Results for “Condition monitoring” — Page 16

DOE OSTI2021

RCT Continuing Training Presentation Transcript (Q3, 2021)

Radiological Control Technicians (RCTs) serve an important part in the mission of Los Alamos National Laboratory by monitoring the diverse radiological conditions at the Lab. This role is critical in maintaining personnel safety from radiological hazards, and in keeping occupational radiation exposure As Low As Reasonably Achievable (ALARA). This training presentation will review performing job coverage and all of the necessary steps associated with it.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2022

Gaussian process for calibration and control of GlueX Central Drift Chamber

We have developed and implemented a machine learning based system to calibrate and control the GlueX Central Drift Chamber at Jefferson Lab, VA, in near real-time. The system monitors environmental and experimental conditions during data taking and uses those as inputs to a Gaussian process (GP) with learned prior. The GP predicts calibration constants in order to recommend a high voltage (HV) setting for the detector that maintains consistent detector performance (gain and resolution) throughout data taking. This approach is in stark contrast to traditional detector operations in which the detector operates at fixed HV and its calibration parameters vary quite considerably with time. Additionally, the ML based system utilizes uncertainty quantification to correct the recommended control parameters when appropriate. We will present results from the ML system autonomously during the Charged Pion Polarizability (CPP) experiment conducted in Hall D at Jefferson Lab.

McSpadden, Helen↗

DOE OSTI2024

Ensemble Manufacturing Techniques for Steam Turbine Components Across Length Scales

Faster design to manufacturing requirements were sought for steam turbine components to meet the changing demands of today’s power grid of improved efficiency through operating temperature increases and enhanced operational flexibility from baseload to cyclic operations. Advances in multiple advanced manufacturing (AM) process enabled redesign of turbine components for extreme environments with the potential to reduce cost. AM is of particular interest to improve component functionality, higher temperature capability, and superior durability in large scale steam turbine applications. AM methods have an immense potential to open-up the design space by working directly with the 3D model to produce near-net shapes, enable fast design-manufacturing iterations, thereby significantly reducing product cost and lead-time up to 25 % from current baseline. However, these benefits cannot be fully realized due to the potential for unknown AM processing defects and their resultant effect upon component performance in service. Siemens is partnering with Oak Ridge National Laboratory (ORNL), Electric Power Research Institute (EPRI), and Connecticut Center for Advanced Technology (CCAT) to advance the knowledge of complex process-material interactions for desired microstructures and properties that are closely interlinked to component geometries across different length scales. The proposed program utilized an ensemble of multidisciplinary technologies to accelerate the development of materials, high-throughput experiments for their qualification, and design flexibility/topology optimization for repair/redesign of components to address critical failure mechanisms for improved performance and increased reliability of existing power plant components. The proposed activities, if successfully demonstrated for identified components, will enable paradigm shift in customized manufacturing and accelerated qualification/certification towards increased steam turbine component durability, increased turbine efficiency, and reduced CO 2 emissions in load-following environments compared to today’s technology. Technology maturation is built into the project as successful research will include customized process-component down-selection enabling AM methodologies to be incorporated directly into the existing supply chain. The specific activities of the proposed effort are: 1. Topology optimization of down-selected steam turbine parts that are amenable to additive and hybrid manufacturing for cost/performance improvement. 2. Process-structure-property relationships for five AM processes for steam turbine materials of interest to compare with conventional materials. 3. Perform part/assembly build process using advanced additive/hybrid machine tools followed by quality inspection of the built components for insight into qualification for production scale-up. Steam turbine rig testing of printed components under targeted, well monitored and characterized environmental conditions of for performance comparison of baseline and redesigned components.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 5: Utah FORGE Well 16B(78)-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 4: Utah FORGE Well 78B-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 3: Utah FORGE Well 56-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 1: Summary of Utah FORGE Wells 16A(78)-32, 56-32, 78B-32 and 16B(78)-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

DOE OSTI2022

Hanford Site Bee Nest Box Monitoring Report for Calendar Year 2021

This report summarizes the results of the third year of monitoring bee nest boxes on the Hanford Site. Twenty bee nest boxes were installed as a component of compensatory mitigation for the installation of the L-894 water line between the 200-East and 200-West Areas of the Hanford Site in July 2019. The goal of this compensatory mitigation is to replace lost nesting habitat for above-ground nesting bees in a mature sagebrush ecosystem. Annual monitoring will track the condition and occupation of the bee nest boxes to determine if the compensatory mitigation was successful and to identify best practices when replacing nesting habitat for native bees.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Hanford Site Bee Nest Box Monitoring Report for Calendar Year 2020

This report summarizes the results of the second year of monitoring bee nest boxes on the Hanford Site. Twenty bee nest boxes were installed as a component of compensatory mitigation for the installation of the L-894 water line between the 200-East and 200-West Areas of the Hanford Site in July 2019. The goal of this compensatory mitigation is to replace lost nesting habitat for above-ground nesting bees in a mature sagebrush ecosystem. Annual monitoring will track the condition and occupation of the bee nest boxes to determine if the compensatory mitigation was successful and to identify best practices when replacing nesting habitat for native bees.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Hanford Site Bee Nest Box Monitoring Report for Calendar Year 2019

This report summarizes the results of the first year of monitoring bee nest boxes on the Hanford Site. Twenty bee nest boxes were installed as a component of compensatory mitigation for the installation of the L-894 water line between the 200-East and 200-West Areas of the Hanford Site. The goal of this compensatory mitigation is to replace lost nesting habitat for above-ground nesting bees in a mature sagebrush ecosystem. Annual monitoring will track the condition and occupation of the bee nest boxes to determine if the compensatory mitigation was successful and to identify best practices when replacing nesting habitat for native bees.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

East Tennessee Technology Park 2006 Illness and Injury Surveillance Report

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Long-Term Stability of Nicotinamide Cofactors in Common Aqueous Buffers: Implications for Cell-Free Biocatalysis

The use of nicotinamide cofactors in cell-free biocatalytic systems is necessitated by the high specificity that these enzymes show for their natural redox mediators. Unfortunately, isolation and use of natural cofactors is costly, which suggests that enhancing their stability is key to enabling their use in industrial processes. This study details NAD+ and NADH stability in three buffer systems (sodium phosphate, HEPES, and Tris) at 19 °C and 25 °C and for up to 43 d. In Tris, both NADH and NAD+ were found to be highly stable. NADH degradation rates of 4 μM/d (19 °C) and 11 μM/d (25 °C) were observed in Tris buffer, corresponding to >90% and 75% remaining after 43 d, respectively. Higher degradation rates (up to 34 μM/d) were observed when sodium phosphate or HEPES buffers were used. The effect of a mild increase in temperature was determined to be significant for long-term stability, and it was shown that degradation under these conditions can be easily monitored via UV–Vis, because the degradation proceeds via the oxidation/de-aromatization of the dihydropyridine ring. Overall, this work emphasizes that the choice of buffer system is consequential for bioreactor systems employing natural nicotinamide cofactors for extended periods of time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

The Event Detection System in the NEXT-White Detector

This article describes the event detection system of the NEXT-White detector, a 5 kg high pressure xenon TPC with electroluminescent amplification, located in the Laboratorio Subterráneo de Canfranc (LSC), Spain. The detector is based on a plane of photomultipliers (PMTs) for energy measurements and a silicon photomultiplier (SiPM) tracking plane for offline topological event filtering. The event detection system, based on the SRS-ATCA data acquisition system developed in the framework of the CERN RD51 collaboration, has been designed to detect multiple events based on online PMT signal energy measurements and a coincidence-detection algorithm. Implemented on FPGA, the system has been successfully running and evolving during NEXT-White operation. The event detection system brings some relevant and new functionalities in the field. A distributed double event processor has been implemented to detect simultaneously two different types of events thus allowing simultaneous calibration and physics runs. This special feature provides constant monitoring of the detector conditions, being especially relevant to the lifetime and geometrical map computations which are needed to correct high-energy physics events. Other features, like primary scintillation event rejection, or a double buffer associated with the type of event being searched, help reduce the unnecessary data throughput thus minimizing dead time and improving trigger efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Gaussian process for calibration and control of GlueX Central Drift Chamber

We have developed and implemented a machine learning based system to calibrate and control the GlueX Central Drift Chamber at Jefferson Lab, VA, in near real-time. The system monitors environmental and experimental conditions during data taking and uses those as inputs to a Gaussian process (GP) with learned prior. The GP predicts calibration constants in order to recommend a high voltage (HV) setting for the detector that maintains consistent detector performance (gain and resolution) throughout data taking. This approach is in stark contrast to traditional detector operations in which the detector operates at fixed HV and its calibration parameters vary quite considerably with time. Additionally, the ML based system utilizes uncertainty quantification to correct the recommended control parameters when appropriate. We will present results from the ML system autonomously during the Charged Pion Polarizability (CPP) experiment conducted in Hall D at Jefferson Lab.

McSpadden, Helen↗

DOE OSTI2024

Adaptive Narrowband Damping for Improving Harmonic Stability of Modular Multilevel Converter: Preprint

Harmonic instability events between modular multilevel converter (MMC) and ac systems have been widely reported in recent years. To resolve it, this paper proposes an adaptive narrowband damping control that automatically programs, adds and adjusts damping around the oscillation frequency when detect the oscillation. The paper first presents a low-pass filter design for MMC control loops, which pushes all negative damping of MMC impedance down to the medium frequency range (< approximately 1000 Hz). This makes narrowband damping can be more targeted and easier to design because multiple harmonic oscillations are avoided. An adaptive damping control that uses online oscillation detection is then proposed, which can automatically configure the narrowband damper to provide damping to the MMC at the detected oscillation frequency. In contrast to existing narrowband damping methods, the proposed adaptive narrowband damper adjusts the damping gain (e.g., to zero when system resonance disappears) and the width of the damping range automatically based on continuous monitoring of system resonance conditions. Electromagnetic transient (EMT) simulation results validate the efficacy of the proposed method in two typical MMC-based power systems.

active damping↗

DOE OSTI2020

Monthly Sewer Monitoring Report for LLNL Livermore Site, April 2020

Lawrence Livermore National Laboratory (LLNL) collects effluent samples from its sewer outfall at the B196 Sewer Monitoring Station (SMS). Effluent flow-proportional composite samples are collected at the SMS on a daily (midnight-to-midnight), weekly (Thursday through Wednesday), and “monthly” (composited from daily) basis; effluent grab samples are also collected each month at that same location. Certified contract laboratories analyzes these compliance samples, and results (Tables 1–3) are used to establish LLNL compliance with the 2019–2020 Wastewater Discharge Permit (Permit 1250) granted by the City of Livermore Water Resources Division (WRD). Supplemental analyses for biochemical oxygen demand (BOD) and total suspended solids (TSS) are performed onsite and reported (Table 4) for the calculation and assessment of sewer service charges. Quarterly, effluent is sampled for metals (24-hour composite) and cyanide (grab sample) concentrations (mg/L). The results are presented in Table 5. In addition to the sampling noted above, the SMS continuously monitors LLNL sewage effluent in real-time for flow rate, pH, metals, and radioactivity. Standard measurement methods are used to monitor flow and pH to determine permit compliance. Unique nonstandard analytical methods monitor for the presence of metals and radioactivity using x-ray fluorescence (XRF) and gamma spectroscopy, respectively. If an anomalous condition is detected by the monitoring system, an alarm activates LLNL’s Sewer Diversion Facility (SDF) and Livermore Water Reclamation Plant (LWRP) operators are notified that a potential release has occurred.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Los Alamos National Laboratory 2022 Annual Site Environmental Report (Rev. 2)

Los Alamos National Laboratory (Laboratory) annual site environmental reports are prepared each year by the Laboratory’s environmental organizations as required by U.S. Department of Energy Order 231.1B, Administrative Change 1, Environment, Safety, and Health Reporting, and Order 458.1, Administrative Change 4, Radiation Protection of the Public and the Environment. The chapters in this report discuss our compliance with environmental laws, regulations, and orders (Chapter 2, Compliance Summary); how we manage the Laboratory’s environmental performance and assure the quality of data from analysis of environmental samples (Chapter 3, Environmental Programs and Analytical Data Quality); how we monitor for air emissions of radioactive materials and for weather conditions (Chapter 4, Air Quality); how we monitor for effects of Laboratory operations on groundwater quality (Chapter 5, Groundwater Protection); how we monitor the levels of chemicals and radionuclides in storm water runoff and sediment (Chapter 6, Watershed Quality); how we monitor for the levels and effects of chemicals and radionuclides in plants, animals, soil, and vegetation (Chapter 7, Ecosystem Health); and finally, what radioactive dose or risk from chemical exposure that members of the public could experience as a result of Laboratory operations (Chapter 8, Public Dose and Risk Assessment).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

An Impedance-Loaded Surface Acoustic Wave Corrosion Sensor for Infrastructure Monitoring

Passive surface acoustic wave (SAW) devices are attractive candidates for continuous wireless monitoring of corrosion in large infrastructures. However, acoustic loss in the aqueous medium and limited read range usually create challenges in their widespread use for monitoring large systems such as oil and gas (O&G) pipelines, aircraft, and processing plants. This paper presents the investigation of impedance-loaded reflective delay line (IL-RDL) SAW devices for monitoring metal corrosion under O&G pipeline-relevant conditions. Specifically, we studied the effect of change in resistivity of a reflector on the backscattered signal of an RDL and investigated an optimal range through simulation. This was followed by the experimental demonstrations of real-time monitoring of Fe film corrosion in pressurized (550 psi) humid CO 2 conditions. Additionally, remote monitoring of Fe film corrosion in an acidic solution inside a 70 m carbon steel pipe was demonstrated using guided waves. This paper also suggests potential ways to improve the sensing response of IL-RDLs.

47 OTHER INSTRUMENTATION↗