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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Hexagonal Distributed Embedded Energy Converters (HexDEECs)

Distributed Embedded Energy Converter Technologies (DEEC-Tec) is a new domain for marine renewable energy research that utilizes a conglomeration of small distributed embedded energy converters (DEECs) that, in aggregate, form larger metamaterial frameworks. These resulting DEEC-Tec metamaterials can then, in turn, be used to construct flexible ocean wave energy converters called flexWECs. DEEC-Tec enables flexWECs: (i) to be inherently broad-banded ocean wave frequency energy converters and (ii) to have an inherent lack of highly loaded rigid bodies. The DEEC-Tec domain also benefits the marine renewable energy domain by inherently availing ways that marine energy can be harvested and converted that heretofore has not yet been considered possible: real-time execution of transforming topologies (e.g., actively changing a flexWEC's shape and form) and morphologies (e.g., actively changing a flexWEC's stiffness and damping throughout its entire structure). Presented, is one specific type of DEEC, a HexDEEC, that shows promise in aiding the adoption and further development of the DEEC-Tec domain - it is a small energy transducer being developed by the United States National Renewable Energy Laboratory. The HexDEEC is a small (characteristic length approximating a centimeter) energy transducer that converts the dynamic deformations of an elastomer into electricity through a charging-discharging cycle of a capacitor whose capacitance is varied by those elastic deformations. The HexDEEC is composed of a hyperelastic hexagonal housing (nominally silicon rubber) with six electrodes on its inner faces. The upper three electrodes share the same charge while the lower three electrodes oppose the upper electrode charges. Externally, the HexDEEC has two arms extending away from the middle vertices of the hexagon. Via principles governing the relationship between electrical capacitance and electrical potential (voltage and charge), electricity is generated when the HexDEEC's arms are dynamically pulled or released under tensile loading as doing so causes the distance between the upper and lower sets of electrodes to change - varying the energy converter's overall capacitance. Analytical and numerical modeling have already been used to estimate the electrical energy produced by a HexDEEC. The cursory models approximate the HexDEEC as a parallel plate variable capacitor - simplifying from six to two opposing plates with a constant dielectric volume between those two plates. To account for the elastic HexDEEC material properties, software such as SolidWorks and STAR-CCM+ have been used to generate hyperelastic models; notably, Mooney-Rivlin based models. Individual HexDEECs have been fabricated by drawing uncured liquid silicon rubber into molds via vacuum pressure. To simplify manufacturing, HexDEEC sub-components - e.g., electrodes, wires - can be placed within those molds such that they are directly embedded into the hexagonal housing during the curing process. Furthermore, DEEC-Tec metamaterials can be created by interweaving or sequentially layering multiple HexDEEC strands together. The HexDEEC based metamaterial could then generate electricity through its gross deformations. Ultimately, HexDEECs represent a specific type of energy transducer that can be leveraged, by the DEEC-Tec domain, to create metamaterials used to construct novel flexWECs.

DEEC-Tec↗
DOE OSTI2014

SU-F-BRD-04: Development of a Secondary MU Calculation Tool for An Integrated MR-LINAC

Purpose: To develop a fast secondary MU calculation tool for an integrated MR-Linac, an emerging technology for delivering image-guided on-line adaptive therapy. Methods: A software tool was developed to implement a modified Clarkson integration algorithm for point-dose calculation, considering the dosimtric effect of a magnetic field. A research planning system, considering the presence of a perpendicular 1.5 T magnetic field, was used to extract the beam data (e.g., depth doses and beam profiles) required for the MU calculation in homogeneous phantom of 60×60×40 cm3 for a prototype of MR-Linac integrating a 1.5 T MR scanner with 6MV photon beams. These dosimetric data may be replaced with those to be collected during the commissioning measurement of the MR-Linac. Results: The presence of the magnetic field resulted in noticeable changes including (1) shifts in beam profiles for small fields (< 2×2 cm2), and (2) changes in central-axis doses when one of field edges is < 2 cm away from the central axis. For example, the maximum change in central-axis dose was up to 8% for one of the field borders with a distance away from the central axis of <1 cm. These changes are relevant for the MU calculation particularly for IMRT and VMAT, where most of segments are small. These magnetic field affected beam profiles and depth doses were included in the software tool. The MU calculations from the software tool for selective representative plans were found to agree with those from the research planning system within 10%. Conclusion: The presence of a perpendicular magnetic field results in noticeable changes in beam profiles and depth doses for small fields. These changes are included in the secondary MU calc{sup 33}u{sup 3}lation to be used as a redundancy check for an integrated MR-Linac.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Investigation of Donor and Acceptor Ion Implantation in AlN

AlGaN alloys with high Al composition and AlN based electronic devices are attractive for high voltage, high temperature applications, including microwave power sources, power switches and communication systems. AlN is of particular interest because of its wide bandgap of ~6.1eV which is ideal for power electronic device applications in extreme environments which requires high dose ion implantation. One of the major challenges that need to be addressed to achieve full utilization of AlN for opto and microelectronic applications is the development of a doping strategy for both donors and acceptors. Ion implantation is a particularly attractive approach since it allows for selected-area doping of semiconductors due to its high spatial and dose control and its high throughput capability. Active layers in the semiconductor are created by implanting a dopant species followed by very high temperature annealing to reduce defects and thereby activate the dopants. Recovery of implant damage in AlN requires excessively high temperature. In this SBIR program we began the investigation by simulation of ion beam implantation profiles for Mg, Ge and Si in AlN over wide dose and energy ranges. Si and Ge are implanted to achieve the n-type doping, Mg is investigated as a p-type doping. The simulation of implantation profiles were performed in collaboration between NRL and Agnitron using a commercial software known as Stopping and Range of Ions in Matter (SRIM). The simulation results were then used as the basis for ion implantation of AlN samples. The implanted samples were annealed by an innovative technique under different conditions and evaluated along the way. Raman spectroscopy and XRD were used to determine the crystal quality of the implanted samples, demonstrating the effectiveness of annealing in removing implant induced damage. Additionally, SIMS was used to verify that a nearly uniform doping profile was achieved near the sample surface. The electrical characteristics of the implanted samples were evaluated by TLM and Hall techniques. Generally, the implanted samples before and after annealing were found to be very resistive. Further work is required before the superior properties of AlN can be fully utilized.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

VADER: A Tool for Criticality Safety Validation

The purpose of criticality safety is to prevent any inadvertent criticality from occurring during the handling or storage of fissile material. Calculations are frequently used to demonstrate that a sufficient subcritical margin exists. Validation is a key aspect of the evaluation process, establishing the suitability, accuracy, and associated uncertainty of the computational method and data to be used for the intended application. The validation process is performed by comparing the results of critical experiments with the calculated results from models of the experiments using the computational method to be validated. Laboratory critical experiments are controlled systems that achieve a k eff of approximately 1 in order to investigate the parameters at which such a critical condition is achieved. The validation parameters that are traditionally applied to safety analysis calculations are the bias and the bias uncertainty . The bias is the deviation of the average k eff of the validation suite from unity. The bias uncertainty accounts for the statistical uncertainty in the bias based on the standard deviation, sample size, and distribution of k eff values of the validation suite. The values of bias and bias uncertainty ensure that the systems predicted to be subcritical by the computational method will indeed be subcritical. The bias and bias uncertainty are often combined to determine an upper subcritical limit (USL) or computational margin that can then be applied to safety analysis calculations. Many methods have been developed by different organizations to calculate the bias and bias uncertainty for various types of criticality analyses. Each of these methods typically requires that the validity of various underpinning statistical assumptions be confirmed to demonstrate that the method is appropriate for the analysis of a given validation suite. An example of the validation decision making flow is shown in Fig.1. As shown in Fig. 1, the analyst performing the validation fits a trend line to the data and performs a test to determine if the trend was a statistically better representation of the data than if it were treated as an uncorrelated sample. If the trend line is a better representation of the data, then the analyst uses any one of a number of trending techniques to determine the bias and bias uncertainty. If a trend is not an appropriate representation of the data, then the analyst proceeds to perform a normality assessment for the data. If the normal assumption can be shown to be acceptable, then the analyst calculates the bias and bias uncertainty with the parametric technique. If the assumption of normality cannot be justified, then the nonparametric technique is used. Once the decision flow has been followed and the appropriate technique has been selected, the bias and bias uncertainty is typically combined with an administrative margin to determine a USL below which calculated values of k eff for safety analysis models can be considered subcritical. The calculations used in each decision are often performed with spreadsheets or with small programs available at various sites performing criticality analyses. Expertise in understanding and interpreting the results must be maintained to perform these calculations. This can often be an error-prone process. Oak Ridge National Laboratory (ORNL) is currently developing the Validation and Data Evaluation Resource (VADER) to simplify and automate the criticality safety validation process and to provide a software quality assurance pedigree to the calculational methods used. This paper discusses the use of the Fulcrum user interface with VADER, the anticipated initial capabilities of VADER to perform validation analyses, and the output from the code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Denoising Seismograms in the Time Domain Using a Deep Learning Model

Deep learning has emerged as a transformative tool for enhancing the extraction of reliable information from seismograms, addressing the increasing demand for precise and efficient seismic data analysis. We introduce an innovative encoder–decoder deep learning model, named WaveDenoiser, designed for noise reduction in the time domain, thereby eliminating the need for spectrogram computations that have been used for existing deep learning tools and significantly improving processing speed. Utilizing the benchmark dataset that is Stanford Earthquake Dataset, we developed three models of varying sizes: base, medium, and large. Notably, the large (referred to as WaveDenoiser) model demonstrated superior performance, achieving a median signal‐to‐noise ratio improvement of 8.8 dB on in‐distribution unseen data (in the same geographic region) and 7.7 dB on out‐distribution unseen data (in a new geographic region), outpacing both the base and medium models. Further evaluation of the WaveDenoiser model revealed a reduction in median arrival‐time errors by 0.02 s for P waves and 0.01 s for S waves when processing waveforms prior to phase picking using PhaseNet on in‐distribution unseen data. When tested on out‐distribution unseen data, the model also effectively reduced the P‐wave median arrival‐time error by 0.02 and 0.01 s in median arrival‐time error for S waves. Importantly, the application of WaveDenoiser resulted in a significant reduction of phase picking outliers by 1.1% to 3.6% for both P and S waves. In addition, we achieved over five times acceleration in processing speed compared with the seisBench implementation of DeepDenoiser. Our findings underscore the potential of WaveDenoiser as a powerful tool for improving seismic data analysis and processing efficiency.

P-waves↗
DOE OSTI2019

Informative Path Planning for Mapping Radiation

This project involves making measurements of contaminated areas using portable radiation detectors and small robots. Tasks involve operating detectors and small robots, combining data acquisition for the two systems, and automating the systems. The end result is a radiation map of contamination areas. Localization of radioactive sources and mapping of contamination distribution is essential when responding to emergencies, or when dealing with cleanup efforts. Radiation maps are used for situational awareness and for establishing a safe perimeter. However, it may be hazardous or impossible for humans to safely enter the site and survey the area. Informative Path Planning (IPP) is used to design a path for a robotic sensor platform to gather the most information about the radiation distribution while operating under the set of constraints given by the dynamics of the robot and other requirements such as minimizing the overall mission time. The key challenge for IPP is the tight coupling in multiple layers of decisions: Selection of locations to visit; Allocation of sensors to those locations; Processing of information gathered. Given a robot equipped with a basic gamma detector and Lidar sensor, how can we efficiently explore an unknown environment in such a way that we can satisfy the robot's constraints while simultaneously maximizing the accuracy of the map and minimizing the total runtime? This work presents a systematic procedure for IPP and environmental mapping that: Selects the best locations at which to sample; Finds the best path for robots; Estimates the measurement value at unknown locations using a Gaussian Process regression framework. Given a set of points where radiation measurements were taken, we are utilizing a Gaussian Process Regression with a Matern kernel to reconstruct the shape of the underlying ground truth. Mapping is done via the Robot Operating System's OpenSlam Gmapping package, which creates a 2D occupancy grid map. Simulated trials were run with a radiation source placed at random locations, and allowing the robot to select and move towards 20 samples at separate locations, as well as sampling along the path while moving. The simulated sensor model assumed an efficiency of 0.3, collection time of 1 second. Various weighting schemes were tested and compared. Quantitative evaluations often favored exploitation-heavy weighting schemes where μ was emphasized, with the Root Mean Squared Error (RMSE) quickly tending towards 2, whereas qualitative comparisons would favor exploration-biased schemes with greater weight on σ. The difference comes from operators often favoring knowing the general location of a source, rather than the exact properties of a source. Weighting of the path-length π often reduced the quality of the regression as less exploration occurred, however this may be deemed a worthwhile trade-off under certain circumstances, such as with sensitive robots. Successfully developed a methodology for informative path-planning for a robot to efficiently gather information and create a map of radiation. In the future, we would like to focus on: Hardware trials with integration of the robot platform and the IPP software; More refined sensor and environmental modeling; Multiple robot platforms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

TH-EF-BRB-07: Novel Hardware and Software Platform for Intermediate Energy 4π Radiotherapy

Purpose: To develop a robust and efficient platform for the optimization and robotic delivery of highly noncoplanar intensity modulated radiotherapy, which enables significant reduction of normal tissue toxicity and escalation of tumor dose. Methods: An innovative high-output compact 3 MV linac was designed for mounting onto a commercial robotic system in order to access the entire 4π beam solution space without moving the patient couch. The use of intermediate energy X-rays for radiotherapy was evaluated in comparison to clinical plans delivered using 6 MV X-rays and a state-of-the-art delivery system. Monte Carlo simulations of a 3 MV percent depth dose curve were performed for intermediate energy dose calculation. The beam model was used to create a convolution/superposition-based dose calculation engine for 3MV X-rays. The 4π greedy column generation algorithm was used for optimized beam selection and fluence map optimization. Results: A detailed design of the first 3 MV linac capable of producing a competitively high dose rate of >800 cGy/min at 100 cm was completed and verified through extensive simulation. The complete linac head including a multileaf collimator can access most of the 4π solution space including the posterior orientations without changing the couch height. When compared to 6 MV clinical plans, the proposed 3 MV 4π plans demonstrated significantly better dose compactness and normal tissue sparing in brain, prostate, and partial breast treatment plans. Conclusion: We demonstrate the design of a highly versatile radiotherapy machine to natively deliver non-coplanar 4π radiotherapy without the need to move the patient during treatment. This novel platform is efficient and capable of providing dosimetry that is 30–50% more compact than existing therapy platforms. The new system is projected to be cost effective due to improved treatment time and automation. NIH R43CA183390, NIH R01CA188300.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Watchdog Project

The Watchdog Project completed 100% of the project Statement of Project Objective (SOPO). The Watchdog project was a very aggressive project looking to accomplish commercialization of technology that had never been commercialized, as a result it took six years to complete not the original three that were planned. No additional federal funds were requested from the original proposal and SEL contributed the additional cost share required to complete the project. The result of the Watchdog Project is the world’s first industrial rated Software Defined Network (SDN) switch commercially available. This technology achieved the SOPOO and DOE Roadmap goals to have strong network access control, improve reliability and network performance, and give the asset owner the ability to minimize attack surface before and during an attack. The Watchdog project is an alliance between CenterPoint Energy Houston Electric, Pacific Northwest National Laboratories (PNNL), and Schweitzer Engineering Laboratories, Inc. (SEL). SEL is the world’s leader in microprocessor-based electronic equipment for protecting electric power systems. PNNL performs basic and applied research to deliver energy, environmental, and national security for our nation. CenterPoint Energy is the third largest publicly traded natural gas delivery company in the U.S and third largest combined electricity and natural gas delivery company. The Watchdog Project efforts were combined with the SDN Project efforts to produce the entire SDN system solution for the critical infrastructure. The Watchdog project addresses Topic Area of Interest 5: Secure Communications, for the DEFOA- 0000359 by protecting the control system local area network itself and the communications coming from and going to the electronic devices on the local network. Local area networks usually are not routed and have little or no filtering capabilities. Combine this with the fact control system protocols are designed with inherent trust the control system owners have very little choice on how to protect communications on the local network. The Watchdog project reduces security risks in electric sector control system local area networks (LANs) by providing: Network access control (NAC) Multi-Layer firewall (physical through transport layer) Containment of malware or unauthorized traffic spreading across the network White list protocols and application message types filtering Configurable, proactive traffic engineering The Watchdog project achieved all of the above by developing an SDN switch.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

National Geothermal Data System: Transforming the Discovery, Access, and Analytics of Data for Geothermal Exploration

Compendium of Papers from the 38th Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California February 11-13, 2013 The National Geothermal Data System (NGDS) is a distributed, interoperable network of data collected from state geological surveys across all fifty states and the nation’s leading academic geothermal centers. The system serves as a platform for sharing consistent, reliable, geothermal-relevant technical data with users of all types, while supplying tools relevant for their work. As aggregated data supports new scientific findings, this content-rich linked data ultimately broadens the pool of knowledge available to promote discovery and development of commercial-scale geothermal energy production. Most of the up-front risks associated with geothermal development stem from exploration and characterization of subsurface resources. Wider access to distributed data will, therefore, result in lower costs for geothermal development. NGDS is on track to become fully operational by 2014 and will provide a platform for custom applications for accessing geothermal relevant data in the U.S. and abroad. It is being built on the U.S. Geoscience Information Network (USGIN) data integration framework to promote interoperability across the Earth sciences community. The basic structure of the NGDS employs state-of-the art informatics to advance geothermal knowledge. The following four papers comprising this Open-File Report are a compendium of presentations, from the 38th Annual Workshop on Geothermal Reservoir Engineering, taking place February 11-13, 2013 at Stanford University, Stanford, California. “NGDS Geothermal Data Domain: Assessment of Geothermal Community Data Needs,” outlines the efforts of a set of nationwide data providers to supply data for the NGDS. In particular, data acquisition, delivery, and methodology are discussed. The paper addresses the various types of data and metadata required and why simple links to existing data are insufficient for promoting geothermal exploration. Authors of this paper are Arlene Anderson, US DOE Geothermal Technologies Office, David Blackwell, Southern Methodist University (SMU), Cathy Chickering (SMU), Toni Boyd, Oregon Institute of Technology’s GeoHeat Center, Roland Horne, Stanford University, Matthew MacKenzie, Uberity, Joe Moore, University of Utah, Duane Nickull, Uberity, Stephen Richard, Arizona Geological Survey, and Lisa Shevenell, University of Nevada, Reno. “NGDS User Centered Design: Meeting the Needs of the Geothermal Community,” discusses the user- centered design approach taken in the development of a user interface solution for the NGDS. The development process is research based, highly collaborative, and incorporates state-of-the-art practices to ensure a quality user interface for the widest and greatest utility. Authors of this paper are Harold Blackman, Boise State University, Suzanne Boyd, Anthro-Tech, Kim Patten, Arizona Geological Survey, and Sam Zheng, Siemens Corporate Research. “Fueling Innovation and Adoption by Sharing Data on the DOE Geothermal Data Repository Node on the National Geothermal Data System,” describes the motivation behind the development of the Geothermal Data Repository (GDR) and its role in the NGDS. This includes the benefits of using the GDR to share geothermal data of all types and DOE’s data submission process. Authors of this paper are Jon Weers, National Renewable Energy Laboratory and Arlene Anderson, US DOE Geothermal Technologies Office. Finally, “Developing the NGDS Adoption of CKAN for Domestic & International Data Deployment,” provides an overview of the “Node-In-A-Box” software package designed to provide data consumers with a highly functional interface to access the system, and to ease the burden on data providers who wish to publish data in the system. It is important to note that this software package constitutes a reference implementation and that the NGDS architecture is based on open standards, which means other server software can make resources available, and other client applications can utilize NGDS data. Authors of this paper are Ryan Clark, Arizona Geological Survey (AZGS), Christoph Kuhmuench, Siemens Corporate Research, and Stephen Richard, AZGS.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

COMSOL Multiphysics Model for HLW Canister Filling

The U.S. Department of Energy (DOE) is building a Tank Waste Treatment and Immobilization Plant (WTP) at the Hanford Site in Washington to remediate 55 million gallons of radioactive waste that is being temporarily stored in 177 underground tanks. Efforts are being made to increase the loading of Hanford tank wastes in glass while meeting melter lifetime expectancies and process, regulatory, and product quality requirements. Wastes containing high concentrations of Al 2 O 3 and Na 2 O can contribute to nepheline (generally NaAlSiO 4 ) crystallization, which can sharply reduce the chemical durability of high level waste (HLW) glass. Nepheline crystallization can occur during slow cooling of the glass within the stainless steel canister. The purpose of this work was to develop a model that can be used to predict temperatures of the glass in a WTP HLW canister during filling and cooling. The intent of the model is to support scoping work in the laboratory. It is not intended to provide precise predictions of temperature profiles, but rather to provide a simplified representation of glass cooling profiles within a full scale, WTP HLW canister under various glass pouring rates. These data will be used to support laboratory studies for an improved understanding of the mechanisms of nepheline crystallization. The model was created using COMSOL Multiphysics, a commercially available software. The model results were compared to available experimental data, TRR-PLT-080, and were found to yield sufficient results for the scoping nature of the study. The simulated temperatures were within 60 ºC for the centerline, 0.0762m (3 inch) from centerline, and 0.2286m (9 inch) from centerline thermocouples once the thermocouples were covered with glass. The temperature difference between the experimental and simulated values reduced to 40 ºC, 4 hours after the thermocouple was covered, and down to 20 ºC, 6 hours after the thermocouple was covered. This level of precision is considered acceptable for the scoping nature of the model and the subsequent laboratory glass studies Using the model, two additional glass pouring cycles were conducted. Representative thermocouple data were plotted to show the variations between the two cycles. This provides preliminary data that will be used in laboratory experiments to determine the potential for controlling nepheline crystallization in glass by varying the glass pouring conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Gridtrust: Electricity Grid Root-of-Trust Decentralized Supply Chain Cyber-Security (Final Scientific/Technical Report)

GridTrust represents a departure from reliance on a single organization or a single person to multiple organizations and therefore multiple people across organizational structures. The motivating idea behind involving multiple organizations is the increase in security due to human factors. More specifically, the requirement that distinct people in different organizations sign off on a change or an update makes a cyberattack much less likely due to the inherent requirement that both organizations be penetrated and fooled. GridTrust focuses on the software update process as the primary exemplar for the research and development work. A novel hardware-based technology referred to as a Physical Unclonable Function (PUF) provides a microchip Root-of-Trust (RoT), i.e., a starting point for verifying that the hardware being communicated with is the hardware the control center believes the hardware to be. As a result, staff at power grid control centers can ensure the accurate and reliable identification of hardware devices from the outset. The GridTrust protocol introduces two key innovations, as detailed in this report. Firstly, the utilization of a PUF as a root-of-trust in the initial phase of a software or firmware update. Secondly, the application of multiple cryptographic signatures from two or more organizations to the update binary. These signatures are verified before implementing the update on a power grid device in the field. In terms of GridTrust hardware design, this report outlines two main components. The first is the GridTrust Native Device, integrating PUF technology intrinsically into the hardware device itself. The second is the GridTrust Interfacing Device, which incorporates PUF technology and multiple cryptographic signatures. These signatures are cross-checked within a separate hardware positioned between the power grid control center and the legacy power grid device, functioning as an intermediary. While the GridTrust Interfacing Device offers the advantage of being applicable to existing power grid equipment, it may have reduced security if the intermediary component is targeted. On the other hand, the GridTrust Native Device boasts increased security due to protocol integration within a unified form factor. The effectiveness of GridTrust technology has been extensively demonstrated, with multiple external red-team attackers unable to breach GridTrust's security measures. This was observed both in controlled laboratory settings during Phase 1 of the project and in real-world conditions within a City of Marietta substation during Phase 2 of the project.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Mid Infra-Red Laser Sensor for Continuous Sulfur Trioxide Monitoring to Improve Coal-Fired Power Plant Performance during Flexible Operations

During the course of this project, we performed exhaustive research and development of SO3/H2SO4 sensing technology for coal-fired power plant applications (Figure 1). The development culminated in a successful field campaign of a prototype continuous real-time H2SO4 monitor at a coal-fired power plant (TRL 6) accomplishing the primary goal of the project. The developed sensors utilize tunable laser absorption spectroscopy (TLAS) operating in the mid-infrared (Mid-IR) wavelength region, which is the so-called “molecular fingerprint” region. Systems operating in the Mid-IR have orders of magnitude more sensitivity than systems operating at shorter wavelengths, such as near-infrared (NIR). However, NIR systems are more widespread due to more mature supporting technology (e.g., fiber optics, optical components, etc.). In this project, we not only produced a specific Mid-IR sensor, we also advanced Mid-IR sensor technology in general through the development and demonstration of such supporting technology. In this project, we also developed proprietary broad tuning lasers enabling the ability to effectively measure SO3, H2SO4, H2O, and SO2. Different molecular species have unique spectral signatures that can be probed with lasers operating at different wavelengths. Standard TLAS uses relatively narrow wavelength tuning distributed feedback (DFB) lasers, which can typically only target a single species with narrow features, and are not appropriate for species with broad features, such as SO3 or H2SO4. In contrast, by developing unique, broad-tuning laser technology, we were able to measure these species, as well as SO2 and H2O simultaneously. Furthermore, to enable real-time analysis at a power plant, we modified a commercially available heated gas cell to operate in the Mid-IR wavelength range and fiber coupled the lasers to enable remote delivery of the beams. To generate reference data (library spectra), our collaborators at the University of California Irvine (UCI) developed a catalytic SO3 generation facility. It is worth mentioning that representative H2SO4 and SO3 Mid-IR spectra are not a part of any publicly available database and the data generated under this project is a valuable resource in and of itself. In addition, based on the UCI study we determined that detection of SO3 is complicated by the very strong SO2 absorption. For that reason, we concentrated on H2SO4 detection. Since SO3 and H2SO4 exist in a flue gas in a state of equilibrium, which depends on temperature and humidity, by measuring water concentration and controlling the temperature of the gas cell, we developed an approach to determine SO3 concentration from the H2SO4 measurement. During the development phase of the project, we performed three testing campaigns at our collaborator’s FERCo flue gas facility with conditions representative of the coal-fired power plant (~ 40ppm SO3, 1700ppm to 2800 ppm SO2, 10% water) with the exception of particulate matter. After three test campaigns at FERCo we performed field testing at Harrison Power Station. The final system was mounted on a duct and measured H2SO4, SO2 and water. The tests were highly successful with a demonstrated real-time H2SO4 precision of 1 ppm with a 1 second update. Our collaborators at EPRI conducted an industry survey and determined that there is a very high interest for the SO3/H2SO4 monitoring in the power generation industry as well as in heavy industries in general. Furthermore, work performed by OptoKnowledge beyond the scope of this project under a synergistic DOE SBIR determined another approach to SO3 detection. We applied for Phase II on this SBIR for development a of versatile SO3/H2SO4 sensor but were not selected. We are currently looking for another opportunity to leverage all the technological advancements produced by this project including but not limited to the flue gas facility at UCI, the hardware and software developed, and relationships with FERCo, EPRI CEMTEK, and Harrison Station.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

A machine learning approach to galaxy properties: joint redshift–stellar mass probability distributions with Random Forest

We demonstrate that highly accurate joint redshift–stellar mass probability distribution functions (PDFs) can be obtained using the Random Forest (RF) machine learning (ML) algorithm, even with few photometric bands available. As an example, we use the Dark Energy Survey (DES), combined with the COSMOS2015 catalogue for redshifts and stellar masses. We build two ML models: one containing deep photometry in the griz bands, and the second reflecting the photometric scatter present in the main DES survey, with carefully constructed representative training data in each case. We validate our joint PDFs for 10 699 test galaxies by utilizing the copula probability integral transform and the Kendall distribution function, and their univariate counterparts to validate the marginals. Benchmarked against a basic set-up of the template-fitting code bagpipes, our ML-based method outperforms template fitting on all of our predefined performance metrics. In addition to accuracy, the RF is extremely fast, able to compute joint PDFs for a million galaxies in just under 6 min with consumer computer hardware. Such speed enables PDFs to be derived in real time within analysis codes, solving potential storage issues. As part of this work we have developed galpro 1, a highly intuitive and efficient python package to rapidly generate multivariate PDFs on-the-fly. galpro is documented and available for researchers to use in their cosmology and galaxy evolution studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Test and Validate Distributed Coaxial Cable Sensors for in situ Condition Monitoring of Coal-Fired Boiler Tubes

This project aims to test, validate, and advance the technology readiness level (from TRL5 to TRL7) of a novel low-cost distributed stainless-steel/ceramic coaxial cable sensing (SSC-CCS) technology for in situ monitoring of the boiler tube temperature in existing coal-fired power plants. The novel SSC-CCS sensing technology and associated condition-based monitoring (CBM) software to be demonstrated in this project will lead to an improved understanding of the boiler tube failure mechanisms and a prognostic system to improve the overall performance, reliability, and flexibility of the nation’s coal-fired power plant fleet. A boiler tube monitoring system with distributed coaxial cable temperature sensors and a sensor acquisition system was constructed. The high-temperature coaxial cable sensor with a length of 1.3m was made by using a quartz tube (1mm inner diameter (ID) and 6mm outer diameter (OD)) to concentrically separate a 304 stainless-steel (SS) rod (1mm OD) and SS tube (7.94mm OD and 6.16mm ID). The sensor acquisition system includes a vector network analyzer (VNA), a radio frequency (RF) power amplifier, multiple switches and a USB hub. The distributed stainless-steel quartz coaxial cable sensor (SSQ-CCS) had a linear response to temperature with a resolution uncertainty of σ = 0.77℃. To withstand the harsh conditions of 3,300 steam pressures and 800℃ high temperatures, the sensor was shielded by a protective tube made of the same material as the boiler tube. The protection tube had an OD of 1.5 inches and a thickness of 0.25 inches. In the laboratory tests, the sensor showed good sensitivity and fast response. The drift was bounded between +0.33% and -0.67% during a test at 600℃ for 350 hours, indicating good stability of the sensor. A field test was conducted where four sensors were welded on four superheat tubes (SH-Ts) at a coal-fired power station over 400 days. Conventional thermocouples were welded to the superheater tubes alongside the coaxial cable sensors for the purpose of comparison. Two sensors were capable of distributed sensing, with three multiplexed sensing sections. The other two sensors were single section. During the 400-day test period, the power plant experienced startups and shutdowns. At the steady state operations, the temperature of the boiler tube is about 600℃ (1112°F). The sensors recorded the entire coal-firing processes (start-up, steady state, and shut-down) and the glitch event. A GSM modem and a Watchdog were added to the system to ensure reliable data recording. The GSM modem sent daily messages to plant managers and Clemson team to inform the status of the sensor system. If the system was not normally working, the Watchdog would reboot the system automatically. The new coaxial cable based distributed sensing technology has been proven to be successful in both laboratory and field tests. A comprehensive four-stage multi-physics computational framework has been developed to assist the design, optimization, installation, and operation of SSQ-CCS. With the consideration of various operation conditions, we predict the distributions of flue gas temperatures within coal-fired boilers, the temperature correlation between the boiler tube and SSQ-CCS, and the safety of SSQ-CCS. A conditional-based monitoring system is implemented as well. The computational framework developed in this work can guide the future operation of coal-fired plants and other power plants for the safety prediction of boiler operations.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2019

Path Forward for Groundwater Compliance Strategy at the Tuba City, Arizona, Disposal Site - 19581

The Tuba City, Arizona, Disposal Site is located in the Navajo Nation and near the Hopi Reservation. A uranium mill operated at the site from 1956 to 1966. During the operational period, mill tailings were slurried to an unlined impoundment. Excess slurry water was transferred to unlined evaporation ponds. Groundwater contamination resulting from the infiltration of fluids in the mill tailings impoundment and evaporation ponds was characterized in the 1990's. The site's Groundwater Compliance Action Plan was prepared in 1999, and a groundwater extraction and treatment system was constructed in 2002. Issues with aquifer productivity and treatment plant reliability led to the suspension of operations in 2014. The limitations of the remediation system prompted a realization that the site conceptual model should be reevaluated. An integrated study to better understand the geochemical and hydrologic factors affecting contaminant transport, to support the development of a new groundwater compliance strategy, was initiated in 2017 and is ongoing. In addition to the groundwater science components, the study included the evaluation of enhanced evaporation methods. The integrated evaluation will lead to refinement of the site groundwater flow model and development of a contaminant transport model and subsequent development of remedial alternatives. Remedial alternatives will be evaluated to determine a new groundwater compliance strategy. The objectives of geochemical testing were to confirm and quantify geochemical reactions controlling uranium fate and transport. These reactions are important because they control the distribution of uranium on the solid phase; potential for release from the solid phase; mobility of uranium in the water phase; and potential for uranium redistribution onto the currently uncontaminated solid phase. A key outcome is the change in understanding of the mass of uranium in the subsurface that is potentially soluble. These results contradict the previous basis for remediation: that uranium was almost exclusively present in soluble form, within the boundaries of the contaminant plume. Testing showed that uranium sorption downgradient from the plume was measurable but relatively minimal. The movement of other mill-related constituents (nitrate, sulfate, alkalinity) results in the dissolution of naturally occurring uranium and a higher than background concentration of uranium in groundwater. These constituents are not subject to sorption, and their downgradient concentrations are reduced only by diffusion and dispersion. The geochemical testing provides conceptual and quantitative information on potential plume migration. While the testing revealed the potential availability of uranium contaminant sources, the aquifer buffering capacity, pH, and presence of oxygen in groundwater may, individually or in combination, be controlling factors for plume movement. Evaluation of evaporative treatment alternatives was undertaken to determine one or more sustainable and efficient methods capable of treating 151 liters per minute (L/min) (40 gallons per minute), the annual average flow rate. In addition to establishing the baseline capacity for evaporation using the site's existing pond, prospective methods of enhanced evaporation included preheating water before inflow to the evaporation pond, vertical circulation in the pond, dye addition, and Wind-Aided Intensified Evaporation. Consideration of a 151 L/min evaporative treatment arose from previous analysis of extraction well production rates and contaminant mass removal, which indicated that about 80% contaminant removal, relative to full-scale operation of the site's groundwater treatment plant, could be achieved with a smaller capacity system. The lower-flow evaporative option also represented a potentially more sustainable treatment system in comparison to restarting or reconfiguring the groundwater treatment plant. Aquifer pumping tests were designed to develop or improve estimates of hydraulic properties such as transmissivity, horizontal and vertical hydraulic conductivity, storativity, and storage coefficient. Testing involved pumping from one well at a constant flow rate for up to 5 days while monitoring groundwater drawdown in the pumping well and five surrounding wells and then shutting down the pumping well to observe groundwater recovery. The aquifer pumping test results provide insight regarding the hydraulics of the saturated zone. The saturated zone is in a low-conductivity formation with preferential flow in the horizontal direction. The aquifer exhibits low vertical conductance. The use of AQTESOLV software indicates that the saturated zone is a layered system due to the cross-bedded sand-grain orientation within the Navajo Sandstone. These indicators of limited vertical flow provide a potential justification for the observed depth of the contaminant plume of 15-46 meters (50-150 feet) below ground surface). Given the relatively low vertical conductance, groundwater extraction should be focused on the upper portions of the saturated zone. Aquifer response testing provided an improved understanding of aquifer characteristics. However, the primary objective, to identify optimal groundwater extraction strategies, has not been fully addressed. A list of path forward activities for hydrologic analyses was developed, with an overarching objective of providing input parameters for groundwater flow and contaminant transport modeling. Defensible predictions of contaminant transport, through modeling, are critical to the development of a new site groundwater compliance strategy. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

SU-E-T-557: Monte Carlo Modeling of Philips RT-250 Orthovoltage Unit for Beam Spectrum Modulation

Purpose: To develop and validate a Monte Carlo (MC) model of a Phillips RT-250 orthovoltage unit to test various beam spectrum modulation strategies for in vitro/vivo studies. A model of this type would enable the production of unconventional beams from a typical orthovoltage unit for novel therapeutic applications such as gold nanoparticle-aided radiotherapy. Methods: The MCNP5 code system was used to create a MC model of the head of RT-250 and a 30 × 30 × 30 cm{sup 3} water phantom. For the x-ray machine head, the current model includes the vacuum region, beryllium window, collimators, inherent filters and exterior steel housing. For increased computational efficiency, the primary x-ray spectrum from the target was calculated from a well-validated analytical software package. Calculated percentage-depth-dose (PDD) values and photon spectra were validated against experimental data from film and Compton-scatter spectrum measurements. Results: The model was validated for three common settings of the machine namely, 250 kVp (0.25 mm Cu), 125 kVp (2 mm Al), and 75 kVp (2 mm Al). The MC results for the PDD curves were compared with film measurements and showed good agreement for all depths with a maximum difference of 4 % around dmax and under 2.5 % for all other depths. The primary photon spectra were also measured and compared with the MC results showing reasonable agreement between the two, validating the input spectra and the final spectra as predicted by the current MC model. Conclusion: The current MC model accurately predicted the dosimetric and spectral characteristics of each beam from the RT-250 orthovoltage unit, demonstrating its applicability and reliability for beam spectrum modulation tasks. It accomplished this without the need to model the bremsstrahlung xray production from the target, while significantly improved on computational efficiency by at least two orders of magnitude. Supported by DOD/PCRP grant W81XWH-12-1-0198.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A geospatial risk analysis graphical user interface for identifying hazardous chemical emission sources

Background: Performing back trajectory and forward trajectory using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) is a reliable approach for assessing particle transport after release among mid-field atmospheric models. HYSPLIT has an externally facing online interface that allows non-expert users to run the model trajectories without requiring extensive training or programming. However, the existing HYSPLIT interface is limited if simulations have a large amount of meteorological data and timesteps that are not coincident. The objective of this study is to design and develop a more robust tool to rapidly evaluate hazard transport conditions and to perform risk analysis, while still maintaining an intuitive and user-friendly interface. Methods: HYSPLIT calculates forward and backward trajectories of particles based on wind speed, wind direction, and the corresponding location, timestamp, and Pasquill stability classes of the regions of the atmosphere in terms of the wind speed, the amount of solar radiation, and the fractional cloud cover. The computed particle transport trajectories, combined with the online Proton Transfer Reaction-Mass Spectrometry (PTR-MS) data (https://figshare.com/articles/dataset/ARL_Data_from_PROS_station_at_Hanford_site/19993964), can be used to identify and quantify the sources and affected area of the hazardous chemicals’ emission using the potential source distribution function (PSDF). PSDF is an improved statistical function based on the well-known potential source contribution function (PSCF) in establishing the air pollutant source and receptor relationship. Performing this analysis requires a range of meteorological and pollutant concentration measurements to be statistically meaningful. The existing HYSPLIT graphical user interface (GUI) does not easily permit computations of trajectories of a dataset of meteorological data in high temporal frequency. To improve the performance of HYSPLIT computations from a large dataset and enhance risk analysis of the accidental release of material at risk, a geospatial risk analysis tool (GRAT-GUI) is created to allow large data sets to be processed instantaneously and to provide ease of visualization. Results: The GRAT-GUI is a native desktop-based application and can be run in any Windows 10 system without any internet access requirements, thus providing a secure way to process large meteorological datasets even on a standalone computer. GRAT-GUI has features to import, integrate, and convert meteorological data with various formats for hazardous chemical emission source identification and risk analysis as a self-explanatory user interface. The tool is available at https://figshare.com/articles/software/GRAT/19426742.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Cybersecurity Platform and Certification Framework Development for Extreme Fast Charging (XFC)-Integrated Charging Ecosystem (Final Project Report)

This report summarizes a pioneering effort in Electric Vehicle charging infrastructure ecosystem cybersecurity requirements, assessment methodologies, functional verification, as well as embodiment of the key technologies in the form of hardware and software tools being made available to the public. EPRI led a team of experts, as well as a stakeholder coalition encompassing all key actors in the EV charging infrastructure ecosystem that includes eXtreme Fast Charging (XFC) equipment (defined as 200kW or above). EV charging infrastructure in the United States is a patchwork of networks that have continued to grow organically and have been designed to serve the charging needs of the EV owners, who are their customers. In doing so, each network provider, as well as their connected entities such as the cloud Electric Vehicle Service Providers or EVSPs, utility back office, utility AMI networks, payment networks, as well as Original Equipment Manufacturer (EV manufacturer) telematics networks, have designed systems that may work well individually, but no single entity is responsible for the entire ecosystem to be secure in terms of data exchange. Furthermore, there is no uniformity in how each actor has implemented the cybersecurity requirements since no system-wide cybersecurity requirements existed prior to this project. The final project report describes the technical approach guided by the EV charging infrastructure cybersecurity working group, convened specifically for this project. The technical approach included definition of requirements at the ecosystem level, treated as a ‘system of systems’, and then passed down to individual systems (EVSE, EV, cloud EVSP, utility, and the payment networks), followed by developing the cybersecurity risk and vulnerability assessment methods, that were later applied to real-world cyber-physical systems at EPRI, ANL, and NREL laboratories, to validate both the process and the results. Finally, in a spotlight over the most vulnerable equipment, which is the EV charge station (AC or DC), the team developed a multi-layer cybersecurity implementation in the embedded domain embodied by the open-source Secure Network Interface Card (SNIC) demonstrating the various ways in which the infrastructure can be secured protecting against the identified attack surfaces. Finally, the entire process of EV infrastructure cybersecurity assessment was encapsulated in the Electric Vehicle Charging Cybersecurity Management (EVC2M) online GUI-based tool, that is expected to be released to the public. The report presents the objectives, the technical approach, the key results, and recommendations for future work.

24 POWER TRANSMISSION AND DISTRIBUTION↗