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Howell, Matthew

Publications and source records attributed to Howell, Matthew.

8 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Transient Optimization of the Cryogenic Moderator System Controller at the Spallation Neutron Source for Improved Performance

The high-energy neutron beam generated at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory is moderated to use cold (slow) neutrons for scientific discoveries. The Cryogenic Moderator System (CMS) removes heat from the neutron beam using cryogenic hydrogen (H 2 ) moderators connected via heat exchangers to a helium (He) refrigeration loop that dissipates heat using a compressor-brake system. However, the CMS is affected by sporadic losses in beam power, referred to as "beam trips," as these events generate significant disturbances in cooling requirements. To accommodate the heat load transients during beam trips, the CMS uses a decentralized control strategy consisting of four flow valves and one electric heater adjusted by independent proportional-integral (PI) controllers. During the CMS’s initial commissioning, the PI gains were calibrated based only on tracking performance, overlooking their effectiveness in disturbance rejection. A data-driven, control-oriented closed-loop model was developed to recalibrate the PI gains and minimize the transient disturbances caused by beam trips. The model consists of three main components: (1) a physics-based model of the He refrigeration loop, (2) a machine-learning model of the cryogenic H 2 cooling trains, and (3) the control logic used for feedback set-point tracking. Experimental results showed that the recalibrated gains obtained in this study improved the CMS’s transient response during beam trips.

Maldonado Puente, Bryan↗
DOE OSTI2024

Progress towards the completion of the proton power upgrade project

The Proton Power Upgrade project at the Spallation Neutron Source at Oak Ridge National Laboratory will increase the proton beam power capability from 1.4 to 2.8 MW. Upon completion in early 2025, 2 MW of beam power will be available for neutron production at the existing first target station (FTS) with the remaining beam power available for the future second target station (STS). The project has installed seven superconducting radio-frequency (RF) cryomodules and supporting RF power systems to increase the beam energy by 30% to 1.3 GeV, and the beam current will be increased by 50%. The injection and extraction region of the accumulator ring are being upgraded, and a new 2 MW mercury target has been developed along with supporting equipment for high-flow gas injection to mitigate cavitation and fatigue stress. The first four cryomodules and supporting systems were commissioned in 2022-2023 and supported neutron production at 1.05 GeV, 1.7 MW with high reliability. The first-article 2 MW target was operated successfully for approximately 4400 MW-Hours over two run periods. The long outage began in August 2023 for installation of the remaining technical equipment and construction of the Ring-to-Target Beam Transport tunnel stub that will enable connection to the STS without interrupting operation of the FTS. The upgrade is proceeding on-schedule and on-budget, and resumption of neutron production for the user program is planned for July 2024.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Progress towards the completion of the proton power upgrade project

The Proton Power Upgrade project at the Spallation Neutron Source at Oak Ridge National Laboratory will increase the proton beam power capability from 1.4 to 2.8 MW. Upon completion in early 2025, 2 MW of beam power will be available for neutron production at the existing first target station (FTS) with the remaining beam power available for the future second target station (STS). The project has installed seven superconducting radio-frequency (RF) cryomodules and supporting RF power systems to increase the beam energy by 30% to 1.3 GeV, and the beam current will be increased by 50%. The injection and extraction region of the accumulator ring are being upgraded, and a new 2 MW mercury target has been developed along with supporting equipment for high-flow gas injection to mitigate cavitation and fatigue stress. The first four cryomodules and supporting systems were commissioned in 2022-2023 and supported neutron production at 1.05 GeV, 1.7 MW with high reliability. The first-article 2 MW target was operated successfully for approximately 4400 MW-Hours over two run periods. The long outage began in August 2023 for installation of the remaining technical equipment and construction of the Ring-to-Target Beam Transport tunnel stub that will enable connection to the STS without interrupting operation of the FTS. The upgrade is proceeding on-schedule and on-budget, and resumption of neutron production for the user program is planned for July 2024.

Champion, Mark↗
DOE OSTI2023

Data-Driven Modeling of a High Capacity Cryogenic System for Control Optimization

The Cryogenic Moderator System (CMS) is responsible for maintaining a steady flow of cold neutrons for numerous physics experiments at the Spallation Neutron Source (SNS) in Oak Ridge National Laboratory (ORNL). Sudden losses in beam power, known as beam trips, cause a major disturbance to the CMS due to large step changes in cooling demands. Ongoing efforts on upgrading the neutron beam power from 1.4 to 2.0MW are expected to generate larger transients that can further strain the CMS subsystems if they are not properly controlled. To manage such disturbances, four flow valves and one electric heater are adjusted by five decentralized proportional-integral-derivative (PID) controllers. However, the original PID gains were calibrated empirically based only on tracking performance and not based on disturbance rejection. To address this issue without compromising current CMS operations, a control-oriented model was developed to recalibrate the PID controllers offline. The zero-dimensional (0-D) model was based on simple physics-based principles and data-driven system identification techniques. The CMS was broken into several subsystems for analysis, each of which corresponds to a parametric model tied to the thermodynamic states of the working fluid. The model parameters were identified using the nonlinear least squares method where the residuals were calculated from available sensor data. Simulation results show that the proposed model can capture the dynamics of the CMS at steady state and during beam trips.

Maldonado Puente, Bryan↗
DOE OSTI2023

Dynamic systems modeling of the spallation neutron source cryogenic moderator system to optimize transient control and prepare for power upgrades

Through support of the US Department of Energy's Office of Basic Energy Sciences, Oak Ridge National Laboratory has begun applying machine learning methods to improve accelerator and target performance of the Spallation Neutron Source (SNS). These methods are being applied to the control optimization and power upgrade of the SNS Cryogenic Moderator System (CMS). A numerical model of the CMS has been developed to study these optimizations and system modifications using EcosimPro. This paper compares steady-state and transient numerical results with experimental data. Control optimization studies focused on dampening mass flow, temperature, and pressure fluctuations during sudden losses of accelerator beam power. This analysis was conducted by adjusting five proportional-integral-derivative controllers connected to four flow control valves and one heater. Future efforts include power uprate studies focused on increasing the CMS cooling capacity. The current accelerator power is 1.4 MW; the first target station is being upgraded to 2.0 MW as part of the Proton Power Upgrade effort. The CMS cooling capacity is sufficient for 2.0 MW operation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

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↗
DOE OSTI2023

Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems

The high complexity and multiscale nature of many engineered systems—such as those in nuclear power plants—make representing and forecasting their dynamic behavior challenging. Physics-based models can be overly complex and computationally intractable, whereas machine learning (ML) tools are often data-hungry and prone to unphysical solutions. This study proposes a knowledge-informed ML-aided hybrid residual modeling approach that offers accurate and efficient time series forecasting for the operation of dynamical engineered systems. Hybrid residual modeling entails a baseline solution from domain knowledge and known physics expressions about the system dynamics integrated with an ML model to capture undiscovered information from the mismatch (i.e., residuals) between true states from measurements and baseline-predicted outputs. This study further quantifies the ML model uncertainty to provide trustworthy solutions. Real-time operational data from thermal-hydraulic flow loops of the cryogenic moderator system in Oak Ridge National Laboratory’s Spallation Neutron Source facility were used to demonstrate the potential of knowledge-informed uncertainty-aware ML in real-world applications. The state variables of the cryogenic helium loop were modeled with (1) first principles–based system identification (sysID), (2) long short-term memory (LSTM) neural network, and (3) hybrid sysID (baseline) + LSTM (residual). The superior predictive capability of the sysID+LSTM model versus stand-alone sysID and LSTM is confirmed by average performance metrics and individual data points across different prediction horizons. By creating a robust representation of the underlying physical system, the widely applicable hybrid residual modeling approach will enable the future development of digital twins for performance prediction, prognostics, and operation control.

Zhao, Xingang↗