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SAM-ML: Integrating data-driven closure with nuclear system code SAM for improved modeling capability
Advanced reactors often involve complicated thermal-fluid (T-F) phenomena. Modeling such phenomena with the traditional one-dimensional (1-D) system code is a challenging task. The System Analysis Module (SAM), a modern nuclear system code, has developed a coarse mesh multi-dimensional (multi-D) flow model to capture the spatial effect of T-F phenomena in advanced reactors. As a coarse mesh solver, constitutive relations are required for SAM's multi-D model for unresolved fine-scale physics, such as turbulence. Here this work presents a novel approach that integrates neural networks as data-driven closure for SAM's multi-D flow model. The data-driven closure is trained with fine-resolution data to ensure its accuracy while maintaining a coarse mesh setup to ensure its efficiency and consistency with SAM. We demonstrate the applicability of this SAM-ML capability in an open volume thermal stratification problem, where a neural network model serves as the eddy viscosity closure. A customized interface between the neural network and SAM is developed to ensure flexible and efficient data exchange. The SAM-ML results demonstrate superior performance compared to SAM's built-in zero-equation eddy viscosity closure. The case study shows that although the generalization capability of the data-driven closure still needs to be improved for different transient case or different geometric setup, SAM -ML demonstrates good potential for challenging simulation problems with improved accuracy and computational efficiency.
S ‐Adenosyl‐ l ‐ethionine is a Catalytically Competent Analog of S ‐Adenosyl‐ l ‐methionine (SAM) in the Radical SAM Enzyme HydG
Abstract Radical S ‐adenosyl‐ l ‐methionine (SAM) enzymes initiate biological radical reactions with the 5′‐deoxyadenosyl radical (5′‐dAdo . ). A [4Fe‐4S] + cluster reductively cleaves SAM to form the Ω organometallic intermediate in which the 5′‐deoxyadenosyl moiety is directly bound to the unique iron of the [4Fe‐4S] cluster, with subsequent liberation of 5′‐dAdo . . We present synthesis of the SAM analog S ‐adenosyl‐ l ‐ethionine (SAE) and show SAE is a mechanistically equivalent SAM‐alternative for HydG, both supporting enzymatic turnover of substrate tyrosine and forming the organometallic intermediate Ω. Photolysis of SAE‐bound HydG forms an ethyl radical trapped in the active site. The ethyl radical withstands prolonged storage at 77 K and its EPR signal is only partially lost upon annealing at 100 K, making it significantly less reactive than the methyl radical formed by SAM photolysis. Upon annealing above 77 K, the ethyl radical adds to the [4Fe‐4S] 2+ cluster, generating an ethyl‐[4Fe‐4S] 3+ organometallic species termed Ω E .
Odd-Even Effects in Charge Transport across n-Alkanethiolate-Based SAMs
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Introducing Ionic and/or Hydrogen Bonds into the SAM//Ga2O3 Top-Interface of Ag-TS/S(CH2)(n)T//Ga2O3/EGaIn Junctions
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SAM Software Quality Assurance Plan Implementation and NQA-1 Assessment
The System Analysis Module (SAM) is an advanced and modern system analysis tool being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. As a modern-day software, SAM development included efforts to follow best practices in software development. These best practices include version control using git, independent reviews of development activities, and detailed descriptions of developments and bug fixes using the GitLab issue and merge request system. In Fiscal Year 2023 (FY23), the SAM development team set out to formalize a Software Quality Assurance (SQA) program that allowed industry partners to credit the informal steps being taken by the SAM development team to ensure the quality of the software. As part of formalizing an SQA program, a SQA Plan (SQAP) was developed, implemented, and assessed. The SAM SQAP targets compliance with NQA-1-2008/2009 Addenda. The SQAP builds on the MOOSE SQAP and the Argonne SSQAPP while accounting for the needs of the multi-organization SAM development team. Modifications to the SAM repository structure, including a new testing system, updated test cases, and the development of an internal website, facilitate the implementation of the SAM SQAP. The initial assessment of the SAM SQAP indicated that the SAM SQAP was adequately and effectively implemented and additional work was required to improve the compliance of the SAM SQAP with NQA-1 2008/2009 Addenda. Several improvements to the SQAP have already been drafted to address these assessments and future work is planned to further improve the SAM SQAP in support of end-user needs.
SAM Photovoltaic Model Technical Reference 2016 Update
This manual describes the photovoltaic performance model in the System Advisor Model (SAM) software, Version 2016.3.14 Revision 4 (SSC Version 160). It is an update to the 2015 edition of the manual, which describes the photovoltaic model in SAM 2015.1.30 (SSC 41). This new edition includes corrections of errors in the 2015 edition and descriptions of new features introduced in SAM 2016.3.14, including: 3D shade calculator Battery storage model DC power optimizer loss inputs Snow loss model Plane-of-array irradiance input from weather file option Support for sub-hourly simulations Self-shading works with all four subarrays, and uses same algorithm for fixed arrays and one-axis tracking Linear self-shading algorithm for thin-film modules Loss percentages replace derate factors. The photovoltaic performance model is one of the modules in the SAM Simulation Core (SSC), which is part of both SAM and the SAM SDK. SAM is a user-friedly desktop application for analysis of renewable energy projects. The SAM SDK (Software Development Kit) is for developers writing their own renewable energy analysis software based on SSC. This manual is written for users of both SAM and the SAM SDK wanting to learn more about the details of SAM's photovoltaic model.
Validation of a Hybrid Domain Overlapping Coupling Between SAM and CFD Against the TALL-3D Transients
The System Thermal Hydraulics (STH) code SAM has been coupled to the Computational Fluid Dynamics (CFD) code Simcenter STAR-CCM+ utilizing a hybrid domain overlapping method with an explicit coupling in time. The coupling aims to extend the STH code’s applicability to scenarios where local momentum and energy transfers are important yet difficult for STH codes to capture, such as three-dimensional (3D) mixing. The coupling method’s numerical stability was verified in the past against two closed-loop configurations, and it was validated against a double T-junction experiment with 3D scalar mixing. In the present work, the coupling method is validated against the TALL-3D STH/CFD coupling benchmark facility. TALL-3D is a three-legged, liquid-metal facility with a large, pool-type enclosure (test section) that exhibits 3D flow effects to be modeled by a CFD code. The rest of the system exhibits approximately 1D behavior well-predicted by an STH code. First, the present STAR-CCM+ CFD model of the 3D test section is validated against experimental data. Then, the SAM-STARCCM+ coupled model is validated against six different TALL-3D steady states, including SAM standalone model results for comparison. Lastly, the SAM-STARCCM+ coupled model is validated against two TALL-3D transients, one exhibiting flow reversal in the test section and one exhibiting nonlinear, Limit Cycle Oscillations (LCO). For the first transient, the SAM-STARCCM+ coupled model properly predicts an increase in the test section’s inlet temperature during flow reversal, and this is not predicted by the SAM standalone model. Following flow reversal, the SAM-STARCCM+ coupled model better-predicts the initial flow recovery and following oscillations as the system approaches a final natural circulation state. For the second transient, no true final steady state is observed due to LCO. Neither the SAM-STARCCM+ coupled model nor the SAM standalone model can perfectly capture the experiment’s changing oscillation frequency during the transient. However, the SAM-STARCCM+ coupled model does reproduce the oscillatory feedback observed in the system. This is a significant achievement as the SAM-STARCCM+ coupled model only uses an explicit coupling in time, as opposed to a semi-implicit coupling. In comparison, previous STH/CFD coupling efforts of the TALL-3D facility required semi-implicit coupling to obtain similar results.
System Advisor Model (SAM) General Description (Version 2017.9.5)
This document describes the capabilities of the System Advisor Model (SAM) developed and distributed by the U.S. Department of Energy's National Renewable Energy Laboratory. The document is for potential users and others wanting to learn about the model's capabilities. SAM is a techno-economic computer model that calculates performance and financial metrics of renewable energy projects. Project developers, policy makers, equipment manufacturers, and researchers use graphs and tables of SAM results in the process of evaluating financial, technology, and incentive options for renewable energy projects. SAM simulates the performance of photovoltaic, concentrating solar power, solar water heating, wind, geothermal, biomass, and conventional power systems. The financial models are for projects that either buy and sell electricity at retail rates (residential and commercial) or sell electricity at a price determined in a power purchase agreement (PPA). SAM's simulation tools facilitate parametric and sensitivity analyses, Monte Carlo simulation and weather variability (P50/P90) studies. SAM can also read input variables from Microsoft Excel worksheets. For software developers, the SAM software development kit (SDK) makes it possible to use SAM simulation modules in their applications written in C/C plus plus, C sharp, Java, Python, MATLAB, and other languages. NREL provides both SAM and the SDK as free downloads at https://sam.nrel.gov. SAM is an open source project, so its source code is available to the public. Researchers can study the code to understand the model algorithms, and software programmers can contribute their own models and enhancements to the project. Technical support and more information about the software are available on the website.
Reactivity Feedback Modeling in SAM
System Analysis Module (SAM) is being developed at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. This report presents the development of Point-Kinetics modeling and reactivity feedback mechanisms in SAM. It also presents a new capability for predicting the thermal expansion in various structural components by coupling SAM with an external thermomechanics module (Tensor Mechanics) from the MOOSE framework. The analysis of the transient behavior of a nuclear reactor requires the coupled simulation of reactor kinetics and thermal-hydraulics of the reactor core, especially for those unprotected transients where the reactor scram system may not function properly. The point kinetics model has been widely used for reactor safety analysis due to its simplicity to capture the transient behavior of the reactor. Various reactivity feedback models have been developed and integrated with the Point-Kinetics module, including fuel axial expansion, core radial expansion, fuel Doppler, and coolant density reactivity. The reactivity feedback models in SAM are similar to the respective models used in SAS4A/SASSYS-1. This report first presents the brief theory of the Point-Kinetics module and reactivity feedback models. A number of verification tests have been performed where the code simulations are compared to the analytical model results. The reactivity feedback due to the thermal deformation, such as the fuel axial expansion and core radial expansion, is important for SFR transient analysis. Simplified thermal expansion models for the fuel pin and reactor constrain system (e.g. grid plate) are developed and verified in SAM. Additionally, a coupling interface is developed to couple SAM with external thermomechanical analysis modules for more accurate predictions of the thermal expansion of different components during the transients. The current coupling interface has been tested with the Tensor Mechanics module from MOOSE. These point kinetics and reactivity feedback modeling capabilities have also been demonstrated by simulating the early stage of the unprotected loss-of-flow (ULOF) accident in the Advanced Burner Test Reactor (ABTR). Both the stand-alone SAM and coupled SAM and Tensor Mechanics simulations are performed. It is confirmed that the major physics phenomena in the heat transport system of the ABTR reactor are captured by SAM, and the point kinetics model, reactivity feedback models, and the coupling schemes are working well as expected.
System Advisor Model, SAM 2014.1.14: General Description
This document describes the capabilities of the U.S. Department of Energy and National Renewable Energy Laboratory's System Advisor Model (SAM), Version 2013.9.20, released on September 9, 2013. SAM is a computer model that calculates performance and financial metrics of renewable energy systems. Project developers, policy makers, equipment manufacturers, and researchers use graphs and tables of SAM results in the process of evaluating financial, technology, and incentive options for renewable energy projects. SAM simulates the performance of photovoltaic, concentrating solar power, solar water heating, wind, geothermal, biomass, and conventional power systems. The financial model can represent financial structures for projects that either buy and sell electricity at retail rates (residential and commercial) or sell electricity at a price determined in a power purchase agreement (utility). SAM's advanced simulation options facilitate parametric and sensitivity analyses, and statistical analysis capabilities are available for Monte Carlo simulation and weather variability (P50/P90) studies. SAM can also read input variables from Microsoft Excel worksheets. For software developers, the SAM software development kit (SDK) makes it possible to use SAM simulation modules in their applications written in C/C++, C#, Java, Python, and MATLAB. NREL provides both SAM and the SDK as free downloads at http://sam.nrel.gov. Technical support and more information about the software are available on the website.
Development and Validation of SAM Multi-dimensional Flow Model for Thermal Mixing and Stratification Modeling
Thermal mixing and stratification in large pools or enclosures are very important phenomena that are critical to nuclear reactor safety. Because of the wide ranges of time and length scales associated with such phenomena, accurate modeling and simulation of thermal mixing and stratification remain as the key unresolved, challenging problems for reactor transient analyses. In traditional system analysis codes, simplified zero-dimensional (0-D) models are widely used for their high numerical efficiency, but they generally suffer from very limited prediction accuracies or range of applicability. Like traditional system analysis codes, the current version of the SAM code has implemented such simplified 0-D and one-dimensional mixing models. On the other hand, high-resolution Computational Fluid Dynamics (CFD) tools are often used to model complex thermal mixing and stratification phenomena. They are, however, generally numerically expensive, and they require large amounts of computational resources. It is therefore desirable to implement advanced and efficient thermal mixing and stratification modeling capabilities embedded in a system analysis code. This approach will improve the accuracy of reactor safety analyses when thermal mixing and stratification are involved, and also avoid using the large computational resources needed for high-resolution CFD analysis. Currently, with the support of the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation program, an effort has been launched to develop and implement a multi-dimensional flow model in the system analysis code SAM, and demonstrate its applications to model thermal mixing and stratification phenomena in large enclosures. The main outcomes of this research and development activity are summarized in this report, which presents an attempt to include a built-in advanced multi-dimensional flow model in a system analysis code with the focus on overcoming the simulation challenges of thermal mixing and stratification phenomena. In this report, we start with the introduction of existing SAM code capabilities to simulate thermal mixing and stratification phenomena, which is followed by a short summary of the multi-dimensional model implemented in the SAM code, including both the physical model and the Finite Element Method code implementation. In this study, two options were implemented in the SAM code to model turbulent flows: a relatively simple built-in turbulence model and an interface to accept externally computed turbulent viscosities (e.g., from a high- resolution CFD simulation). Code validation studies on this newly added capability were then carried out to compare SAM simulation results with experimental data from the SUPERCAVNA facility, which was designed to study the complex flow recirculation and thermal stratification phenomena relevant to sodium fast reactor designs. In this study, one transient and two steady-state test cases were used for code validation. Different approaches have been used to model the complex turbulence flow fields in the SUPERCAVNA facility. A highly simplified zero-equation turbulence model was first used, but it was determined that it is too simple to capture the complex turbulence flow fields in these test cases. Subsequently, the code validation continued with the use of turbulent viscosity data from high-resolution STAR-CCM+ CFD simulations to improve the accuracy of the results. Using this approach, the SAM simulation results showed very good agreement with both the SUPERCAVNA experimental data and STAR-CCM+ simulation results. In this report, we demonstrate the development, implementation, and successful validation of a multi-dimensional flow model in the SAM code, which aims to improve the simulation accuracy for complex thermal mixing and stratification phenomena. Lessons have also been learned, including that in cases where the flow fields are not well predicted by the zero-equation model, the iinput of turbulent viscosities from an external source can enhance the overall predictive capabilities needed to accurately capture complex thermal-hydraulic phenomena. Therefore, future research will be needed to further improve the code’s capabilities, such as by developing a more efficient and robust approach to capture the turbulence effects in the SAM code.
Radical SAM enzymes: Nature's choice for radical reactions
Enzymes that use a [4Fe-4S] 1+ cluster plus S-adenosyl-L-methionine (SAM) to initiate radical reactions (radical SAM) form the largest enzyme superfamily, with over half a million members across the tree of life. This review summarizes recent work revealing the radical SAM reaction pathway, which ultimately liberates the 5´-deoxyadenosyl (5´-dAdo•) radical to perform extremely diverse, highly regio- and stereo-specific, transformations. Most surprising was the discovery of an organometallic intermediate Ω exhibiting an Fe-C5´-adenosyl bond. Ω liberates 5´-dAdo• through homolysis of the Fe-C5´ bond, in analogy to Co-C5´ bond homolysis in B12, previously viewed as biology’s paradigmatic radical generator. The 5´-dAdo• has been trapped and characterized in radical SAM enzymes via a recently-discovered photoreactivity of the [4Fe- 4S] + /SAM complex, and has been confirmed as a catalytically active intermediate in enzyme catalysis. The regioselective SAM S-C bond cleavage to produce 5´-dAdo• originates in the JahnTeller effect. The simplicity of SAM as a radical precursor, and the exquisite control of 5´-dAdo• reactivity in radical SAM enzymes, may be why radical SAM enzymes pervade the tree of life, while B12 enzymes are only a few.
Structural Basis for Methyl Transfer by a Radical SAM Enzyme
The radical S-adenosyl-l-methionine (SAM) enzymes RlmN and Cfr methylate 23S ribosomal RNA, modifying the C2 or C8 position of adenosine 2503. The methyl groups are installed by a two-step sequence involving initial methylation of a conserved Cys residue (RlmN Cys{sup 355}) by SAM. Methyl transfer to the substrate requires reductive cleavage of a second equivalent of SAM. Crystal structures of RlmN and RlmN with SAM show that a single molecule of SAM coordinates the [4Fe-4S] cluster. Residue Cys{sup 355} is S-methylated and located proximal to the SAM methyl group, suggesting the SAM that is involved in the initial methyl transfer binds at the same site. Thus, RlmN accomplishes its complex reaction with structural economy, harnessing the two most important reactivities of SAM within a single site.
Benchmark Simulation of Natural Circulation Cooling System with Salt Working Fluid Using SAM
Liquid salt-cooled reactors, such as the Fluoride Salt-Cooled High-Temperature Reactor (FHR), offer passive decay heat removal through natural circulation using Direct Reactor Auxiliary Cooling System (DRACS) loops. The behavior of such systems should be well-understood through performance analysis. The advanced system thermal-hydraulics tool System Analysis Module (SAM) from Argonne National Laboratory has been selected for this purpose. The work presented here is part of a larger study in which SAM modeling capabilities are being enhanced for the system analyses of FHR or Molten Salt Reactors (MSR). Liquid salt thermophysical properties have been implemented in SAM, as well as properties of Dowtherm A, which is used as a simulant fluid for scaled experiments, for future code validation studies. Additional physics modules to represent phenomena specific to salt-cooled reactors, such as freezing of coolant, are being implemented in SAM. This study presents a useful first benchmark for the applicability of SAM to liquid salt-cooled reactors: it provides steady-state and transient comparisons for a salt reactor system. A RELAP5-3D model of the Mark-1 Pebble-Bed FHR (Mk1 PB-FHR), and in particular its DRACS loop for emergency heat removal, provides steady state and transient results for flow rates and temperatures in the system that are used here for code-to-code comparison with SAM. The transient studied is a loss of forced circulation with SCRAM event. To the knowledge of the authors, this is the first application of SAM to FHR or any other molten salt reactors. While building these models in SAM, any gaps in the code’s capability to simulate such systems are identified and addressed immediately, or listed as future improvements to the code.
Code validation of SAM using natural-circulation experimental data from the compact integral effects test (CIET) facility
The primary objective of this study is to validate the system analysis code, SAM, using experimental data from the Compact Integral Effects Test (CIET) experimental loop. SAM is a modern system analysis code being developed at Argonne National Laboratory for safety analysis of designs for advanced non-light water reactors (non-LWRs), such as sodium-cooled fast reactors, high-temperature gas-cooled reactors, and fluoride salt-cooled high-temperature reactors (FHRs). To support SAM code development for the wide range of non-LWR applications, it is of paramount importance to validate the code against experiments highly relevant to these reactor concepts. Additionally, the CIET facility, which was designed to reproduce the thermal-hydraulics response of FHRs under both forced- and natural-circulation conditions, has been identified and selected as one of the benchmark test facilities for SAM code validation. In this study, two sets of available CIET tests were selected for SAM code validation purposes, namely, power step change transient tests and steady-state natural-circulation tests. For all selected tests, SAM-predicted results show very good agreement with experimental data. The successful validation of SAM against these selected CIET experiments demonstrates that the computer code is well suited for thermal-hydraulics analysis of FHR designs.
Crystal Structure of Bicc1 SAM Polymer and Mapping of Interactions between the Ciliopathy-Associated Proteins Bicc1, ANKS3, and ANKS6
Head-to-tail polymers of sterile alpha motifs (SAM) can scaffold large macromolecular complexes. Several SAM-domain proteins that bind each other are mutated in patients with cystic kidneys or laterality defects, including the Ankyrin (ANK) and SAM domain-containing proteins ANKS6 and ANKS3, and the RNA-binding protein Bicc1. To address how their interactions are regulated, we first determined a high-resolution crystal structure of a Bicc1-SAM polymer, revealing a canonical SAM polymer with a high degree of flexibility in the subunit interface orientations. We further mapped interactions between full-length and distinct domains of Bicc1, ANKS3, and ANKS6. Neither ANKS3 nor ANKS6 alone formed macroscopic homopolymers in vivo. However, we report ANKS3 recruited ANKS6 to Bicc1, and the three proteins together cooperatively generated giant macromolecular complexes. Thus, the giant assemblies are shaped by SAM domains, their flanking sequences, and SAM-independent protein-protein and protein-mRNA interactions.