high-quality draft genomes from complex samples. Here, we applied these methods to evaluate the interlinked roles of the most abundant organisms in biogeochemical cycling in the aquifer sediment. Community proteomics confirmed these activities. The eight most abundant organisms belong to novel lineages, and two represent phyla with no previously sequenced genome. Four organisms are predicted to fix carbon via the Calvin Benson Bassham, Wood Ljungdahl or 3-hydroxyproprionate/4-hydroxybutarate pathways. The profiled organisms are involved in the network of denitrification, dissimilatory nitrate reduction to ammonia, ammonia oxidation and sulfate reduction/oxidation, and require substrates supplied by other community members. An ammonium-oxidizing Thaumarchaeote is the most abundant community member, despite low ammonium concentrations in the groundwater. Finally, this organism likely benefits from two other relatively abundant organisms capable of producing ammonium from nitrate, which is abundant in the groundwater. Overall, dominant members of the microbial community are interconnected through exchange of geochemical resources.

60 APPLIED LIFE SCIENCES↗

SU-F-T-12: Monte Carlo Dosimetry of the 60Co Bebig High Dose Rate Source for Brachytherapy

Purpose: The purpose of this work is to obtain the dosimetry parameters in accordance with the AAPM TG-43U1 formalism with Monte Carlo calculations regarding the BEBIG 60Co high-dose-rate brachytherapy. The geometric design and material details of the source was provided by the manufacturer and was used to define the Monte Carlo geometry. Methods: The dosimetry studies included the calculation of the air kerma strength Sk, collision kerma in water along the transverse axis with an unbounded phantom, dose rate constant and radial dose function. The Monte Carlo code system that was used was EGSnrc with a new cavity code, which is a part of EGS++ that allows calculating the radial dose function around the source. The XCOM photon cross-section library was used. Variance reduction techniques were used to speed up the calculation and to considerably reduce the computer time. To obtain the dose rate distributions of the source in an unbounded liquid water phantom, the source was immersed at the center of a cube phantom of 100 cm3. Results: The obtained dose rate constant for the BEBIG 60Co source was 1.108±0.001 cGyh-1U-1, which is consistent with the values in the literature. The radial dose functions were compared with the values of the consensus data set in the literature, and they are consistent with the published data for this energy range. Conclusion: The dose rate constant is consistent with the results of Granero et al. and Selvam and Bhola within 1%. Dose rate data are compared to GEANT4 and DORZnrc Monte Carlo code. However, the radial dose function is different by up to 10% for the points that are notably near the source on the transversal axis because of the high-energy photons from 60Co, which causes an electronic disequilibrium at the interface between the source capsule and the liquid water for distances up to 1 cm.

60 APPLIED LIFE SCIENCES↗

3D Multiresolution Velocity Model Fusion with Probability Graphical Models

ABSTRACT The variability in spatial resolution of seismic velocity models obtained via tomographic methodologies is attributed to many factors, including inversion strategies, ray-path coverage, and data integrity. Integration of such models, with distinct resolutions, is crucial during the refinement of community models, thereby enhancing the precision of ground-motion simulations. Toward this goal, we introduce the probability graphical model (PGM), combining velocity models with heterogeneous resolutions and nonuniform data point distributions. The PGM integrates data relations across varying resolution subdomains, enhancing detail within low-resolution (LR) domains by utilizing information and prior knowledge from high-resolution (HR) subdomains through a maximum posterior problem. Assessment of efficacy, utilizing both 2D and 3D velocity models—consisting of synthetic checkerboard models and a fault-zone model from Ridgecrest, California—demonstrates noteworthy improvements in accuracy, compared to state-of-the-art fusion techniques. Specifically, we find reductions of 30% and 44% in computed travel-time residuals for 2D and 3D models, respectively, as compared to conventional smoothing techniques. Unlike conventional methods, the PGM’s adaptive weight selection facilitates preserving and learning details from complex, nonuniform HR models and applies the enhancements to the LR background domain.

Geochemistry & Geophysics↗

The Impact of City-level Permitting Processes on Residential Photovoltaic Installation Prices and Development Times: An Empirical Analysis of Solar Systems in California Cities

Business process or “soft” costs account for well over 50% of the installed price of residential photovoltaic (PV) systems in the United States, so understanding these costs is crucial for identifying PV cost-reduction opportunities. Among these costs are those imposed by city-level permitting processes, which may add both expense and time to the PV development process. Building on previous research, this study evaluates the effect of city-level permitting processes on the installed price of residential PV systems and on the time required to develop and install those systems. The study uses a unique dataset from the U.S. Department of Energy’s Rooftop Solar Challenge Program, which includes city-level permitting process “scores,” plus data from the California Solar Initiative and the U.S. Census. Econometric methods are used to quantify the price and development-time effects of city-level permitting processes on more than 3,000 PV installations across 44 California cities in 2011. Results indicate that city-level permitting processes have a substantial and statistically significant effect on average installation prices and project development times. The results suggest that cities with the most favorable (i.e., highest-scoring) permitting practices can reduce average residential PV prices by $0.27–$0.77/W (4%–12% of median PV prices in California) compared with cities with the most onerous (i.e., lowest-scoring) permitting practices, depending on the regression model used. Though the empirical models for development times are less robust, results suggest that the most streamlined permitting practices may shorten development times by around 24 days on average (25% of the median development time). These findings illustrate the potential price and development-time benefits of streamlining local permitting procedures for PV systems.

14 SOLAR ENERGY↗

Method of controlling a vehicle to adjust perception system energy usage

A method of controlling a vehicle includes determining a current operating situation of the vehicle, and identifying a subset of a plurality of sensors of the vehicle needed to provide data to enable a vehicle control function for the current operating situation of the vehicle. A remainder of the plurality of sensors is disengaged to reduce electric energy usage by the vehicle while the vehicle is operating in the current operating situation of the vehicle. A sampling rate for the selected subset of sensors may be reduced to further reduce energy usage of the vehicle. Additionally, an energy reduction processing strategy may be implemented to reduce a processor frequency or a voltage of a computing device used to provide the vehicle control function to further reduce energy usage of the vehicle.

Hu, Yuxiao↗

Investigations of Beam Dynamics Issues at Current and Future Hadron Accelerators (Final Report)

There is a synergy between the fields of Beam Dynamics (BD) in modern particle accelerators and Applied Mathematics (AMa). We have formulated significant problems in BD and have developed and applied tools within the contexts of dynamical systems, topological methods, numerical analysis and scientific computing, probability and stochastic processes, and mathematical statistics. We summarize the three main areas of our AMa work since 2011. First, we continued our study of Vlasov-Maxwell systems. Previously, we developed a state of the art algorithm and code (VM3@A) to calculate coherent synchrotron radiation in single pass systems. In this cycle we carefully analyzed the major expense, namely the integral-over-history (IOH), and developed two approaches to speed up integration. The first strategy uses a representation of the Bessel function J0 in terms of exponentials. The second relies on “local sequences” developed recently for radiation boundary conditions, which are used to reduce computational domains. Although motivated by practicality, both strategies involve interesting and rather deep analysis and approximation theory. As an alternative to VM3@A, we are integrating Maxwell’s equations by a time-stepping method, bypass- ing the IOH, using a Discontinuous Galerkin (DG) method. DG is a generalization of Finite Element and Finite Volume methods. It is spectrally convergent, unlike the commonly used Finite Difference methods, and can handle complicated vacuum chamber geometries. We have applied this in several contexts and have obtained very nice results including an explanation of an experiment at the Canadian Light Source, where the geometry is quite complex. Second, we continued our study of spin dynamics in storage rings. There is much current and proposed activity where spin polarized beams are being used in testing the Standard Model and its modifications. Our work has focused on invariant spin fields (ISFs) and amplitude dependent spin tunes (ADSTs), which are essential for estimating beam polarization. Several algorithms have been developed since the 1980s for computing the ISF, among them the Heinemann- Hoffstaetter method of stroboscopic averaging (SA) which is implemented in the code SPRINT. SA, which computes the ISF by using spin tracking data, can find the ISF to computer precision if it exists and thus can give evidence for existence of the ISF. Central to our work is resolving the ISF conjecture, which says that, off orbital resonance, an ISF exists. Thus Heinemann developed, in his 2010 PhD thesis, a new framework which unifies and generalizes the notions of ISF and ADST by using bundle theory. This lead to a long paper which was a major collaborative effort during the recent cycle. In a nutshell, our bundle approach elegantly unifies the dynamics of spin-1/2 and spin-1 particles, e.g., protons and deuterons. In fact it is well known that these two kinds of dynamics are driven by the same spin transfer matrix and in our approach one sees the deeper reason for this: the spin transfer matrix carries the natural dynamics of a principal bundle whereas the difference between the spin-1/2 and spin-1 dynamics lies in their different geometrical situation, i.e., different underlying associated bundles. Thus one arrives at new results for polarized beams, among them the Invariant Reduction Theorem (IRT) and the Cross Section Theorem (CST). The IRT gives a necessary and sufficient condition for the ISF to exist. The SA technique revealed, 20 years ago, that each ISF can be viewed as a complex agglomerate of spin tracking data. The bundle approach goes one step further by using the IRT and the CST to glue spin tracking data into agglomerates which are candidates for ISFs. We gain insight because the “good” agglomerates, in the presence of an ISF, are very different from the “bad” ones. Finally we mention that the bundle approach has analogies to the approach used in geometrical Yang-Mills theory. Third, we studied X-Ray Free Electron Lasers (FELs), which are electron accelerators producing coherent undulator radiation over a wide range of frequencies from microwaves to x-rays. The photon beams produced in FEL undulators are used to study material samples in biology, material science etc. We developed a mathematical analysis, based on the 6D Lorentz system, of energetic electrons moving through a planar undulator excited by a Maxwell traveling wave field of wavelength λ. Our Method of Averaging perturbation analysis yields non-resonant and near-to-resonant normal form approximations as a function of λ, which we present in two averaging theorems. We prove the theorems in detail, error bounds and giving a tutorial on mathematically rigorous perturbation theory in a context where proofs are easily understood. To our knowledge the planar problem has not been analyzed with the generality here nor has the standard FEL pendulum system, which appears on resonance, been derived with error bounds. In addition to the domains of validity of the normal forms we obtain new insights that require further study, including a more general low gain theory. With a firm foundation in the non-collective case above we are studying the 3D collective case from start up from noise to high gain and saturation. We have formulated the noise start up as a problem of going from the microscopic Klimontovich-Maxwell to the macroscopic Vlasov-Maxwell with a Vlasov correction term. In the 1D setting, we seek an alternative to the phenomenological Vlasov approach which models shot noise by a perturbation on an initial “smooth” density. The 1D wave equation with a Klimontovich source is often the starting point for the 1D FEL high gain theory. We have a new representation of solutions which may lead to new insights.

43 PARTICLE ACCELERATORS↗

Physics-informed State-space Neural Networks for transport phenomena

This work introduces Physics -informed State -space neural network Models (PSMs), a novel solution to achieving real-time optimization, flexibility, and fault tolerance in autonomous systems, particularly in transportdominated systems such as chemical, biomedical, and power plants. Traditional data -driven methods fall short due to a lack of physical constraints like mass conservation; PSMs address this issue by training deep neural networks with sensor data and physics -informing using components' Partial Differential Equations (PDEs), resulting in a physics -constrained, end -to -end differentiable forward dynamics model. Further, through two in silico experiments - a heated channel and a cooling system loop - we demonstrate that PSMs offer a more accurate approach than a purely data -driven model. In the former experiment, PSMs demonstrated significantly lower average root -mean -square errors across test datasets compared to a purely data -driven neural network, with reductions of 44 %, 48 %, and 94 % in predicting pressure, velocity, and temperature, respectively. Beyond accuracy, PSMs demonstrate a compelling multitask capability, making them highly versatile. In this work, we showcase two: supervisory control of a nonlinear system through a sequentially updated state -space representation and the proposal of a diagnostic algorithm using residuals from each of the PDEs. The former demonstrates PSMs' ability to handle constant and time -dependent constraints, while the latter illustrates their value in system diagnostics and fault detection.

42 ENGINEERING↗

Numerical study of variable density turbulence interaction with a normal shock wave

Accurate numerical simulations of shock–turbulence interaction (STI) are conducted with a hybrid monotonicity-preserving–compact-finite-difference scheme for a detailed study of STI in variable density flows. Theoretical and numerical assessments of data confirm that all turbulence scales as well as the STI are well captured by the computational method. Linear interaction approximation (LIA) convergence tests conducted with the shock-capturing simulations exhibit a similar trend of converging to LIA predictions to shock-resolving direct numerical simulations (DNS). The effects of density variations on STI are studied by comparing the results corresponding to an upstream multi-fluid mixture with the single-fluid case. Here the results show that for the current parameter ranges, the turbulence amplification by the normal shock wave is much higher and the reduction in turbulence length scales is more significant when strong density variations exist. Turbulent mixing enhancement by the shock is also increased and stronger mixing asymmetry in the postshock region is observed when there is significant density variation. The turbulence structure is strongly modified by the shock wave, with a differential distribution of turbulent statistics in regions having different densities. The dominant mechanisms behind the variable density STI are identified by analysing the transport equations for the Reynolds stresses, vorticity, normalized mass flux and density specific volume covariance.

42 ENGINEERING↗

Single-Polymer–Particle Growth Kinetics with Molecular Catalyst Speciation and Single-Turnover Imaging

The dynamics of the local environments surrounding molecular polymerization catalysts plausibly impact turnover kinetics, but the impact of and nature of such dynamics have previously been obscured by ensemble averaging. With Grubbs’ second generation ruthenium metathesis catalyst and a precipitation polymerization system, studies at the single-particle and -turnover level establish that (1) an inverse correlation exists between rate and duration of single-polymer–particle growth of aggregates, consistent with a local environment density model for the time-variable kinetics; (2) cross-linking additives produced a small, but detectible, reduction in overall monomer incorporation; (3) total ruthenium quantity within the polymer particles (as characterized by energy dispersive X-ray spectroscopy) is differentiable from the quantity that is catalytically active (as characterized by in situ fluorescence microscopy), providing catalyst speciation information; and (4) time-resolved enyne metathesis reactions can be imaged, corresponding to single turnovers at individual molecular catalysts during polymer growth under synthetically relevant conditions. Here, these findings identify and characterize reactivity distributions likely arising from the dynamics of local environments. As such, these data provide reactivity information that is unavailable through traditional ensemble analytical methods that obscure this type of information through averaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TREAT neutronics analysis and design support, Part II: Multi-SERTTA-CAL

Experiment vehicle design is necessary in preparation for Transient Reactor Test (TREAT) facility restart and the resumption of transient testing to support Accident Tolerant Fuel (ATF) characterization and other future fuels testing requirements. Currently the most mature vehicle design is the Multi-SERTTA (Static Environments Rodlet Transient Test Apparatuses), which can accommodate up to four concurrent rodlet-sized specimens under separate environmental conditions. Robust test vehicle design requires neutronics analyses to support design development, optimization of the power coupling factor (PCF) to efficiently maximize energy generation in the test fuel rodlets, and experiment safety analyses. An integral aspect of prior TREAT transient testing was the incorporation of calibration experiments to experimentally evaluate and validate test conditions in preparation of the actual fuel testing. The calibration experiment package established the test parameter conditions to support fine-tuning of the computational models to deliver the required energy deposition to the fuel samples. The calibration vehicle was designed to be as near neutronically equivalent to the experiment vehicle as possible to minimize errors between the calibration and final tests. The Multi-SERTTA-CAL vehicle was designed to serve as the calibration vehicle supporting Multi-SERTTA experimentation. Models of the Multi-SERTTA-CAL vehicle containing typical PWR-fuel rodlets were prepared and neutronics calculations were performed using MCNP6.1 with ENDF/B-VII.1 nuclear data libraries; these results were then compared against those performed for Multi-SERTTA to determine the similarity and possible design modification necessary prior to construction of these experiment vehicles. The estimated reactivity insertion worth into the TREAT core is very similar between the two vehicle designs, with the primary physical difference being a hollow Inconel tube running down the length of the calibration vehicle. Calculations of PCF indicate that on average there is a reduction of approximately 6 % for PWR fuel rodlets irradiated under both wet and dry conditions. Changes to the primary or secondary vessel structure in the calibration vehicle can be performed to offset this discrepancy and maintain neutronic equivalency. Current possible modifications to the calibration vehicle include reduction of the primary vessel wall thickness, swapping Zircaloy-4 for stainless steel 316 in the secondary containment, or slight modification to the temperature and pressure of the water environment within the primary vessel. Removal of some of the instrumentation within the calibration vehicle can also serve to slightly increase the PCF. Future efforts include further modification and optimization of the Multi-SERTTA and Multi-SERTTA-CAL designs in preparation of actual TREAT transient testing. Experimental results from both test vehicles will be compared against calculational results and methods to provide validation and support additional neutronics analyses. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Bayes goes fast: Uncertainty quantification for a covariant energy density functional emulated by the reduced basis method

A covariant energy density functional is calibrated using a principled Bayesian statistical framework informed by experimental binding energies and charge radii of several magic and semi-magic nuclei. The Bayesian sampling required for the calibration is enabled by the emulation of the high-fidelity model through the implementation of a reduced basis method (RBM)—a set of dimensionality reduction techniques that can speed up demanding calculations involving partial differential equations by several orders of magnitude. The RBM emulator we build—using only 100 evaluations of the high-fidelity model—is able to accurately reproduce the model calculations in tens of milliseconds on a personal computer, an increase in speed of nearly a factor of 3,300 when compared to the original solver. Besides the analysis of the posterior distribution of parameters, we present model calculations for masses and radii with properly estimated uncertainties. We also analyze the model correlation between the slope of the symmetry energy L and the neutron skin of 48 Ca and 208 Pb. The straightforward implementation and outstanding performance of the RBM makes it an ideal tool for assisting the nuclear theory community in providing reliable estimates with properly quantified uncertainties of physical observables. Such uncertainty quantification tools will become essential given the expected abundance of data from the recently inaugurated and future experimental and observational facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Toward predictive permeabilities: Experimental measurements and multiscale simulation of methanol transport in Nafion

A polymer membrane's permeability to solutes determines its suitability for various applications: a permeability value is essential for predicting performance in diverse contexts. Using aqueous methanol permeation through Nafion as an example, we describe a methodology for determining membrane permeability that accounts for boundary layer effects and the possibility of swelling. For the materials and apparatus used herein, analysis of a permeance measurement and computational fluid dynamics simulations show that the mass transfer boundary layer is on the order of ones to tens of microns. Additionally, the data are used to develop and validate a multiscale model describing solute permeation through a hydrated membrane as a series of physical mechanistic steps: reversible adsorption from solution at the membrane interface, diffusion driven by a concentration gradient within the membrane, and reversible desorption into solution at the opposite membrane interface. The validated model is used to predict methanol transport across a solar-driven CO 2 reduction device and to assess the impact of polymer changes on the measured value. The approach of combining experimental data, computational fluid dynamics, and the mechanistic multiscale model is expected to provide more accurate analysis of membrane permeation data in cases with polymer swelling or unusual device geometries, among others.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

3D seismic imaging of a fracture damage zone controlling reservoir compartmentalization at the Raft River EGS using multi-azimuth walkaway VSP

Accurate imaging of steeply dipping fracture zones in crystalline enhanced geothermal systems (EGS) is critical for constraining permeability architecture and guiding stimulation design. However, such structures remain poorly resolved by conventional surface seismic methods. We present a fully three-dimensional (3D) elastic-waveform inversion-migration workflow applied to multi-azimuth walkaway vertical seismic profiling (VSP) data acquired in a deviated borehole at the Raft River EGS. The workflow integrates first-arrival traveltime tomography, multi-scale elastic waveform inversion (EWI), and elastic least-squares reverse-time migration (ELSRTM) to recover high-resolution compressional-and shear-wave velocity models and to image structural discontinuities in the crystalline basement. The results reveal a laterally continuous low-velocity anomaly, with shear-wave velocity reductions of 25-30%, consistent with fractureinduced mechanical weakening. Two steeply dipping discontinuities bound a 50-80 m wide fracture damage zone. Independent constraints from microseismic clustering and geochemical compartmentalization corroborate the geometry and structural significance of this feature. Synthetic modeling further confirms that structures of this scale are resolvable (~30 m). These findings indicate that the Narrows structure is a distributed fracture damage zone rather than a discrete fault plane. By resolving fracture-zone geometry at the tens-of-meters scale using a single borehole, this workflow provides a practical and transferable approach for improving structural characterization, reducing uncertainty in permeability architecture, and supporting reservoir modeling and stimulation design in fractured crystalline EGS reservoirs.

58 GEOSCIENCES↗

The relation of magnetic properties and anomalous Hall behaviors in Mn4N (200) epitaxial films

Highlights: • Ferrimagnetic Mn4N(200) were grown on MgO(100) by plasma assisted molecular beam epitaxy. • We elucidate the relation of nitrogen vacancies and the magnetism by adjusting the growth pressure. • We state the relation of longitudinal resistivity and temperature as ρ{sub xx}∝T{sup 1.9994} (T ≤ 86K) and ρ{sub xx}∝T{sup 0.3068} (T > 86K) by data fitting. • We introduce a method to estimate the Debye temperature of Mn{sub 4}N materials and the residual resistance of 0 K. • We verify the linear relation between anomalou Hall resistivity (ρ{sub AH}) and magnetization at low magnetic field. - Abstract: The Mn{sub 4}N(200) films were grown on MgO(100) substrates by molecular beam epitaxy. The saturated magnetizations are 0.735 μB/f.u. and 0.892 μB/f.u. under pressure of 7.5 × 10{sup −6} mbar–9.5 × 10{sup −6} mbar. Increasing of growth pressure enhances the magnetism of Mn{sub 4}N due to the reduction of nitrogen vacancies. Debye temperature (T{sub D}) of Mn{sub 4}N is estimated to be 86 K. The longitudinal resistivity is linear to T{sup 1.9994} when T D , which coincides with electron-electron scattering of ferromagnetic coupling. The longitudinal resistivity originates from electron-electron scattering below T{sub D} since electron-phonon scattering is frozen. The longitudinal resistivity at 0 K is about 10% lower than 5 K as 7.085 μΩ cm. Mn{sub 4}N films show obvious anomalous Hall Effect in perpendicular magnetic fields. The anomalous Hall resistivity (ρ{sub AH}) of Mn{sub 4}N film is obtained by subtracting the ordinary Hall resistivity from transverse resistivity. The ρ{sub AH} is verified to be linear to magnetization at low magnetic field strength region (0–9 KOe).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

Here, we propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. Conversely, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. Furthermore, we describe a framework in this work that paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerating Scientific Simulations with Bi-Fidelity Weighted Transfer Learning

High-fidelity modeling is an essential design tool for many engineering applications. However, for complex systems, computational cost can be a limiting factor. Analyzing parameter sensitivity, uncertainty quantification, and design optimization require many model evaluations. Surrogate models are often used to develop the relationship between model parameters and quantities of interest. However, in the case of complex systems, surrogate models require several degrees of freedom and, thus, a large number of data points to determine the correct dependencies. For many applications, this may be prohibitively expensive. The reduction of computational requirements can be achieved by leveraging low-fidelity models. Low-fidelity models represent the system at a coarser resolution with the advantage of computational efficiency. Therefore, a bi-fidelity modeling paradigm, which augments the accuracy of a low-fidelity model in a computationally efficient manner by invoking limited runs of a high-fidelity model, can be leveraged to sufficiently balance the accuracy and computational requirements. In this work, a bi-fidelity weighted transfer learning method using neural networks was applied to a computational fluid dynamics heat transfer modeling problem. The transfer learning advantage was investigated as a function of hyperparameters. Our main finding is that the use of a bi-fidelity modeling paradigm achieves accuracy close to that of a high-fidelity Gaussian process model while significantly reducing computational cost. The bi-fidelity model achieves comparable performance with 90 high-fidelity samples-that is, 60% less than the samples needed to achieve similar accuracy without the use of bi-fidelity modeling,

Borowiec, Katarzyna↗

High-Pressure Laminar Flame Speeds and Markstein Lengths of Syngas Flames Diluted in Carbon Dioxide and Helium

Abstract New laminar flame speed and burned-gas Markstein length data for H2–CO–O2–CO2–He mixtures have been measured from spherically expanding flames. Experiments were conducted at 10 atm and room temperature for H2:CO ratios ranging from 2:1 to 1:4 and for overall CO2 mole fractions from 0% to 30%. CO2 dilution had little effect on Markstein length, but CO2 dilutions of 10%, 20%, and 30% caused average reductions in flame speed of 47%, 73%, and 89%, respectively, regardless of H2:CO ratio. The study was designed to isolate the dilution effect of CO2 on flame speed, and a detailed analysis using the FCO2 method was used to show that the chemical-kinetic participation of CO2 was responsible for up to 20% of the reduction in flame speed. Hence, the majority (80% or more) of the reduction in flame speed due to CO2 is from the thermal effect. Accurate flame speed predictions were produced by five different chemical kinetics mechanisms for most conditions, with the slight exception of high-CO, high-CO2 mixtures. A thorough sensitivity analysis highlighted the larger effect of CO2 dilution on the important kinetics reactions than the effect of changing H2:CO. Sensitivity analysis also showed that the chain branching reaction H2O + O ⇌ OH + OH could be modified (albeit beyond its uncertainty) to achieve more accurate flame speed predictions, but also indicated that further improvement of flame speed modeling would require changes to many lesser reactions.

Engineering↗

Flaw Tolerance Assessment for DOE Standard SNF Dry Storage Canisters - 26550

The U.S. DOE has designed four spent nuclear fuel (SNF) dry storage canisters for storing DOE standardized SNFs. The DOE standard canisters are cylindrical shells with a diameter of 24 inches (610 m) or 18 inches (457 m), a wall thickness of 0.5 inches (12.7 m) or 0.375 inches (9.53 m), and a length of 15 feet (4.57 m) or 10 feet (3.05 m). These DOE canister geometries are completely different from commercial canisters. The latter may experience chloride-induced stress cracking corrosion (CI-SCC) because they are stored near coastal regions. The former may not experience CI-SCC but face different challenges because they are stored in the SNF storage facilities. Because of large residual stresses, mechanical flaws may occur in the DOE canisters during long-distance transportation or lifting handling. To date, only limited structural integrity analyses were carried out through drop tests on the DOE canisters, but a more general flaw tolerance assessment has not been performed. Therefore, the failure assessment diagram (FAD)-based fracture mechanics method, as codified by the latest API 579-1/ASME FFS-1-2021 Edition, is adopted in this work to assess surface flaw tolerance for DOE canisters under operation loading and welding residual stresses (WRS), where the new code-recommended WRS distributions are used. To more adequately consider the transverse distribution of WRS, an equivalent WRS distribution is proposed to account for the WRS reduction with distance from the weld centerline. Moreover, the closed-form solutions of stress intensity factor K, which serves as the crack driving force during subcritical crack growth, are developed from the tabular data of the K factors provided in API 579-1/ASME FFS-1 and used to determine more accurate flaw sizes at flaw instability. Subsequently, the Level 2 assessment procedures with 12 assessment steps, as codified and detailed in API 579-1 and ASME FFS-1, are followed to assess the flaw tolerance for the surface flaws in the DOE standard canisters with consideration of normal or accident operation loads combined with WRS. The assessment results show that the four designs of DOE standard canisters can tolerate all surface flaws that meet the code permitted maximum sizes of a flaw length of 8 inches (i.e., 200 mm) and a flaw depth of 80% wall thickness. This demonstrates that all designs of DOE standard canisters are robust and reliable.

DOE standard canister↗