A Refined Zero‐Buoyancy Plume Model for Large‐Scale Atmospheric Profiles and Anvil Clouds in Radiative‐Convective Equilibrium
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Digital image segmentation is provided. The method comprises training a neural network for image segmentation with a labeled training dataset from a first domain, wherein a subset of nodes in the neural net are dropped out during training. The neural network receives image data from a second, different domain. A vector of N values that sum to 1 is calculated for each image element, wherein each value represents an image segmentation class. A label is assigned to each image element according to the class with the highest value in the vector. Multiple inferences are performed with active dropout layers for each image element, and an uncertainty value is generated for each image element. Uncertainty is resolved according to expected characteristics. The label of any image element with an uncertainty above a threshold is replaced with a new label corresponding to a segmentation class based on domain knowledge.
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U.S. industry is expected to deploy tristructural isotropic (TRISO) particle fuel technologies for commercial reactors within the next decade. In our previous work, we defined a preliminary transient design space for TRISO fuels, identified potential gaps in the available data, and began to develop multiphysics modeling tools that could be applied to design targeted Transient Reactor Test Facility (TREAT) experiments to fill these gaps. This work builds on that foundation by (1) updating BISON fuel performance and Griffin reactor physics models to reflect the current TREAT experiment tube and capsule designs,(2) coupling the codes to improve the accuracy and usability of the transient design analyses, and (3) demonstrating their use over an expanded design space that includes fuel burnup. The simulated mechanical responses of the TRISO particles were complex functions of fission product accumulation, fission gas release, and irradiation-induced dimensional change in the pyrolytic carbon layers. Predicted tangential stresses in particle silicon carbide layers were least compressive for preheated tests involving fresh fuels but remained compressive throughout the ranges of temperature, heat rate, and burnup considered in this work. Finally, comparisons between the potential TREAT transients and historical test reactor irradiations showed that the TREAT tests would produce significantly lower average energy deposition rates, yielding less severe transients with greater relevance to near-term commercial applications. Use of these predictive capabilities has the potential to increase the value of each test, improving the overall efficiency and cost effectiveness of transient testing for TRISO and other advanced fuels.
This is the four-page proceedings paper for the ANS IHLRWM conference planned in Nov. 2025.
The Hofmann stability chart is used to screen working points in space-charge-dominated linacs. We identify two errors in its published higher-order dispersion relations: missing $(1\mp2\hatη^2/α)$ factors in the third-order $S^4$ coupling residues, and a sign error in the stated isotropic reduction of the fourth-order relation. Both corrections follow from Hofmann's Vlasov-Poisson equations without fitted parameters. They reproduce coherent tune-shift coefficients in the author's later monograph that the printed forms miss by 24% and 127%. Mode-resolved figures from a published application agree with the corrected relations and reject the printed forms, indicating an inconsistency between the 1998 equations and the calculations underlying those tested figures. We quantify the effect on the non-oscillatory stability chart. Inside the adopted $S^2\le10$ comparison domain, printed and corrected forms disagree on 0.73-2.11% of cells, with no preferred direction. Among excluded cells, disagreement reaches 22%, and the printed relation over-predicts instability at every sampled anisotropy. This concentration may help explain why the errors persisted, although it does not establish their historical cause. For PIP-II, the corrected chart flags four of thirty-two evaluable periods, including one on a third-order odd branch missed by a second-order screen. This count covers non-oscillatory modes only and remains conditional on an unresolved factor-five disagreement between two codes on transverse emittance growth.
This document is intended to serve as an installation, usage, and basic theory guide for the two dimensional triangulation software 'HARLEY' written for the Silicon Graphics IRIS workstation. This code consists of an incremental triangulation algorithm based on point insertion and local edge swapping. Using this basic strategy, several types of triangulations can be produced depending on user selected options. For example, local edge swapping criteria can be chosen which minimizes the maximum interior angle (a MinMax triangulation) or which maximizes the minimum interior angle (a MaxMin or Delaunay triangulation). It should be noted that the MinMax triangulation is generally only locally optical (not globally optimal) in this measure. The MaxMin triangulation, however, is both locally and globally optical. In addition, Steiner triangulations can be constructed by inserting new sites at triangle circumcenters followed by edge swapping based on the MaxMin criteria. Incremental insertion of sites also provides flexibility in choosing cell refinement criteria. A dynamic heap structure has been implemented in the code so that once a refinement measure is specified (i.e., maximum aspect ratio or some measure of a solution gradient for the solution adaptive grid generation) the cell with the largest value of this measure is continually removed from the top of the heap and refined. The heap refinement strategy allows the user to specify either the number of cells desired or refine the mesh until all cell refinement measures satisfy a user specified tolerance level. Since the dynamic heap structure is constantly updated, the algorithm always refines the particular cell in the mesh with the largest refinement criteria value. The code allows the user to: triangulate a cloud of prespecified points (sites), triangulate a set of prespecified interior points constrained by prespecified boundary curve(s), Steiner triangulate the interior/exterior of prespecified boundary curve(s), refine existing triangulations based on solution error measures, and partition meshes based on the Cuthill-McKee, spectral, and coordinate bisection strategies.
We review the Best Theory + Reliable High-resolution Experiment (BTRHE) strategy for obtaining highly accurate molecular rovibrational line lists with InfraRed (IR) intensities. The need for highly accurate molecular rovibrational line lists is two-fold: a) assignment of the many rovibrational lines for common stable molecules especially those that exhibit a large amplitude motion, such as NH3, or have a high density of states such as SO2; and b) characterization of the atmospheres of exoplanets which will be one of the main areas of research in astronomy in the coming decades. The first motivation arises due to the need to eliminate lines due to common molecules in an astronomical observation in order to identify lines from new molecules, while the second motivation arises due to the need to obtain accurate molecular opacities in order to characterize the atmosphere of an exoplanet. The BTRHE strategy first consists of using high quality ab initio quantum chemical methods to obtain a global potential energy surface (PES) and dipole moment surface (DMS) that contains the proper physics. The global PES is then refined using a subset of the reliable high-resolution experimental data. The refined PES then gives energy level predictions to an accuracy similar to the reproduction accuracy of the experimental data used in the refinement step in the interpolation region (i.e., within the range of the experimental data used in the refinement step). The accuracy of the energy levels will slowly degrade as they are extrapolated to spectral regions beyond the high-resolution experimental data used in the refinement step. However, because the degradation is slow, the predicted energy levels can be used to assign new high-resolution experiments, and the data from these can then be used in a subsequent refinement step. In this way, the global PES eventually can yield highly accurate energy levels for all desired spectral regions including to very high energies and high J values. We show that IR intensities computed with the BTRHE rovibrational wavefunctions and the DMS can be very accurate provided one has minimized the fitting error of the DMS and tested the completeness of the DMS. Some examples of our work on NH3, CO2, and SO2 are given to highlight the usefulness of the BTRHE strategy and to provide ideas on how to further improve its predictive power in the future. In particular, it is shown how successive refinement steps, once new high-resolution data is available, can lead to PESs that yield highly accurate transition energies to larger spectral regions. The importance of including non-adiabatic corrections to reduce the J-dependence of errors for H-containing molecules is shown with work on NH3. Another very important aspect of the BTRHE approach is the consistency across isotopologues, which allows for highly accurate line lists for any isotopologue once one is obtained for the main isotopologue (which has more high-resolution data available for refinement).
A procedure for solving the conical Euler equations on an adaptively refined mesh is presented, along with a method for determining which cells to refine. The solution procedure is a central-difference cell-vertex scheme. The adaptation procedure is made up of a parameter on which the refinement decision is based, and a method for choosing a threshold value of the parameter. The refinement parameter is a measure of mesh-convergence, constructed by comparison of locally coarse- and fine-grid solutions. The threshold for the refinement parameter is based on the curvature of the curve relating the number of cells flagged for refinement to the value of the refinement threshold. Results for three test cases are presented. The test problem is that of a delta wing at angle of attack in a supersonic free-stream. The resulting vortices and shocks are captured efficiently by the adaptive code.
Modeling procedures which predict accurately the postbuckling response of composite panels with skewed stiffeners are presented. A particular experimental program is considered and detailed finite element models are created to represent the conditions in the experiment. First, a simple baseline model with minimal detail is defined. Then, a number of modeling refinements that improve the accuracy of the model are identified. These refinements are applied individually to the baseline model to assess the effect of each refinement on the predicted response. The individual refinements are then combined to create an advanced finite element model. In addition to model refinements which affect the overall panel response, a modeling procedure for simulating nonuniform initial load introduction that is specific to an particular experiment is described and demonstrated. By implementing a number of modeling refinements, a finite element model is developed which improves the correlation between the measured and predicted responses. The skewed stiffener detail and anisotropic skin in the selected problem create axial-shear stiffness coupling which makes this problem sensitive to the constraint on the shear displacement. The remainder of the modeling refinements considered are applicable to general structural configurations. The results presented may be used to guide future efforts to improve correlation between predicted and measured responses for post buckled stiffened panels.
This paper presents a computational framework for uncertainty characterization and propagation, and sensitivity analysis under the presence of aleatory and epistemic un- certainty, and develops a rigorous methodology for efficient refinement of epistemic un- certainty by identifying important epistemic variables that significantly affect the overall performance of an engineering system. The proposed methodology is illustrated using the NASA Langley Uncertainty Quantification Challenge (NASA-LUQC) problem that deals with uncertainty analysis of a generic transport model (GTM). First, Bayesian inference is used to infer subsystem-level epistemic quantities using the subsystem-level model and corresponding data. Second, tools of variance-based global sensitivity analysis are used to identify four important epistemic variables (this limitation specified in the NASA-LUQC is reflective of practical engineering situations where not all epistemic variables can be refined due to time/budget constraints) that significantly affect system-level performance. The most significant contribution of this paper is the development of the sequential refine- ment methodology, where epistemic variables for refinement are not identified all-at-once. Instead, only one variable is first identified, and then, Bayesian inference and global sensi- tivity calculations are repeated to identify the next important variable. This procedure is continued until all 4 variables are identified and the refinement in the system-level perfor- mance is computed. The advantages of the proposed sequential refinement methodology over the all-at-once uncertainty refinement approach are explained, and then applied to the NASA Langley Uncertainty Quantification Challenge problem.
Here, this paper presents for the first time an adaptive immersed approach for level-set topology optimization using higher-order truncated hierarchical B-spline discretizations for design and state variable fields. Boundaries and interfaces are represented implicitly by the iso-contour of one or multiple level-set functions. An immersed finite element method, the eXtended IsoGeometric Analysis, is used to predict the physical response. The proposed optimization framework affords different adaptively refined higher-order B-spline discretizations for individual design and state variable fields. The increased continuity of higher-order B-spline discretizations together with local refinement enables direct control over the accuracy of the representation of each field while simultaneously reducing computational cost compared to uniformly refined discretizations. A flexible mesh adaptation strategy enables local refinement based on geometric measures or physics-based error indicators. These adaptive discretization and analysis approaches are integrated into gradient-based optimization schemes, evaluating the design sensitivities using the adjoint method. Numerical studies illustrate the features of the proposed framework with static, linear elastic, multi-material, two- and three-dimensional problems. The examples provide insight into the effect of refining the design variable field on the optimization result and the convergence rate of the optimization process. Using coarse higher-order B-spline discretizations for level-set fields promotes the development of smooth designs and suppresses the emergence of small features. Moreover, adaptive mesh refinement for state variable fields results in a reduction of overall computational cost. Higher-order B-spline discretizations are especially interesting when evaluating gradients of state variable fields due to their higher inter-element continuity.
Locating hydrides is crucial in organometallic chemistry but difficult to do accurately using X-ray diffraction. Electron diffraction has been proposed as a way to overcome this problem but has not been systematically compared to neutron diffraction and to quantum crystallography (Hirshfeld atom refinement, HAR) to test this hypothesis. Here, we present a comparative analysis of methods for a terminal cobalt hydride complex by comparing a single-crystal neutron diffraction reference structure to results from single-crystal X-ray diffraction with and without Hirshfeld atom refinement (HAR, NoSpherA2), density functional theory (DFT), and electron diffraction (3D-ED/MicroED) refined under kinematical and dynamical formalisms. Conventional X-ray diffraction gives lower precision than neutron diffraction as expected. Despite expected improvements, HAR gives systematic deviation from the neutron benchmark. Interestingly, optimized DFT equilibrium geometries are closer to the neutron value than the value from HAR. On the other hand, electron diffraction with a high-quality data set coupled with dynamical refinement localizes the hydride in difference maps and gives excellent agreement with the neutron data. Dynamical refinement is crucial, as kinematical refinement does not allow assignment of a hydride peak. This cross-modal comparison defines the conditions under which 3D-ED/MicroED delivers high-precision metal–hydride distances for this open-shell cobalt hydride.
Efforts to identify the most-economic methods to decarbonize several sectors of the U.S. economy are underway. Industrial processes such as crude-oil refining rely heavily on energy-dense and easily stored and transported fossil fuels for powering their operations. Refineries use large amounts of energy, primarily derived from fossil sources to separate crude-oil components, break down heavier hydrocarbons into lighter compounds, remove impurities, reform hydrocarbon molecules, and generate steam and electricity for pumps and compressors and other various auxiliary systems. Crude-oil refining operations such as distillation, cracking, desulfurization, reforming, utilities systems and some offsite facilities collectively account for most of the energy consumption. Other operations such as hydrocracking or hydrotreating also require hydrogen for developing hydrogenation reactions which involve substantial heating to keep the reactors at high-temperature and pressure levels. All heat and energy demands are typically provided by natural gas (NG), oil, or other fuels, which makes refinery industry one of the most-difficult sectors to decarbonize. Nuclear power is a viable and energy-dense source of clean electricity, heat, and hydrogen to provide the large, sustainable energy supply that the refining industry demands. The U.S. Department of Energy’s (DOE’s) Integrated Energy Systems (IES) program is working to perform research and development, design, economic siting, and risk analysis. This state-of-the-art work will enable the first on-site demonstrations and commercial deployments of advanced small modular nuclear reactors (SMNRs) integrated with industries such as chemical production, refining, iron and steel making, and more. IES seeks to demonstrate the ability of advanced nuclear reactors to meet the heat and power demands of these industries while reducing carbon emissions in a sustainable and cost-competitive way. The primary objective of this research effort is to analyze industrial-scale SMNR integration intended to decarbonize refining facilities. The foreseen outcome is the provision of reliable, cost-competitive, and sustainable clean energy, alongside a reduction of carbon emissions. Specifically, the focus of this work lies on meeting the reference facilities’ heat and electricity demands with nuclear power while also supplying clean hydrogen via integrated high-temperature steam electrolysis (HTSE). This report presents a comprehensive technical and economic assessment of the integration of advanced nuclear reactors into a reference refinery, leveraging financial incentives from the Inflation Reduction Act (IRA). The evaluation aims to explore the potential economic benefits and challenges associated with incorporating advanced nuclear reactors into refinery operations, particularly in terms of energy efficiency, economic implications and environmental impact. By examining both the technical feasibility and economic viability, this analysis seeks to identify existing gaps and propose solutions for successful nuclear integration implementation. The findings are intended to provide valuable insights for stakeholders considering the adoption of advanced nuclear reactors in the refining sector. A refinery reference-plant was developed, using an open-source refinery model, Petroleum Refinery Lifecycle Inventory Model (PRELIM) and expert assessment, as a base case for comparison with various nuclear integration options. The capacity of 100 kbd/day (KBD) of heavy crude-oil feed was selected to represent a general coking-type refinery with deep conversion capabilities (incorporating heavy-oil upgrading with FCC, coking, and associated hydrotreating process units), using a heavy crude-oil feed, which represents about 70% of U.S. refineries configurations. A summary of all cases considered in this study is shown in Table 1.
This paper will discuss on-orbit dynamic tests, modal analysis, and model refinement studies performed as part of the Mir Structural Dynamics Experiment (MiSDE). Mir is the Russian permanently manned Space Station whose construction first started in 1986. The MiSDE was sponsored by the NASA International Space Station (ISS) Phase 1 Office and was part of the Shuttle-Mir Risk Mitigation Experiment (RME). One of the main objectives for MiSDE is to demonstrate the feasibility of performing on-orbit modal testing on large space structures to extract modal parameters that will be used to correlate mathematical models. The experiment was performed over a one-year span on the Mir-alone and Mir with a Shuttle docked. A total of 45 test sessions were performed including: Shuttle and Mir thruster firings, Shuttle-Mir and Progress-Mir dockings, crew exercise and pushoffs, and ambient noise during night-to-day and day-to-night orbital transitions. Test data were recorded with a variety of existing and new instrumentation systems that included: the MiSDE Mir Auxiliary Sensor Unit (MASU), the Space Acceleration Measurement System (SAMS), the Russian Mir Structural Dynamic Measurement System (SDMS), the Mir and Shuttle Inertial Measurement Units (IMUs), and the Shuttle payload bay video cameras. Modal analysis was performed on the collected test data to extract modal parameters, i.e. frequencies, damping factors, and mode shapes. A special time-domain modal identification procedure was used on free-decay structural responses. The results from this study show that modal testing and analysis of large space structures is feasible within operational constraints. Model refinements were performed on both the Mir alone and the Shuttle-Mir mated configurations. The design sensitivity approach was used for refinement, which adjusts structural properties in order to match analytical and test modal parameters. To verify the refinement results, the analytical responses calculated using original and refined math models were compared with the measured responses. The results from this study show that the refined models predict more accurately the dynamics of the actual structure. The MiSDE test and analysis results provided the information and experience on test design, flight testing, and data analysis for the ISS and other future spacecraft, which are critical to the verification of analytical models and structural loads.
Icosahedral boron materials, which include regular icosahedra of 12 boron atoms have gained increasing attention due to their potential applications as superhard materials, semiconductors, and energy storage media. However, the synthesis of high quality crystals of these materials has been a major barrier to the development of these applications. To enable computational prediction of synthesis conditions yielding high-quality icosahedral boron crystals, herein we tested and refined a set of ReaxFF parameters for the nucleation and growth of such crystals. We focused on matching the relative energies of small boron clusters obtained by density functional theory since such small clusters and similar motifs are likely present in crystal nuclei and at the interface of growing crystals. Using a training set of B 80 clusters, including a low-energy core–shell structure containing a B 12 icosahedron core and a high-energy single-shell structure produced in preliminary ReaxFF simulations, the ReaxFF parameter set was refined to better reproduce energies calculated by density functional theory (DFT). Among existing ReaxFF parameter sets and the machine-learning interatomic potentials MACE-MP-0, MACE-MP-0b3, MACE-MPA-0, PFP v7.0.0, and SevenNet-MF-ompa, only our new parameter set and PFP v7.0.0 correctly ranked these B 80 clusters. This refinement led to improved agreement with DFT for a test set of 58 clusters consisting of 8–103 boron atoms. Furthermore, our refined parameter set yielded greater local icosahedral structure than the previously existing ReaxFF parameter set for larger scale simulations of crystallization from supercooled liquid boron. Additionally, simulations of solid boron in contact with molten nickel using our refined ReaxFF parameters yielded a boron solubility value that agrees moderately well with experimental expectations, while the previous boron parameters gave a value that was much too low.