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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Subtask 1.5 – CO2 Injection Monitoring with an Optimized Scalable, Automated, Semipermanent Seismic Array

The scalable, automated, semipermanent seismic array (SASSA) method is a flexible and relatively cost-effective surface geophysical method for regular time-lapse monitoring of the movement of injected carbon dioxide (CO2) in a reservoir for CO2 enhanced oil recovery (EOR) or geologic CO2 storage operations. It has the advantages of a low-environmental-footprint while monitoring regions of a reservoir from the surface without the need for a regular grid distribution of receivers. Automated data collection is possible. As only time-lapse amplitude changes at the reservoir level due to CO2 movement within the reservoir are monitored, the turnaround time to deliver results from the SASSA method can be short, without the need for long, time-consuming data-processing workflows. As data is collected and processed, incremental information can be provided to the field operator. The Energy & Environmental Research Center (EERC) conducted a SASSA field test from September 2018 to November 2020 in a portion of the Bell Creek Field in Montana, which implemented new CO2 EOR field activities during the study period. Lessons learned from a proof-of-concept study were incorporated to improve the data quality of the SASSA method and demonstrate the viability of the technology. The EERC implemented several enhancements to improve data quality, including 1) an iterative survey design, which allowed placing the receivers in strategic locations where the movement of the CO2 in the reservoir could be tracked with minimum interference by the cultural noise in the study area; 2) the use of powerful seismic sources in the form of surface orbital vibrators, and 3) data acquisition during optimal periods. History-matched reservoir simulation was performed to predict gas saturation and pressure response induced by CO2 injection in the study area. The results were compared with the SASSA-measured responses to CO2 injection as a partial validation technique. A match between the two methods was observed for most of the SASSA points predicted to have intersected a CO2 saturation change. The validated results provide confidence that the SASSA method can be used independently as a CO2 saturation monitoring technique. As data are collected and processed, incremental information can be provided to the field operator. The critical components of the SASSA workflow for a successful application of the method are the following: Iterative survey design with information about CO2 injection activities from the oilfield operator. A detailed CO2 injection plan is the key driver to select the strategic monitoring location of the SASSA sensors. After this information is incorporated in the initial distribution of sources and receivers in the study area, high-resolution satellite images are used to identify ground locations not affected by cultural noise sources, such as power lines, pipelines/flow lines, or roadways. In the next iteration of the survey design, a scouting trip to the study area is needed to understand more details of the noise sources identified in the previous step and the intensity of the field activities that can also generate noise during the monitoring. Integrating the information from the scouting trip into the survey design to select the optimum source and receiver locations is the final step. Noise attenuation. The variety of noise types during seismic monitoring of an oil field is enormous. Tailored noise characterization and processing at a node-by-node level can enhance the performance and sensitivity of the SASSA technique. Future advancements that could improve the efficiency and application of the SASSA technology include: Gaining a better understanding of the noise field produced by the seismic source to aid the choice of receiver location. Surface noise from the source can overwhelm the small signal changes due to CO2 that the SASSA method measures. Improved data-processing workflow to automatically analyze and adapt to dynamic noise conditions associated with industrial settings. This subtask was funded through the EERC–DOE Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE- FE0024233.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Reaction Rate Ratios for Recent Fast Metal Experiments with Large Plutonium Masses

Reaction rate ratios are integral responses that are used within the criticality experiments field because they contain spectral information. While these types of measurements have been utilized for nuclear data validation with historic experiments, few experiments of this type have been utilized for recent experiments, as few exist. This work focuses on measured reaction rate ratios for two nearly bare plutonium critical assemblies with different geometries: one that is cube like (with a Pu mass of 40 kg) and one that is slab like (with a Pu mass of 109 kg). Irradiations were performed with both configurations in which foils were placed near the center of the assembly. Plutonium, highly enriched uranium, depleted uranium, and Au foils were included in the irradiation and counted via high-purity germanium detectors. From these measurements, reaction rate ratios were calculated. Measured and simulated values and uncertainties are presented for the reaction rate ratios. Ratios utilizing the following reactions are given in this work: 197 Au(n, γ), 197 Au(n,2n), 235 U(n,fission), 238 U(n, fission), 238 U(n,2n), 238 U(n,γ), and 239 Pu(n,fission). Uncertainties for the measured reaction rate ratios ranged from 4% to 7%, and the contribution of various parameters to this uncertainty was investigated. The results are compared to historical experiments and should be used for nuclear data validation for future nuclear data library releases. These measurements are part of the EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) project, which utilizes measurement responses in addition to k eff (such as these reaction rate ratios) to help reduce uncertainties in 239 Pu nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

OC6 Phase Ia Definition Document: Validation of Nonlinear Hydrodynamic Loading on the DeepCwind Semisubmersible

The objective of OC6 Phase I is to investigate the persistent under-prediction (about 20% on average) of the structural loads in the OC5-DeepCwind floating semisubmersible wind system, as observed within the previous OC5 Phase II project. The OC5 results indicate that much of this under-prediction originates from the low-frequency response of the system at the surge/pitch natural frequencies, resulting from nonlinear hydrodynamic loading and/or overprediction of hydrodynamic damping. This work package therefore focuses on better understanding this low-frequency response behavior, the applicability of computational-fluid-dynamics (CFD) models and engineering-level hydrodynamic models for predicting the nonlinear hydrodynamic loading, and the level of uncertainty in the measured response characteristics. To address these objectives, two experimental campaigns were developed and performed in 2017 and 2018 by a sub-group of the OC5 project: Floating test campaign: A simplified OC5-DeepCwind semisubmersible model (no turbine, rigid tower) was moored to three taut-spring lines and subjected to motion decay and wave tests (regular and irregular waves), during which motion amplitudes of the model were measured (see Figure 1a). The purpose of this test campaign was to examine the repeatability of the low-frequency response of the system to wave excitation and determine the level of uncertainty in the response behavior.Constrained test campaign: The same model, but without the tower present, was fixed to a carriage and subjected to towing, forced oscillation and wave tests (regular and irregular waves), during which forces exerted upon the model were measured (see Figure 1b). The purpose of this test campaign was to examine the hydrodynamic loading contributions by separating the wave excitation and radiation forces. Both model test campaigns were performed in the concept basin of the Maritime Research Institute Netherlands (MARIN) in Wageningen, the Netherlands and the first test was within the framework of the MARINET2 project. Both experimental campaigns were examined within Phase Ia of the OC6 project. The purpose of this report is to supply the needed information to participants of the OC6 project to build and simulate the experimental campaigns.

17 WIND ENERGY↗
DOE OSTI2021

Quantifying Negative Effects of Carbon-Binder Networks from Electrochemical Performance of Porous Li-Ion Electrodes

Porous Li-ion electrodes contain active particles, ion transporting electrolyte, and carbon-binder networks. While macrohomogeneous models are often used to predict electrode behavior, accurate predictions remain challenging, owing to the incomplete understanding of the critical role of carbon-binder networks and how they affect the electrochemical response. The present study systematically characterizes these effects in terms of effective properties by utilizing macrohomogeneous models to analyze the measured responses for electrodes with different carbon-binder content, electrode thickness, and porosity but with identical materials. We find that the impact of the carbon-binder network is more severe than previously thought. Even for low carbon-binder content (5 %wt. dry electrode), the presence of the network decreases the reaction area and increases the ion transport resistance, negatively impacting electrode performance. These effects scale with not just porosity or active material volume but also with carbon-binder content. The findings underscore the importance of connecting all effective properties to electrode specifications in a full factorial sense to transform the electrode design paradigm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Quantitative measurement of pebble fuel anisotropy using generalized ellipsometry

The renewed development of high-temperature gas-cooled reactors has created a need to modernize pebble fuel quality control methods. One important specification in these methods is the coefficient of thermal expansion (CTE) anisotropy, which reflects graphite grain alignment and affects fuel performance. This study investigates the feasibility of using two-modulator generalized ellipsometry microscopy (2-MGEM) as a potential surrogate metric for CTE anisotropy. Graphite matrix compacts with controlled levels of anisotropy were fabricated by varying pre-pressures during forming and were subsequently characterized using both optical dilatometry and 2-MGEM. Measured responses were compared to an isotropic reference pebble produced using an industrial manufacturing process to provide a practical baseline. The resulting measurements revealed a strong quantitative correlation between the CTE anisotropy ratio and the corresponding diattenuation ratio. However, propagated measurement uncertainties in the optical method were found to limit definitive pass/fail discrimination, highlighting the need for improved precision before qualification as a quality control tool. Still, the results establish a quantitative relationship between optical and CTE anisotropy and support further development of 2-MGEM as a potential surrogate method for evaluating graphite matrix anisotropy in pebble fuel manufacturing.

Raftery, Alicia [ORNL] (ORCID:0000000259076427)↗
DOE OSTI2024

Forced Oscillation Source Location in Power Systems Using MVMD-assisted DEF in TF Plane

Fast and accurate forced oscillation source location (FOSL) is critical for mitigating forced oscillations in power systems. Here, to overcome the shortcomings of traditional dissipating energy flow (DEF) in decomposing the forced oscillation components from the measurement responses, a multivariate variational mode decomposition (MVMD)-assisted FOSL is proposed in this paper to locate the forced oscillation sources from measurements in time-frequency (TF) plane. The multi-channel measurement matrix of each generator is formed, then the multi-channel modes are decomposed from the formed multi-channel measurement matrix using the MVMD. Further, the intrinsic mode functions (IMFs) associated with the forced oscillation mode are distinguished from the decomposed modes according to the relative energy weights. With the distinguished IMFs, the MVMD-assisted DEF calculation method is developed to locate the forced oscillation source. Finally, the performance of the proposed method is evaluated using the simulation data of the WECC 179-bus test system and IEEE-NASPI Oscillation Source Location Contest as well as the actual PMU data of ISO New England. The results validated the effectiveness and accuracy of the proposed method in the FOSL.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Photoinduced patterning of oxygen vacancies to promote the ferroelectric phase of Hf 0.5 Zr 0.5 O 2

Photoinduced reductions in the oxygen vacancy concentration were leveraged to increase the ferroelectric phase fraction of Hf 0.5 Zr 0.5 O 2 thinfilms. Modest ( ~ 2 — 77 pJ=cm 2 ) laser doses of visible light (488 nm, 2.54 eV) spatially patterned the concentration of oxygen vacancies as monitored by photoluminescence imaging. Local, tip-based, near-field, nanoFTIR measurements showed that the photoinduced oxygen vacancy concentration reduction promoted formation of the ferroelectric phase (space group Pca2 1 ), resulting in an increase in the piezoelectric response measured by piezoresponse force microscopy. Photoinduced vacancy tailoring provides, therefore, a spatially prescriptive, postsynthesis, and low-entry method to modify phase in HfO 2 -based materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A structure-preserving machine learning framework for accurate prediction of structural dynamics for systems with isolated nonlinearities

The nonlinearities present in structural systems are often found in isolated regions within the structure, such as those containing joints or interfaces. However, despite the localized nature of these nonlinearities their presence serves to couple together the modes of the underlying linear system and significantly complicate the development of appropriate reduced-order models; the localized nonlinearities have a global effect on the dynamics of the system. Further, in the presence of evolving structural health the nonlinearities can arise from accumulating damage, with dynamics distinct from those observed in the healthy state. The present work develops a data-driven formulation to identify and include the contributions of the isolated nonlinearities on the dynamics of the underlying linear structure. A novel coordinate separation is developed that decomposes those nonlinearities restricted to the isolated subdomain from the known linear system defined over the entire domain, and the influence of the isolated nonlinearities is reintroduced as an appropriately identified traction at the boundary of the isolated subdomain, referred to as the deviatoric force. In the region exterior to the nonlinear subdomain the response of the ideal linear system recovers that of the original nonlinear system. In this work, the deviatoric force component is predicted using a structure-preserving multilayer perceptron, based only on measured responses at the boundary of the isolated subdomain. Therefore introduction of the perceptron is able to bypass the direct numerical simulation of the nonlinearities within the isolated subdomain. This approach is illustrated through a simple structural system in which an interior region contains cubic nonlinearities and hysteretic damping. Once trained, the machine learning system is able to accurately predict the deviatoric force so that the ideal system recovers the response of the original system in the region outside the isolated nonlinear subdomain. Moreover, the data-driven approach is able to accurately predict the response when the system is subject to differing initial conditions and external excitation without the need for retraining, so that the proposed approach provides a robust description of the structural dynamics of the overall system.

Machine learning↗
DOE OSTI2023

Embedded Fiber Bragg Grating (FBG) Sensors Fabricated by Ultrasonic Additive Manufacturing for High-Frequency Dynamic Strain Measurements

This article demonstrates high-frequency dynamic strain measurements using fiber Bragg grating (FBG) sensors embedded in metal parts. Using an ultrasonic additive manufacturing (UAM) process, FBGs inscribed in polyimide coated optical fibers were embedded in aluminum parts. An electromagnetic shaker was used to exert dynamic events on the embedded FBG sensors with frequencies from 1 to 10 kHz. The high-speed interrogation of FBG sensors was accomplished using a tunable vertical-cavity surface-emitting laser (VCSEL) and a high-speed interrogation system sampling at 120 kHz. The strain response measured by the FBG sensors was compared with real-time measurements using a laser velocimeter. A finite-element analysis (FEA) was performed to simulate responses to both static strain and high-frequency dynamic strain. In conclusion, results show that strains as small as 2.5$με$ can be resolved at frequencies up to 10 kHz.

36 MATERIALS SCIENCE↗
DOE OSTI2022

AC compensation of 3D magnetic diagnostic signals in DIII-D and National Spherical Torus Experiment-Upgrade (NSTX-U) for real-time application

A time domain algorithm has been developed to remove the vacuum pickup generated by both coil current (DC) and induced vessel current (AC) in real time from three dimensional (3D) magnetic diagnostic signals in the National Spherical Torus Experiment-Upgrade (NSTX-U) and DIII-D tokamaks. The possibility of detecting 3D plasma perturbations in real time is essential in modern and future tokamaks to avoid and control MHD instabilities. The presence of vacuum field pickup, due to toroidally asymmetric (3D) coils or to misalignment between sensors and axisymmetric (2D) coils, pollutes the measured plasma 3D field, making the detection of the magnetic field produced by the plasma challenging. Although the DC coupling between coils and sensors can be easily calculated and removed, the AC part is more difficult. Here, an algorithm based on a layered low-pass filter approach for the AC compensation and its application for DIII-D and NSTX-U data is presented, showing that this method reduces the vacuum pickup to the noise level. Comparison of plasma response measurements with and without vacuum compensation shows that accurate mode locking detection and plasma response identification require precise AC and DC compensations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Angular distribution of neutron production by proton and carbon-ion therapeutic beams

Carbon-ion beams are increasingly used in the clinical practice for external radiotherapy treatments of deep-seated tumors. At therapeutic energies, carbon ions yield significant secondary products, including neutrons, which may be of concern for the radiation protection of the patient and personnel. We simulated the neutron yield produced by proton and carbon-ion pencil beams impinging on a clinical phantom at three different angles: 15°, 45° and 90°, with respect to the beam axis. We validated the simulated results using the measured response of organic scintillation detectors. We compared the results obtained with FLUKA 2011.2 and MCNPX 2.7.0 based on three different physics models: Bertini, Isabel, and CEM. Over the different ions, energies, and angles, the FLUKA simulation results agree better with the measured data, compared to the MCNPX results. Simulations of carbon ions at low angles exhibit both the highest deviation from measured data and inter-model discrepancy, which is probably due to the different treatment of the pre-equilibrium stage. The reported neutron yield results could help in the comparison of carbon-ion and proton treatments in terms of secondary neutron production for radiation protection applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Defensive Cybersecurity Architecture Design Using Force-on-Force Cyber-Physical Modeling

Currently, nuclear power plant physical security systems are highly dependent on air-gaps as a protective measure against cyber-threats. Cyber-physical threats become more likely as advanced cyber-threat capabilities to jump air-gaps transition into common use. Defending against the emerging threat of cyber-enabled physical intrusions is poorly understood. The consequence of these cyber-physical attacks has no quantitative analysis method to inform risk-informed, performance-based cybersecurity approaches. By modifying the physical security simulation tool Dante, cyber-physical threat consequence was able to be analyzed on a notional facility. The results of this analysis are used to design a Defensive Cybersecurity Architecture (DCSA) for the physical security system to produce example resilience measures for this notional facility. A DCSA defines security levels to provide a graded approach for defending plant functions, and security zones for trusted communication between systems. This approach can be applied to real world systems to produce physical protection systems and response measures that are resilient to cyber-physical threats.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Simulations of Grid-Responsive HVAC Cooling Measures via Ice/PCM storage

This study uses EnergyPlus building energy simulations to assess grid-responsive HVAC cooling measures during peak hours having high electricity price, including: lock the high capacity of a two-speed cooling coil during grid-response hours; and use ice/PCM energy storage to drive a chilled water coil and meet the cooling load, when shut off the main electric cooling coil. Here, the impacts on peak power reductions, energy and utility cost savings, and comfort levels in residential buildings of two U.S. cities were revealed.

Shen, Bo↗
DOE OSTI2021

Fission Product Yield Data Adjustment in a Prototype Version of TSURFER

The TSURFER (Tool for Sensitivity/Uncertainty analysis of Response Functionals using Experimental Results) module of Oak Ridge National Laboratory’s (ORNL’s) SCALE code system has been updated to perform nuclear data adjustments for fixed-source irradiation/depletion problems. TSURFER uses a generalized linear least squares (GLLS) approach to consolidate a prior set of measured responses and corresponding calculated values to create the most self-consistent set of nuclear data. Traditionally, TSURFER adjustments have been performed for multigroup nuclear data such as reaction cross sections. In this work, TSURFER is expanded to perform adjustments to independent fission product yields and branching ratios that need equality constraints. To preserve equality constraints after the data adjustment procedure, an updated GLLS formulation includes a new Lagrange multiplier that forces data adjustment to sum to 0 for a given fission yield/branching ratio parent. A test problem illustrates that the newly updated TSURFER module satisfies the required constraint that adjustments for fission yield data sum to 0.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Nonsteady Load Responses to Daytime Atmospheric Turbulence Eddies on the DOE 1.5 MW Wind Turbine at NREL

Field data collected from the NREL/GE 1.5MW wind turbine (WT) and met tower (MetT) at the NREL Wind Technology Center near Boulder, CO June-October 2018 were analyzed to quantify the impacts of turbulence eddies on the load responses measured from sensors on the main shaft, blade and tower. The passage of individual mountain-generated eddies from the met tower to the WT were critically determined by correlating the optimal time shifts in signal between MetT and nacelle anemometers with mean advection time. Loading responses from mountain eddy passage were compared with atmospheric eddies from the north/south, unimpeded by the mountains, and found to be similar. Whereas time variations in torque were highly correlated with time changes in horizontal eddy velocity, the out-of-plane bending moments on the main shaft (directly forcing the main bearing) were uncorrelated with horizontal eddy velocity. This result is consistent with a previous LES study indicating that the main bearing is forced by asymmetrical interactions between the WT rotor and turbulence eddies, while power fluctuations respond primarily to advective eddy velocity. Surprisingly, the nacelle anemometer produced statistics very similar to the MetT.

ENGINEERING,WIND ENERGY↗
DOE OSTI2023

Nonsteady Load Responses to Mountain-Generated Turbulence Eddies on the DOE 1.5 MW Wind Turbine at the National Wind Technology Center

Field data collected from the NREL/GE 1.5MW wind turbine and met tower at the NREL Wind Technology Center near Boulder, Colorado from June-October 2018 were analyzed to quantify the impacts of turbulence eddies on the load responses measured from sensors on the main shaft, blade and tower. The passage of individual mountain-generated eddies from the met tower to the wind turbine were critically determined by correlating the optimal time shifts in signal between met tower and nacelle anemometers with mean advection time. Loading responses from mountain eddy passage were compared with atmospheric eddies from the north/south, unimpeded by the mountains, and found to be similar. Whereas time variations in torque were highly correlated with time changes in horizontal eddy velocity, the out-of-plane bending moments on the main shaft (directly forcing the main bearing) were uncorrelated with horizontal eddy velocity. This result is consistent with a previous LES study indicating that the main bearing is forced by asymmetrical interactions between the rotor and turbulence eddies, while power fluctuations respond primarily to advective eddy velocity. Surprisingly, the nacelle anemometer produced statistics very similar to the met tower.

ENGINEERING,WIND ENERGY↗
DOE OSTI2020

Methodology for inferring reactor core power distribution from an optical fiber based gamma thermometer array

Here, a 4-step data analytic methodology has been devised for the purpose of inferring the distribution of power in a reactor core, based on the response of an array of optical fiber based gamma thermometers (OFBGTs). This data analytic methodology is crucial for the development of a system of OFBGTs for the purpose of calibrating local power range monitors in boiling water reactors. Such a system would be an improvement to the present calibration system in boiling water reactors, in terms of safety, efficiency, and permanence. The first step of this methodology is to establish an energy balance method. In this method, one uses MCNP to determine response functions, which allow one to convert from gamma thermometer response to power. The gamma thermometers and the reactor core are segmented, such that each gamma thermometer segment provides an estimate of power for each reactor core segment. The estimates of power for the reactor core segments (hereafter referred to as fuel assembly segments) are calculated based on the measured response of the gamma thermometers. The second step of the methodology is to employ a weighting scheme to combine the estimates of the power of the various fuel assembly segments, based on the response of the various OFGBT segments and the incremental dose rates of the various fuel assembly segments to the OFBGT segments. The third step is to iteratively calculate the estimates of the power of the fuel assembly segments, until a convergence criterion is met, which indicates that the calculation has converged. The fourth and final step of the methodology is to estimate the uncertainty of the power for each fuel assembly segment. The mathematical basis for this step is not the focus of this paper. We have used a 3-D homogeneous reactor model to demonstrate the data analytic methodology; and have found that the data analytic methodology operates as intended.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗