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Kumar, Vineet

Publications and source records attributed to Kumar, Vineet.

At least 19 records

Mic-hackathon 2024: hackathon on machine learning for electron and scanning probe microscopy

Microscopy is one of the primary sources of information on materials structure and functionality at the nanometer and atomic scales. The data generated through microscopy is often contained in well-structured datasets, enriched with extensive metadata and sample histories, although not always with the same level of detail or storage format. The broad incorporation of data management plans by major funding agencies ensures the preservation and accessibility of this data. However, deriving insights from these rich datasets remains challenging due to the lack of established code ecosystems, standardized benchmarks, and integration strategies. Correspondingly, the efficiency of data usage is very low, and time expenditures at the analysis stage are enormous. In addition to post-acquisition data analysis, the emergence of application programming interfaces by major microscope manufacturers now creates opportunities for real-time ML-based data analytics to enable automated decision making, and particularly ML-agent controlled real-time microscope operation. Despite these opportunities, there is a significant gap in integrating the ML community with the broader microscopy community, limiting the value that these methods bring to physics and materials discovery and materials optimization. Hackathons address these challenges by fostering collaboration between ML experts and microscopy professionals, encouraging the development of innovative solutions that leverage ML for microscopy and preparing the workforce of the future both for microscopy-intensive domains areas, instrument manufacturers, and ML scientists interested in real world applications for fundamental research, materials optimization, and manufacturing. The hackathon generated benchmark datasets and digital twins of microscopes that further contribute to the development of the field and establish data analysis ecosystems. All the codes can be found at GitHub(https://github.com/KalininGroup/Mic-hackathon-2024-codes-publication/tree/1.0.0.1) and Zenodo (https://zenodo.org/records/15579940).

97 MATHEMATICS AND COMPUTING↗

A Digital Twin Framework for Liquid-cooled Supercomputers as Demonstrated at Exascale

We present ExaDigiT, an open-source framework for developing comprehensive digital twins of liquid-cooled supercomputers. It integrates three main modules: (1) a resource allocator and power simulator, (2) a transient thermo-fluidic cooling model, and (3) an augmented reality model of the supercomputer and central energy plant. The framework enables the study of "what-if" scenarios, system optimizations, and virtual prototyping of future systems. Using Frontier as a case study, we demonstrate the framework's capabilities by replaying six months of system telemetry for systematic verification and validation. Such a comprehensive analysis of a liquid-cooled exascale supercomputer is the first of its kind. ExaDigiT elucidates complex transient cooling system dynamics, runs synthetic or real workloads, and predicts energy losses due to rectification and voltage conversion. Throughout our paper, we present lessons learned to benefit HPC practitioners developing similar digital twins. We envision the digital twin will be a key enabler for sustainable, energy-efficient supercomputing.

Brewer, Wes↗

Visualizing an Exascale Data Center Digital Twin: Considerations, Challenges and Opportunities

Digital twins are an excellent tool to model, visualize, and simulate complex systems, to understand and optimize their operation. In this work, we present the technical challenges of real-time visualization of a digital twin of the Frontier supercomputer.We show the initial prototype and current state of the twin and highlight technical design challenges of visualizing such a large High Performance Computing (HPC) system. The goal is to understand the use of augmented reality as a primary way to extract information and collaborate on digital twins of complex systems. This leverages the spatio-temporal aspect of a 3D representation of a digital twin, with the ability to view historical and real-time telemetry, triggering simulations of a system state and viewing the results, which can be augmented via dashboards for details. Finally, we discuss considerations and opportunities for augmented reality of digital twins of large-scale, parallel computers.

Maiterth, Matthias↗

Thermo-Fluid Modeling Framework for Supercomputer Digital Twins: Part 1, Demonstration at Exascale

A thermo-fluid modeling framework is being developed for ExaDigiT---an open-source framework for developing comprehensive digital twins of liquid-cooled supercomputers. The work is being conducted in two parts, and discussion is divided into two companion papers. The work documented in this paper focuses on the development of a cooling system library in Dymola for the Frontier supercomputer at Oak Ridge National Laboratory. The second part, outlined in a companion paper, focuses on a templating structure called Auto-CSM for easily creating model-agnostic, physics-based thermo-fluid cooling system models for liquid-cooled supercomputers using a text-based schema. The cooling model is being developed using primarily the open-source Transient Simulation Framework of Reconfigurable Models (TRANSFORM) library. The library follows the templating architecture developed within the TRANSFORM library for modeling subsystems. A full-system validation was performed to validate a very simple model that is integrated with the system controls, and the results are presented herein.

Kumar, Vineet↗

Thermo-Fluid Modeling Framework for Supercomputing Digital Twins: Part 2, Automated Cooling Models

The development of digital twins for the purpose of improving the energy efficiency of supercomputing facilities is a non-trivial endeavor that is complicated by the difficulty of creating physics-based thermo-fluid cooling system models (CSMs). Within ExaDigit---an open-source framework for liquid-cooled supercomputing digital twins---a thermo-fluid modeling framework is being developed. This effort has been segmented into two with two companion papers describing each portion of the overall effort. Part 1 focuses on the development of a cooling system library in Dymola for the Frontier supercomputer at Oak Ridge National Laboratory {\cite{Kumar2024}. Part 2, this paper, describes an effort to create a template-based auto-generation methodology for CSMs, called \textit{AutoCSM}. In this paper, an overview of the initial AutoCSM architecture and workflow is provided, along with a practical example using the Oak Ridge Leadership Computing Facility's (OLCF) Frontier supercomputer CSM. AutoCSM will (1) improve ExaDigiT's user accessibility by providing a flexible workflow for modularizing the creation of the CSM system and control logic, (2) decrease the development time of CSMs, and (3) standardize the method for incorporating CSMs into the ExaDigiT framework.

Greenwood, Scott↗

Sister Rod Destructive Examinations (FY23) Appendix I: SNF Aerosols Released During Rod Fracture

This report documents work performed under the Spent Fuel and Waste Disposition’s Spent Fuel and Waste Science and Technology program for the US Department of Energy (DOE) Office of Nuclear Energy (NE). This work was performed to fulfill Level 3 Milestone M3SF-23OR010201026, “FY23 M3 draft report on results from testing in FY23,” within work package SF-23OR01020102 and is an updated to the work reported in M2SF-23OR010201024, M2SF-22OR010201047, M2SF-21OR010201032, M2SF-19ORO010201026, and M2SF-19OR010201028. As a part of the DOE NE High Burnup Spent Fuel Data Project, Oak Ridge National Laboratory (ORNL) is performing destructive examinations (DEs) of high burnup (HBU) (>45 GWd/MTU) spent nuclear fuel (SNF) rods from the North Anna Nuclear Power Station operated by Dominion Energy. The SNF rods, called sister rods or sibling rods, are all HBU and include four different kinds of fuel rod cladding: standard Zircaloy-4 (Zirc-4), low-tin Zirc-4, ZIRLO, and M5. The DEs are being conducted to obtain a baseline of the HBU rods’ condition before dry storage and are focused on understanding overall SNF rod strength and durability. Fuel rods and defueled cladding will be tested to derive material properties. Although the data generated can be used for multiple purposes, one primary goal for obtaining the post-irradiation examination data and the associated measured mechanical properties is to support SNF dry storage licensing and relicensing activities by (1) addressing identified knowledge gaps and (2) enhancing the technical basis for post-storage transportation, handling, and subsequent disposition.This report documents the status of the ORNL Phase 1 DE activities related to the collection of SNF aerosol particles released during fuel rod fracture in 4-point bending in Phase 1 of the sister rod test program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

CTF Validation and Verification: Version 4.4

Coolant-Boiling in Rod Arrays- Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for light water reactor (LWR) analysis. It uses a two-fluid, three-field (i.e., fluid film, fluid drops, and vapor) modeling approach. Both subchannel and 3D Cartesian forms of nine conservation equations are available for LWR modeling. The code was originally developed by Pacific Northwest Laboratory in 1980 and has been used and modified by several institutions over the last several decades. COBRA-TF is also used at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently became the CTF. One part of the improvement process includes validating the methods in CTF. This document seeks to provide a certain level of certainty and confidence in the predictive capabilities of the code for the scenarios it was designed to model—rod bundle geometries with operating conditions that are representative of prototypical pressurized water reactor (PWR)s and boiling water reactor (BWR)s in both normal and accident conditions. This is done by modeling a variety of experiments that simulate these scenarios and then presenting a qualitative and quantitative analysis of the results that demonstrates the accuracy to which CTF is capable of capturing specific quantities of interest.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Simulations of Water Flow in Relation to a Steady Criticality in an Unsaturated Alluvial Repository

Oak Ridge National Laboratory (ORNL) is examining the conditions under which a criticality event could be ruled out for large packages placed in an unsaturated alluvial repository. This work specifically examines the water level in a stylized waste package that is assumed (1) to fail on the top, and (2) to empty as water is driven away—not by boiling—but by fluid flow phenomena driven by thermal gradients. This analysis uses the PFLOTRAN code package. Specifically, this year’s work includes examination of the heat rate at which water is driven away for various percolation rates using the same assumptions listed in the 2022 annual report. The STANDARDS (formerly UNF-ST&DARDS) package has predicted dual-purpose canister (DPC) neutron multiplication factors (k-effectives) ranging above 1.1 (unitless) with failed components. The DPC designs were not created with the intent to use for disposal purposes. Emplacing such packages may be worth consideration if it can be shown that criticality is either extremely unlikely or of very low consequence to the repository’s safety case. This work aims to help establish hydrologic boundary conditions for a highly hypothetical, highly stylized subsurface criticality event. The approach to critical is assumed to be slow, producing steady heating rates under a few kilowatts. For a DPC containing capillary media, the simulated power required for dry-out was proportional to the percolation rate but was unaffected by the size of a large breech on top of the DPC. Results for single cases with no capillary media in the DPC suggest that higher infiltration rates may be required in those cases to cause flooding. Bounding mechanisms and assumptions must be identified and characterized further by performing additional perturbations to various input parameters to demonstrate robustness of the results. This might be accomplished by examining responses to power pulses to determine the system transfer function required to enable a reduced order feedback model.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Digital Twin Development of FASTR

This work package is focused on creating a digital twin (DT) of the Facility to Alleviate Salt Technology Risks (FASTR) experiment. FASTR is a high-profile facility tasked with maturing molten salt applications such as liquid salt energy storage, concentrated solar power facilities, and molten salt cooling systems supporting other advanced reactor technologies, all of which may be incorporated as components within the Integrated Energy Systems (IES) program. As part of creating a digital twin (DT), verification and validation (V&V) has been performed for the physics-based model, and gaps have been identified. Additionally, a preliminary integration of the FASTR model has been completed with the existing physics-based model of the Thermal Energy Distribution System (TEDS)/Microreactor AGile Non-nuclear Experimental Testbed (MAGNET) facility at Idaho National Laboratory (INL). A Functional Mock-up Unit (FMU) of the physics-based system model and a reduced-order model (ROM) were both used to test for a preliminary hardware in the loop operation when the physical loop was offline. Future tasks could include improving the physics-based model to better match the available experimental data, improving the hardware in the loop integration, and improving the integration with the TEDS model.

14 SOLAR ENERGY↗

Computational modeling and validation of a modified Marple cascade impactor

Oak Ridge National Laboratory (ORNL) is investigating respirable aerosol fractions from failed high-burnup (HBU) commercial spent nuclear fuel (CSNF) rods (Montgomery et al., 2022). The work aims to characterize the source term of radioactive aerosols that could result from mechanical failure and handling of failed fuel rods during storage and/or transportation. The experiment involves capturing and characterizing aerosols from a four-point bending experiment of fueled rod segments at ORNL’s Irradiated Fuels Examination Laboratory (IFEL). For this, a Marple cascade impactor (Series 290) with the ability to collect particles up to aerodynamic equivalent diameters of ~15 μm was tested for feasibility. The commercially available Marple cascade impactor design was modified for the experiment, where the cascade inlet was replaced with a 3D printed inlet nozzle. Collection efficiency curves were then generated with the modified impactor, and the cascade’s performance was tested using ISO dust capture experiments followed by SEM analysis of the collection and computational modeling. The current work highlights the performance testing and experimental validation of this modified Marple Impactor for spent nuclear fuel aerosol collection.

Kumar, Vineet↗

HIGH-LOW FIDELITY THERMAL HYDRAULIC COUPLING USING AI/MACHINE LEARNING ALGORITHMS

The primary goal of the US Department of Energy (DOE) office of Nuclear Energy Integrated Energy Systems (IES) program is to develop the tools and framework for coupling multi-scale and multi-physical thermal and electrical energy usage and storage systems. High- and low-fidelity (high–low) coupling is a key feature of multi-scale, multi-component systems and has been an important focus of research in the nuclear energy community for the past two decades. An essential feature of demonstrating the capability to couple high-fidelity and low-fidelity systems for real-time applications are surrogate/reduced order models (ROM). For the purposes of this study, surrogate models are essentially Blackbox models, typically developed using supervised Machine learning (ML) algorithms. The surrogate models can be used to mimic the response of high-fidelity models to represent large historical datasets and coupled with more general low-fidelity system models distributed as Functional Mock-up Interface (FMI) or Functional Mock-up Units (FMU) modules. The example is demonstrated with Spallation Neutron Source (SNS) First Target Station flow loop data. The flow loop is a liquid mercury loop with a pump, piping, heat exchange, and internal heat generation in the target window. This work elucidates some of the potential benefits and future needs of developing tools for high–low system coupling of energy systems.

Williams, Wesley↗

Sister Rod Destructive Examinations (FY22) Appendix I: SNF Aerosols Released During Rod Fracture

As a part of the DOE NE High Burnup Spent Fuel Data Project, Oak Ridge National Laboratory (ORNL) is performing destructive examinations (DEs) of high burnup (HBU) (>45 GWd/MTU) spent nuclear fuel (SNF) rods from the North Anna Nuclear Power Station operated by Dominion Energy. The SNF rods, called sister rods or sibling rods, are all HBU and include four different kinds of fuel rod cladding: standard Zircaloy-4 (Zirc-4), low-tin Zirc-4, ZIRLO, and M5. The DEs are being conducted to obtain a baseline of the HBU rods’ condition before dry storage and are focused on understanding overall SNF rod strength and durability. Fuel rods and defueled cladding will be tested to derive material properties. Although the data generated can be used for multiple purposes, one primary goal for obtaining the post-irradiation examination data and the associated measured mechanical properties is to support SNF dry storage licensing and relicensing activities by (1) addressing identified knowledge gaps and (2) enhancing the technical basis for post-storage transportation, handling, and subsequent disposition. This report documents the status of the ORNL Phase 1 DE activities related to the collection of SNF aerosol particles released during fuel rod fracture in 4-point bending in Phase 1 of the sister rod test program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

GDSA - Modeling and Integration – ORNL: PFLOTRAN modeling

This report summarizes work done at Oak Ridge National Laboratory (ORNL) related to post-closure criticality consequence analysis of dual-purpose canister (DPC) direct disposal in unsaturated alluvium. PFLOTRAN software was used to model the behavior of a breached DPC with low water infiltration rates and unsaturated conditions in alluvial deposits such that a low-power criticality event occurs with a focus on thermal hydrological constraints on criticality timing and power output. This summary describes initial exploration of those thermal hydrological processes and of the long-term average power output from a criticality event that could be sustained without driving water out of the DPC package and thereby terminating the criticality event. The objectives are (1) to identify, for different groundwater infiltration rates, the time at which the DPC fills with water sufficiently to potentially initiate criticality; (2) to bound the power output that could be produced by a criticality event that would thermally drive water out of the package at various percolation rates; and (3) provide an estimate of how the size of a package breach affects the water infiltration and therefore the possibility timing of criticality.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Improvement of two-phase closure models in CTF using Bayesian inference

Under the Consortium for Advanced Simulation of Light Water Reactors (CASL) program, extensive capabilities have been developed in CTF to analyze light-water reactors (LWRs) for normal operating conditions, departure from nucleate boiling (DNB), and system transients. However, further improvements are required in the modeling and simulation of boiling water reactors (BWRs), which is a focus of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In this work, CTF validation results were used to optimize selected modeling coefficients by calibrating to experimental data using a Bayesian inference approach. Here, calibration studies were conducted to improve (vapor) void fraction prediction without worsening the two-phase pressure drop prediction, as well as to improve the two-phase pressure drop prediction. Calibration was performed for interfacial drag and wall shear models. Surrogates were developed to alleviate the computational expense required for sampling the parameter space using Markov chain Monte Carlo (MCMC). An assessment performed with calibrated models demonstrated an improvement of CTF in its prediction of key parameters such as void fraction and two-phase pressure drop.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗