Results for “mock” — Page 9

DOE OSTI2022

Accurate relativistic observables from postprocessing light cone catalogs

We introduce and study a new scheme to construct relativistic observables from postprocessing light cone data. This construction is based on a novel approach, LC-metric, which takes general light cone or snapshot output generated by arbitrary N-body simulations or emulations and solves the linearized Einstein equations to determine the spacetime metric on the light cone. We find that this scheme is able to determine the metric to high precision, and subsequently generate accurate mock cosmological observations sensitive to effects such as post-Born lensing and nonlinear integrated Sachs-Wolfe contributions. By comparing to conventional methods in quantifying those general relativistic effects, we show that this scheme is able to accurately construct the lensing convergence signal. We also find that the accuracy of this method in quantifying the integrated Sachs-Wolfe effects in the highly nonlinear regime outperforms conventional methods by an order of magnitude. Furthermore, this scheme opens a new path for exploring and modeling higher-order and nonlinear general relativistic contributions to cosmological observables, including mock observations of gravitational lensing and the moving lens and Rees-Sciama effects.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Analytic Gaussian covariance matrices for galaxy N-point correlation functions

Here, we derive analytic covariance matrices for the N-point correlation functions (NPCFs) of galaxies in the Gaussian limit. Our results are given for arbitrary N and projected onto the isotropic basis functions given by spherical harmonics and Wigner 3j symbols. A numerical implementation of the 4PCF covariance is compared to the sample covariance obtained from a set of lognormal simulations, Quijote dark matter halo catalogues, and MultiDark-Patchy galaxy mocks, with the latter including realistic survey geometry. The analytic formalism gives reasonable predictions for the covariances estimated from mock simulations with a periodic-box geometry. Furthermore, fitting for an effective volume and number density by maximizing a likelihood based on Kullback-Leibler divergence is shown to partially compensate for the effects of a nonuniform window function. Our result is recently shown to facilitate NPCF analysis on a realistic survey data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Hyper Suprime-Cam Year 3 results: Measurements of clustering of SDSS-BOSS galaxies, galaxy-galaxy lensing, and cosmic shear

Here we utilize the Sloan Digital Sky Survey Baryon Oscillation Spectroscopic Survey (SDSS-BOSS) galaxies and its overlap with approximately 416 sq degrees of deep grizy-band imaging from the Subaru Hyper Suprime-Cam Survey (HSC). We perform measurements of three two-point correlations which form the basis of the cosmological inference presented in our companion papers, Miyatake et al. and Sugiyama et al. We use three approximately volume limited subsamples of spectroscopic galaxies by their i-band magnitude from the SDSS-BOSS: LOWZ (0.1 < z < 0.35), CMASS1 (0.43 < z < 0.55) and CMASS2 (0.55 < z < 0.7), respectively. We present high signal-to-noise ratio measurements of the projected correlation functions of these galaxies, which is expected to be proportional to the projected matter correlation function on large scales with a proportionality constant dependent on the bias of galaxies. In order to help break the degeneracy between the amplitude of the matter correlation and the bias of these spectroscopic galaxies, we use the distortions of the shapes of fainter galaxies in HSC due to weak gravitational lensing, to measure the galaxy-galaxy lensing signal, which probes the projected galaxy-matter cross-correlation function of the SDSS-BOSS galaxies. We also measure the cosmic shear correlation functions from HSC galaxies which is related to the projected matter correlation function. We demonstrate the robustness of our measurements by subjecting each of them to a variety of systematic tests. Our use of a single sample of HSC source galaxies is crucial to calibrate any residual systematic biases in the inferred redshifts of our galaxies. We also describe the construction of a suite of mocks: (i) spectroscopic galaxy catalogs which obey the clustering and abundance of each of the three SDSS-BOSS subsamples, and (ii) galaxy shape catalogs which obey the footprint of the HSC survey and have been appropriately sheared by the large-scale structure expected in a Lambda Cold Dark Matter model. Finally, we use these mock catalogs to compute the covariance of each of our observables.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Dissecting a strongly coupled scalar nucleon

We continue our investigation of the stress within a strongly coupled scalar nucleon, and now dissect the gravitational form factors into contributions from its constituents, the (mock) nucleon and the (mock) pion. The computation is based on a nonperturbative solution of the scalar Yukawa model in the light-front Hamiltonian formalism with a Fock sector expansion, including up to one nucleon and two pions. By employing the “good currents” T i + + , T i + − and T i 12 , we extract the full set of gravitational form factors A i , D i , c ¯ i without the contamination of the spurious form factors and free of uncanceled UV divergences. With these results, we decompose the mass of the system into its constituents and compute the matter and mechanical radii, gaining insights into the strongly coupled system. Published by the American Physical Society 2024

Cao, Xianghui (ORCID:0009000359096713)↗

DOE OSTI2024

Optimizing Transmission of Acoustic Signals to Monitor Internal Conditions of Canisters for Dry Storage of Commercial Spent Nuclear Fuel

Safe storage of spent nuclear fuel (SNF) is critical to the nuclear fuel cycle and the future of nuclear energy. In the United States, SNF is stored primarily via two methods regulated by the U.S. Nuclear Regulatory Commission: wet storage in SNF pools and dry storage in dry cask storage systems (DCSSs). After about five years of cooling in spent fuel pools, the fuel assemblies are transferred into DCSSs, and the systems are filled with helium and sealed by welding. Deterioration of conditions inside of a DCSS is reflected in changes in the internal gas properties; this motivates the development of acoustic techniques to monitor internal gas properties, over extended storage periods, using sensors mounted on the exterior of the storage packages. However, a major challenge in collecting acoustic signals is the impedance mismatch between the steel canister shell and the gas. Only a small fraction of the ultrasonic signal can be transmitted through the gas medium. This paper documents experimental studies conducted on a full-scale canister mock-up to capture the gas-borne signals. Damping materials were pasted on the outside, and blocking and unblocking tests were conducted to identify the gas-borne signal. The results show that the excitation frequency plays an important role in maximizing the gas-borne signals. The gas-borne signal was successfully detected at around the theoretical time-of-flight. A high signal-to-noise ratio was achieved in the measurements. Next, the acoustic impedance matching layers were introduced, and the gas signal was drastically improved compared with that using no AIM layers.

Spent nuclear fuel (SNF), Canisters, Internal cond↗

DOE OSTI2026

Evaluating isoprenol production using the IPP-bypass pathway in the oleaginous yeast Rhodosporidium toruloides

Background To strengthen the national energy supply, there is an increasing demand for domestically generated aviation fuels. Bio-derived advanced aviation fuels offer the opportunity to meet this domestic need while presenting a unique opportunity to investigate the production of novel aviation fuels. Isoprenol, a chemical precursor to such novel fuels, has been shown to be a biologically producible compound in model organisms, but its bio-producibility needs to be further explored in organisms more compatible with industrial bioproduction. Results In this work, we evaluate isoprenol production using the promising bioproduction yeast, Rhodosporidium toruloides. First, we show successful isoprenol production using the IPP-bypass pathways most successful in laboratory strains of E. coli and S. cerevisiae. Next, we demonstrate that increased flux through the mevalonate pathway only modestly increases isoprenol titers. Using proteomics, we identified a potential bottleneck in production at the final step in the IPP-bypass pathway and explored alternative enzymes for this step. Finally, the top three strains of R. toruloides were evaluated in sorghum hydrolysates generated using cholinium lysinate. Through this work, 93.1 mg/L of isoprenol was produced in mock medium and 27.3 mg/L in sorghum hydrolysates. Conclusion Together these results lay the foundation for future work for the production of isoprenol from bioproduction crops.

Advanced aviation fuel↗

DOE OSTI2024

Effects of machine learning errors on human decision-making: manipulations of model accuracy, error types, and error importance

Abstract This study addressed the cognitive impacts of providing correct and incorrect machine learning (ML) outputs in support of an object detection task. The study consisted of five experiments that manipulated the accuracy and importance of mock ML outputs. In each of the experiments, participants were given the T and L task with T-shaped targets and L-shaped distractors. They were tasked with categorizing each image as target present or target absent. In Experiment 1, they performed this task without the aid of ML outputs. In Experiments 2–5, they were shown images with bounding boxes, representing the output of an ML model. The outputs could be correct (hits and correct rejections), or they could be erroneous (false alarms and misses). Experiment 2 manipulated the overall accuracy of these mock ML outputs. Experiment 3 manipulated the proportion of different types of errors. Experiments 4 and 5 manipulated the importance of specific types of stimuli or model errors, as well as the framing of the task in terms of human or model performance. These experiments showed that model misses were consistently harder for participants to detect than model false alarms. In general, as the model’s performance increased, human performance increased as well, but in many cases the participants were more likely to overlook model errors when the model had high accuracy overall. Warning participants to be on the lookout for specific types of model errors had very little impact on their performance. Overall, our results emphasize the importance of considering human cognition when determining what level of model performance and types of model errors are acceptable for a given task.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

AbacusSummit Halo Light Cone Catalogs

This is a set of halo light cone catalogs from the AbacusSummit suite of cosmological N-body simulations (abacussummit.readthedocs.io/). They are a value-added data product provided by post-processing the simulation output. The main application of the halo light cone catalogs is the construction of realistic mock galaxy catalogues and weak lensing maps on the sky. The algorithm (described in Hadzhiyska et al. 2021) associates CompaSO halos from 29 redshift epochs spanning z = 0.1-2.5 with their particles at the time of light-cone crossing. It then records the halo and particle information into an easily accessible product, which can be read with the CompaSO reader. The 25 base resolution boxes at fiducial cosmology have a halo light cone catalog covering an octant of the sky to z approx 0.8 and about 2000 deg2 extending to z approx 2.4. The huge boxes provide light cone information of the full sky until z approx 2.18 and extend further towards the corners of the box (available until z = 2.25). Galaxy mock catalogs on the sky can be generated easily though the AbacusHOD script providing an extended HOD framework (see Yuan et al. 2021, for details), which has been modified to work with the halo light cone catalogs. The available tracers are luminous red galaxies (LRGs), emission-line galaxies (ELGs), and quasi-stellar objects (QSOs).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Muon-neutrino disappearance with multiple liquid argon time projection chambers in the Fermilab Booster neutrino beam

The Short Baseline Neutrino (SBN) program consists of three liquid argon time projection chamber (LArTPC) experiments: SBND, MicroBooNE and ICARUS, with 110 m, 470 m and 600 m baselines respectively. The detectors are located in the Booster Neutrino Beam (BNB) at Fermilab which has a peak energy around 0.7 GeV and contains predominantly muon neutrinos. The baseline and energy range of the SBN program is conducive to measuring neutrino oscillation parameters under various sterile neutrino hypotheses. Sterile neutrinos have been proposed as a possible solution to the numerous short baseline anomalies. The proposed particles must be sterile in nature such that they do not interact via the weak force, however they may undergo oscillations with the active neutrino flavours. Their existence may consequently be confirmed through measurements of the appearance and disappearance of the active flavours. The analyses presented in this thesis aimed to calculate and understand the sensitivity of the SBN program to measuring the ?µ disappearance parameters under the (3+1) sterile neutrino oscillation hypothesis. The sensitivity of SBN to measuring the ?µ disappearance sterile oscillation parameters, sin2 2?µµ, ?m2 41, was calculated through semi-exclusive joint fits of the ?µ CC 0p and ?µ CC Other reconstructed neutrino energy spectra. The first iteration used truth-level Monte Carlo (MC) events, and determined that the 5s SBN sensitivity is comparable to the 90% MINOS/MINOS+ confidence level and supersedes the 90% MiniBooNE confidence level across entire phase space. Semi-exclusive joint fits of the aforementioned sample spectra were performed between the MC and multiple mock data sets in SBND. This analysis assessed the accuracy with which the near detector can disentangle systematic from physics effects in the oscillation analysis. The result was a 5.49% discrepancy between the ICARUS Monte Carlo and mock data event rates, when the systematic constraints from the near detector fit were extrapolated to the far detector. The second iteration of the SBN sensitivity analysis involved the application of an event selection procedure developed in SBND, following the full reconstruction chain. ?µ CC 0p events were selected from sample of neutrinos with 84.5% efficiency and 84.3% purity. The sterile neutrino sensitivity was determined once more at the near detector with these samples, and was shown to be consistent with the truth-level studies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Differentiable Predictions for Large Scale Structure with SHAMNet

In simulation-based models of the galaxy-halo connection, theoretical predictions for galaxy clustering and lensing are typically made based on Monte Carlo realizations of a mock universe. In this paper, we use Subhalo Abundance Matching (SHAM) as a toy model to introduce an alternative to stochastic predictions based on mock population, demonstrating how to make simulation-based predictions for clustering and lensing that are both exact and differentiable with respect to the parameters of the model. Conventional implementations of SHAM are based on iterative algorithms such as Richardson-Lucy deconvolution; here we use the JAX library for automatic differentiation to train SHAMNet, a neural network that accurately approximates the stellar-to-halo mass relation (SMHM) defined by abundance matching. In our approach to making differentiable predictions of large-scale structure, we map parameterized PDFs onto each simulated halo, and calculate gradients of summary statistics of the galaxy distribution by using autodiff to propagate the gradients of the SMHM through the statistical estimators used to measure one- and two-point functions. Our techniques are quite general, and we conclude with an overview of how they can be applied in tandem with more complex, higher-dimensional models, creating the capability to make differentiable predictions for the multi-wavelength universe of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

The Dark Energy Spectrographic Instrument (DESI) Optical Fiber System

The specific research of the DESI project is to study in detail the expansion history of the Universe over the past 10 billion years. In order to do this, the project designed, fabricated, tested and commissioned the DESI instrument which has been deployed at the Mayall Telescope at the Kitt Peak National Observatory near Tucson, Arizona. The DESI project was conducted by approximately 30 US and foreign national laboratories. The complete instrument includes a prime focus corrector assembly, a focal plane with 5,000 optical fibers whose position can be set by robotic positioners, and ten spectrographs. Each spectrograph can accommodate the light from 500 fibers and include three color channels that are illuminated by a common collimator mirror and other planar transfer optics. In order for this entire system to work, optical fibers are required to connect each positioner to the spectrographs. Our CRADA with Durham University in the UK provided the 10 crucial fiber cables required to connect the DESI focal plane to the 10 spectrographs. The key major goals of this CRADA were achieved. Survey planning was another key component to the Durham contribution. Drs. Frenk, Baugh, Cole, Edge, Lacey, Li, Lucey, Massey, Metcalfe, Norberg and Shanks were all important contributors to the working groups to which they were assigned. Their work to implement emission lines and QSO in lightcone mocks, mocks for non-standard cosmologies/modified gravity, optimization of completeness of BGS in crowded regions and extended source photometry have been vital in the early planning for targets during commissioning. The major role in the project involved Dr. Ray Sharples and his team. They provided a significant portion of the design, fabrication and testing of the optical fiber system. In particular, they were responsible for the design, production of engineering drawings, component procurements, and fabrication of the 10 DESI Science fiber cables. Working in close collaboration with Dr. Claire Poppett, they also designed and fabricated the slit assemblies, the specialized termination of the groups of 500 fibers which plug into the spectrographs.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Status Report on IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENviroment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report provides discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity is maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In addition to the investigative work being conducted on FMUs and FMIs, a series of updates to the hybrid repository has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and opensourcing the HYBRID repository with an integrated regression system.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2020

Coupling of CTF and TRANSFORM using the Functional Mockup Interface

An in-memory coupling between the sub-channel thermal hydraulics code COBRA-TF (CTF), which is included in the Virtual Environment for Reactor Applications (VERA), and the systems code Transient Simulation Framework of Reconfigurable Models (TRANSFORM) was developed in this work. Data exchange is accomplished by using the Functional Mock-Up Interface (FMI), an open standard for coupling dynamic systems models together. The FMI-based coupling necessitated the development of a novel FORTRAN wrapper for communicating with Functional Mock-Up Units. This wrapper will facilitate future FMI-based code couplings with other FORTRAN-based programs. CTF-TRANSFORM is exercised on a simplified Molten Salt Reactor Experiment (MSRE) model in steady-state and transient configurations. The coupled CTF-TRANSFORM model is shown to predict core temperature deltas similar to those available in historical MSRE operational data and is shown to be robust to fast power transients.The coupling paves the way to performing sensitivity and design studies impossible with VERA/CTF alone, in which secondary and tertiary loop operating conditions and design parameters may be perturbed and their impact on the core operating conditions studied.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Model 9975 O Ring Fixture LongTerm Leak Performance (FY2021 Status Report)

Leak testing experiments to monitor the aging performance of Viton® GLT and GLT-S O-rings used in the model 9975 shipping package has been ongoing since 2004 at Savannah River National Laboratory. Seventy tests using mock-up 9975 primary containment vessels (PCVs) with GLT O-rings were assembled and heated to temperatures ranging from 200 to 450 °F. Due to material substitution, fourteen tests with GLT-S O-rings were initiated in 2008 and heated to temperatures ranging from 200 to 400 °F. The conditioning temperatures are elevated compared to the calculated maximum O-ring temperature in a 9975 package in storage, 158 °F, to accelerate aging and enable observations of O-ring failures in a reasonable time frame. The fixtures are leak tested periodically and all GLT O-ring fixtures aging at 350 °F or above have failed to maintain a leak-tight seal. Eight GLT O-ring fixtures aging at 300 °F have failed after 2.8 to 5.7 years at temperature while the remaining fixtures at 300 °F were retired from testing following more than five years without failure. There has been one GLT O-ring fixture which failed after 13.4 years aging at 200 °F. However, 19 other GLT O-rings aging at 200 °F have remained leak-tight for over 14 years and remain in test. No failures have yet been observed in GLT O-ring fixtures aging at 270 °F for 9.5 years. All GLT-S O-ring fixtures aging at 300 °F or above have failed their leak test. No failures have yet been observed in GLT-S O-ring fixtures aging at 200 and 250 °F for 11.5 years. Data from the O-ring fixtures are generally consistent with results from compression stress-relaxation testing, and provide confidence in the predictive models based on those results. However, uncertainty exists in extrapolating these elevated temperature results to the lower temperatures of interest for normal storage in K-Area Complex (KAC). Oxygen consumption testing, which includes results from temperatures near KAC normal storage temperatures, is ongoing to provide further confidence and corroborate these extrapolations. The collective data from these test efforts suggest the minimum O-ring service life at KAC normal storage conditions should be at least 34 years for GLT and GLT-S O-rings. Measurement of compression set in O-rings removed from failed fixtures, compared to that from KAC surveillance O-rings, indicate significant margin remains for O-rings still in service in 9975 packages in KAC. Aging and periodic leak testing will continue for the remaining 26 mock-up PCV fixtures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

42 ENGINEERING↗

DOE OSTI2021

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

14 SOLAR ENERGY↗

DOE OSTI2021

Status Report on the INL IES Plug-and-Play Framework

This report discusses the advancements and status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and usage, which aims to ease the sharing and simulation of complex dynamic models. This report discusses the FMI/FMU development advancements, overall focusing on the deployment of methodologies for RAVEN to export and use FMI/FMU of both Python-based models and advanced AI-constructed algorithms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Radiation Hardened Foam Cold Test Plan – Phase-I: Foam Adhesion, Contamination Fixation, Moisture Stresses, Pipe Cutting, and Thermal Profile Testing

This document outlines the Phase-I test objectives and implementation plan for a down-selective foam fixative technology intended to facilitate activities in support of the Savannah River Site (SRS) F/H labs deactivation and decommissioning (D&D) efforts. It is a collaborative effort between Savannah River National Laboratory (SRNL), Florida International University (FIU), and the SRS F/H labs team intended to test and evaluate the potential of an intumescent, fire-retardant foam in mitigating the release of contamination during dismantling operations on radioactively contaminated piping in legacy facilities. The cold test plan addresses specific requirements highlighted by site and safety personnel and will be executed in FIU’s Outdoor Test and Evaluation Facility using a mock-up that replicates the operational conditions at the proposed hot test location at F/H labs. Results from the cold test plan will inform the hot test at F/H labs, which will use the foam fixative to confine and/or isolate residual contamination within a 3-dimensional void space of Hastelloy C-22 piping designated for removal from the site and transported to a proper disposal facility. Phase-I testing will address eight test objectives: (1) evaluation of the adhesion and bonding properties of foam fixative in piping, (2) evaluation of the adhesion of the foam fixative in piping under varying moisture conditions, (3) determination of the heat profile of the foam fixative during curing, (4) determination of the relationship between pipe diameter and foam fixative quantity, (5) determination of the internal pipe pressure after foam deployment and curing, (6) development of a leak test standard operating procedure to test for the effectiveness of the foam plug, (7) initiation of a literature review to determine if using a hot tap is a viable method to deliver foam into piping, and (8) initiation of a 10-foot mock up test that will be used in Phase-II cold testing. The cold test will be conducted at FIU and all testing activities will comply with SRNL Conduct of R&D Protocols (SRNL-IM-2020-00019).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗