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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The effects of microstructures and radiation damage on the deformation behavior of a HT-9 alloy using microtensile testing

Understanding the influence of radiation damage on the mechanical properties of HT-9 and other tempered martensitic alloys is part of the mission in developing radiation-tolerant materials for the next generation of nuclear reactors. Although there has been extensive data on the macroscopic mechanical properties of the irradiated HT-9 alloys and microstructural changes, it is not well-understood how radiation damage and the resulting microstructural changes influence the local mechanical properties. In this study, we utilized in situ SEM microtensile testing to investigate the deformation behavior of specific martensitic boundaries in 1 dpa proton-irradiated HT-9 and answered the question of what is the weakest link. Additionally, we provided the direct observation of the failure modes of microtensiles containing high angle and low angle martensitic boundaries. In the unirradiated condition, the deformation is ductile and no martensitic boundary failure is observed. In the irradiated condition, the high angle martensitic boundaries are more susceptible to radiation-induced boundary failure as compared to the low angle martensitic boundaries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multicomponent gas mixture parametric CFD study of condensation heat transfer in small modular reactor system safety

Safety is always the primary concern for designing and analyzing nuclear reactor systems. The requirements for the safety margin for advanced small modular reactor (SMR) systems are targeted even higher than the conventional commercial large-scale nuclear reactors incorporating the passive and inherent safety systems. The SMR systems are designed with the condensation passive containment cooling system (PCCS), which plays a critical role in removing reactor heat during a steam release accident case. However, the presence of non-condensable gas (NCG), like air, reduces the heat transfer performance. This physics phenomenon becomes multifactorial for nuclear reactor containment during a fuel failure accident case that releases hydrogen gas. Besides, the mixture component of steam-air-hydrogen varies in reactor accident cases, which need simulation and validation keeping parameters of importance. Reviews showed that previous studies for SMR’s PCCCS did not cover the condensation heat transfer (CHT) in the presence of multicomponent NCG mixture parametric computational fluid dynamics (CFD) simulation and validation, making a research gap in the SMR design safety. A comprehensive CHT parametric CFD study was performed for SMR PCCS to fill this research gap. This study used experimental data as simulation 3D physics domain inlet and outlet boundary conditions. However, the wall boundary conditions were constant temperature, curve-fit, and annular coolant for verifying the turbulence models. Parametric simulations were performed, verified, and optimized for steam-NCGs mixtures. The multicomponent gases, multiphase mixtures, and fluid film condensation models were applied with associated turbulence models. The results of the parametric study were evaluated for realistic reactor conditions. Results showed that parametric study provided critical insight about the dependency of multicomponent gas mixture parameters that supports reactor safety design, analysis, and licensing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Relating Measured Component Damage to Assessed Component Reliability in Reliability Integrity Management (RIM)

There is currently no widely agreed detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. It may be possible to develop an approach to licensing such a plant that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev.0, endorses, with conditions, the subject portion of the ASME Code. But that portion of the ASME code is written at a very high level, and there are fundamental technical challenges associated with applying it literally to licensing a real plant. In the RIM approach, applicants need to do the following (among other things): • Allocate target reliabilities to structures, systems, and components (SSCs) that collectively support the top-level plant safety and availability objectives; • Understand failure modes of those SSCs, and the degradation mechanisms that could lead to those failure modes; • Develop and propose a program of surveillances that will identify degradation prior to failure of SSCs; • Provide a means of reporting results, taking actions for anomalous or undesirable conditions, and give the regulator assurance of continued safe operations. Applying RIM in a specific case will call for advances in the state of practice of relating physical observables to functional reliability of certain component types. Except where a given level of damage corresponds to a failed (or nearly failed) state, it is not practical to establish a precise quantitative relationship between physical observables and reliability. This paper focuses on managing risk of passive component failures based on observable damage parameters. A simple approach to cumulative damage modeling will be illustrated with a view to possible use in RIM applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A continuum damage approach to spallation and the role of microinertia

Spall failure is of interest due to its prevalence in high strain rate problems in which the spallation is driven by the interaction of release waves. In this article, a porosity-based damage model that includes microinertial effects is used to examine spall failure. The model is successfully calibrated to plate impact-driven experiments and then used to evaluate experimental conditions producing more extreme strain rate conditions, such as those in laser-driven experiments. The incorporation of microinertia allows us to better understand the increase in apparent macroscopic spall strength seen at high strain rates. Correspondingly, we conclude that the incorporation of microinertial effects improves the model’s predictive capabilities. Microinertial effects result in more severe local tensile stresses that affect the damage evolution, and microinertia can play a significant role in the approach to the material’s ideal strength at extreme loading rates. Additionally, a preliminary parametric study is also carried out to investigate the role of microstructural aspects such as nucleation volume fraction and initial pore radius. One counter-intuitive result from the microinertial effects is that, for a given nucleation site volume fraction, having larger initial pore nucleation sites can lead to an improved macroscopic spall strength.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Decision-making based on Markov decision process in integrated artificial reasoning framework—Part I: Theory

This paper presents a decision-making framework based on an integrated artificial reasoning framework and Markov decision process (MDP). The integrated artificial reasoning framework provides a physics-based approach that converts system information into state transition models, and the analysis result will be represented by the transition probabilities that can be used with an MDP to find a traceable and explainable optimal pathway. A dynamic Bayesian network (DBN) is well suited for representing the structure of an MDP. The causality information among process variables (or among subsystems) is mathematically represented in a DBN by the conditional probabilities of the node’s states provided different probabilities of the parent node’s states. To define node states in a physically understandable manner, we used multilevel flow modeling (MFM). An MFM follows the fundamental energy and mass conservation laws and supports the selection of process variables that represent the system of interest so that causal relations among process variables are properly captured. An MFM-based DBN supports developing state transition models in an MDP to capture the effect of process variables of system having physical relations. The operators of the target system can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from component degradation or random failures. We analyzed a simplified exemplary system to illustrate an optimal operational policy using the suggested approach.

Markov decision process↗
DOE OSTI2023

Probabilistic Multi-Hazard Performance Assessment of Concrete Structures in Nuclear Installations

Concrete structures in nuclear installations are subject to time-dependent degradation mechanisms that can deteriorate their physical and mechanical properties, potentially exacerbating the risk of structural failure under external forces such as a seismic event. Previous research has extensively investigated the seismic response of nuclear concrete structures and the associated risk, as well as their effect on structural components safety margins. However, substantial work is still necessary to incorporate concrete aging effects into such evaluations. In fact, most models in the literature assume pristine concrete conditions and do not account for the impact of aging on the structural components’ fragility curves. This work identifies relevant time-dependent degradation mechanisms and provides simplified models to predict the the evolution of key material properties based on data from the literature. Namely, this work focuses on the aging effects of corrosion, alkali–silica reaction (ASR), and irradiation on reinforced concrete within US Department of Energy (DOE) nuclear facilities and nuclear power plants (NPP) structures. Furthermore, degradation models based on literature data are presented that define the relationship between probabilistic material properties and the concrete’s age. In this work, sampled material properties served as input for a simplified finite element model (FEM) of a critical nuclear structural system, with the output of the FEM being the seismic response for a given ground motion. The results of the FEM were then used within a probabilistic performance assessment with a statistically significant number of samples. The research presented herein addresses the detrimental effects of hazards caused by natural phenomena on deteriorated concrete elements of nuclear installations. This work directly benefits the safety analysis performed on US DOE/ National Nuclear Security Administration (NNSA) nuclear facilities located in areas prone to seismic activity. The results presented herein could aid in the improvement of DOE-STD-1020, the DOE Standard that addresses seismic risk analysis and capacity evaluation in DOE facilities. DOE-STD-1020 refers to the requirements in American Society of Civil Engineers (ASCE) 4-98, now superseded by ASCE 4-16, that shall be met in performing dynamic response analyses and generating in-structure response spectra, provided that such requirements are consistent with the requirements of ASCE/Structural Engineering Institute (SEI) 43-05. Moreover, the results presented herein could also aid in the updating of section C3.1.1. of ASCE 4-16 to account for the effects of aging on the stiffness of reinforced elements and American Concrete Institute (ACI) 349.3R-18, “Report on Evaluation and Repair of Existing Nuclear Safety-Related Concrete Structures.” Ultimately, this work can assist the risk assessment of potential lifetime extension of the existing US commercial nuclear fleet (light water reactors) and the safety analysis of the emerging advanced nuclear reactors. The proposed proof-of-concept methodology employs open-source DOE computational tools and is transferable to commercial software commonly used by engineering firms.

42 ENGINEERING↗
DOE OSTI2020

Comparison between PARFUME and Bison Using the AGR-2 Irradiation Experiment

This report documents comparisons between Fuel Model (PARFUME) model predictions versus Bison for selected compacts from the second irradiation test of the Advanced Gas Reactor (AGR) program that occurred from June 2010 to October 2013 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). PARFUME is a fuel performance analysis and modeling code, used for evaluating gas-reactor tristructural isotropic (TRISO) coated particle fuel for prismatic, pebble bed, plate, and cylindrical type fuel geometries. PARFUME is an integrated mechanistic computer code that evaluates the thermal, mechanical, and physico-chemical behavior of TRISO coated-fuel particles and the probability for fuel failure given the particle-to-particle statistical variations in physical dimensions and material properties that arise during the fuel fabrication process. Bison is a nuclear fuel performance application built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library (Permann 2020). Bison is capable of modeling multiple fuel forms in a wide variety of dimensions and geometries. It solves coupled nonlinear partial differential equations, including heat conduction, mechanics, fission product species transport etc., in a fully implicit manner. Comparisons between PARFUME and Bison were performed using four compacts from the AGR-2 experiment. Selected outputs were chosen based on their impact on the probability of the SiC layer failing. In general there was good agreement between PARFUME and Bison with the exception of predicting the gap formed between the buffer and IPyC. Further comparisons between PARFUME and Bison are planned to further develop Bison’s capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

ACCELERATED DEPLOYMENT OF NOVEL MATERIALS BASED ON RELIABILITY INTEGRITY MANAGEMENT USING CUMULATIVE DAMAGE MODELING

There is currently no widely agreed, detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. This paper discusses a framework for solving this problem that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev. 0, endorses, with conditions, the subject portion of the 2019 ASME Code. The proposed framework is meant to support development of a licensing case by addressing certain remaining technical challenges. The framework discussed here is compatible with the Licensing Modernization Project, but applying it in a specific case will call for advances in the state of practice, if not the state of the art. The RIM approach calls for applicants to (a) allocate reliability targets to plant structures, systems, and components (SSCs), (b) show that they are able to relate the currently observed physical condition of each SSC in the program to its failure probability well enough to determine whether the target reliability allocations are being satisfied, allowing for uncertainty related to the novelty of the materials/designs/operating environments, and (c) be able to demonstrate that the proposed program of surveillances will reliably detect unacceptable degradation of an SSC before SSC failure occurs. A modeling approach potentially applicable to item (b), based on cumulative damage modeling rather than failure rates, is briefly illustrated.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Energetic Materials

Energetic materials comprise explosives, pyrotechnics, and propellants. The science of energetic materials is dedicated to developing a means to predict performance and safety characteristics with high fidelity. This is a particular challenge and is predicated on materials science and engineering, physics, chemistry, and dynamic response in extreme conditions. Fundamental elements of these complicated composite materials remain grand challenges—from the design of high-energy metastable molecules, to the engineering of composite formulations, to the processing parameters that link to safety and performance characteristics in as-yet undetermined ways. Key elements include crystalline mechanics, grain dynamics, multiphase interfaces, thermal and mechanical damage, and failure—all linked to multistep and high-rate chemistry and shock physics. A future revolution in our understanding and predictive capability for energetic materials behavior and responses is dependent upon sustained focus and advances in materials research and development.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Moving from Information Assurance to Functional Assurance with Engineered Controls

Cyber threats to operational technology demand more than traditional IT defenses—they require full-spectrum mission assurance. Cyber-Informed Engineering (CIE) is an approach that embeds engineered controls into system design to ensure critical functions remain safe and reliable, even under attack. Unlike conventional cybersecurity tools, engineered controls act directly on physical processes to prevent unacceptable outcomes such as equipment damage or mission failure. This session will outline the CIE framework and share examples of consequence-based design that deliver true resilience, not just fail-safe behaviors. Attendees will learn how to integrate these principles into the engineering lifecycle to support resilient-by-design architectures and inform emerging standards. This talk sets the stage for the panel discussion on advancing CIE across sectors as digital and physical systems converge.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Physics-informed neural networks for identification of material properties using standing waves

A metallic structure in its initial stage of failure involves plastic deformation or environmental degradation that changes the elastic modulus and density. This work presents the detection of change in wave velocity (a function of elastic modulus and density) as a system identification problem. A physics-informed neural network (PINN) is proposed to solve the system identification problem. The PINN takes the spatial coordinates of scanning locations and time as inputs and provides the displacement and wave velocity as outputs. The governing partial differential equation of standing waves in a rod is incorporated into the neural network as physics in the form of a loss function. The wave velocity vector is randomly initiated. During the training of the network, physics is used to determine and update the wave velocity target vector from the network’s displacement predictions. The measured data, comprising sparse displacement response on the rod structure, are used to train the PINN. The wave velocity at the sparse locations on the rod is learned from the predicted displacements during the training. Using the predictions of the trained network, the response of free vibration or material property variation can be reconstructed at unscanned locations on the structure to obtain high-resolution maps for full-field imaging to detect and localize the changes caused by plastic deformation. The PINN’s sparse scanning and simultaneous prediction capability during training can lead to high scanning and data-processing speeds. This capability yields a nondestructive evaluation system that can predict the presence of degraded material locations as the structural vibrations are scanned and processed in real time.

Rathod, Vivek↗
DOE OSTI2023

Faster-than-real-time Simulation with Demonstration for Resilient DER Integration

The US electric grid is facing operational, stability, and security challenges. Transmission system operators need some measure of visibility into distribution system renewable generation. Distribution system generation needs to support transmission system voltage. The grid is experiencing an expansion in measurement systems. How to take full advantage of this expansion and defend against attacks, both cyber and physical, poses additional challenges. The Faster-than-real-time Simulation with demonstration for Resilient DER Integration project set out to do the following: a. Flatten the voltage profile through the feeders and system for cost saving and voltage stabilization needs. b. Increase the amount of intermittent distributed energy resources (IDERs) that could be deployed on a utility feeder and provide 100% or more energy needed for the demands on that feeder, and c. based on an accurate model (Digital Twin) of the utilities system, be able to detect any abnormalities on the utilities distribution system. To manage the voltage and increase IDER penetration (a,b), Graph Trace Analysis is employed in a time-series, optimal power flow to coordinate the time-varying feedback control setpoints of a distribution feeder’s utility control devices. Under the coordinated control are a Load Tap Changing Transformer, a voltage regulator, and five switched capacitor banks. The feeder serves over 2000 customers, the feeder secondaries are modeled, and the feeder has 2.3 MW of PV generation, corresponding to a 17.4% penetration of PV generation. The feeder model has over 12,000 components, where every customer load bus and PV generator are modeled. The accuracy of the power flow solution is compared against historical meter voltage measurements, the improvement in conservation voltage reduction energy savings as a function of the coordinated control desired voltage profile is investigated, and the increase in PV penetration of the coordinated control over the existing control is presented. To achieve improved control performance while observing system operation constraints, bellwether Advanced Metering Infrastructure (AMI) voltage measurements are used to adjust the desired voltage profile used by the optimal power flow analysis. To detect and alleviate or negate attacks or failures on the distribution and transmission utility grids (c) the grid needs to be resilient and self-healing. In this project software was designed to do just that. At the center of the software is an Integrated System Model (ISM) that spans from transmission to secondary distribution. The ISM is employed in real-time abnormality detection, voltage stability forecasting, and multi-mode control. Testing results are presented for: 1—attacks on utility infrastructure; 2—energy savings from optimal control; 3—distribution system control response during a low voltage transmission system event; 4—cyber-attacks on PV inverters, where physical inverters are used in hard-ware-in-the-simulation-loop studies. Contributions of this work include real-time analysis that spans from three-phase transmission through secondary distribution; an approach for detecting abnormalities that employs measurements from three independent measurement systems; and a multi-mode distribution system control that responds to cyber-attacks, physical attacks, equipment failures, and transmission system needs.

Integrated System Model, Graph Trace Analysis, Adv↗
DOE OSTI2022

Characterization of the Insoluble Solids of the 241-17F and 241-49H Pump house Water Sample

Six different water samples from 241-17F and 241-49H pump house were analyzed for chemical and physical characteristics as part of efforts to understand recent mechanical seal failures associated with four new cooling water pumps. A focus of this work was characterization of any “as found” insoluble solids. The insoluble material found in the FCRW (F-Area caustic water treated with sodium chromate at 241-17F) sample are mostly magnetite (Fe3O4 or possibly equipment rust) and silica. It was found that 26% of measured FCRW particles have at least one dimension larger than 15 microns. The insoluble particles found in the source water, domestic water (FDW), are mostly kaolin (aluminosilicate) and some iron oxide. All found FDW particles were larger than 15 microns. The insoluble particles of the other source water, FArea well water (FWW), were mostly iron oxide with some trapped cations like calcium. Only 8% of found FWW particles were bigger than 15 microns.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Wind Turbine Drivetrain Reliability Research - Gearbox Bearing Axial Cracking Failure Mode Example

The U.S. Department of Energy's National Renewable Energy Laboratory and Argonne National Laboratory have been conducting wind turbine drivetrain (formerly gearbox) reliability research for many years. Although the drivetrain focus has not changed, detailed projects are adjusted every few years based on dynamic needs seen in the field across the wind industry. This webinar will walk through the research methodology by using wind turbine gearbox bearing axial cracking failure mode as an example. The detailed steps include: 1) top failure mode identification based on actual failure data collected from project partners, 2) bench-top testing to identify possible contributing factors and formulate a damage metric, 3) physics domain modeling and validation through testing, 4) reliability assessment and prognosis based on the physics domain model and data domain inputs, and further enhancement through machine learning algorithms, using actual wind plant operational and failure event data. Hopefully, the presented work is of interest to the IISE community, and some members can apply their expertise to wind turbine and plant applications, helping enhance wind power generation technology advancement and its broader deployment.

axial cracking↗
DOE OSTI2023

Cyber-Informed Engineering Principles: What’s in it for me?

CIE is an emerging method to integrate cybersecurity considerations into the conception, design, development, and operation of any physical system that has digital connectivity, monitoring, or control. CIE complements—but does not replace—the application of cybersecurity standards or practices currently in place within an organization. Rather, it expands cybersecurity decisions into the engineering space, not by asking engineers to become cyber experts, but by calling on engineers to apply engineering tools and make engineering decisions that improve cybersecurity outcomes. CIE examines the engineering consequences that a sophisticated cyber attacker could achieve, and drives engineering changes that may provide deterministic mitigations to limit or eliminate those consequences. Engineers and technicians that design critical energy infrastructure installations can integrate the 12 principles of CIE into each phase of the engineering lifecycle, from concept to retirement. These principles are aimed at system or design engineers, operators, and technicians, rather than software engineers or operational cybersecurity practitioners, because the engineers who design, build, operate, and maintain the physical infrastructure are best positioned to leverage a system’s engineering design to diminish the severity of cyber attacks or digital technology failures. This approach creates new opportunities for engineering teams—and not just cybersecurity teams—to secure the system using the physics and mechanics of engineering controls—not just digital monitoring and controls.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Distribution of blackouts in the power grid and the Motter and Lai model

Carreras, Dobson, and colleagues have studied empirical data on the sizes of the blackouts in real grids and modeled them with computer simulations using the direct current approximation. They have found that the resulting blackout sizes are distributed as a power law and suggested that this is because the grids are driven to the self-organized critical state. In contrast, more recent studies found that the distribution of cascades is bimodal resulting in either a very small blackout or a very large blackout, engulfing a finite fraction of the system. Here we reconcile the two approaches and investigate how the distribution of the blackouts changes with model parameters, including the tolerance criteria and the dynamic rules of failure of the overloaded lines during the cascade. Finally, we study the same problem for the Motter and Lai model and find similar results, suggesting that the physical laws of flow on the network are not as important as network topology, overload conditions, and dynamic rules of failure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Resilient high-temperature reverse osmosis desalination membranes

Conventional thin-film composite (TFC) reverse osmosis (RO) membranes experience irreversible performance loss at high temperatures, restricting their use in industries with high-temperature streams, including oil and gas, pharmaceuticals, electronics, power generation, food production, and hybrid desalination plants. However, the mechanisms driving the performance decline of TFC membranes at high temperatures remain poorly understood. Herein, we combine controlled experiments, molecular dynamics simulations, and micromechanical modeling to elucidate TFC failure mechanisms and to evaluate thermally resilient thin-film cross-linked (TFX) composite membrane. Upon exposure to elevated temperatures (>60°C), salt rejection of TFC dropped from ~99 to <90%, with irreversible structural damage in the polysulfone layer, confirmed by scanning electron microscopy. In contrast, the TFX membrane maintained ~99% salt rejection and showed no signs of physical degradation up to 80°C. Our combined analyses revealed that TFC membrane failure arises from irreversible pore expansion in the thermoplastic polysulfone support, leading to polyamide film rupture and delamination. TFX membranes resist thermal deformation, enabling ultrahigh-temperature RO desalination and water reuse.

Wu, Jishan [Rice Univ., Houston, TX (United States↗
DOE OSTI2020

Surge-Energy and Overvoltage Ruggedness of P-Gate GaN HEMTs

An essential ruggedness of power devices is the capability of safely withstanding the surge energy. The surge ruggedness of the GaN high-electron-mobility transistor (HEMT), a power transistor with no or minimal avalanche capability, has not been fully understood. This article unveils the comprehensive physics associated with the surge-energy withstand process and the failure mechanisms of p-gate GaN HEMTs. Two commercial p-gate GaN HEMTs with Ohmic- and Schottky-type gate contacts are studied. Two circuits are developed to study the device surge ruggedness: an unclamped inductive switching circuit is first used to identify the withstand dynamics and failure mechanisms, and a clamped inductive switching circuit with a controllable parasitic inductance is then designed to mimic the surge energy in converter-like switching events. The p-gate GaN HEMT is found to withstand the surge energy through a resonant energy transfer between the device capacitance and the load/parasitic inductance rather than a resistive energy dissipation as occurred in the avalanche. If the device resonant voltage goes below zero, the device reversely turns on and the inductor is discharged. The device failure occurs at the transient of peak resonant voltage and is limited by the device overvoltage capability rather than the surge energy, dV/dt , or overvoltage duration. Almost no energy is dissipated in the resonant withstand process and the device failure is dominated by an electric field rather than a thermal runaway. Furthermore, these results provide critical understandings on the ruggedness of GaN HEMTs and important references for their qualifications and applications.

42 ENGINEERING↗