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DOE OSTI2012

Theoretical investigations of the physical properties of zircon-type YVO{sub 4}

The crystal structure, electronic properties, elastic properties, hardness and thermodynamic properties of the laser host material zircon-type YVO{sub 4} are studied using the pseudopotential plane wave method within the local density approximation (LDA) and generalized gradient approximation (GGA). The calculated ground state values such as lattice parameter, bulk modulus and its pressure derivative, the band structure and densities of states were in favorable agreement with previous works and the existed experimental data. The elastic constants C{sub ij}, the aggregate elastic moduli (B, G, E), Poisson's ratio and elastic anisotropy have been investigated. In YVO{sub 4}, V-O bonds with shorter bond length and larger Mulliken population make great contribution to hardness than Y-O bonds. Using quasi-harmonic Debye model considering the phonon effects, bulk modulus, heat capacity and thermal expansion coefficient of YVO{sub 4} are calculated within a range of 0-6 GPa and 0-1200 K. - Graphical Abstract: (a) Directional dependence of Young's modulus in zircon-type YVO{sub 4} and (b) projections of the directional dependent Young's modulus in different planes for zircon-type YVO{sub 4}. The units are in GPa. Highlights: Black-Right-Pointing-Pointer This paper systematically studied the physical properties of zircon-type YVO{sub 4} from first-principles calculations. Black-Right-Pointing-Pointer Zircon-type YVO{sub 4} is mechanically stable and it is ductile for B/G>1.75 and v>0.26. Black-Right-Pointing-Pointer Universal elastic anisotropy index A{sup U} for zircon-type YVO{sub 4} is 2.41, so YVO{sub 4} is anisotropic. Black-Right-Pointing-Pointer V-O bonds with shorter bond length and larger Mulliken population make greater contribution to the hardness of YVO{sub 4}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

The LSST AGN Data Challenge: Selection Methods

Abstract Development of the Rubin Observatory Legacy Survey of Space and Time (LSST) includes a series of Data Challenges (DCs) arranged by various LSST Scientific Collaborations that are taking place during the project's preoperational phase. The AGN Science Collaboration Data Challenge (AGNSC-DC) is a partial prototype of the expected LSST data on active galactic nuclei (AGNs), aimed at validating machine learning approaches for AGN selection and characterization in large surveys like LSST. The AGNSC-DC took place in 2021, focusing on accuracy, robustness, and scalability. The training and the blinded data sets were constructed to mimic the future LSST release catalogs using the data from the Sloan Digital Sky Survey Stripe 82 region and the XMM-Newton Large Scale Structure Survey region. Data features were divided into astrometry, photometry, color, morphology, redshift, and class label with the addition of variability features and images. We present the results of four submitted solutions to DCs using both classical and machine learning methods. We systematically test the performance of supervised models (support vector machine, random forest, extreme gradient boosting, artificial neural network, convolutional neural network) and unsupervised ones (deep embedding clustering) when applied to the problem of classifying/clustering sources as stars, galaxies, or AGNs. We obtained classification accuracy of 97.5% for supervised models and clustering accuracy of 96.0% for unsupervised ones and 95.0% with a classic approach for a blinded data set. We find that variability features significantly improve the accuracy of the trained models, and correlation analysis among different bands enables a fast and inexpensive first-order selection of quasar candidates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

MO-DE-207A-09: Low-Dose CT Image Reconstruction Via Learning From Different Patient Normal-Dose Images

Purpose: To investigate a novel low-dose CT (LdCT) image reconstruction strategy for lung CT imaging in radiation therapy. Methods: The proposed approach consists of four steps: (1) use the traditional filtered back-projection (FBP) method to reconstruct the LdCT image; (2) calculate structure similarity (SSIM) index between the FBP-reconstructed LdCT image and a set of normal-dose CT (NdCT) images, and select the NdCT image with the highest SSIM as the learning source; (3) segment the NdCT source image into lung and outside tissue regions via simple thresholding, and adopt multiple linear regression to learn high-order Markov random field (MRF) pattern for each tissue region in the NdCT source image; (4) segment the FBP-reconstructed LdCT image into lung and outside regions as well, and apply the learnt MRF prior in each tissue region for statistical iterative reconstruction of the LdCT image following the penalized weighted least squares (PWLS) framework. Quantitative evaluation of the reconstructed images was based on the signal-to-noise ratio (SNR), local binary pattern (LBP) and histogram of oriented gradients (HOG) metrics. Results: It was observed that lung and outside tissue regions have different MRF patterns predicted from the NdCT. Visual inspection showed that our method obviously outperformed the traditional FBP method. Comparing with the region-smoothing PWLS method, our method has, in average, 13% increase in SNR, 15% decrease in LBP difference, and 12% decrease in HOG difference from reference standard for all regions of interest, which indicated the superior performance of the proposed method in terms of image resolution and texture preservation. Conclusion: We proposed a novel LdCT image reconstruction method by learning similar image characteristics from a set of NdCT images, and the to-be-learnt NdCT image does not need to be scans from the same subject. This approach is particularly important for enhancing image quality in radiation therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Explaining Globally Inhomogeneous Future Changes in Monsoons Using Simple Moist Energy Diagnostics

Here, this study examines the annual cycle of monsoon precipitation simulated by models from phase 6 of the Coupled Model Intercomparison Project (CMIP6), then uses moist energy diagnostics to explain globally inhomogeneous projected future changes. Rainy season characteristics are quantified using a consistent method across the globe. Model bias is shown to include rainy season onsets tens of days later than observed in some monsoon regions (India, Australia, and North America) and overly large summer precipitation in others (North America, South America, and southern Africa). Projected next-century changes include rainy season lengthening in the two largest Northern Hemisphere monsoon regions (South Asia and central Sahel) and shortening in the two largest Southern Hemisphere regions (South America and southern Africa). Changes in the North American and Australian monsoons are less coherent across models. To understand these changes, relative moist static energy (MSE) is defined as the difference between local and tropical-mean surface air MSE. Future changes in relative MSE in each region correlate well with onset and demise date changes. Furthermore, Southern Hemisphere regions projected to undergo rainy season shortening are spanned by an increasing equator-to-pole MSE gradient, suggesting their rainfall will be increasingly inhibited by fluxes of dry extratropical air; Northern Hemisphere regions with projected lengthening of rainy seasons undergo little change in equator-to-pole MSE gradient. Thus, although model biases raise questions as to the reliability of some projections, these results suggest that globally inhomogeneous future changes in monsoon timing may be understood through simple measures of surface air MSE.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1987

Laser schlieren crystal monitor

A system and method for monitoring the state of a crystal which is suspended in a solution is described which includes providing a light source for emitting a beam of light along an optical axis. A collimating lens is arranged along the optical axis for collimating the emitted beam to provide a first collimated light beam consisting of parallel light rays. By passing the first collimated light beam through a transparent container, a number of the parallel light rays are deflected off the surfaces of said crystal being monitored according to the refractive index gradient to provide a deflected beam of deflected light rays. A focusing lens is arranged along optical axis for focusing the deflected rays towards a desired focal point. A knife edge is arranged in a predetermined orientation at the focal point; and a screen is provided. A portion of the deflected beam is blocked with the knife edge to project only a portion of the deflected beam. A band is created at one edge of the image of the crystal which indicates the state of change of the surface of the crystal being monitored.

Owen, Robert B.↗

NASA NTRS1997

Constrained Multipoint Aerodynamic Shape Optimization Using an Adjoint Formulation and Parallel Computers

An aerodynamic shape optimization method that treats the design of complex aircraft configurations subject to high fidelity computational fluid dynamics (CFD), geometric constraints and multiple design points is described. The design process will be greatly accelerated through the use of both control theory and distributed memory computer architectures. Control theory is employed to derive the adjoint differential equations whose solution allows for the evaluation of design gradient information at a fraction of the computational cost required by previous design methods. The resulting problem is implemented on parallel distributed memory architectures using a domain decomposition approach, an optimized communication schedule, and the MPI (Message Passing Interface) standard for portability and efficiency. The final result achieves very rapid aerodynamic design based on a higher order CFD method. In order to facilitate the integration of these high fidelity CFD approaches into future multi-disciplinary optimization (NW) applications, new methods must be developed which are capable of simultaneously addressing complex geometries, multiple objective functions, and geometric design constraints. In our earlier studies, we coupled the adjoint based design formulations with unconstrained optimization algorithms and showed that the approach was effective for the aerodynamic design of airfoils, wings, wing-bodies, and complex aircraft configurations. In many of the results presented in these earlier works, geometric constraints were satisfied either by a projection into feasible space or by posing the design space parameterization such that it automatically satisfied constraints. Furthermore, with the exception of reference 9 where the second author initially explored the use of multipoint design in conjunction with adjoint formulations, our earlier works have focused on single point design efforts. Here we demonstrate that the same methodology may be extended to treat complete configuration designs subject to multiple design points and geometric constraints. Examples are presented for both transonic and supersonic configurations ranging from wing alone designs to complex configuration designs involving wing, fuselage, nacelles and pylons.

Reuther, James↗

DOE OSTI2026

Boride-based Ceramic Super-high Temperature Thermocouples in Harsh Environments (Final Scientific/Technical Report)

An electromotive force (emf) can be generated along a temperature gradient between the cold end and hot end of a thermoelectric material, termed the Seebeck effect. Based on the Seebeck effect, metallic alloys have been extensively employed to detect temperatures for centuries, named thermocouples. However, commercially available thermocouple alloys suffer from limitations, such as oxidation, chemical degradation, and poor long-term stability under high-temperature harsh environments. This DOE-funded project aimed to develop high-temperature, chemically tolerant thermocouples suitable for operation in extreme environments relevant to semiconducting thermoelectric materials. The research focused on boride-based semiconducting thermoelectric compounds as candidates for next-generation thermocouples with enhanced oxidation resistance, chemical stability, and thermal robustness under conditions representative of charcoal-fired electricity facilities. During the funded years, boride materials were synthesized using an arc-plasma technique under ambient air and argon atmospheres, enabling scalable and cost-effective production compared with conventional boride fabrication methods. The synthesized borides were processed into nanostructured powders, followed by consolidation into dense bulk materials using a spark plasma sintering (SPS) bottom-up approach. Comprehensive characterization was performed, including microstructural analysis, electrical transport measurements, and optical and thermal property evaluation. Both p-type and n-type boride electric legs were fabricated and integrated into boride-based thermocouples. The thermal and irradiation stabilities of the boride nanomaterials and bulk thermoelectric materials were systematically evaluated to assess suitability for long-term operation in harsh environments. Additionally, 12 students were broadly hands-on trained spanning the full research workflow, including word processing and technical editing (e.g., LATEX for manuscript and poster preparation), data collection and analysis (using Python and related libraries and hardware interfaces), sample preparation (including arc-plasma synthesis and spark plasma sintering), and advanced characterization techniques (such as X-ray diffraction, UV–vis spectroscopy, electron microscopy, differential thermal analysis (DTA), and Seebeck coefficient measurements, etc). Overall, this project demonstrated the feasibility of boride-based thermoelectric materials as durable high-temperature thermocouples, providing a promising pathway toward robust temperature sensing technologies aligned with DOE energy infrastructure and extreme-environment monitoring needs.

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS1990

Research on diabatic initialization

The objective of this research project is to contribute to improvement in the synoptic analyses in the tropics for numerical weather prediction and climate research. In addition to a prediction model, four dimensional data assimilation systems have two principal components. One is objective analysis and the other is initialization. Various methods of objective analysis are designed primarily to analyze the mass and rotational wind fields. Methods of initialization are developed to obtain the irrotational wind and its associated vertical velocity field which are balanced with the mass field and free from meteorological noise. There are essentially three approaches to the problem of initialization: quasi-geostrophic theory, bounded derivative method and nonlinear normal mode method. In the midlatitudes, these approaches generally produce satisfactory results even without diabatic effects for large-scale motions. In the tropics, the situation is quite different from that in the midlatitudes. Because of a small magnitude of the Coriolis parameter and a weak horizontal temperature gradient in the tropics, any method of initialization must incorporate diabatic effects. In fact, it can be said that understanding the problem of diabatic initialization is the key to improving the analysis and weather forecasting in the tropics.

Kasahara, Akira↗

NASA NTRS1996

Cascade Error Projection: A Learning Algorithm for Hardware Implementation

In this paper, we workout a detailed mathematical analysis for a new learning algorithm termed Cascade Error Projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters. Furthermore, CEP learning algorithm is operated only on one layer, whereas the other set of weights can be calculated deterministically. In association with the dynamical stepsize change concept to convert the weight update from infinite space into a finite space, the relation between the current stepsize and the previous energy level is also given and the estimation procedure for optimal stepsize is used for validation of our proposed technique. The weight values of zero are used for starting the learning for every layer, and a single hidden unit is applied instead of using a pool of candidate hidden units similar to cascade correlation scheme. Therefore, simplicity in hardware implementation is also obtained. Furthermore, this analysis allows us to select from other methods (such as the conjugate gradient descent or the Newton's second order) one of which will be a good candidate for the learning technique. The choice of learning technique depends on the constraints of the problem (e.g., speed, performance, and hardware implementation); one technique may be more suitable than others. Moreover, for a discrete weight space, the theoretical analysis presents the capability of learning with limited weight quantization. Finally, 5- to 8-bit parity and chaotic time series prediction problems are investigated; the simulation results demonstrate that 4-bit or more weight quantization is sufficient for learning neural network using CEP. In addition, it is demonstrated that this technique is able to compensate for less bit weight resolution by incorporating additional hidden units. However, generation result may suffer somewhat with lower bit weight quantization.

Duong, Tuan A.↗

DOE OSTI2013

Hydrogeologic Modeling at the Sylvania Corning FUSRAP Site - 13419

A comparative groundwater hydrogeologic modeling analysis is presented herein to simulate potential contaminant migration pathways in a sole source aquifer in Nassau County, Long Island, New York. The source of contamination is related to historical operations at the Sylvania Corning Plant ('Site'), a 9.49- acre facility located at 70, 100 and 140 Cantiague Rock Road, Town of Oyster Bay in the westernmost portion of Hicksville, Long Island. The Site had historically been utilized as a nuclear materials manufacturing facility (e.g., cores, slug, and fuel elements) for reactors used in both research and electric power generation in early 1950's until late 1960's. The Site is contaminated with various volatile organic and inorganic compounds, as well as radionuclides. The major contaminants of concern at the Site are tetrachloroethene (PCE), trichloroethene (TCE), nickel, uranium, and thorium. These compounds are present in soil and groundwater underlying the Site and have migrated off-site. The Site is currently being investigated as part of the Formerly Utilized Sites Remedial Action Program (FUSRAP). The main objective of the current study is to simulate the complex hydrogeologic features in the region, such as numerous current and historic production well fields; large, localized recharge basins; and, multiple aquifers, and to assess potential contaminant migration pathways originating from the Site. For this purpose, the focus of attention was given to the underlying Magothy formation, which has been impacted by the contaminants of concern. This aquifer provides more than 90% of potable water supply in the region. Nassau and Suffolk Counties jointly developed a three-dimensional regional groundwater flow model to help understand the factors affecting groundwater flow regime in the region, to determine adequate water supply for public consumption, to investigate salt water intrusion in localized areas, to evaluate the impacts of regional pumping activity, and to better understand the contaminant transport and fate mechanisms through the underlying aquifers. This regional model, developed for the N.Y. State Department of Environmental Conservation (NYSDEC) by Camp Dresser and McKee (CDM), uses the finite element model DYNFLOW developed by CDM, Cambridge, Massachusetts. The coarseness of the regional model, however, could not adequately capture the hydrogeologic heterogeneity of the aquifer. Specifically, the regional model did not adequately capture the interbedded nature of the Magothy aquifer and, as such, simulated particles tended to track down-gradient from the Site in relatively straight lines while the movement of groundwater in such a heterogeneous aquifer is expected to proceed along a more tortuous path. This paper presents a qualitative comparison of site-specific groundwater flow modeling results with results obtained from the regional model. In order to assess the potential contaminant migration pathways, a particle tracking method was employed. Available site-specific and regional hydraulic conductivity data measured in-situ with respect to depth and location were incorporated into the T-PROG module in GMS model to define statistical variation to better represent the actual stratigraphy and layer heterogeneity. The groundwater flow characteristics in the Magothy aquifer were simulated with the stochastic hydraulic conductivity variation as opposed to constant values as employed in the regional model. Contaminant sources and their exact locations have been fully delineated at the Site during the Remedial Investigation (RI) phase of the project. Contaminant migration pathways originating from these source locations at the Site are qualitatively traced within the sole source aquifer utilizing particles introduced at source locations. Contaminant transport mechanism modeled in the current study is based on pure advection (i.e., plug flow) and mechanical dispersion while molecular diffusion effects are neglected due to relatively high groundwater velocities encountered in the aquifer. In addition, fate of contaminants is ignored hereby to simulate the worst-case scenario, which considers the contaminants of concern as tracer-like compounds for modeling purposes. The results of the modeling analysis are qualitatively compared with the County's regional model, and patterns of contaminant migration in the region are presented. (authors)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Projecting Permafrost Thaw of Sub-Arctic Tundra With a Thermodynamic Model Calibrated to Site Measurements

Northern circumpolar permafrost thaw affects global carbon cycling, as large amounts of stored soil carbon becomes accessible to microbial breakdown under a warming climate. The magnitude of carbon release is linked to the extent of permafrost thaw, which is locally variable and controlled by soil thermodynamics. Soil thermodynamic properties, such as thermal diffusivity, govern the reactivity of the soil-atmosphere thermal gradient, and are controlled by soil composition and drainage. In order to project permafrost thaw for an Alaskan tundra experimental site, we used seven years of site data to calibrate a soil thermodynamic model using a data assimilation technique. The model reproduced seasonal and interannual temperature dynamics for shallow (5–40 cm) and deep soil layers (2–4 m), and simulations of seasonal thaw depth closely matched observed data. The model was then used to project permafrost thaw at the site to the year 2100 using climate forcing data for three future climate scenarios (RCP 4.5, 6.0, and 8.5). Minimal permafrost thawing occurred until mean annual air temperatures rose above the freezing point, after which we measured over a 1 m increase in thaw depth for every 1 °C rise in mean annual air temperature. Under no projected warming scenario was permafrost remaining in the upper 3 m of soil by 2100. We demonstrated an effective data assimilation method that optimizes parameterization of a soil thermodynamic model. The sensitivity of local permafrost to climate warming illustrates the vulnerability of sub-Arctic tundra ecosystems to significant and rapid soil thawing.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2012

STANDARDIZATION OF CEBAF 12 GEV UPGRADE CAVITY TESTING

CEBAF 12GeV upgrade project includes 80 new 7-cell cavities to form 10 cryomodules. Each cavity underwent RF qualification at 2.07K using a high power accelerating gradient test and an HOM survey in Jefferson Lab's Vertical Testing Area (VTA) before cavity string assembly. In order to ensure consistently high quality data, updated cavity testing procedures and analysis were implemented and used by a group of VTA operators. For high power tests, a cavity testing procedure was developed and used in conjunction with a LabVIEW program to collect the test data. Additionally while the cavity was at 2.07K, an HOM survey was performed using a network analyzer and a combination of Excel and Mathematica programs. Data analysis was standardized and an online logbook, Pansophy, was used for data storage and mining. The Pansophy system allowed test results to be easily summarized and searchable across all cavity tests. In this presentation, the CEBAF 12GeV upgrade cavity testing procedure, method for data analysis, and results reporting results will be discussed.

43 PARTICLE ACCELERATORS↗

DOE OSTI2012

Creating NDA working standards through high-fidelity spent fuel modeling

The Next Generation Safeguards Initiative (NGSI) is developing advanced non-destructive assay (NDA) techniques for spent nuclear fuel assemblies to advance the state-of-the-art in safeguards measurements. These measurements aim beyond the capabilities of existing methods to include the evaluation of plutonium and fissile material inventory, independent of operator declarations. Testing and evaluation of advanced NDA performance will require reference assemblies with well-characterized compositions to serve as working standards against which the NDA methods can be benchmarked and for uncertainty quantification. To support the development of standards for the NGSI spent fuel NDA project, high-fidelity modeling of irradiated fuel assemblies is being performed to characterize fuel compositions and radiation emission data. The assembly depletion simulations apply detailed operating history information and core simulation data as it is available to perform high fidelity axial and pin-by-pin fuel characterization for more than 1600 nuclides. The resulting pin-by-pin isotopic inventories are used to optimize the NDA measurements and provide information necessary to unfold and interpret the measurement data, e.g., passive gamma emitters, neutron emitters, neutron absorbers, and fissile content. A key requirement of this study is the analysis of uncertainties associated with the calculated compositions and signatures for the standard assemblies; uncertainties introduced by the calculation methods, nuclear data, and operating information. An integral part of this assessment involves the application of experimental data from destructive radiochemical assay to assess the uncertainty and bias in computed inventories, the impact of parameters such as assembly burnup gradients and burnable poisons, and the influence of neighboring assemblies on periphery rods. This paper will present the results of high fidelity assembly depletion modeling and uncertainty analysis from independent calculations performed using SCALE and MCNP. This work is supported by the Next Generation Safeguards Initiative, Office of Nuclear Safeguards and Security, National Nuclear Security Administration.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

Final Report for Project 13-4791: New Mechanistic Models of Creep-Fatigue Crack Growth Interactions for Advanced High Temperature Reactor Components

This project developed and validated a novel, multi-scale, mechanism-based model to quantitatively predict creep-fatigue crack growth and failure for Ni-based Alloy 617 at 800°C. Alloy 617 is a target material for intermediate heat exchangers in Generation IV very high temperature reactor designs, and it is envisioned that this model will aid in the design of safe, long lasting nuclear power plants. The technical effectiveness of the model was shown by demonstrating that experimentally observed crack growth rates can be predicted under both steady state and overload crack growth conditions. Feasibility was considered by incorporating our model into a commercially available finite element method code, ABAQUS, that is commonly used by design engineers. While the focus of the project was specifically on an alloy targeted for Generation IV nuclear reactors, the benefits to the public are expected to be wide reaching. Indeed, creep-fatigue failure is a design consideration for a wide range of high temperature mechanical systems that rely on Ni-based alloys, including industrial gas power turbines, advanced ultra-super critical steam turbines, and aerospace turbine engines. It is envisioned that this new model can be adapted to a wide range of engineering applications.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Integral Reactor Containment Condensation Model and Experimental Validation

This NEUP funded project, NEUP 12-3630, is for experimental, numerical and analytical studies on high-pressure steam condensation phenomena in a steel containment vessel connected to a water cooling tank, carried out at Oregon State University (OrSU) and the University of Wisconsin at Madison (UW-Madison). In the three years of investigation duration, following the original proposal, the planned tasks have been completed: (1) Performed a scaling study for the full pressure test facility applicable to the reference design for the condensation heat transfer process during design basis accidents (DBAs), modified the existing test facility to route the steady-state secondary steam flow into the high pressure containment for controllable condensation tests, and extended the operations at negative gage pressure conditions (OrSU). (2) Conducted a series of DBA and quasi-steady experiments using the full pressure test facility to provide a reliable high pressure condensation database (OrSU). (3) Analyzed experimental data and evaluated condensation model for the experimental conditions, and predicted the prototypic containment performance under accidental conditions (UW-Madison). A film flow model was developed for the scaling analysis, and the results suggest that the 1/3 scaled test facility covers large portion of laminar film flow, leading to a lower average heat transfer coefficient comparing to the prototypic value. Although it is conservative in reactor safety analysis, the significant reduction of heat transfer coefficient (50%) could under estimate the prototypic condensation heat transfer rate, resulting in inaccurate prediction of the decay heat removal capability. Further investigation is thus needed to quantify the scaling distortion for safety analysis code validation. Experimental investigations were performed in the existing MASLWR test facility at OrST with minor modifications. A total of 13 containment condensation tests were conducted for pressure ranging from 4 to 21 bar with three different static inventories of non-condensable gas. Condensation and heat transfer rates were evaluated employing several methods, notably from measured temperature gradients in the HTP as well as measured condensate formation rates. A detailed mass and energy accounting was used to assess the various measurement methods and to support simplifying assumptions required for the analysis. Condensation heat fluxes and heat transfer coefficients are calculated and presented as a function of pressure to satisfy the objectives of this investigation. The major conclusions for those tests are summarized below: (1) In the steam blow-down tests, the initial condensation heat transfer process involves the heating-up of the containment heat transfer plate. An inverse heat conduction model was developed to capture the rapid transient transfer characteristics, and the analysis method is applicable to SMR safety analysis. (2) The average condensation heat transfer coefficients for different pressure conditions and non-condensable gas mass fractions were obtained from the integral test facility, through the measurements of the heat conduction rate across the containment heat transfer plate, and from the water condensation rates measurement based on the total energy balance equation. 15 (3) The test results using the measured HTP wall temperatures are considerably lower than popular condensation models would predict mainly due to the side wall conduction effects in the existing MASLWR integral test facility. The data revealed the detailed heat transfer characteristics of the model containment, important to the SMR safety analysis and the validation of associated evaluation model. However this approach, unlike separate effect tests, cannot isolate the condensation heat transfer coefficient over the containment wall, and therefore is not suitable for the assessment of the condensation heat transfer coefficient against system pressure and noncondensable gas mass fraction. (4) The average condensation heat transfer coefficients measured from the water condensation rates through energy balance analysis are appropriate, however, with considerable uncertainties due to the heat loss and temperature distribution on the containment wall. With the consideration of the side wall conduction effects, the results indicate that the measured heat transfer coefficients in the tests is about 20% lower than the prediction of Dehbi’s correlation, mainly due to the side wall conduction effects. The investigation also indicates an increase in the condensation heat transfer coefficient at high containment pressure conditions, but the uncertainties invoked with this method appear to be substantial. (5) Non-condensable gas in the tests has little effects on the condensation heat transfer at high elevation measurement ports. It does affect the bottom measurements near the water level position. The results suggest that the heavier non-condensable gas is accumulated in the lower portion of the containment due to stratification in the narrow containment space. The overall effects of the non-condensable gas on the heat transfer process should thus be negligible for tall containments of narrow condensation spaces in most SMR designs. Therefore, the previous correlations with noncondensable gas effects are not appropriate to those small SMR containments due to the very poor mixing of steam and non-condensable gas. The MELCOR simulation results agree with the experimental data reasonably well. However, it is observed that the MELCOR overpredicts the heat flux for all analyzed tests. The MELCOR predicts that the heat fluxes for CCT’s approximately range from 30 to 45 kW/m2 whereas the experimental data (averaged) ranges from about 25 to 40 kW/m2. This may be due to the limited availability of liquid film models included in MELCOR. Also, it is believed that due to complex test geometry, measured temperature gradients across the heat transfer plate may have been underestimated and thus the heat flux had been underestimated. The MELCOR model predicts a film thickness on the order of 100 microns, which agrees very well with film flow model developed in this study for scaling analysis. However, the expected differences in film thicknesses for near vacuum and near atmospheric test conditions are not significant. Further study on the behavior of condensate film is expected to refine the simulation results. Possible refinements include but are not limited to, the followings: CFD simulation focusing on the liquid film behavior and benchmarking with experimental analyses for simpler geometries. 16 1 INTRODUCTION This NEUP funded project, NEUP 12-3630, is for experimental, numerical and analytical studies on high-pressure steam condensation phenomena in a steel containment vessel connected to a water cooling tank, carried out at Oregon State University (OrSU) and the University of Wisconsin at Madison (UW-Madison). The experimental results are employed to validate the containment condensation model in reactor containment system safety analysis code for integral SMRs. Such a containment condensation model is important to demonstrate the adequate cooling. In the three years of investigation, following the original proposal, the following planned tasks have been completed: (1) Performed a scaling study for the full pressure test facility applicable to the reference design for the condensation heat transfer process during design basis accidents (DBAs), modified the existing test facility to route the steady-state secondary steam flow into the high pressure containment for controllable condensation tests, and extended the operations at negative gage pressure conditions (OrSU). (2) Conducted a series of DBA and quasi-steady experiments using the full pressure test facility to provide a reliable high pressure condensation database (OrSU). (3) Analyzed experimental data and evaluated condensation model for the experimental conditions, and predicted the prototypic containment performance under accidental conditions (UW-Madison). The results are applicable to integral Small Modular Reactor (SMR) designs, including NuScale, mPower, Westinghouse SMR, Holtec-160 and other integral reactors with small containments of relatively high pressures under accidental conditions. Testing has been conducted at the OrSU laboratory in the existing MASLWR (Multi-Application Small Light Water Reactor) integral test facility sponsored by the US Department of Energy. Its highpressure stainless steel containment model (~2 MPa) is scaled to the NuScale SMR currently under development at NuScale Power, Inc.. Minor modifications to the model containment have been made to control the non-condensable gas fraction and to utilize the secondary loop stable steam flow for condensation testing. UW-Madison has developed a containment condensation model, which leveraged previous validated containment heat transfer work carried out at UW-Madison, and extended the range of applicability of the model to integral SMR designs that utilize containment vessels of high heat transfer efficiencies. In this final report, the research background and literature survey are presented in Chapter 2 and 3, respectively. The test facility description and modifications are summarized in Chapter 4, and the scaling analysis is introduced in Chapter 5. The tests description, procedures, and data analysis are presented in Chapter 6, while the numerical modeling is presented in Chapter 7, followed by a conclusion section in Chapter 8.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Accuracy of predictions made by machine learned models for biocrude yields obtained from hydrothermal liquefaction of organic wastes

Hydrothermal liquefaction (HTL) has potential for converting abundant wet organic wastes into renewable fuels. Because HTL consists of a complex reaction network, deterministic, physics-based prediction of its biocrude yield is prohibitively difficult. Data-driven methods provide an alternative to the physics-based approach; however, rigorous testing must be performed to ensure the accuracy of predictions made by data-driven methods. To this end, a data set was assembled consisting of 570 data points appearing in the open literature. The data set was divided into training, validation, and test sub-sets and used for evaluating different machine learning regression approaches to predict biocrude yield. Among the tested algorithms, Random Forest and eXtreme Gradient Boosting (XGBoost) predicted biocrude yields in a test set that had not been used for training with the greatest accuracy, with root mean square errors (RMSE) of 8.34 and 8.57, respectively. Further refinement of the Random Forest model reduced its RMSE to 8.07. In comparison, predictions of a series of literature models resulted in RMSE ranging from 9.16 in the most accurate case to 27.6 in the least accurate; most literature models yielded RMSE values > 10. Using biocrude yield predictions from the most accurate Random Forest model and a probabilistic economic analysis found that the model accuracy is sufficient to prioritize allocation of resources based on projected minimum fuel selling price. In our report the models and analysis represent a major advance in the ability to use readily available data to predict biocrude yields on new feedstocks that have not previously been studied.

42 ENGINEERING↗

DOE OSTI2019

Pathways to Carbon Liberation: A Systems Approach to Understanding Carbon Transformations and Losses from Thawing Permafrost

Our objective in this project was to discover how microbial communities mediate the fate of carbon in thawing permafrost under climate change. We proposed a systems approach integrating (a) molecular microbial and viral ecology, (b) molecular organic chemistry and stable and radiocarbon isotopes, and (c) state-of-the-art modeling, along a chronosequence of permafrost thaw in subarctic Sweden. The fate of carbon (C) in thawing permafrost is an outstanding challenge of modern biogeochemistry and climate change. Permafrost C pools are large (~1700 PgC), and C dynamics of thawing permafrost complex: old C decomposes as it is liberated from thawing permafrost as CO 2 or CH 4 , with a significant fraction cycling through lake sediments, even as new C accumulates due to thaw-initiated ecological succession. Our work is allowing better prediction of the net effect of these processes. Microbes mediate C dynamics in thawing permafrost, but a mechanistic understanding of how to scale microbial population dynamics, genomic potential, and expression to ecosystem-scale processes has been missing. A key question was: What is the interplay of microbial communities and organic matter chemical structure in the decomposition/preservation of organic C across a thaw gradient? And intriguingly, what (if any) is the role of phage (viruses that infect prokaryotic cells) in mediating these processes? Viruses appear to play a large role in driving oceanic function, but these phenomena are virtually unstudied in terrestrial systems. This endeavor linking microbial and viral dynamics, organic geochemistry and trace gas production will improve models of C cycling in permafrost systems, and clarify the fate of C under future climates. Technical Approach – We conducted a study at Stordalen Mire, Sweden, along a permafrost thaw chronosequence encompassing permafrost palsas and their initial collapse stage, thawing bog sites (dominated by Sphagnum moss), fully-thawed and inundated fen sites (dominated by Eriophorum spp or Carex spp.), and lakes. Our project used cutting edge technologies in both biogeochemistry and molecular microbial ecology to advance systems biology research on microbial carbon cycling through: (a) systems-level mapping of chemical states and ages of organic matter (via FT-ICR-MS and 14 C analysis) along thaw gradients to associated microbial communities, biochemical potentials, and activities (via meta-genomics, -transcriptomics, –proteomics, and viral genomics), and to CO 2 and CH 4 fluxes; (b) experimental incubations using Quantum Dot Probing, to test key hypotheses, arising from (a), about particular microbially-driven biochemical degradation pathways; (c) bioinformatics designed to simultaneously enhance the DOE Knowledgebase, and (d) integrated ecosystem C-cycle modeling testable by soil organic chemical and microbial data. Results from this project spanned 4 categories: (i) integrative across disciplines, and disciplinarily-focused in (ii) microbiology, (iii) biogeochemistry, and (iv) modeling. In integrated understanding of the system, we answered the questions posed above, mapping resident microbes to carbon transformations to reveal a carbon-processing shift with permafrost thaw, and discovering abundant, diverse and habitat-specific viruses that appear to be impacting carbon cycling, while also relating microbial communities to modeled processes. In microbiology-specific papers, we dug into viromes, microbial community networks, and informatic methods, while also introducing a new permafrost-associated phylum and its ecogenomic context. Relevance to DOE FOA - With a focus on discovering how microbial communities mediate the fate of old and new carbon in permafrost systems with climate change, our work directly responds to the call for “–omics driven basic research on the contribution of... microbial communities to C cycling processes in terrestrial ecosystems.” We bridge all three of the focal areas of the call, including (i) “Systems biology studies”, and development of –omics approaches (ii) “to investigate microbial community functional processes”, and (iii) “for imaging and analysis of microbially-mediated carbon cycling.”

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗