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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

Determining Coal Ash Impacts on Radium and Thorium Background Levels in Soil Using Rare Earth Element Analyses - 18604

One challenge at large remediation sites contaminated with radiological materials is differentiating between low-level site-related contamination and NORM. This is because sites contaminated with radiological materials, such as thorium processing and mining and milling facilities, often generate wastes that contain contaminants that are similar to NORM deposits. For sites in urban areas, this issue is further compounded due to the presence of historic industrial fill (historic fill) containing materials such as fly ash, coal ash, and red brick, that exhibit elevated radioactivity levels. These materials often have activity levels near, or even well above, a site's cleanup goal. At a large Superfund Site in the eastern US (Site), many of the suspected Site-related fill areas are commingled with coal and fly ash. As the cleanup criteria for the radionuclides of concern (ROC), radium (Ra) and thorium (Th), is 5 pico-Curies per gram above background, a four-pronged approach was developed to determine if the coal and fly ash are impacting the background levels of the ROCs. This evaluation included a review of boring logs to visually confirm the presence of historic fill, as well as coal fragments and coal ash; a literature review to establish the typical concentrations of Ra and Th found in coal and fly ash from US sources; the use of rare earth analyses to establish chemical signatures for non-Site related historic fill containing coal ash versus Site-related fill; and a quantitative analysis of Site-related data to determine if the radioactivity levels in historic fill containing coal were elevated. Soil samples were collected from two locations at the Site; fill areas containing coal ash that were not suspected to be impacted by Site activities, as well as fill areas containing coal ash that were associated with the former processing facility. These samples were analyzed for rare earth elements (REE), as well as Ra-228 and Th-232 and the ratios of lanthanum, cerium, and neodymium to Ra-228 and Th-232 were established for each sample. Based on a comparison of these data, a strong correlation was established between the rare earth/thorium decay chain ratios and the classification of material as either Site or non-Site related. These data were used to develop a higher background activity for fill areas containing non-Site related NORM. While the cleanup level defined in the Record of Decision remained unchanged, the higher background derived from the fly ash/coal ash material, as identified by REE analyses, resulted in higher project screening levels, which ensured that excavation activities did not 'chase' material that was not Site-related. To date, use of the coal ash background level has saved millions of dollars in cleanup costs since non-Site related contamination is not being remediated. Use of this approach to determine the appropriate background level for a site is relatively straightforward since it relies on visual observation of the soil for coal and fly ash, along with REE analyses, which is an inexpensive, quick, and established analytical method for soil samples. As long as a good rare earth profile of both contaminated and natural (in this case fly ash and coal ash) material can be established, the results can be quite definitive, which could result in significant volume reduction by minimizing the amount of material excavated and disposed of. This will lead to cost and time savings for what could be an otherwise costly and potentially complex excavation. Anyone performing environmental remediation of NORM contaminated sites may benefit from this paper and presentation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Sorption Behavior of Iodate Ions on Calcium Silicate Hydrate under a High Saline Condition - 18176

The sorption behavior of iodate ions on calcium-silicate hydrate (CSH) gel under high saline condition was examined by monitoring the concentrations of iodate ions and chloride ions using ion chromatography and Raman spectroscopy, without drying process. In the sorption experiments, a stable isotope I-127 was used as an alternative of I-129 which is radioactive one. Each sample was synthesized with mixing CaO powder, SiO{sub 2} as fumed silica and NaCl solution. Ca/Si molar ratios of CSH gel were set to 0.4, 0.8, 1.2 and 1.6 (add 0.2, 0.6, 1.0 and 1.4 only L/S = 20), and the concentration of NaCl solution was set to 0 M or 0.6 M for simulating the condition of fresh or saline groundwater. The liquid/solid (L/S) ratios of CSH gel were set to 10, 15 and 20, and the total weight of solid phase was 1.5 g. At the same time, NaIO{sub 3} solution was added to the sample in order to adjust its concentration to 1.0 mM, 0.67 mM and 0.5 mM for each L/S ratios. The synthesis procedure for all samples was conducted in a glove bag filled with nitrogen gas. The curing period was 7, 14, 30, and 60 days at a room temperature (298 K) with shaking at 120 strokes/min. As a results, the concentration of iodate ions in the liquid phase decreased for all samples under experimental conditions. Besides, the sorption behavior of iodate ions were hardly changed by the concentration of NaCl. That is, iodate ions migrated to solid phase in spite of the high concentration of NaCl. The distribution coefficients, Kd, increased as Ca/Si ratio increased, and hardly depended on NaCl concentration. The results of Raman analysis shows that the structure of CSH gel was almost not changed with or without NaCl from the viewpoint of the silicate chain under this condition. These results suggest that a sorption process except for the electrostatic process such as an ion exchange and a complexation exists between CSH gel and iodate ions. Besides, CSH gel might be able to contribute the retardation for the migration of iodate ions without changing its structure, even if the disposal environment are saturated by a high saline groundwater. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Solution-Based, Anion-Doping of Li 4 Ti 5 O 12 Nanoflowers for Lithium-Ion Battery Applications

Solution–based, anionic doping represents a convenient strategy with which to improve upon the conductivity of candidate anode materials such as Li 4 Ti 5 O 12 (LTO). As such, novel synthetic hydrothermally–inspired protocols have primarily been devised herein, aimed at the large–scale production of unique halogen–doped, micron–scale, three–dimensional, hierarchical LTO flower–like motifs. Although fluorine (F) doping has been explored, the use of chlorine (Cl) dopants is the primary focus here. Several experimental variables, such as dopant amount, lithium hydroxide concentration, and titanium butoxide purity, were probed and perfected. Furthermore, the Cl doping process did not damage the intrinsic LTO morphology. The analysis, based on interpreting a compilation of SEM, XRD, XPS, and TEM–EDS results, was used to determine an optimized dopant concentration of Cl. Electrochemical tests demonstrated an increased capacity via cycling of 12 % for a Cl–doped sample as compared with pristine LTO. Moreover, the Cl–doped LTO sample described in this study exhibited the highest discharge capacity yet reported at an observed rate of 2C for this material at 143mAh g –1 . Overall, these data suggest that the Cl dopant likely enhances not only the ion transport capabilities, but also the overall electrical conductivity of our as–prepared structures. Furthermore, to help explain these favorable findings, theoretical DFT calculations were used to postulate that the electronic conductivity and Li diffusion were likely improved by the presence of increased Ti 3+ ion concentration coupled with widening of the Li migration channel.

25 ENERGY STORAGE↗
DOE OSTI2018

Effect of NaOH Concentration and Adding Sequences on Structural and Magnetic Properties of Ni{sub 0.4}Co{sub 0.6}Fe{sub 2}O{sub 4} Nanopowders Prepared Via Co-precipitation Route

Ni{sub 0.4}Co{sub 0.6}Fe{sub 2}O{sub 4} nanopowders were prepared via the co-precipitation route followed by annealing treatment. The structural and magnetic properties of the as-synthesized samples were determined by XRD, FT-IR, TG-DSC, and PPMS measurements, respectively. The XRD patterns indicated a single-phase cubic spinel structure for all the Ni-Co ferrite samples, regardless of adding sequences of the reactants or NaOH concentration. The analysis of the XRD patterns revealed that the enhancement in lattice constant with increasing NaOH concentration is related to the prevention of oxidization of Co{sup 2+} ions in the Ni-Co ferrite lattice. The FT-IR spectra indicated that samples prepared in the B process have fewer impurities than those prepared in the A process. The enhancement in saturation magnetization with the increase in sodium hydroxide concentration could be attributed to the strengthening of super-exchange interaction between A and B sublattices, due to replacements of Co{sup 3+} ions (magnetic moment of 0 μ{sub B}) by Co{sup 2+} ions (magnetic moment of 3 μ{sub B}) at B sublattices. The obvious increase in the coercivity field with the increase in concentration of NaOH solutions can be interpreted in terms of enhancement of magneto-crystalline anisotropy that originated from gradual substitutions of Co{sup 3+} ions with Co{sup 2+} ions at the octahedral sites.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Comparative Study of the Effect of Magnetic Nanoparticle CoFe{sub 2}O{sub 4} on Fluctuation-Induced Conductivity of Y-123 and Y-358 Superconductors

In this study, a comparative investigation of the electrical conductivity fluctuations in nano-CoFe{sub 2}O{sub 4} added to Y{sub 3}Ba{sub 5}Cu{sub 8}O{sub 18±x} (Y-358) and YBa{sub 2}Cu{sub 3}O{sub 7−d} (Y-123) products is performed. All products were made using the solid-state reaction process. X-ray powder diffraction (XRD) analyses confirmed the formation of different phases. Scanning electron microscope (SEM) analysis shows the reduction of grain size with increasing the quantity of nano-CoFe{sub 2}O{sub 4} particles for both the Y-123 and Y-358 samples. The decrease of grain size is more accentuated in the case of the Y-358 samples compared with the Y-123 ones. The data of conductivity fluctuations are examined in terms of the derivative of the electrical resistivity with respect to temperature and the logarithmic derivative of the conductivity with regard to temperature. The results illustrate the existence of a transition with two stages; intragrain and intergrain. It is demonstrated that the addition of CoFe{sub 2}O{sub 4} nanoparticles affects the electrical conductivity fluctuations, the values of the critical exponents, and the fluctuation dimensionality in YBCO systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

A precise non-invasive blood glucose measurement system using NIR spectroscopy and Huber’s regression model

Diabetes is one of the prominent diseases around the world. Presently, invasive techniques need a finger prick blood sample . A repetitively painful procedure that produces the chance of infection. To resolve this issue, non-invasive measurement approach is proposed. In this paper, an efficient NIR wave based optical detection system is proposed with optimized post-processing regression model. After real-time data analysis, it has been found that the coefficient of determination (R{sup 2}) is improved with the value of 0.9084 using proposed regression model. Mean absolute derivative is also increased with 3.87 mg/dl corresponding to predicted blood glucose concentration. Mean absolute relative difference has exceeded to 3.25%, and average error is improved with 3.77% using proposed regression model. Average accuaracy has been analyzed 94–95% for predicted blood glucose concentration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Visual Tool for Assessing Stability of DER Configurations on Three-Phase Radial Networks

Here, we present a method and tool for evaluating the placement of Distributed Energy Resources (DER) on distribution circuits in order to control voltages and power flows. Our previous work described Phasor-Based Control (PBC), a novel control framework where DERs inject real and reactive power to track voltage magnitude and phase angle targets. Here, we employ linearized power flow equations and integral controllers to develop a linear state space model for PBC acting on a three-phase unbalanced network. We use this model to evaluate whether a given inverter-based DER configuration admits a stable set of controller gains, which cannot be done by analyzing controllability nor by using the Lyapunov equation. Instead, we sample over a parameter space to identify a stable set of controller gains. Our stability analysis requires only a line impedance model and does not entail simulating the system or solving an optimization problem. We incorporate this assessment into a publicly available visualization tool and demonstrate three processes for evaluating many control configurations on the IEEE 123-node test feeder (123NF).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Characterization of Uranium Ore Concentrate Chemical Composition via Raman Spectroscopy

Uranium Ore Concentrate (UOC, often called yellowcake) is a generic term that describes the initial product resulting from the mining and subsequent milling of uranium ores en route to production of the U-compounds used in the fuel cycle. Depending on the mine, the ore, the chemical process, and the treatment parameters, UOC composition can vary greatly. With the recent advent of handheld spectrometers, we have chosen to investigate whether either commercial off-the-shelf (COTS) handheld devices or laboratory-grade Raman instruments might be able to i) identify UOC materials, and ii) differentiate UOC samples based on chemical composition and thus suggest the mining or milling process. Twenty-eight UOC samples were analyzed via FT-Raman spectroscopy using both 1064 nm and 785 nm excitation wavelengths. These data were also compared with results from a newly developed handheld COTS Raman spectrometer using a technique that lowers background fluorescence signal. Initial chemometric analysis was able to differentiate UOC samples based on mine location. Additional compositional information was obtained from the samples by performing XRD analysis on a subset of samples. The compositional information was integrated with chemometric analysis of the spectroscopic dataset allowing confirmation that class identification is possible based on compositional differences between the UOC samples, typically involving species such as U3O8, α-UO2(OH)2, UO4•2H2O (metastudtite), K(UO2)2O3, etc. While there are clearly excitation λ sensitivities, especially for dark samples, Raman analysis coupled with chemometric data treatment can nicely differentiate UOC samples based on composition and even mine origin.

Su, Yin-Fong↗
DOE OSTI2025

Spectral kernel machines with electrically tunable photodetectors

Spectral machine vision collects spectral and spatial information as three-dimensional hypercubes and digitally processes them, which causes a data bottleneck, limiting power efficiency, frame rate, and spectral-spatial resolution. This work introduces spectral kernel machines (SKMs) to overcome these bottlenecks. SKM directly compresses spectral analysis through the output photocurrent and learns from example objects to identify and classify new samples in a "sniff-and-seek" mode. We experimentally demonstrated SKMs with electrically tunable bipolar black phosphorus-molybdenum disulfide (bP-MoS2) photodiodes in the near- and mid-infrared band and silicon photoconductors in the visible band, performing versatile intelligent tasks from chemometrics to semiconductor metrology. This architecture consumed substantially less power and was more than an order of magnitude faster than existing solutions for hyperspectral image analysis, defining an intelligent imaging and sensing paradigm with intriguing possibilities.

Zhang, Dehui↗
DOE OSTI2023

Water chemistry in flume channel and hyporheic zone (i.e., porewater) associated with: “Rethinking Aerobic Respiration in the Hyporheic Zone Under Variation in Carbon and Nitrogen Stoichiometry”

Dissolved oxygen (DO), total organic carbon (TOC), total nitrogen (TN), molecular data for organic matter, and biochemical reactions for surface water and porewater (i.e., hyporheic zone) collected from a water recirculating flume located at the University of Texas, Austin. The flume contained real river water from Lower Colorado River(Austin, TX) and clean sand. Hyporheic exchange in the flume was induced through The study aims to understand relationships between aerobic metabolism of organic matter and molecular characteristics of organic matter, such as thermodynamic signature and nitrogen content, through the extent of the hyporheic zone at 10 cm- resolution, and through time. During the experiment, organic matter (dry leaves) was added to the flume and removed after 24 hours. The water samples were collected before the addition of leaves, at the time of removal of leaves, and at hour 72. The water samples were analyzed using ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) and total organic carbon (TOC) and total nitrogen (TN) analysis. Dissolved oxygen content throughout the surface water and the hyporheic zone of the flume was measured with a large planar optode. This data package is associated with the publication ’ Rethinking Aerobic Respiration in the Hyporheic Zone Under Variation in Carbon and Nitrogen Stoichiometry’ published in Environmental Science and Technology (Turețcaia et al., 2023 https://doi.org/10.1021/acs.est.3c04765). The dataset is comprised of five folders (1) Diss_O2_pic, (2) input_files (3) output_files; (4) python_code; and (5) R_code . Diss_O2_pic contains siximages of dissolved oxygen distribution in a bedform at hours 0, 24, and 72 of the experiment conducted in a large recirculation flume. Images are in separate R and G channels (i.e., RGB). The input_files contains (1) a csv file with FTICR peaks identified within each sample, (2) a csv file with molecular information pertinent to FTICR data with Gibbs free energy calculations adjusted for environmental temperature, (3) a csv file containing concentrations of non-purgeable organic carbon measured throughout the experiment , (4) a csv file containing concentrations of total nitrogen measured throughout the experiment, (5) a csv file containing total biochemical reactions (i.e., transformations) identified in the dataset, (6) a csv containing transformation profiles, and (7) a csv file containing transformations with formulas, and (8) a jpg file with schematic representation of locations for sample collection. The output_files contains (1) and xlsx file containing percent biochemical reactions containing nitrogen identified across all 39 sample, (2) a csv file of merged FTICR data and molecular information files, (3) a csv files containing average Gibbs free energy within sampling domains and at each sampling location, (4) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 0, (5) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 24, (6) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 72, (7) a csv file with percent chemical classes identified across sampling locations at hour 0, (8) a csv file with percent chemical classes identified across sampling locations at hour 24, (9) a csv file with percent chemical classes identified across sampling locations at hour 72, and (10) a csv file containing percent nitrogen containing biochemical reactions identified across sampling locations at hours 0, 24, and 72. The python_code contains seven ipynb files which are Jupyter Notebooks used for data analysis and figures generation. The R_code contains 3 R files with R code used for data analysis and figures generation. This data package contains the processed data used in the associated manuscript. This data has not been previously published.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A scalable transformer model for real-time decision making in neutron scattering experiments

The U.S. Department of Energy's (DOE's) neutron research facilities at Oak Ridge National Laboratory (ORNL), including the High Flux Isotope Reactor (HFIR) and the Spallation Neutron Source (SNS), are a state-of-the-art neutron scattering facility that allows researchers to study the structure and dynamics of materials at the atomic scale. At the SNS, neutrons are measured using the time-of-flight (TOF) technique as they move through a neutron beamline to interact with a sample. Large volumes of neutron scattering data are collected and recorded in neutron event mode. Optimal productivity of the TOF instrument is limited due to the lack of real-time data analysis tools. The large amount of data generated by the experiments can be challenging to process and analyze in real time, particularly for experiments that require rapid feedback and adjustment of experimental parameters. The regular computer/workstation cannot keep up with the experiment speed to provide real-time feedback to adjust experimental parameters, so connecting the supercomputers available to the neutron facility is necessary to achieve real-time data analysis and experiment steering. To address this challenge, we exploit the Frontier supercomputer at Oak Ridge Leadership Computing Facility (OLCF) to train a scalable temporal fusion transformer model for real-time decision making of TOF neutron scattering experimentation. Here, in this paper, we present the results using Frontier to provide the processing power needed to rapidly process and analyze large volumes of single-crystal diffraction data collected at TOPAZ, a neutron time-of-flight Laue single-crystal diffractometer at the SNS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Uranium Immobilization through Fe(II) bio-oxidation: A Column study

Current research on the bioremediation of heavy metals and radionuclides is focused on the ability of reducing organisms to use these metals as alternative electron acceptors in the absence of oxygen and thus precipitate them out of solution. However, many aspects of this proposed scheme need to be resolved, not the least of which is the time frame of the treatment process. Once treatment is complete and the electron donor addition is halted, the system will ultimately revert back to an oxic state and potentially result in the abiotic reoxidation and remobilization of the immobilized metals. In addition, the possibility exists that the presence of more electropositive electron acceptors such as nitrate or oxygen will also stimulate the biological oxidation and remobilization of these contaminants. The selective nitrate-dependent biooxidation of added Fe(II) may offer an effective means of “capping off” and completing the attenuation of these contaminants in a reducing environment making the contaminants less accessible to abiotic and biotic reactions and allowing the system to naturally revert to an oxic state. Our previous DOE-NABIR funded studies demonstrated that radionuclides such as uranium and cobalt are rapidly removed from solution during the biogenic formation of Fe(III)-oxides. In the case of uranium, X-ray spectroscopy analysis indicated that the uranium was in the hexavalent form (normally soluble) and was bound to the precipitated Fe(III)-oxides thus demonstrating the bioremediative potential of this process. We also demonstrated that nitrate-dependent Fe(II)-oxidizing bacteria are prevalent in the sediment and groundwater samples collected from sites 1 and 2 and the background site of the NABIR FRC in Oakridge, TN. However, all of these studies were performed in batch experiments in the laboratory with pure cultures and although a significant amount was learned about the microbiology of nitrate-dependent bio-oxidation of Fe(II), the effects of complex processes (such as advective flow) present in the natural environment are unknown. The objective of the current studies was to address some of these short-comings in an attempt to develop this bioremediative strategy into a robust, field applicable technology. This objective was approached by both pure culture studies investigating the mechanism of Fe(II) oxidation by nitrate reducing bacteria and examining the flow dynamics and microbial processes in advective flow columns amended with Fe(II) and nitrate over an extended period.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Characterization of Non-pertechnetate Species Relevant to the Hanford Tank Waste

Among radioactive constituents present in the tank waste stored at the U.S. DOE Hanford Site, technetium-99 (Tc), which is generated from the fission of 235 U and 239 Pu in high yields, presents a unique challenge in that it has a long half-life ( = 292 keV; T1/2 = 2.11105 y) and exists predominately in soluble forms in the liquid supernatant and salt cake fractions of the waste. In the strongly alkaline environments prevalent in most of the tank waste, its dominant chemical form is pertechnetate (TcO 4 - , oxidation state +7). However, attempts to remove Tc from the Hanford tank waste using ion-exchange processes specific to TcO 4 - only met with limited success, particularly when processing tank waste samples containing elevated concentrations of organic complexants. This suggests that a significant fraction of the soluble Tc can be present as low-valent Tc (oxidation state < +7) (non-pertechnetate). The chemical identities of these non-pertechnetate species are poorly understood. Previous analysis of the SY-101 and SY-103 tank waste samples provided strong evidence that non-pertechnetate can be comprised of [fac-Tc(CO) 3 ] + complexes containing Tc in oxidation state +1 (Lukens et al. 2004). During the last three years, our team has expanded this work and demonstrated that high-ionic-strength solutions typifying tank waste supernatants promote oxidative stability of the [fac-Tc(CO) 3 ] + species (Rapko et al. 2013a; 2013b; Levitskaia et al. 2014; Chatterjee et al. 2015). Obtained results also suggest possible stabilization of Tc(VI) and potentially Tc(IV) oxidation states in the high-ionic-strength alkaline matrices particularly in the presence of organic chelators, so that Tc(IV, VI) can serve as important redox intermediates facilitating the reduction of Tc(VII) to Tc(I). Designing strategies for effective Tc management, including separation and immobilization, necessitates understanding the molecular structure of the non-pertechnetate species and their identification in the actual tank waste samples, which would facilitate development of new treatment technologies effective for dissimilar Tc species. The key FY 2016 results are summarized below.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Study of Poly(ether ketone ketone) (PEKK): Outgassing Characteristics and Likely Residual Synthesis Impurities

In May-June, 2020, a study was conducted to characterize the outgassing properties of a series PEKK (Poly(ether ketone ketone)) samples using cryo-GC/MS headspace analysis. Three sets of samples were interrogated: sample group 1 consisted of 2 additively manufactured PEKK samples (PEKK "ole and "New") prepared by KCNSC from powder material from Solvay Specialty Polymers USA, LLC. Sample groups 2 and 3 consist of 5 PEKK powder types (used as feedstock for additive manufacturing processes) and 4 additively-manufactured PEKK material lots, respectively. Contrary to expectations, all samples of PEKK material were observed to outgas sulfur-containing compounds. Other analyses (EDS/EMA, GC-TOF/MS of PEKK sample extractions) confirmed the presence of sulfur in the PEKK bulk material. Specifically, Diphenyl sulfone (used as a reagent or high-temperature solvent in the synthesis of Polyaryletherketone or PAEK polymers) was observed in three of the powders and in both the PEKK "Old" and "New" samples, suggesting that the source of the sulfur can be traced to impurities in the material left over from the synthesis process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Accurate Prediction of Algal Biomass Lipid, Protein, and Carbohydrate Composition with Machine Learning Regression Modelling of Near-IR Spectra

During large scale algal biomass cultivation, it is difficult to reliably control relative composition to target levels. Rapid determination of chemical composition is feasible by using near infrared (NIR) spectral data. We sought to build and improve on reliable high-throughput screening prediction method based on partial least squares regression (PLSR) by the application of artificial neural networks (ANN) and associated optimization strategies. The algal biomass sample set was designed and created in an iterative process of culturing in physiologically diverse conditions at the GAI field site, followed by compositional analyses at NREL. The workflow allowed us to identify gaps in compositional space for informing the subsequent cultivation and sampling efforts and generated a high quality set of 210 unique samples with chemical analysis results, spectral scanning data, and cultivation metadata. We observed a significant improvement in the performance of carbohydrate content predictions using an optimized ANN model compared to PLSR, with > 16% reduction in mean absolute percent error (MAPE) when tested on the same set of reserved data. The optimized ANN models for FAME and protein prediction performed exceptionally well with 5.99% and 5.09% MAPE, respectively. Application of these methods to detection and quantification of minor biomass constituents that are relevant to certain product streams has shown positive preliminary results, opening the possibility for extensions to the outputs of this powerful data type. All models are accompanied by prediction uncertainties and unsupervised spectral outlier detection to alert an operator to unreliable spectral data. These tools can be deployed for rapid determination of algal culture status, and cultivation and biomass quality improvement.

algal biofuels↗
DOE OSTI2016

Quantitative Analysis Guidance in Safety Software Validation

Quantitative analysis in software development has been a challenging topic over the years in safety software. While qualitative processes for vigorous safety software verification and validation (V and V) have been provided through standard such as IEEE 1012, quantitative analysis for V and V tasks such as correctness, completeness or accuracy evaluation have not been formally defined. In practice, there are quantitative analyses in terms of using software metrics. Many of these software metrics are useful in analyzing the test results. Some of them are used for providing guidance in code evaluation activities e.g. numbers of line of codes not exceeding certain limits, recursive calls are not allowed, etc. However, few can be used for providing quantitative analysis guidance for the V and V tasks such as completeness evaluation. AREVA Federal Services (AFS) has provided services for many nuclear projects in US. Through compliance with IEEE 1012, AFS V and V processes have provided vigorous qualitative processes ensuring quality level of the software products used in the project meeting the required nuclear software level. In addition, quantitative analysis is developed to provide structured validation framework ensuring 'zero defect' in the software products. This paper describes some aspects of the quantitative approaches using a sample safety application. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Uncertainty propagation and sensitivity analysis for constrained optimization of nuclear waste vitrification

Abstract The vitrification of high‐level waste (HLW) by heating a mixture of glass‐forming chemicals (GFCs) with the waste can be improved using a constrained optimization problem. This study explores how different uncertainty propagation (UP) methods implemented with the optimization process can affect the glass formulation of nuclear waste glasses. UP is the effort of propagating uncertain inputs through a system to understand and quantify output distributions. Uncertainty intervals are crafted from output distributions to inform the optimization algorithm. UP is often implemented with Monte Carlo (MC) sampling for large nonlinear systems, which can be difficult to implement within a constrained optimization algorithm that requires derivative information. Other UP methods often used for optimization under uncertainty (OUU) can be designed to work within an established constrained optimization framework. Methods of UP are evaluated in this study including iterative sampling approaches, first‐order approximations, and surrogate modeling with machine learning (ML). A method of dimensional reduction based on global sensitivity analysis is introduced to support the UP methods for the large dimensionality of the problem. Analytical UP methods able to achieve similar optimums 10 times faster than the baseline MC approach, and produce 93.9% similar output distributions are reported.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Multiphase Model of Semisolid Slurry Generation and Isothermal Holding During Cooling Slope Rheoprocessing of A356 Al Alloy

In the present paper, we present an experimentally validated 3D multiphase and multiscale solidification model to understand the transport processes involved during slurry generation with a cooling slope. In this process, superheated liquid alloy is poured at the top of the cooling slope and allowed to flow along the slope under the influence of gravity. As the melt flows down the slope, it progressively loses its superheat, starts solidifying at the melt/slope interface with formation of solid crystals, and eventually exits the slope as semisolid slurry. In the present simulation, the three phases considered are the parent melt as the primary phase, and the solid grains and air as secondary phases. The air phase forms a definable air/liquid melt interface as the free surface. After exiting the slope, the slurry fills an isothermal holding bath maintained at the slope exit temperature, which promotes further globularization of microstructure. The outcomes of the present model include prediction of volume fractions of the three different phases considered, grain evolution, grain growth, size, sphericity and distribution of solid grains, temperature field, velocity field, macrosegregation and microsegregation. In addition, the model is found to be capable of making predictions of morphological evolution of primary grains at the onset of isothermal coarsening. The results obtained from the present simulations are validated by performing quantitative image analysis of micrographs of the rapidly oil-quenched semisolid slurry samples, collected from strategic locations along the slope and from the isothermal slurry holding bath.

36 MATERIALS SCIENCE↗