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DOE OSTI2023

Model Predictive Control-Based Trajectory Shaper for Safe and Efficient Adaptive Cruise Control

Recent studies show that commercially-available adaptive cruise control (ACC) systems are string-unstable, indicating that ACC-driven vehicles amplify speed fluctuations from downstream traffic and induce stop-and-go waves. Moreover, it is challenging to revise the original control algorithm of an ACC system to achieve string stability due to its internal complexity and powertrain uncertainties. To achieve desired control performance given a string-unstable ACC system and circumvent revising the original control algorithm, this study proposes a model predictive control-based trajectory shaper (MPC-TS), which only modifies the sensor-measured trajectory information (i.e., position and speed) of the preceding vehicle. The proposed MPC-TS leverages the input shaping technique to generate reference trajectory to improve string stability, while incorporating tracking errors and vehicle acceleration/deceleration magnitude in the MPC cost function and constraining fluctuations of vehicle speed and spacing to ensure desired car-following performance. Numerical experiments validate the control performance of ACC with the proposed MPC-TS in terms of string stability, safety, traffic efficiency, and comfort.

Zhou, Anye↗

DOE OSTI2021

Advanced Electron Microscopy of Nanophased Synthetic Polymers and Soft Complexes for Energy and Medicine Applications

After decades of developments, electron microscopy has become a powerful and irreplaceable tool in understanding the ionic, electrical, mechanical, chemical, and other functional performances of next-generation polymers and soft complexes. The recent progress in electron microscopy of nanostructured polymers and soft assemblies is important for applications in many different fields, including, but not limited to, mesoporous and nanoporous materials, absorbents, membranes, solid electrolytes, battery electrodes, ion- and electron-transporting materials, organic semiconductors, soft robotics, optoelectronic devices, biomass, soft magnetic materials, and pharmaceutical drug design. For synthetic polymers and soft complexes, there are four main characteristics that differentiate them from their inorganic or biomacromolecular counterparts in electron microscopy studies: (1) lower contrast, (2) abundance of light elements, (3) polydispersity or nanomorphological variations, and (4) large changes induced by electron beams. Since 2011, the Center for Nanophase Materials Sciences (CNMS) at Oak Ridge National Laboratory has been working with numerous facility users on nanostructured polymer composites, block copolymers, polymer brushes, conjugated molecules, organic–inorganic hybrid nanomaterials, organic–inorganic interfaces, organic crystals, and other soft complexes. This review crystalizes some of the essential challenges, successes, failures, and techniques during the process in the past ten years. It also presents some outlooks and future expectations on the basis of these works at the intersection of electron microscopy, soft matter, and artificial intelligence. Machine learning is expected to automate and facilitate image processing and information extraction of polymer and soft hybrid nanostructures in aspects such as dose-controlled imaging and structure analysis.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Sub-Alfvénic Turbulence: Magnetic-to-kinetic Energy Ratio, Modification of Weak Cascade, and Implications for Magnetic Field Strength Measurements

Abstract We study the properties of sub-Alfvénic magnetohydrodynamic (MHD) turbulence, i.e., turbulence with Alfvén mach number M A = V L / V A < 1, where V L is the velocity at the injection scale and V A is the Alfvén velocity. We demonstrate that MHD turbulence can have different properties, depending on whether it is driven by velocity or magnetic fluctuations. If the turbulence is driven by isotropic bulk forces acting upon the fluid, i.e., is velocity driven, in an incompressible conducting fluid we predict that the kinetic energy is M A − 2 times larger than the energy of magnetic fluctuations. This effect arises from the long parallel wavelength tail of the forcing, which excites modes with k ∥ / k ⊥ < M A . We also predict that as the MHD turbulent cascade reaches the strong regime, the energy of slow modes exceeds the energy of Alfvén modes by a factor M A − 1 . These effects are absent if the turbulence is driven through magnetic fluctuations at the injection scale. We confirm our predictions with numerical simulations. Since the assumption of magnetic and kinetic energy equipartition is at the core of the Davis–Chandrasekhar–Fermi (DCF) approach to measuring magnetic field strength in sub-Alfvénic turbulence, we conclude that the DCF technique is not universally applicable. In particular, we suggest that the dynamical excitation of long azimuthal wavelength modes in the galactic disk may compromise the use of the DCF technique. We discuss alternative expressions that can be used to obtain magnetic field strength from observations and consider ways of distinguishing the cases of velocity and magnetically driven turbulence using observational data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Rethinking Coherent Diffraction Instruments for High Brightness Sources

Over the past two decades, exceptional progress has been made providing coherent x-ray beams at both high-brightness synchrotron sources and x-ray free electron lasers (XFEL). The availability of these coherent x-rays has led to a surge in instruments that exploit x-ray coherence for either x-ray photon correlation spectroscopy (XPCS) or coherent diffraction imaging (CDI). A key to these techniques has been to resolve, or at least nearly resolve, the speckles associated with the scattering from structural disorder. Given practical limits on detector pixel size, this requires long sample-to-detector distances. This paper presents numerical simulations of an instrument that can efMiciently provide a long sample-detector distance while maintaining the ability to rapidly set momentum transfer by inserting crystals with different order in the incident beam, thus changing in incident direction instead of moving the detector.

Fuoss, Paul H↗

DOE OSTI2022

A micromorphic filter for determining stress and deformation measures from direct numerical simulations of lower length scale behavior

A micromorphic filter is presented for the extraction of stress and deformation measures from underlying direct numerical simulation (DNS) of microstructural mechanical response. The filter is consistent with the micromorphic continuum theory of Eringen and Suhubi (1964), and allows the interrogation of a DNS to generate higher order constitutive models. The filter adopts aspects of the overlap coupling techniques for atomistic-continuum scale-bridging in order to update the nodal degrees of freedom of the finite-element-based filter. Here, two methods for the extraction of quantities of interest from the underlying DNS are presented. The first is a least squares fitting technique which is appropriate for finite-element-style macro-scale domains, and the second is a variationally based approach which generalizes the method to any macro-scale domain which has a variational form. No restrictions on the form of the micro-scale simulation are inherent to the approach, provided that the required quantities (stress, position, etc.) can be provided. The filter is applied to a simple homogeneous medium undergoing homogeneous deformation to demonstrate the recovery of a classical continuum response, what we call the null case. We then apply the framework to the same homogeneous medium with a central and edge penny-shaped crack to show micromorphic effects. We demonstrate that varying the size of the filter causes the micromorphic behaviors to arise and then dissipate as the filter becomes smaller than the crack's length scale. Additionally we show the effect of filter size on a chiral element network along with a plate perforated with evenly spaced and perturbed holes through the thickness. The micromorphic effects are shown to be present for the chiral elements under any loading but become most pronounced when a single element is located within each averaging domain. Micromorphic effects become pronounced for the plate upon the onset of localization.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Development of an Ultrahigh-bandwidth Phase Contrast Imaging System for detection of electron scale turbulence and Gigahertz Radio-Frequency Waves

The study of waves and turbulence is vital to the development of future reactor-grade plasma devices developed in the quest for fusion energy. These fluctuations are responsible for moving heat and particles across the magnetic field, and a predictive understanding of them is needed to achieve the density and temperature required to sustain a plasma fusion reaction. While many techniques have been developed for measuring waves and fluctuations, every measurement method has limitations. There are relatively few techniques for measuring very high frequency fluctuations, such as radio frequency waves injected to heat the plasma, unstable waves driven by suprathermal particles, or short wavelength electrostatic waves driven by electron temperature or density gradients. The present project builds upon the proven phase contrast imaging (PCI) technique to extend the response of the diagnostic by orders of magnitude in frequency and almost a factor of ten in spatial resolution. PCI provides a measurement of electron density based on small angle scattering of a CO-2 laser beam by using optical techniques to render a phase shift as an intensity change on a detector. Due to the telecommunications revolution, technological development by manufacturers has focused on components in the near -infrared, so that high- quality lasers and detectors at 1.55 µm are readily available. Shifting PCI design to a new, shorter wavelength has numerous advantages and challenges. Similar detector performance is available with room-temperature arrays with GHz bandwidth, while the detector arrays for 10.6 µm required liquid nitrogen cooling and were therefore limited to a bandwidth of about 1 MHz. Shifting to a shorter wavelength reduces the angle at which the laser beam scatters off of plasma waves, allowing more such scattered components to pass through the aperture of the vacuum vessel port and be collected by the PCI, which increases the spatial resolution. Concomitant with these benefits, various questions of performance arise. At shorter laser wave- length, the sensitivity to mirror and lens quality is increased, the contribution of the laser to the overall system noise is increased, and the sensitivity to vibrations is increased. The custom optical components at the heart of the PCI technique were required to be properly scaled for the shorter wavelength, so fabrication technologies needed to be explored. This project was designed to show that a low noise, high response PCI system at 1.55 µm could be constructed and operated, and then to quantify potential issues to allow extrapolation to a full-size production system providing physics measurements on a large plasma device. The first stage, producing the custom optical component called a Phase Plate, was successfully achieved using two methods. First, an easily reproduced masking and coating technique was able to produce good phase plates with the required parameters. Second, a nanofabrication technique was found to produce extremely high quality phase plates at a competitive price. The PCI constructed with the new phase plates and 1.55 µm laser was found to provide excellent wavelength measurements with the theoretically expected response. The sensitivity to optical surface quality was found to be in line with previous measurements at 10.6 µm. The observed signal-to-noise ratio was similar to the theoretically expected value. The effect of vibrations on PCI was studied with the first measurement of the effect of beam motion on PCI response and comparison to theory, allowing for a quantitative prediction of the effect of vibrations on a production PCI system and the requirements for improved beam stabilization. PCI is an extremely cost-effective method to provide a low noise, absolutely calibrated measurement of plasma fluctuations across a wide spatial scale. This project has shown that a 1.55 µm PCI using modern techniques and components is less expensive than the 10.6 µm PCI of a few years ago, with the largest savings in phase plate fabrication and the infrared detector array.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Approximate inverse-based block preconditioners in poroelasticity

We focus on the fully implicit solution of the linear systems arising from a three-field mixed finite element approximation of Biot’s poroleasticity equations. The objective is to develop algebraic block preconditioners for the efficient solution of such systems by Krylov subspace methods. In this work, we investigate the use of approximate inverse-based techniques to decouple the native system of equations and obtain explicit sparse approximations of the Schur complements related to the physics-based partitioning of the unknowns by field type. Here, the proposed methods are tested in various numerical experiments including real-world applications dealing with petroleum and geotechnical engineering.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Machine Learning technique for isotopic determination of radioisotopes using HPGe γ-ray spectra

γ-ray spectroscopy is a quantitative, non-destructive technique that may be utilized for the identification and quantitative isotopic estimation of radionuclides. Traditional methods of isotopic determination have various challenges that contribute to statistical and systematic uncertainties in the estimated isotopics. Furthermore, these methods typically require numerous pre-processing steps, and have only been rigorously tested in laboratory settings with limited shielding. Here, in this work, we examine the application of a number of machine learning based regression algorithms as alternatives to conventional approaches for analyzing γ-ray spectroscopy data in the Emergency Response arena. This approach not only eliminates many steps in the analysis procedure, and therefore offers potential to reduce this source of systematic uncertainty, but is also shown to offer comparable performance to conventional approaches in the Emergency Response Application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Autonomous aerial flight path inspection using advanced manufacturing techniques

Robotic systems have shown capabilities to perform inspection tasks in dangerous and difficult-to-access environments, such as those found in different components of power plants. However, most of the current robotic inspection technology is designed for specific components. Aerial robots, commonly termed as Drones, have raised an option to inspect a wider range of structural components. Nevertheless, current aerial inspecting technology still relies on a human pilot with limited line of sight, field of view and a reduced perception as the drone flies away, which prevents performing close-quarter inspection in intricate, structurally complex and GPS-denied environments. This work introduces offline inspection path generation methods based on robotics-integrated to manufacturing techniques. One method uses computer-aided manufacturing (CAM) techniques and the other an additive manufacturing (AM) approach to generate the flight path. That is to say, the drone would fly along the path described by a 3D (Three Dimensional) printer’s extruder or a CNC (Computer Numerical Control) machining tool, enabling to fly very close the structure even in physical structures with a complex geometry. Once the trajectories are generated, they are introduced for its validation in the Gazebo robotics simulator. Simulation results demonstrate the proper performance of the method and confirm that this approach can be used for close inspection of structural components.

42 ENGINEERING↗

DOE OSTI2020

Extended Lagrangian Born–Oppenheimer molecular dynamics using a Krylov subspace approximation

It is shown how the electronic equations of motion in extended Lagrangian Born–Oppenheimer molecular dynamics simulations can be integrated using low-rank approximations of the inverse Jacobian kernel. This kernel determines the metric tensor in the harmonic oscillator extension of the Lagrangian that drives the evolution of the electronic degrees of freedom. The proposed kernel approximation is derived from a pseudoinverse of a low-rank estimate of the Jacobian, which is expressed in terms of a generalized set of directional derivatives with directions that are given from a Krylov subspace approximation. The approach allows a tunable and adaptive approximation that can take advantage of efficient preconditioning techniques. The proposed kernel approximation for the integration of the electronic equations of motion makes it possible to apply extended Lagrangian first-principles molecular dynamics simulations to a broader range of problems, including reactive chemical systems with numerically sensitive and unsteady charge solutions. This can be achieved without requiring exact full calculations of the inverse Jacobian kernel in each time step or relying on iterative non-linear self-consistent field optimization of the electronic ground state prior to the force evaluations as in regular direct Born–Oppenheimer molecular dynamics. We note the low-rank approximation of the Jacobian is directly related to Broyden’s class of quasi-Newton algorithms and Jacobian-free Newton–Krylov methods and provides a complementary formulation for the solution of nonlinear systems of equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Volumetric Rendering on Wavelet-Based Adaptive Grid

Numerical modeling of physical phenomena frequently involves processes across a wide range of spatial and temporal scales. In the last two decades, the advancements in wavelet-based numerical methodologies to solve partial differential equations, combined with the unique properties of wavelet analysis to resolve localized structures of the solution on dynamically adaptive computational meshes, make it feasible to perform large-scale numerical simulations of a variety of physical systems on a dynamically adaptive computational mesh that changes both in space and time. Volumetric visualization of the solution is an essential part of scientific computing, yet the existing volumetric visualization techniques do not take full advantage of multi-resolution wavelet analysis and are not fully tailored for visualization of a compressed solution on the wavelet-based adaptive computational mesh. Our objective is to explore the alternatives for the visualization of time-dependent data on space-time varying adaptive mesh using volume rendering while capitalizing on the available sparse data representation. Two alternative formulations are explored. The first one is based on volumetric ray casting of multi-scale datasets in wavelet space. Rather than working with the wavelets at the finest possible resolution, a partial inverse wavelet transform is performed as a preprocessing step to obtain scaling functions on a uniform grid at a user-prescribed resolution. As a result, a solution in physical space is represented by a superposition of scaling functions on a coarse regular grid and wavelets on an adaptive mesh. An efficient and accurate ray casting algorithm is based just on these coarse scaling functions. Additional details are added during the ray tracing by taking an appropriate number of wavelets into account based on support overlap with the interpolation point, wavelet coefficient magnitude, and other characteristics, such as opacity accumulation (front to back ordering) and deviation from frontal viewing direction. The second approach is based on complementing of wavelet-based adaptive mesh to the traditional Adaptive Mesh Refinement (AMR) mesh. Both algorithms are illustrated and compared to the existing volume visualization software for Rayleigh-Benard thermal convection and electron density data sets in terms of rendering time and visual quality for different data compression of both wavelet-based and AMR adaptive meshes.

Vezolainen, Alexei V.↗

DOE OSTI2022

CO 2 zonal injection rate allocation and plume extent evaluation through wellbore temperature analysis

Temperature analysis during a pause in injection operations, known as warmback analysis, has been used in the petroleum industry for evaluating the injection conformance and estimating the location of the flooded front in applications, such as waterflooding oil reservoirs. Here in this work, methods are introduced to extend the application of temperature warmback analysis to estimate the zonal CO 2 injection rate and zonal CO 2 plume extent during geologic CO 2 storage in a saline aquifer. First, novel analytical solutions are developed to model transient temperature in the aquifer during the injection and subsequent shut-in periods considering two-phase flow (gaseous CO 2 and aqueous brine) conditions in the aquifer. The solution involves a discretization of the aquifer into regions; the energy and mass conservation equations for the regions are solved simultaneously considering appropriate boundary conditions at the interfaces. Two solutions techniques are presented: multi-region and three-region solutions. Inverse models are developed accordingly to evaluate the injection profile and estimate the extent of the plume front in the reservoir during the injection period. The multi-region solution results in an inversion approach that requires regression analysis. However, the three-region formulation results in a simple graphical technique for inverse modeling. The analytical solutions are validated against a thermally coupled reservoir simulation tool using different synthetic cases for CO 2 injection in deep saline aquifers. The results of the developed solutions provide a good match with numerical results during forward and inverse modeling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Assessment of effective elastic constants of U-10Mo fuel: A multiscale modeling and homogenization study

The significant microstructural changes that U-Mo fuel undergoes during operation degrades its mechanical properties and structural integrity. Microstructural evolution entails the formation, evolution, and redistribution of porosity in conjunction with grain refinement. In the present paper, we employ numerical approaches to assess the impact of the various microstructural features—grains, nanoscale intragranular fission gas bubbles, and mesoscale intergranular voids—on the degradation of elastic constants. Phase-field microstructure models are combined with the asymptotic expansion homogenization technique in order to derive the effective elastic constants as a function of porosity and fission density. Here the results are verified and compared against theoretical bounds. Using this approach, elastic degradation in operating nuclear fuels can be quantified when the distributions of microstructural features are known.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Ultra-short pulse generation from mid-IR to THz range using plasma wakes and relativistic ionization fronts

In this work, we discuss numerical and experimental results on frequency downshifting and upshifting of a 10 μ m infrared (IR) laser to cover the entire wavelength (frequency) range from λ = 1 to 150 μ m ( ν = 300–2 THz) using two different plasma techniques. The first plasma technique utilizes frequency downshifting of the drive laser pulse in a nonlinear plasma wake. Based on this technique, we have proposed and demonstrated that in a tailored plasma structure, multi-millijoule energy, single-cycle, long-wavelength IR (3–20 μ m) pulses can be generated by using an 810 nm Ti:sapphire drive laser. Here, we extend this idea to the THz frequency regime. We show that sub-joule, terawatts, single-cycle terahertz (2–12 THz or 150–25 μ m) pulses can be generated by replacing the drive laser with a picosecond 10 μ m CO 2 laser and a different shaped plasma structure. The second plasma technique employs frequency upshifting by colliding a CO 2 laser with a rather sharp relativistic ionization front created by ionization of a gas in less than half cycle (17 fs) of the CO 2 laser. Even though the electrons in the ionization front carry no energy, the frequency of the CO 2 laser can be upshifted due to the relativistic Doppler effect as the CO 2 laser pulse enters the front. The wavelength can be tuned from 1 to 10 μ m by simply changing the electron density of the front. While the upshifted light with 5 < λ ( μ m ) < 10 propagates in the forward direction, that with 1 < λ ( μ m ) < 5 is back-reflected. These two plasma techniques seem extremely promising for covering the entire molecular fingerprint region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

ML-Based Power System Stability Assessment Considering Network Topology Changes: WECC 20,000+ Bus System Case Study

Modern power grids are fast-changing and thus require real-time monitoring and online stability assessment. With the rapid development of machine learning (ML) techniques, using data-driven models to provide fast and accurate estimations of power system stability marginal information, such as frequency nadir for frequency stability and critical clearing time (CCT) for transient stability, have become possible. However, despite the numerous research on ML-based methods for frequency nadir and CCT prediction, there is limited work on the impact of different network topology changes. Furthermore, most previous studies only focused on small or synthetic systems, and there is a lack of research on actual large power system models. In this paper, the above issues are addressed by studying the actual U.S. Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. Massive simulations are conducted in PowerWorld Simulator to study the impact of various topology change scenarios on both frequency stability and transient stability. System operating information is extracted from the success dispatch cases of various network topologies to generate a comprehensive dataset for ML-based models. Two ML methods, random forest (RF) and multilayer perceptron (MLP) neural network, are trained and tested for both frequency nadir prediction and CCT prediction. Test results have proven the models are capable of online stability assessment for large power networks such as the WECC system with sufficient accuracy.

critical clearing time↗

DOE OSTI2025

Hybrid chemical characterization of latent images in EUV resist with 12 nm half-pitch features

With the advancement of high numerical aperture extreme ultraviolet (EUV) lithography, the new platform will enable chipmakers to achieve critical dimensions of 8 nm. However, resist materials face significant challenges in delivering increased sensitivity while managing rising stochastic variations. We aim to develop comprehensive techniques to characterize the chemical profile of latent images, stored in EUV resists after exposure and postexposure baking, which is essential for understanding the origin of stochastic effects. Infrared photo-induced force microscopy (IR PiFM) is a bimodal atomic force microscopy technique combined with an infrared light source, allowing for simultaneous sub-5 nm topographic and chemical characterization within a localized environment. Critical-dimension resonant soft X-ray scatterometry (CD-RSoXS) provides statistical data that reveal structural and chemical information for comparative analysis. For the first time, IR PiFM has been used to chemically map the latent images of EUV resists (after exposure and postexposure baking) at a record high resolution of 12 nm half-pitch, enabling nondestructive analysis of patterns prior to development. Furthermore, CD-RSoXS offers direct experimental observation and comparison of exposed, postexposure baked, and developed patterns, which align with the IR PiFM results. We demonstrate that the IR PiFM technique offers valuable insights into both high spatial resolution and local chemical information simultaneously. In addition, CD-RSoXS provides statistical results that support our main findings. This hybrid metrology approach leverages a multifaceted dataset by combining the most reliable information from each source, which is essential for a comprehensive understanding of the stochastic effects in EUV lithography processes.

O’Reilly, Padraic↗

DOE OSTI2023

Concordance

Dimension reduction techniques have long been an important topic in statistics, and active subspaces (AS) have received much attention this past decade in the computer experiments literature. The most common approach towards estimating the AS is to use Monte Carlo with numerical gradient evaluation. This software takes a new approach towards estimating the active subspace, in which Multivariate Adaptive Regression Splines (MARS) is used as a surrogate model, and relevant calculation are obtained analytically. Using a MARS surrogate has many advantages including improved scaling, better estimation of active subspaces in high dimensions and the ability to handle a large number of prior distributions in closed form. This software is also capable of conducting a so-called "concordance analysis", using a generalization of ASs which we refer to as "Co-Active" subspaces.

Rumsey, Kelin↗

DOE OSTI2025

Evidence for a Single Holocene Paleoseismic Event on the Pajarito Fault, Northern New Mexico

Low-slip rate fault systems tend to be less studied than their high-slip rate counterparts, and paleoseismic techniques used to study them may pose challenges in interpretation that differ from high-slip rate systems. A good example of this is the Pajarito fault system (PFS), a normal fault complex within the Rio Grande rift. Despite numerous previous paleoseismic trenching studies conducted on the PFS between 1990 and 2003, considerable uncertainty remains regarding its Holocene paleoseismic history, particularly for the primary Pajarito fault (PF). To further clarify the PF paleoseismic history, we present data from paleoseismic investigations of 6 trenches at 3 distinct locations along the PF. Though the totality of the age and structural data obtained in this study is complex and not entirely consistent with any one interpretation, a single Holocene paleoearthquake occurring younger than ∼1,600 to 2,300 kcal yr BP is the simplest interpretation. It is possible that the PF records two Holocene events, with a penultimate event 6.9–2.4 kcal yr BP event and the aforementioned most recent event (MRE) between 2.3 and 1.6 kcal yr BP. However, only a single wall of one trench, out of a total of 12 walls in our 6 trenches, provides evidence supporting that interpretation. This study finds evidence of a single late Holocene paleoseismic event on the PF and sparse evidence for 2 Holocene paleoseismic events on the PF and highlights the benefits of logging multiple trench walls to better understand the complexity that results from this low-slip rate, low-deposition-rate fault system.

58 GEOSCIENCES↗