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At least 217 records · Page 12

Integrating Machine Learning into a Methodology for Early Detection of Wellbore Failure [Slides]

Approximately 93% of US total energy supply is dependent on wellbores in some form. The industry will drill more wells in next ten years than in the last 100 years (King, 2014). Global well population is around 1.8 million of which approximately 35% has some signs of leakage (i.e. sustained casing pressure). Around 5% of offshore oil and gas wells “fail” early, more with age and most with maturity. 8.9% of “shale gas” wells in the Marcellus play have experienced failure (120 out of 1,346 wells drilled in 2012) (Ingraffea et al., 2014). Current methods for identifying wells that are at highest priority for increased monitoring and/or at highest risk for failure consists of “hand” analysis of multi-arm caliper (MAC) well logging data and geomechanical models. Machine learning (ML) methods are of interest to explore feasibility for increasing analysis efficiency and/or enhanced detection of precursors to failure (e.g. deformations). MAC datasets used to train ML algorithms and preliminary tests were run for “predicting” casing collar locations and performed above 90% in classification and identifying of casing collar locations.

54 ENVIRONMENTAL SCIENCES↗

Integrating Machine Learning into a Methodology for Early Detection of Wellbore Failure [Slides]

Approximately 93% of US total energy supply is dependent on wellbores in some form. The industry will drill more wells in next ten years than in the last 100 years (King, 2014). Global well population is around 1.8 million of which approximately 35% has some signs of leakage (i.e. sustained casing pressure). Around 5% of offshore oil and gas wells “fail” early, more with age and most with maturity. 8.9% of “shale gas” wells in the Marcellus play have experienced failure (120 out of 1,346 wells drilled in 2012) (Ingraffea et al., 2014). Current methods for identifying wells that are at highest priority for increased monitoring and/or at highest risk for failure consists of “hand” analysis of multi-arm caliper (MAC) well logging data and geomechanical models. Machine learning (ML) methods are of interest to explore feasibility for increasing analysis efficiency and/or enhanced detection of precursors to failure (e.g. deformations). MAC datasets used to train ML algorithms and preliminary tests were run for “predicting” casing collar locations and performed above 90% in classification and identifying of casing collar locations.

54 ENVIRONMENTAL SCIENCES↗

Geomechanical characterization of Rock Valley carbonates

In Rock Valley, Nevada, the USA, past earthquake sequences and shallow faulting in Paleozoic carbonates remain poorly understood. Carbonates are typically more ductile rocks that do not experience large stress drops or fracture coalescence, which contradicts previous observations in the region. As part of the Source Physics Experiment, an effort has been made to experimentally characterize the petrophysical and geomechanical properties of carbonates from Rock Valley. Well core and outcrop samples were used to determine the difference between shallow-buried Tertiary limestones and deeply buried Paleozoic limestones and dolostones. The carbonates possessed porosities between 3 and 9%, with V P and V S in the Tertiary carbonates around 2700 and 1800 m/s, respectively, and 6000 and 3100 m/s, respectively, in the Paleozoic carbonates. Microstructural characterization revealed that the Paleozoic carbonates contained significantly more pre-existing damage and alteration than the Tertiary carbonates, though the deformation varies from localized to diffuse. Unconfined Brazilian tests and triaxial tests with confining pressures between 0 and 50 MPa showed that, although samples all experienced failure, the dolostones typically failed at greater stresses and possessed greater E/ν ratios than the limestones. Furthermore, the Hoek–Brown failure criterion was used to construct failure envelopes with the compressive and tensile failure tests. Velocity, density, and porosity measurements were used to construct a hypothetical velocity-depth profile and compare the results with the theoretical petrophysical measurements. Using brittleness analysis, the likely failure conditions were determined to be low-porosity dolomitic rock for fault nucleation in the Paleozoic basement.

Brittleness↗

A multiscale cohesive law for carbon fiber networks

Better predictive models of mechanical failure in low-weight heat shield composites would aid material certification for missions with aggressive atmospheric entry conditions. In this study, we develop such a model for the rapid engineering analysis of the failure limits of phenolic impregnated carbon ablator (PICA) - a leading heat shield material whose structural component is a carbon fiber network. We hypothesize inelastic deformation failure mechanisms and model their behavior using molecular dynamics simulations to calculate the binding energy. We then upscale this binding energy to the macroscale using a renormalization argument. The approach delivers insightful and reasonably accurate macroscale predictions that compare favorably to experiments. In application, the model is validated for a particular variety of PICA by comparison to experiment and would then be used to study design scenarios in different entry conditions.

36 MATERIALS SCIENCE↗

Joint Development of SAS4A Code in Application to Oxide-fueled LFR Severe Accident Analysis

The scope of this project was to pursue specific SAS4A liquid-metal cooled reactor (LMR) safety analysis software extensions to simulate postulated accidents with fuel failures for oxide-fueled Lead-cooled Fast Reactors (LFRs). Since most U.S. LMR experience is on sodium-cooled fast reactor options based on past testing and operation experience with EBR-II and FFTF, the DOE’s legacy fast reactor safety analysis capabilities were focused on metal-fueled pool-type concepts with sodium coolant. In recent years, Westinghouse Electric Company (WEC) has decided to pursue an LFR design as one of their next generation nuclear technology options because of its favorable safety and economics attributes. Oxide fuel is considered among other fuel options due to previous WEC experience with this fuel form. Development of this new technology requires the availability of adequately accurate computational tools, some of which can be adapted from versions of similar software used for analysis of other LMRs. Although Argonne National Laboratory’s (ANL) SAS4A/SASSYS-1 safety analysis software suite (shortened as SAS4A code hereafter for brevity) has the basic capabilities to model LFR system designs, the SAS4A code modules used in the analysis of accidents with fuel/cladding failures lack appropriate models for the unique phenomena that govern as-irradiated oxide-fuel damage mechanisms in lead coolant. Therefore, the objective of this project was to extend the capabilities of SAS4A with mechanistic oxide-fuel failure models in lead coolant for margin to failure assessments, analysis of failure modes, location and timing of failures under different accident scenarios consistent with the whole-plant dynamic response including the reactivity feedback, and assessment of the potential for fuel damage propagation due to potential fission gas jet and fuel-fragment/molten fuel impingement to neighboring fuel pins in an assembly. This report provides mainly a summary of Argonne’s technical contributions in the joint project, but the reports and publications by the Participant team are included as references at the end of the report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

In Situ Synchrotron Tensile Investigations on Ultrasonic Additive Manufactured (UAM) Zirconium

The microstructure evolution of ultrasonic additive manufactured (UAM) zirconium under room temperature uniaxial tensile straining is reported. Miniature dog-bone tensile specimens of two orientations were cut from a UAM zirconium bar for in situ synchrotron tensile tests. Wide-angle X-ray scattering (WAXS) scanning at the Advanced Photon Source (APS) at Argonne National Laboratory was used to unveil the changes in microstructure of the entire gauge regions throughout the straining. A series of WAXS data analysis methods were utilized to quantify both elastic and plastic deformation mechanisms within the strained specimens. Stress concentrations were identified during early stage of plastic deformation, which become candidate necking positions and eventually lead to failure. Fracture surface analysis implied that these stress concentration locations may be correlated to the fabrication defects, providing insightful guidance for future improvement of the UAM zirconium process.

36 MATERIALS SCIENCE↗

Safety Risk Reliability Model Library

SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).

Wang, Congjian↗

Use of AI for Interpreting Technical Specifications for Power Uprates in Nuclear Power Plants

Powerpoint presentation. Background information provided on power plant uprates. Discussion of the current and proposed approaches to power plant uprates. Explanation of what data is used to draft a LAR. Methods such as retrieval augmented generation (RAG) and fine-tuning are discussed. Use case analysis is performed. Different failure types are examined. Conclusions are drawn from the analysis. Future work is proposed.

97 - MATHEMATICS AND COMPUTING↗

Evaluation of Joint Cyber/Safety Risk in Nuclear Power Systems

This report presents an analysis of the Emergency Core Cooling System (ECCS) for a generic Boiling Water Reactor (BWR)-4 NPP. The Electric Power Research Institute (EPRI) developed Hazards and Consequences Analysis for Digital Systems (HAZCADS) process is applied to the ECCS and its subsystems to identify unsafe control actions (UCAs) which act as possible cyber events of concern. The analysis is performed for two design basis events: Small-break Loss of Coolant Accident (SLOCA) and general transients (TRANS), such as unintended reactor trip. In previous work, HAZCADS UCAs were combined with other cyber-attack analysis to develop a risk-informed approach; however, this was for a single system. This report explores advanced systems engineering modeling approaches to model the interactions between digital assets across multiple systems which may be targeted by cyber adversaries. The complex and interdependent design of digital systems has the potential to introduce emergent cyber properties that are generally not covered by hazard analyses nor formal nuclear Probabilistic Risk Assessment (PRA). The R&D and supporting analysis presented here explores approaches to predict and manage how interdependent system properties effect risk. To show the potential impact of a successful cyber-attack to formal PRA event tree probabilities, HAZCADS analysis was also used. HAZCADS was also used to model the automatic depressurization system (ADS) automatic actuation. This analysis extended to an integrated system analysis for common-cause failure (CCF). In this aspect, the HAZCADS analysis continued by analyzing plant design details for system connectivity in support of critical plant functions. A dependency matrix was developed to depict the integrated functionality of the interconnected systems. Areas of potential CCF are indicated. Future work could include adversary attack development to show how CCF could be caused, resulting in PRA events. Across the multiple systems that comprise the ECCS, the analysis shows that the change in such probabilities was very different between systems. This indicates that some systems have a larger potential risk impact from successful cyber-attack or digital failure, which indicates a need for these systems to have a higher priority for design and defensive measures. Furthermore, we were able to establish that a risk analysis using any arbitrary threat model establishes an ordering of components with regard to cyber-risk. This ordering can be used to influence the overall system design with an eye to lowering risk, or as a way to understand real-time risk to operational systems based on a current threat landscape. Expert knowledge of both the analysis process and the system being analyzed is required to perform a HAZCADS analysis. The need for a tiered risk analysis is demonstrated by the results of this report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Bio-project “derisking” through development of systematic methodologies and frameworks for risk assessment

One of the primary hindrances to producing a viable, sustainable domestic biomass industry for renewable biofuels, bio-products and bio-power is the lack of understanding and quantification of the risks associated with both the biomass supply chain and preprocessing and conversion technologies. Currently a consistent method for assessing, comparing, and quantifying risks in biomass supply chains does not exist, creating a major investment barrier to bioenergy projects in the U.S. The lack of a standardized approach has resulted in bioenergy stakeholders independently using inconsistent approaches and evaluation criteria, leading to unreliable and incomparable assessments of risks and financing barriers to bio-project development. Along with the challenges of inconsistent risk assessment for supply chain risk, technology specific risks based on variability in biomass properties are not fully understood and can pose significant unforeseen challenges for bioenergy projects. In many cases these properties have not yet been identified and the impacts on the proposed technology and products unquantified. This is particularly challenging for emerging preprocessing and conversion technologies. Without a firm understanding of the preprocessing/conversion technology-specific critical properties, the risk of a proposed bio-project cannot be fully evaluated. To address inconsistent risk evaluation in the biomass supply chain supporting project financing, a Biomass Supply Chain Risk Standards (BSCRS) framework was developed. The BSCRS framework includes a comprehensive list of known and perceived risks (Risk Indicators) to the supply chain developed through 100’s of interviews with bioenergy industry experts spanning from feedstock growers and suppliers to representatives from the financial sector. These risks have been organized into a manageable hierarchy of Risk Categories and Risk Factors that can be practically assessed. This BSCRS framework also provides mitigation strategies for multiple Risk Indicators from best available industry practices and research findings. Additionally, a risk quantification methodology for each Risk Factor, Risk Category, and the bio-project as a whole was developed to enable capital markets to assess feedstock risk more efficiently and more accurately. Multiple case studies representing existing bio-projects have been used to evaluate and verify the BSCRS framework and scoring methodology. To address technological risk along with the supply chain risk captured in the developed BSCRS framework, this work also focuses on development of a systematic criticality assessment tool using well-accepted, quantitative risk analysis methods to evaluate bioenergy feedstock critical properties impacting system unit operations. The proposed Failure Mode and Effect Analysis (FMEA) approach uses a team of subject area experts (SAEs) for each targeted unit operation within a system. Collectively, the team will develop and use a quantitative scoring system to assess the material attributes, process parameters, and quality attributes for key unit operations that have already been identified. The FMEA process generates Risk Priority Numbers (RPNs) for the various failures and predominant causes for each material/process unit/product combination resulting in a semi-quantitative, standardized methodology for assessing technological risk and biomass properties contributing to that risk.

09 BIOMASS FUELS↗

Hazard and risk analysis framework for nuclear power plant–based integrated energy systems

Employing integrated energy systems (IESs) with nuclear power plants (NPPs) can improve NPP utilization by leveraging dedicated thermal and electric power delivery, but it may also increase operational safety risks. This paper presents a framework to identify and quantify hazards and risks for such IESs. The framework combines accidentology to review past industrial accidents with failure modes and effects analysis (FMEA) to identify potential future incidents. Hydrogen explosion and toxic chemical release hazards are of particular concern. Explosion consequences are quantified using the Bauwens-Dorofeev (Bauwens) and trinitrotoluene equivalent mass (TNT-EM) methods, while chemical release consequences are computed using the Gaussian atmospheric dispersion method. Operational disturbances from direct electrical and thermal integration that may affect NPP safety are modeled using probabilistic risk analysis (PRA). Hazards and risks are then evaluated for regulatory compliance. The framework is applied to IESs comprising pressurized or boiling water reactors supplying three levels of thermal and electrical power to industrial customers. Case studies include high-temperature steam electrolysis hydrogen plants of varying capacities and a synthetic fuel production plant. Sensitivity analysis examines piping component failures in the PRA model as a precursor to cost estimation for thermal extraction line design. Additionally, Fussel-Vessely (FV) and risk increase importance (RII) measures identify risk-informed design improvements for the thermal extraction system. FMEA highlights hazards such as loss of offsite power, prompt loss of electrical load, loss of thermal output, and immediate steam diversion, in addition to hydrogen explosions and toxic chemical releases. Both Bauwens and TNT-EM methods suggest maintaining several hundred meters of separation between the NPP and hydrogen facility to mitigate explosion risks. PRA results show a maximum initiating event frequency increase of 1.15% and an overall risk increase of 0.28%. Importance measure analysis identifies upstream pipe leak isolation components as critical. Evaluating the results against safety regulations, it is concluded that hazards and risks can be managed to comply with regulations through risk-informed thermal and electrical connection designs, component selection, maintenance programs, and safe separation distances between NPPs and integrated industrial facilities.

08 - HYDROGEN↗

Wind Turbine Gearbox Failure Detection Through Cumulative Sum of Multivariate Time Series Data

The wind energy industry is continuously improving their operational and maintenance practice for reducing the levelized costs of energy. Anticipating failures in wind turbines enables early warnings and timely intervention, so that the costly corrective maintenance can be prevented to the largest extent possible. It also avoids production loss owing to prolonged unavailability. One critical element allowing early warning is the ability to accumulate small-magnitude symptoms resulting from the gradual degradation of wind turbine systems. Inspired by the cumulative sum control chart method, this study reports the development of a wind turbine failure detection method with such early warning capability. Specifically, the following key questions are addressed: what fault signals to accumulate, how long to accumulate, what offset to use, and how to set the alarm-triggering control limit. We apply the proposed approach to 2 years’ worth of Supervisory Control and Data Acquisition data recorded from five wind turbines. We focus our analysis on gearbox failure detection, in which the proposed approach demonstrates its ability to anticipate failure events with a good lead time.

17 WIND ENERGY↗

Control, Fault Management, and Grid Support Functionality of an MV AC-DC Solid State Transformer based EV Extreme Fast Charging Station

Electric vehicles (EVs) have become increasingly popular in recent times while revolutionizing the consumer and commercial transportation market. The development of charging infrastructure has become one of the priorities for increasing the adoption of EVs. Extreme fast charging (XFC) technology can reduce the so-called ’range anxiety’ of consumers as they significantly reduce the charging time. With the advent of wide band-gap (WBG) power devices and improvement in power electronic converters, medium voltage (MV) solid state transformer (SST) based XFC system has the potential to replace the traditional XFC stations because of the lower footprint, ease of installation, enhanced control feature, and better system efficiency. The control system design is one of the critical aspects of the SST development process. Careful consideration and detailed analysis are required to find out suitable control method for the SST based on its topology among different centralized and decentralized control architectures. Also, the control parameters selection and potential improvement to the transient response of the controller ought to be investigated. Another major concern of the SST is different types of internal fault which reduces the overall reliability of the XFC system. As a result, designing a robust protection system is essential. Among different fault modes, open circuit switch faults have received significant attention as an active research area because of their likelihood and severe effects on converters. Therefore, the power stages used in the XFC system require functional and accurate open circuit switch fault management methods. An equally significant aspect of this SST based XFC is its compatibility in a microgrid where there is no synchronous generator present. When the grid is not available, the XFC SSTs can provide grid forming capability and continue supplying the critical loads in islanded mode. The transition between grid connected and islanded mode, especially the grid resynchronization process has to be carefully performed for the safety of the microgrid components. The challenges posed by the aforementioned issues have inspired the work done in this dissertation. Here, a 13.2 kV, 1 MVA, AC/DC SST for the XFC system is examined and a comparative analysis is conducted to select the control architecture based on feasibility of implementation and performance. A detailed control parameter design process is demonstrated considering the sensor dynamics and delay. The selected decentralized control method is augmented by introducing a novel sensor-less load current feedforward method to provide better voltage regulation at the DC bus during a change of load. Next, in the fault management section, a hierarchical failure mode effect analysis (FMEA) is proposed to enable a systematic design of the internal fault protection of the XFC SST as there are limited examples in the literature regarding the analysis of the safety and design of the protection of a power electronic converter system. Novel open circuit switch fault management methods for the converters in the system are presented. Finally, XFC SST based MV microgrid operations in grid connected mode and islanded mode are explored. A secondary control method for grid resynchronization is presented and a design process of control parameters is shown to ensure the stability of the secondary voltage and frequency regulation.

30 DIRECT ENERGY CONVERSION↗

Guidelines for predicting stress in cemented doublets undergoing temperature change

This work explores quick predictive methods for calculating potentially risky stresses and deflections in cemented doublets experiencing temperature change that agree well with finite element analysis. There are three failure modes of interest: cohesive failure of the adhesive, delamination (surface bond failure or debonding), and glass fracture. Adhesive theory, confirmed by finite element analysis, predicts stress singularities that complicate interpretation of the stress calculations. The presence of a stress singularity indicates the breakdown of linear elastic assumptions, but damage initiation and stress singularities are related. The authors find that geometry details near a bond edge can exacerbate or minimize damage initiation and stress concentrations. Because the interpretation of the stress results is complicated, the authors investigated predicted stresses in doublets that have been successfully tested between -40 and 85 °C. This study found that the product (ΔT ∙ Δα) should be less than 189 ppm, where ΔT is the temperature excursion and Δα is the difference in glass coefficient of thermal expansion. If the product (ΔT ∙ Δα) is equal to or greater than 189 ppm, further analysis and testing is warranted. But the authors also show that the fabrication process can significantly influence stress failure, particularly with large diameter doublets.

47 OTHER INSTRUMENTATION↗

Guidelines for predicting stress in cemented doublets undergoing temperature change

This work explores quick predictive methods for calculating potentially risky stresses and deflections in cemented doublets experiencing temperature change that agree well with finite element analysis. There are three failure modes of interest: cohesive failure of the adhesive, delamination (surface bond failure or debonding), and glass fracture. Adhesive theory, confirmed by finite element analysis, predicts stress singularities that complicate interpretation of the stress calculations. The presence of a stress singularity indicates the breakdown of linear elastic assumptions, but damage initiation and stress singularities are related. The authors find that geometry details near a bond edge can exacerbate or minimize damage initiation and stress concentrations. Because the interpretation of the stress results is complicated, the authors investigated predicted stresses in doublets that have been successfully tested between -40 and 85 °C. This study found that the product (∆T ∙ ∆α) should be less than 189 ppm, where ∆T is the temperature excursion and ∆α is the difference in glass coefficient of thermal expansion. If the product (∆T ∙ ∆α) is equal to or greater than 189 ppm, further analysis and testing is warranted. But the authors also show that the fabrication process can significantly influence stress failure, particularly with large diameter doublets

42 ENGINEERING↗

Microscale mechanical modeling of deformable geomaterials with dynamic contacts based on the numerical manifold method

Abstract Micromechanical modeling of geomaterials is challenging because of the complex geometry of discontinuities and potentially large number of deformable material bodies that contact each other dynamically. In this study, we have developed a numerical approach for micromechanical analysis of deformable geomaterials with dynamic contacts. In our approach, we detect contacts among multiple blocks with arbitrary shapes, enforce different contact constraints for three different contact states of separated, bonded, and sliding, and iterate within each time step to ensure convergence of contact states. With these features, we are able to simulate the dynamic contact evolution at the microscale for realistic geomaterials having arbitrary shapes of grains and interfaces. We demonstrate the capability with several examples, including a rough fracture with different geometric surface asperity characteristics, settling of clay aggregates, compaction of a loosely packed sand, and failure of an intact marble sample. With our model, we are able to accurately analyze (1) large displacements and/or deformation, (2) the process of high stress accumulated at contact areas, (3) the failure of a mineral cemented rock samples under high stress, and (4) post-failure fragmentation. The analysis highlights the importance of accurately capturing (1) the sequential evolution of geomaterials responding to stress as motion, deformation, and high stress; (2) large geometric features outside the norms (such as large asperities and sharp corners) as such features can dominate the micromechanical behavior; and (3) different mechanical behavior between loosely packed and tightly packed granular systems.

58 GEOSCIENCES↗

2023 Risk Management Plan and Register for Low-Power WEC for Non-Grid Applications

This is an updated risk management plan and risk register for the design, build and test of a novel, remote, low-power wave energy converter (WEC) for non-grid applications. This Columbia Power Technologies project seeks to develop a prototype low-power WEC that lowers the total cost of ownership and provides robust, new capabilities for customers in the maritime environment. The testing location for this prototype is the U.S. Navy Wave Energy Test Site (WETS) in Kaneohe Bay, O'ahu, Hawai'i. Detailed in the Risk Management Plan document is a Failure Modes, Effects, and Criticality Analysis (FMEC) that systematically identifies all potential failure modes and their effects on the system. Risk registers for major subsystems were completed according to the methodology described in the Risk Management Plan and are also included here.

16 TIDAL AND WAVE POWER↗

Thermal Assessment and In-Situ Monitoring of Insulated Gate Bipolar Transistors in Power Electronic Modules: Preprint

Insulated gate bipolar transistor (IGBT) power modules are devices commonly used for switching of high voltages and currents. Usage and environmental conditions can cause these power modules to degrade over time, and this gradual process may eventually lead to catastrophic failure of the device. This degradation process may cause some early performance symptoms related to the state of health of the power module, making it possible to detect reliability degradation of the IGBT module. Testing can be used to accelerate this process, permitting a rapid determination of whether specific declines in device reliability can be characterized. In this study, thermal cycling was conducted on multiple power modules simultaneously in order to assess the effect of thermal cycling on the degradation of the power module. In-situ monitoring of temperature was performed from inside each power module using high temperature thermocouples. Device imaging and characterization was performed along with temperature data analysis, to assess failure modes and mechanisms within the power modules. While the experiment was aimed to assess the potential damage effects of thermal cycling on die attach, results indicated that wirebond degradation was the life limiting failure mechanism.

33 ADVANCED PROPULSION SYSTEMS↗