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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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DOE OSTI2024

Quantum Imaging with X-rays

Quantum imaging encompasses a broad range of methods that exploit the quantum properties of light to capture information about an object. One such approach involves using a two-photon quantum state, where only one photon interacts with the object being imaged while its entangled partner carries spatial or temporal information. To implement this technique, it is necessary to generate specific quantum states of light and detect photons at the single-photon level. While this method has been successfully demonstrated in the visible electromagnetic spectrum, extending it to X-rays has faced significant challenges due to the difficulties in producing a sufficient rate of X-ray photon pairs and detecting them with adequate resolution. Here, we demonstrate record high rates of correlated X-ray photon pairs produced via a spontaneous parametric down-conversion process and we employ these photons to perform quantum correlation imaging of several objects, including a biological sample (E. cardamomum seedpod). Notably, we report an unprecedented detection rate of about 6,300 pairs per hour and the observation of energy anti-correlation for the X-ray photon pairs. We also present a detailed analysis of the properties of the down-converted X-ray photons, as well as a comprehensive study of the correlation imaging formation, including a study of distortions and corrections. These results mark a substantial advancement in X-ray quantum imaging, expanding the possibilities of X-ray quantum optical technologies, and illustrating the pathway towards enhancing biological imaging with reduced radiation doses.

Gofron, Kaz [ORNL] (ORCID:0000000314415736)↗
DOE OSTI2018

Control of Ionomer Distribution in Roll-to-Roll Coated Fuel Cell Catalyst Layers

Fuel cell catalyst layers are a complex mixture of catalyst particles and ion-conducting polymers. The performance of catalyst layers is highly dependent on microstructure, which must balance proton and electron conduction with gas transport. As fuel cells transition from the laboratory to industrial production for vehicles and other applications, there is a need to understand how manufacturing processes impact the microstructure and, ultimately, the performance of catalyst layers. In this work, we have focused on the roll-to-roll coating of catalyst layers for proton exchange membrane fuel cells. The catalyst layers are responsible for the electrochemical reactions that enable power production. In these devices the catalyst is commonly a Pt nanoparticle supported on porous carbon blacks. The ion conducting polymer, or ionomer, is typically a perfluorosulfonic acid. The most common being Nafion. To fabricate the catalyst layer, the catalyst particles are dispersed in an ink with the ionomer and cast to form the catalyst layer. Commonly, laboratory samples are prepared using spray coating or hand painting, which effectively coat many thin layers to achieve the desired catalyst layer thickness. This creates catalyst layers with uniform distributions of materials throughout the thickness of the full catalyst layer. In contrast, roll-to-roll methods, like slot die, gravure or screen printing, coat the catalyst layer as a single wet film. As the film dries, ink constituents are able to segregate, leading to a heterogeneous distribution of materials through the thickness of the layer. It is also known that the choice of solvent and drying rate can affect the morphology of the catalyst layer. Thus, there is a need to understand how ink formulation and the drying process influence the distribution of materials and catalyst layer morphology. Here, we have explored the influence of solvent and drying rate on morphology of roll-to-roll coated catalyst layers. We show the development of the Kelvin probe method as a rapid screening technique for qualitative analysis of ionomer distribution. We also utilize nano X-ray computed tomography to visualize electrode structure and to quantify particle-size and pore-size distributions, thickness-dependent ionomer distribution, tortuosity, and effective transport properties. We find that solvent has a strong influence on ionomer distribution, with less of an effect on porosity. Conversely, drying temperature has a strong influence on porosity, but less influence on ionomer distribution. Finally, we utilize in situ fuel cell performance testing and other advanced diagnostics to quantify the impact of catalyst layer properties on fuel cell performance and demonstrate that roll-to-roll coating is capable of coating high performance catalyst layers in multi-meter lengths.

14 SOLAR ENERGY↗
DOE OSTI2015

TU-AB-201-02: An Automated Treatment Plan Quality Assurance Program for Tandem and Ovoid High Dose-Rate Brachytherapy

Purpose: For tandem and ovoid (T&O) HDR brachytherapy in our clinic, it is required that the planning physicist manually capture ∼10 images during planning, perform a secondary dose calculation and generate a report, combine them into a single PDF document, and upload it to a record- and-verify system to prove to an independent plan checker that the case was planned correctly. Not only does this slow down the already time-consuming clinical workflow, the PDF document also limits the number of parameters that can be checked. To solve these problems, we have developed a web-based automatic quality assurance (QA) program. Methods: We set up a QA server accessible through a web- interface. A T&O plan and CT images are exported as DICOMRT files and uploaded to the server. The software checks 13 geometric features, e.g. if the dwell positions are reasonable, and 10 dosimetric features, e.g. secondary dose calculations via TG43 formalism and D2cc to critical structures. A PDF report is automatically generated with errors and potential issues highlighted. It also contains images showing important geometric and dosimetric aspects to prove the plan was created following standard guidelines. Results: The program has been clinically implemented in our clinic. In each of the 58 T&O plans we tested, a 14- page QA report was automatically generated. It took ∼45 sec to export the plan and CT images and ∼30 sec to perform the QA tests and generate the report. In contrast, our manual QA document preparation tooks on average ∼7 minutes under optimal conditions and up to 20 minutes when mistakes were made during the document assembly. Conclusion: We have tested the efficiency and effectiveness of an automated process for treatment plan QA of HDR T&O cases. This software was shown to improve the workflow compared to our conventional manual approach.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets

Abstract The specificity of toxicant-target biomolecule interactions lends to the very imbalanced nature of many toxicity datasets, causing poor performance in Structure–Activity Relationship (SAR)-based chemical classification. Undersampling and oversampling are representative techniques for handling such an imbalance challenge. However, removing inactive chemical compound instances from the majority class using an undersampling technique can result in information loss, whereas increasing active toxicant instances in the minority class by interpolation tends to introduce artificial minority instances that often cross into the majority class space, giving rise to class overlapping and a higher false prediction rate. In this study, in order to improve the prediction accuracy of imbalanced learning, we employed SMOTEENN, a combination of Synthetic Minority Over-sampling Technique (SMOTE) and Edited Nearest Neighbor (ENN) algorithms, to oversample the minority class by creating synthetic samples, followed by cleaning the mislabeled instances. We chose the highly imbalanced Tox21 dataset, which consisted of 12 in vitro bioassays for > 10,000 chemicals that were distributed unevenly between binary classes. With Random Forest (RF) as the base classifier and bagging as the ensemble strategy, we applied four hybrid learning methods, i.e., RF without imbalance handling (RF), RF with Random Undersampling (RUS), RF with SMOTE (SMO), and RF with SMOTEENN (SMN). The performance of the four learning methods was compared using nine evaluation metrics, among which F 1 score, Matthews correlation coefficient and Brier score provided a more consistent assessment of the overall performance across the 12 datasets. The Friedman’s aligned ranks test and the subsequent Bergmann-Hommel post hoc test showed that SMN significantly outperformed the other three methods. We also found that a strong negative correlation existed between the prediction accuracy and the imbalance ratio (IR), which is defined as the number of inactive compounds divided by the number of active compounds. SMN became less effective when IR exceeded a certain threshold (e.g., > 28). The ability to separate the few active compounds from the vast amounts of inactive ones is of great importance in computational toxicology. This work demonstrates that the performance of SAR-based, imbalanced chemical toxicity classification can be significantly improved through the use of data rebalancing.

Idakwo, Gabriel↗
DOE OSTI2016

SU-F-T-62: Three-Dimensional Dosimetric Gamma Analysis for Impacts of Tissue Inhomogeneity Using Monte Carlo Simulation in Intracavitary Brachytheray for Cervix Carcinoma

Purpose: The aim of this study was to investigate the impacts of tissue inhomogeneity on dose distributions using a three-dimensional (3D) gamma analysis in cervical intracavitary brachytherapy using Monte Carlo (MC) simulations. Methods: MC simulations for comparison of dose calculations were performed in a water phantom and a series of CT images of a cervical cancer patient (stage: Ib; age: 27) by employing a MC code, Particle and Heavy Ion Transport Code System (PHIT) version 2.73. The {sup 192}Ir source was set at fifteen dwell positions, according to clinical practice, in an applicator consisting of a tandem and two ovoids. Dosimetric comparisons were performed for the dose distributions in the water phantom and CT images by using gamma index image and gamma pass rate (%). The gamma index is the minimum Euclidean distance between two 3D spatial dose distributions of the water phantom and CT images in a same space. The gamma pass rates (%) indicate the percentage of agreement points, which mean that two dose distributions are similar, within an acceptance criteria (3 mm/3%). The volumes of physical and clinical interests for the gamma analysis were a whole calculated volume and a region larger than t% of a dose (close to a target), respectively. Results: The gamma pass rates were 77.1% for a whole calculated volume and 92.1% for a region within 1% dose region. The differences of 7.7% to 22.9 % between two dose distributions in the water phantom and CT images were found around the applicator region and near the target. Conclusion: This work revealed the large difference on the dose distributions near the target in the presence of the tissue inhomogeneity. Therefore, the tissue inhomogeneity should be corrected in the dose calculation for clinical treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-06: Traumatic Brachial Plexus Injury Imaging, Developing a Coherent Clinical Protocol From Literature Review Through Practice

Purpose: Medical Physics teams can now play a critical role to help plan and provide studied approaches for traumatic brachial plexus MR imaging (tbpMRI). This is especially important for coordination with uncommon applications, since it is challenging to select the right modality, parameters, and train technologists on the essential components. For this work, we started with a review of the medical literature, performed crossover/volunteer studies to bring tbpMRI to practice with greater image QC and protocol management. Methods: To the best of our knowledge, we reviewed the known searchable domain for tbpMRI. We found 69 total articles since 2000. Articles were evaluated with our published protocol for literature management (LIMES3). Two physicists and two radiologists condensed the information from all articles into a knowledgebase. Results: The initial literature demonstrated great heterogeneity, which was a sign that this area needed greater consistency. Despite inconsistency and imprecision, we extracted the most relevant targets using our long-term experience with protocol development in MSK. We ran volunteers on six different magnets of various field strengths with multiple receiver coils, and rebuilt a coherent protocol for tbpMRI. Our radiologists rated LIMES3 work as superior. We have received referrals from the ER and have conducted four patient evaluations. Conclusion: Traumatic brachial plexus MRI has great possible benefits for patients. This work supports the complexity of tbpMRI scanning. As this is rarely performed, it requires a more diligent protocol workflow, coordination of caregivers, and education within multiple clinical departments. Choosing the correct imaging exam can be critical, as patients can have significant neuropathy and/or paralysis. The LIMES3 protocol is well liked at our institution, and forms the cornerstone of understanding for our work. Our literature management led to a better clinical protocol creation despite the diffuse and inconclusive information presented in the existing medical literature.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Risk Importance Ranking of Fire Data Parameters to Enhance Fire PRA Model Realism

Fire is historically and analytically a significant contributor to nuclear power plant risk. The level of fire risk and the methods, tools and data for modeling this risk is highly debated by experts. One area of debate is the input data used in fire modeling and how to deal with this data’s high uncertainty. This report outlines initial work performed for determining the key parameters causing this uncertainty and how it propagates into nuclear power plant models. This research paves the way for the development of methods to reduce fire data uncertainty used in modeling. The Nuclear Regulatory Commission has mandated that nuclear power plants perform fire risk modeling. However, there are several issues with the current risk modeling implementation that affect the results. Approved modeling methods can be overly conservative and often do not match plant experience. Also, the data used in the modeling can have high uncertainties and is influenced by expert judgement. To evaluate input data uncertainty, researchers performed an initial review of several fire experiments done at Sandia National Laboratories. Uncertainties for fire data can come from many sources, such as experiment design constraints, environmental conditions, or other plant-specific aspects. There are many different significant and insignificant parameters driving the uncertainty. Additionally, the uncertainty of the different input data used in the fire modeling could have a significant or insignificant effect on the entire plant risk. A four-step methodology was developed to perform Integrated Probabilistic Risk Assessment Importance Ranking. A demonstration case using these steps was set up and three of the four steps were completed in fiscal year (FY) 2019 and the fourth step done FY 2020. These steps are: 1. The qualitative analysis of potential sources was conducted with the following items identified for the demonstration. • Maximum heat release rate • Time to maximum heat release rate • Duration of max heat release rate • Time to decay • Thermal conductivity of concrete • Specific heat of concrete • Density of concrete • Cable jacket thickness 2. A quantitative characterization of dominant sources of uncertainty was performed. A list of distributions and determined values of the dominant sources is shown in Appendix A. 3. A quantitative screening of the potential sources of uncertainty using Morris Elementary Effects Analysis was completed. An experimental model using the physics-based fire modeling tool Fire Dynamics Simulator was developed and coupled with the Risk Analysis Virtual Environment. The Morris analysis identified at least two parameters that can be eliminated as significant contributors (specific heat of concrete and cable jacket thickness). 4. Global importance measure (Global IM) analysis to generate a comprehensive ranking based on their influence on the plant risk. In this research, a moment-independent Global IM is used since it can address (a) uncertainty in the input parameters of the fire model, (b) uncertainty in the risk outputs, and (c) non-linearity and interactions among input parameters in the fire model, more accurately than the correlation-based and variance-based global methods. The observations from the research showed that, depending on the initial and boundary conditions of the fire scenarios, fire-induced damage could have a very small probability and could be dominated by the tail of the uncertainty distribution; hence, the accuracy of the correlation-based and variance-based methods is questionable. The moment-independent Global IM analysis in this research provides a better understanding of how experimental uncertainty data affects industry’s plant models and where improvements in that data will have the largest benefit for improving fire modeling accuracy in causing core damage. Among the five unscreened parameters obtained from the Morris EE analysis, the Global IM analysis results for the case study indicated that max heat release rate and fire location are the most important parameters. The report also outlines benefits of using a unified computational platform that integrates the underlying simulations (e.g., a fire progression model), quantitative screening (using the Morris EE method), and the Global IM analysis. A unified platform can (i) facilitate the ranking of input parameters considering multiple key fire scenarios simultaneously, rather than considering one scenario at a time, (ii) contribute to more explicit and accurate treatment of dependencies at multiple levels of Fire PRA, (iii) facilitate the sampling-based uncertainty quantification for Fire PRA, and (iv) help generating both “industry-wide” and "plant-specific" ranking of uncertainty sources in Fire PRA. Future research should be done to include additional parameters such as detection/suppression or cable fire spread. Adding a PRA software such as SAPHIRE to the RAVEN platform would help with plant model integration and improve treatment of fire-induced dependency. The I-PRA risk importance ranking methodology offered in this report can provide valuable information for efficiently (a) enhancing the realism of Fire PRA for existing plants and (b) supporting the development of Dynamic Fire PRA for advanced reactors and new plants.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Comparison of Infiltration Test Methods for Soil Health Assessment

Infiltration rate (IR) has been commonly used as a metric to evaluate soil quality and health. For the USDA Soil Quality Test Kit, a 15-cm (6-in) diameter (ID) cylinder is used to measure IR with 444 cm 3 (equivalent to 2.54 cm or 1 in) of water while other standard IR procedures require substantially larger volumes of water. The general objective of this study was to compare different methods for IR measurement. Using three replications, IR measurements were conducted along a 9-m (27-ft) long transect in two different soil types by the double-ring infiltrometer (DRI) using 25- and 50-cm (10-and 20-in, respectively) cylinders, single-ring infiltrometer (SRI) using 25- and 50-cm cylinders, Cornell sprinkle infiltrometer (CSI) using a 24.1-cm (9.5-in) cylinder, the USDA recommended procedure using a 15-cm diameter cylinder (hereafter referred to as USDA-15 method), and a modified USDA method using a 24.1-cm diameter cylinder. Although the USDA-15 method is simple and requires a small amount of water, based on high variability among replications and significant reduction in IR during early stages of water entry into the soil, the procedure does not offer an accurate estimate of the soil infiltration potential. The CSI procedure was reproducible, but it is more cumbersome to perform than other methods. The DRI, SRI, and CSI methods required a much greater volume of water than the USDA-15 method but produced results that are more consistent. The most consistent results were obtained by the CSI and DRI methods. The modified USDA method results were similar to the SRI method and were an improvement over the original USDA-15 method. For assessing soil health, additional investigations should be conducted to evaluate a modified version of the USDA procedure using a larger cylinder.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Chloroform Hydrodechlorination over Palladium–Gold Catalysts: A First-Principles DFT Study

Hydrodechlorination is a promising method for treating toxic chlorocarbon compounds. Pd is among the most effective catalysts for chloroform hydrodechlorination, and experiments have shown that the Pd–Au alloy catalyst yields superior catalytic performance over pure Pd. In this paper, we examine the chloroform hydrodechlorination mechanism over Pd(1 1 1) and Pd ML /Au(1 1 1) surfaces using periodic, self-consistent density functional theory calculations (DFT, GGA–PW91) and maximum rate analysis. We suggest that the reaction occurs on both surfaces through complete dechlorination of chloroform followed by hydrogenation of CH* to methane, and that the initial dechlorination step is likely the rate-limiting step. Finally, on Pd(1 1 1), the chloroform dechlorination barrier is 0.24 eV higher than the desorption barrier, whereas on Pd ML /Au(1 1 1), the chloroform dechlorination barrier is 0.07 eV lower than the desorption barrier, which can explain the higher hydrodechlorination activity of the Pd–Au alloy catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Analysis of predicted mean vote-based model predictive control for residential HVAC systems

Model Predictive Control (MPC) is an advanced process control method that has attracted much attention in building heating, ventilation, and air conditioning (HVAC) systems. Here, this paper analyzes the optimal precooling performance in residential buildings using MPC with two different comfort indices, namely, temperature and predicted mean vote (PMV). It first formulates, for each comfort index, an optimization problem that accounts for different factors, such as weather, home thermal condition, prediction horizon, time-of use (TOU) utility rate, and rated cooling capacity. The problem is then solved, resulting in an MPC strategy that determines the HVAC on/off control signal and minimizes energy cost over a receding time horizon while maintaining thermal comfort. The energy performance difference between temperature-based and PMV-based MPC strategies is subsequently investigated, especially in light of the interior wall surface temperature and under different combinations of the factors. Extensive simulation results demonstrated that the proposed MPC strategies are adaptive and their performances depend primarily on weather, home thermal condition, and prediction horizon, while the impact of TOU utility rate and rated cooling capacity is relatively small. Because the PMV-based MPC strategy can take advantage of the lower interior wall surface temperature due to precooling, it resulted in 8–45% cost savings for the scenarios investigated and an average increase of 0.042–0.113 in the absolute value of the PMV index compared to the temperature-based MPC strategy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

A mixing timescale model for TPDF simulations of turbulent premixed flames

Transported probability density function (TPDF) methods are an attractive modeling approach for turbulent flames as chemical reactions appear in closed form. However, molecular micro-mixing needs to be modeled and this modeling is considered a primary challenge for TPDF methods. In the present study, a new algebraic mixing rate model for TPDF simulations of turbulent premixed flames is proposed, which is a key ingredient in commonly used molecular mixing models. The new model aims to properly account for the transition in reactive scalar mixing rate behavior from the limit of turbulence-dominated mixing to molecular mixing behavior in flamelets. An a priori assessment of the new model is performed using direct numerical simulation (DNS) data of a lean premixed hydrogen–air jet flame. The new model accurately captures the mixing timescale behavior in the DNS and is found to be a significant improvement over the commonly used constant mechanical-to-scalar mixing timescale ratio model. An a posteriori TPDF study is then performed using the same DNS data as a numerical test bed. The DNS provides the initial conditions and time-varying input quantities, including the mean velocity, turbulent diffusion coefficient, and modeled scalar mixing rate for the TPDF simulations, thus allowing an exclusive focus on the mixing model. Here, the new mixing timescale model is compared with the constant mechanical-to-scalar mixing timescale ratio coupled with the Euclidean Minimum Spanning Tree (EMST) mixing model, as well as a laminar flamelet closure. It is found that the laminar flamelet closure is unable to properly capture the mixing behavior in the thin reaction zones regime while the constant mechanical-to-scalar mixing timescale model under-predicts the flame speed. Furthermore, the EMST model coupled with the new mixing timescale model provides the best prediction of the flame structure and flame propagation among the models tested, as the dynamics of reactive scalar mixing across different flame regimes are appropriately accounted for.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Facile synthesis of fusiform layered oxides assisted by microwave as cathode material for lithium-ion batteries

Graphical abstract: Fusiform layered oxides synthesized by microwave solvothermal reaction with excellent electrochemical property as cathode material for lithium-ion batteries. - Highlights: • LiMn{sub 0.25}Ni{sub 0.5}Co{sub 0.25}O{sub 2} is obtained by microwave solvothermal reaction. • Material synthesized at 800 °C exhibits fusiform hierarchical morphology. • High initial discharge capacity of 183 mAh g{sup −1} is reached at 0.1C. • 154 mAh g{sup −1} is remained with a capacity retention of 84.2% after 100 cycles. • Excellent rate capability is also obtained. - Abstract: A facile microwave solvothermal reaction is performed to synthesize novel LiMn{sub 0.25}Ni{sub 0.5}Co{sub 0.25}O{sub 2} ternary layered oxide with 1 D fusiform morphology. Scanning electron microscopy (SEM) images show that material synthesized at 800 °C well keeps the fusiform morphology of the precursor with a particle size of 100–300 nm. All the three elements are perfectly dispersed and a well-formed layered structure is obtained. Thus, good electrochemical performances with high initial discharge capacity of 183 mAh g{sup −1} is reached. Furthermore, high discharge capacity of 154 mAh g{sup −1} is remained with a capacity retention of 84.2% after 100 cycles at 20 mA g{sup −1}. Excellent rate capability is also obtained with high discharge capacity of 99 mAh g{sup −1} at 2000 mA g{sup −1}. It seems such facile microwave solvothermal method is one of the most promising candidates for preparing ternary layered oxides with excellent electrochemical properties as cathode material for lithium ion batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Identifying the Role of Magnesium Content in Assessing the Electrochemical Performance of (CoCuMgNiZn)O

High-entropy oxides (HEOs) featuring 5 or more metals in approximately equimolar ratios, such as the prototypical rock-salt-structured (CoCuMgNiZn)O, have attracted interest for their potential to display material properties superior to oxides with combinations of 4 or fewer of the component metals. In particular, (CoCuMgNiZn)O has shown promise as an anode for lithium-ion batteries with a high specific capacity retention over extended cycling. Previous studies have suggested that magnesium, despite being electrochemically inert, provides a crucial contribution to the favorable performance of this HEO by stabilizing the crystal structure through repeated charge–discharge cycles. This paper probes the extent and mechanism of the magnesium effect by using a facile microwave-assisted hydrothermal synthesis method to vary the level of Mg content. Moreover, we extensively characterized the product with techniques such as 4D-STEM and ICP-OES, which have not previously been applied in combination with this material, in order to elucidate the relationships among chemical composition, nanostructure, and performance. Here, we show that the level of Mg incorporation is positively correlated with long-term stability and negatively correlated with rate capacity, and that the latter effect yields a stronger influence upon the overall performance, with the best-performing sample possessing a Mg quantity equivalent to ∼1/5 that of an equimolar concentration. This finding demonstrates not only that the variation of individual elemental levels offers a promising and relatively unexplored avenue to optimize the electrochemical performance of HEO materials but also that it should not be assumed that equimolar compositions of constituent elements are necessarily the best.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Soil Environmental Conditions in the East River Watershed, CO

This dataset contains depth-resolved soil environmental variables collected between June 2016 and October 2018 from the Bradley Meadow site in the East River watershed. Datalogger output from 7 Campbell CS655 12 cm Soil Moisture and Temperature Sensors including depth, temperature, volumetric water content, and electrical conductivity are included in ‘BM_Merged_T_VWC_0616_10_18.csv’. Sensors were installed in June 2016. Data have been processed to merge raw sensor data and to remove additional variables. No additional QA/QC was performed. Measured pCO2 and depth are contained in ‘BM_EGM_WELL_CO2.csv’. These data represent gas well samples measured via injection using a PP Systems EGM-5 infra-red gas analyzer as described in the methods section. Measured CO2 surface flux values are contained in 'BM_EGM_Surface_Flux.csv'. These were measured using the PP Systems EGM-5 with the Soil Respiration Chamber attachment. Multiple reps are reported for each measurement including CO2 flux rate calculations using built-in linear and quadratic function methods, and average and standard deviations are taken across all reps and calculation methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

RCCS Testing with the Water-based NSTF: Year-1 Single-Phase Results

Under support from the Department of Energy (DOE) and the Office of Advanced Reactor Technologies (ART), a large scale test facility has been constructed to generate validation data for passive decay heat removal systems of advanced reactors. Located at Argonne National Laboratory, the Natural convection Shutdown heat removal Test Facility (NSTF) reflects key features of a ½ scale, water-based, Reactor Cavity Cooling System (RCCS). This report serves as a summary of the single-phase testing results obtained during the programs first year of matrix testing. An introduction to the high-level program objectives is first presented, followed by a brief summary of facility design, instrumentation, and control systems. Details of the NQA-1 driven test method are included, which govern the programs quality assurance requirements and provide a background for the testing strategy and procedures. Checkout activities, including verification of gross system mass and energy balances, heat loss quantification, and isothermal facility characterization, were performed early in the first year and results presented in this report. These tests have identified relevant facility characteristics such as K-factors, frictional pressure losses, parasitic heat loss rates, and transient heating response. Results are then presented from four accepted matrix tests where the facility established a steady-state, single-phase mode of flow operation. All matrix tests were performed with an identical top-level procedure: first initiating a heater power ramp to target levels, and then holding power levels constant until the facilities structural members and network piping reached thermal equilibrium. Upon obtaining stable thermal and hydraulic conditions, active cooling was initiated off of the bulk storage tank to maintain constant riser inlet temperatures of 30°C. This steady-state period was then held for a minimum required duration, at which point the heaters were ramped down and test concluded. The two baseline tests completed reflect conditions prototypic to the full scale plant at both normal operation, and design basis Depressurized Loss of Forced Cooling (DLOFC) conditions. These parameters are defined by full RCCS decay heat loads of 1.4 MWt and 2.1 MWt, which translate to NSTF scale thermal power levels of 34.4 kWt and 51.6 kWt, respectively. Two additional tests were also conducted, which repeated baseline cases but included modification by single parameter variations in decay heat load, or heater power, at 700 kWt, and 2.8 MWt. Finally, a scoping test was performed to demonstrate the facilities ability to operate in a two-phase mode of operation. The facility successfully operated for a 3-hour period at this mode, reaching peak inventory temperatures of 105°C and condensing approximately 50 gallons of boil-off inventory. The testing parameters for this demonstration were based off the design basis DLOFC condition, and will be the reference for new baseline cases as the program moves forward with two-phase matrix testing.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Estimation of Turbulence Parameters from Scanning Lidars and in-situ Instrumentation in the Perdigao 2017 Campaign

The understanding of the sources, spatial distribution and temporal variability of turbulence in the atmospheric boundary layer (ABL) and improved simulation of its forcing processes require observations in a broad range of terrain types and atmospheric conditions. In this study, we estimate turbulence kinetic energy (TKE) dissipation rate using multiple techniques, including traditional in-situ measurements of sonic anemometers on meteorological towers, a hot-wire anemometer on a tethered lifting system (TLS), as well as remote-sensing retrievals from a vertically staring lidar and two lidars performing range-height indicator (RHI) scans. For the retrieval of e from the lidar RHI scans, we introduce a modification of the Doppler Spectral Width (DSW) method. This method uses spatio-temporal averages of the variance of the line-of-sight (LOS) velocity and the turbulent broadening of the Doppler backscatter spectrum. We validate this method against the observations from the other instruments, also including uncertainty estimations for each method. The synthesis of the results from all instruments enables a detailed analysis of the spatial and temporal variability of e across a valley between two parallel ridges at the Perdigao 2017 campaign. We find that the shear zones above and below nighttime low-level jets (LLJ) experience turbulence enhancements, as does the wake of a wind turbine (WT). We analyze in detail how e varies in the early morning of 14 June 2017, when the turbulence in the valley, approximately eleven rotor diameters downstream of the WT, is still significantly enhanced by the WT wake.

17 WIND ENERGY↗
DOE OSTI2017

Thermal Analysis of a Fuel Channel

To better study and understand the efficiency of fuel channels in reactors, a thermal analysis method was developed to conduct a study on any fuel channel to gain a better understanding of the temperature, heat rate, heat flux, and power profiles of such fuel channels. This study is conducted on a typical PWR (Pressurized Water Reactor) fuel assembly. The justification for specifically choosing a PWR fuel channel is because PWRs are the most widely used type of reactors around the world. This study was performed using NEWT code in SCALE 6, ANSYS, and SolidWorks. MATLAB and Excel were also utilized for some of the calculations. The power and heat rate of the fuel rod were calculated, alongside a 2D mapping of temperature, heat flux, directional heat flux, and thermal error on a 3D model of the fuel channel by analyzing the fuel rod and the surrounding water moderator independently.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗