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At least 469 records · Page 26

Modeling gas, hydrates, and slope stability on the U.S. Atlantic margin during Pleistocene glacial cycles

Changes in temperature and sea level can cause dissociation of methane hydrates in shallow marine sediments, leading to seafloor destabilization. Along the U.S. Atlantic margin, there exists a well-documented history of slope failure and numerous recorded occurrences of gas seeps. Several studies have linked slope failure in the region to gas seepage and hydrate dissociation driven by glacial-interglacial transitions, but this linkage has not been quantitatively demonstrated. Along the shelf edge, in an area where shallow methane gas seeps have been identified, we modeled methane gas and hydrate formation using a one-dimensional fluid flow model. Methane gas formation was modeled over the last 120,000 years to simulate a glacial-interglacial cycle. Here, we ran this model at 16,044 individual locations in the region between 29° N – 45° N and 82° W – 66° W at a resolution of 1 x 1 arcminutes, focusing specifically on water depths between 200 and 1000 m that bracket the seafloor outcrop of the base of the hydrate stability zone. Using historic temperature and pressure records from the last 120,000 years, sediment properties in the area, and factor of safety calculations, we found that hydrate dissociation alone is unlikely to cause sediment failure in the region, implying that an additional driving force would be necessary for failure to occur.

Hydrate dissociation↗

A flexible data acquisition system architecture for the Nab experiment

Here, the Nab experiment will measure the electron–neutrino correlation and Fierz interference term in free neutron beta decay to test the Standard Model and probe Beyond the Standard Model physics. Using National Instrument’s PXIe-5171 Reconfigurable Oscilloscope module, we have developed a data acquisition system that is not only capable of meeting Nab’s specifications, but flexible enough to be adapted in situ as the experimental environment dictates. The L1 and L2 trigger logic can be reconfigured to optimize the system for coincidence event detection at runtime through configuration files and LabVIEW controls. This system is capable of identifying L1 triggers at a rate of at least 1 MHz, while reading out a peak signal rate of approximately 2 GB/s. During the commissioning phase of the experiment, the system ran at a sustained readout rate of 400 MB/s of detector signal data originating from roughly 6 kHz L2 triggers, well within the peak performance of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Validation of URANS and STRUCT-ε turbulence models for stratified sodium flow

Simulations of a transient stratified sodium experiment are carried out using a classic unsteady RANS model and the second-generation URANS model, STRUCT-ε. Turbulence modeling challenges and their implications to stratified flow prediction are discussed in the context of other sources of error. Input errors are discussed and addressed; discretization error is calculated to be less than 5% of the inlet velocity, for 80% of the domain; and remaining errors in temperature distributions are attributed to the turbulence model. Qualitative flow features from the simulations are presented and discussed. Compared to the experiment, the STRUCT-ε turbulence model provides a more physically accurate prediction of temperature and momentum mixing in key regions of the domain. Quantitative measures such as the L 2 norm of the temperature discrepancy demonstrate the improved performance of the STRUCT-ε approach. In conclusion, the magnitude of the temperature fluctuations is very well-predicted by the STRUCT-ε, while URANS overpredicts them by approximately 50%.

42 ENGINEERING↗

Comparison of URANS and LES predictions for the open phase of the OECD NEA CSNI fluid structure interaction CFD benchmark

The OECD NEA CSNI WGAMA CFD Task Group ran a benchmark in 2020 and 2021 to assess the predictive capabilities of coupled fluid structure interaction (FSI) CFD analysis methods. This paper presents the predictions made for the open phase of the benchmark using URANS and LES turbulence modelling approaches, and a comparison of the results to the experimental data. The benchmark comprised a channel containing two inline cylinders in cross-flow. The cylinders were fixed at one end, free at the other, and had measured resonant frequencies and damping properties. The URANS modelling used ANSYS Fluent 2-way coupled to ANSYS Mechanical. The LES modelling used Nek5000, 1-way coupled to Diablo. Comparisons with cross-channel velocity profiles are presented, both for the mean flow and its RMS. Comparisons are also made to the frequency spectra for point measurements of fluid velocity and pressure, and for the accelerations of the free end of each cylinder. URANS predicts the average velocity profiles relatively well, and is able to predict the velocity and acceleration spectra at the shedding frequency. However, the frequency content at the 4th harmonic of the shedding frequency is low in the URANS flow fields, and so does not excite accelerations at the resonant frequency of the cylinders. LES makes better predictions of the average profiles, and the velocity spectra agree well at both the shedding frequency and at higher frequencies. In conclusion, the 1-way coupled LES results show good agreement for acceleration spectra.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A review of computational methods for studying oscillating water columns – the Navier-Stokes based equation approach

This review evaluates the state-of-the-practice numerical tools used to predict the performance of Oscillating Water Column (OWC). The OWC is a widely studied Wave Energy Converter that provides a reliable form of renewable form of electricity that can potentially meet global energy needs. However, the fluid-flow phenomena affecting its hydrodynamic performance are not fully understood. While there has been the successful full-scale deployment of OWCs, various computational methods are being explored to optimize this technology. Potential flow theory is commonly used to evaluate the efficiency of OWCs; however, this assumption tends to over-predict the hydrodynamic performance. Recently, numerical studies using a diverse set of commercial, open-source, or in-house Computational Fluid Dynamics (CFD) using Reynolds Averaged Navier Stokes (RANS) and Large-Eddy Simulation codes show a better comparison to available experimental results but are computationally expensive. ANSYS Fluent was found to be the most widely used CFD code applied to the study of the OWCs, with a high degree of accuracy in terms of experimental validation of numerical results.

16 TIDAL AND WAVE POWER↗

Effects of boundary hydraulics, dissolved oxygen, and dissolved organic carbon on growth and death dynamics of aerobic microbes in riverbed dune-induced hyporheic zones

Surface and groundwater interact in the hyporheic zone beneath and adjacent to rivers in the presence of a diverse microbial community. Heterotrophic bacteria mediate a range of environmentally important reactions, yet few studies have quantified bacterial growth and death dynamics in the hyporheic zone, and none have systematically analyzed their response to variations in hydraulic or chemical conditions. Here we used MODFLOW and SEAM3D to simulate hydraulics; dissolved oxygen (DO) and dissolved organic carbon (DOC) transport; and aerobic microbial metabolism, growth, and death in hyporheic zones induced by riverbed dunes. We ran simulations both with and without growth/death processes, and varied hydraulic parameters and DO/DOC boundary concentrations. Microbial biomass reached steady state (t = 3 days) in every simulation, at which time there was greater biomass and DOC biodegradation rates in the hyporheic flowcell (300% and 85% higher for the base case, respectively) when accounting for microbial growth dynamics. This occurred as microbial biomass tailored its spatial distribution to the availability of DO and DOC, demonstrating the importance of simulating growth/death processes. Biomass generally increased with hyporheic flow cell area as upwelling groundwater decreased. When varying surface water DO and DOC source concentrations relative to the base case, the greatest effect on biomass occurred when increasing DOC and decreasing DO. We determined minimum DO and DOC steady-state concentrations required for microbial growth, but the minimums were not absolute or related by stoichiometry. Increasing DOC created a smaller area of microbes with higher concentrations relative to the base case. Increasing DO slightly increased the area occupied by microbes while keeping the total biomass nearly constant. Overall, microbial growth and death dynamics depend on DO and DOC availability in the hyporheic zone, which is dependent on DOC/DO boundary concentrations and hyporheic flow paths, and in turn the hydraulic interaction between surface water and groundwater.

54 ENVIRONMENTAL SCIENCES↗

Comparing Adjoint Waveform Tomography Models of California Using Different Starting Models

Abstract Adjoint waveform tomography (AWT) sits at the cutting edge of seismic tomography on local, regional, and global scales. However, the choice in starting model may have a significant impact on the final inversion results. In this paper, we present 3 AWT models of California that are based on different starting models. We chose three models that were inverted at different scales: SPiRaL, a global travel‐time tomography model (Simmons et al., 2021, 10.1093/gji/ggab277 ), CSEM_NA, a regional adjoint tomography model of North America and the North Atlantic (Krischer et al., 2018, 10.1029/2017JB015289 ), and WUS256, a regional adjoint tomography model of the western US (Rodgers et al., 2022, https://doi.org/10.1029/2022JB024549 ). We then inverted three AWT models using the same source and receiver set. We ran each model over three period bands: 30–100 s, 25–100 s, and 20–80 s. Once the iterations were finalized, we used five methods of testing model similarity in both the model and data space. We conclude that the choice of starting model has a minimal impact on long wavelength models if an appropriate multi‐scale inversion approach is used.

58 GEOSCIENCES↗

A Refined Understanding of the Ice Cloud Longwave Scattering Effects in Climate Model

Abstract Because longwave (LW) absorption by greenhouse gases and clouds is more significant than the LW scattering effect by clouds, most climate models neglect cloud LW scattering to save computational costs. Ignoring cloud LW scattering directly overestimates outgoing longwave radiation (OLR). This study included ice‐cloud LW scattering treatment in the Exascale Energy Earth System Model (E3SM) version 2 and ran fully‐coupled simulations, prescribed sea surface temperature simulations, and offline radiative transfer calculations to comprehensively assess the impact of ice‐cloud LW scattering on global climate simulation. The instantaneous effect due to ice‐cloud LW scattering reduces the OLR by ∼1 W/m 2 on the global average and 2 W/m 2 on the tropical average. Tropospheric warming and high cloud amount reduction act to partially compensate for such instantaneous OLR reduction caused by the inclusion of LW scattering. When the simulation reaches the equilibrium, the surface warms by 0.66 K on average with respect to the simulation without LW scattering, with the Arctic surface temperature differences more than twice as large as that of the global mean. The impact of including LW scattering on the simulated climate change in response to 4 × CO 2 is also assessed. While including the cloud LW scattering does not significantly modify radiative forcing and total radiative feedback under such a scenario, it results in a 10% more positive cloud feedback.

54 ENVIRONMENTAL SCIENCES↗

WUS324: Multiscale Full Waveform Inversion Approaching Convergence Improves Waveform Fits While Imaging Seismic Structure of the Western United States

Abstract We report a new model of radially anisotropic crustal and upper mantle structure of the western United States (WUS324) obtained from full waveform inversion of earthquake data. We ran three multiscale inversion stages beyond model WUS256 (Rodgers et al., 2022, https://doi.org/10.1029/2022jb024549 ) allowing them to approach convergence to fit a larger data set to a shorter minimum period of 16 s. WUS324 is based on 324 total iterations from its starting model, significantly more (16 times) than previous studies. Waveform misfit reductions are 66%–70% for both the inversion data and an independent validation data set providing confidence in the predictive power of the model. WUS324 provides much better fits and reveals shear wavespeed, v S , structure of this large region with more detail than previous waveform tomography models. We show representative images demonstrating the resolution of diverse seismic structure across this highly heterogeneous region including oceanic lithosphere, subducting slabs and continental magmatism.

58 GEOSCIENCES↗

Fluid‐Driven Cohesive Strengthening: Critical Role of Reaction Kinetics as the Determinant for Frictional Stability

After an earthquake, faults in the Earth's crust lock up and slowly regain strength. This process, called fault healing, plays a key role in determining how often earthquakes happen and how large they can be. While scientists know that healing involves both mechanical friction and chemical changes in rocks, it has been unclear how these processes work together, especially over shorter timescales in laboratory settings. In our study, we ran controlled experiments on the mineral anhydrite under different fluid conditions. We found that the presence and pressure of water speeds up fault healing by triggering a chemical reaction that strengthens the fault over time. This strengthening makes the fault more resistant to sliding, which could delay future earthquakes—but also sets the stage for larger ones when they do occur. We propose a model that combines frictional and chemical processes to explain this water‐activated, time‐dependent healing. Importantly, our results show that even faults typically considered stable could still produce earthquakes if they undergo sufficient chemical healing. This has broad implications for understanding where and when earthquakes might strike, especially in fluid‐rich environments such as subduction zones and geoenergy settings.

Affinito, R [Pennsylvania State Univ., University ↗

The Role of Snowmelt and Subsurface Heterogeneity in Headwater Hydrology of a Mountainous Catchment in Colorado: A Model‐Data Integration Approach

Mountainous headwater streams are sustained by both snowmelt‐driven streamflow and groundwater discharge in the Upper Colorado River Basin. However, predicting headwater stream discharge magnitude and peak flow timing is challenging in mountainous terrains, where snowmelt rates vary with vegetation type and elevation, and heterogeneous subsurface physical properties influence groundwater storage and its release. We used a model‐data integration approach to investigate the roles of snowmelt and subsurface structure in stream discharge and groundwater level. We ran an ensemble of 100 integrated surface‐subsurface hydrologic models for a mountainous headwater catchment near Crested Butte, Colorado, USA. We also evaluated and calibrated these models against observed data sets, including snow depth measurements using distributed temperature probes, stream discharge, and groundwater levels. Calibration with multiple data sources using neural density estimators has further constrained uncertainty in subsurface properties and snowmelt rates. Results indicated that observed slower snowmelt rates in evergreen forests delayed the peak flow and baseflow onset. In upstream areas with lower subsurface permeability, water was stored within the subsurface but was not released as interflow or shallow groundwater flow, and thereby not contributing to downstream streamflow during recession limb periods. Double peaks in groundwater occurred in areas with spatial subsurface heterogeneity, in our case due to the contrast between granodiorite and Mancos shale. These process‐based insights into groundwater and snowmelt dynamics in mountainous headwaters will help improve predictions of headwater hydrology.

Wang, Lijing [University of Connecticut, Storrs, C↗

When Do Riverine Systems “Feel the Burn”? Simulating How Burn Extent and Severity Modulate Hydrologic Controls on Biogeochemical Export

Wildfires impact terrestrial landscapes and downstream river corridors through shifts in vegetation and soil properties leading to downstream hydrologic and water quality impacts. The magnitude of these impacts depend on a complex and interconnected set of wildfire, landscape, and aquatic processes. Here, we isolate the impact of post-fire hydrologic changes on streamflow, nitrate, and dissolved organic carbon using the Soil and Water Assessment Tool (SWAT) model. We explore how responses differ across burn severity and area burned in two test basins: a humid forested basin and a semi-arid mixed land use basin. We ran 1830 wildfire simulations testing impacts of area burned, burn severity, and post-fire precipitation on streamflow, nitrate, and dissolved organic carbon. Our work suggests that area burned thresholds differ with burn severity and analyte. Additionally, post-fire transport of dissolved organic carbon was sensitive to both area burned and severity, while nitrate was primarily sensitive to area burned. Despite a muted (−9.5 to 5.7 mm yr −1 change) hydrologic response in the semi-arid basin, the model predicted large (7%–288% increase) shifts in dissolved organic carbon, suggesting that post-fire shifts in flow pathways and soil properties are key in its response. The limited shifts in nitrate responses in the simulations highlight that terrestrial post-fire transformations, rather than hydrologic changes, may control the increases in stream nitrate often observed post-fire. As wildfire regimes are shifting, improving understanding of post-fire nutrient export responses is critical to protect freshwater resources and aquatic ecosystems.

Wampler, Katherine A. [Pacific Northwest National ↗

Detecting damaged buildings using real-time crowdsourced images and transfer learning

After significant earthquakes, we can see images posted on social media platforms by individuals and media agencies owing to the mass usage of smartphones these days. These images can be utilized to provide information about the shaking damage in the earthquake region both to the public and research community, and potentially to guide rescue work. This paper presents an automated way to extract the damaged buildings images after earthquakes from social media platforms such as Twitter and thus identify the particular user posts containing such images. Using transfer learning and ~ 6500 manually labelled images, we trained a deep learning model to recognize images with damaged buildings in the scene. The trained model achieved good performance when tested on newly acquired images of earthquakes at different locations and when ran in near real-time on Twitter feed after the 2020 M7.0 earthquake in Turkey. Furthermore, to better understand how the model makes decisions, we also implemented the Grad-CAM method to visualize the important regions on the images that facilitate the decision.

58 GEOSCIENCES↗

Engineering block co-polymer anion exchange membrane domains for highly efficient electrode-decoupled redox flow batteries

We report, anion exchange membranes (AEMs) with high permselectivity, chemical stability and mechanical robustness are a key enabling technology for a variety of electrochemical energy conversion and storage systems such as fuel cells, redox flow batteries and water electrolyzers. Herein we examine well understood chemically stable triblock co-polymer AEMs derived by the chloromethylation (CM-) and subsequent trimethylamine (TMA) functionalization of polystyrene-block-poly(ethylene-ran-butylene)-block-polystyrene (SEBS) block co-polymers. We show using small angle X-ray scattering (SAXS) that the introduction of a hydrophobic reinforcement matrix disrupts phase segregation and decreases ionic domain sizes in these AEM separators. The reinforcement matrix simultaneously causes the ultimate tensile strength (UTS) of the reinforced separator to increase by almost 600% compared to the unreinforced form, while maintaining comparable elasticity (ca. 500% elongation at break). Such reinforced r-SEBS30-TMA separators enable electrode-decoupled redox flow batteries (ED-RFBs) with significantly improved lifetimes by decreasing per cycle capacity fade from 0.5% to <0.05%. This 10× improvement in operando permselectivity opens the door to ED-RFBs employing inexpensive elemental actives achieving decades-long usable lifespans.

25 ENERGY STORAGE↗

Understanding interfacial segregation in polymer blend films with random and mixed side chain bottlebrush copolymer additives

Bottlebrush polymers are complex macromolecules with tunable physical properties dependent on the chemistry and architecture of both the side chains and the backbone. Prior work has demonstrated that bottlebrush polymer additives can be used to control the interfacial properties of blends with linear polymers but has not specifically addressed the effects of bottlebrush side chain microstructures. Here, using a combination of experiments and self-consistent field theory (SCFT) simulations, we investigated the effects of side chain microstructures by comparing the segregation of bottlebrush additives having random copolymer side chains with bottlebrush additives having a mixture of two different homopolymer side chain chemistries. Specifically, we synthesized bottlebrush polymers with either poly(styrene-ran-methyl methacrylate) side chains or with a mixture of polystyrene (PS) and poly(methyl methacrylate) (PMMA) side chains. Furthermore, the bottlebrush additives were matched in terms of PS and PMMA compositions, and they were blended with linear PS or PMMA chains that ranged in length from shorter to longer than the bottlebrush side chains. Experiments revealed similar behaviors of the two types of bottlebrushes, with a slight preference for mixed side-chain bottlebrushes at the film surface. SCFT simulations were qualitatively consistent with experimental observations, predicting only slight differences in the segregation of bottlebrush additives driven by side chain microstructures. Specifically, these slight differences were driven by the chemistries of the bottlebrush polymer joints and side chain end-groups, which were entropically repelled and attracted to interfaces, respectively. Using SCFT, we also demonstrated that the interfacial behaviors were dominated by entropic effects with high molecular weight linear polymers, leading to enrichment of bottlebrush near interfaces. Surprisingly, the SCFT simulations showed that the chemistry of the joints connecting the bottlebrush backbones and side chains played a more significant role compared with the side chain end groups in affecting differences in surface excess of bottlebrushes with random and mixed side chains. This work provides new insights into the effects of side chain microstructure on segregation of bottlebrush polymer additives.

36 MATERIALS SCIENCE↗

Sequentially regular polymer acceptors featuring flexible spacers for high-performance and mechanically robust all-polymer solar cells

Developing high-performance and mechanically robust polymer solar cells (PSCs) is crucial for realizing wearable power sources. While efficient all-polymer solar cells (all-PSCs) can be fabricated from polymerized small-molecule acceptors (PSMAs) with high optical absorption and electron mobilities, they still show limited mechanical robustness. Here, we achieve highly efficient and mechanically robust all-PSCs by designing a PSMA (PYFS-Reg) containing sequence-regular flexible spacers (FSs). The regular incorporation of the FS units into PSMAs is essential in simultaneously improving the electrical and mechanical properties of blend films. As a result, all-PSCs featuring PYFS-Reg achieve a high power conversion efficiency (PCE = 16.1%) and stretchability (crack onset strain (COS) = 22.4%), outperforming PSMAs without FSs (i.e., PYBDT, PCE = 12.6% and COS = 11.7%) or with randomly distributed FSs (i.e., PYFS-Ran, PCE = 12.2% and COS = 18.1%). Importantly, these all-PSCs are fabricated by an environmentally benign, non-halogenated solvent process. To further demonstrate their feasible applications in wearable devices, we construct intrinsically stretchable (IS) all-PSCs by using PYFS-Reg-based active layers, which exhibit a high PCE (10.6%) and excellent device stretchability (strain at PCE 80% = 36.7%).

14 SOLAR ENERGY↗

Using Flory–Huggins-informed human-in-the-loop Bayesian optimization to map the phase diagram of polymer blends

Mapping the phase diagram of polymer blends is an essential step in controlling the structure–property relationship of polymer-based materials. However, traditional grid-based approaches are inefficient and rely on subjective judgements for terminating the experimental campaign. Artificial intelligence-guided experimentation offers a compelling alternative, especially when data-driven decision-making is interfaced with established polymer thermodynamics to improve efficiency and interpretability. Here, we introduce a physics-informed Bayesian optimization approach to guide the mapping of the phase diagram of a model blend containing poly(methyl methacrylate) and poly(styrene-ran-acrylonitrile). Physical information is derived from a Flory–Huggins representation of the spinodal curve, which is integrated into the Bayesian optimization process as a structured prior mean that acts as a soft constraint. Implemented as a human-in-the-loop workflow, the approach leverages optical imaging of film cloudiness with iterative Gaussian process surrogate modeling and a parameter selection decision policy to identify the composition-temperature conditions for sequential iterations. Convergence of kernel and Flory–Huggins-based hyperparameters provided a stopping criterion, ensuring an objective and interpretable termination of the experimental campaign. The framework recovered the known lower critical solution temperature (∼160 °C), while increasing material efficiency through targeted sampling. This work establishes a proof-of-concept for the application of Bayesian optimization workflows to study polymer blend miscibility.

36 MATERIALS SCIENCE↗

StaNdaRT: a repository of standardised test models and outputs for supernova radiative transfer

We present the first results of a comprehensive supernova (SN) radiative-transfer (RT) code-comparison initiative (StaNdaRT), where the emission from the same set of standardised test models is simulated by currently used RT codes. We ran a total of ten codes on a set of four benchmark ejecta models of Type Ia SNe. We consider two sub-Chandrasekhar-mass (M tot = 1.0 M ⊙ ) toy models with analytic density and composition profiles and two Chandrasekhar-mass delayed-detonation models that are outcomes of hydrodynamical simulations. We adopt spherical symmetry for all four models. The results of the different codes, including the light curves, spectra, and the evolution of several physical properties as a function of radius and time are provided in electronic form in a standard format via a public repository. We also include the detailed test model profiles and several Python scripts for accessing and presenting the input and output files. We also provide the code used to generate the toy models studied here. In this paper, we describe the test models, radiative-transfer codes, and output formats in detail, and provide access to the repository. We present example results of several key diagnostic features.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗