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DOE OSTI2020

JAK inhibition reduces SARS-CoV-2 liver infectivity and modulates inflammatory responses to reduce morbidity and mortality

Using AI, we identified baricitinib as having antiviral and anticytokine efficacy. We now show a 71% (95% CI 0.15 to 0.58) mortality benefit in 83 patients with moderate-severe SARS-CoV-2 pneumonia with few drug-induced adverse events, including a large elderly cohort (median age, 81 years). An additional 48 cases with mild-moderate pneumonia recovered uneventfully. Using organotypic 3D cultures of primary human liver cells, we demonstrate that interferon-α2 increases ACE2 expression and SARS-CoV-2 infectivity in parenchymal cells by greater than fivefold. RNA-seq reveals gene response signatures associated with platelet activation, fully inhibited by baricitinib. Using viral load quantifications and superresolution microscopy, we found that baricitinib exerts activity rapidly through the inhibition of host proteins (numb-associated kinases), uniquely among antivirals. This reveals mechanistic actions of a Janus kinase-1/2 inhibitor targeting viral entry, replication, and the cytokine storm and is associated with beneficial outcomes including in severely ill elderly patients, data that incentivize further randomized controlled trials.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

PELICAN Status Report for Year 2021

The Pressure Drop Experimental Loop for Investigations of Core Assemblies in Advanced Nuclear Reactors, PELICAN, is a novel experimental facility designed and constructed to recreate the prototypic full scale hydraulic flow conditions for the Versatile Test Reactor (VTR) currently under development by the U.S. Department of Energy. To support VTR design efforts, PELICAN is used to replicate VTR’s primary heat transport system (PHTS) in the core assembly region. The measurement objectives for data generated from this test facility are to mimic the prototypic VTR assembly and to meet the validation needs for code calculations and simulations of the reference design for the VTR core. These objectives focus on the need to validate pressure drop results across the various segments of the fuel assembly, including the axial reflectors, fuel, and transition regions, as they relate directly to the pumping power and safety behavior of the reactor. In the following sections, the major milestones for the experimental work performed on PELICAN over the calendar year (CY) 2021 are presented. In the next section, we discuss the assembly and shakedown testing of the facility. In Section 3, an analysis of the errors in the major measurements is performed. In Section 4 and 5 we present the results from the first set of test articles placed inside the loop. The design of the remaining test articles as part of the full assembly are shown in Section 6 and the conclusion and path forward for the following year, CY22 is given in the final section.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Simulation of Multipaction in LB650 Cavity with Weld Profile

This study aims to simulate multipaction in LB650 cavity with weld profile, a first step to replicating an actual cavity, whereas past studies have ignored the same. We attempt to align the simulation data with the experimental data and report the subsequent findings.

Ninan, Z.↗

DOE OSTI2022

On the Rapid Calculation of Binding Affinities for Antigen and Antibody Design and Affinity Maturation Simulations

The accurate and efficient calculation of protein-protein binding affinities is an essential component in antibody and antigen design and optimization, and in computer modeling of antibody affinity maturation. Such calculations remain challenging despite advances in computer hardware and algorithms, primarily because proteins are flexible molecules, and thus, require explicit or implicit incorporation of multiple conformational states into the computational procedure. The astronomical size of the amino acid sequence space further compounds the challenge by requiring predictions to be computed within a short time so that many sequence variants can be tested. In this study, we compare three classes of methods for antibody/antigen (Ab/Ag) binding affinity calculations: (i) a method that relies on the physical separation of the Ab/Ag complex in equilibrium molecular dynamics (MD) simulations, (ii) a collection of 18 scoring functions that act on an ensemble of structures created using homology modeling software, and (iii) methods based on the molecular mechanics-generalized Born surface area (MM-GBSA) energy decomposition, in which the individual contributions of the energy terms are scaled to optimize agreement with the experiment. When applied to a set of 49 antibody mutations in two Ab/HIV gp120 complexes, all of the methods are found to have modest accuracy, with the highest Pearson correlations reaching about 0.6. In particular, the most computationally intensive method, i.e., MD simulation, did not outperform several scoring functions. The optimized energy decomposition methods provided marginally higher accuracy, but at the expense of requiring experimental data for parametrization. Within each method class, we examined the effect of the number of independent computational replicates, i.e., modeled structures or reinitialized MD simulations, on the prediction accuracy. We suggest using about ten modeled structures for scoring methods, and about five simulation replicates for MD simulations as a rule of thumb for obtaining reasonable convergence. We anticipate that our study will be a useful resource for practitioners working to incorporate binding affinity calculations within their protein design and optimization process.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Accelerated Aging Humidity Chamber for Nuclear Grade HEPA Filter Media

A unique accelerated aging humidity chamber for simulating the natural aging process of nuclear grade high efficiency particulate air (HEPA) filter media is being designed, implemented, and tested. The nuclear industry currently lacks information regarding the shelf life and service life of HEPA filter media. The Department of Energy recommends disposing of HEPA filters 10 years after the manufacture date for filters operated under dry conditions. Studies have shown the tensile strength and water repellency of HEPA filter media diminish with age. The chamber's principal function is to sustain an elevated relative humidity condition for an extended duration specified by the Arrhenius aging model. To accomplish this, various design parameters were established: (1) consistently achieve uniform humidity conditions within the chamber to equally expose media sheets, (2) ensure the chamber is sufficiently sealed to mitigate the uncontrolled infiltration of air, (3) confidently secure the media sheets to avert the introduction of unnecessary stressing/creasing, (4) fabricate the chamber from clear polycarbonate material to allow inspection of the media sheets, (5) provide a safe and ergonomic design for personnel, (6) ensure the chamber design is replicable and relatively easy to fabricate/assemble. A humidity source, fan, PID controller, humidity and temperature transmitters, and data loggers are required for proper operation and control of the chamber. The humidity source must accommodate target values up to 95% relative humidity throughout the chamber. The three humidity and temperature transmitters are strategically spaced throughout the chamber to ensure uniform conditions. The 10 cubic feet per minute (CFM) fan selected intends to accomplish the desired air change rate inside the chamber of approximately 20 air changes per hour (ACH). The 2 plenums on the upper and lower portions of the chamber utilize a perforated design to uniformly distribute air, promote air mixing, and control the air velocity entering the chamber. Industrial blueprint hanging clamps are being retrofitted to be seated within the chamber drawers and firmly secure the nuclear grade filter media. The aged media will be evaluated using autopsy methodology, and the results obtained intend to help clarify the useful life of nuclear grade HEPA filters. Nuclear grade high efficiency particulate air (HEPA) filters are defined as disposable, extended-media, dry-type filters with a rigid casing enclosing the full depth of the pleats and have a minimum particle removal efficiency of 99.97%. [1] - HEPA filters are constantly exposed to stressors and subsequently have been shown to degrade as the filter ages. Properties such as tensile strength and water repellency, along with others, are negatively impacted. [2] - Due to the scarcity of naturally aged HEPA filters available, it is crucial to develop accelerated aging methods which effectively mimic the natural degradation effects. - After accelerated aging, the filters are subject to testing in the Axial Flow Large Scale Test Stand (ALSTS) and other analysis techniques such as the same qualification tests performed directly after being manufactured. - Quality data is necessary for future decisions regarding the lifetime of nuclear grade HEPA filters. - The objective is to develop a prototype accelerated aging humidity chamber for nuclear grade HEPA filter media. The chamber should expose the media to commonly occurring stressors to expedite the degradation process caused by aging. PID yields reliable and reproducible results: - CFD model correlates well with actual performance; - Further analysis is needed to complete characterization; - Future work for the chamber is still to be completed. The data shown in Figure 5 and Table 1 indicate the system is functioning as designed. As can be determined from the system response evaluation in Table 1, the PID controller is yielding reliable and reproducible results at each set point. As the set point increases, the time constant and 20% settling time increase accordingly. From the results in Table 1, it stands to reason that the CFD model correlates well with the actual performance of the system. Each system response parameter for the 90%RH* CFD model is slightly lower than the parameters collected from the physical model tested at an equivalent set point. This is to be expected considering the inlet in the CFD model is a constant supply of water vapor, whereas the physical model uses a PID controller to monitor the amount of water vapor needed and reacts accordingly. More analysis is still to be done on the prototype chamber. A pressure test will be conducted in order to determine the hourly leak rate of the chamber. This test will involve constant air flow into the chamber until the desired pressure is reached. A uniformity test will also be conducted in order to ensure each filter medium is being exposed to equivalent relative humidity levels. This test will involve an array of humidity meters strategically oriented inside the chamber to record any possible gradients. Future work for the chamber includes dehumidification abilities, tests while fully loaded with filters, and temperature control. Once completed, the autopsy team at Institute of Clean Energy Technology will conduct necessary accelerated aging studies as needed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel

Abstract Estimates of plant traits derived from hyperspectral reflectance data have the potential to efficiently substitute for traits, which are time or labor intensive to manually score. Typical workflows for estimating plant traits from hyperspectral reflectance data employ supervised classification models that can require substantial ground truth datasets for training. We explore the potential of an unsupervised approach, autoencoders, to extract meaningful traits from plant hyperspectral reflectance data using measurements of the reflectance of 2151 individual wavelengths of light from the leaves of maize ( Zea mays ) plants harvested from 1658 field plots in a replicated field trial. A subset of autoencoder‐derived variables exhibited significant repeatability, indicating that a substantial proportion of the total variance in these variables was explained by difference between maize genotypes, while other autoencoder variables appear to capture variation resulting from changes in leaf reflectance between different batches of data collection. Several of the repeatable latent variables were significantly correlated with other traits scored from the same maize field experiment, including one autoencoder‐derived latent variable (LV8) that predicted plant chlorophyll content modestly better than a supervised model trained on the same data. In at least one case, genome‐wide association study hits for variation in autoencoder‐derived variables were proximal to genes with known or plausible links to leaf phenotypes expected to alter hyperspectral reflectance. In aggregate, these results suggest that an unsupervised, autoencoder‐based approach can identify meaningful and genetically controlled variation in high‐dimensional, high‐throughput phenotyping data and link identified variables back to known plant traits of interest.

Tross, Michael C.↗

DOE OSTI2015

SU-E-T-238: Deriving Electron Contamination Spectra From Pure and Clinical Photon Beams

Purpose: To extract the electron contamination energy spectra for an Elekta Precise Linac, based on pure photon and measured clinical beam percentage depth dose data. And to include this as an additional source in isource 4 in DOSXYZnrc. Methods: A pure photon beam was simulated for the Linac using isource 4 in the DOSXYZnrc Monte Carlo (MC) code. Percentage depth dose (PDD) data were extracted afterwards for a range of field sizes (FS). These simulated dose data were compared to actual measured dose PDD data, with the data normalized at 10 cm depth. The resulting PDD data resembled the electron contamination depth dose. Since the dose fall-off is a strictly decreasing function, a method was adopted to derive the contamination electron spectrum. Afterwards this spectrum was used in a DOSXYZnrc MC simulation run to verify that the original electron depth dose could be replicated. Results: Various square aperture FS’s for 6, 8 and 15 megavolt (MV) photon beams were modeled, simulated and compared to their respective actual measured PDD data. As FS increased, simulated pure photon depth-dose profiles shifted deeper, thus requiring electron contamination to increase the surface dose. The percentage of electron weight increased with increase in FS. For a FS of 15×15 cm{sup 2}, the percentage electron weight is 0.1%, 0.2% and 0.4% for 6, 8 and 15 MV beams respectively. Conclusion: From the PDD results obtained, an additional electron contamination source was added to the photon source model so that simulation and measured PDD data could match within 2 % / 2 mm gamma-index criteria. The improved source model could assure more accurate simulations of surface doses. This research project was funded by the South African Medical Research Council (MRC) with funds from National Treasury under its Economic Competitiveness and Support package.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Bridging the gap between peak and average loads on science networks

Backbone networks are typically overprovisioned in order to support peak loads. Research and education networks (RENs), for example, are often designed to operate at 20–30% of capacity. Thus, Internet2 upgrades its backbone interconnects when the weekly 95th-percentile load is reliably above 30% of link capacity, and analysis of ESnet traffic between major laboratories shows a substantial gap between peak and average utilization. As science data volumes increase exponentially, it is unclear whether this overprovisioning trend can continue into the future. Even if overprovisioning is possible, it may not be the most cost-effective (and desirable) approach going forward. Under the current mode of free access to RENs, traffic at peak load may include both flows that need to be transferred in near-real time–for example, for computation and instrument monitoring and steering–and flows that are less time-critical, for example, archival and storage replication operations. Thus, peak load does not necessarily indicate the capacity that is absolutely required at that moment. We thus examine how data transfers are impacted when the average network load is increased while the network capacity is kept at the current levels. We also classify data transfers into on-demand (time-critical) and best-effort (less time-critical) and study the impact on both classes for different proportions of both the number of on-demand transfers and amount of bandwidth allocated for on-demand transfers. For our study, we use real transfer logs from production GridFTP servers to do simulation-based experiments as well as real experiments on a testbed. We find that when the transfer load is doubled and the network capacity is fixed at the current level, the gap between peak and average throughput decreases by an average of 18% in the simulation experiments and 16% in the testbed experiments, and the average slowdown experienced by the data transfers is under 1.5×. Moreover, when transfers are classified as on-demand or best-effort, on-demand transfers experience almost no slowdown and the mean slowdown experienced by best-effort transfers is under 2× in the simulation experiments and under 1.2× in the testbed experiments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Global‐view coefficients: a data management solution for parallel quantum Monte Carlo applications

Summary Quantum Monte Carlo (QMC) applications perform simulation with respect to an initial state of the quantum mechanical system, which is often captured by using a cubic B‐spline basis. This representation is stored as a read‐only table of coefficients and accesses to the table are generated at random as part of the Monte Carlo simulation. Current QMC applications, such as QWalk and QMCPACK, replicate this table at every process or node, which limits scalability because increasing the number of processors does not enable larger systems to be run. We present a partitioned global address space approach to transparently managing this data using Global Arrays in a manner that allows the memory of multiple nodes to be aggregated. We develop an automated data management system that significantly reduces communication overheads, enabling new capabilities for QMC codes. Experimental results with QWalk and QMCPACK demonstrate the effectiveness of the data management system. Copyright © 2016 John Wiley & Sons, Ltd.

Niu, Qingpeng↗

DOE OSTI2025

Data for Machado-Silva et al. (2024), "Short-Term Groundwater Level Fluctuations Drive Subsurface Redox Variability"

This dataset contains the analytical data reported in Machado-Silva et al. (2024) as part of the COMPASS-FME project, which seeks to advance a scalable, predictive understanding of the fundamental biogeochemical processes, ecological structure, and ecosystem dynamics that distinguish coastal terrestrial-aquatic interfaces from the purely terrestrial or aquatic systems to which they are coupled. The dataset consists of water quality parameters as well as redox potential, water content, and electrical conductivity. These data were collected in 2022 in Crane Creek (CRC), Portage River (PTR), and Old Woman Creek (OWC). Each of these sites included uplands (UP), transitions (TR), wetland-transition edge (WTE), and wetland (W) zones. The sites represent replicates of the Lake Erie terrestrial-aquatic interface under fluctuating water levels and are located in well-preserved areas with natural or restored marsh and forest cover.This dataset consists of a single data file (Machado_Silva_et_al_2024_EST_data.csv) that is in comma-separated value (CSV) format. No special software is required to read it.This dataset uses the ESS-DIVE Hydrologic Monitoring Reporting Format 1.0.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Customizable Scale-Out Key-Value Stores

Enterprise KV stores are often not well suited for HPC applications, and thus cumbersome end-to-end KV design customization is required to meet the needs of modern HPC applications. To this end, in this article we present bespoKV, an adaptive, extensible, and scale-out KV store framework. bespoKV decouples the KV store design into the control plane for distributed management and the data plane for local data store. For the control plane, bespoKVprovides pre-built modules, called controlets, supporting common distributed functionalities (e.g., replication, consistency, and topology) and their various combinations. This decoupling allows bespoKV to take a user-provided single-server KV store, called a datalet, and transparently enables a scalable and fault-tolerant distributed KV store service. The resulting distributed stores are also adaptive to consistency or topology requirement changes and can be easily extended for new types of services. Such specializations enable innovative uses of KV stores in HPC applications, especially for emerging applications that utilize KV-friendly workloads. We evaluate bespoKV in a local testbed as well as in a public cloud settings. Experiments show that bespoKV-enabled distributed KV stores scale horizontally to a large number of nodes, and performs comparably and sometimes 1.2× to 2.6× better than the state-of-the-art systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

HP-FLEX: Field demonstration of the semantics-driven configuration of a Model Predictive Control system to make heat pumps flexible

Model Predictive Control (MPC) has demonstrated significant potential for optimizing building operations and enabling demand flexibility. However, the widespread adoption of MPC is hindered by complex manual configuration and commissioning processes that must be conducted by control experts working alongside building operators. These challenges drive up costs and reduce scalability, particularly when technical human resources and building automation systems are limited, such as in small and medium commercial buildings (SMCBs). This paper demonstrates how semantic standards, specifically ASHRAE 223P, can accelerate the adoption of MPC applications for load flexibility in SMCBs. The authors present a replicable control framework, titled “HP-FLEX” that leverages a building’s semantic model to bootstrap the required data configuration for an MPC controller developed for optimizing heat pump systems as flexible grid resources. The semantic model helps streamline the deployment workflow, particularly for site setup, data/control commissioning, and model setup. This integration enhances portability, transferability, and scalability of the HP-FLEX MPC, which has been developed to support MPC-based supervisory HVAC controllers in SMCBs. Additionally, the paper details the required building and thermostat metadata information to enable the HP-FLEX MPC based on field demonstrations. The new workflow was tested in a small commercial building located in California, U.S., and demonstrated a load shifting performance of 9% based on a dynamic pricing signal that varies by the hour. This work provides a practical pathway for transitioning sophisticated building applications from custom to standardized semantic representations, supporting the broader adoption of advanced control strategies like MPC. The framework also establishes a foundation for evolving metadata requirements as applications mature while maintaining compatibility with industry standards.

Paul, Lazlo↗

DOE OSTI2024

Pinellas County Clear Sky Assessment Process: Prioritizing Solar + Storage for Resilient Facilities & Communities

The Clear Sky Tampa Bay project was a 15-month collaborative research effort to support solar + storage deployment for community resilience in Florida. The Clear Sky Decision Support Toolkit is a collection of resources designed to support users in conducting solar + storage prioritization and feasibility screening assessments at critical facilities. The Tampa Bay Regional Planning Council worked with four local governments in the region to test and apply the Toolkit. This case study series describes how each partner government used the Toolkit and highlights key insights and lessons learned that other users could follow to replicate the process. Pinellas County applied the Clear Sky Decision Support Toolkit to improve interagency coordination and gather data to analyze solar + storage projects for its critical facilities. This case study examines energy resilience strategies for the Pinellas County Solid Waste-to-Energy Plant. The Toolkit's modular assessment process developed institutional capacity and knowledge within the county and will assist in the research and application of future solar energy projects.

14 SOLAR ENERGY↗

DOE OSTI2025

HP-FLEX: Field Demonstration of the Semantics-Driven Configuration of a Model Predictive Control System to Make Heat Pumps Flexible

Paul, Lazlo↗

DOE OSTI2015

Developing Uintah's Runtime System for Forthcoming Architectures

The need to solve ever-more complex science and engineering problems on computer architectures that are rapidly evolving poses considerable challenges for modern simulation frameworks and packages. While the decomposition of software into a programming model that generates a task-graph for execution by a runtime system make portability and performance possible, it also imposes considerable demands on that runtime system. Here, the challenge of meeting those demands for near-term and longer term systems in the context of the Uintah framework is considered in key areas such as support for data structures, tasks on heterogeneous architectures, performance portability, power management and designing for resilience by the use of replication based upon adaptive mesh refinement processes is addressed. Examples of techniques in these areas are used to illustrate performance improvements obtained for present large-scale systems and the needs of proposed systems considered.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Mitovirus and Mitochondrial Coding Sequences from Basal Fungus Entomophthora muscae

Fungi constituting the Entomophthora muscae species complex (members of subphylum Entomophthoromycotina, phylum Zoopagamycota) commonly kill their insect hosts and manipulate host behaviors in the process. In this study, we made use of public transcriptome data to identify and characterize eight new species of mitoviruses associated with several different E. muscae isolates. Mitoviruses are simple RNA viruses that replicate in host mitochondria and are frequently found in more phylogenetically apical fungi (members of subphylum Glomeromyoctina, phylum Mucoromycota, phylum Basidiomycota and phylum Ascomycota) as well as in plants. E. muscae is the first fungus from phylum Zoopagomycota, and thereby the most phylogenetically basal fungus, found to harbor mitoviruses to date. Multiple UGA (Trp) codons are found not only in each of the new mitovirus sequences from E. muscae but also in mitochondrial core-gene coding sequences newly assembled from E. muscae transcriptome data, suggesting that UGA (Trp) is not a rarely used codon in the mitochondria of this fungus. The presence of mitoviruses in these basal fungi has possible implications for the evolution of these viruses.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Investigation of thermolytic hydrogen generation rate of tank farm simulated and actual waste

To support resolution of Potential Inadequacies in the Safety Analysis for the Savannah River Site (SRS) Tank Farm, Savannah River National Laboratory conducted research to determine the thermolytic hydrogen generation rate (HGR) with simulated and actual waste. Gas chromatography methods were developed and used with air-purged flow systems to quantify hydrogen generation from heated simulated and actual waste at rates applicable to the Tank Farm Documented Safety Analysis (DSA). Initial simulant tests with a simple salt solution plus sodium glycolate demonstrated the behavior of the test apparatus by replicating known HGR kinetics. Additional simulant tests with the simple salt solution excluding organics apart from contaminants provided measurement of the detection and quantification limits for the apparatus with respect to hydrogen generation. Testing included a measurement of HGR on actual SRS tank waste from Tank 38. A final series of measurements examined HGR for a simulant with the most common SRS Tank Farm organics at temperatures up to 140 °C. The following conclusions result from this testing. HGR was measured for an actual-waste Tank 38 sample. The HGR measurements at 80, 90, 100, and 110 °C were 1.7×10 -7 , 4.7×10 -7 , 5.9×10 -7 , and 2.6×10 -6 ft 3 hr -1 gal -1 , respectively. The Limit of Detection and Limit of Quantification for the HGR measurements were 2.6×10-8 ft3 hr-1 gal-1 and 5.1×10 -8 ft 3 hr -1 gal -1 , respectively. HGR was measured in a high boiling point (HBP) simulant with major known SRS Tank Farm organic compounds. Testing used fresh organics and did not simulate the long-term exposure of these organics already experienced in the waste. Hence, testing is expected to provide high bias to the hydrogen generation rates. The final HGR measurements at 75, 100, and 140 °C were 6.2×10 -7 , 3.0×10 -6 , and 8.1×10 -5 ft 3 hr -1 gal -1 , respectively. Decreases in the HGR were noted at isothermal conditions with steady gas tracer concentration, which clouds development of a temperature dependent correlation for generation rate. While the simulant contains high concentrations of major SRS organics tested at high temperatures found in the 3H Evaporator, this limited data set may not fully bound values under all possible operating conditions. The HGR measurement apparatus was successfully employed to replicate hydrogen production rate experiments. Simulant without deliberately added organic carbon was found to contain approximately 200 mg/L of organic carbon from tramp organics in the reagents used to prepare the solution. The tests using such simulant generated hydrogen at rates consistent with, but somewhat lower than, those predicted at equivalent carbon and aluminum loadings by methods used at the Hanford Site. Prior to identifying the organic contaminants, potential sources of hydrogen in simulants without deliberately added organic carbon were examined. Testing determined that this hydrogen is not due to caustic reaction of organic materials of construction within the reaction vessel, electrolysis due to current leak, anode/cathode reactions, corrosion, or the method of heating employed in the experiment. During the HBP and Tank 38 testing, a peak was identified at a retention time greater than the retention time of the inert tracer of krypton. This peak has been identified as methane, and the data have been reexamined to obtain methane concentrations. For the HBP testing, methane concentration was constant at the highest temperature studied (140 °C) and higher than hydrogen. At the lower temperatures (100 and 75 °C), methane and hydrogen tracked closely, with methane concentration generally lower than hydrogen. For Tank 38, methane concentration was approximately 1/3 of the hydrogen concentration during testing (100 and 110 °C). At lower temperatures for Tank 38 testing (90, 80, and 27 °C), methane fell below the quantification range.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Data Driven Smart Proxy for CFD Application of Big Data Analytics & Machine Learning in Computational Fluid Dynamics, Part Three: Model Building at the Layer Level

To ensure the usefulness of simulation technologies in practice, their credibility needs to be established with Uncertainty Quantification (UQ) methods. In this project smart proxy is introduced to significantly reduce the computational cost of conducting large number of multiphase CFD simulations. Smart proxy for CFD models are developed using pattern recognition capabilities of Artificial Intelligence (AI), Machine Learning (LM) and Data Mining (DM) technologies. Several CFD simulation runs with different inlet air velocities for a rectangular fluidized bed are used to create a smart CFD proxy that is capable of replicating the CFD results for a wide variety of inlet velocities. The smart CFD proxy is validated with blind CFD runs (CFD runs that have not played any role during the development [training, calibration and validation] of the smart CFD proxy). In our earlier work, CFD data was used to train ANN at the cell level. That is an ANN was trained for each computational cell used in the CFD simulations. In the present work, the ANN is constructed and trained based on cross sectional area average of each variable, such as pressure, velocities and volume fraction (Layer Level). This leads to improvements in the training time at the expense of less spatial resolution. The resulting trained ANN provides spatially average value of parameters of interest, along the length of the fluidized bed. Upon completion of this project, UQ studies that rely on hundreds or thousands of smart CFD proxy runs can be accomplished in minutes. Following figure demonstrates a validation example (blind CFD run) showing the results from the MFiX and the smart CFD proxy for pressure drop across a fluidized bed at time-step of 1400 (the layer number corresponds to the vertical location in the bed).

97 MATHEMATICS AND COMPUTING↗