Subhasish Mohanty

Effect of Pressurized Water Reactor Environment on Material Parameters of 316 Stainless Steel: A Cyclic Plasticity Based Evolutionary Material Modeling Approach

At present, the fatigue life of nuclear reactor components is estimated based on empirical approaches, such as stress/strain versus life (S∼N) curves and Coffin-Manson type empirical relations. In most cases, the S∼N curves are generated from uniaxial fatigue test data, which may not truly represent the multi-axial stress state at the component level. Also, the S∼N curves are based on the final life of the specimen, which may not accurately represent the mechanistic time-dependent evolution of material behavior. These discrepancies lead to large uncertainties in fatigue life estimations. We propose a modeling approach based on evolutionary cyclic plasticity that can be used for developing finite element models of nuclear reactor components subjected to multi-axial stress states. These models can be used for more accurately predicting the stress-strain evolution over time in reactor components and, in turn, fatigue life. The model parameters were estimated for 316 stainless steel material, which are widely used in U.S. nuclear reactors. The model parameters were estimated for different test conditions to understand their evolution over time and their sensitivity to particular test conditions, such as the pressurized water reactor coolant condition.Copyright

Status report on assessment of environmentally assisted fatigue for LWR extended service conditions

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Thermal-Mechanical Stress Analysis of PWR Pressure Vessel and Nozzles under Grid Load-Following Mode: Interim Report on the Effect of Cyclic Hardening Material Properties and Pre-existing Cracks on Stress Analysis Results

This report provides an update on an assessment of environmentally assisted fatigue for light water reactor components under extended service conditions. This report is a deliverable under the work package for environmentally assisted fatigue as part of DOE’s Light Water Reactor Sustainability Program. In a previous report (September 2015), we presented tensile and fatigue test data and related hardening material properties for 508 low-alloys steel base metal and other reactor metals. In this report, we present thermal-mechanical stress analysis of the reactor pressure vessel and its hot-leg and cold-leg nozzles based on estimated material properties. We also present results from thermal and thermal-mechanical stress analysis under reactor heat-up, cool-down, and grid load-following conditions. Analysis results are given with and without the presence of preexisting cracks in the reactor nozzles (axial or circumferential crack). In addition, results from validation stress analysis based on tensile and fatigue experiments are reported.

Tensile and Fatigue Testing and Material Hardening Model Development for 508 LAS Base Metal and 316 SS Similar Metal Weld under In-air and PWR Primary Loop Water Conditions

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Pressurized Water Reactor Environment Effect on 316 Stainless Steel Stress Hardening/Softening: An Experimental Study

In USA there are approximately 100 operating light water reactors (LWR) consisting fleet of both pressurized water reactors (PWR) and boiling water reactors (BWR). Most of these reactors were built before 1970 and the design lives of most of these reactors are 40 years. It is expected that by 2030, even those reactors that have received 20 year life extension license from the US nuclear regulatory commission (NRC) will begin to reach the end of their licensed periods of operation. For economical reason it is be beneficial to extend the license beyond 60 to perhaps 80 years that would enable existing plants to continue providing safe, clean and economic electricity without significant green house gas emissions. However, environmental fatigue is one of the major aging related issues for these reactors, and may create hurdles in long term sustainability of these reactors. To address some of the environmental fatigue related issues, Argonne National Laboratory (ANL) with the sponsorship of Department of Energy’s Light Water Reactor Sustainability (LWRS) program trying to develop mechanistic approach for more accurate life estimation of LWR components. In this context ANL conducted many fatigue experiments under different test and environment conditions on 316 stainless steel (316SS) material that is or similar grade steels are widely used in US reactors. Contrary to the conventional S∼N curve based empirical fatigue life estimation approach, the aim of the present DOE sponsored work is to understand material ageing more mechanistically (e.g. time dependent hardening and softening) under different test and environmental conditions. Better mechanistic understanding will help to develop computer based advanced modeling tools to better extrapolate stress-strain evolution of reactor component under multi-axial stress states and hence to help predicting their fatigue life more accurately. In this paper (part-I) the fatigue experiments under different test and environment conditions and related stress-strain results for 316 SS are discussed. In another paper (part-II) the related evolutionary cyclic plasticity material modeling techniques and results are discussed.Copyright

Fatigue damage prediction of cruciform specimen under biaxial loading

This article investigates an energy-based multiscale damage criterion for a biaxial loading case. The criterion incorporates crystal plasticity at the microscale that produces a damage tensor, representing the local damage state derived from a least squares method. The damage tensor, driven by modification of strain energy density on each potential slip system, is averaged from local to grain level to obtain a damage vector for each grain. The Kreisselmeier–Steinhauser function, which produces an envelope function for multiobjective optimization is adopted to predict the failure of a meso–representative volume element, and to calculate the damage index for meso–representative volume element. A weighted averaging method is also used to simultaneously provide the most potential cracking directions for meso–representative volume element. In order to verify that the developed method is capable of producing an acceptable prediction of fatigue damage initiation and growth under multiaxial loading conditions, a cruciform specimen is used for biaxial loading. A biaxial torsion MTS machine is used to conduct fatigue tests on the cruciform specimen. Numerical fatigue analysis is also performed based on the multiscale fatigue damage criterion. Comparing the simulation results with the experimental data shows that the multiscale fatigue damage model can provide acceptable prediction of failure of meso–representative volume element and crack direction.

Study the Cyclic Plasticity Behavior of 508 LAS under Constant, Variable and Grid-Load-Following Loading Cycles for Fatigue Evaluation of PWR Components

This report provides an update of an earlier assessment of environmentally assisted fatigue for components in light water reactors. This report is a deliverable in September 2016 under the work package for environmentally assisted fatigue under DOE’s Light Water Reactor Sustainability program. In an April 2016 report, we presented a detailed thermal-mechanical stress analysis model for simulating the stress-strain state of a reactor pressure vessel and its nozzles under grid-load-following conditions. In this report, we provide stress-controlled fatigue test data for 508 LAS base metal alloy under different loading amplitudes (constant, variable, and random grid-load-following) and environmental conditions (in air or pressurized water reactor coolant water at 300°C). Also presented is a cyclic plasticity-based analytical model that can simultaneously capture the amplitude and time dependency of the component behavior under fatigue loading. Results related to both amplitude-dependent and amplitude-independent parameters are presented. The validation results for the analytical/mechanistic model are discussed. This report provides guidance for estimating time-dependent, amplitude-independent parameters related to material behavior under different service conditions. The developed mechanistic models and the reported material parameters can be used to conduct more accurate fatigue and ratcheting evaluation of reactor components.

Online Stress Corrosion Crack Monitoring in Nuclear Reactor Components Using Active Ultrasonic Sensor Networks and Nonlinear System Identification: Data Fusion Based Big Data Analytics Approach

The current state of the art nondestructive evaluation (NDE) techniques used in nuclear reactor structural inspection are manual labor intensive, time consuming, and only used when the reactor has been shut down. Also, despite periodic inspection of plant components, a failure mode such as stress corrosion crack can initiate in between two scheduled inspections and can become critical before the next scheduled inspection. In this context, real time monitoring of nuclear reactor components is necessary for continuous and autonomous monitoring of component structural health. In this research, an active ultrasonic based on-line monitoring (OLM) framework is developed which can be used for real-time monitoring of degradation of nuclear power plant systems, structures, and components. Nonlinear system identification technique such as Bayesian Gaussian Process technique method is investigated to estimate the structural degradation in real-time. Active broadband ultrasound input is used for damage interrogation and a multi-sensor configuration is implemented to improve spatial resolution of state estimation. The damage index at any particular time is computed using nonlinear techniques such as Gaussian Process probabilistic modeling and the necessity of sensor data fusion is evaluated. The framework was demonstrated through the monitoring of an anomaly trend in a nuclear reactor steam generator tube undergoing stress corrosion cracking (SCC) testing.Copyright

A Bayesian-Probabilistic Framework for Real-Time Fatigue Usage Factor Monitoring of Nuclear Reactor Components

Real-time estimation of the fatigue usage factor of nuclear reactor components are helpful tools for on-demand assessment of component structural integrity. Real-time measurements of field variables, such as stress and strain, along with the use of historic/available stress/strain versus fatigue life data and a Bayesian-probabilistic framework can not only help to estimate the fatigue usage factor of reactor components in real time but also can help to estimate the associated confidence bounds. In this paper, a Gaussian Process based Bayesian-probabilistic framework is proposed for real-time estimation of mean fatigue usages factor and associated probabilistic bounds. The preliminary proof of concept was demonstrated through fatigue experiments with 316 stainless steel specimens under different conditions: a) under 300 °C and pressurized water reactor (PWR) water chemistry, and b) room temperature and in-air condition. At present the proposed probabilistic monitoring approach is not part of any code requirements, however the proposed framework is output of a futuristic basic research work, which requires more advancement. Also the results discussed in the paper are part of very preliminary basic research and requires advance validation such as under realistic nuclear reactor conditions.Copyright

Active sensing waveform design for estimating progressive fatigue damage in structures

We describe a stochastic ltering approach for tracking progressive fatigue damage in structures, wherein physically based damage evolution information is combined with active sensing guided wave measurements. The input waveform used to excite dispersive modes within the structure is adaptively con gured at each time step in order to maximize the damage estimation performance. The damage evolution model is based on Paris Law, and hidden Markov modeling of time-frequency features obtained from received signals is used to de ne the measurement model. Damage state estimation is performed using a particle lter. Results are presented for fatigue crack estimation in an aluminum specimen.