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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Mind-the-gap - Part III: Doppler velocity measurements from space

Convective motions and hydrometeors microphysical properties are highly sought-after parameters for evaluating atmospheric numerical models. With most of the Earth's surface covered by water, space-borne Doppler radars are ideal for acquiring such measurements at a global scale. While these systems have proven to be useful tools for retrieving cloud microphysical and dynamical properties from the ground, their adequacy, and specific requirements for spaceborne operation still need to be evaluated. Comprehensive forward simulations enable us to assess the advantages and drawbacks of six different Doppler radar architectures currently planned or under consideration by space agencies for the study of cloud dynamics. Radar performance is examined against state-of-the-art numerical model simulations of well-characterized shallow and deep, continental, and oceanic convective cases. Mean Doppler velocity (MDV) measurements collected at multiple frequencies (13, 35 and 94 GHz) provide complementary information in deep convective cloud systems. The high penetration capability of the 13-GHz radar enables to obtain a complete, albeit horizontally under-sampled, view of deep convective storms. The smaller instantaneous field of view (IFOV) of the 35-GHz radar captures more precise information about the location and size of convective updrafts above 5-8 km height of most systems which was determined is the portion of storms where the mass flux peak is typically located. Finally, the lower mean Doppler velocity uncertainty of displaced phase center antenna (DPCA) radars makes them an ideal system for studying microphysics in shallow convection and frontal systems, as well as ice and mixed-phase clouds. It is demonstrated that a 94-GHz DCPA system can achieve retrieval errors as low as 0.05-0.15 mm for raindrop volume-weighted mean diameter and 25% for rime fraction (for a -10 dBZ echo).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

How to estimate soil organic carbon stocks of agricultural fields? perspectives using ex-ante evaluation

Estimating soil organic carbon (SOC) stocks of agricultural fields has a range of important applications from development of sustainable management practices to monitoring carbon stocks. There are many estimation strategies with the potential for more reliable estimates of SOC stock and more efficient use of soil sampling and analysis resources, especially by leveraging readily available auxiliary information such as remote sensing. However, concrete guidance for strategy selection is lacking. This study narrows this gap with a comparison of strategies for estimating deep SOC stock (0–60 cm) in a prototypical field. Using high density SOC stock measurements and simulation, we built on past studies by 1) ex-ante evaluating a large number of strategy options, 2) using a Bayesian approach to quantify the uncertainty of the comparison, and 3) considering multiple Bayesian models to assess sensitivity to this modeling choice. We found that, using readily available auxiliary information, both balanced and stratified sampling offer substantial improvements over simple random sampling. The auxiliary information most important for this improvement is a Sentinel-2 SOC index = blue / (green × red), followed by the topographic wetness index. We found that these results are robust to the choice of mapping method, but that there is uncertainty in the magnitude of improvement. Here, we recommend future studies implement this Bayesian approach for simulated ex-ante evaluation of SOC stock estimation strategies across more fields to investigate the generalizability of these findings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

0D, 1D, 2D, and 3D simulations of an idealized coaxial impedance-matched Marx generator

We have conducted 0D, 1D, 2D, and 3D simulations of an idealized coaxial impedance-matched Marx generator (IMG) []. The 0D calculations were conducted with a four-element circuit model; the 1D, 2D, and 3D calculations were conducted with highly resolved, fully electromagnetic representations. The IMG consists of 30 stages distributed axially and connected electrically in series. Each stage is powered by two bricks separated by 180° and connected electrically in parallel. Each brick comprises two opposite-polarity capacitors in series with a single switch. The bricks drive an internal impedance-matched coaxial transmission line terminated by a resistive load. The simulations neglect effects due to the switch-triggering circuit, the capacitor-charging circuit, external conducting boundaries, and reactive components of the load. We find dimensionality does not significantly affect the electrical power delivered by the IMG to its load: peak load powers estimated by the 0D, 1D, 2D, and 3D simulations agree to within 1%. The 3D calculations demonstrate that electromagnetic power radiated by the bricks, and axial gaps between stages, reduces the peak load power by less than ∼ 1 % . Each simulation assumes the load impedance is 34% above that at which the load power is maximized. Operating an IMG with such an overmatched load offers several advantages while decreasing the peak load power by only 2%. The 0D, 1D, 2D, and 3D models outlined herein could be adapted to assess computationally competing IMG designs, and conduct a variety of numerical IMG experiments, an IMG is constructed. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

IRIS-MASH: Efficient Multi-device Asynchronous Multi-Stream Heterogeneous Computing

In the rapidly evolving field of high-performance computing (HPC), effectively leveraging heterogeneous devices through asynchronous task programming is paramount. This paper presents a robust asynchronous task programming model tailored for a multi-device, multi-stream execution environment that incorporates a diverse array of heterogeneous computing units, including GPUs from various vendors and other accelerators. Current state-of-the-art task programming models provide methodologies to support asynchronous task executions, but they typically handle homogeneous devices using native programming languages, while support for heterogeneous devices is limited to frameworks like OpenCL. This gap presents significant challenges in abstracting heterogeneous devices to harness their true asynchronous capabilities effectively using their native programming languages. By implementing asynchronous task execution, our model significantly boosts the performance of tiled algorithm task graphs through overlapping data transfers with computation and enabling the simultaneous execution of multiple kernels. We integrate this approach into a heterogeneous Intelligent Runtime System (IRIS) and assess its performance using a suite of tiled algorithm benchmarks from the heterogeneous math kernels library (MatRIS) based on IRIS. Experimental results demonstrate a performance improvement ranging from 1.6 × to 2 × over IRIS without asynchronous support, and a notable 22% performance enhancement compared to established runtime systems such as StarPU and PaRSEC. This approach significantly improves computation efficiency of HPC workflows and provides a solid base for future exploration and development in the area of asynchronous task programming in heterogeneous systems.

Miniskar, Narasinga Rao [ORNL] (ORCID:000000018259↗
DOE OSTI2024

Prospective Seal Unit Spatial Extent Database for U.S. Sedimentary Basins

The Prospective Seal Unit Spatial Extent Database for U.S. Sedimentary Basins contains a series of spatial datasets representing spatial extents of publicly available data for caprock and seal rock units within the Appalachian Basin, Denver-Julesburg Basin, Great Valley Basin (Sacramento and San Joaquin Basins), Illinois Basin, Michigan Basin, San Juan Basin, U.S. Gulf Coast Basin, and Williston Basin. The database is designed to support carbon storage feasibility and resources assessment for carbon transport and storage (CTS) projects while displaying the spatial extent of prospective seal units and provide a guide to the original data source. This database leverages publicly available data resources from authoritative sources (e.g. U.S. Geological Survey, State Geologic Surveys, and published reports), and aims to help guide users to understand the seal unit's spatial coverage and data gaps from the regional to sub-basin/field scale. The database is organized by seal unit/formation, including the spatial extent for data found to be available for the seal unit. The various datasets represented include spatial extents of the lithologic formation, depth to top structural contour maps, and thickness/isopach maps. Included in this submission are the following resources: 1. Geodatabase/Dataset: “prospective-seal-unit-extents-2025.gdb” 2. ReadMe: “readme-prospective-seal-unit-spatial-extent-dataset-2025.pdf” 3. Data Catalog: “prospective-seal-unit-spatial-extents-data-catalog-2025.xlsx” 4. Data Sources Key: “data-source.csv” Please see NETL disclaimers here: https://netl.doe.gov/home/disclaimer

Basin↗
DOE OSTI2023

Potential impacts of Fukushima nuclear wastewater discharge on nutrient supply and greenhouse gas emissions of food systems

Seafood plays a critical role in promoting a nutritious and climate-friendly food system but faces challenges from marine contamination that pose food safety risks. Here, to address these challenges, we developed a Marine Pollution-induced Food System Risk Assessment and Response (MP-FSRAR) model to assess the impact of consumer perceptions of marine pollution risk events on nutrient supply and greenhouse gas (GHG) emissions. Applying this model to the proposed Fukushima Nuclear Wastewater Discharge (FNWD) into the Pacific Ocean, we identified the potential variation in nutrient supply and GHG emissions resulting from changes in Chinese consumers' willingness to consume seafood under 12 scenarios. Our analysis revealed nutrient supply gaps in daily protein, minerals, vitamins, and fatty acids, ranging from 1.5 to 2.7 g/person, 2.5–4.5 mg/person, 5.6–10.3 mcg/person, and 0.08–0.14 g/person, respectively. Closing the protein gap in China would require an additional 3.2–15.8 billion kg yr -1 protein-rich foods, including aquatic, livestock, dairy, and pulses. Additional food supply would increase extra GHG emissions by 1–79 billion kg CO 2 e yr -1 , resulting in potential GHG emissions being transmitted to other countries through the trade chain. Furthermore, we found that the livestock-based food substitution pathway had 40 times higher GHG emissions than the plant-based one. Our MP-FSRAR model provides global stakeholders with new perspectives on the potential consequences of consumer perceptions of marine pollution risks and offers valuable insights for developing countermeasures to build a more resilient and low-carbon food system.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Public electric vehicle charging station utilization in the United States

The utilization of electric vehicle (EV) charging equipment is a key driver of charging station economics, but current trends and factors related to the utilization of public charging infrastructure in the United States are not well understood. This study analyzes EV charging data from 3,705 nationwide public Level 2 (L2) and direct current fast charging (DCFC) stations over 2.5 years (2019-2022), observing utilization patterns over time. Regression analysis is used to assess the relationships between station utilization and several contextual and environmental factors. We conclude that local EV adoption is a strong indicator of utilization; L2 station utilization decreases with the size of the local charging network, while DCFC stations are less affected; and increased charging power has a greater effect on utilization for DCFC stations than L2. This study fills a critical research gap by reporting updated public charging station utilization statistics and analysis for the U.S. market.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Establishing a versatile toolkit of flux enhanced strains and cell extracts for pathway prototyping

Building and optimizing biosynthetic pathways in engineered cells holds promise to address societal needs in energy, materials, and medicine, but it is often time-consuming. Cell-free synthetic biology has emerged as a powerful tool to accelerate design-build-test-learn cycles for pathway engineering with increased tolerance to toxic compounds. However, most cell-free pathway prototyping to date has been performed in extracts from wildtype cells which often do not have sufficient flux towards the pathways of interest, which can be enhanced by engineering. Here, in this study, to address this gap, we create a set of engineered Escherichia coli and Saccharomyces cerevisiae strains rewired via CRISPR-dCas9 to achieve high-flux toward key metabolic precursors; namely, acetyl-CoA, shikimate, triose-phosphate, oxaloacetate, α-ketoglutarate, and glucose-6-phosphate. Cell-free extracts generated from these strains are used for targeted enzyme screening in vitro. As model systems, we assess in vivo and in vitro production of triacetic acid lactone from acetyl-CoA and muconic acid from the shikimate pathway. The need for these platforms is exemplified by the fact that muconic acid cannot be detected in wildtype extracts provided with the same biosynthetic enzymes. We also perform metabolomic comparison to understand biochemical differences between the cellular and cell-free muconic acid synthesis systems (E. coli and S. cerevisiae cells and cell extracts with and without metabolic rewiring). While any given pathway has different interfaces with metabolism, we anticipate that this set of pre-optimized, flux enhanced cell extracts will enable prototyping efforts for new biosynthetic pathways and the discovery of biochemical functions of enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Impacts of Sea‐Level Rise on Coastal Groundwater Table Simulated by an Earth System Model With a Land‐Ocean Coupling Scheme

Abstract Sea‐level rise (SLR) poses a severe threat to the coastal environment through seawater intrusion into freshwater aquifers. The rising groundwater table also exacerbates the risk of pluvial, fluvial, and groundwater flooding in coastal regions. However, current Earth system models (ESMs) commonly ignore the exchanges of water at the land‐ocean interface. To address this gap, we developed a novel land‐ocean hydrologic coupling scheme in a state‐of‐the‐science ESM, the Energy Exascale Earth System Model version 2 (E3SMv2). The new scheme includes the lateral exchange between seawater and groundwater and the vertical infiltration of seawater driven by the SLR‐induced inundation. Simulations were performed with the updated E3SMv2 for the global land‐ocean interface to assess the impacts of SLR on coastal groundwater under a high CO 2 emission scenario. By the middle of this century, seawater infiltration on the inundated areas will be the dominant component in the land‐ocean coupling process, while the lateral subsurface flow exchange will be much smaller. The SLR‐induced seawater infiltration will raise the groundwater levels, enhance evapotranspiration, and increase runoff with distinct spatial patterns globally in the future. Although the coupling process is induced by SLR, we found topography and warming temperature have more control on the coupling impacts, probably due to the relatively modest magnitude of SLR during the selected future period. Overall, our study suggests significant groundwater and seawater exchange at the land‐ocean interface, which needs to be considered in ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

NRC Multiphysics Analysis Capability Deployment FY2020: Part 3

This report details progress and activities of Idaho National Laboratory (INL) on the Nuclear Regulatory Commission (NRC) project “Development and Modeling Sup- port for Advanced Non-Light Water Reactors.” The tasks completed for this report are: Task2c: Explicit modeling of pebble transient temperature response. In this simulation, the 400 MWth Pebble-Bed Modular Reactor (PBMR) design, PBMR- 400, experiences a 20-second power ramp from 100% to 150% power. This is followed by a similar reduction in the power back to 100%. Several multiscale pebble coupling approaches are tested with one pebble per mesh element in the active core region. The results show good conservation behavior and the stability of the coupling.; Extended scope part 1: An assessment of the computational efficiency of the Discontinuous Finite Element Method (DFEM) heat transfer solver shows good scalability. The DFEM solver is a factor of 4 more expensive in solution time than the Finite Element Method (FEM) solver for heat transfer problems due to the increased number of degrees of freedom. Nonetheless, the DFEM approach provides the user with the flexibility to model gap heat transfer problems.; Extended scope part 2: The GapHeatTransferInterfaceMaterial was improved to give the user increased flexibility with the modeling of heat transfer through gaps with the DFEM solver. A number of gap parameters can now be coupled both through functions and variables.; Extended scope part 3: Demonstration of how the gap width between hexagonal fuel cells can be calculated during a heat-up transient and used in the GapHeatTransferInterface model. A full-domain DFEM model with gap expansion is coupled to a SubApp that models the thermal expansion of the base plate. The results show the expected physical behavior, although have not been fully bench-marked at this point in time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Contributing to Long-term Wind Resource Characterization through Buoy-based Observations of Meteorological and Oceanographic Conditions

The U.S. Department of Energy (DOE) supports development of renewable power generation within the U.S. with increasing emphasis on offshore wind energy. This development is currently impeded by a lack of long-term wind observations above the ocean surface at wind turbine rotor plane heights. Pacific Northwest National Laboratory (PNNL) procured two AXYS WindSentinelTM buoys on behalf of DOE to support offshore wind resource assessment. The buoys are available for loan to qualified users according to agency priorities. The Lidar Buoy Loan Program represents an opportunity for organizations with an interest in offshore wind energy to work together with DOE to provide valuable meteorological and oceanographic data to the offshore community that is needed for offshore wind resource characterization. The buoys have already begun to fill observational gaps in offshore winds during long-term deployments off the coasts of Virginia and New Jersey and are scheduled for deployment off the coast of California in 2020. This paper provides an overview of the Lidar Buoy Loan Program, along with highlights of previous deployments, a summary of the upgrades to the lidar systems, and a discussion of the planned activities related to the buoys and the Lidar Buoy Loan Program.

floating lidar, offshore wind energy, wind resourc↗
DOE OSTI2025

Clumping index estimation with 30°-tilted cameras in row crops: Evaluation of methods and segment size effects

The clumping index (CI) quantifies the spatial distribution of foliage elements and is essential for accurately estimating the plant area index (PAI), canopy radiative transfer, and photosynthesis. Traditionally, the finite-length averaging method (LX), the gap size distribution method (CC), and a combined approach of CC and LX (CLX) have been applied to instruments like TRAC and digital hemispherical photography to estimate CI. However, a comprehensive evaluation of these methods in row crops remains limited, especially regarding the influence of segment size on CI. Meanwhile, digital cameras offer a cost-effective and user-friendly solution for canopy measurements in row crops, yet their application in this context remains underexplored. In this study, we employed a new approach using a 30°-tilted digital camera to estimate CI in corn and soybean fields, applying the LX, CC, and CLX methods. We systematically assessed the performance of these three methods by combining field measurements in real-world fields with simulations using the LESS 3D radiative transfer model. Our results showed that CLX applied to the whole image and 45° segment offered accurate estimation of CI (bias within ±0.1, RMSE < 0.2) and PAI (bias within ±0.4, RMSE < 1) in real-world fields and LESS simulations. The accuracy of the LX method was highly sensitive to segment size, with the best performance observed at the 15° segment (PAI bias within ±0.4). In contrast, the CC method remained stable across different segment sizes, and its performance was generally comparable to that of LX, except at the 15° segment. Across view zenith angles, CI derived from CC generally showed a continuous increase, while those from LX and CLX followed a rising trend at small zenith angles but began to decline at 68°, likely due to an increasing proportion of no-gap segments. Seasonally, LX tended to show decreasing CI during early growth stages but increased as the canopy matured, whereas CC and CLX showed gradually increasing CI before plateauing at peak PAI. The 30°-tilted camera effectively captured CI variations across different angles and growth stages, making it a practical and robust instrument for row crop canopy structure analysis. Furthermore, applying these CI methods to digital cameras offers a low-cost and accessible CI estimation alternative, improving canopy structure monitoring accuracy in row crops.

30°-tilted camera↗
DOE OSTI2023

Review of quantitative methods to assess impacts of changing climate and socioeconomic conditions on Arctic transportation systems

Rapid climate and socioeconomic changes are transforming Arctic human- Earth systems. An integral part of these systems is mobility, which encompasses the transport of humans and goods into, out of, and between Arctic regions. Impacts of climate and socioeconomic drivers on Arctic mobility are heterogenous. Methodologies are needed to quantify these impacts in measures that can be linked with broader socioeconomic systems. This article reviews existing such methods and organizes them into a conceptual framework to understand trends and gaps in the literature. We found methods quantifying impacts of a range of climate drivers on most transportation modes present in the Arctic, but few methods focused on socioeconomic drivers. Also underrepresented were methods explicitly considering adaptive capacity of transportation systems. In conclusion, we provide insight into the data and relationships relevant to understanding impacts of Arctic change on transportation systems and how these impacts fit into broader human- Earth systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Thirdhand tobacco smoke exposure increases the genetic background-dependent risk of pan-tumor development in Collaborative Cross mice

Increasing evidence has shown that thirdhand smoke (THS) exposure is likely to induce adverse health effects. An important knowledge gap remains in our understanding of THS exposure related to cancer risk in the human population. Population-based animal models are useful and powerful in investigating the interplay between host genetics and THS exposure on cancer risk. Here, we used the Collaborative Cross (CC) mouse population-based model system, which recapitulates the genetic and phenotypic diversity observed in the human population, to assess cancer risk after a short period of exposure, between 4 and 9 weeks of age. Eight CC strains (CC001, CC019, CC026, CC036, CC037, CC041, CC042 and CC051) were included in our study. We quantified pan-tumor incidence, tumor burden per mouse, organ tumor spectrum and tumor-free survival until 18 months of age. At the population level, we observed a significantly increased pan-tumor incidence and tumor burden per mouse in THS-treated mice as compared to the control (p = 3.04E-06). Lung and liver tissues exhibited the largest risk of undergoing tumorigenesis after THS exposure. Tumor-free survival was significantly reduced in THS-treated mice compared to control (p = 0.044). At the individual strain level, we observed a large variation in tumor incidence across the 8 CC strains. CC036 and CC041 exhibited a significant increase in pan-tumor incidence (p = 0.0084 and p = 0.000066, respectively) after THS exposure compared to control. We conclude that early-life THS exposure increases tumor development in CC mice and that host genetic background plays an important role in individual susceptibility to THS-induced tumorigenesis. Genetic background is an important factor that should be taken into account when determining human cancer risk of THS exposure.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Visual‐Analytics Bridge Complexity and Accessibility for Robust Urban Water Planning

Urban water resources planning is complicated by unprecedented uncertainty in supply and demand. Real‐world planning often simplifies the full range of uncertainty faced by a system into a limited set of deterministic scenarios to enhance accessibility for decision‐makers and the public. However, overlooking uncertainty can expose the system to failures. On the other end of the spectrum, academically developed tools for scenario analysis rigorously quantify the combined effects of multiple sources of uncertainty, but the practical application of these models is limited by the challenges of information visualization and communication of results. In short, municipal water supply planners lack access to planning frameworks that effectively integrate a rigorous treatment of uncertainty with accessible, user‐friendly visual and interactive tools to enhance user accessibility. In this work, we fill this gap by proposing Visual‐Robust Decision Making, and demonstrate an application for the city of Santa Barbara (SB), CA. Santa Barbara faces multiple uncertainties from pending state and federal regulations to changing hydrology and water demand. The city seeks to increase its water portfolio robustness by expanding its seawater desalination plant, but must decide how much capacity to add. We introduce computational tools that assess uncertainty across nine uncertain drivers identified with the help of water planners in SB. To allow public participation in the desalination expansion decision, we develop interactive visual‐analytics to aid decision‐makers and stakeholders in navigating complex scenario analysis outcomes. Our results quantify the tradeoffs between increased capacity and system robustness and aim to enhance participation and uncertainty characterization of urban water planning efforts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Fine-scale landscape characteristics, vegetation composition, and snowmelt timing control phenological heterogeneity across low-Arctic tundra landscapes in Western Alaska

The Arctic is warming at over twice the rate of the rest of the Earth, resulting in significant changes in vegetation seasonality that regulates annual carbon, water, and energy fluxes. However, a crucial knowledge gap exists regarding the intricate interplay among climate, permafrost, and vegetation that generates high phenology variability across extensive tundra landscapes. This oversight has led to significant discrepancies in phenological patterns observed across warming experiments, long-term ecological observations, and satellite and modeling studies, undermining our ability to understand and forecast plant responses to climate change in the Arctic. To address this problem, we assessed plant phenology across three low-Arctic tundra landscapes on the Seward Peninsula, Alaska, using a combination of in-situ phenocam observations and high-resolution PlanetScope CubeSat data. We examined the patterns and drivers of phenological diversity across the landscape by (1) quantifying phenological diversity among dominant plant function types (PFTs) and (2) modeling the interrelations between plant phenology and fine-scale landscape features, such as topography, snowmelt, and vegetation. Our findings reveal that both spring and fall phenology varied significantly across Arctic PFTs, accounting for about 25%–44% and 34%–59% of the landscape-scale variation in the start of spring [SOS] and start of fall [SOF], respectively. Deciduous tall shrubs (e.g. alder and willow) had a later SOS (~7 d behind the mean of other PFTs), but completed leaf expansion (within 2 weeks) considerably faster compared to other PFTs. We modeled the landscape-scale variation in SOS and SOF using Random Forest, which showed that plant phenology can be accurately captured by a suite of variables related to vegetation composition, topographic characteristics, and snowmelt timing (variance explained: 53%–68% for SOS and 59%–82% for SOF). Notably, snowmelt timing was a crucial determinant of SOS, a factor often neglected in most spring phenology models. Our study highlights the impact of fine-scale vegetation composition, snow seasonality, and landscape features on tundra phenological heterogeneity. Improved understanding of such considerable intra-site phenological variability and associated proximate controls across extensive Arctic landscapes offers critical insights for representation of tundra phenology in process models and associated impact assessments with climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

An operator-based approach to topological photonics

Abstract Recently, the study of topological structures in photonics has garnered significant interest, as these systems can realize robust, nonreciprocal chiral edge states and cavity-like confined states that have applications in both linear and nonlinear devices. However, current band theoretic approaches to understanding topology in photonic systems yield fundamental limitations on the classes of structures that can be studied. Here, we develop a theoretical framework for assessing a photonic structure’s topology directly from its effective Hamiltonian and position operators, as expressed in real space, and without the need to calculate the system’s Bloch eigenstates or band structure. Using this framework, we show that nontrivial topology, and associated boundary-localized chiral resonances, can manifest in photonic crystals with broken time-reversal symmetry that lack a complete band gap, a result that may have implications for new topological laser designs. Finally, we use our operator-based framework to develop a novel class of invariants for topology stemming from a system’s crystalline symmetries, which allows for the prediction of robust localized states for creating waveguides and cavities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2

The project Characterization of Pliocene and Miocene Formations in the Wilmington Graben, Offshore Los Angeles, for Large-Scale Geologic Storage of CO2 is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Los Angeles Basin presents an opportunity for large-scale geologic CO2 storage. Due to its large population and historical and geologic setting as one of the most prolific oil and gas producing basins in the United States, the region is home to more than 12 major power plants and oil refineries that produce more than 5 million metric tons of fossil fuel-related CO2 emissions each year. GeoMechanics Technologies worked to characterize the Pliocene and Miocene sediments in the Wilmington Graben, offshore of Los Angeles, California, for high-volume CO2 storage. The Graben is located offshore of the Los Angeles and Long Beach Harbor area, making it accessible yet geologically isolated from the nearby Wilmington oilfield and onshore areas. These sediments span more than 5,000 feet of vertical interval with an estimated storage resource of more than 100 million metric tons of CO2. The project team analyzed and interpreted existing geologic data within the region, including detailed exploration well log data and 2-D and 3-D seismic data. New seismic lines were acquired to fill in current data gap areas and two new characterization wells were drilled and logged. This information was integrated with existing geologic interpretations for adjacent onshore areas to help characterize optimal areas for CO2 storage and seals to safely store CO2. Integrated 3-D geologic and geomechanical models for the Wilmington Graben were developed to simulate the fate and transport of injected CO2 in the subsurface and to assess risks. This project contributed to the understanding of injectivity, containment mechanisms, rate of dissolution and mineralization, and storage capacity of the Wilmington Graben and associated analogous basins. This effort also provided greater insight into the potential for offshore geologic formations to safely and permanently store CO2.

.las↗