Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “energy monitoring”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Three-pole wigglers at NSLS-II

The National Synchrotron Light Source-II (NSLS-II) at Brookhaven National Lab (BNL) is a third-generation medium-energy storage ring with 3 GeV and sub-nm-rad horizontal emittance, equipped with a top-off capability of 500 mA. It is designed to deliver an extremely intense photon beam across a wide spectral range, from the far-infrared to the very hard X-ray region. This outstanding performance is achieved through a combination of bending magnets (BM), three-pole wigglers (3 PW), and advanced insertion device (ID) sources. Six three-pole wigglers have been constructed at the NSLS-II IDs Lab. These devices are used to produce broadband radiation with lower angular power density and to monitor the electron beam emittance and energy spread. Here, this paper describes the R&D activities focused on developing the required magnetic and mechanical designs, along with magnetic field optimization and the final magnetic measurement results. It also covers the spectral brightness, flux, power density, spatial and angular output properties of the 3 PWs, including their commissioning results and their effects on the performance of the NSLS-II storage ring.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Demonstrating Advanced Sensors for In-Situ Monitoring Towards Qualification of Nuclear Relevant Components

The U.S. Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing qualification of laser powder bed fusion (LPBF) components for nuclear applications. A major focus of this effort is the use of in situ process monitoring and machine learning–based tools to establish real-time quality assurance. The primary objective of this report is to identify and evaluate the most relevant in situ sensor systems for LPBF, and to document the deployment of these systems across platforms critical to the AMMT program. This work demonstrates how in situ monitoring can detect process anomalies, track geometry-dependent flaws, and identify limiting combinations of processing parameters—particularly those related to energy density and complex geometries (e.g., overhanging structures). To support this goal, a diverse suite of sensor modalities was evaluated across LPBF platforms, including visible and near-infrared (NIR) imaging, fringe projection profilometry, long-wavelength infrared (LWIR) thermography, and high-speed photodiode/pyrometry systems. These sensor streams were integrated with Peregrine, a machine-agnostic software platform that, among other capabilities, can generate real-time process anomaly classification. This report documents sensor deployments on multiple AMMT flagship platforms, including the Concept Laser M2 and Renishaw AM400/AM250 systems. Calibration builds with complex, flaw-prone geometries such as unsupported overhangs, stepped features, and thin walls, were used to evaluate how well Peregrine and its associated sensors could detect process anomalies and other instabilities under varied energy densities. It will be shown how Peregrine reliably identifies common process anomalies such as recoater streaking, superelevation, etc., and can be used in post-build analysis for anomaly spatial distributions throughout the build height to better understand the impact of geometry and processing parameter choice on the build. This work demonstrates measurable progress toward the vision that components can be born-qualified by establishing a real-time monitoring framework, identifying limiting process conditions, and laying the foundation for sensor fusion–enabled prediction pipelines that are scalable across platforms and applicable to nuclear-relevant components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

WEC fault modelling and condition monitoring: A graph-theoretic approach

The nature of wave resources usually requires wave energy converter (WEC) components to handle peak loads (i.e., torques, forces, and powers) that are many times greater than their average loads, accelerating equipment degradation. Moreover, due to their isolated nature and harsh operating environment, WEC systems are projected to possess high operations and maintenance (O&M) cost, i.e., around 27% of their leveled cost of energy. As such, developing techniques to mitigate these costs through the application of condition monitoring and fault tolerant control will significantly impact the economic feasibility of grid connected WEC power. Toward this goal, models of faulty components are developed in the open source modeling platform, WEC-Sim, to estimate the performance and measurable states of a WEC operating with likely device and sensor failures. Two types of faulty component models are then applied to a point absorber WEC model with basic controller damping and spring forces. Resulting changes in device behavior are recorded as a benchmark, and a graph-theoretic approach is proposed for fault detection and identification utilizing multivariate time series. Simulation results demonstrate that these faults can greatly affect the WEC performance, and that the proposed method can effectively detect and classify different types of faults.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Sensors with Intelligent Measurement Platform for Monitoring and Control in Distribution Circuits

This paper presents a medium-voltage intelligent measurement platform that provides post-processing of raw measurements received from commercially-available voltage/current sensors to enhance accuracy and bandwidth of the monitoring system. Furthermore, this platform integrates into a Data Distribution Service (DDS) messaging bus for distributed control and interoperability. The authors present the design, specifications, and major components included in the platform, and argue for applications and use cases that most benefit from this new approach. A laboratory testbed has been created to demonstrate the functionality, for which test results are presented for selected test cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Temperature Distribution Within an Ignition Kernel Initiated by a Laser-Induced Plasma

The sizes of, and temperature distributions within, ignition kernels initiated by a Q-switched neodymium-doped yttrium aluminum garnet laser-induced plasma in an unconfined lean premixed hydrogen-air upward jet flow are investigated. The experiments involved a range of jet velocities and a range of deposited laser energies at a fixed height above the exit along the axis of a burner. The growth of, and the temperature distributions within, the ignition kernels, as affected by the size and the energy distribution of the laser-induced plasma, are monitored with an infrared camera. The initial ignition kernels’ areas are larger with higher laser pulse energies and remain unchanged up to [Formula: see text] and then increase by factors of up to 3 at [Formula: see text]. The change in the kernel area caused by the jet velocities is less than 1.5%. An increase of the bulk velocity by 190% decreases the ignition kernel temperature by 6%. This reduction in the ignition kernel temperatures is because of an increase in energy losses by a factor of 2 and decreases in heat releases by 2% at [Formula: see text] and by 11% at [Formula: see text]. The present contributions are: measurements of and insights into temperature distributions and kernel development rates during the laser-induced plasma ignition process at different deposited energies and flow velocities.

Engineering↗
DOE OSTI2023

Unsupervised acoustic detection of fatigue-induced damage modes from wind turbine blades

This paper proposes a new in-situ damage detection approach for wind turbine blades, which leverages blade-internal non-stationary acoustic pressure fluctuations caused by the mechanical loading as the main source of excitation. This acoustic excitation was leveraged for the detection of fatigue-related damage modes on a full-scale wind turbine blade undergoing edgewise fatigue testing. An unsupervised, data-driven structural health monitoring strategy was developed to learn the normal cavity-internal acoustic sequences generated by the blade’s load cycles and to detect damage-related anomalies in the context of those sequences. A linear cepstral-coefficient based feature set was used to characterize the cavity-internal acoustics and LSTM-autoencoders were trained to accurately reconstruct healthy-case sequences. The reconstruction error was then used to characterize anomalous acoustic patterns within the blade cavity. The technique was able to detect a damage event earlier than a strain-based system by 120,000 load cycles.

17 WIND ENERGY↗
NASA NTRS1998

Guest Investigator Studies with the Compton Gamma Ray Observatory

The cumulative all-sky survey by the Compton Gamma Ray Observatory (CGRO), composed of data acquired during the first three years of the mission, included a number of regions of very limited exposure. The most glaring deficiency in coverage was toward the region of the South Galactic Pole (SGP), which received significantly less exposure than other directions- by a factor of at least 2 to 3. Furthermore, nearly all of the SGP exposure was accumulated during the first year of the mission. Since blazars are known to be time-variable, and of unknown duty cycle, a pointing of the CCRO in that direction was considered highly desirable, and long overdue. In addition, data gathered from a pointing toward the SGP and its comparison with comprehensive data available for the North Galactic Pole would be extremely valuable to investigators studying the extragalactic diffuse emission. The reasons outlined above prompted our initiation of a Cycle 4 campaign to systematically search with EGRET and COMPTEL for gamma-ray emission from sources near the South Galactic Pole. The Cycle 4 SGP campaign consisted of tnvo 14-day observations separated in in time by approximately 10 months. The temporal separation of the observations was requested to allow a test for possible variations in the detected sources. Our primary targets were 38 FSRQs which lie within 30 degrees of the SGP, and which satisfy the basic criteria for candidate gamma-ray AGNs,flat-spectrum radio sources, many of which exhibit blazar-type properties). These targets were selected from the standard references, and from the available on-line databases (e.g., the NASA Extragalactic Database, NED), as the most promising AGN targets in the vicinity of the SGP. A 30 radius from the SGP was chosen as the boundary of our survey, since the selected targets would then fall within the most sensitive portion of the fields of view of EGRET and COMPTEL (i.e., within a 30 zenith angle), for a CGRO pointing directed exactly at the SGP. Our South Galactic Pole Survey yielded a number of exciting results. The EGRET data were analyzed using the maximum likelihood techniques to estimate the intensity, spectrum, and position of gamma-ray sources in the field of view. Our analysis revealed four sources at energies greater than 100 MeV with likelihood ratios corresponding to greater than 30 detections (Vestrand et al. 1996). One of the sources is associated with the well known gamma-ray blazar PKS 0208-512, but the other three were previously unknown. Among the new detections was PKS 2155-304 which is often considered a prototype of the x-ray selected BL Lacs. PKS 2155-304, which was also detected at hard x-ray energies by CGRO/OSSE, is one of the brightest BL Lac objects in the sky at optical through x-ray energies and has a history of rapid, strong multiwavelength variability. As such, it has been the subject of intensive, contemporaneous, multiwavelength monitoring covering radio frequencies to x-ray energies.

Vestrand, W. T.↗
DOE OSTI2021

Data-driven estimation of energy consumption for electric bus under real-world driving conditions

Reliable and accurate estimation of an electric bus’s instantaneous energy consumption is critical in evaluating energy impacts of planning and control of electric bus operations. In this study, we developed machine learning-based long short-term memory (LSTM) and artificial neural network (ANN) models to estimate 1 Hz energy consumption of electric buses based on continuous monitoring data of electric buses in Chattanooga, Tennessee, in 2019 and 2020. We propose a data-partitioning algorithm to separate energy charging and discharging modes before applying data-driven estimation models. Here, a K-fold cross-validation-based model selection process was conducted to identify the optimal model structure and input variables in terms of prediction accuracy. The estimation results show the predicted mean absolute percentage error rates of LSTM and ANN models were 3% and 5%, respectively. We compared the proposed models with existing models in the literature based on the same testing data to demonstrate the predictability of our models.

Artificial neural network↗
NASA NTRS2000

Analysis of MIR-18 results for physical and biological dosimetry: radiation shielding effectiveness in LEO

We compare models of radiation transport and biological response to physical and biological dosimetry results from astronauts on the Mir space station. Transport models are shown to be in good agreement with physical measurements and indicate that the ratio of equivalent dose from the Galactic Cosmic Rays (GCR) to protons is about 3/2:1 and that this ratio will increase for exposures to internal organs. Two biological response models are used to compare to the Mir biodosimetry for chromosome aberration in lymphocyte cells; a track-structure model and the linear-quadratic model with linear energy transfer (LET) dependent weighting coefficients. These models are fit to in vitro data for aberration formation in human lymphocytes by photons and charged particles. Both models are found to be in reasonable agreement with data for aberrations in lymphocytes of Mir crew members: however there are differences between the use of LET dependent weighting factors and track structure models for assigning radiation quality factors. The major difference in the models is the increased effectiveness predicted by the track model for low charge and energy ions with LET near 10 keV/micrometers. The results of our calculations indicate that aluminum shielding, although providing important mitigation of the effects of trapped radiation, provides no protective effect from the galactic cosmic rays (GCR) in low-earth orbit (LEO) using either equivalent dose or the number of chromosome aberrations as a measure until about 100 g/cm 2 of material is used.

Flight Experiment↗
DOE OSTI2020

Indoor air quality in California homes with code-required mechanical ventilation

Data were collected in 70 detached houses built in 2011-2017 in compliance with the mechanical ventilation requirements of California's building energy efficiency standards. Each home was monitored for a 1-week period with windows closed and the central mechanical ventilation system operating. Pollutant measurements included time-resolved fine particulate matter (PM 2.5 ) indoors and outdoors and formaldehyde and carbon dioxide (CO 2 ) indoors. Time-integrated measurements were made for formaldehyde, NO 2 , and nitrogen oxides (NO X ) indoors and outdoors. Operation of the cooktop, range hood, and other exhaust fans was continuously recorded during the monitoring period. Onetime diagnostic measurements included mechanical airflows and envelope and duct system air leakage. All homes met or were very close to meeting the ventilation requirements. On average, the dwelling unit ventilation fan moved 50% more airflow than the minimum requirement. Pollutant concentrations were similar to or lower than those reported in a 2006-2007 study of California new homes built in 2002-2005. Mean and median indoor concentrations were lower by 44% and 38% for formaldehyde and 44% and 54% for PM 2.5 . Ventilation fans were operating in only 26% of homes when first visited, and the control switches in many homes did not have informative labels as required by building standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1973

OGO-6 gas-surface energy transfer experiment

The kinetic energy flux of the upper atmosphere was analyzed using OGO-6 data. Energy transfer between 10 microwatts/sq cm and 0.1 W/sq cm was measured by short-term frequency changes of temperature-sensitive quartz crystals used in the energy transfer probe. The condition of the surfaces was continuously monitored by a quartz crystal microbalance to determine the effect surface contamination had on energy accommodation. Results are given on the computer analysis and laboratory tests performed to optimize the operation of the energy transfer probe. Data are also given on the bombardment of OGO-6 surfaces by high energy particles. The thermoelectrically-cooled quartz crystal microbalance is described in terms of its development and applications.

Mckeown, D.↗
DOE OSTI2024

Triton Initiative: FY 2024 Communications, Outreach, and Engagement End-of-Year Report

The Department of Energy (DOE) Water Power Technologies Office (WPTO) Triton Initiative works to reduce barriers to permitting of marine energy testing and installation through environmental monitoring research that can help inform decision-makers on potential environmental effects associated with these systems. Communications, outreach, and engagement efforts are critical to Triton's success, which involves facilitating the effective communication and dissemination of environmental monitoring research information and results to end-users and fostering collaborations between researchers and industry partners to address the most pressing needs of this emerging industry. The Triton Initiative's communications, outreach, and engagement (TCOE) foundational goals are to educate and raise awareness of ME and the role of Triton's environmental monitoring research in supporting the industry, build trust with audiences through transparent communications and outreach, and evaluate and refine TCOE tactics based on feedback and metrics. The TCOE FY 2024-specific objectives were to (1) refine and grow Triton's audience network by reaching new individuals and communities within Triton's target audience base, and (2) improve the strategy and evaluation of TCOE efforts to demonstrate the value of communications and outreach for the ME community. This report presents the results and analysis of communications activities from September 1, 2023 through August 31, 2024. We assess the TCOE target audiences, highlight notable successes and lessons learned from FY2024, and identify the most effective channels and activities used to connect with those audiences to achieve the TCOE goals.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Tracking the Oxidation of Silicon Anodes Using Cryo-EELS upon Battery Cycling

Silicon is a high-capacity material for the anode of a rechargeable lithium-ion battery. One of the fundamental challenges for using Si in anodes is capacity fading, which has been revealed to be partially associated with the interfacial instability between the Si and liquid electrolyte due to the large volume swing of Si upon charging and discharging. Smart nanoscale design concepts, either pre-synthesized or formed in-situ, have led to the mitigation of the detrimental factors associated with the volume swing of Si. However, it has never been clear as how the chemical state of Si evolves and contributes to the capacity fading upon battery cycling. Here, we use cryo-electron energy loss spectroscopy (EELS) to directly monitor, at sub-nanometer scale, the chemical evolution of Si upon battery cycling. We discover that during the cycling process, Si particles are progressively oxidized to form SiO 2 , which is initiated from the particle surface and gradually penetrates toward the interior of the particle, directly contributing to the capacity fading. Possible mechanisms of Si oxidation are postulated. We further show how the cycling stability can be improved by an electrolyte additive to form an effective passivation layer, representatively, even a small concentration of fluoroethylene carbonate (FEC) causes the formation of an LiF layer on the Si nanoparticle surface that prevents Si oxidation and improves cycling stability. Furthermore, the present work unveils Si oxidation as a previously unrecognized factor that contributes to capacity fading, therefore providing insight into the design of anodes with Si based materials.

25 ENERGY STORAGE↗
NASA NTRS1987

X-ray intensity and spectral variations in the BL Lac sources H2155-304 and PKS0548-322

The results from the X-ray observations of two BL Lacertae objects, H2155-304 and PKS0548-322, are presented. The observations were carried out with the HEAO-1 A2 Low Energy Detectors, the High Resolution Imager, and the Monitor Proportional Counter aboard the Einstein Observatory. Correlated X-ray intensity variations of about 20 percent in the 0.15-3.5 keV energy band and about 40 percent in the 1.5-10 keV energy band are observed in H2155-304 over a period of about 8 hr. A factor of two change in the intensity of PKS0548-322 in the 3.5-10 keV energy interval is also detected over a time interval of 1 hr. Variations in the X-ray intensity over a timescale of months and the hardening of the spectrum with increasing intensity are seen in the HEAO-1 A2 data on H2155-304. The shortest observed timescale for the variability is used to derive an upper limit on the mass of the central accreting source in the two BL Lac objects studied here.

Agrawal, P. C.↗
DOE OSTI2020

Automatic Seismic Phase Picking Using Deep Learning for the EGS Collab project

Microseismic monitoring plays an important role in many energy-related and environmental industries.The microseismic event catalog and seismic structure of the subsurface are two of the primary outputsof the microseismic monitoring system. Though rough locations of microseismic events can be estimated automatically, obtaining high-resolution microseismic event locations requires a significant amount of human laborespecially on seismic phase picking. Unlike traditional automatic pickers that are usually less precise than human analysts, a fewrecently proposed algorithms based on deepneural networks(DNN)were able to match or surpass human performance for earthquake signals. Due to differences in the spatial scale of the study area, sensor sampling rate, and geometry of the monitoring system, it is not clear whether these deepneural networkmodels can be used to speed up microseismic data processing. In this paper, we adapted the DNN based technique for automatic phase picking of microseismic signals. We usedmicroseismic data recorded at the experiment 1 site of the enhancedgeothermal system (EGS) Collab project anddesigneda workflowthat we call transfer-learning aided double-difference tomography (TADT),thatcombines transfer learning and seismic tomography. We re-train an existing DNN with our data to obtain a newmodel using around 3500 seismogramsand associated manual phase picks. Thistransfer learnedmodel is able to reach human performance but muchfaster than human analysts. The transfer-learning-derived phase pickswereused to improve microseismic event locations and imagethesubsurface. The results are similar to or slightly better than those obtained with manual phase picks.

Chai, Chengping↗
DOE OSTI2022

Investigation of Multiple Data Streams for Gearbox Bearing Fault Prediction Through Machine-Learning Models

Operations and maintenance (O&M) cost of wind plant accounts up to 30% of total energy cost, which can be reduced through continuous monitoring and successfully detecting incipient wind turbine failures. To accomplish this, condition monitoring and predictive maintenance systems are being implemented in wind industry to support O&M decision making. A wide range of approaches for condition monitoring and fault prediction have been developed. These approaches generally use historical data of wind turbines collected by Supervisory Control and Data Acquisition (SCADA) system to identify patterns that lead to failure. These SCADA data show the overall condition of a wind turbine and can be leveraged to detect when the turbine's performance is degrading and to identify if a fault is developing. However, it becomes challenging to predict the failure of a specific wind turbine gearbox bearing, because the SCADA data are often not directly linked to the component. To bridge the gap, we have investigated features calculated from SCADA data using physics-based models and the gearbox design over the years. The damaged metric we used in the physics domain is frictional energy. Combining these physics domain variables with SCADA data as inputs to various machine learning models for gearbox bearing fault prediction, we have demonstrated the benefits of leveraging both physics and data domain models. It was an attempt to improve frictional-energy-based damage metric by adding data domain inputs, as we had learned that the frictional-energy-based damage metric alone is not sufficient to single out failed bearings from healthy. As condition monitoring data (either vibration or oil debris data) has become available at more and more wind plants, we would like to evaluate whether by adding the condition monitoring data can help further improve the performance of frictional-energy-based damage metric for gearbox bearing fault prediction. Both cases by modeling through various machine learning algorithms are discussed in this study along with some observations.

fault prediction↗
DOE OSTI2026

HDG-1 Experiment Irradiation Monitoring Data Qualification Final Report

SUMMARY The U.S. Department of Energy (DOE) Advanced Reactor Technologies (ART) Graphite Research and Development (GRD) Program is conducting a series of six experiments to quantify the effects of irradiation on nuclear-grade graphite. This report documents the qualification of irradiation monitoring data for the fifth experiment, High Dose Graphite-1 (HDG-1). Qualified monitoring data are required by the ART program to support the design and licensing of the first high-temperature reactor (HTR) nuclear plant. Data are classified as Qualified if they meet the usage requirements described in the experiment planning and quality assurance (QA) documents, Failed if they do not meet those requirements and provide no usable information, or Trend if they do not fully meet all requirements but still provide useful information subject to an assessment of how any deficiencies may affect a particular use of the data. HDG-1 irradiation began with Advanced Test Reactor (ATR) Cycle 168B on August 24, 2020, and concluded after Cycle 173C on January 27, 2025. The HDG-1 capsule was removed from the reactor core twice—during core internal change (CIC) Cycle 170A and powered axial locator mechanism (PALM) Cycle 172A—to prevent overheating of the graphite specimens during high-power PALM cycles. The capsule was therefore irradiated during a total of seven normal ATR cycles: 168B, 169A, 171A, 171B, 173A, 173B, and 173C. Irradiation monitoring data evaluated in this report include thermocouple (TC) temperature, gas flow rate, gas moisture, gas pressure, specimen load, and graphite stack displacement. Temperature. A total of 14,508,065 TC temperature records were captured. Of these, 13,901,785 (95.8%) are Qualified and 606,280 (4.2%) are Failed. The principal source of failed temperature data was the instrument failure of TC-9 (Zone 2) on June 24, 2024, and TC-10 (Zone 1) on July 5, 2024, near the end of Cycle 173A, which resulted in 595,554 Failed readings. An additional 379 missing values and 10,347 slightly negative values from TC-13 during ATR outages are also Failed. Neither TC-9 nor TC-10 was used as a temperature-control TC, and their failures did not compromise capsule condition monitoring. Correlation analysis of all 13 TCs found no evidence of virtual junction formation. Control chart analysis revealed clear downward drift of approximately 80°C for TC-6 (Zone 3) relative to other stable TCs, and possible downward drift of approximately 60°C for TC-13 relative to the Zone 5 control TC (TC-1), though TC-13 remained consistent with the Zone 2 control TC (TC-12). Gas flow. A total of 20,088,090 gas flow rate records were captured. Of these, 19,941,463 (99.3%) are Qualified and 146,627 (0.7%) are Failed due to missing values. All argon, helium, and total gas flow data were within expected ranges throughout the irradiation. Gas moisture. A total of 1,116,005 outlet gas moisture values were captured. Of these, 1,101,421 (98.7%) are Qualified and 14,584 (1.3%) are Failed, comprising 14,556 out-of-range values and 28 missing values. The out-of-range moisture values exceeded 22,000 ppmv for approximately 1 week at the beginning of Cycle 173A, when accumulated moisture evaporated after the capsule was retrieved from water storage during PALM Cycle 172A and reinserted into the east flux trap. Moisture levels returned to below 25 ppmv for the remaining three cycles, and the transient high-moisture event did not affect the integrity of specimen irradiation. Gas pressure. A total of 7,812,035 gas pressure values were captured. Of these, 6,642,048 (85.0%) are Qualified and 1,169,987 (15.0%) outlet pressure values are Failed, comprising 718,537 zero outlet pressure values due to sensor failure from Cycle 168B through Cycle 171B, 54,550 missing values, and 396,900 too-low outlet pressure values, ranging from 1.1 to 1.6 psia after sensor replacement during Cycle 173A. Load. A total of 6,696,030 load values were captured. Of these, 6,694,580 (99.98%) are Qualified and 1,450 (0.02%) are Failed due to missing values. Applied loads to the six specimen stacks were stable throughout the irradiation. Stack displacement. A total of 6,696,030 displacement values were captured. Of these, 5,713,297 (85.32%) are Qualified and 3,781 (0.06%) are Failed due to missing values. Stack displacement increased consistently throughout the irradiation, reaching approximately 3.08 in. for Channels 5 and 6 by the end of irradiation. 978,952 (14.62%) substantially elevated displacements observed for Channel 6 beginning in Cycle 171A and for Channel 5 beginning in Cycle 173A are assigned Trend status. Raising pressure. A total of 1,115,999 raising pressure values were captured. Of these, 1,115,430 (99.95%) are Qualified and 569 (0.05%) are Failed due to missing values. Ram pressure. A total of 6,696,030 ram pressure values were captured. Of these, 6,692,249 (99.95%) are Qualified and 3,484 (0.05%) are Failed due to missing values. Stack raising was perf

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Time-Lapse Integration at FWU: Fluids, Rock Physics, Numerical Model Integration, and Field Data Comparison

We present the current status of time-lapse seismic integration at the Farnsworth (FWU) CO2 WAG (water-alternating-gas) EOR (Enhanced Oil Recovery) project at Ochiltree County, northwest Texas. As a potential carbon sequestration mechanism, CO2 WAG projects will be subject to some degree of monitoring and verification, either as a regulatory requirement or to qualify for economic incentives. In order to evaluate the viability of time-lapse seismic as a monitoring method the Southwest Partnership (SWP) has conducted time-lapse seismic monitoring at FWU using the 3D Vertical Seismic Profiling (VSP) method. The efficacy of seismic time-lapse depends on a number of key factors, which vary widely from one application to another. Most important among these are the thermophysical properties of the original fluid in place and the displacing fluid, followed by the petrophysical properties of the rock matrix, which together determine the effective elastic properties of the rock fluid system. We present systematic analysis of fluid thermodynamics and resulting thermophysical properties, petrophysics and rock frame elastic properties, and elastic property modeling through fluid substitution using data collected at FWU. These analyses will be framed in realistic scenarios presented by the FWU CO2 WAG development. The resulting fluid/rock physics models will be applied to output from the calibrated FWU compositional reservoir simulation model to forward model the time-lapse seismic response. Modeled results are compared with field time-lapse seismic measurements and strategies for numerical model feedback/update are discussed. While mechanical effects are neglected in the work presented here, complementary parallel studies are underway in which laboratory measurements are introduced to introduce stress dependence of matrix elastic moduli.

4D↗