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DOE OSTI2022

Leveraging Multiple Raman Excitation Wavelength Systems for Process Monitoring of Nuclear Waste Streams

Processing nuclear waste from sites such as Hanford is a significant environmental cleanup need while being a significant logistical challenge. Integration of process monitoring tools, that can provide in situ and real-time feedback about the process, can significantly alleviate needs to collect grab samples for process control and product characterization. Raman spectroscopy paired with chemometric analysis is one process monitoring tool that can provide chemical composition information on a large number of chemical targets in nuclear waste streams. However, methods to improve limits of detection as well as drop uncertainty in quantification are needed. Optimizing instrument specifications can achieve this, here this is demonstrated by comparing limits of detection for key analytes when using Raman systems with 671 nm, 532 nm, and 405 nm excitation wavelengths. Generally, limits of detection decease (allowing the measurement of lower salt concentrations) with decreasing wavelength. Similarly, data collection times and averaging were optimized. Finally, multiple chemometric modeling approaches were leveraged, including multiblock methods that combined data from all three Raman systems to simultaneously quantify targets with improved sensitivity.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Knowledge Beacons: Web services for data harvesting of distributed biomedical knowledge

The continually expanding distributed global compendium of biomedical knowledge is diffuse, heterogeneous and huge, posing a serious challenge for biomedical researchers in knowledge harvesting: accessing, compiling, integrating and interpreting data, information and knowledge. In order to accelerate research towards effective medical treatments and optimizing health, it is critical that efficient and automated tools for identifying key research concepts and their experimentally discovered interrelationships are developed. As an activity within the feasibility phase of a project called “Translator” (https://ncats.nih.gov/translator) funded by the National Center for Advancing Translational Sciences (NCATS) to develop a biomedical science knowledge management platform, we designed a Representational State Transfer (REST) web services Application Programming Interface (API) specification, which we call a Knowledge Beacon. Knowledge Beacons provide a standardized basic API for the discovery of concepts, their relationships and associated supporting evidence from distributed online repositories of biomedical knowledge. This specification also enforces the annotation of knowledge concepts and statements to the NCATS endorsed the Biolink Model data model and semantic encoding standards (https://biolink.github.io/biolink-model/). Implementation of this API on top of diverse knowledge sources potentially enables their uniform integration behind client software which will facilitate research access and integration of biomedical knowledge.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2020

Top Loading Helium Cryostat Integrated with High-Pressure Cell with Fast Remote Pressure Control (Final Report for SBIR Phase 1)

A large number of physical phenomena, such as superconductivity and quantum critical phenomena, often appear only at very low temperatures below 5 K. There is an immense interest to investigate these phenomena at high pressure as a means of tuning interatomic distances, and thus the interaction parameters controlling these phenomena, in a continuous and controlled fashion. The current P-T condition for neutron scattering experiments are limited to either relatively low pressures of about 2 GPa at temperatures below 5 K, or to relatively high temperatures at pressures or tens of GPa. The purpose of this research is to develop neutron sample environment instrumentation for reaching 10-20 GPa at 1-2K with rapid and reliable online pressure and temperature control (i.e. without having to interrupt the experiment). The ultimate goal of the project is to design an integrated fast-cooling low-temperature sample environment cryogenic system compatible with state of the art neutron diamond anvil cells suitable for single-crystal neutron scattering experiments for temperatures down to 2K and pressures of several tens of GPa. The integrated system will consist of top-loading Helium flow cryostat with in-situ sample alignment mechanisms, large-volume diamond anvil cells (DAC) made from novel superalloy Pascalloy and optimized for fast cooling and heating, and a compact remote pressure control mechanism for the DAC based on a novel concept of inflatable bellows integrated with a lever-arm based force amplifier. In Phase I, we have designed, manufactured, and tested prototypes of the novel compact force-amplified pneumatic pressure control mechanism for Neutron Diamond Anvil Cell (nDAC), which allows to use pneumatic bellows system for smooth remote pressure control in the nDAC inside a top-loading cryostat with bore size of 70 mm or larger. This allows significant minimum temperature decrease in remotely controlled nDAC from 5-10 K down to 2 K. We also studied mechanical properties of a novel non-magnetic superalloy Pascalloy with different heat-treatment conditions and preliminary results indicate that up to date this is probably the strongest and most suitable material for making more compact and lightweight cryogenic nDACs for neuron scattering experiments at extreme conditions, allowing much faster cooling and heating. Potential applications: The new developments will allow to create a wide range of compact Diamond Anvil Cells for neutron diffraction which can reach several tens of GPA pressure at 2-4 K while preserving accurate remote pressure control capabilities. The new concepts can be used for developing sample environment instrumentation outside the neutron scattering field. The new development have very strong potential for expanding experimental capabilities in materials sciences and have high commercialization potential. The proposed new cryogenic high-pressure system or any of its individual components will be in high demand not only in neutron scattering facilities, but also at synchrotron beamlines and other high-pressure research facilities around the world.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Advanced Reactor Control and Operations (ARCO): A University Research Facility for Developing Optimized Digital Control Rooms

The Advanced Reactor Control and Operations (ARCO) facility was constructed in January 2018 to serve as a test bed for advanced reactor control rooms and operator support systems. Since then, it has supported human-machine interface user experience research, fault detection and mitigation technology development, control room concept of operations development, and remote operations research. ARCO serves as the control room for the Compact Integral Effects Test (CIET) facility, which replicates the primary-side flow paths and thermal-hydraulic behavior of a fluoride-salt-cooled high-temperature reactor (FHR) using simulant fluids and scaling principles. New reactor designs feature different operating conditions and scenarios than those in existing reactors. ARCO supports the research and development of digital tools for operator communications, intuitive real-time data analysis, online health monitoring and prognostics, and control room cybersecurity. By integrating these different technologies, ARCO acts as a prototypical control system to iteratively develop methods and tools of operation in advanced small modular nuclear reactors. This paper describes the features of and challenges to operating advanced small modular reactors underlying the design basis for ARCO and its operator support systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRSDate not supplied

Considering Cell Proliferation to Optimize Detection of Radiation-induced 53BP1+ Foci in 15 Mouse Strains ex vivo

Due to high metabolic activity, proliferating cells continuously generate free radicals, which induce DNA double strand breaks (DSB). Fluorescently tagged nuclear foci of DNA repair protein 53 binding protein-1(53BP1) are used as a standard metric for measuring DSB formation at baseline and in response to environmental insults such as radiation. Here we demonstrate that the background level of spontaneous 53BP1+ foci formation can be modeled mathematically as a function of cell confluence, which is a metric of proliferation rate. This model was validated using spontaneous 53BP1+ foci data from 68 cultures of primary skin fibroblasts derived from 15 different strains of mice, showing a ~10 fold decrease from low to full confluence that is independent of mouse strain. We developed an online open access tool to correct for the impact of cell confluence on the detection of radiation-induced 53BP1+ foci (RIF). This tool provides guidelines for the number of cells required to reach statistical significance for the detection of excess foci induced by low doses of ionizing radiation as a function of confluence and time post-irradiation. We hope that this quantification tool will help the radiation biology community in the design of future experiments that utilize 53BP1+ foci-based quantification of radiation responses in vitro. Our “tool for enhanced results of RIF in cells” (terRIFic) can be found at: https://radbiolab.shinyapps.io/terrific/

Radiation, DNA damage, confluence↗

DOE OSTI2022

Scientific Computational Imaging Code (SCICO)

Scientific Computational Imaging Code (SCICO) is a Python package for solving the inverse problems that arise in scientific imaging applications. Its primary focus is providing methods for solving ill-posed inverse problems by using an appropriate prior model of the reconstruction space. SCICO includes a growing suite of operators, cost functionals, regularizers, and optimization routines that may be combined to solve a wide range of problems, and is designed so that it is easy to add new building blocks. SCICO is built on top of JAX rather than NumPy, enabling GPU/TPU acceleration, just-in-time compilation, and automatic gradient functionality, which is used to automatically compute the adjoints of linear operators. An example of how to solve a multi-channel tomography problem with SCICO is shown in Figure 1. The SCICO source code is available from GitHub, and pre-built packages are available from PyPI. It has extensive online documentation, including API documentation and usage examples, which can be run online at Google Colab and binder.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Photovoltaic and Behind-the-Meter Battery Storage: Advanced Smart Inverter Controls and Field Demonstration

Electric utilities have little visibility of the electrical distribution system, and consequently, limited diagnostic capabilities. The distribution grid was designed for a unidirectional power flow, where energy is supplied by few large centralized power plants; however, this is set to change to meet California’s aggressive decarbonization goals. The large-scale deployment of distributed renewable generation, such as photovoltaics (PV), can have many negative effects on an unprepared grid. As illustrated in the California “duck curve,” PV generation modifies load profiles during the day, which causes steep ramping in the evening. This effect indicates the need to revise the electrical grid’s design and operation. This project sought to (a) create a centralized resource in California to test and validate distribution technology controls with industry standard PV, storage, and high-fidelity sensors, (b) support strategic and operational decisions for new grid architectures by providing simulation models, (c) promote new ways to control clusters of PV smart inverters, in accordance with California Rule 21, and (d) innovate, develop, and field test a predictive controller to maximize economic profit for the customer while supporting the grid. The controller was built using the state-of-the-art model predictive control methodology to optimally control behind-the-meter PV and battery storage. In consideration of the duck curve, the controller optimally controls the battery dispatch by charging during excess generation periods and discharging during the critical afternoon demand hours. The controller was evaluated in annual simulations and revealed the potential cost-effectiveness of behind-the-meter battery storage. The simulations showed that the annual electricity bill could be reduced by as much as 35 percent, with a payback period of the investment in battery storage in about 6 years – significantly shorter than the manufacturer’s 10-year warranty. All developed simulation models, the grid event library, and the MPC controller are open-source and available online.

Model Predictive control↗

DOE OSTI2026

Design of a Molten Salt Flow Cell for Combined Absorbance and Laser-Induced Breakdown Spectroscopy for Online Measurements

A novel flow cell allowing for multiple optical spectroscopy measurements on flowing molten salts was designed, and demonstrative calibrations of impurities in aqueous samples were performed. Online compositional measurements of molten salts are of high interest to monitor the state of relevant solar and nuclear systems. Here, the Spectroscopic Configuration for Optical Real-Time Characterization of High-Temperature (SCORCH) fluids cell was designed to meet this need by providing optical access to a high-temperature molten salt sample stream without physical contact between the sample and window materials. Laser-induced breakdown spectroscopy (LIBS) was utilized to quantify Li, Cr, Fe, Ni, Sr, and Pr at concentrations ranging nominally from 0 to 315 mmol L −1 . Laser power, frequency, and plasma position were optimized to mitigate challenges associated with sample splashing. Univariate calibration models were built with R 2 > 0.98, percent root mean square error of cross-validation (%RMSECV) as low as 2.7%, and limits of quantification (LOQs) down to 4.1 mmol L −1 . Simultaneously, absorbance calibrations were developed for the applicable analytes (Cr, Ni, and Pr) using Beer’s law with a pathlength of 4.41 ± 0.10 mm. These models provide excellent quantification performance with R 2 > 0.999, %RMSECV as low as 0.6%, and LODs down to 0.08 mmol L −1 . Although these calibrations were performed for each spectroscopic technique separately, the two methods may be combined in the future through multivariate modeling and sensor fusion to provide more robust models with the benefits of both techniques (e.g., absorbance: oxidation state concentrations, LIBS: elemental concentration). Additionally, optimized spectrometers may be deployed to enhance sensitivity.

absorbance spectroscopy↗

DOE OSTI2021

Interactive Web Application for Traffic Simulation Data Management and Visualization

As traffic simulation software becomes more effective for realistically simulating and analyzing traffic dynamics and vehicle interactions on the mesoscopic and microscopic level, the management, dissemination, and collaborative visualization of traffic simulation results produced by individual transportation planners presents a significant challenge. Existing online content management systems have a very limited capability in allowing users to query specific traffic simulation scenarios and geospatially visualize simulation results through shareable and interactive web interfaces. This paper presents a web-based application for promoting the archiving, sharing, and visualization of large-scale traffic simulation outputs. The application is developed to enhance cyber-physical controls, communications, and public education for collaborative transportation planning. Unique features of the web application include: (a) allowing users to upload their new traffic simulation scenarios (parameters and outputs), as well as search existing scenarios using easily accessible interfaces; (b) optimizing simulation output files with heterogeneous data formats and projected coordinate systems for web-based storage and management using a scalable and searchable data/metadata standard; (c) standardizing user-uploaded simulation outputs using web interfaces and data processing libraries with parallel computing capacity; and (d) providing shareable web visual interfaces for visualizing the traffic flow and signal information stored in simulation outputs (e.g., regional traffic patterns and individual vehicle interactions) and visually comparing multiple simulation outputs both spatially and temporally. Furthermore, the paper presents the conceptual design and implementation of this application, and demonstrates the application’s performance for sharing, comparing, and visualizing simulation outputs from VISSIM and SUMO, two commonly used traffic simulation software programs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2024

Development of algorithms for augmenting and replacing conventional process control using reinforcement learning

Here, this work seeks to allow for the online operation and training of model-free reinforcement learning (RL) agents but limit the risk to system equipment and personnel. The parallel implementation of RL alongside more conventional process control (CPC) allows for the RL algorithm to learn from CPC. The past performance of both methods are assessed on a continuous basis allowing for a transition from CPC to RL and, if needed, transitioning back to CPC from RL. This allows for the RL algorithm to slowly and safely assume control of the process without significant degradation in control performance. It is shown that the RL can derive a near optimal policy even when coupled with a suboptimal CPC. It is also demonstrated that the coupled RL-CPC algorithm learns at a faster rate than traditional RL methods of exploration while the algorithm’s performance does not deteriorate below CPC, even when exposed to an unknown operating condition.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2021

Simulation of Isotopic Concentrations and Gamma Spectra from Dynamic Fission Sources

A tool was developed to rapidly generate synthetic gamma-ray spectra to evaluate safeguards material control and accounting methods for liquid-fueled molten salt reactors. Molten salt reactor operations pose unique challenges to nuclear safeguards methods and protocols compared to deployed reactors designs (e.g., light water reactors). This research evaluates the use of gamma-ray spectroscopy to monitor fission product isotopic flow through a reactor model to understand expected operations and investigate changes to the spectra with material diversion scenarios. The large design space of molten salt reactors (e.g., liquid-fueled, liquid-cooled, online separations) could potentially lead to many measurement points within the reactor system. The developed analytical tool generates and evaluates synthetic gamma-ray spectra from dynamic reactor simulations by extracting isotopic inventory to generate source terms. An implementation in the Gamma Detector Response and Analysis Software (GADRAS) Application Program Interface (API) uses the source terms, a model of the reactor component, a detector response function, and measurement plan to quickly generate and analyze spectra. Prospective measurements are then evaluated in the more accurate but slower Geant4 simulations. Utilization of the developed modeling tool and analysis of the subsequent spectra enables optimization of collimation, shielding requirements, and expected count rates that are used to determine key measurement points in the modeled reactor design.

O'Brien, Sean↗

DOE OSTI2024

Deep Learning Image Segmentation for Atmospheric Rivers

Abstract The identification of atmospheric rivers (ARs) is crucial for weather and climate predictions as they are often associated with severe storm systems and extreme precipitation, which can cause large impacts on society. This study presents a deep learning model, termed ARDetect, for image segmentation of ARs using ERA5 data from 1960 to 2020 with labels obtained from the TempestExtremes tracking algorithm. ARDetect is a convolutional neural network (CNN)-based U-Net model, with its structure having been optimized using automatic hyperparameter tuning. Inputs to ARDetect were selected to be the integrated water vapor transport (IVT) and total column water (TCW) fields, as well as the AR mask from TempestExtremes from the previous time step to the one being considered. ARDetect achieved a mean intersection-over-union (mIoU) rate of 89.04% for ARs, indicating its high accuracy in identifying these weather patterns and a superior performance than most deep learning–based models for AR detection. In addition, ARDetect can be executed faster than the TempestExtremes method (seconds vs minutes) for the same period. This provides a significant benefit for online AR detection, especially for high-resolution global models. An ensemble of 10 models, each trained on the same dataset but having different starting weights, was used to further improve on the performance produced by ARDetect, thus demonstrating the importance of model diversity in improving performance. ARDetect provides an effective and fast deep learning–based model for researchers and weather forecasters to better detect and understand ARs, which have significant impacts on weather-related events such as floods and droughts.

Galea, Daniel↗

DOE OSTI2015

A modified priority list-based MILP method for solving large-scale unit commitment problems

This paper studies the typical pattern of unit commitment (UC) results in terms of generator’s cost and capacity. A method is then proposed to combine a modified priority list technique with mixed integer linear programming (MILP) for UC problem. The proposed method consists of two steps. At the first step, a portion of generators are predetermined to be online or offline within a look-ahead period (e.g., a week), based on the demand curve and generator priority order. For the generators whose on/off status is predetermined, at the second step, the corresponding binary variables are removed from the UC MILP problem over the operational planning horizon (e.g., 24 hours). With a number of binary variables removed, the resulted problem can be solved much faster using the off-the-shelf MILP solvers, based on the branch-and-bound algorithm. In the modified priority list method, scale factors are designed to adjust the tradeoff between solution speed and level of optimality. It is found that the proposed method can significantly speed up the UC problem with minor compromise in optimality by selecting appropriate scale factors.

Ke, Xinda↗

DOE OSTI2026

SULI Report - Development of a Molten Salt Circulation Loop for in-situ Spectroscopy

This project supports the development of real time optical monitoring capabilities for molten salt reactor (MSR) environments by designing, testing, and refining a molten salt circulation loop suitable for combined laser induced breakdown spectroscopy (LIBS) and ultraviolet visible (UV Vis) absorption measurements. Online spectroscopic monitoring is increasingly important for nuclear safeguards, corrosion tracking, and material accountancy, yet MSR process fluids present substantial challenges due to their chemical complexity and hazards such as high temperatures and radiation. To address these needs, this work focuses on Phase I, the development of a room temperature aqueous circulation loop that serves as a surrogate platform for evaluating flow behavior, optical access, and component performance prior to high temperature salt operation. Initial testing identified several practical issues—including leaks, obstructions, and two-phase flow through the absorption cell—that were systematically resolved through hardware replacement, flow path redesign, and venturi pressure optimization. Relocating the flow cell upstream of the primary venturi enabled periods of stable single-phase flow, demonstrating the feasibility of integrating optical diagnostics into a circulation system. The results of Phase I provide essential design insight for Phase II, which will incorporate furnace compatible materials and LiCl KCl eutectic salt. Completion of the molten salt system will deliver a reusable testbed for evaluating multimodal spectroscopic techniques, advancing nondestructive, real time monitoring tools for future MSR and nuclear fuel cycle applications.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

DOE OSTI2019

Compact millimeter-wavelength Fourier-transform spectrometer

Here, we have constructed a Fourier-transform spectrometer (FTS) operating between 50 GHz and 330 GHz with minimum volume (355×260×64 mm) and weight (5.9 kg) while maximizing optical throughput (100 mm 2 sr) and optimizing the spectral resolution (4 GHz). This FTS is designed as a polarizing Martin–Puplett interferometer with unobstructed input and output in which both input polarizations undergo interference. The instrument construction is simple with mirrors milled on the box walls and one motorized stage as the single moving element. We characterize the performance of the FTS, compare the measurements to an optical simulation, and discuss features that relate to details of the FTS design. The simulation is also used to determine the tolerance of optical alignments for the required specifications. We detail the FTS mechanical design and provide the control software as well as the analysis code online.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Feasibility Study of Spectrophotometry to Support a Promethium Production Program at ORNL

Optical spectroscopy can be used to optimize analytical measurements for lanthanide elements and provide real-time feedback to help guide production operations. This study evaluates spectrophotometry for the determination of samarium (Sm 3+ ) and neodymium (Nd 3+ ) in aqueous and organic solutions at concentrations relevant to a promethium (Pm) program separation scheme. Detection limits approached 0.5 mM for Nd 3+ and 2 mM for Sm 3+ using Ocean Insight spectrophotometers. Additionally, Sm 3+ detection limits using laser fluorescence spectra for Sm 3+ approached single ppm (mg∙L -1 ) levels. An absorption spectrum containing Nd and Pm is also reported and discussed. This work demonstrates proofof-principle concepts for applying spectrophotometry to online monitoring applications in support of a future Pm production program.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Accelerating the rate of discovery: toward high-repetition-rate HED science

As high-intensity short-pulse lasers that can operate at high-repetition-rate (HRR) (>10 H z ) come online around the world, the high energy density (HED) science they enable will experience a radical paradigm shift. The >10 3 increase in shot rate over today's shot-per-hour drivers translates into dramatically faster data acquisition, more experiments, and the ability to exploit machine learning, and thus the potential to significantly accelerate the advancement of HED science. A wide range of HED experiments, from opacity investigations to secondary source generation to plasma nuclear physics, will benefit from the increased statistics, precision, and exploration of phase space. Besides increasing the rate at which scientific experiments can be performed, HRR also allows for the rapid delivery of optimal experiments supported by simulations and modeling augmented by close coupling to empirical data. To fully realize such an HRR framework, numerous subsystems must be developed and brought together, including feedback laser control loops, high-throughput targetry and diagnostics, cognitive simulation, enhanced HED codes, and advanced data analytics. This paper describes the vision for an integrated HRR laser experimental HED system and outlines some of the major considerations and challenges for realizing it.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2011

Cassini Tour Atlas Automated Generation

During the Cassini spacecraft s cruise phase and nominal mission, the Cassini Science Planning Team developed and maintained an online database of geometric and timing information called the Cassini Tour Atlas. The Tour Atlas consisted of several hundreds of megabytes of EVENTS mission planning software outputs, tables, plots, and images used by mission scientists for observation planning. Each time the nominal mission trajectory was altered or tweaked, a new Tour Atlas had to be regenerated manually. In the early phases of Cassini s Equinox Mission planning, an a priori estimate suggested that mission tour designers would develop approximately 30 candidate tours within a short period of time. So that Cassini scientists could properly analyze the science opportunities in each candidate tour quickly and thoroughly so that the optimal series of orbits for science return could be selected, a separate Tour Atlas was required for each trajectory. The task of manually generating the number of trajectory analyses in the allotted time would have been impossible, so the entire task was automated using code written in five different programming languages. This software automates the generation of the Cassini Tour Atlas database. It performs with one UNIX command what previously took a day or two of human labor.

Grazier, Kevin R.↗