Automatic Differentiation and Source Code Generation for Dynamic Modeling and Simulation of Brine Systems
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This is a wrapper around the LANL NJOY-2016 code that interfaces with extended code capabilities and minor modification of the LANL NJOY-2016 code that supports modeling radiation damage to materials. The NJOY Nuclear Data Processing System is a modular computer code designed to read evaluated data in ENDF format, transform the data in various ways, and output the results as libraries designed to be used in various applications. The wrapper provided here permits Sandia-specific control parameters to be used in the input data file. The modifications incorporated here enhance the ability of NJOY to address material damage response functions for many materials, e.g. to include the NRT and arc-dpa forms of the damage energy in addition to the default NJOY-2016 implementation of the sharp-threshold Kinchin-Pease threshold energy treatment. All of the modifications provided here are being made available to the GitHub-based NJOY-2016 code. As useful enhancements found here are incorporated into the baseline NJOY-2016 code, they will be eliminated from this version so as to maintain our compatibility with the baseline NJOY-2016 code. SAND2020-13060 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA00035
The progenitors of gamma-ray bursts - the brightest explosions in our universe - are still poorly understood. It has been suggested that massive stars collapsing in interacting binary systems (i.e. with a closely orbiting compact object companion) can provide the necessary angular momentum and dense surrounding medium to explain observations of radio-loud gamma-ray bursts. We explore this progenitor system using the population synthesis code COSMIC. We explore the dependence of the properties of an interacting binary systems - including the remnant types and their masses - on metallicity and mass raction of the binary system. We also explore how the rates of populations of these systems depend on metallicity. Our findings help constrain what properties lead to viable GRB progenitors, especially radio loud GRBs.
Gottesman-Kitaev-Preskill (GKP) codes encode a qubit in displaced phase-space combs of a continuous-variable (CV) quantum system and are useful for correcting a variety of high-weight photonic errors. Here we propose atomic ensemble analogs of the single-mode CV GKP code by using the quantum central limit theorem to pull back the phase-space structure of a CV system to the compact phase space of a quantum spin system. We study the optimal recovery performance of these codes under error channels described by stochastic relaxation and isotropic ballistic dephasing processes using the diversity combining approach for calculating channel fidelity. Additionally, we find that the spin GKP codes outperform other spin system codes such as cat codes or binomial codes. Our spin GKP codes based on the two-axis countertwisting interaction and superpositions of SU(2) coherent states are direct spin analogs of the finite-energy CV GKP codes, whereas our codes based on one-axis twisting do not yet have well-studied CV analogs. A state preparation scheme for the spin GKP codes is proposed which uses the linear-combination-of-unitaries method, applicable to both the CV and spin GKP settings. Finally, we discuss a fault-tolerant approximate gate set for quantum computing with spin-GKP-encoded qubits, obtained by translating gates from the CV GKP setting using the quantum central limit theorem.
"Kinetic simulations of microstructural evolution" (KSOME) is an object Kinetic Monte Carlo (OMKC) simulation code. It is developed to simulate microstructural evolution in materials during irradiation. KSOME is developed from ground up with priority given to the flexibility, ease of upgradability, and computation efficiency, in that order. With previously developed simulation codes, various processes (more precisely, the diffusion-reaction processes) that can occur in a system were hardwired into the code. Hence, to perform higher fidelity simulations, a significant coding effort was required every time to incorporate either a more accurate description of existing processes or new processes. With KSOME, the necessity for frequent code upgrades whenever there is a need to perform higher fidelity simulations is either eliminated or reduced significantly. In KSOME, the categories of various diffusion-reaction processes and the data-management system are hardwired, while the execution of the diffusion-reaction processes specific to a system is specified via input files. In the present version of KSOME, the analytical expression required to calculate defect interaction radii are inputted via a text file. However, the ability to parse mathematical expressions from a text file can be extended to input the analytical expression to calculate other defect properties; including the expressions to calculate the change in the migration barriers of mobile defects due to long-range interaction with extended defects
Focal Area(s): (2)Predictive modeling using AI techniques and AI-derived model components; use of AI and other tools to design a prediction system comprising of a hierarchy of models. (3) Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge- guided AI. Science Challenge: The Energy Exascale Earth System Model (E3SM) is a fully coupled, state-of-the-science Earth system model that uses code optimized for DOE's advanced computers to address the most critical scientific questions facing our nation and society (Golaz et al., 2019). The E3SM Land model (ELM) is designed to understand how the changes in terrestrial land surfaces will interact with other Earth system components and has been used to understand hydrologic cycles, biogeophysics, and ecosystem dynamics. In spite of great successes, the ELM has several known issues that restrain rapid improvements. For example, the ELM uses equilibrium models to simulate dynamic land-climate interactions and it requires long model spin-up time to identify suitable initial conditions for transient simulations. The ELM lacks built-in uncertainty mechanisms that can improve the robustness of model predictions. The ELM is a holistic, deterministic model system with a rigid design, and in many situations, it is hard to modify the ELM system to incorporate new theory/hypothesis and new data across scales to address emerging science problems (such as predicting the impacts of water cycle extremes). In addition, The ELM is technically optimized for traditional CPU-centric computers and it cannot fully utilize the current and incoming leadership computers for model simulations and uncertainty quantification (UQ). The success of artificial intelligence (AI) has inspired scientists to use AI models to discover intrinsic features from simulation data (Chattopadhyay et al., 2020) and observational data (Reichstein et al., 2019) to gain further process understanding of Earth science problems. However, autonomous AI model training through deep learning usually requires a huge amount of annotated data. To overcome the limitations from the data and computing resources, knowledge-guided AI models are necessary where human-knowledge is ingested in model construction (Banino et al., 2018) and training process (Silver et al., 2016) for efficient learning. Herein, we present a new way that leverages the process understanding from the ELM to guide AI model development for the ELM enhancement and UQ. We hope this study can inspire further Earth and environmental system model developments and transformations.
This report demonstrates new functionality and applications stemming from the development of high fidelity to low fidelity (high-low) coupling for system simulations and to further explore the capabilities of RAVEN in the performance of uncertainty quantification in this kind of high-low coupled system models. The work builds from previous work on high-low coupling that utilized CTF, the high fidelity subchannel analysis code, with a low fidelity model built in TRANSFORM, the system analysis code, utilizing the Functional Mock-Up Interface (FMI)
This code implements a Fully Homomorphic Encryption (FHE) system, enabling secure computation on encrypted data without requiring decryption. It supports encryption, decryption, and homomorphic operations like matrix multiplication and addition. This code is adaptable for integrating FHE into linear-time invariant (LTI) systems, including digital control and filtering. With proper configuration from subject matter expertise, encrypted system parameters and signals can be manipulated to perform tasks like state updates, output calculations, and convolution in the encrypted domain. By preserving the structure of LTI systems while ensuring privacy, the framework facilitates secure applications in areas such as autonomous systems, signal processing, and industrial automation. The code initializes the encryption system using parameters provided in the env dictionary. These parameters include the ciphertext modulus, key dimension, plaintext fixed-point scaling factor, and noise bound. During initialization, a secret key is generated, which is essential for encrypting and decrypting data securely. The modular design allows users to tailor these parameters to specific use cases or security requirements. The code implements multiple cryptographic schemes. The learning with errors (LWE) encryption method encodes cleartext message to their plaintext fixed-point representation then encrypted into ciphertext space with additive noise. This noise ensures the security of the scheme, relying on the computational hardness of the LWE problem. The code also includes the Gentry-Sahai-Waters (GSW) scheme based off the LWE problem. Homomorphic matrix multiplication is performed between the LWE and GSW to encrypted data. This is achieved using a decomposition function on the LWE ciphertext during the multiplication operation. For higher-dimensional data, the code includes a method to encrypt entire matrices (GSWMat) using GSW encryption. These encrypted matrices can then be used for homomorphic matrix multiplications (MatMult). The decryption function uses the secret key to recover the original plaintext, removing the added noise and scaling that was originally applied during encryption.
A goal across many physics and engineering disciplines is to use radiation-hydrodynamics codes to accurately simulate systems that are expected to deviate from local thermodynamic equilibrium (LTE), such as laser-driven hohlraums, stellar coronae, and supernova ejecta. The computational expense of traditional non-LTE (NLTE) opacity calculations can dominate the cost of simulating these systems and render NLTE physics untenable in most cases. In this paper, we present a new parallel implementation for NLTE opacity calculations that employs advanced load balancing, vectorization, and memory management to significantly reduce the computational costs of these calculations. Using the radiation-hydrodynamics code xRAGE , we demonstrate this new implementation on three test problems and present order-of-magnitude speed improvements.
The Kelvin–Helmholtz Instability (KHI) is an interface instability that develops between two fluids or plasmas flowing with a common shear layer. KHI occurs in astrophysical jets, solar atmosphere, solar flows, cometary tails, planetary magnetospheres. Two applications of interest, encompassing both space and fusion applications, drive this study: KHI formation at the outer flanks of the Earth’s magnetosphere and KHI growth from non-uniform laser heating in magnetized direct-drive implosion experiments. Here, we study 2D KHI with or without a magnetic field parallel to the flow. We use both the GAMERA code, which solves the compressible Euler equations, and the STRATOSPEC code, which solves the Navier-Stokes equations under the Boussinesq approximation, coupled with the magnetic field dynamics. GAMERA is a global three-dimensional MHD code with high-order reconstruction in arbitrary nonorthogonal curvilinear coordinates, which is developed for a large range of astrophysical applications. STRATOSPEC is a three-dimensional pseudo-spectral code with an accuracy of infinite order (no numerical diffusion). Magnetized KHI is a canonical case for benchmarking hydrocode simulations with extended MHD options. An objective is to assess whether or not, and under which conditions, the incompressibility hypothesis allows to describe a dynamic compressible system. For comparing both codes, we reach the inviscid incompressible regime, by decreasing the Mach number in GAMERA, and viscosity and diffusion in STRATOSPEC. Here, we specifically investigate both single-mode and multi-mode initial perturbations, either with or without magnetic field parallel to the flow. The method relies on comparisons of the density fields, 1D profiles of physical quantities averaged along the flow direction, and scale-by-scale spectral densities. We also address the triggering, formation and damping of filamentary structures under varying Mach number or Atwood number, with or without a parallel magnetic field. Comparisons show very satisfactory results between the two codes. The vortices dynamics is well reproduced, along with the breaking or damping of small-scale structures. We end with the extraction of growth rates of magnetized KHI from the compressible regime to the incompressible limit in the linear regime assessing the effects of compressibility under increasing magnetic field. The observed differences between the two codes are explained either from diffusion or non-Boussinesq effects.
This milestone report summarizes recent work to investigate higher fidelity modeling and simulation practices for large-break loss-of-coolant accident (LBLOCA) analysis in high-burnup pressurized water reactor (PWR) cores. Because of current industry interest in extending fuel cycle lengths ranging from 18 to 24-months, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has been investigating the susceptibility of high-burnup core designs to fuel fragmentation, release, and dispersal (FFRD) during accident conditions such as LBLOCA. This work has prioritized developing and demonstrating a methodology for calculating core-wide susceptibility to FFRD and addressing uncertainties identified in the analysis and the US Nuclear Regulatory Commission (NRC) Research Information Letter on FFRD. Part of this investigation seeks to quantify differences between system-level thermal hydraulic behavior and higher fidelity subchannel modeling methods to identify potential safety concerns or opportunities to minimize FFRD susceptibility. To this end, the NEAMS subchannel code, CTF, is being used, along with the NRC system analysis code TRACE, for analysis of LBLOCA in a core containing high-burnup fuel. This project includes two thrusts: (1) improving on the existing TRACE model for a 4-loop PWR for LBLOCA so that the model is higher fidelity and consistent with current USNRC best practices, and (2) using CTF to perform pin-resolved modeling of the core region of the reflood phase of a LBLOCA in a high-burnup PWR.
We present the orbital solution of a peculiar double-lined spectroscopic and eclipsing binary system, 2M17091769+3127589. This solution was obtained by a simultaneous fit of both APOGEE radial velocities and TESS and ASAS-SN light curves to determine masses and radii. This system consists of an M=0.256{sub -0.006}{sup +0.010} M {sub ⊙}, R=3.961{sub -0.032}{sup +0.049} R {sub ⊙} red giant and a hotter M=1.518{sub -0.031}{sup +0.057} M {sub ⊙}, R=2.608{sub -0.321}{sup +0.034} R {sub ⊙} subgiant. Modeling with the MESA evolutionary codes indicates that the system likely formed 5.26 Gyrs ago, with a M = 1.2 M {sub ⊙} primary that is now the system’s red giant and a M = 1.11 M {sub ⊙} secondary that is now a more massive subgiant. Due to Roche-lobe overflow as the primary ascends the red giant branch, the more evolved “primary” (i.e., originally the more massive star of the pair) is now only one sixth as massive as the “secondary.” Such a difference between the initial and the current mass ratio is one of the most extreme detected so far. Evolutionary modeling suggests the system is still engaged in mass transfer, at a rate of M-dot ~10{sup -9} M {sub ⊙}/yr, and it provides an example of a less evolved precursor to some of the systems that consist of white dwarfs and blue stragglers.
Increasing policy support and declining prices for battery energy storage systems (BESS) are driving rapid growth in the installation of these systems in the United States and around the world. Because a BESS is modular in nature and has limited infrastructure requirements, it can be built in close proximity to existing uses, which creates the potential for conflict. As the use of BESS grows, local planning and zoning staff are increasingly being asked to determine where the systems can be built and how their impacts on surrounding uses can be mitigated. While a large-scale BESS offers significant electric grid and societal benefits, it can also pose safety, visual, auditory, and environmental impacts on the community in which it is located. While these are material impacts, current safety codes for energy storage systems and land use frameworks provide planners with the necessary tools and processes to mitigate those impacts and ensure that their communities safely receive the benefits of energy storage systems. This report provides an overview of BESS from a land use perspective and describes their implications for zoning and project permitting. It concludes with an analysis of current energy storage zoning standards adopted by local jurisdictions in the U.S. Its intent is to objectively inform land use decisions for energy storage projects by equipping planning officials with relevant information about these technologies and knowledge of what questions to ask during review processes, so that energy storage projects can move forward in ways that will benefit electric systems while not unduly affecting host communities.
This study examined the use of zoned ventilation systems using a coupled CONTAM/EnergyPlus model for new California dwellings. Several smart control strategies were developed with a target of halving ventilation-related energy use, largely through reducing dwelling ventilation rates based on zone occupancy. The controls were evaluated based on the annual energy consumption relative to continuously operating non-zoned, code-compliant mechanical ventilation systems. The systems were also evaluated from an indoor air quality perspective using the equivalency approach, where the annual personal concentration of a contaminant for a control strategy is compared to the personal concentration that would have occurred using a continuously operating, non-zoned system. Individual occupant personal concentrations were calculated for the following contaminants of concern: moisture, CO2, particles, and a generic contaminant. Zonal controls that saved energy by reducing outside airflow achieved typical reductions in ventilation-related energy of 10% to 30%, compared to the 7% savings from the unzoned control. However, this was at the expense of increased personal concentrations for some contaminants in most cases. In addition, care is required in the design and evaluation of zonal controls, because control strategies may reduce exposure to some contaminants, while increasing exposure to others.
Using a real-space high-order finite-difference approach, we investigate the electronic structure of large spherical silicon nanoclusters. Within Kohn-Sham density functional theory and using pseudopotentials, we report the self-consistent field convergence of a system with over 100000 atoms: a Si 107,641 H 9,084 nanocluster with a diameter of 16 nm. Our approach uses Chebyshev-filtered subspace iteration to speed up the convergence of the eigenspace, and blockwise Hilbert space-filling curves to speed up sparse matrix-vector multiplications, all of which are implemented in the parsec code. For the largest system, we utilized 2048 nodes (114 688 cores) on the Frontera machine in the Texas Advanced Computing Center. Our quantitative analysis of the electronic structure shows how it gradually approaches its bulk counterpart as a function of nanocluster size. The band gap is enlarged due to quantum confinement in nanoclusters, but decreases as the system size increases, as expected. In conclusion, our work serves as a proof of concept for the capacity of the real-space approach in efficiently parallelizing very large calculations using high-performance computer platforms, which can straightforwardly be replicated in other systems with more than 10 5 atoms.
The Holos-Quad micro-reactor concept, developed by HolosGen LLC, is equipped with a 22 MWt (Mega-Watt thermal) core and an integral power conversion system converting the core thermal energy into approximately 10 MWe (Mega-Watt electric). This design can be configured to support a wide range of applications. It is a very innovative high-temperature gas-cooled reactor concept using TRI-structural ISOtropic particle fuel (TRISO) distributed in graphite hexagonal blocks, cooled with helium in a direct Brayton cycle independently executed by four Subcritical Power Modules (SPMs) fitted into a hardened 40-foot container whose dimensions are in compliance with ISO shipping containers requirements. In FY2019 HolosGen LLC was awarded by the Department of Energy Advanced Research Project Agency-Energy (DOE ARPA-E) under the MEITNER funding program. As part of the MEITNER award, the Argonne National Laboratory (ANL) contributed expertise through two specialized teams: The “Design Team” and the “Resource Team”. The Design Team was dedicated to validate feasibility of the Holos-Quad core and to optimize its core design through neutronics analyses. The Resource Team was dedicated to feasibility verification via high-fidelity codes of Holos-Quad thermal-hydraulic, heat transfer, shielding, and structural aspects. This report summarizes the activities conducted by ANL Design Team. A rigorous design approach based on multi-criteria optimization and code-to-code comparison involving stochastic and high-fidelity deterministic solutions was developed and employed at several evolutionary stages of the Holos-Quad design. Several generations of the Holos-Quad core were designed within this project before converging to the current full-scale Gen 2+ design that is detailed in this report. Figure EA-1 illustrates a cross-sectional view of Gen 2+ Holos-Quad core configuration, and Figure EA-2 provides a simplified perspective view of 1-of-4 SPMs. The Holos-Quad uses four thermal-hydraulically independent SPMs locked into stationary positions during power operation, surrounded by BeO reflector and structural component fully comprised within the dimensional constraints represented by traditional ISO containers. One of the benefits of this approach is to enable transportation of each SPM promptly after irradiation in shielded containers. The core is designed to operate for approximately 8 full-power years while the reactivity controls and power conversion system enable load-following operations. The reactivity controls are represented by independent, diversified, and redundant reactivity control systems based on control drums and redundant sets of shutdown rods. The high-fidelity simulation tools were used to assess detailed power and flux distributions of the three-dimensional full-core or quarter-core of the Gen 2+ configuration. Single-physics and multi-physics simulations of the neutronics code PROTEUS and the thermal-hydraulic code System Analysis Module (SAM) were performed to analyze the Holos design configurations with detailed high-fidelity solutions. The design work performed confirmed feasibility of the Holos-Quad concept, provided realistic design description for detailed design of the operational system, and identified several core design improvements to be further considered for future reactor development activities.
This paper presents the current state of the global gyrokinetic code Orb5 as an update of the previous reference [Jolliet et al., Comp. Phys. Commun. 177 409 (2007)]. The Orb5 code solves the electromagnetic VlasovMaxwell system of equations using a PIC scheme and also includes collisions and strong flows. The code assumes multiple gyrokinetic ion species at all wavelengths for the polarization density and drift-kinetic electrons. Variants of the physical model can be selected for electrons such as assuming an adiabatic response or a “hybrid” model in which passing electrons are assumed adiabatic and trapped electrons are drift-kinetic. A Fourier filter as well as various control variates and noise reduction techniques enable simulations with good signal-to-noise ratios at a limited numerical cost. They are completed with different momentum and zonal flow-conserving heat sources allowing for temperature-gradient and flux-driven simulations. The code, which runs on both CPUs and GPUs, is well benchmarked against other similar codes and analytical predictions, and shows good scalability up to thousands of nodes.
Heliogen has designed a 1.3 MW particle and supercritical carbon dioxide (sCO2) test loop to retire technical and manufacturing risks. The data from this facility will be used to validate near commercial-scale particle heat exchanger modules. The heat exchanger is scaled to capture all features of the full-scale modules. Testing will be conducted with CARBOBEAD HSP 16/30, a larger particle size than other recent testing. The system was designed to ASME codes with the constraint that sCO2 piping and other major components are stainless steels.