Results for “field validation” — Page 51

DOE OSTI2020

Adaptive Multirate Mass Transfer (aMMT) Model: A New Approach to Upscale Regional‐Scale Transport Under Transient Flow Conditions

Abstract The long‐term evaluation of regional‐scale groundwater quality needs efficient upscaling methods for transient flow. Upscaling techniques, such as the Multirate Mass Transfer (MRMT) method with constant upscaling parameters, have been used for transport with steady‐state flow, yet the upscaling parameters (i.e., rate coefficients) may be time dependent. This study proposed and validated an adaptive MRMT (aMMT) method by allowing the mass transfer coefficients in MRMT to change with the flow field. Advective‐dispersive contaminant transport simulated in a 3‐D heterogeneous medium was used as a reference solution. Equivalent transport under homogeneous flow conditions was evaluated by applying the MRMT and aMMT models for upscaling. The relationship between mass transfer coefficients and flow rates was fitted under steady‐state flow driven by various hydraulic gradients. A power law relationship was obtained, which was then used to update the mass transfer coefficients in each stress period under transient flow conditions in the aMMT method. Results indicated that for advection‐dominated transport, both the MRMT and aMMT methods can upscale the anomalous transport dynamics affected by subgrid heterogeneity under transient flow conditions. Whereas for diffusion‐dominated systems, the MRMT model failed to capture the tails of tracer breakthrough curves after the boundary condition changed, but the results from the aMMT model were significantly improved. However, if the overall flow direction changed, both MRMT and aMMT failed to represent the breakthrough curve tail generated by the heterogeneous system. The results point toward a promising path for upscaling transport in complex aquifers with transient flow.

Guo, Zhilin↗

DOE OSTI2023

Embedding security into ferroelectric FET array via in situ memory operation

Non-volatile memories (NVMs) have the potential to reshape next-generation memory systems because of their promising properties of near-zero leakage power consumption, high density and non-volatility. However, NVMs also face critical security threats that exploit the non-volatile property. Compared to volatile memory, the capability of retaining data even after power down makes NVM more vulnerable. Existing solutions to address the security issues of NVMs are mainly based on Advanced Encryption Standard (AES), which incurs significant performance and power overhead. In this paper, we propose a lightweight memory encryption/decryption scheme by exploiting in-situ memory operations with negligible overhead. To validate the feasibility of the encryption/decryption scheme, device-level and array-level experiments are performed using ferroelectric field effect transistor (FeFET) as an example NVM without loss of generality. Besides, a comprehensive evaluation is performed on a 128 × 128 FeFET AND-type memory array in terms of area, latency, power and throughput. Compared with the AES-based scheme, our scheme shows ~22.6×/~14.1× increase in encryption/decryption throughput with negligible power penalty. Furthermore, we evaluate the performance of our scheme over the AES-based scheme when deploying different neural network workloads. Our scheme yields significant latency reduction by 90% on average for encryption and decryption processes.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Conservative discontinuous Galerkin scheme of a gyro-averaged Dougherty collision operator

Here, a conservative discontinuous Galerkin scheme for a non-linear Dougherty collision operator in full-f long-wavelength gyrokinetics is presented. Analytically this model operator has the advective-diffusive form of Fokker-Planck operators, it has a non-decreasing entropy functional, and conserves particles, momentum and energy. Discretely these conservative properties are maintained exactly as well, independent of numerical resolution. In this work the phase space discretization is performed using a novel version of the discontinuous Galerkin scheme, carefully constructed using concepts of weak equality and recovery. Discrete time advancement is carried out with an explicit time-stepping algorithm, whose stability limits we explore. The formulation and implementation within the long-wavelength gyrokinetic solver of Gkeyll are validated with relaxation tests, collisional Landau-damping benchmarks and the study of 5D gyrokinetic turbulence on helical, open field lines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Predictive turbulence-driven flux model of scrape-off layer widths across confinement regimes in tokamaks

Reliable scrape-off layer (SOL) profile decay lengths predictions are needed to design and operate future tokamaks. The present manuscript describes a new model based on turbulent transport that is able to predict SOL widths for both L-mode and H-mode plasmas. The model is based upon the sheared-spectral filament paradigm (Peret et al (WEST Team) 2022 Phys. Plasmas 29 072306), however, incorporating the effects of thermal transport in order to calculate the parallel heat fluxes. The effects of magnetic shear and ExB shear on the cross-field transport are crucial to explain the shorter SOL decay lengths found in H-mode. The model is validated against a database of thousands of DIII-D L-mode and H-mode SOL profiles. We also calculate SOL decay length predictions in terms of plasma and engineer control parameters, which are in agreement with the multi-machine empirical H-mode scaling (Eich et al (ASDEX Upgrade Team and JET EFDA Contributors) 2013 Nucl. Fusion 53 093031), however, with an additional device geometry dependence. ITER SOL width predictions by the model are 3 times higher than the empirical scaling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Quantum Filtering and Analysis of Multiplicities in Eigenvalue Spectra

Fine-grained spectral properties of quantum Hamiltonians, including both eigenvalues and their multiplicities, provide useful information for characterizing many-body quantum systems as well as for understanding phenomena such as topological order. Extracting such information with small additive error is #BQP-complete in the worst case. In this work, we introduce QFAMES (quantum filtering and analysis of multiplicities in eigenvalue spectra), a quantum algorithm that efficiently identifies clusters of closely spaced dominant eigenvalues and determines their multiplicities under physically motivated assumptions, which allows us to bypass worst-case complexity barriers. QFAMES also enables the estimation of observable expectation values within targeted energy clusters, providing a powerful tool for studying quantum phase transitions and other physical properties. We validate the effectiveness of QFAMES through numerical demonstrations, including its applications to characterizing quantum phases in the transverse-field Ising model and estimating the ground-state degeneracy of a topologically ordered phase in the two-dimensional toric code model. We also generalize QFAMES to the setting of mixed initial states. Our approach offers rigorous theoretical guarantees and significant advantages over existing subspace-based quantum spectral analysis methods, particularly in terms of the sample complexity and the ability to resolve degeneracies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Applicability of semiclassical methods for modeling laser-enhanced fusion rates in a realistic setting

In the context of the potential laser-induced enhancement to the rates of DHe 3 and DT fusion, we discuss the frequently-used Wentzel-Kramers-Brillouin (WKB) method and the imaginary-time method (ITM). For static external electric fields, we find that these methods predict significant enhancement to the fusion cross section for electric-field strengths > 10 14 V/m, especially at low values (≈ keV) for the enter-of-mass (CoM) energy. When considering dynamic electric fields, this enhancement can be amplified by considering increased photon frequencies. However, we also pro- vide a review of the region of laser-parameter phase space where these semiclassical methods are applicable. Here, we conclude that this allowable region decreases for higher photon frequencies in con-junction with lower values for the electric-field strength, motivating the need for future experiments to test the predictions of these methods and their ranges of validity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Experimental study correlating damage and permeability in concrete using confined, flattened Brazilian disks

This research experimentally studies coupled hydro-mechanical relationships using flattened Brazilian disks under confinement, with concurrent permeability measurements and acoustic emission monitoring. A series of tests are performed on concrete, as representative samples of brittle geo-materials, under a range of confining stresses between 2.76 and 13.79 MPa. Acoustic emission data is used to quantify damage and identify damage thresholds. Damage is then correlated to pre-peak changes in permeability. The advancement of models that couple transport properties to mechanical responses are of interest in the fields of carbon sequestration, hydrofracking, production of geothermal energy, induced seismicity, and underground nuclear waste storage, and these experiments validate a novel experimental approach towards investigating hydro-mechanical relationships.

Boyce, S.↗

DOE OSTI2026

Status Update of Permanent Magnet Radiation Resiliency Studies at CEBAF

The proposed energy upgrade of the Continuous Electron Beam Accelerator Facility (CEBAF) incorporates Fixed-Field Alternating-gradient (FFA) arcs utilizing permanent magnet technology. Given the radiation environment within the CEBAF tunnel enclosure, validating the long-term magnetic stability of these materials is a critical step for the project's technical feasibility. This contribution presents an overview of the ongoing permanent magnet radiation resiliency program at Jefferson Lab. We briefly review the experimental methodology used to monitor demagnetization in situ and summarize the operational experience from the initial data-taking campaign. Furthermore, we discuss the upgrades implemented for the second exposure campaign, currently underway, which aims to refine dose correlation and reduce systematic uncertainties. We report on the general status of the program and the roadmap for certifying permanent magnet optics for the proposed upgrade energies.

Bodenstein, R. [Thomas Jefferson National Accelera↗

DOE OSTI2022

Experimental Investigation of Low-Frequency Distributed Acoustic Strain-Rate Responses to Propagating Fractures

Summary Low-frequency distributed acoustic sensing (LF-DAS) responds to strain changes due to far-field fracture propagation. To better understand the LF-DAS response to fracture propagation, we performed laboratory-scale hydraulic fracture experiments with embedded optical strain sensors. The objectives of this research are to generate hydraulic fractures of known geometry, measure the strain response along the embedded fiber-optic cable comparable to LF-DAS measurements, and use the results to inform the interpretation of field-derived LF-DAS data. The experiments were conducted in unconfined transparent cubic blocks with a dimension of 8 in. on each side. The block was made of transparent epoxy to visualize the fracture propagation. Fiber-optic sensing cables were embedded in the block at different distances to the source of injection. We injected dyed water through an injection tubing to generate a transverse, radial fracture along an initial flaw. An optical interrogator recorded the response of offset fiber Bragg grating (FBG) strain sensors normal to the plane of the fracture. The strain data were visualized on a waterfall plot, akin to visualizations of field-derived LF-DAS data. Dimensional analysis was used to scale the laboratory results to field conditions. We compared the evolution of the strain response at the fiber-optic cable, injection pressure, and rate with known fracture geometry. The measured strains were compared with Sneddon’s (1946) linear elastic solution for a penny-shaped crack and found to follow this behavior. The generated radial fractures in transparent media can be modeled with Sneddon’s linear elastic radial fracture model and a Mode I critical stress intensity factor. The LF-DAS characteristic response of a narrowing region of extension surrounded by compression was exhibited as a fracture that approached and intersected the fiber-optic cable. The experimentally derived strain and strain-rate waterfall plots with known fracture geometry, injection rate, and pressure response provide insight in understanding LF-DAS responses in the field. Furthermore, we developed a method to estimate fracture geometry evolution from the fiber-optic strain data and validated the method against the experimental data.

Engineering↗

DOE OSTI2021

Review of the November 11, 1905 Earthquake: Seismic Intensity Data, Magnitude, and Location Report

The macroseismic location and magnitude of the Shoshone 1905 earthquake has been based on the application of objective and quantitative approaches that produce estimates of earthquake source location and magnitude, and associated uncertainties. The performance of all three approaches applied depends critically on the characteristics of the seismic intensity field. Regional intensity attenuation relations were derived based on a calibration set of earthquakes and then, the procedure was validated using three independent very recent events. The macroseismic epicenter location was determined by either a grid search procedure, the spatial distribution of the sites experiencing the largest intensities, or a combination of both. The macroseismic magnitude estimates are based on the derived regional intensity attenuation relations. There is consistency in the location and magnitude of the November 1905 earthquake as obtained by the three methods. The overlapping region of the 68% bootstrap resampling solutions suggests a reliable epicenter location within 41.550N ? 42.060N and 113.478W ? 112.320W. This region encloses the original Oaks (1992) epicenter location. Macroseismic magnitude estimates range between 5.87 and 6.05.

58 GEOSCIENCES↗

DOE OSTI2022

Strain Gauge Diagnostic Development for use in Vessel Health Monitoring for Hydro-shots

Six-foot vessels are a crucial component to protecting high fidelity equipment at DARHT. Analysis shows these vessels have a limited life span (~10 shots) due to fatigue, ratcheting, and damage accumulation. Vessel health monitoring and diagnostics can help inform decision on a vessel’s fitness for service. Strain gauges are an easy and effective sensor for use in vessel health monitoring. In early March, J-2 executed a qualification shot, uniform blast loading with minimal fragments, with bi-axial strain gauges fielded at four locations around vessel. Several damage features were extracted from the data, and frequency content helps to validate computer modelling of the vessel response. Permanent plastic strain at each location was significant with location one having the most strain at the end state, with 230 micro-strain. However, residual pressure in the vessel could be a major factor in this strain. PEEQ is a measure of total plastic equivalent strain accumulation. The equivalent strain at location one exceeded the plastic strain limit four times and accumulated the most PEEQ with 2036 micro-strain. As expected, this qualification shot did contribute to damage in the vessel, and should be considered in its fitness for service, but not critical enough to pull it from service. Frequency content also gave valuable information on the modal response of the vessel and contributes to the understanding of how the vessel responds to the initial blast load with an expected lower frequency membrane/breathing mode and transitioning to higher frequency bending modes in the vessel wall.

42 ENGINEERING↗

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 OSTI2025

Collaborative Proposal: Improving understanding of the internal structure and dynamics of deep convection using ARM observations and large eddy simulations

Recent observational and large eddy simulation (LES) modeling studies have nearly unanimously supported the view of deep cumulus convection being composed of a series of quasi-spherical bubbles of buoyant air, known as moist thermals. Despite the prevalence of moist thermals in deep convection, a comprehensive theory for the dynamics of these structures is lacking. Most current conceptual models for cumulus convection are based on canonical scaling theories for dry thermals or plumes; however, there is considerable evidence that the behavior of moist thermals differs markedly from these theories. Furthermore, the theoretical basis for most cumulus parameterizations originates from the plume conceptual model, and therefore these parameterizations are inconsistent with the real structure of moist convection. Motivated by the aforementioned knowledge gaps, this “end-to-end” research effort use theory, observations, numerical simulations, and direct improvements to the Zhang-McFarlane (ZM) convection scheme in the global climate Community Atmosphere Model (CAM) to address the following research questions: What key environmental parameters determine whether or not shallow convection will transition into deep convection, in the context of thermal-like updrafts? What factors regulate the size of thermals within cumulus updrafts? How does vertical wind shear influence thermal behavior, and as a consequence, vertical velocity and mass flux profiles and the shallow-to-deep convective transition? What are the critical processes that determine updraft vertical velocities and their connection to the vertical mass flux profile for thermal-like updrafts? Idealized LES modeling will be used in conjunction with theoretical models for the core properties of thermal-like updrafts to better understand key processes that regulate thermal ascent rates and entrainment properties. Thermal-tracking procedures will be used to characterize the behavior of thermals within the LES, and recently developed direct measures of entrainment and detrainment will be used to quantify entrainment/detrainment rates. Building from these results, we will analyze the structure of moist thermals from hemispheric range-height indicator scans taken during the Atmospheric Radiation Measurement Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign, and from “real case” LES of CACTI events. This combined modeling and observational analysis will provide essential validation for the existing body of research on moist thermal dynamics, which is based primarily on modeling studies. With the insight gained from the aforementioned activities, we will modify the Zhang-McFarlane convection scheme to improve its representation of updraft vertical velocity and entrainment rate profiles. These process-level changes will be tested in the Community Atmosphere Model to assess the impact on global climate simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

A Novel Method for Setting Meaningful Thresholds for RMS-Energy Oscillation Detectors

Oscillation detection and mitigation is a crucial aspect of reliable power system operation. Several transmission system operators and reliability coordinators use the RMS-energy method of oscillation detection, but the process of setting thresholds is time and labor intensive. The current industry practice in the United States is to set thresholds based on the RMS-energy's value during ambient conditions, which can often lead to nuisance alarms that require thresholds to be manually retuned. In this paper, we propose a method for setting RMS-energy thresholds that directly accounts for oscillation amplitudes specified by the user. A theoretical analysis of the statistical properties of the RMS-energy incorporates these user-specified amplitudes, resulting in thresholds that reliably detect oscillations of interest while avoiding nuisance alarms. Theoretical results are validated with simulated measurements and the real-world practicality of the method is established with publicly available field-measured data from the Grid Event Signature Library.

Follum, James D.↗

DOE OSTI2025

Edge ML for CAN bus intrusion detection in AVs

Autonomous Vehicles (AVs) are revolutionizing transportation, but their reliance on interconnected cyber-physical systems exposes them to unprecedented cybersecurity risks. This study addresses the critical challenge of detecting real-time cyber intrusions in self-driving vehicles by leveraging a dataset from the Udacity self-driving car project. We simulate four high-impact attack vectors, Denial of Service (DoS), spoofing, replay, and fuzzy attacks, by injecting noise into spatial features (e.g., bounding box coordinates) to replicate adversarial scenarios. We develop and evaluate two lightweight neural network architectures (NN-1 and NN-2) alongside a logistic regression baseline (LG-1) for intrusion detection. The models achieve exceptional performance, with NN-2 attaining an AUC score of 93.15% and 93.15% accuracy, demonstrating their suitability for edge deployment in AV environments. Through explainable AI techniques, we uncover unique forensic fingerprints of each attack type, such as spatial corruption in fuzzy attacks and temporal anomalies in replay attacks, offering actionable insights for feature engineering and proactive defense. Visual analytics, including confusion matrices, ROC curves, and feature importance plots, validate the models' robustness and interpretability. This research sets a new benchmark for AV cybersecurity, delivering a scalable, field-ready toolkit for Original Equipment Manufacturers (OEMs) and policymakers. By aligning intrusion fingerprints with SAE J3061 automotive security standards, we provide a pathway for integrating machine learning into safety-critical AV systems. Our findings underscore the urgent need for security-by-design AI, ensuring that AVs not only drive autonomously but also defend autonomously. This work bridges the gap between theoretical cybersecurity and life-preserving engineering, offering a leap toward safer, more secure autonomous transportation.

97 MATHEMATICS AND COMPUTING↗