Search NASA⌕ Search

Engineering topics

Winder, Drew E.

Publications and source records attributed to Winder, Drew E..

Assessment of simulated and observed cavitation-induced erosion damage in Spallation Neutron Source target vessels

Cavitation-induced erosion damage in different Spallation Neutron Source (SNS) target designs are simulated using explicit finite element–based techniques and compared with observations of erosion in targets after operation. The efficacy of the previously developed method, called saturation time, was evaluated using erosion-damaged samples from new target designs. A new metric called maximum bubble size was implemented under the rationale that larger cavitation bubbles will collapse more intensely. The maximum cavitation bubble size over 1 ms of simulated time was calculated based on the Rayleigh–Plesset equation for each element integration point and presented as a contour map at the vessel surface for assessing with erosion observations. SNS targets are now operated with helium gas injection to reduce cavitation damage. A simulation method using a material model for the mixture of mercury and gas bubbles was recently developed and used to account for the effect of small gas bubbles on the structural response of the target vessel. Furthermore, this work compares the new method's results with observed cavitation damage. Maps of the calculated maximum bubble size for targets operated with and without gas injection were compared with photographs of erosion damage observed in SNS targets. The patterns in maximum bubble size maps correlated well with observations of erosion patterns in target vessels after service. Advantages and challenges of the maximum bubble size simulation technique are provided, and differences between results from the previous and the newly proposed metric are discussed.

Jiang, Hao↗

Calibration of the 2-Phase Bubble Tracking Model for Liquid Mercury Target Simulation with Machine Learning Surrogate Models

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory is one of the most powerful accelerator-driven neutron sources in the world. The intense protons strike on SNS's mercury target to provide bright neutron beams, which also leads to severe fluid-structure interactions inside the target. Prediction of resultant loading on the target is difficult particularly when helium gas is injected into mercury to reduce the loading and mitigate the pitting damage on vessel walls. A 2-phase material model that incorporates the Rayleigh-Plesset (R-P) model is expected to address this multi-physics problem. However, several uncertain parameters in the R-P model require intensive simulations to determine their optimal values. With the help of machine learning and the measured target strain, we have studied the major uncertain parameters in this R-P model and developed a framework to identify optimal parameters that significantly reduce the discrepancy between simulations and experimental strains. The preliminary results show the possibility of using this mercury/helium mixture and surrogate models to predict a better match of target strain response when the helium gas is injected.

Lin, Lianshan↗

Spallation Neutron Source Hydrogen Relief Analysis for the Cryogenic Moderator System

The Spallation Neutron Source at Oak Ridge National Laboratory operates the Cryogenic Moderator System (CMS) which provides hydrogen cooling at 20K to three neutron moderators. Each hydrogen loop is protected by multiple burst discs and reclosing relief valves. As a result of the Proton Power Upgrade project, the CMS moderator loops will hold more hydrogen and thus require piping modifications. Operational experience has demonstrated that transient pressure increases in these hydrogen loops occasionally result in the rupture of the burst discs. The causes for pressure transients in the system that might lead to hydrogen venting are varied and complex, for example loss of vacuum or cooling. Dynamic simulation and analysis of the parameters considered as the worst-case relief venting scenario were performed and will be presented.

47 OTHER INSTRUMENTATION↗

Benchmarking and Exploring Parameter Space of the 2-Phase Bubble Tracking Model for Liquid Mercury Target Simulation

High intensity proton pulses strike the Spallation Neutron Source (SNS)’s mercury target to provide bright neutron beams. These strikes deposit extensive energy into the mercury and its steel vessel. Prediction of the resultant loading on the target is difficult when helium gas is intentionally injected into the mercury to reduce the loading and to mitigate the pitting damage on the vessel. A 2-phase material model that incorporates the Rayleigh-Plesset (R-P) model is expected to address this complex multi-physics dynamics problem by including the bubble dynamics in the liquid mercury. We present a study comparing the measured target strains in the SNS target station with the simulation results of the solid mechanics simulation framework. We investigate a wide range of various physical model parameters, including the number of bubble families, bubble size distribution, viscosity, surface tension, etc. to understand their impact on simulation accuracy. Our initial findings reveal that using 8-10 bubble families in the model renders a simulation strain envelope that covers the experimental ones. Further optimization studies are planned to predict the strain response more accurately.

Lin, Lianshan↗

Model calibration of the liquid mercury spallation target using evolutionary neural networks and sparse polynomial expansions

The mercury constitutive model predicting the strain and stress in the target vessel plays a central role in improving the lifetime prediction and future target designs of the mercury targets at the Spallation Neutron Source. We leverage the experiment strain data collected over multiple years to improve the mercury constitutive model through a combination of large scale simulations of the target behavior and the use of machine learning tools for parameter estimation. We present two interdisciplinary approaches for surrogate-based model calibration of expensive simulations using evolutionary neural networks and sparse polynomial expansions. The newly calibrated simulations achieve 7% average improvement on the prediction accuracy and 8% reduction in mean absolute error compared to previously reported reference parameters, with some individual sensors experiencing up to 30% improvement. The calibrated simulations can aid in fatigue analysis to estimate the mercury target lifetime, which reduces abrupt failure and saves tremendous amount of costs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Upgraded fiber-optic sensor system for dynamic strain measurement in Spallation Neutron Source

We describe an upgraded fiber-optic sensor system and its performance in measuring the dynamic strains in a mercury target of the Spallation Neutron Source (SNS). Strains result from dynamic pressure waves in the stainless-steel mercury target induced by short (~700 ns), intense (up to 23.3 kJ), high-energy (~1 GeV) proton pulses. In the upgraded sensor system, the output of each sensor head is interrogated with a compact, all-fiber based Faraday Michelson interferometer, which generates interference signals with a steady phase shift. Strain waveforms are recovered from the phase-shifted interference signals using a high-speed digital signal processing procedure developed in our previous work. We demonstrate successful measurements of dynamic strain pulses, e.g., 400με over 190μs , on a recently installed SNS target using the upgraded sensor system. The measured strain waveforms are analyzed for more than 20 sensor locations and/or orientations, and provide information regarding the temporal structure of strain profiles and dependence of the strain magnitude on the proton powers of 200 – 1400 kW. The new interrogator also measures the radiation-induced-attenuation (RIA) in the optical fiber, enabling experimental investigations of RIA profiles induced by a 700-ns radiation pulse. The radiation effects on the strain measurement performance are discussed over a radiation dose range of up to 4×10 8 Gy and an RIA compensation method is proposed. The measurements allow insight into the response of this unique piece of equipment and can be used for validation of simulations.

47 OTHER INSTRUMENTATION↗

Sensitivity Analysis of Tunable Equation of State Material Model In Pulsed Mercury Target Simulation

A pulsed neutron spallation target is subjected to very short but intense loads from repeated proton pulses. Approximately 60% of the energy from each proton pulse is deposited into the mercury target material and the stainless-steel target structure, leading to a high-pressure region in both the stationary target structure and the flowing mercury. The high-pressure region propagates and leads to fluid-structure interaction. The resultant loading on the target structure containing liquid mercury is difficult to predict, although various simulation approaches and material models for the mercury have been tried. To date, the best match of simulation to experimental data is obtained by using an equation of state (EOS) material model with a specified tensile cutoff pressure, which simulates the cavitation threshold. The inclusion of a threshold to represent cavitation is key to the successful predictions of stress waves triggered by the high-energy pulse striking the mercury and vessel. However, recent measurements of target structure strain show that significant discrepancies remain between the measured and simulated strain values in the EOS mercury model. These differences grow when noncondensable helium gas is intentionally injected into the flowing mercury to reduce the loading on the structure. An EOS-based proportional–integral–derivative (PID) mercury model has been proposed to reduce the gap between the measured and simulated vessel strain responses for targets with gas injection. The conceptual and numerical description and initial investigation of the PID model are presented in previous work. Further studies of this PID model — including the sensitivity of the structure’s strain response to model parameters (the tensile cutoff, PID parameters Kp, Ki, and Kd) — are reported in this article. Results show the strain response is more sensitive to changes in the tensile cutoff value than to changes in the model parameters Kp, Ki, and Kd. These results will aid in future work where the model parameters will be optimized to match simulation data to strain measurements.

Lin, Lianshan↗