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All sources NASA NTRS DOE OSTI

DOE OSTI2018

Testing the Performance and Dynamic Control of Energy-Efficient Cellular Shades in the PNNL Lab Homes

This report describes the experimental design and results of testing the energy performance of Hunter Douglas double-cell cellular shades under various control schemes in the Pacific Northwest National Laboratory’s (PNNL) Lab Homes. The results of both heating and cooling season experiments are presented, where testing is designed to assess the heating, ventilation, and air conditioning (HVAC) savings resulting from the thermal insulating properties as well as the automated and dynamic control strategies of shading devices. Control schemes tested include common “connected home” strategies where controls are integrated and coordinated between the window shading device, building thermostats, and external sensors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Digital archives, big data and image-based culturomics for social impact assessment: Opportunities and challenges

Social impact assessment (SIA) is well-established but uses conventional approaches that have become less effective in recent decades, particularly in relation to declining survey response rates and a lack of youth engagement. Images from digital archives and social media sources are poised to advance the research and practice of SIA by transcending text-based methods with insights into changing landscapes, and human engagement with them. This viewpoint describes progress, challenges and cautions toward the development of such tools (defined as culturomics), using hydroelectricity cases to illustrate potential approaches. These tools build on foundational work in a range of disciplines, including the humanities and computer science. We describe necessary advances in machine learning, image digitization, and data aggregation and visualization techniques, as well as ways to ensure that such tools are carefully tested, applied and interpreted. Challenges include the automation, acquisition and management of datasets, and using these tools appropriately and equitably. Critically, culturomics of any kind must not be used as a replacement for engagement with people, but as complementary to inclusive stakeholder engagement. - Highlights: •Image-based digital archives and social media present opportunities for new SIA tools. •Application-ready big data approaches are emerging across many fields. •SIA scholars, practitioners and stakeholders should engage with culturomics. •Challenges include automation, digitization, interpretation and justice. •Culturomics of any kind must not replace engagement with people.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Cyber threat assessment of machine learning driven autonomous control systems of nuclear power plants

We report advanced cyber-attacks against critical infrastructure and the energy sector are becoming more common. With the invention of autonomous control systems (ACS) within advanced nuclear reactor designs, system designers, reactor operators, and regulators must consider cybersecurity during the design and operational phases. This article provides a cyber threat assessment of machine learning (ML)-based digital twinning (DT) technologies in the context of advanced reactor ACS. A cyber–physical testbed was created to emulate nuclear reactor digital instrumentation and controls (I&C) and act as a basis for the ACS. The ACS was designed as two plant-level DTs predicting reactor malfunctions and determining control actions and two component-level DTs responsible for classifying component states and forecasting component inputs and outputs (I/O). Two duplicate ACS designs– one using a traditional ML framework and one using an automated ML (AutoML) framework– were created and tested against cyber-attacks on training data, real-time process data, and ML model architectures to determine their respective qualitative cyber-risk in terms of likelihood and impact. Both frameworks showed similar cyber-resilience against training, real-time, and ML architecture attacks, proving that neither is inherently more secure. Recommended safeguard and security measures are posed to system designers, reactor operators, and regulators to maintain the cybersecurity of ML-based DT technologies such as ACS, prompting a holistic view of shared responsibility for maintaining cyber-secure ML-based systems.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Extracting structural motifs from pair distribution function data of nanostructures using explainable machine learning

Characterization of material structure with X-ray or neutron scattering using e.g. Pair Distribution Function (PDF) analysis most often rely on refining a structure model against an experimental dataset. However, identifying a suitable model is often a bottleneck. Recently, automated approaches have made it possible to test thousands of models for each dataset, but these methods are computationally expensive and analysing the output, i.e. extracting structural information from the resulting fits in a meaningful way, is challenging. Our Machine Learning based Motif Extractor (ML-MotEx) trains an ML algorithm on thousands of fits, and uses SHAP (SHapley Additive exPlanation) values to identify which model features are important for the fit quality. We use the method for 4 different chemical systems, including disordered nanomaterials and clusters. ML-MotEx opens for a type of modelling where each feature in a model is assigned an importance value for the fit quality based on explainable ML.

36 MATERIALS SCIENCE↗

DOE OSTI2015

SU-E-T-160: Characterization and Monitoring of Linear Accelerator Gantry Radiation Isocenter Motion

Purpose: To characterize the motion of the radiation isocenter, over time, as a function of gantry rotation for multiple linear accelerators (linacs). Two semi-automated image-based quality control (QC) test workflows were designed to achieve this goal. Methods: The full QC-test workflow for motion characterization consisted of acquiring 16 megavoltage images at 8 gantry angles of a ball-bearing suspended off the end of the couch. Performance constancy was assessed using a shortened QC-test workflow which consisted of imaging a cube phantom placed on the couch (5 images at 4 gantry angles). Both workflows use an image processing algorithm to determine the field center and phantom position on each image and computed radiation isocenter motion as a function of gantry angle. Motion was characterized for 9 linacs of same model and performance monitored for 2 months on 3 linacs. Results: The maximum isocenter motion determined with the full-workflow for 9 linacs was within 0.38–0.79 mm. The shortened-workflow usually agreed within 0.1 mm with the full-workflow and the time required for these methods was about 4 and 15 min, respectively. For all linacs, the isocenter motion perpendicular to the gantry rotation plane followed a consistent pattern with maximum amplitude of 0.36–0.59 mm. In the gantry rotation plane, the variation among linacs was higher and the beam axis described a circle of up to 0.6 mm radius around the gantry axis of rotation (2 linacs). The radiation isocenter motion was stable as a function of time for the monitored linacs and was within ±0.1 mm of the average. Conclusion: Radiation isocenter motion parallel and perpendicular to the gantry rotation plane was characterized. In the gantry rotation plane, beam spot positioning adjustment might be used to reduce the observed radiation isocenter motion. A shortened-workflow was designed and enables performance monitoring over time.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-FG-BRB-12: Real-Time Visualization of Discrete Spot Scanning Proton Therapy Beam for Quality Assurance

Purpose: With the growing adoption of proton beam therapy there is an increasing need for effective and user-friendly tools for performing quality assurance (QA) measurements. The speed and versatility of spot-scanning proton beam (PB) therapy systems present unique challenges for traditional QA tools. To address these challenges a proof-of-concept system was developed to visualize, in real-time, the delivery of individual spots from a spot-scanning PB in order to perform QA measurements. Methods: The PB is directed toward a custom phantom with planar faces coated with a radioluminescent phosphor (Gd2O2s:Tb). As the proton beam passes through the phantom visible light is emitted from the coating and collected by a nearby CMOS camera. The images are processed to determine the locations at which the beam impinges on each face of the phantom. By so doing, the location of each beam can be determined relative to the phantom. The cameras are also used to capture images of the laser alignment system. The phantom contains x-ray fiducials so that it can be easily located with kV imagers. Using this data several quality assurance parameters can be evaluated. Results: The proof-of-concept system was able to visualize discrete PB spots with energies ranging from 70 MeV to 220 MeV. Images were obtained with integration times ranging from 20 to 0.019 milliseconds. If not limited by data transmission, this would correspond to a frame rate of 52,000 fps. Such frame rates enabled visualization of individual spots in real time. Spot locations were found to be highly correlated (R{sup 2}=0.99) with the nozzle-mounted spot position monitor indicating excellent spot positioning accuracy Conclusion: The system was shown to be capable of imaging individual spots for all clinical beam energies. Future development will focus on extending the image processing software to provide automated results for a variety of QA tests.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Pecos v. 1.0

Pecos is a python package designed to perform quality control analysis on time series data for system operations. The software loads time indexed databases, performs a series of quality control tests defined by the user, and creates automated reports which include summary statistics, tables, and graphics.

Klise, Katherine↗

DOE OSTI2025

Combining genome-wide association studies and expression quantitative trait nucleotide mapping with molecular and genetic validations to identify transcriptional networks regulating drought tolerance in Populus

Objectives: (i). To deploy a large-scale experimental drought trial for up to 1000 unique genotypes of Populus equipping the sites with controlled irrigation and drought treatments that are fully automated and monitored. FULLY COMPLETED (ii) To test the hypothesis that a suite of traits identified for drought tolerance in P. nigra can be measured in drought and control treatments in the wide germplasm collection of P. trichocarpa. FULLY COMPLETED (iii) To use established and novel GWAS model approaches to identify gene loci linked to drought tolerance traits on interest in P. trichocarpa. FULLY COMPLETED (iv) To undertake comparative analysis of GWAS results for drought tolerance traits in P. nigra and P. trichocarpa. PARTIALLY COMPLETED – remains active (v) Using RNAseq in P. trichocarpa, in droughted and control treatments to identify cis- and trans-regulated eQTN. FULLY COMPLETED (vi) Validate up to 50 cis-QTNs, from network hubs using transient protoplast assays. FULLY COMPLETED (vii) To establish Agrobacterium-based gene editing protocols in Populus. FULLY COMPLETED (viii) To utilize early leads from previous research to investigate at least 6 candidate genes for drought tolerance in Populus. FULLY COMPLETED (ix) To validate up to 20 candidate genes for drought tolerance in P. trichocarpa refined from the long-list tested in the transient assays for cis-acting hub gene targets. PARTIALLY COMPLETED- remains active.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

ASME Code change proposal to implement new universal high temperature constitutive models for Section III, Division 5

This report completes work on a universal high temperature constitutive model suitable for use with the ASME Boiler & Pressure Vessel Code Section III, Division 5 rules for the design by inelastic analysis of Class A nuclear reactor components. The goals of this work are to provide a simple model form that adequately captures the high temperature response of materials and can be applied to any future Code material. Additionally, the report describes an automated process for calibrating a model against test data. The idea is to simplify the effort required to generate a constitutive model for an arbitrary material, provided test data is available. This will accelerate the process of qualifying new Code materials in the future. In addition, the report provides calibrated models and detailed validation comparisons to test data for five currently-qualified or soon-to-be qualified materials: 316H, Grade 91, Alloy 800H, Alloy 617, and Alloy 709. The report surveys the available data for the remaining two ASME Class Materials --- 2.25Cr-1Mo and 304H --- concluding that there is enough data data to generate a model for 2.25Cr-1Mo steel provided some additional sources of non-public data can be included in the test database, but that a dedicated cyclic test campaign would be needed for 304H. Supplemental material includes the full text of an ASME Code change proposal to incorporate the models for the four currently-qualified Class A material, detailed validation comparisons to test data for the five material models, and input files for reference implementations of the constitutive models in the NEML and NEML2 modeling frameworks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Pecos v. 1.0

Klise, Katherine↗

DOE OSTI2017

Implementation of new PRODIAG algorithm and simulation-based acceptance test - 219

This paper presents the improvement of an automated-reasoning computer program for nuclear power plant diagnosis, namely PRODIAG. PRODIAG, first developed at the Argonne National Laboratory, uses confluence-based reasoning to perform fault diagnosis in engineering systems that can be described by the conservation laws for mass, energy, and momentum. Therefore, unlike other plant configuration-dependent rule-based diagnosis algorithms, the code is generally applicable to a wide variety of plant configurations by simply replacing the plant instrumentation diagram (PID) database. The need for improvement was raised when the original PRODIAG failed to provide the requisite degree of extensibility and maintainability for new applications. These shortcomings have been addressed through a new code architecture that uses an objected-oriented logic-programming language in place of the original Prolog language and uses an open-source automated reasoning engine in place of the original hardwired rule-evaluation sequence. This paper presents the architecture and implementation details of the code transition. Verification and validation studies were performed for the new PRODIAG, which involved re-running the distinct fault cases defined at the time the code was originally developed. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Adaptive Dynamic Digital Twin for Test Scenario Generation

Vehicle testing has been an important part in the development of both highly automated vehicles (HAV) and advanced driving assistant systems (ADAS). Obtaining a good representation of the Vehicle Under Test (VUT) is crucial for test scenario library generation (TSLG). Current vehicle testing methods often involve calibrating car-following models using vehicle trajectory data to create static representations that cannot be dynamically updated. For instance, when multiple vehicle trajectories are collected, it is difficult to automatically determine whether a new trajectory improves the model's representativeness or degrades its accuracy. In this paper, we introduce a dynamically updated digital twin modeling framework featuring an adaptive mechanism that evaluates new trajectory data. This mechanism can decide whether to incorporate newly collected data into the current model or create a separate digital twin model when the trajectory significantly differs from prior data. Vehicle location, speed, and acceleration extracted from the newly collected trajectory data are used to support the dynamic update decision. By integrating this digital twin model into the test library generation process, we demonstrate its ability to assist in generating test libraries while effectively handling newly collected data.

Chen, Hanlin [ORNL] (ORCID:0000000165087715)↗

DOE OSTI2023

TDCOSMO. X. Automated modeling of nine strongly lensed quasars and comparison between lens-modeling software

When strong gravitational lenses are to be used as an astrophysical or cosmological probe, models of their mass distributions are often needed. We present a new, time-efficient automation code for the uniform modeling of strongly lensed quasars with GLEE, a lens-modeling software for multiband data. By using the observed positions of the lensed quasars and the spatially extended surface brightness distribution of the host galaxy of the lensed quasar, we obtain a model of the mass distribution of the lens galaxy. We applied this uniform modeling pipeline to a sample of nine strongly lensed quasars for which images were obtained with the Wide Field Camera 3 of the Hubble Space Telescope. The models show well-reconstructed light components and a good alignment between mass and light centroids in most cases. We find that the automated modeling code significantly reduces the input time during the modeling process for the user. The time for preparing the required input files is reduced by a factor of 3 from ~3 h to about one hour. The active input time during the modeling process for the user is reduced by a factor of 10 from ~ 10 h to about one hour per lens system. This automated uniform modeling pipeline can efficiently produce uniform models of extensive lens-system samples that can be used for further cosmological analysis. A blind test that compared our results with those of an independent automated modeling pipeline based on the modeling software Lenstronomy revealed important lessons. Quantities such as Einstein radius, astrometry, mass flattening, and position angle are generally robustly determined. Other quantities, such as the radial slope of the mass density profile and predicted time delays, depend crucially on the quality of the data and on the accuracy with which the point spread function is reconstructed. Better data and/or a more detailed analysis are necessary to elevate our automated models to cosmography grade. Nevertheless, our pipeline enables the quick selection of lenses for follow-up and further modeling, which significantly speeds up the construction of cosmography-grade models. This important step forward will help us to take advantage of the increase in the number of lenses that is expected in the coming decade, which is an increase of several orders of magnitude.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

RCBC Automatic Monitoring and Control Recommendations

The recompression closed Brayton cycle (RCBC) test rig at the Sandia Brayton Laboratory provides a development platform to accelerate the commercialization of key technologies for supercritical CO 2 (sCO 2 ) closed loop Brayton cycles. The test rig enables testing to gain experience and confidence with new technologies, equipment, and processes, and automating monitors and controls will enhance Sandia’s ability to perform the types and amounts of testing needed. This report identifies candidates for automatic monitoring and control to ensure the loop remains within design limits and minimize risk to equipment due to off-normal events or conditions.

42 ENGINEERING↗

DOE OSTI2022

From fault-detection to automated fault correction: A field study

A fault detection and diagnostics (FDD) tool, as addressed by this study, is a tool that continuously identifies the presence of faults and efficiency improvement opportunities through a one-way interface to the building automation system and the application of automated analytics. Although FDD tools can inform operators of building operational faults, currently an action is always required to correct the faults to generate energy savings. Fault auto-correction integrating with commercial FDD technology offerings can close the loop between the passive diagnostics and active control, increase the savings generated by FDD tools, and reduce the reliance on human intervention. This paper presents the field study of seven fault auto-correction algorithms implemented in commercial FDD platforms. Implementation includes software changes in the FDD tools and additional controls hardware or software changes in the BAS that were required to enable the execution of different types of auto-correction algorithms in real buildings. The routines successfully and automatically correct faults and improve the operation of large built-up Heating, Ventilation, and Air Conditioning (HVAC) systems, common in most commercial buildings. The auto-correction algorithms are tested across four buildings and three different building automation systems, following a rigorous procedure to make sure they work properly and do not negatively impact the system and building occupants. Finally, technology benefits, market drivers, and scalability changes are drawn from the implementation effort and test results, to drive future research and industry engagement.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2013

Engineering Upgrades to the Radionuclide Aerosol Sampler/Analyzer for the CTBT International Monitoring System

The Radionuclide Aerosol Sampler/Analyzer (RASA) is an automated aerosol collection and analysis system designed by Pacific Northwest National Laboratory in the 1990’s and is deployed in several locations around the world as part of the International Monitoring System (IMS) required under the Comprehensive Nuclear-Test-Ban Treaty (CTBT). The utility of such an automated system is the reduction of human intervention and the production of perfectly uniform results. However, maintainability and down time issues threaten this utility, even for systems with over 90% data availability. Engineering upgrades to the RASA are currently being pursued to address these issues, as well as Fukushima lessons learned. Current work includes a new automation control unit, and other potential improvements such as alternative detector cooling and sampling options are under review. This paper presents the current state of upgrades and improvements under investigation

Forrester, Joel B.↗

DOE OSTI2025

Bayesian Optimization for Reactor Design Optimization

This study present a test case in which the Bayesian Optimization method is applied to a simulation-based reactor core design optimization problem. The test case aims to showcase the potential of an automated design optimization algorithm for reactor designs by streamlining the reactor core design workflow, given the high computational cost of simulations. The contributions of this work are threefold. First, the existing HTGR model is converted into a simulation-based design optimization test case by developing a pipeline that enables modification of key design parameters and evaluates design performance based on simulation outputs. Second, Bayesian Optimization is implemented and adapted to demonstrate the feasibility of automatic design optimization for nuclear reactor core. Proposed approach leverages Gaussian Process models to characterize the relationship between design variables and performance metrics, while incorporating novel acquisition functions that balance exploration of the design space with exploitation of promising configurations. This implementation lays the foundation for the future developments of reactor design optimization algorithms.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Make the World Safer from Nuclear Weapons

Senior Nuclear Scientist Ted Bowyer knows firsthand the challenges associated with protecting our nation. Ted and his colleagues help detect the proliferation of nuclear weapons. They developed award-winning technologies that give international treaty verification authorities “eyes and ears” around the globe. The instruments, located in 80 countries, help ensure compliance with the Comprehensive Nuclear Test-Ban Treaty, or CTBT. They are completely automated radionuclide monitoring systems that would detect airborne radioactive particles if a nuclear detonation occurred in the air, underground or at sea. Some samples collected through these technologies are sent to PNNL’s Shallow Underground Laboratory—the only certified U.S. radionuclide laboratory for the CTBT’s International Monitoring System Organization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗