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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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35 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Effects of topography on tropical forest structure depend on climate context

Abstract Topography affects abiotic conditions which can influence the structure, function and dynamics of ecological communities. An increasing number of studies have demonstrated biological consequences of fine‐scale topographic heterogeneity but we have a limited understanding of how these effects depend on the climate context. We merged high‐resolution (1 m 2 ) data on topography and canopy height derived from airborne lidar with ground‐based data from 15 forest plots in Puerto Rico distributed along a precipitation gradient spanning c . 800–3,500 mm/year. Ground‐based data included species composition, estimated above‐ground biomass (AGB), and two key functional traits (wood density and leaf mass per area, LMA) that reflect resource‐use strategies and a trade‐off between hydraulic safety and hydraulic efficiency. We used hierarchical Bayesian models to evaluate how the interaction between topography × climate is related to metrics of forest structure (i.e. canopy height and AGB), as well as taxonomic and functional alpha‐ and beta‐diversity. Fine‐scale topography (characterized with the topographic wetness index, TWI) significantly affected forest structure and the strength (and in some cases direction) of these effects varied across the precipitation gradient. In all plots, canopy height increased with topographic wetness but the effect was much stronger in dry compared to wet forest plots. In dry forest plots, topographically wetter microsites also had higher levels of AGB but in wet forest plots, topographically drier microsites had higher AGB. Fine‐scale topography influenced functional composition but had only weak or non‐significant effects on taxonomic and functional alpha‐ and beta‐diversity. For instance, community‐weighted wood density followed a similar pattern to AGB across plots. We also found a marginally significant association between variation of wood density and topographic heterogeneity that depended on climate context. Synthesis . The effects of fine‐scale topographic heterogeneity on tropical forest structure and composition depend on the climate context. Our study demonstrates how a stronger integration of topographic heterogeneity across precipitation gradients could improve estimates of forest structure and biomass, and may provide insight to the ways that topography might mediate species responses to drought and climate change.

Muscarella, Robert↗
DOE OSTI2026

GridCoPilot for Thermal Events: An LLM-Based Platform for Power Grid Reliability Analysis

Large Language Models show promise for translating natural language into database queries, but deploying such systems in safety-critical domains requires high reliability. We present an application of GridCoPilot to thermal event analysis (heatwaves and coldwaves) that affect power grid reliability. Our approach uses a LangChain SQL Agent to translate natural language queries into auditable SQL statements, with deterministic visualization routines that parse the structured query results. We introduce structural framing as a design principle, we integrate a NERC-region-level event library with county-level meteorology and decompose the combined data into three relational tables (event metadata, county-level event details, and a county-to-NERC subregion mapping), using prompt-guided joins to direct the model toward correct multi-table queries. For two core analytical patterns (identifying worst events by region and by region-year), the system achieved 100% SQL accuracy across all 16 NERC subregions and both event types (64 queries total). These results validate the approach for target use cases, though performance on diverse natural language formulations requires further investigation. We discuss design trade-offs, failure modes including JSON output truncation, and pathways for extending this approach to other hazard domains.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Numerical Analysis of Fatigue Behavior of ITER-Like Monoblock Divertor Interlayer Under Coupled Heat Loads

High-confinement mode is a very prominent operation style for future fusion device due to its unique advantages. However, the conjuncted edge localized modes (ELMs) are very difficult to control so that divertor plates are very prone to suffer both stationary high heat flux (HHF) loads of long-pulse operating mode and transient shock loads of ELMs. Most previous researches focus on degradation of plasma facing material (PFM), however, as a layer joining PFM and cooling tube, the soft copper interlayer suffers concentrated thermal stress loads due to mismatched thermal expansion of PFM and cooling tube. Its thermal fatigue behavior under such coupled loads is also of great significance to structural safety of divertor component. With such a motivation, the reduction effects on fatigue life time of a typical interlayer of monoblock divertor under series of coupled HHF and ELMs shock loading conditions are investigated. It is found that: (1) The transient shock feature of ELMs loading is propagated into interlayer with less sharp pattern. The increase of damage induced by coupled ELMs loading is limited in single cycle, while the accumulated damage of multiple consecutive coupled loading cycles is increased nonlinearly. (2) Under the coupled HHF and ELMs loading, the fatigue life time of interlayer is generally decreasing. The magnitude of decrease is increasing nonlinearly with the magnitude of ELMs peak and averaged heat flux. (3) For three characteristic parameters of ELMs shock loading such as frequency, duration and peak heat flux, the peak heat flux and frequency are two parameters more sensitive to determine coupled reduction effects on fatigue lifetime of the interlayer, while for high frequency case, time averaged heat flux takes the lead.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

GPR Robotic Assisted Non-Destructive Evaluation of Concrete Structures - 20196

Reinforced concrete structures are always under exposure of internal or external deteriorations due to many factors such as environmental, nuclear radiation or even construction deficiencies. The use of nondestructive test is one of the reliable methods to inspect structural members. In this case, GPR has a good capability to detect inside deteriorations of concrete structures. However, in many cases it is hard to inspect structural members by hand due to safety issues or inaccessibility. Thus, an alternative way to reduce such risks is to employ robot to carry nondestructive equipment. In this research, twelve reinforced concrete RC beams (8 x 16 x 96, width, height and length) are cast in the lab. Three RC beams have no defect and nine others various defects such as corrosion, de-bonded bars, void, delamination and honeycombing. The one-point load is applied at the center of the RC beam. The loading level is carried out at three levels: 50%, 75% and 100% of maximum load and total load-displacement diagram are performed. The load is held at each level and the robotic GPR is used to scan the side of RC beams. Then, RADAN software is employed to find out any defects at different loading conditions and visualize the crack propagation. The RADAN results show that the pattern of crack propagation for corrosion and debonding are same. Also, the load-displacement results present that inside defect cause reduction of load-capacity of RC beam. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Corrosion of Aluminum in the Chemical Environment after a Loss of Coolant Accident (LOCA)

Probabilistic assessment of Generic Safety Issue (GSI)- 191 generated further studies to improve the characterization of post-Loss of Coolant Accident (LOCA) aluminum release from corrosion sources, since the current industry approach of assessing aluminum release is only valid for deterministic assessments of GSI-191. The nuclear industry has long accepted that solution pH, solution temperature, sump chemical constituents and the phenomena of silicate or phosphate 'inhibition' affects the quantity of aluminum released and the quality of results obtained from models used to predict aluminum release. While improvements in the characterization of aluminum release has been made, the impacts of solution velocity, concurrent corrosion of other metals [6], and trace amount of chemical constituents such as chloride and sulfate ions on aluminum release in post-LOCA conditions have not been assessed. Those factors are well known to influence aluminum corrosion, and will be investigated in this work. The effect of flow on aluminum corrosion rate is characterized using different hydrodynamic system, which has not been investigated in GSI-191 related studies. The corrosion rate depends on the mass-transfer rate which is a function of flow velocity and flow pattern. The inhibition effect of silicon on aluminum corrosion is characterized, and the representative silicon concentration in post-LOCA condition has the potential to significantly inhibit the aluminum corrosion rate. The experiments that investigated silicon effects on aluminum corrosion also showed that calcium leached from Cal-sil can slow corrosion and that the silicon inhibition effect on aluminum corrosion became less pronounced at higher temperature and lower pH. Trace chloride and fluoride ions slightly increased aluminum corrosion rate, and the presence of sulfite ions could mitigate this harmful effect. The corrosion of zinc significantly retarded the aluminum corrosion rate, while presence of copper and carbon steel has little effect on aluminum corrosion in both galvanic and non-galvanic corrosion cases. This work is not complete and is currently evaluating high temperature (>95 C) test with all parameters mentioned and evaluation of the effects on variable boron concentrations at set conditions; Therefore an improved aluminum release model for probabilistic aluminum release model is not proposed. However, this work shows the important impact on aluminum corrosion of parameters not characterized by other studies. To obtain representative aluminum release results for use in GSI-191 probabilistic analysis, the model should be built on data obtained from experiments that account for all parameters that may impact aluminum corrosion and release. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗
DOE OSTI2025

Application of Cyber-Informed Engineering for Protecting BESS

This white paper synthesizes an array of crucial grid services provided by BESS technology, assesses its architecture and communications, and presents a case study for analysis against the principles introduced by Cyber-Informed Engineering (CIE). Furthermore, in walking through the analysis, this paper presents a framework to evaluate risks and solutions when considering BESS components. Asset owners and buyers could perform this analysis to assess their BESS product implementations, alternative inverter-based resources (IBR), and energy management systems (EMS). Battery systems fulfill various roles contingent on the unique market demands and the specific challenges presented by regional grid infrastructures. These roles also vary due to the differing utility models for ownership and operation, which are adapted to meet regional and local capabilities and requirements. Concerns have been raised regarding the potential for adversaries to exploit knowledge of battery operational patterns to orchestrate decisive attacks. However, the security of operational data for these systems may not be the primary vulnerability, as much of this information is already well-understood within the community. Applying a modest degree of subject matter expertise can often yield valuable predictions regarding how a battery will respond under certain conditions, such as grid emergencies, high or low-temperature days, Public Safety Power Shutoff (PSPS) events, and outages. The operational characteristics of batteries are well-documented, and their capabilities, including the risks associated with misoperation and the resulting consequences, are published and understood within the industry. CIE practices represent the next step in gaining functional assurance and providing an acceptable level of risk, regardless of whether a battery vendor can support a trusted and validated supply chain. While this issue has exacerbated supply chain challenges, it is not an isolated condition. This foreign supply route is the primary source of BESS for the U.S. market. Significant efforts are underway through the Bipartisan Infrastructure Law (BIL) to change that. Still, strategic short-term operational mitigations are needed to ensure the security of our operational technology (OT) systems, which are enhanced by instilling trust and are separate from vendors implementing CIE principles.

25 ENERGY STORAGE↗
DOE OSTI2022

Development and validation of a mathematical model of heart rate response to fluid perturbation

Physiological closed-loop controlled (PCLC) medical devices monitor and automatically adjust the patient’s condition by using physiological variables as feedback, ideally with minimal human intervention to achieve the target levels set by a clinician. PCLC devices present a challenge when it comes to evaluating their performance, where conducting large clinical trials can be expensive. Virtual physiological patients simulated by validated mathematical models can be utilized to obtain preclinical evidence of safety and assess the performance of the PCLC medical device during normal and worst-case conditions that are unlikely to happen in a limited clinical trial. A physiological variable that plays a major role during fluid resuscitation is heart rate (HR). For in silico assessment of PCLC medical devices regarding fluid perturbation, there is currently no mathematical model of HR validated in terms of its predictive capability performance. This paper develops and validates a mathematical model of HR response using data collected from sheep subjects undergoing hemorrhage and fluid infusion. The model proved to be accurate in estimating the HR response to fluid perturbation, where averaged between 21 calibration datasets, the fitting performance showed a normalized root mean square error (NRMSE) of 7.41 ± 2.8%. The model was also evaluated in terms of model predictive capability performance via a leave-one-out procedure (21 subjects) and an independent validation dataset (6 subjects). Two different virtual cohort generation tools were used in each validation analysis. The generated envelope of virtual subjects robustly met the defined acceptance criteria, in which 95% of the testing datasets presented simulated HR patterns that were within a deviation of 50% from the observed data. In addition, out of 16000 and 18522 simulated subjects for the leave one-out and independent datasets, the model was able to generate at least one virtual subject that was close to the real subject within an error margin of 9.56 ± 3.15% and 11.1 ± 1.22% NRMSE, respectively. In conclusion, the model can generate valid virtual HR physiological responses to fluid perturbation and be incorporated into future non-clinical simulated testing setups for assessing PCLC devices intended for fluid resuscitation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

SU-E-J-59: Effective Adaptive DMLC Gated Radiotherapy with OAR Sparing

Purpose: Patient respiratory motion degrades the effectiveness of cancer radiation treatment. Advanced respiratory gating delivers radiation dose accurately yet with elongated treatment time. The goal of this research is to propose a novel adaptive dMLC dynamic gating with high delivery efficiency and precision. Methods: The dose delivery of dMLC is aided by simultaneous tracking of tumor and organ at risk (OAR). The leaf opening/closing will follow the motion trajectory of the tumor while sparing the OAR. The treatment beam turns on only when there is no overlapping between OAR and tumor in BEV. A variety of evaluation metrics were considered and calculated, including duty cycle, beam toggling rate, and direct irradiation avoidance to OAR, under various combinations of different tumor margins and the distance between the centers of the tumor and OAR in BEV (expressed as dx). Results: Retrospective simulation was performed to investigate the feasibility and superiority of this technique using four groups of synchronized tumor and OAR motion data. The simulation results indicate that the tumor and OAR motion patterns and their relative positions are the dominant influential factors. The duty cycle can be greater than 96.71% yet can be as low as 6.69% depending different motion groups. This proposed technique provides good OAR protection, especially for such cases with low duty cycle for which as high as 77.71% maximal direct irradiation to OAR can be spared. Increasing dx improves the duty cycle (treatment efficiency) and provides better OAR volume sparing, whereas, that of the tumor margins has the opposite influence. Conclusion: This real-time adaptive dMLC gated radiation treatment with synchronous tumor and OAR tracking has inherent accurate dose delivery to tumor with reduced treatment time. In addition, the OAR protection capability make it an outstanding potential treatment strategy for mobile tumors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Is infrared-collinear safe information all you need for jet classification?

Machine learning-based jet classifiers are able to achieve impressive tagging performance in a variety of applications in high-energy and nuclear physics. However, it remains unclear in many cases which aspects of jets give rise to this discriminating power, and whether jet observables that are tractable in perturbative QCD such as those obeying infrared-collinear (IRC) safety serve as sufficient inputs. In this article, we introduce a new classifier, Jet Flow Networks (JFNs), in an effort to address the question of whether IRC unsafe information provides additional discriminating power in jet classification. JFNs are permutation-invariant neural networks (deep sets) that take as input the kinematic information of reconstructed subjets. The subjet radius and a cut on the subjet’s transverse momenta serve as tunable hyperparameters enabling a controllable sensitivity to soft emissions and nonperturbative effects. We demonstrate the performance of JFNs for quark vs. gluon and Z vs. QCD jet tagging. For small subjet radii and transverse momentum cuts, the performance of JFNs is equivalent to the IRC-unsafe Particle Flow Networks (PFNs), demonstrating that infrared-collinear unsafe information is not necessary to achieve strong discrimination for both cases. As the subjet radius is increased, the performance of the JFNs remains essentially unchanged until physical thresholds that we identify are crossed. For relatively large subjet radii, we show that the JFNs may offer an increased model independence with a modest tradeoff in performance compared to classifiers that use the full particle information of the jet. These results shed new light on how machines learn patterns in high-energy physics data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

SU-B-BRF-01: Professional Council Symposium: The Evolving US Healthcare Delivery Model, How Will the Medical Physics Profession Be Impacted and How Should We Respond?

The United States' healthcare delivery model is undergoing significant change. Insurance and reimbursement models are rapidly evolving, federal allocations are shifting from specialty services to preventive and generalpractice services, and Accountable Care Organizations are gaining in prominence. One area of focus is on the perceived over-utilization of expensive services such as advanced imaging and, in some cases, radiation therapy. Reimbursement incentives are increasingly aimed at quality metrics, leading to an increased interest in the core concepts of High Reliability Organizations. With the shift in federal resources away from specialty services and the increasing prominence of Accountable Care Organizations, we will likely be challenged to re-assess our traditional model for delivering medical physics services. Medical physicists have a unique combination of education and training in physics principles, radiation physics applications in medicine, human anatomy, as well as safety analysis and quality control methods. An effective medical physicist recognizes that to advance the institution's mission, the medical physicist must join other professional leaders within the institution to provide clear direction and perspective for the entire team. To do that, we must first recognize the macro changes in our healthcare delivery system and candidly assess how the medical physics practice model can evolve in a prudent way to support the institution's objectives while maintaining the traditionally high level of quality and safety. This year's Professional Council Symposium will explore the many facets of the changing healthcare system and its potential impact on medical physics. Dr. Shine will provide an overview of the developing healthcare delivery and reimbursement models, with a focus on how the physician community has adapted to the changing objectives. Mr. White will describe recent changes in the reimbursement patterns for both imaging and radiation therapy services, the underlying imperatives that will influence additional changes in the near-term future, and the broader changes in the medical physics workforce that may arise due to many (often conflicting) directives and incentives both internal and external to the profession. Maintaining the integrity of the medical physics profession and the high quality of medical physics services will require a shared understanding of the changing practice environment and a firm commitment to protecting the key priorities of clinical medical physics as the healthcare system transitions to a new and very different model. To be effective as medical physicists, we must learn how to provide leadership in our respective institutions. Learning Objectives: Understand the macro changes occurring in the US healthcare delivery system. Understand the likely near-term, and possible longer-term, impact on the medical physics profession. Understand some strategies for providing leadership during this period of significant change.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2019

Operando FTIR Studies of Electrolyte Solution Structures and Dynamics at Electrode-Electrolyte Interfaces

The well-stabilized electrode-electrolyte interface (EEI) is critical to battery performance and safety, thus understanding the electrolyte solution structures (e.g., ion solvation and ionic association) and dynamics within EEI is an important area of study. Unfortunately, due to the sensitive nature of the electrodes, ex-situ characterization methods are limited and challenging to interpret as chemical and structural changes occur upon deconstructing the cell. In this work, we present operando characterization of near-surface electrolyte solution structures and dynamics by ATR-FTIR spectroscopy during battery cycling. We studied two selected model electrodes, a lithium nickel manganese cobalt oxide (NMC) or a planar silicon (Si), in a standard Gen2 electrolyte of 1.2 M LiPF6 in ethylene carbonate (EC):ethyl methyl carbonate (EMC) (3:7 wt%). In the former case, the composite cathode on aluminum foil is placed face-down on an ATR crystal. A ring of lithium metal serves as the counter/reference electrode and no separator is required. In the latter case, a lightly doped p-type silicon wafer is phosphorous-doped at the surface to increase the conductivity of the sample without compromising infrared transparency. The ATR crystal is then pressed on the back of the silicon with a minimal air gap to ensure sufficient optical contact between the two materials. The front of wafer is then placed in a modified coin-type cell geometry with a minimal electrolyte, a separator, and a lithium metal counter/reference electrode. In both experiments, we analyze the electrolyte solution structures within the EEI and find similar patterns as a function of potential. Firstly, we find that EMC decomposes faster than EC -suggesting that EMC plays a greater role in the electrochemical reactions on the electrode surface (e.g., formation of a protective layer to prevent further electrolyte decomposition). Secondly, we monitor the increase/decrease of the vibrational absorption peaks attributed to carbonates coordinated with Li+ ions relative to the decrease/increase of their uncoordinated counterparts, as expected when changing the local concentration of Li+ ions near the electrode surface during deintercalation/intercalation into the electrode. Finally, we observe that the features assigned to the Li+-PF6 -/-solvent molecules contact ion pair relative to the uncoordinated PF6 - anion. These observations give important information regarding the electrolyte solution structures and dynamics near the electrode surfaces. We look forward to applying these techniques to additional lithiumion battery systems with different cathode or anode materials and beyond lithium-ion systems to characterize surface chemistry/evolution (on-going research) and solution structures/dynamics (in particular, (de)solvation behaviors) within the EEI, which can be a bottleneck to efficient ion transfer from the electrolyte to the electrode.

14 SOLAR ENERGY↗
DOE OSTI2024

Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient System (CYDRES)

The DOE CYDRES project is driven by the urgent need to address critical research gaps in the domain of cyber-physical security of smart buildings, including Grid-interactive Efficient Buildings (GEBs). CYDRES, a real-time advanced building resilient platform, aims to enhance the cyber-attack-immune capabilities of buildings through multi-layered prevention, detection, and adaptation mechanisms. CYDRES consists of five key modules: a multi-layer network analyzer, an Automatic Fault Detection, Diagnosis, and Prognosis (AFDDP) framework, an intelligent mode selector, a cyber-resilient control framework, and a situation awareness platform. The Network Analyzer employs a data-driven framework that includes a protocol state learning tool and a CRF (Conditional Random Field) command validator. In Hardware-In-the-Loop (HIL) testbeds, it achieved 100% detection accuracy with a false alarm rate of 3%, validating its efficacy in identifying selected cyber-attacks. The AFDDP framework leverages pattern matching, PCA (Principal Component Analysis)-based strategies, and a DBN (Dynamic Bayesian Network)-based fault diagnosis approach to pinpoint the causes of physical system abnormalities using Building Automation System (BAS) data. In HIL experiments, the AFDDP module attained a detection accuracy of over 95% with a false alarm rate below 7%. Additionally, the fault detector utilized machine learning (Random Forest) and deep learning (Multi-Layer Perceptron) methods with acoustic sensor data to achieve a 100% fault detection accuracy in Heating, Ventilation, and Air-Conditioning (HVAC) equipment. The Mode Selector offered real-time impact analysis, allowing immediate actions to protect BASs in the face of emerging threats. The cyber-resilient control framework included an adaptive Model Predictive Control (MPC) and a measurement compensator, reducing temperature violations by up to 94% and improving the total demand flexibility by up to 70% in HIL experiments. Such HIL experiments covered a cyber-attack case and a physical fault case, showcasing CYDRES’ efficiency in maintaining operational continuity during threats. The situation awareness platform in Grafana enhanced real-time threat detection and response visualization, augmenting the operational awareness for building operators. CYDRES demonstrated high technical effectiveness in various test scenarios, particularly in HIL environments. The project's phased development approach ensured efficient use of resources, highlighting its practical feasibility and readiness for commercialization. By enhancing the security and resilience of building operations, CYDRES represents a significant advance in mitigating risks associated with cyber-physical systems, thereby enhancing public confidence in the safety of modern building infrastructure. Future directions for the project include expanding testing protocols, refining AFDDP methodologies, exploring more comprehensive resilient control strategies, and testing in real commercial buildings.

42 ENGINEERING↗
DOE OSTI2019

Transhepatic Tract Embolisation After Biliary Intervention Using n-Butyl Cyanoacrylate and Autologous Blood: A Retrospective Analysis of 42 Patients

Purpose: We evaluated the safety and efficacy of transhepatic tract embolisation after a biliary intervention using n-butyl cyanoacrylate (NBCA) and autologous blood. Materials and Methods: Between January 2017 and December 2018, 42 consecutive patients (mean age: 71 ± 15 years, 24 men) with malignant (n = 26) or benign (n = 16) biliary obstructions underwent percutaneous biliary intervention followed by tract embolisation within 2 weeks. Forty-six transhepatic tracts (4 bilateral) in 42 patients were embolised using a NBCA and lipiodol mixtures (1:1–1:2 ratios) after intraductal infusion of peripherally obtained autologous blood. The indwelling catheter diameters were 8.5–14 Fr. The median interval between percutaneous biliary drainage and tract embolisation was 10 days (range 3–14 days). Glue-cast formation via fluoroscopy and immediate complications were reviewed retrospectively in medical records. Follow-up data (median: 135, range 11–720 days) including computed tomography (CT) images (n = 17) were evaluated for delayed complications and glue-cast formation. Results: Successful glue-cast formations were achieved in all 46 tracts. No patients experienced haemorrhage, and only one patient had external bile leakage. Eight patients complained of abdominal pain (numerical scale ≤ 5) immediately after embolisation, which was controlled by analgesics. Two patients had transient fever. Segmental (n = 11) or sub-segmental (n = 6) glue-cast patterns were identified along the transhepatic tract by follow-up CT. No biliary obstructions were caused by inadvertent glue spread. Fragmented glue was detected outside the stent in one patient. Conclusion: Transhepatic parenchymal tract embolisation with NBCA and autologous blood is a safe and feasible method for preventing bile leakage. Level of Evidence: Level 4, Case Series.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Measuring, Cutting and Sorting Irradiated Control Rods to Limit the Volume of Intermediate Level Long-lived Waste - 17001

During operation, the PWR control rods are either completely extracted (scram or safety rods) or partially inserted in the operating zone of the core (fine control or operating rods). At the nominal rating conditions or close to them, the operating zone is limited to some steps of insertion in the order of a few tens of cm. In fact, only the lower part of the control rods are subjected to a significant neutron flux with an impact on the neutron activation and so on the waste classification (Low Level Short-lived Waste versus Intermediate Level Long-lived Waste). Our calculative as well as experimental experience confirms the significant presence of radionuclides in the control rods, but only in the lower parts. Measuring, cutting and finally sorting control rod scraps can reduce the volume of Intermediate Level Long-lived Waste planned for our storage deposit facility. This paper presents the EDF/DP2D methodologies followed to determine the sort criteria between the Low Level Short-lived Waste versus the Intermediate Level Long-lived Waste zones for the Silver-Indium-Cadmium control rods. The irradiated control rods are stored in cases without their head. Each case can contain several control rods, and the cases are stored under water in the fuel assembly pool. To calculate the radioactive inventories, we have developed a calculation scheme which is composed of a 3-dimensional mapping of the neutron flux, a calculation of the evolution of the isotopic compositions under neutron flux and finally a comparison between calculated and measured values. The main hypotheses of the control rods calculation take into account: - 3-dimensional geometry and 3-dimensional neutron sources distribution, - the isotopic compositions including impurities, - the history of irradiation resulting mainly from the daily power production, the positions of the control rods in the loading patterns and the positions in the axial operating zone. In order to validate the calculations, measurements were made 20 meters under water in the fuel assembly pool. The experimental results show the presence of many gamma emitter radionuclides. Only Ag-108m was retained for validating the calculations. This is due to the fact that silver is considered as the 'standard' chemical element for our control rods and silver produces Ag-108m which is a long-lived gamma emitter radionuclide. The analysis of the calculated results and the measured values allow us to build a simplified physics model for the simulation of the control rods activation. Finally three sort criteria can be proposed: - Without measurement devices, the sorting is based on an empirical sort criterion. Cuttings must then be made on the 2 back-ends of the control rod pins. This option is due to the difficulty in knowing the orientation of the pins in the storage cases. The cutting lines are placed at approximately 1 m from the 2 back-ends of the pins. This approach does not allow a great optimization of the sorting, less than 50% of the length of the control rods can be saved from Intermediate Level Long-lived Waste storage. - With a simple dose rate measurement device, the knowledge of the orientation of the pins in the storage cases allows us to limit cuttings to the lower part of the control rods. Depending on the 'top to tail' cases, between approximately 50% and 75% of the length of the control rods can be saved from Intermediate Level Long-lived Waste storage. - With an accurate measurement device, the sorting can be based on a specific activity of Ag-108m. Over 4400 Bq/g of Ag-108m (corresponding to the Intermediate Level Long-lived Waste limit), the control rod pieces can be considered as a long-lived waste. The measurements must be made over the 2 back-ends of control rod pins to examine the cases of 'top to tail' storage. This approach allows a great optimization of the sorting. Depending on the history of irradiation, more than 75% of the length of the control rods can be saved from Intermediate Level Long-lived Waste storage. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Reactivity Coefficient Calculation for a Low-Power LEU Research Reactor

Core design studies on a 20-MW thermal power low enriched uranium (LEU) fueled research reactor are underway at the NIST Center for Neutron Research (NCNR) with the primary purpose of providing quality neutron beams for scientific research. The 'tank-in-pool' design pattern is adopted for the new reactor: A compact core composed of two horizontally split halves are surrounded by a cylindrical D{sub 2}O reflector tank, and the tank is itself surrounded by a large H{sub 2}O pool, which functions as thermal and biological shielding. The split core consists of 18 MTR-type fuel elements which are evenly distributed into two regions. The LEU fuel used in the study is the U{sub 3}Si{sub 2}-Al dispersion fuel with U-235 enrichment of 19.75%, the only NRC certified LEU fuel in the U.S. The core is cooled and moderated by H{sub 2}O, and separated from D{sub 2}O by zircaloy core boxes. Hafnium control blades are utilized as both criticality and safety control elements for the reactor. They are controlled by a mechanical driver located at the bottom of the core but with the fully withdrawn positions at the top of the core. In a standard reactor calculation, it is necessary to evaluate the reactivity coefficient with respect to some physical parameters such as fuel or moderator temperature. For nearly all reactor designs, negative reactivity coefficients are required for safety. As a light-water cooled thermal reactor, the new reactor is designed to work in an under-moderated mode with the most achievable reactivity. The core is required to have negative reactivity coefficients under any normal or abnormal circumstances such as over power transient, loss of coolant or reflector, etc. Therefore the reactivity coefficient addresses reactor safety concerns as well as provides valuable quantitative parameters for reactor safety analyses. In this summary, three typical reactivity coefficients for the low-power LEU core are calculated using the Monte-Carlo code MCNP-6: the moderator temperature coefficient (MTC), the fuel temperature coefficient (FTC), and the void coefficient (VC). A direct perturbation methodology is applied to calculate all these coefficients. The perturbed case is produced by manually perturbing a single physical property with respect to the reference case (the one with normal operational conditions), as the multiplication factor (i.e. k{sub eff}) of the perturbed case is calculated by MCNP. The corresponding reactivity coefficient is thereby determined by dividing the reactivity change over the associated parameter changes. Core design studies are underway at NIST to develop a low-power LEU fueled beam reactor to advance the neutron source capability at NCNR for the next century. The reactivity effect caused by moderator temperature, fuel temperature and void is investigated though a direct perturbation approach using the MCNP code. The MTC, FTC, and VC for a representative startup core is obtained and the negative effect characteristics of these coefficients are observed. The reactivity effects under several postulated abnormal scenarios are also investigated. The overall negative feedback to the reactivity at each situation is confirmed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Subtask 1.4 - Techno-Economic Assessment of Regional Carbon Utilization Scenarios and Attendant Monitoring Technology

The U.S. Department of Energy (DOE) Carbon Storage Program seeks to develop technologies to significantly improve the effectiveness of carbon capture and storage (CCS), reduce the cost of implementation, and support the readiness of widespread commercial deployment by 2035. To accomplish this goal, technical and economic barriers must be addressed and the results used to inform regulators and industry on the safety, permanence, and viability of carbon storage. To help overcome these barriers, the Energy & Environmental Research Center (EERC) conducted three activities: 1) investigate the regional techno-economic life cycle of CO2 enhanced oil recovery (EOR) in North Dakota, 2) assist DOE in determining the prospective CO2 storage resource of residual oil zones (ROZs), and 3) develop a seismic technique for monitoring geologic storage of CO2. These three activities address two strategic goals enumerated in the DOE–EERC Cooperative Agreement, namely, 1) to advance foundational science and 2) to inform data-driven policies that enhance U.S. economic growth and job creation, energy security, and environmental quality. Activity 1 In North Dakota, there is synergistic incentive to develop and implement CO2 EOR technologies. Regional industry partners are actively seeking options that can cost-effectively improve the efficiency of power production, while also coproducing CO2 for use in EOR applications. A full-value-chain techno-economic assessment that links lignite resources, power generation, and EOR is needed to determine the implications for a state or region to continue to use these resources or look elsewhere for other energy sources and revenue streams. The integration of North Dakota’s lignite power industry with the state’s oil industry has the potential to revitalize legacy oil fields and produce up to 1 billion barrels of additional oil using CO2 EOR while providing a market for a CO2 commodity captured at coal-fired power plants. Revitalization of North Dakota’s legacy oil fields will bring new industry investment to the state, resulting in the growth of oil-related jobs and revenue through oil sales, severance tax, and associated oilfield development activities (drilling, pipelines, etc.). CO2 demand for EOR and incremental oil production were calculated for 201 conventional oil fields in North Dakota. Infrastructure development in the fields was estimated using 1) a traditional vertical well arrangement of CO2 injectors and oil producers and 2) an advanced case where horizontal wells were used exclusively. Pipeline, compression, and recycling infrastructure requirements were also estimated. When viewed from the CO2 capture and CO2 EOR sectors, the advanced case showed a positive investment scenario when including potential benefits of the 45Q tax credit policy. An economic evaluation of a full implementation of CO2 EOR showed an average $60 billion potential state economic impact estimated over the 37-year construction and production time frame could be realized with an assumed oil price of $65/bbl. Oil price ranges of $35–$90/bbl cause an estimated variation of ±$5 billion over the potential effort. The total net state government revenues were estimated over the 37-year construction and production time frame. With an assumed oil price of $65/bbl, total potential fiscal impact could average $7.4 billion. This result ranges about ±$2.5 billion for a potential EOR implementation effort for oil price ranges of $35–$90/bbl. This broad-brush assessment was focused on “magnitude-of-effect” perspectives of what CO2 capture and use for EOR could mean to the state. Whether CO2 EOR ever becomes widely adopted is not the issue at this stage of evaluation. The question being answered is, How valuable could CO2 capture and CO2 EOR be for the state and local jurisdictions in western North Dakota? The results of the current economic assessment remove any ambiguity to that question. Full implementation of CO2 EOR as modeled in this study provides substantial economic benefits to the state, even at low oil prices (i.e., $35/bbl). Job creation and government revenues could be substantial, depending on the scale of implementation. With a better understanding of what CO2 EOR might mean for the state’s economy, the focus can now shift to the policies and financial mechanisms needed to make private investment in CO2 capture and use as EOR competitive with other energy-related pursuits. Activity 2 ROZs contain remnants of oil not swept away by natural waterflooding. Although nearly all of the identified ROZs are found in West Texas, there is evidence that this category of oil reservoir can be found in other major oil-producing basins of the United States. Because the formation of these oil reservoirs is distinct from other conventional reservoirs, the method to estimate the prospective CO2 storage resource in ROZs may be equally distinct from the method used for conventional fields. As such, the EERC collaborated with DOE’s National Energy Technology Laboratory (NETL) to investigate the feasibility of CO2 storage in ROZs and determine what specific modification (if any) needs to be made to the current DOE volumetric method to estimate prospective CO2 storage resource in oil reservoirs. This activity built on a previous EERC investigation to identify ROZs in the Williston and Powder River Basins and upon collaborations between the EERC and NETL to develop storage resource estimation methods for different types of geologic CO2 storage. Review of the volumetric approach raised questions about the applicability of such an approach to hydrocarbon-bearing zones without the inclusion of potential hydrocarbon production. A production-based approach was presented by the EERC to inform the working group of additional methods of increasing the CO2 storage resource potential. Because the production-based method focuses more heavily on oil recovery than CO2 storage, it was not included in the working group manuscript. Activity 3 The EERC has used sparse and irregular seismic arrays to detect CO2 injected into a reservoir. The variability of seismic noise recorded by the sensors directly impacts the seismic interpretation. However, designing noise attenuation workflows effectively can be a more challenging task using sparse and irregular arrays for data acquisition. Based on the hypothesis that noncoherent noise is stationary during weekly data acquisition, a new machine-learning algorithm was developed to automatically estimate noise conditions using passive records, noise from active records, and ancillary information. The new noise attenuation processing workflow can improve the time-lapse detection of CO2 from sparse and irregular array acquisitions. Results show spatial and temporal noise patterns can be related to the location of the sensors and the weather conditions during the data acquisition and that our attenuation processing workflow can improve the time-lapse detection of CO2 from sparse and irregular array acquisitions. This effort was funded in part through the EERC–DOE Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Department of Commerce.

Peck, Wesly↗