High-fidelity simulation of soot formation and thermal radiation in a laboratory-scale Rich-Quench-Lean burner
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Abstract We present the first multi-fidelity Bayesian optimization (BO) approach for solving inverse problems in the quantum control of prototypical quantum systems. Our approach automatically constructs time-dependent control fields that enable transitions between initial and desired final quantum states. Most importantly, our BO approach gives impressive performance in constructing time-dependent control fields, even for cases that are difficult to converge with existing gradient-based approaches. We provide detailed descriptions of our machine learning methods as well as performance metrics for a variety of machine learning algorithms. Taken together, our results demonstrate that BO is a promising approach to efficiently and autonomously design control fields in general quantum dynamical systems.
A significant body of work exists showing that providing a nonlinear programming (NLP) solver with expressions for the problem constraint gradient substantially increases the speed of program execution and can also improve the robustness of convergence, especially for local optimizers. Calculation of these derivatives is often accomplished through the computation of spacecraft's state transition matrix (STM). If the two-body gravitational model is employed as is often done in the context of preliminary design, closed form expressions for these derivatives may be provided. If a high fidelity dynamics model, that might include perturbing forces such as the gravitational effect from multiple third bodies and solar radiation pressure is used then these STM's must be computed numerically. We present a method for the power hardward model and a full ephemeris model. An adaptive-step embedded eight order Dormand-Prince numerical integrator is discussed and a method for the computation of the time of flight derivatives in this framework is presented. The use of these numerically calculated derivatieves offer a substantial improvement over finite differencing in the context of a global optimizer. Specifically the inclusion of these STM's into the low thrust missiondesign tool chain in use at NASA Goddard Spaceflight Center allows for an increased preliminary mission design cadence.
The Geostationary Operational Environmental Satellite-R Series (GOES-R) is the next generation of Untied States geostationary weather satellites. The GOES-R series significantly improves the detection and observation of environmental phenomena that directly affect public safety, protection of property and the economic health and prosperity of the United States and all countries within the western hemisphere. Given the real-time or ''now-casting'' nature of the GOES science gathering mission, any data outage or interruption can reduce warning times or scientific fidelity for critical weather data. GOES-R mission level requirements limit key performance product outages to a total of six hours per year to maximize science data availability. Lower level requirement only allow for 120 minutes of disruption between the spacecraft bus interface to the instruments. This requirement is met using both design features of the satellite and ground system, in addition to operational strategies.
This presentation concentrates on the potential of long duration Venus surface missions, and the role of Silicon Carbide (SiC) electronics and sensor advancements in such exploration. For example, SiC integrated circuit (IC) electronics have matured to a state where a simple long-life scientific probe is feasible for extended Venus surface operations. These electronics have been demonstrated for more than a year at 500˚C, and 60 days in high-fidelity simulated Venus surface conditions [1-2]. Further, high temperature chemical sensing technology, including SiC-based gas sensors, integrated with SiC electronics can enable future exploration of the Venus surface atmosphere [3]. Continued maturation of these high temperature electronics and sensors has been part of the Long-Lived In-Situ Solar System Explorer (LLISSE) project to provide an operational system for in situ exploration of the Venus surface up to 60 days [4]. A key focus of this work includes increasing the complexity and decreasing the power consumption of the ICs which will pave the way to enhanced capabilities, such as long-duration Venus seismic measurements and other mission capabilities currently under development. This is in parallel to work expanding the capabilities of the sensor technology to provide science measurements on the Venus surface. This presentation will give an overview of possible extended duration Venus surface exploration and some of the SiC-based technologies that can enable this exploration.
The accurate classification of aerosol types injected into the stratosphere is important to properly characterize their chemical and radiative impacts within the Earth climate system. The updated stratospheric aerosol subtyping algorithm used in the version 4.5 (V4.5) release of the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) level 2 data products now delivers more comprehensive and accurate classifications than its predecessor. The original algorithm identified four aerosol subtypes for layers detected above the tropopause: volcanic ash, smoke, sulfate/other, and polar stratospheric aerosol (PSA). In the revised algorithm, sulfates are separately identified as a distinct, homogeneous subtype, and the diffuse, weakly scattering layers previously assigned to the sulfate/other class are recategorized as a fifth “unclassified” subtype. By making two structural changes to the algorithm and revising two thresholds, the V4.5 algorithm improves the ability to discriminate between volcanic ash and smoke from pyrocumulonimbus injections, improves the fidelity of the sulfate subtype, and more accurately reflects the uncertainties inherent in the classification process. The 532 nm lidar ratio for volcanic ash was also revised to a value more consistent with the current state of knowledge. This paper briefly reviews the previous version of the algorithm (V4.1 and V4.2) then fully details the rationale and impact of the V4.5 changes on subtype classification frequency for specific events where the dominant aerosol type is known based on the literature. Classification accuracy is best for volcanic ash due to its characteristically high depolarization ratio. Smoke layers in the stratosphere are also classified with reasonable accuracy, though during the daytime a substantial fraction are misclassified as ash. It is also possible for mixtures of ash and sulfate to be misclassified as smoke. The V4.5 sulfate subtype accuracy is less than that for ash or smoke, with sulfates being misclassified as smoke about one-third of the time. However, because exceptionally tenuous layers are now assigned to the unclassified subtype and the revised algorithm levies more stringent criteria for identifying an aerosol as sulfate, it is more likely that layers labeled as this subtype are in fact sulfate compared to those assigned the sulfate/other classification in the previous data release.
Combustion instability modeling of Solid Rocket Motors (SRM) remains a topic of active research. Many rockets display violent fluctuations in pressure, velocity, and temperature originating from the complex interactions between the combustion process, acoustics, and steady-state gas dynamics. Recent advances in defining the energy transport of disturbances within steady flow-fields have been applied by combustion stability modelers to improve the analysis framework. Employing this more accurate global energy balance requires a higher fidelity model of the SRM flow-field and acoustic mode shapes. The current industry standard analysis tool utilizes a one dimensional analysis of the time dependent fluid dynamics along with a quasi-three dimensional propellant grain regression model to determine the SRM ballistics. The code then couples with another application that calculates the eigenvalues of the one dimensional homogenous wave equation. The mean flow parameters and acoustic normal modes are coupled to evaluate the stability theory developed and popularized by Culick. The assumption of a linear, non-dissipative wave in a quiescent fluid remains valid while acoustic amplitudes are small and local gas velocities stay below Mach 0.2. The current study employs the COMSOL Multiphysics finite element framework to model the steady flow-field parameters and acoustic normal modes of a generic SRM. This work builds upon previous efforts to verify the use of the acoustic velocity potential equation (AVPE) laid out by Campos. The acoustic velocity potential (psi) describing the acoustic wave motion in the presence of an inhomogeneous steady high-speed flow is defined by, del squared psi - (lambda/c) squared psi - M x [M x del((del)(psi))] - 2((lambda)(M)/c + M x del(M) x (del)(psi) - 2(lambda)(psi)[M x del(1/c)] = 0. with M as the Mach vector, c as the speed of sound, and λ as the complex eigenvalue. The study requires one way coupling of the CFD High Mach Number Flow (HMNF) and mathematics module. The HMNF module evaluates the gas flow inside of a SRM using St. Robert's law to model the solid propellant burn rate, slip boundary conditions, and the supersonic outflow condition. Results from the HMNF model are verified by comparing the pertinent ballistics parameters with the industry standard code outputs (i.e. pressure drop, axial velocity, exit velocity). These results are then used by the coefficient form of the mathematics module to determine the complex eigenvalues of the AVPE. The mathematics model is truncated at the nozzle sonic line, where a zero flux boundary condition is self-satisfying. The remaining boundaries are modeled with a zero flux boundary condition, assuming zero acoustic absorption on all surfaces. The one way coupled analysis is perform four times utilizing geometries determined through traditional SRM modeling procedures. The results of the steady-state CFD and AVPE analyses are used to calculate the linear acoustic growth rate as is defined by Flandro and Jacob. In order to verify the process implemented within COMSOL we first employ the Culick theory and compare the results with the industry standard. After the process is verified, the Flandro/Jacob energy balance theory is employed and results displayed.
The NEAMS Multiphysics Applications team aims at providing assessment of code useability and functionality for microreactor design and analyses, together with demonstration of their capabilities to properly capture the steady-state and time-dependent behavior of different microreactor concepts. In FY-24, significant progress was achieved in improving multi-physics models of several microreactors systems: HP-MR, GC-MR and KRUSTY. These efforts focused on solving more complex multiphysics problems enabled by enhanced tools capability, verifying and validating results obtained, providing feedback to developers for suggested improvements, and sharing these models to facilitate user training. A series of new multiphysics transients were completed on the HP-MR (using Griffin/BISON/Sockeye) with core startup transient, control drum inadvertent rotation accident, and hydrogen leakage from hydride moderator (also including SWIFT). On the GC-MR, a new full-core model was developed and analyzed through a series of new multiphysics (Griffin/BISON/SAM) transients to simulate moderator leakage (also including SWIFT), flow blockage and coolant depressurization. Additional and updated TRISO failure analyses were completed on the HP-MR unit-cell and GC-MR assembly models leveraging improved TRISO modeling capabilities. The amount of SiC failure following accidental transients at end-of-life was null. However, GC-MR assembly TRISO analysis highlighted Pd penetration rate can be problematic and may require design changes on the studied microreactor concept. The neutronics discrepancies observed on the KRUSTY model in previous years were resolved using hybrid set of Monte Carlo/Deterministic cross-sections. The multiphysics (Griffin neutronics / BISON thermal-mechanics) 15₵ insertion transient simulation displayed good agreement when comparing with experimental data. Initial modeling of the 30 ₵ reactivity insertion also displays promising results. Such close agreement provides important validation data that can be leveraged by the NEAMS program and by microreactor vendors to support licensing of their technology. Finally, important experience was gathered with the NEAMS tools leading to several user feedback shared with tools developers, especially with regards to MOOSE mesh generator and Griffin. This project led to many publications demonstrating modeling capabilities, and to three models shared on the Virtual Test Bed.
The Multi-Mission Power Analysis Tool (MMPAT) simulates a spacecraft power subsystem including the power source (solar array and/or radioisotope thermoelectric generator), bus-voltage control, secondary battery (lithium-ion or nickel-hydrogen), thermostatic heaters, and power-consuming equipment. It handles multiple mission types including heliocentric orbiters, planetary orbiters, and surface operations. Being parametrically driven along with its user-programmable features can reduce or even eliminate any need for software modifications when configuring it for a particular spacecraft. It provides multiple levels of fidelity, thereby fulfilling the vast majority of a project s power simulation needs throughout the lifecycle. It can operate in a stand-alone mode with a graphical user interface, in batch mode, or as a library linked with other tools. This software can simulate all major aspects of a spacecraft power subsystem. It is parametrically driven to reduce or eliminate the need for a programmer. Added flexibility is provided through user-designed state models and table-driven parameters. MMPAT is designed to be used by a variety of users, such as power subsystem engineers for sizing power subsystem components; mission planners for adjusting mission scenarios using power profiles generated by the model; system engineers for performing system- level trade studies using the results of the model during the early design phases of a spacecraft; and operations personnel for high-fidelity modeling of the essential power aspect of the planning picture.
Inspection and certification comprise the most significant bottlenecks in advanced manufacturing for NNSA applications, often requiring far more time and resources than the fabrication of the parts themselves. Traditional methods, such as manual review and X-ray computed tomography, are not only slow and costly, but also struggle to provide a clear connection between manufacturing instructions and the final performance of critical components. This gap limits both the agility and assurance needed to support the modernization and safety of the United States nuclear stockpile. In response, our Strategic Initiative established a digital twin framework that integrates realtime process monitoring, automated data analysis, and immersive virtual reality collaboration into a unified inspection pipeline. By leveraging data from sensors, machine instructions, and imaging, we created high-fidelity virtual models of manufactured parts that could be rapidly analyzed and certified. This approach was first demonstrated with Direct Ink Write, and then extended to other manufacturing settings, including conventional (or “subtractive”) manufacturing and to predict the end of life performance of parts per the aging and lifetimes programs. The result is a transformational capability: inspection times have been reduced by a factor of 120,000 without loss of accuracy and while simultaneously improving traceability and confidence in part quality. This framework not only streamlines certification for critical applications, but also positions the national security enterprise to respond more flexibly to emerging challenges, supporting agile manufacturing and digital engineering practices across a broad range of mission-relevant domains.
Here, the equation of state (EOS) and shock compression of bulk vanadium were investigated using canonical ab initio molecular dynamic simulations, with experimental validation to 865 GPa from shock data collected at Sandia's Z Pulsed Power Facility. In simulations the phase space was sampled along isotherms ranging from 3000 K to 50 000 K, for densities between ρ = 3 and 15 g / cm 3 , with a focus on the liquid regime and the body-centered-cubic phase in the vicinity of the melting limit. The principal Hugoniot predicted from first principles is overall consistent with shock data, while it showed that current multiphase SESAME-type EOS for vanadium needed revision in the liquid regime. A more accurate SESAME EOS was developed using constraints from experiments and simulations. This work emphasizes the need to use a combined theoretical and experimental approach to develop high-fidelity EOS models for extreme conditions.
The calibration of CALPHAD (CALculation of PHAse Diagrams) models involves the solution of a very challenging high-dimensional multiobjective optimization problem. Traditional approaches to parameter fitting predominantly rely on gradient-free methods, which while robust, are computationally inefficient and often scale poorly with model complexity. In this work, we introduce and demonstrate a generalizable framework for analytic gradient-based optimization of the parameters of the CALPHAD model enabled by the recently formalized Jansson derivative technique. This method allows for efficient evaluation of gradients of thermodynamic properties at equilibrium with respect to model parameters, even in the presence of arbitrarily complex internal degrees of freedom. Leveraging these semi-analytic gradients, we employ the conjugate gradient (CG) method to optimize thermodynamic model parameters for four binary alloy systems: Cu-Mg, Fe-Ni, Cr-Ni, and Cr-Fe. Across all systems, CG achieves comparable or superior optimality relative to Bayesian ensemble Markov Chain Monte Carlo (MCMC) with improvements in computational efficiency ranging from one to three orders of magnitude. Furthermore, our results establish a new paradigm for CALPHAD assessments in which high fidelity data-rich model calibration becomes tractable using deterministic gradient-informed algorithms.
The Z-pinch m = 0 instability as well as its stabilization by radially sheared axial flow is studied using the nonlinear ideal five-moment twofluid (5M2F) model with an extension of that model to include Braginskii heat and momentum transport. Using the ideal 5M2F model, linear growth rate results are compared with prior work using MHD and Hall MHD. At small normalized wavenumber, 1 < k a < 4 , where a is the effective pinch radius, 5M2F results agree with Hall MHD within 20% in scenarios without radially sheared axial flow. With the sheared flow and focusing on ka = 10/3, agreement with Hall MHD is excellent. In the limit of small ion inertial length, results also match with MHD. A comparison with PIC modeling of shear-free m = 0 stability focuses on a plasma scenario based on recent experimental results. In a scan of mode wavenumber, ideal 5M2F results are qualitatively similar to PIC: the growth rate rises to a peak at a moderate wavenumber and declines at a large wavenumber in contrast to MHD results, which show the saturation of the growth rate with the increasing wavenumber rather than a decline. The peak normalized 5M2F growth rate is γ τ A = 1.5 , where sA is the Alfven transit time across the pinch. The peak occurs at normalized wavenumber ka = 10. For comparison, PIC results have a peak growth of γ τ A = 0.77 at ka = 5. Including Braginskiibased closure of the 5M2F model does not qualitatively change the ideal results in this particular case. Nonlinear saturation is studied using the 5M2F model with the dissipative Braginskii-based closure in cases with pinch-edge sheared-flow speed equal to half the Alfven speed. Nonlinear mixing due to the sheared flow yields a quasi-steady state after modest losses of pinch ion inventory and pinch thermal energy, approximately 30% and 10%, respectively. 5M2F modeling captures the essential physics of m = 0 instability and offers a computationally tractable route to high-fidelity modeling of 3D Z-pinch behavior, including m = 1 instability.
We present a method to improve the convergence of variational algorithms based on hidden inverses (HIs) to mitigate coherent errors. In the context of error mitigation, this means replacing the hardware implementation of certain Hermitian gates with their inverses. Doing so results in noise cancellation and a more resilient quantum circuit. This approach improves performance in a variety of two-qubit error models where the noise operator also inverts with the gate inversion. We apply the mitigation scheme on superconducting quantum processors running the variational quantum eigensolver (VQE) algorithm to find the H 2 ground-state energy. When implemented on superconducting hardware we find that the mitigation scheme effectively reduces the energy fluctuations in the parameter learning path in VQE, reducing the number of iterations for a converged value. We also provide a detailed numerical simulation of VQE performance under different noise models and explore how HIs and randomized compiling affect the underlying loss landscape of the learning problem. These simulations help explain our experimental hardware outcomes, helping to connect lower-level gate performance to application-specific behavior in contrast to metrics like fidelity which often do not provide an intuitive insight into observed high level performance.
Quantum computing is in an era of limited resources. Current hardware lacks high fidelity gates, long coherence times, and the number of computational units required to perform meaningful computation. Contemporary quantum devices typically use a binary system, where each qubit exists in a superposition of the 0 and 1 states. Furthermore, it is often possible to access the 2 or even 3 states in the same physical unit by manipulating the system in different ways. In this work, we consider automatically encoding two qubits into one four-state ququart via a compression scheme. We use quantum optimal control to design efficient proof-of-concept gates that fully replicate standard qubit computation on these encoded qubits.
The central goal of this research program was to establish fundamental synthesis and processing principles to enable the fabrication of single crystal quantum dot solids (QDS) with programmable structure (i.e., hexagonal and square) and composition. Our approach towards that goal leveraged access to and experience with unique in-situ, multi-probe characterization techniques to understand and ultimately control the fundamental relationship between processing conditions and nucleation and growth of QDS. The program integrated synthesis and fabrication (Hanrath) with in-situ TEM analysis (Kourkoutis) and computational modeling (Clancy) to gain atomic-level insights into the underlying physical phenomena governing assembly and attachment and to guide the development of optimized processing methods. We have established a foundational understanding of physicochemical interactions of self-assembly at a fluid interface, superlattice structure transformation pathways, the critical role of disorder during the initial dimerization of colloidal quantum dot monomers, and the residual strain distribution within the inter-dot epitaxial bridge which hampers the formation of novel electronics states of the quantum dot solids. Collectively, these insights have contributed towards advancing the mechanistic understanding of the complex choreography of assembly and attachment as well as understanding what currently limits further advances in high-fidelity quantum dot solids and tiles.
The Microreactor Applications Research Validation and EvaLuation (MARVEL) project is producing a high temperature liquid metal-cooled nuclear test bed at Idaho National Laboratory (INL) to ultimately improve the integration of microreactors to end-user applications. This ambitious effort seeks to design, authorize, construct, test, and operate the reactor within five years. In order to construct and operate the MARVEL reactor in a timely manner, the system will utilize materials and component designs which have already been used, qualified, or licensed from previous reactors. The MARVEL reactor will be located at the INL Transient Reactor Test (TREAT) facility in the north high-bay equipment pit and will use the existing 304 stainless steel-clad U-ZrH1.6 pin-type fuel system developed by General Atomics and purchased from TRIGA International. This fuel has been previously qualified under the United States Department of Energy’s (US DOE) Reduced Enrichment for Research and Test Reactors (RERTR) Program. Even though the regulator of the MARVEL reactor is the US DOE, the standards and overall approach recommended by the Nuclear Regulatory Commission is well-defined and utilized here. Following NUREG-1537 regulatory guidance, this report documents the authorization case for the MARVEL fuel system’s application to MARVEL and establishes stable and predictable fuel performance during the most thermophysically unfavorable conditions achievable in the MARVEL reactor. To that end, this report provides a comprehensive survey of the known thermophysical properties, performance, and quantitative relationships associated with the MARVEL reactor fuel element and uses this information to determine its mechanical integrity and risk of reaching unacceptable conditions during the most extreme accident scenarios predicted for the reactor using the most conservative assumptions available. The information contained herein is compiled from a combination of historical reports and peer reviewed scientific publication manuscripts. Known mechanisms under which the fuel is susceptible to failure are highlighted and compared to conditions that could exist in the MARVEL reactor during an unanticipated transient or accident scenario. The two scenarios considered for analysis in this report are (1) an unprotected loss of flow accident and (2) a hypothetical unprotected loss of coolant accident during the loss of flow accident. Preliminary 2D steady-state analyses herein indicate that both fuel-cladding chemical interactions and fuel-cladding mechanical interactions are negligible throughout the fuel’s operational cycle under both normal and high temperature accident scenario conditions. Although higher fidelity 3D time-dependent modeling and simulations are planned, the following may be concluded presently. The MARVEL fuel element maintains its geometric stability and structural integrity during the most extreme accident scenarios predicted for the MARVEL reactor. The hoop stress during the unprotected loss of flow accident reaches about -1.27 MPa; this negative stress indicates that it is compressive rather than tensile. The compressive stress is a result of the NaK pressure on the outside of the fuel element, caused by the restricted thermal expansion of the NaK coolant, exceeding the internal pressures generated inside of the fuel element. The hoop stress generated in the cladding during the unprotected loss of coolant accident reaches a maximum of about approximately 10 MPa, which is nearly an order of magnitude less than the predicted yield strength of the cladding under high-temperature accident scenario conditions. Calculations were compared with results from high performance computational simulations using BISON and are in very close agreement. A conservative MARVEL fuel meat peak temperature limit of 900 °C is recommended presently, which is about 180 °C higher than the peak fuel temperature predicted to occur during the most extreme accident. Based on the known properties and behavior of the MARVEL fuel element, the fuel successfully meets its design and safety requirements under normal and most extreme accident conditions with a large safety margin.