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At least 1,657 records · Page 92

Real-Time FPGA Implementation For Frequency Sweep Interferometry In The LBNF Complex

The Long Baseline Neutrino Facility (LBNF) will deliver a 2.4 MW muon neutrino beam from Fermilab to the Deep Underground Neutrino Experiment (DUNE), requiring unprecedented precision in beamline alignment to achieve DUNE's neutrino oscillation measurement goals. Vertical misalignments of beamline components as small as 0.5 mm can contribute 6-7\% uncertainty in predicted neutrino flux, necessitating sub-0.1 mm alignment monitoring capabilities. The Horn Location Sensor (HLS) system employs frequency sweep interferometry (FSI) in a distributed hydrostatic leveling network to achieve the required precision under harsh radiation conditions up to 5000 kRad/year. Traditional FSI implementations suffer from laser sweep nonlinearities that degrade resolution and require computationally intensive post-processing corrections using gas reference cells. This work presents a real-time FPGA-based implementation of the HLS data acquisition and processing system using a sweep tracker interferometer for dynamic sweep linearization. The system utilizes a PYNQ-Z2 FPGA with programmable logic implementing parallel 16k-point FFT processing across four channels, synchronized by the sweep tracker signal to eliminate post-processing requirements. Spectral performance testing demonstrates significant improvements in peak sharpness compared to traditional fixed-frequency digitization. The FPGA implementation enables real-time displacement monitoring with processing speeds orders of magnitude faster than software-based approaches, essential for the operational requirements of LBNF's eventual distributed sensor network. This advancement in real-time FSI processing directly supports DUNE's precision neutrino physics program by providing the rapid feedback necessary for maintaining stringent beamline alignment tolerances during high-power beam operations.

Rossel, A. Jacob [Fermilab; Unlisted]↗

Insights from a workplace SARS-CoV-2 specimen collection program, with genomes placed into global sequence phylogeny

In 2020, the Department of Energy established the National Virtual Biotechnology Laboratory (NVBL) to address key challenges associated with COVID-19. As part of that effort, Pacific Northwest National Laboratory (PNNL) established a capability to collect and analyze specimens from employees who self-reported symptoms consistent with the disease. During the spring and fall of 2021, 688 specimens were screened for SARS-CoV-2, with 64 (9.3%) testing positive using reverse-transcriptase quantitative PCR (RT-qPCR). Of these, 36 samples were released for research. All 36 positive samples released for research were sequenced and genotyped. Here, the relationship between patient age and viral load as measured by Ct values was measured and determined to be only weakly significant. Consensus sequences for each sample were placed into a global phylogeny and transmission dynamics were investigated, revealing that the closest relative for many samples was from outside of Washington state, indicating mixing of viral pools within geographic regions.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic Networks for On Demand Degradable Adhesives, Scaffolds and Templates (Abbreviated Final Report)

This feasibility study was motivated by a need for alternative mandrel materials to meet the next generation of inertial confinement fusion (ICF) ablator capsules. In response, a new polymer material based on reversible covalent bonds was proposed, with the objective to design thermosets to withstand elevated temperatures (140-200 degrees Celsius) while also being thermally degradable on-demand via controlled decomposition at temperatures above 200 degrees Celsius. A series of cyclopentadiene (Cp) containing thermosets were designed and synthesized to evaluate curing, reversibility and degradability controlled via retro-Diels Alder reactions using Cp-cycloaddition adducts as crosslinks. Ultimately, the current iteration of materials and strategy pursued in this study was assessed as impractical for meeting the needs and objectives of Lawrence Livermore National Laboratory’s (LLNL) target fabrication program.

36 MATERIALS SCIENCE↗

A numerical solver for investigating the space charge effect on the electric field in liquid argon time projection chambers

This paper reports the development of a numerical solver aimed to simulate the interaction between the space charge (i.e. ions) distribution and the electric field in liquid argon time projection chamber (LArTPC) detectors. The ion transport equation is solved by a time-accurate, cell-centered finite volume method and the electric potential equation by a continuous finite element method. The electric potential equation updates the electric field which provides the drift velocity to the ion transport equation. The ion transport equation updates the space charge density distribution which appears as the source term in the electric potential equation. The interaction between the space charge distribution and the electric field is numerically simulated within each physical time step. The convective velocity in the ion transport equation can include the background flow velocity in addition to the electric drift velocity. The numerical solver has been parallelized using the Message Passing Interface (MPI) library. Numerical tests show and verify the capability and accuracy of the current numerical solver. It is planned that the developed numerical solver, together with a Computational Fluid Dynamics (CFD) package which provides the flow velocity field, can be used to investigate the space charge effect on the electric field in large-scale particle detectors.

42 ENGINEERING↗

Kinemetrics Q330M+ Digitizer Evaluation

Sandia National Laboratories has tested and evaluated a new digitizer, the Q330M+, manufactured by Quanterra, a division of Kinemetrics Inc. This digitizer is used to record sensor output for seismic and infrasound monitoring applications. The purpose of the digitizer evaluation was to measure the performance characteristics in such areas as sensitivity, input impedance, power consumption, self noise, dynamic range, system noise, relative transfer function, analog bandwidth, modified noise power ratio, harmonic distortion, common mode, cross talk, timing tag accuracy and timing drift. The Q330M+ provides six channels of 24 bit digitization, all of which may be transmitted utilizing CD1.1 protocol, at multiple sample rates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Combined Heat and Power Systems Technology Development and Demonstration 370 kW High Efficiency Microturbine

The C370 Program was awarded in October 2010 with the ambitious goal of designing and testing the most electrically efficient recuperated microturbine engine at a rated power of less than 500 kW. The aggressive targets for electrical efficiency, emission regulatory compliance, and the estimated price point make the system state-of-the-art for microturbine engine systems. These goals will be met by designing a two stage microturbine engine identified as the low pressure spool and high pressure spool that are based on derivative hardware of Capstone’s current commercially available engines. The development and testing of the engine occurred in two phases. Phase I focused on developing a higher power and more efficient engine, that would become the low pressure spool which is based on Capstone’s C200 (200kW) engine architecture. Phase II integrated the low pressure spool created in Phase I with the high pressure spool, which is based on Capstone’s C65 (65 kW) commercially available engine. Integration of the engines, based on preliminary research, would allow the dual spool engine to provide electrical power in excess of 370 kW, with electrical efficiency approaching 42%. If both of these targets were met coupled with the overall CHP target of 85% total combined heating and electrical efficiency California Air Resources Board (CARB) level emissions, and a price target of $600 per kW, the system would represent a step change in the currently available commercial generation technology. Phase I of the C370 program required the development of the C370 low pressure spool. The goal was to increase the C200 engine power by a minimum of 25% — 250 kW — and efficiency from 32% to 37%. These increases in the C200 engine output were imperative to meet the power requirements of the engine when both spools were integrated. An additional benefit of designing and testing the C370 low pressure spool was the possibility of developing a stand-alone product for possible commercialization. The low pressure spool design activity focused on an aeropath derivative of the current C200 engine. The aeropath derivative included changes to the compressor section —compressor and inducer — and to the turbine nozzle. The increased power also necessitated a larger, more powerful generator and generator controller to support the increased power requirements. These two major design changes were completed by utilizing both advanced 3D modeling and computational fluid dynamics modelling. After design, modeling, and analysis, the decision was made to acquire and integrate the components for testing. The second task of Phase I was to integrate and test the components of the low pressure spool to validate power and efficiency. Acquisition of the components for the low pressure spool was completed utilizing Capstone’s current supplier base. Utilization of Capstone’s supply base for integration of the test article would allow — if the decision was made —expedited commercialization of the product. After integration of the engine components, the engine was tested and evaluated for performance and emissions. Test data analysis confirmed that the engine met all power and efficiency requirements and did so while maintaining CARB level emissions. The emissions were met without the use of any post processing or catalyst. After testing was completed, the DOE authorized — via a milestone review — proceeding to Phase II: the development of the integrated C370 engine. The C370 high pressure spool design activity required significant changes to the C65 engine architecture. The engine required a high power density generator, completely redesigned compressor stage, turbine section, recuperator, controls architecture, and intercooler stage asThe two most critical design challenges were the turbine section (the nozzle and turbine) and the controls architecture. The design and analysis of all of the components was completed and integrated into a system model. The system model — after numerous iterations — indicated that, once integrated, the engine will meet or exceed all system requirements. Unfortunately, the turbine section’s life requirements remain a technical challenge and will require continued refinement of the bi-metallic turbine wheel design and manufacturing approach to meet the life requirement at theses high temperatures. The current controls architecture requires substantial effort to develop a system capable of handling the high-speed, near real-time controls requirement, but it was determined not to be a technical roadblock for the project. The C370 Program has been a significant effort with state-of-the-art technical targets. The targets have pushed Capstone’s designers to the limits of current technology. The program has been fortunate to see many successes: the successful testing of the low pressure spool (C250), the development of new material processes, and the implementation of new design practices. The technology and practices learned during the program will be utilized in Capstone’s current product lines and future products. The C370 Program has been a resounding success on many fronts for the DOE and for Capstone.

none↗

Dynamic Polymer Networks for On Demand Degradable Adhesives, Scaffolds, and Templates (Full Technical Report)

This feasibility study was motivated by a need for alternative mandrel materials to meet the next generation of inertial confinement fusion (ICF) ablator capsules. In response, a new polymer material based on reversible covalent bonds was proposed, with the objective to design thermosets to withstand elevated temperatures (140-200 degrees Celsius) while also being thermally degradable on-demand via controlled decomposition at temperatures above 200 degrees Celsius. A series of cyclopentadiene (Cp) containing thermosets were designed and synthesized to evaluate curing, reversibility and degradability via controlled retro-Diels Alder reactions using Cp-cycloaddition adducts as crosslinks. Ultimately, the current iteration of materials and strategy pursued in this study was assessed as impractical for meeting the needs and objectives of Lawrence Livermore National Laboratory’s (LLNL) target fabrication program.

36 MATERIALS SCIENCE↗

Distinct Gas-Particle Partitioning and Viscosity Characteristics of Secondary Organic Aerosols Derived from α-Pinene versus Ocimene

Secondary organic aerosols (SOA) have complex, multicomponent composition that controls particle viscosity and gas-particle partitioning, key factors to their atmospheric evolution. This study investigates the chemical composition, volatility and viscosity of SOA formed by ozonolysis of cyclic α-pinene (PSOA) and acyclic ocimene (OSOA) monoterpenes. Using Temperature-Programmed Desorption combined with Direct Analysis in Real-Time ionization and High-Resolution Mass Spectrometry, we determined the molecular composition and saturation mass concentration of individual SOA constituents. These data enabled gas-particle partitioning and viscosity estimates under varied atmospheric conditions. PSOA, composed of higher molecular weight and less oxidized species, shows higher condensability and viscosity under high total organic mass (tOM) loadings. Here, in contrast, OSOA, consisting of more oxidized, lower molecular weight species, exhibits greater sensitivity to tOM, with viscosity increasing significantly upon dilution. Poke-flow experiments support this trend, indicating that OSOA undergoes more dynamic compositional and phase changes during atmospheric aging. These observations reveal distinct dynamic trends in the atmospheric transformations and reactivity of SOA from cyclic and acyclic monoterpenes, with the latter showing greater compositional changes during aging that alter viscosity and diffusion. This highlights the importance of incorporating such dynamic transformations into atmospheric models to improve predictions of SOA atmospheric loadings, lifetimes, and impacts.

cyclic and acyclic monoterpenes↗

Preface and Summary

Primary Physics with Secondary Beams of K L 's Not all of physics can be explored by primary beams of electrons and protons, however much these have taught us over the past 60 years. Electron-positron colliders give access to restricted sets of quantum numbers. From proton-proton collisions we have long learned about all manner of high energy reactions. However, access to excited mesons and baryons has been most universally achieved with pion and kaon secondary beams, and latterly pho-ton beams both virtual and real. Nowadays the wealth of information on polarized photon beams on polarized targets has totally revolutionized baryon spectroscopy, especially in the lightest flavor sector. The measurement of polarization asymmetries has constrained partial wave analyses far beyond anything conceivable with pion beams. Nevertheless, these only give access to the product of photocouplings of each excited baryon and its coupling to the hadron final state, such as πN , ππN , ηN , etc. Contemporaneously, in the meson sector, the COMPASS experiment with pion beams on protons at 190 GeV/c, together with heavy flavor decays in e + e - annihilation, have given access to multi-meson final states, like 2π, 3π, with greater precision than ever before. This has given hints and suggestions of new resonances, like the a 1 (1420). To understand the constituent structure of hadrons requires information on the relationship of each meson and baryon to those with different flavors, but the same J P quantum numbers. At its simplest, this is to understand the quark model multiplet structure, where this is appropriate. What is more, so ubiquitous are ππ, πK, KK, ηπ, ηK, ... final states as the decay products of almost every hadron, that knowledge of the properties of these is critical to every analysis. Unitarity colors and shapes the universality of such final state interactions in each set of quantum numbers. This means that however precise our measurements of γN → πη () N , with GlueX for instance, we cannot really determine the fine resonant structure of such a process without some information on πη and πη scattering too. Nor can we determine any flavor partners without information on the corresponding Kη () channels. For that secondary kaon beams are essential. While J-PARC has a whole program of charged strange particle and hypernuclear reactions, photon beams allow unique access to other channels. It was realized long ago that intense photon beams like that about to be delivered to Hall D at JLab, could produce secondary beams. The charged particles can readily be bent away, leaving a neutral particle beam dominated by K L : long lived kaons being produced far more copiously than neutrons above 3–4 GeV momentum. Such a facility provides access to a whole range of physics that is the subject of this meeting. The reactions that can be studied cover the meson spectrum and dynamics, the baryon spectrum and dynamics, and final state interactions that link mesons and baryons together. This includes particularly the channels Kπ, Kη, Kη in the meson sector. These explore the very limitations of chiral dynamics: the strange quark's current mass is 30-50 times that of the

42 ENGINEERING↗

Marine Corps Base Camp Lejeune LANDIS-II Model Outputs

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.The LANDIS-II model shows different annual estimates of forest C storage (g/m2) across the MCBCL landscape, based on the user selecting different forest management scenarios typically used in the southeastern US. LANDIS-II is a model with several extensions capable of simulating different landscape and ecosystem-level dynamics.

54 ENVIRONMENTAL SCIENCES↗

Advanced Computing, Data Science, and Artificial Intelligence Research Opportunities for Energy-Focused Transportation Science

The Energy Efficient Mobility Systems (EEMS) technology landscape is complex and rapidly evolving, which provides both tremendous opportunities and formidable challenges. Significant alterations to the mobility landscape are underway due to the advent of vehicle and infrastructure connectivity, autonomous driving, and rapid passenger- and freight-vehicle electrification. Advanced computing will play an increasingly important role in enabling the EEMS program to understand and identify the most important levers to improve the energy productivity of future integrated mobility systems. It is also driving new approaches to mobility and the research to unlock an affordable, efficient, safe, and accessible transportation future. Driving much of this change is the collection, analysis, and strategic use of massive amounts of diverse, complex data from infrastructure and vehicles with on-board sensors and data storage and transmission capabilities. Diverse and representative data are key to implementing approaches to maximize mobility energy productivity. While high-fidelity modeling of integrated transportation networks has strengthened our understanding of dynamic movement and behavior patterns, existing tools must be expanded beyond their current focus. This work necessitates data infrastructure investments (e.g., secure-streaming data platforms driven by ubiquitous sensors and video analytics) as well as investments in critical capabilities for large-scale automated analysis and organization using modern machine learning, statistics, and artificial intelligence. Other chief needs include agile, large-scale storage that can be quickly searched and queried for relevant data to support validation and model development, data-sharing agreements, and formatting standards for key data types. The future of public transit must be explored in greater detail, research must inform design, and opportunities must be identified for improving the mobility productivity of public transit in both urban and rural America.

33 ADVANCED PROPULSION SYSTEMS↗

Milky way bulge extra-tidal star survey: MWBest

The Milky Way Bulge Extra-Tidal Star Survey (MWBest) is a spectroscopic initiative aimed at identifying stars that have been tidally stripped from globular clusters in the inner regions of the Galaxy. As part of the Visiting Faculty Program at Fermilab, we have developed theoretical tools and simulations to compare against observed signatures of extra-tidal stars surrounding both bulge globular clusters (GCs) and low-luminosity clusters. By combining the spatial distributions of simulated stripped stars with new MWBest observations, we are gaining insight into the gravitational potential of the inner Galaxy and the role that bulge GCs may play in enriching the surrounding field star population. We further explore the hypothesis that some low-luminosity bulge GCs may in fact be dense clumps of debris, stripped from more massive GCs as they migrate inward due to dynamical friction.

Kunder, Andrea [Unlisted, US, WA]↗

Ab Initio Evaluation of Uranium Carbide S(α,β) and Thermal Neutron Cross Sections

Uranium Carbide (UC) is a nuclear fuel material which offers better neutron economy and lower fuel-cycle costs compared to conventional mixed-oxide fuels. UC’s lattice binding and dynamical properties impact thermal neutron scattering and low temperature epithermal resonance absorption. The Thermal Scattering Law (TSL) describes the scattering system available energy and momentum transfer states. There is no TSL evaluation for UC in the ENDF/B-VIII.0 database; herein, ab-initio lattice dynamics (AILD) techniques are invoked to calculate the phonon spectrum for UC using spin-orbit-coupling density functional theory (DFT). The TSLs, inelastic and elastic thermal scattering cross sections for Uranium and Carbon in UC, respectively, are calculated in FLASSH for use in higher fidelity reactor design calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗

A novel Variable Refrigerant Flow (VRF) heat recovery system model: Development and validation

As one of the latest emerging HVAC technologies, the Variable Refrigerant Flow (VRF) system with heat recovery (HR) configurations has obtained extensive attention from both the academia and industry. Compared with the conventional VRF systems with heat pump (HP) configurations, VRF-HR is capable of recovering heat from cooling zones to heating zones and providing simultaneous cooling and heating operations. Moreover, this could lead to substantial energy saving potential and more flexible zonal control. In this paper, a novel model is developed to simulate the energy performance of VRF-HR systems. It adheres to a more physics-based development with the ability to simulate the refrigerant loop performance and consider the dynamics of more operational parameters, which is crucial for representing more advanced control logics. Another key feature of the model is the introduction of component-level curves for indoor units and outdoor units instead of overall performance curves for the entire system, and thus it requires much fewer user-specified performance curves as model inputs. The validation study reflects good agreements between the simulated energy use from the new VRF-HR model and the laboratory measurement data across all operational modes at sub-hourly time steps. The model has been adopted in the official release of the EnergyPlus simulation program since Version 8.6, which enables more accurate and robust assessments of VRF-HR systems to support their applications in energy retrofit of existing buildings or design of zero-net-energy buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A morphology independent methodology for quantifying planview river change and characteristics from remotely sensed imagery

Remotely sensed imagery of rivers has long served as a means for characterizing channel properties and detection of planview change. In the last decade the dramatic increase in the availability of satellite imagery and processing tools has created the potential to greatly expand the spatial and temporal scale of our understanding of river morphology and dynamics. To date, the majority of GIS and automated analyses of planview changes in rivers from remotely sensed data has been developed for single-threaded meandering river systems. These methods have limited applicability to many of the earth's rivers with complex multi-channel planforms. Here we present the methodologies of a set of analysis algorithms collectively called Spatially Continuous Riverbank Erosion and Accretion Measurements (SCREAM). SCREAM analyzes planview river metrics regardless of river morphology. These algorithms quantify both the erosion and accretion rates of riverbanks from binary masks of channels generated from imagery acquired at two time periods. Additionally, the program quantifies the area of change between river channels and the surrounding floodplain and area of islands lost or formed between these two time periods. To examine variations in erosion rates in relation to local channel attributes and make rate comparisons between river systems of varying sizes, the program determines channel widths and bank curvature at every bank pixel. SCREAM was developed and tested on rivers with diverse and complex planform morphologies in imagery acquired from a range of observational platforms with varying spatial resolutions. Here, validation and verification of SCREAM-generated metrics against manual measurements show no significant measurement errors in determination of channel width, erosion, and bank aspects. SCREAM has the potential to provide data for both the quantitative examination of the controls on erosion rates and for the comparison of these rates across river systems ranging broadly in size and planform morphology.

47 OTHER INSTRUMENTATION↗

Peptoid Backbone Flexibilility Dictates Its Interaction with Water and Surfaces: A Molecular Dynamics Investigation

Peptoids are peptide-mimetic biopolymers that are easy-to-synthesize and adaptable for use in drugs, chemical scaffolds, and coatings. However, there is insufficient information about their structural preferences and interactions with the environment in various applications. We conducted a study to understand the fundamental differences between peptides and peptoids using molecular dynamics simulations with semi-empirical (PM6) and empirical (AMBER) potentials, in conjunction with metadynamics enhanced sampling. From studies of single molecules in water and on surfaces, we found that sarcosine (model peptoid) is much more flexible than alanine (model peptide) in different environments. However, the sarcosine and alanine interact similarly with a hydrophobic or a hydrophilic. Finally, this study highlights the conformational landscape of peptoids and the dominant interactions that drive peptoids towards these conformations. ACKNOWLEDGMENT: MD simulations and manuscript preparation were supported by the MS3 (Materials Synthesis and Simulation Across Scales) Initiative at Pacific Northwest National Laboratory (PNNL), a multi-program national laboratory operated by Battelle for the U.S. Department of Energy. CJM was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences Division of Chemical Sciences, Geosciences, and Biosciences. MDB was supported by the US Department of Energy, Office of Basic Energy Sciences, Biomolecular Materials Program at PNNL. Computing resources were generously allocated by University of Washington's IT department and PNNL's Institutional Computing program. The authors greatly acknowledge conversations with Dr. Kayla Sprenger, Josh Smith, and Dr. Yeneneh Yimer.

alanine↗

Improved Characterization and Modeling of Tight Oil Formations for CO 2 Enhanced Oil Recovery Potential and Storage Capacity Estimation

Tight oil formations such as those in the Bakken petroleum system are known to hold hundreds of billions of barrels of oil in place; however, the primary recovery factor for these plays is typically less than 10%. Tight oil formations, including the Bakken Formation, therefore, may be attractive candidates for enhanced oil recovery (EOR) using CO 2 . Multiphase fluid behavior and flow in fluid-rich shales can vary substantially depending on the size of pore throats, and properties such as fluid viscosity and density are much different in nanoscale pores than in macroscale pores. Thus it is critical to understand the nature and distribution of nano-, micro-, and macroscale pores and fracture networks. To address these issues, the Energy & Environmental Research Center (EERC) has been conducting a research program entitled “Improved Characterization and Modeling of Tight Oil Formations for CO 2 Enhanced Oil Recovery Potential and Storage Capacity Estimation.” The objectives of the project are 1) the use of advanced characterization methods to better understand and quantify the petrophysical and geomechanical factors that control CO 2 and oil mobility within tight oil formation samples, 2) the determination of CO 2 permeation and oil extraction rates in tight reservoir rocks and organic-rich shales of the Bakken, and 3) the integration of the laboratory-based CO 2 permeation and oil extraction data and the characterization data into geologic models and dynamic simulations to develop predictions of CO 2 storage resource and EOR in the Bakken tight oil formation. A combination of standard and advanced petrophysical characterization techniques were applied to characterize samples of Bakken Formation tight reservoir rock and shales from multiple wells. Techniques included advanced computer tomography (CT) imaging, scanning electron microscopy (SEM) techniques, whole-core and micro x-ray CT imaging, field emission (FE) SEM, and focused ion beam (FIB) SEM. Selected samples were also analyzed for geomechanical properties. X-ray CT imaging yielded information on the occurrence of fractures, bedding planes, fossils, and bioturbation in core, as well as data on bulk density and photoelectric factor logs, which were used to interpret porosity, organic content, and mineralogy. FESEM was used for characterization of nano- and microscale features, including nanoscale pore visualization and micropore and pore throat mineralogy. FIBSEM yielded micro- to nanoscale visualization of fracture networks, porosity and pore-size distribution, connected versus isolated porosity, and distribution of organics. Results from the characterization activities provide insight on nanoscale fracture properties, pore throat mineralogy and connectivity, rock matrix characteristics, mineralogy, and organic content. Laboratory experiments demonstrated that CO 2 can permeate the tight matrix of Bakken shale and nonshale reservoir samples and mobilize oil from those samples. Geologic models were created at scales ranging from the core plug to the reservoir, and dynamic simulations were conducted. The data from the characterization and laboratory-based activities were integrated into modeling research activities to determine the fundamental mechanisms controlling fluid transport in the Bakken, which support EOR scheme design and estimation of CO 2 storage potential in tight oil formations. Simulation results suggest a CO 2 storage resource estimate range of 169 million to 1.5 billion tonnes for the Bakken in North Dakota, possibly resulting in 1.8 billion to 16 billion barrels of incremental oil.

04 OIL SHALES AND TAR SANDS↗