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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

ABRF Proteome Informatics Research Group (iPRG) 2016 Study: Inferring Proteoforms from Bottom-up Proteomics Data

This report presents the results from the 2016 ABRF Proteome Informatics Research Group (iPRG) study on proteoform inference and FDR estimation from bottom-up proteomics data. For this study, three replicate Q Exactive Orbitrap LC-MS/MS datasets were generated from each of four E. coli samples spiked with different equimolar mixtures of small recombinant proteins selected to mimic pairs of homologous proteins. Participants were given raw data and a sequence file, and asked to identify the proteins and provide estimates on the false discovery rate at the proteoform level. As part of this study, we tested a new submission system with a format validator running on a virtual private server (VPS) and allowed methods to be provided as executable R Markdown or IPython Notebooks. The task was perceived as difficult, and only eight unique submissions were received, though those who participated did well, with no one method performing best on all samples. However, none of the submissions included a complete Markdown or Notebook, even though examples were provided. Future iPRG studies need to be more successful in promoting and encouraging participation. The VPS and submission validator easily scale to much larger numbers of participants in these types of studies. The unique “ground-truth” dataset for proteoform identification generated for this study is now available to the research community, as are the server-side scripts for validating and managing submissions.

Proteomics, proteoforms, inference, false discover↗
DOE OSTI2018

Potential Experimental Topics for EGS Collab Experiment 3

To facilitate the success of FORGE, the DOE GTO has initiated a new research effort, the EGS Collab project, which will utilize readily accessible underground facilities that can refine our understanding of rock mass response to stimulation and provide a test bed at intermediate (~10 m) scale for the validation of thermal-hydrological-mechanical-chemical modeling approaches as well as novel monitoring tools. The first two EGS Experiments 1 and 2 are planned be performed under different stress/fracture conditions, and will evaluate different stimulation processes: Experiment 1 will focus on hydrofracturing of a competent rock mass, while Experiment 2 will concentrate on hydroshearing of a rock mass that contains natural fractures. Experiment 3 is scheduled to begin in 2019 will build off the lessons learned in Experiments 1 and 2 and will investigate alternate stimulation and operation methods to improve heat extraction in an EGS reservoir. This paper evaluates potential experiments that could potentially be conducted in Experiment 3. The two technical parameters defining energy extracted from EGS reservoirs with the highest economic uncertainty and risk are the production well flow rates and the reservoir thermal drawdown rate. A review of historical and currently on-going EGS studies has identified that over ½ of the projects have identified heat extraction challenges during their operation associated with these two parameters as well as some additional secondary issues. At present, no EGS reservoir has continuously produced flow rates on the order of 80 kg/s. Short circuiting (i.e. early thermal breakthrough) has been identified in numerous cases. In addition, working fluid loss (i.e. the difference between the injected fluid mass and the extracted fluid mass as compared to the injected mass) has been as high as 90%. Finally, the engineering aspects of operating a true EGS multi-fracture reservoir such as repairing/modifying fractures and controlling working fluid fluxes within multiple fractures for the effective EGS fracture management has not been sufficiently studied. To examine issues such as these, EGS Collab Experiment 3 may be conducted in the testbeds prepared for Experiments 1 and 2 by improving the previously performed stimulations, or conducted at a new site performing new stimulations with alternate method. Potential experiments may include using different stimulation and working fluids, evaluating different stimulation methods, using proppants to enhance permeability, and other high-risk high-reward methods that can be evaluated at the 10-m scale environment.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Potential Experimental Topics for EGS Collab Experiment 3

To facilitate the success of FORGE, the DOE GTO has initiated a new research effort, the EGS Collab project, which will utilize readily accessible underground facilities that can refine our understanding of rock mass response to stimulation and provide a test bed at intermediate (~10 m) scale for the validation of thermal-hydrological-mechanical-chemical modeling approaches as well as novel monitoring tools. The first two EGS Experiments 1 and 2 are planned be performed under different stress/fracture conditions, and will evaluate different stimulation processes: Experiment 1 will focus on hydrofracturing of a competent rock mass, while Experiment 2 will concentrate on hydroshearing of a rock mass that contains natural fractures. Experiment 3 is scheduled to begin in 2019 will build off the lessons learned in Experiments 1 and 2 and will investigate alternate stimulation and operation methods to improve heat extraction in an EGS reservoir. This paper evaluates potential experiments that could potentially be conducted in Experiment 3. The two technical parameters defining energy extracted from EGS reservoirs with the highest economic uncertainty and risk are the production well flow rates and the reservoir thermal drawdown rate. A review of historical and currently on-going EGS studies has identified that over 1/2 of the projects have identified heat extraction challenges during their operation associated with these two parameters as well as some additional secondary issues. At present, no EGS reservoir has continuously produced flow rates on the order of 80 kg/s. Short circuiting (i.e. early thermal breakthrough) has been identified in numerous cases. In addition, working fluid loss (i.e. the difference between the injected fluid mass and the extracted fluid mass as compared to the injected mass) has been as high as 90%. Finally, the engineering aspects of operating a true EGS multi-fracture reservoir such as repairing/modifying fractures and controlling working fluid fluxes within multiple fractures for the effective EGS fracture management has not been sufficiently studied. To examine issues such as these, EGS Collab Experiment 3 may be conducted in the testbeds prepared for Experiments 1 and 2 by improving the previously performed stimulations, or conducted at a new site performing new stimulations with alternate method. Potential experiments may include using different stimulation and working fluids, evaluating different stimulation methods, using proppants to enhance permeability, and other high-risk high-reward methods that can be evaluated at the 10-m scale environment.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

SU-F-T-36: Dosimetric Comparison of Point Based Vs. Target Based Prescription for Intracavitary Brachytherapy in Cancer of the Cervix

Purpose: Improved patient imaging used for planning the treatment of cervical cancer with Tandem and Ovoid (T&O) Intracavitary high-dose-rate brachytherapy (HDR) now allows for 3D delineation of target volumes and organs-at-risk. However, historical data relies on the conventional point A-based planning technique. A comparative dosimetric study was performed by generating both target-based (TBP) and point-based (PBP) plans for ten clinical patients. Methods: Treatment plans created using Elekta Oncentra v. 4.3 for ten consecutive cervical cancer patients were analyzed. All patients were treated with HDR using the Utrecht T&O applicator. Both CT and MRI imaging modalities were utilized to delineate clinical target volume (CTV) and organs-at-risk (rectum, sigmoid, bladder, and small bowel). Point A (left and right), vaginal mucosa, and ICRU rectum and bladder points were defined on CT. Two plans were generated for each patient using two prescription methods (PBP and TBP). 7Gy was prescribed to each point A for each PBP plan and to the target D90% for each TBP plan. Target V90%, V100%, and V200% were evaluated. In addition, D0.1cc and D2cc were analyzed for each organ-at-risk. Differences were assessed for statistical significance (p<0.05) by use of Student’s t-test. Results: Target coverage was comparable for both planning methods, with each method providing adequate target coverage. TBP showed lower absolute dose to the target volume than PBP (D90% = 7.0Gy vs. 7.4Gy, p=0.028), (V200% = 10.9cc vs. 12.8cc, p=0.014), (ALeft = 6.4Gy vs. 7Gy, p=0.009), and (ARight = 6.4Gy vs. 7Gy, p=0.013). TBP also showed a statistically significant reduction in bladder, rectum, small bowel, and sigmoid doses compared to PBP. There was no statistically significant difference in vaginal mucosa or ICRU-defined rectum and bladder dose. Conclusion: Target based prescription resulted in substantially lower dose to delineated organs-at-risk compared to point based prescription, while maintaining similar target coverage.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Particle Mass Flow Control for High-Temperature Concentrating Solar Receivers

This report summarizes the results of a two-year project funded by the U.S. Department of Energy's Solar Energy Technologies Office (SuNLaMP 1506) to evaluate the performance of high-temperature (>700 °C) particle receivers for concentrating solar power (see Appendix A for project information). In the first year, novel particle release patterns were designed and tested to increase the effective solar absorptance of the particle curtain. Modeling results showed that increasing the magnitude and frequency of different wave-like patterns increased the effective absorptance and thermal efficiency by several percentage points, depending on the mass flow rate. Tests showed that triangular-wave, square-wave, and parallel-curtain particle release patterns could be implemented and maintained at flow rates of ~10 kg/s/m. The second year of the project focused on the development and testing of particle mass-flow control and measurement methods. An automated slide gate controlled by the outlet temperature of the particles was designed and tested. Testing demonstrated that the resolution accuracy of the slide-gate positioning was less than ~1 mm, and the speed of the slide gate enabled rapid adjustments to accommodate changes in the irradiance to maintain a desired outlet temperature range. Different in-situ particle mass-flow measurement techniques were investigated, and two were tested. The in-situ microwave sensor was found to be unreliable and sensitive to variations in particle flow patterns. However, the in-situ weigh hopper using load cells was found to provide reliable and repeatable measurements of real-time in-situ particle mass flow. On-sun tests were performed to determine the thermal efficiency of the receiver as a function of mass flow rate, particle temperature, and irradiance. Models of the tests were also developed and compared to the tests.

14 SOLAR ENERGY↗
DOE OSTI2020

Deep Learning for Intelligent Bubble Size Detection in the Spallation Neutron Source Visual Target

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) will undergo proton power upgrade (PPU), increasing the proton beam power from 1.4 MW to 2.8 MW. From 2.8 MW, 2.0 MW will go to the current First Target Station and the rest will go to the future Second Target Station (STS). The First Target Station uses a liquid mercury target that is contained in a 316L stainless steel vessel. The proton beam is pulsed at 60 Hz, with a pulse of about 0.7μs. When the proton beam hits the target, the intense energy deposition leads to a rapid rise in temperature in the mercury. This temperature rise creates pressure waves that propagate through the mercury and cause cavitation erosion. The power upgrade will cause stronger pressure waves that will further increase damage because of cavitation. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at 1.4 MW. However, at higher power, additional mitigation is necessary. Therefore, the 2 MW target vessel will be equipped with swirl bubblers and an additional gas injection port near the nose to inject more gas in the target. To develop a gas injection strategy and design, flow visualization in water with a transparent prototypical target (“visual target”) was performed. Bubble sizes and their spatial distribution in the flow loop are crucial to understanding the effectiveness of the bubbles in mitigating pressure waves. Bubbles were generated in the visual target under varied conditions of input pressures with helium and air. Images were captured using a high-speed camera at varied frame rates at different positions away from the swirl bubbler and different depths in the flow loop under varying lighting conditions. Initially, methods such as circular Hough transforms were applied after a series of images processing to obtain a general distribution of bubble sizes. Bubbles smaller than 500 μm are preferred to effectively mitigate the effect of pressure waves, which demands an accurate bubble detection and sizing system. Intelligent detection and identification of bubble sizes alleviate misdetection and improves accuracies. Employing neural networks, intelligent detection of bubble sizes and their distribution was developed and provides a robust alternative to traditional techniques. Human intervention was employed to label in-focus and out-of-focus bubbles in the set of training images. An object detection network using a pretrained convolutional neural network was created that extracted the features from the training images. Data augmentation was used to improve network accuracy through a random transformation of the original data.

Rasheed, Fayaz↗
DOE OSTI2021

Controlling Heterogeneous Catalysis with Organic Monolayers on Metal Oxides

A key theme of heterogeneous catalysis research is achieving control of the environment surrounding the active site to precisely steer the reactivity toward desired reaction products. One method toward this goal has been the use of organic ligands or self-assembled monolayers (SAMs) on metal nanoparticles. Metal-bound SAMs are typically employed to improve catalyst selectivity but often decrease the reaction rate as a result of site blocking from the ligands. Recently, the use of metal oxide-bound organic modifiers such as organophosphonic acid (PA) SAMs has shown promise as an additional method for tuning reactions on metal oxide surfaces as well as modifying oxide-supported metal catalysts. In this Account, we summarize recent approaches to enhance catalyst performance with oxide-bound monolayers. These approaches include (1) modification of metal oxide catalysts to tune surface reactions, (2) formation of SAMs on the oxide component of supported metal catalysts to modify sites at the metal–support interface, and (3) enhancement of catalyst performance (e.g., stability) through modification of sites remote from the active sites. Further, both the headgroups and organic tail groups of PA SAMs or other ligands can influence reactions on metal oxide surfaces. Binding of the headgroup can selectively poison certain active sites, altering the selectivity in a manner analogous to metal-bound ligands (at the expense of active site quantity). Moreover, tail groups can be functionalized to interact favorably with reactants and intermediates, for instance through dipole–dipole interactions. On supported metal catalysts like Pt/Al 2 O 3 , PA SAMs can selectively form on the oxide support. This selective deposition allows for modification of the metal–support interface with minimal blockage of metal sites. PA headgroups were shown to provide tunable acid sites at the interface, dramatically improving hydrodeoxygenation rates of various alcohols. Additionally, organic tail functionality was used to activate or stabilize specific reactants at the interface, such as with the use of amine-functionalized PAs to stabilize chemisorption of CO 2 during the reverse water gas shift reaction. PAs have also been found to affect the electronic properties of bulk metal sites through long-range electron withdrawal via the oxide, providing an additional avenue to tune catalytic behavior. Finally, organic modifiers were shown to enhance catalytic performance without directly modifying the active site. For instance, in biphasic liquid environments the modification of catalyst particles with hydrophobic or hydrophilic SAMs shifts the selectivity of multipath reactions on the basis of the hydrophobicities of different intermediates and products. As another “long-range” effect, the deposition of ligands on oxide supports improved catalyst stability through both improved resistance to sintering and suppression of active site poisoning. The recent contributions discussed in this Account demonstrate the versatility and significant potential for the approach of modifying catalysts with oxide-bound organic monolayers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

The Influence of Microstructure on Oxidation Rate Of V–Cr–Ta–Zr Alloy During Its Chemical-Heat Treatment

Using the methods of scanning (electron backscatter diffraction) and transmission electron microscopy, an investigation of the influence of microstructure of a V–Cr–Ta–Zr alloy on the rate of surface oxide scale formation in the course of its chemical-heat treatment using oxidation in air is performed. It is shown that a preliminary plastic deformation, ensuring a multiple increase in the density of dislocations and misorientation boundaries, results in a 10% thicker surface oxide layer and a respective increase in the concentration of oxygen in the alloy during the final stage of its chemical-heat treatment. The role of this factor in developing the chemical-heat treatment regimes is discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Corrosion Behavior of AZ31 Magnesium Alloy Produced by Continuous Variable Cross Section Direct Extrusion

In order to study the corrosion behavior of magnesium alloys of high performance in the simulated seawater by continuous variable cross section direct extrusion (CVCDE), an electrochemical method and weight loss method were used to study the difference between AZ31 magnesium alloys produced by CVCDE with different numbers of interim dies to examine the electrochemical corrosion behavior and corrosion rate at 3.5 wt.% NaCl solution in this paper. Scanning electron microscopy and x-ray diffraction were used to analyze the morphology of corrosion surfaces and the composition of the corrosion products of samples soaked for different times. The results show that after CVCDE with different numbers of interim dies, the size of the microstructure is refined gradually, and the grain orientation is also different; with the increase in the number of interim dies, the thermodynamic corrosion tendencies are different, and the corrosion resistance of samples extruded by conventional extrusion is relatively good; the charge transfer and material transfer process are the two main factors affecting the corrosion rate, which determines the direction of the electrochemical reaction; the corrosion form of the sample extruded by CVCDE is the local corrosion which is the filiform corrosion and pitting corrosion, and the corrosion product is mainly water-insoluble Mg(OH){sub 2}.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Comparative Assessment of Pose Prediction Accuracy in RNA–Ligand Docking

Structure-based virtual high-throughput screening is used in early-stage drug discovery. Over the years, docking protocols and scoring functions for protein–ligand complexes have evolved to improve the accuracy in the computation of binding strengths and poses. In the past decade, RNA has also emerged as a target class for new small-molecule drugs. However, most ligand docking programs have been validated and tested for proteins and not RNA. Here, we test the docking power (pose prediction accuracy) of three state-of-the-art docking protocols on 173 RNA–small molecule crystal structures. The programs are AutoDock4 (AD4) and AutoDock Vina (Vina), which were designed for protein targets, and rDock, which was designed for both protein and nucleic acid targets. AD4 performed relatively poorly. For RNA targets for which a crystal structure of a bound ligand used to limit the docking search space is available and for which the goal is to identify new molecules for the same pocket, rDock performs slightly better than Vina, with success rates of 48% and 63%, respectively. However, in the more common type of early-stage drug discovery setting, in which no structure of a ligand–target complex is known and for which a larger search space is defined, rDock performed similarly to Vina, with a low success rate of ~27%. Further, Vina was found to have bias for ligands with certain physicochemical properties, whereas rDock performs similarly for all ligand properties. Thus, for projects where no ligand–protein structure already exists, Vina and rDock are both applicable. However, the relatively poor performance of all methods relative to protein–target docking illustrates a need for further methods refinement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Mitigation of Shuttle Effect in Li–S Battery Using a Self-Assembled Ultrathin Molybdenum Disulfide Interlayer

Lithium–sulfur batteries are promising for low-cost and high-energy storage, but their applications are still limited by poor cycling stability owing to soluble lithium polysulfide shuttling during battery operation. Avoiding shuttle effect is challenging but it is essential to avoid active material loss and prevent performance decay. We use an ultrathin layer of MoS 2 with thickness of 10–40 nm, which is 1–2 orders of magnitude thinner than conventional interlayers, for Li–S batteries to mitigate polysulfide shuttling. The MoS2 layer formed by exfoliated nanoflakes is deposited by the scalable liquid-based self-assembly method. With less than 1% of additional weight in the cathode, the MoS 2 interlayer with complete coverage inhibits polysulfide diffusion across the separator and therefore remarkably improves the battery performances. Reversible specific capacity reaches 1010 and 600 mA h g –1 at 0.5 and 2C rates, respectively, which decay slowly over 400 cycles (0.11% per cycle). Moreover, the MoS 2 films with high density of catalytic active flake edges enable high areal sulfur loading up to 10 mg cm –2 and areal capacity up to 9.7 mA h cm –2 at a current density of 3.2 mA cm –2 .

25 ENERGY STORAGE↗
DOE OSTI2021

Spatially Resolved Potential and Li-Ion Distributions Reveal Performance-Limiting Regions in Solid-State Batteries

The performance of solid-state electrochemical systems is intimately tied to the potential and lithium distributions across electrolyte–electrode junctions that give rise to interface impedance. Here, we combine two operando methods, Kelvin probe force microscopy (KPFM) and neutron depth profiling (NDP), to identify the rate-limiting interface in operating Si-LiPON-LiCoO 2 solid-state batteries by mapping the contact potential difference (CPD) and the corresponding Li distributions. The contributions from ions, electrons, and interfaces are deconvolved by correlating the CPD profiles with Li-concentration profiles and by comparisons with first-principles-informed modeling. Furthermore, we find that the largest potential drop and variation in the Li concentration occur at the anode–electrolyte interface, with a smaller drop at the cathode–electrolyte interface and a shallow gradient within the bulk electrolyte. Correlating these results with electrochemical impedance spectroscopy following battery cycling at low and high rates confirms a long-standing conjecture linking large potential drops with a rate-limiting interfacial process.

25 ENERGY STORAGE↗
DOE OSTI2021

Real-Time Lossless Compression for Ultra-High-Density Synchrophasor and Point on Wave Data

Modern advanced Phasor Measurement Units (PMUs) are developed with ultra-high reporting rates to meet the demand for monitoring the power systems dynamics in detail. Due to the large volume of data, the communication and storage systems are seriously challenged with the presence of Ultra-High-Density (UHD) synchrophasor and Point on Wave (POW) data. Therefore, it is an urgent task to compress the UHD data for more efficient communication and data storage. This paper proposes several methods to compress the synchrophasor and POW data in a lossless manner. First, an Improved-Time-Series-Special Compression (ITSSC) method is proposed to compress the UHD frequency data. Second, a Delta-difference Huffman method is combined with the TSSC algorithm to compress the UHD phase angle data. Finally, a cyclical high-order delta modulation method is proposed to compress the UHD POW data. The proposed models are extensively tested and compared with different existing lossless compression algorithms using the field-collected synchrophasor and POW data at different reporting rates. The results indicate that the proposed algorithms are efficient in performing lossless compression for the UHD synchrophasor and POW data in real time.

42 ENGINEERING↗
DOE OSTI2016

Evaluation of a deformable registration algorithm for subsequent lung computed tomography imaging during radiochemotherapy

Purpose: Rating both a lung segmentation algorithm and a deformable image registration (DIR) algorithm for subsequent lung computed tomography (CT) images by different evaluation techniques. Furthermore, investigating the relative performance and the correlation of the different evaluation techniques to address their potential value in a clinical setting. Methods: Two to seven subsequent CT images (69 in total) of 15 lung cancer patients were acquired prior, during, and after radiochemotherapy. Automated lung segmentations were compared to manually adapted contours. DIR between the first and all following CT images was performed with a fast algorithm specialized for lung tissue registration, requiring the lung segmentation as input. DIR results were evaluated based on landmark distances, lung contour metrics, and vector field inconsistencies in different subvolumes defined by eroding the lung contour. Correlations between the results from the three methods were evaluated. Results: Automated lung contour segmentation was satisfactory in 18 cases (26%), failed in 6 cases (9%), and required manual correction in 45 cases (66%). Initial and corrected contours had large overlap but showed strong local deviations. Landmark-based DIR evaluation revealed high accuracy compared to CT resolution with an average error of 2.9 mm. Contour metrics of deformed contours were largely satisfactory. The median vector length of inconsistency vector fields was 0.9 mm in the lung volume and slightly smaller for the eroded volumes. There was no clear correlation between the three evaluation approaches. Conclusions: Automatic lung segmentation remains challenging but can assist the manual delineation process. Proven by three techniques, the inspected DIR algorithm delivers reliable results for the lung CT data sets acquired at different time points. Clinical application of DIR demands a fast DIR evaluation to identify unacceptable results, for instance, by combining different automated DIR evaluation methods.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Particle velocity measurement within a free-falling particle curtain using microscopic shadow velocimetry

We report an optical method for particle velocity measurement that is suitable for the measurement of particle velocities within dense particle-laden flows with high spatial resolution. The technique is based on particle shadow velocimetry with the use of a long-distance microscopic lens for images collection. The narrow depth of field of the lens allows particles within the focal plane to have much higher pattern intensities than those outside it on the collected images. Data processing was then employed to remove particles from outside the focal plane based on the gradient of the signal and a threshold. Following this, particle velocity was calculated from two successive images in the usual way. The technique was successfully demonstrated in a free-falling particle curtain with volume fractions in the four-way coupling regime of near-spherical micro-particles falling under gravity. The method was successfully employed to measure the transverse velocity profile through the curtain, which is the first time that such a measurement has been performed. Other highly-fidelity experimental data, which is also well suited to model development and validation, include the particle mass flow rate, curtain thickness and opacity.

Han, Shipu (ORCID:0000000278545882)↗
DOE OSTI2018

Development of a Library for Conducting Monte Carlo Tallies on Heterogeneous Systems

A library is introduced that enables users to conduct Monte Carlo tallies on heterogeneous computing systems. The library can be built with or linked to a Monte Carlo transport code to provide tally capabilities for the project. The library provides a set of tools and an interface for constructing tallies that can be computed on CPUs or GPUs regardless of where the sample data was generated. The library can be incorporated into existing Monte Carlo transport codes at both the research and production level with minimal intrusion into the transport code. The tally library is capable of computing a variety of tallies including track-length histogram (mesh) tallies, collisionbased kernel density estimators, functional expansion tallies, eigenvalue sensitivity coefficients via iterated fission probability, and sensitivities of reaction rates or adjoint-weighted quantities via differential operator sampling. The parallelization methods are discussed and speedups are shown for 2-D and 3-D problems with comparisons to both the tally library CPU implementations as well as the tally capabilities in the host transport code. Performance results and examples are shown for MCNP, MCATK, and OpenMC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Coupled Bison/Thermochimica Simulation of Hydride Formation in Zircalloy Cladding

The report describes implementation of the thermodynamics models for simulation of zirconium hydride formation in LWR fuel cladding. The current models for ZrH x formation are based on empirical rate models that must calibrated to materials and regimes of interest. The thermodynamic approach enables hydride formation calculations based on fundamental thermodynamics principles and material composition. Thermodynamic formulations and models were implemented in the Idaho National Laboratory fuel performance code Bison using Material, Kernel and AuxKernel methods. The results for the Material and Kernel implementation are shown in this report. The Material method implementation naturally fits the concept of modeling evolution of material state in the material models. Given the relatively high cost of thermodynamic computation, the advantage of the AuxKernel compared to Material implementation is the ability to control the execution and computational cost. The implemented formulations are illustrated on example problems which fit the experimental data and satisfy the computational requirements of conservation equations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Deep Learning for In-Situ Layer Quality Monitoring during Laser-Based Directed Energy Deposition (LB-DED) Additive Manufacturing Process

Defects are a leading issue for the rejection of parts manufactured through the Directed Energy Deposition (DED) Additive Manufacturing (AM) process. In an attempt to illuminate and advance in situ quality monitoring and control of workpieces, we present an innovative data-driven method that synchronously collects sensing data and AM process parameters with a low sampling rate during the DED process. The proposed data-driven technique determines the important influences that individual printing parameters and sensing features have on prediction at the inter-layer qualification to perform feature selection. Three Machine Learning (ML) algorithms including Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN) are used. During post-production, a threshold is applied to detect low-density occurrences such as porosity sizes and quantities from CT scans that render individual layers acceptable or unacceptable. This information is fed to the ML models for training. Training/testing are completed offline on samples deemed “high-quality” and “low-quality”, utilizing only features recorded from the build process. CNN results show that the classification of acceptable/unacceptable layers can reach between 90% accuracy while training/testing on a “high-quality” sample and dip to 65% accuracy when trained/tested on “low-quality”/“high-quality” (respectively), indicating over-fitting but showing CNN as a promising inter-layer classifier.

36 MATERIALS SCIENCE↗