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Model-based Design Optimization to Achieve the Performance Goals (16.0 SEER/9.5 HSPF), Developing Heat Pump by Using Low-GWP Refrigerants and 5 mm Diameter Tubes

Usage of low-GWP refrigerants can reduce the Green House Gas (GHG) emission of HVAC systems. Our research in previous milestone report has shown that using heat exchangers with 5 mm diameter tubes instead of 9 mm diameter tubes is a promising solution to meet the performance goals of heat pump using low-GWP refrigerants. In addition, the 5mm tube heat exchangers can lead to lower system refrigerant charge and as a result, reduce environmental impact further. However, shifting to small tube diameters requires in-depth heat exchanger design optimization to adapt to the transition to low-GWP refrigerants. In the 2nd quarter of FY21, we conducted multi-objective optimizations using Particle Swarm Optimization algorithm on a residential 5-ton air source heat pump to investigate the potential system performance improvements and material savings. 4 low-GWP refrigerants, ARM20A, ARM20B, R454A and R454C are investigated in this study. The objectives of the optimization are to minimize the heat pump material cost and to maximize the system performance simultaneously. As a result, the HXs material cost is reduced by up to 77% according to the copper and aluminum material price in current market. Under heating mode operation, the smart 4-way valve guarantees that the optimal low-GWP systems maintain or outperform the heating performance of the R410A baseline system. The model-based design optimization yields 18.3-18.9 SEER and 10.6-11.9 HSPF for optimal systems using different low-GWP refrigerants. The initial performance goals (16.0 SEER/9.5 HSPF) are achieved. Furthermore, up to 50% system refrigerant charge reduction is possible in the optimized low-GWP heat pump system using ARM20B. And 91%-95% predicted life-time direct CO 2 emission reduction is achieved by using the optimal 5mm tube low-GWP heat pumps. The significant material saving, charge reduction and direct CO 2 emission reduction help in reducing the environmental impacts of heat pump systems. The optimal heat exchangers resulting from this research can fit into the original baseline indoor and outdoor fan-coil unit. This can reduce the retrofitting effort by minimizing the change in manufacturing and installation of the heat pumps and guarantee the compatibility with end-users’ house structure. Finally, the new products can be easily accepted by manufacturers and end-users.

42 ENGINEERING↗

Integrated System and Application Continuous Performance Monitoring and Analysis Capability

Scientific applications run on high-performance computing (HPC) systems are critical for many national security missions within Sandia and the NNSA complex. However, these applications often face performance degradation and even failures that are challenging to diagnose. To provide unprecedented insight into these issues, the HPC Development, HPC Systems, Computational Science, and Plasma Theory & Simulation departments at Sandia crafted and completed their FY21 ASC Level 2 milestone entitled "Integrated System and Application Continuous Performance Monitoring and Analysis Capability." The milestone created a novel integrated HPC system and application monitoring and analysis capability by extending Sandia's Kokkos application portability framework, Lightweight Distributed Metric Service (LDMS) monitoring tool, and scalable storage, analysis, and visualization pipeline. The extensions to Kokkos and LDMS enable collection and storage of application data during run time, as it is generated, with negligible overhead. This data is combined with HPC system data within the extended analysis pipeline to present relevant visualizations of derived system and application metrics that can be viewed at run time or post run. This new capability was evaluated using several week-long, 290-node runs of Sandia's ElectroMagnetic Plasma In Realistic Environments ( EMPIRE ) modeling and design tool and resulted in 1TB of application data and 50TB of system data. EMPIRE developers remarked this capability was incredibly helpful for quickly assessing application health and performance alongside system state. In short, this milestone work built the foundation for expansive HPC system and application data collection, storage, analysis, visualization, and feedback framework that will increase total scientific output of Sandia's HPC users.

97 MATHEMATICS AND COMPUTING↗

Integrated System and Application Continuous Performance Monitoring and Analysis Capability (Final)

Scientific applications run on high-performance computing (HPC) systems are critical for many national security missions within Sandia and the NNSA complex. However, these applications often face performance degradation and even failures that are challenging to diagnose. To provide unprecedented insight into these issues, the HPC Development, HPC Systems, Computational Science, and Plasma Theory & Simulation departments at Sandia crafted and completed their FY21 ASC Level 2 milestone entitled "Integrated System and Application Continuous Performance Monitoring and Analysis Capability." The milestone created a novel integrated HPC system and application monitoring and analysis capability by extending Sandia’s Kokkos application portability framework, Lightweight Distributed Metric Service (LDMS) monitoring tool, and scalable storage, analysis, and visualization pipeline. The extensions to Kokkos and LDMS enable collection and storage of application data during run time, as it is generated, with negligible overhead. This data is combined with HPC system data within the extended analysis pipeline to present relevant visualizations of derived system and application metrics that can be viewed at run time or post run. This new capability was evaluated using several week-long, 290-node runs of Sandia’s ElectroMagnetic Plasma In Realistic Environments (EMPIRE) modeling and design tool and resulted in 1TB of application data and 50TB of system data. EMPIRE developers remarked this capability was incredibly helpful for quickly assessing application health and performance alongside system state. In short, this milestone work built the foundation for expansive HPC system and application data collection, storage, analysis, visualization, and feedback framework that will increase total scientific output of Sandia’s HPC users.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

PF-4 Seismic Performance Reassessment Project (P-SPRaP), Interim Risk Methodology and Deliverables [Slides]

Background: Interim Risk was added to P-SPRaP (SPR Phase 2) to produce intermediate results which build confidence, exercise methodology, develop early insights, and (most importantly) mitigate LANL pit production program risk. Status: SPR Phase 2 is actively underway, has P-SPRaP project team priority focus, and is targeting completion in FY21 (September 2021). Deliverable: Presentation of interim risk results (loss of confinement for screened in failure modes), list of potential criticisms of Interim Risk approach / methodology that intervenors could raise, cost and schedule for completion of Final Risk.

58 GEOSCIENCES↗

Development of Digital Twin Predictive Model for PWR Components: Updates on Multi Times Series Temperature Prediction Using Recurrent Neural Network, DMW Fatigue Tests, System Level Thermal-Mechanical-Stress Analysis

The long-term operation (LTO) of nuclear power plant (NPP) beyond their original design life of 40 years, can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Frequent NDE requirement may lead to frequent shutdown of the NPP. This in turn can lead to power outage and additional NDE-inspection-cost related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing more digital approach such as by using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. Towards this goal Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program is working on the development of a DT framework that can be used for real time environmental fatigue prediction of reactor components. The DT framework is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics such as finite element (FE) based modeling tools. Towards this overall goal, following are some of the major contributions made during the FY21: 1) Multiple 82/182 dissimilar metal weld (DMW) specimens (both solid-weld and joint-weld representing the actual reactor multi-metal nozzles) were fatigue tested. The resulting fatigue lives were compared to the NUREG-6909 based best-fit and design fatigue curves. Additionally, the results of 52/152 DMW fatigue specimens (which were recently tested at Republic of Korea under the sponsorship of International Nuclear Energy Research Initiative - INERI program) were compared to the NUREG-6909 based best-fit and design fatigue curves. From the comparison of 82/182 and 52/152 DMW test data with NUREG-6909 best-fit curve, most of the reported test data fall way away from the NUREG-6909 suggested best-fit or mean curve. The NUREG-6909 suggested best-fit curve is the best-fit curve of austenitic stainless steel and due to lack of enough data on Nickel-based welds, this is currently being used for predicting the life of Nickel-alloy-based welded components. However, the above observation may require higher scaling factor (e.g., ASME suggested factor of 20 on cycles rather than the current NUREG-6909 suggested factor of 12 on cycles) for scaling the austenitic-stainless-steel best-fit-curve for estimating the design or safe-life of a welded component. Accordingly, for example, if a DMW component experience a strain amplitude of 0.6% the PWR-water life of the component would be 52 cycles instead of 85 cycles. However, more DMW tests are required to further ascertain the above-mentioned observations. 2) A system level CAD and finite element model were developed which consists of reactor pressure vessel (RPV), part of steam generator (SG), part of pressurizer (PRZ), hot leg (HL), and surge line (SL). This is with detailed nozzle geometry and thermal-mechanical material properties of different metals to simulate realistic thermal-mechanical stress under connected system global thermal-mechanical boundary conditions. 3) Different system level heat transfer analyses were performed with estimation of relevant heat transfer coefficients. The resulting data were used in subsequent system level thermal-mechanical stress analysis and for generating spatial-temporal training and validation data for a system level digital-twin based temperature predictor. Transient heat transfer analyses were performed considering thermal boundary condition under design-basis (DB) loading and EDF (Électricité de France) data-based grid-load-following (EDF-GLF) loading cycles. 4) System level thermal-mechanical stress analysis was performed for identifying damage-prone hotspots and for future extension of the model for cyclic state prediction. From the system-level model simulation under DB loading cycle it is found that HL and the SL nozzle that connect to the HL can experience significant stress and strain and could be one of the weakest links in the overall reactor coolant system (RCS). 5) An AI/ML based DT model was developed for multi-time-series temperature prediction at any inside/outside thickness locations of PWR pressure boundary components. This is by using Recurrent-neural-network (RNN) and keras machine learning libraries. The RNN model was validated against two laboratory test-based data sets with one obtained through ANL’s in-air fatigue test system and other through PWR-water test loop. The experimentally validated DT model further validated against FE model results to predict thermal scarification related spatialtemporal temperatures at random locations of a component. The well validated DT model was then used for demonstrating spatial-temporal temperature prediction under 100+ years of reactor operation subjected to combined DB, EDF-GLF and randomized grid-load-following (RANDOMGLF) loading Cycles. The expert-elicitation DT model framework was developed assuming field/input/process measurements can be available from a few existing plant sensors and can readily be used by the NPP operators. The above temperature prediction model will feed to the next-step stress analysis model based on which the life of a component can be predicted in realtime, which is one of our future works.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Testing in Support of the Development of EPP Plus SMT Design Method at ORNL (FY2021)

Experiments in support of the development of the integrated Elastic–Perfectly Plastic (EPP) plus Simplified Model Test (SMT) design methodology, referred to as the EPP+SMT method, continued in FY21. This report focuses on the methodology for developing the EPP+SMT creep-fatigue (CF) design curves at low strain ranges. The creep damage-based method and dissipated work-based method were used to evaluate the available CF data at the low strain range region. A set of failure criteria were determined, and a simple extrapolation method was developed to predict the CF life cycles at low strain ranges that are not accessible by experiments due to the extraordinarily long failure times at the low strain region (thousands to hundreds of thousands of years) and the inability of the test machine to control these small strain ranges due to the signal to noise issues. An experimental method with the concept of block-strain range CF testing was proposed to generate the information needed to extrapolate the CF design curves to low strain ranges. Based on this new testing approach, a preliminary EPP+SMT CF design curve was developed for Alloy 617 at 950°C with tension hold time of 100 s. The analysis in this report shows the potential of generating a set of EPP+SMT CF design curves with different hold times within a reasonable amount of time and testing effort. Based on such a progress, a hold time extrapolation procedure for low strain ranges will be developed in FY22 and critical testing will be carried out to complete the development of the EPP+SMT CF design curves for Alloy 617.

36 MATERIALS SCIENCE↗

Digital Platform Informed Certification of Components Derived from Advanced Manufacturing Technologies

The Transformational Challenge Reactor is being designed at Oak Ridge National Laboratory to demonstrate the feasibility of constructing a reactor core using advanced manufacturing technology. This technology includes additive manufacturing combined with machine learning, materials science, and data science technologies in an effort to facilitate the expansion of additive manufacturing into advanced nuclear energy systems and other applications requiring a high level of quality assurance. The Transformational Challenge Reactor is employing additive manufacturing and artificial intelligence to deliver a new approach. Beginning in FY21, the focus of the program has shifted away from demonstrating a reactor, and instead, towards delivering on four key thrust areas: (1) artificial intelligence-informed design, (2) advanced materials, (3) integrated sensing and control, and (4) the digital platform. Of these four thrust areas, the most pertinent to this report is the digital platform. The digital platform has the potential to be a key enabler for a paradigm shift in how components, those derived from advanced manufacturing technologies, are certified for use in nuclear applications. This is achieved primarily using machine learning to discover correlations from the abundance of data produced through additive manufacturing and those physical properties critical to the performance of the component.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Application of NEAMS Codes to Capture MSR Phenomena

This report documents work completed in FY21 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program’s Molten Salt Reactor (MSR) Application Drivers activity at Argonne. The common focus was on identifying the modeling and simulation functional requirements for designing, licensing, and operating MSRs and applying those capabilities already developed in NEAMS tools to example problems of interest. The four main parts of this report each focuses on a specific area of simulation physics as it relates to MSR phenomena: fuel evolution, chemistry, computational fluid dynamics (CFD), and systems analysis. In terms of fuel evolution, which includes depletion, decay, on-line separations, and transmutation, the current state of computational capabilities for modeling this behavior in liquid-fueled molten salt reactor is discussed. Some of the functional requirements to accomplish the various applications of MSR fuel depletion modeling are highlighted, followed by a summary of recent approaches and code development activities. The chemistry functional requirements were discussed in the context of several applications of high importance for MSRs, such as corrosion, salt chemistry, and species transport. Each of these types of chemistry modeling have considerable impact on various aspects of reactor applications, including informing on reactor designs, improving operational efficiencies, analyzing safety and reactivity concerns, and estimating the mechanistic source term of the reactor. A brief overview is also provided on code development activities ongoing under NEAMS relevant to chemistry modeling of MSRs. In terms of CFD applications, the state-of-the-art spectral element code, Nek5000 was used to model the fluid dynamics within a full core of the Molten Salt Fast Reactor (MSFR) concept designed as part of the Euratom EVOL project. This concept was selected as the challenge problem because of its similar features to several U.S. industry concepts. The goal was to model some of the fast MSR design challenges, including potential large internal re-circulations, the need of accurate tracking of delayed neutron precursors (DNP), and the lack of relevant thermal-hydraulics models/correlations, etc. Therefore, a series of CFD models were created for the MSFR core cavity using a k – τ model two-equation model for the turbulence. These first full core results demonstrated that any potential recirculation zones could be properly identified with the current NEAMS CFD capabilities. The development of these models will also set the stage for future testing of Nek5000’s functionalities to model other MSR thermal-fluid phenomena. Lastly, the validation of SAM against experimental data from the Molten Salt Reactor Experiment, which started in FY19, continues with the inclusion of modeling the reactivity insertion tests. This involved using SAM and its point kinetics model for flowing fuel salt to recreate the time dependent power changes and response after positive reactivity insertions at the 1, 5, and 8 MWt power levels. Through these exercises, several code modifications were suggested to the SAM development team and accommodated to enable closer agreement with solid technical and physical justifications. These include adding a moderator reactivity feedback coefficient as an available input and modifying the solution approach for the point kinetics model. Additional SAM development suggestions for flowing fuel MSRs include adding the capability to allow the moderator power change proportionally with the reactor power and enabling specification of the power and DNP distributions separately.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Understanding Photocarrier and Gas Dynamics to Rationally Design Heterostructured Nanocatalysts for Solar CO 2 Conversion

Recent research in CO 2 photocatalysis has largely focused on exploring new catalysts; however, details of how these materials work often remain unclear. Knowledge of these processes will allow one to rationally design highly efficient catalysts for solar CO 2 conversion. This project aims to develop new techniques and establish new capabilities in SRNL to enable the study of photocatalysts and other materials in extreme detail. In FY21, we developed two new in situ techniques that are unique to SRNL, allowing the study of reaction intermediates and adsorbed gases during photocatalysis. We also established new in-house capabilities for catalyst synthesis and transient absorption (TA) spectroscopy, which enables the study of very short-lived excited states on photocatalysts. These capabilities will be used extensively for this project and in other current projects relevant to clean energy technologies such as photovoltaic cells, providing a good return on investment in the coming years.

14 SOLAR ENERGY↗

ExaSGD: 2021 Kernel Thrust Activities

The Kernel Thrust milestone ADSE22-214 covers the development of device-capable optimization algorithms and solvers technologies required by the ExaSGD project’s software stack in order to solve security-constrained alternating current optimal power flow (SC-ACOPF) problems on emerging exascale architectures. To this extent, in FY21 the main objective of the Kernel Thrust was (i) provide robust optimization solver(s) that run efficiently on hardware accelerator devices (i.e., NVIDIA and AMD GPUs) to perform intra-node computations and (ii) provide coarse-grain parallel optimization capabilities that exploit the decomposition opportunities present in the SC-ACOPF challenge problems to provide exascale-capable solvers.

97 MATHEMATICS AND COMPUTING↗

Operational and Mission Highlights: A Monthly Summary of Top Achievements October 2021

Working with the Design Agency (Q-6), Production Agency Quality (PAQ) Division, and the NNSA Los Alamos Field Office, Detonator Production recently sold Lot 3354 to NNSA. Detonator Production personnel shipped the lot to Pantex — the Laboratory will continue to support the W76 into the future. The sale and shipment of Lot 3354 was accomplished before the closeout of FY21, achieving a key milestone that required active participation from several stakeholders within the Lab, as well as organizations external to the Laboratory. Both organizations found remedies to address challenges associated with this lot that had persisted since 2019.

99 GENERAL AND MISCELLANEOUS↗

Methods and Usability Enhancements in Shift for Non-LWR Applications

Several development and analysis tasks were undertaken in FY21 under the Nuclear Energy Advanced Modeling and Simulation program to enhance modeling of non light–water reactors (LWRs) with Shift. Specifically, these efforts targeted enhancements for tristructural isotropic (TRISO) fuel modeling. A new Shift user interface was developed that allows for much better usability and ease of modeling for non-LWR problems and TRISO fuel. Performance studies were conducted using an HTR-10 fuel pebble model by comparing different geometry packages in Shift, KENO-VI, and Serpent. These studies showed that the new geometry package in Shift performs well compared to Serpent for TRISO fuel modeling with consistent tracking options between both packages. The studies also identified the most critical areas of improvement for more efficiently performing Monte Carlo transport on TRISO fuel models with Shift. Tally calculations in Shift were optimized for non-LWR cross section generation and depletion calculations, and areas for further optimization and accuracy improvements were identified. Finally, initial collaboration efforts were formed between Idaho National Laboratory, Argonne National Laboratory, and the Nuclear Regulatory Commission to use Shift for Comprehensive Reactor Analysis Bundle support.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Organic Iodide Sorption from Dilute Gas Streams

Reprocessing used nuclear fuel releases volatile radionuclides, including 129 iodine (I), into the off-gas of a processing plant. Volatile radioiodine could be present in several forms, depending on the chemistry of the process used and the off-gas stream. Inorganic I 2 is expected to be the predominant I species in the dissolver off-gas (DOG), with minor organic iodides present. The bulk of the I is expected to volatilize into the DOG in parts-per-million-level (ppm) concentrations. In contrast, in the vessel off-gas (VOG), most of the volatile I is expected to be found as organic iodides, such as CH 3 I, C 4 H 9 I, and C 12 H 25 I. These species are expected to be present in parts-per-billion-level (ppb) concentrations but require abatement, even at low expected concentrations, to meet regulatory emissions limits in the United States. Historically, studies of I abatement by Ag-functionalized sorbents have focused on inorganic I in the DOG, but in the last few years, more research attention has been given to organic iodides, especially longer chain species, such as C 4 H 9 I, and C 12 H 25 I. This report has three main goals: (1) to present new data generated at Oak Ridge National Laboratory (ORNL) in FY21 on the sorption behavior of organic iodides on AgZ, (2) to summarize and synthesize organic iodide data produced by ORNL and Idaho National Laboratory (INL) over the last 4 years to answer questions on organic iodides behavior outlined in the 2018 joint test plan (Jubin et al. 2018), and (3) to propose a VOG abatement system design that can provide the capture efficiencies required to meet I emission limits. The 2021 ORNL experimental campaign tested the effects of organic iodide speciation and concentration in the off-gas, superficial velocity of the off-gas, and effects of aging on AgZ sorbent capacity. These studies found that the sorption rate of organic iodides by AgZ depends on the hydrocarbon chain length and the concentration in the off-gas. Higher molecular weight organic iodides adsorb to AgZ more slowly than I. At a concentration of 50 ppm concentration in the off-gas, CH 3 I loads 8% slower, C 4 H 9 I loads 20% slower, and C 12 H 25 I loads 40% slower than I. The lowest concentration loading rates calculated were in 5 ppm organic iodide gas streams in which AgZ gained on average 0.14 mg I/g sorbent/hour in the bench scale test system. Thus, longer sorbent beds might be needed to accommodate slower loading rates onto AgZ in lower concentration gas streams. Although sorption rate varies as a function of hydrocarbon chain length, the saturation concentration of the sorbent for these I-bearing species does not vary. Aging AgZ in a humid air stream for 9 months drops the overall sorbent capacity by ~35% for CH 3 I, ~50% for C 4 H 9 I, and ~40% for C 12 H 25 I. This results in a saturation capacity between 35 and 70 mg I/g sorbent for the aged AgZ. In conjunction with recent data produced by INL, these data are used to estimate the mass transfer zone (MTZ) and decontamination factor (DF) for sorbent beds of AgZ. Sorption tests performed with iodide gas concentrations of about 1 ppm and higher at a superficial gas velocity of 10 m/min, indicate that MTZ depths for these conditions tend to range between about 8-20 cm. Tests performed at lower concentrations between 50-90 ppb and at gas superficial velocities of 1, 10, and 20 m/min indicate that the MTZ depth increases with increasing superficial gas velocity. The 20 m/min test indicates that the MTZ for those conditions was at least 22 cm, and doubling the superficial gas velocity from 10 to 20 m/min could roughly double or triple the MTZ depth. Doubling and tripling the bounding MTZ depth of 20 cm for the body of MTZ estimates made at with 10 m/min superficial velocity would extend the MTZ for a superficial velocity of 20 m/min to 40-60 cm. This bounding limit applies to all of the organic iodides that have been tested. These results also indicate that the sorption rate-limiting step is not sensitive to the superficial gas velocity; otherwise the MTZ depth would not have increased approximately in proportion to the increase in the gas superficial velocity. This further suggests that the rate limiting step is not associated with mass transfer of the sorbate to the sorbent surface, or mass transfer of the reaction byproducts from the sorbent surface, but is associated with sorption or chemical reactions on the sorbent surface or in sorbent pores. Deep bed testing at INL has established DFs of >2,000 for I, CH 3 I, and C 4 H 9 I under a range of conditions (Soelberg et al. 2021, Bruffey et al. 2019). DF does not seem to be affected by the concentration of the organic iodide in the gas stream over the range of 1 to 50 ppm. Thus, if the MTZ is accommodated in sorbent bed design for the DOG and VOG, then regulatory DFs will be met. To meet the third objective outlined in this report, these experimental data were used to update an engineering evaluation of the VOG first completed in 2016. The updated VOG design can be found in an accompanying document (Welty et al., 2021; INL- LTD-21-64587). This report finds that the VOG will decrease in both size and complexity, relative to previous designs, and will still meet regulatory requirements for all iodine forms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Diagnostic and predictive capabilities of the TCR digital platform

The Transformational Challenge Reactor program is leveraging additive manufacturing technologies to fabricate the nuclear components required to assemble a microreactor core. Compared with traditional manufacturing processes, additive manufacturing allows for direct observation of the interior of the component during manufacturing. This unique capability promises significant possibilities for creating a new paradigm for nuclear component qualification by leveraging in-situ process data. This report describes FY21 efforts to predict material tensile properties based on data collected during the laser powder bed fusion printing process. The primary focus of this report is the test campaign designed to generate the large quantities of training data required to implement artificial intelligence algorithms that can predict these material properties. Preliminary prediction results and a demonstration of the overall data collection, analysis, and visualization pipeline are also provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

I.1 Heavy-Duty Diesel Combustion (Sandia National Laboratories)

Regulatory drivers and market demands for lower pollutant emissions, lower carbon dioxide emissions, and lower fuel consumption motivate the development of cleaner and more fuel-efficient engine operating strategies. Most current production heavy-duty diesel engines use a combination of both in-cylinder and exhaust emissions-control strategies to achieve these goals. The emissions and efficiency performance of in-cylinder strategies depend strongly on flow and mixing processes that can be influenced by using multiple fuel injections. Past work performed under this project showed that adding a second injection can reduce soot to levels below what would have been produced by an unchanged first injection, thereby increasing load while decreasing soot and potentially reducing brake specific fuel consumption. Information characterizing the important in-cylinder processes with multiple injections has been gleaned from ensemble-averaged planar laser-induced incandescence (PLII) imaging visualizing the soot cloud and planar induced fluorescence (PLIF) of OH characterizing the soot oxidation regions. PLII showed a consistent disruption of the first injection soot cloud by the second injection. In conjunction with OH-PLIF, differences in soot oxidation patterns for multiple injections compared to single injections were observed. This understanding was further enhanced in FY20, when high-speed imaging resolving the above-mentioned effects in a single cycle were combined with direct numerical simulations investigating the multiple-injection ignition process on the microscopic level of turbulence and chemistry interaction. In FY21, these findings in conjunction with findings from other researchers published in the scientific literature were composed into a preliminary multiple-injection conceptual model of fuel-mixing, injection and ignition processes. Remaining key research questions were also highlighted. In addition, wall heat flux was investigated experimentally and with numerical simulations to understand the potential of multiple injections to reduce the engine heat losses and further enhance the efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

MOSCATO Solver Development and Integration Plan

During FY21, we conducted ongoing development work for the MOSCATO (Molten Salt Chemistry and Transport) solver. The code development work primarily consisted of transitioning capabilities from the original version of the solver, which was written in OpenFOAM, into Nek5000. In doing so, a fast, highly parallelizable solver was created that is capable of complex chemistry and corrosion simulations for engineering-scale molten salt systems. The Nek5000 version of MOSCATO is now fully featured and capable of higher-fidelity simulations than were previously possible. Demonstration cases including a thermal convection loop have been simulated to test these new capabilities. Although capable of large-scale simulations, MOSCATO is not well-suited to parametric studies of complete reactor geometries. These types of simulations are instead better handled by reduced-order modeling codes such as ORNL’s Mole code. Reduced-order simulation tools like Mole, however, are dependent on high fidelity correlations to account for complex, coupled three-dimensional phenomena that they do not directly simulate. Tools such as MOSCATO must therefore be used to create these correlations, as suitable empirical relationships are not available for most molten salt systems. Toward that end, we used the Nek-derived version of MOSCATO to create new mass transfer correlations for three relevant cases including tubular, tube bank, and subchannel geometries. These new correlations are more accurate than any existing ones and can be readily integrated into any reduced-order modeling tools that are targeting full-scale MSR simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

LANL’s Digital Supply Chain Transformation with Ariba Part 2 [Slides]

LANL’s budget continues to increase. Our annual procurement spend has increased from approximately 750 million two years ago to 1.4 Billion in FY21. Procurement for LANL is a mix of indirect and direct but had limited managed spend – more standalone orders vs master contracts. The level of transformation we were looking to achieve required a comprehensive approach, encompassing people, processes and software solutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗