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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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NASA NTRS2019

Expanding the Sample of Radio Minihalos in Galaxy Clusters

Radio minihalos are diffuse synchrotron sources of unknown origin found in the cool cores of some galaxy clusters. We use GMRT and VLA data to expand the sample of minihalos by reporting three new minihalo detections (A2667, A907, and PSZ1 G139.61+24.20) and confirming minihalos in five clusters (MACS J0159.8–0849, MACS J0329.6–0211, RXC J2129.6+0005, AS 780, and A3444). With these new detections and confirmations, the sample now stands at 23, the largest sample to date. For consistency, we also reanalyze archival VLA 1.4 GHz observations of seven known minihalos. We revisit possible correlations between the nonthermal emission and the thermal properties of their cluster hosts. Consistent with our earlier findings from a smaller sample, we find no strong relation between the minihalo radio luminosity and the total cluster mass. Instead, we find a strong positive correlation between the minihalo radio power and X-ray bolometric luminosity of the cool core (r < 70 kpc). This supplements our earlier result that most, if not all, cool cores in massive clusters contain a minihalo. Comparison of radio and Chandra X-ray images indicates that the minihalo emission is typically confined by concentric sloshing cold fronts in the cores of most of our clusters, supporting the hypothesis that minihalos arise from electron reacceleration by turbulence caused by core gas sloshing. Taken together, our findings suggest that the origin of minihalos should be closely related to the properties of thermal plasma in cluster cool cores.

Galaxies radio continuum↗
NASA NTRS2021

Transition Analysis for the CRM-NLF Wind Tunnel Configuration

This paper presents the results of an ongoing study into the linear stability characteristics of the boundary layer flow over the common research model with natural laminar flow (CRMNLF) aircraft configuration. The flow conditions match selected test conditions from a recent wind tunnel experiment in the National Transonic Facility at the NASA Langley Research Center. Previous work involving parallel stability computations of a boundary layer flow based on the conical flow approximation has shown that the measured onset of laminar-turbulent transition during the experiments can be correlated with the linear amplification of Tollmien- Schlichting (TS) and stationary crossflow (CF) instabilities in the swept wing boundary layer. Here, we examine the effects of the simplifying approximations in both basic state computation and the stability analysis, with the goal of quantifying the resulting changes in the N-factor correlations. Specifically, the basic states are computed by using full Navier-Stokes equations and the stability analysis is performed by using a nonorthogonal coordinate system that allows a clear distinction between planar TS and CF instabilities. Furthermore, the effects of curvature and nonparallel mean flow have been included in the stability computations based on the parabolized stability equations (PSE). The fully turbulent Reynolds-Averaged-Navier-Stokes (RANS) mean flow solutions show good agreement with the measured wall pressure distribution. Viscous-inviscid interactive effects are observed to be important because the shock fronts along the suction surface are influenced by the imposed transition front. The stability results confirm the previous findings related to TS amplification within the inboard region of the wing and the dominance of stationary CF modes in the outboard region. However, given the close proximity of the measured transition front and the dual shock system within the outer part of the wing, the onset of transition may well be shock limited within the outboard region. In general, the transition criterion based on the dual N-factor method with N TS = N CF = 6 is reasonably successful at correlating with the measured transition fronts at Re MAC = 15 million and AoA = 1.5, 2 degrees; however, the low values of the correlating N-factors at Re MAC = 17.5 million support the hypothesis that the measured transition at the higher Reynolds number may have been strongly influenced by the merging of turbulent wedges that originate from surface imperfections near the leading edge.

Boundary layer transition↗
NASA NTRS2021

Transition Analysis for the CRM-NLF Wind Tunnel Configuration

This paper presents the results of an ongoing study into the linear stability characteristics of the boundary layer flow over the common research model with natural laminar flow (CRMNLF) aircraft configuration. The flow conditions match selected test conditions from a recent wind tunnel experiment in the National Transonic Facility at the NASA Langley Research Center. Previous work involving parallel stability computations of a boundary layer flow based on the conical flow approximation has shown that the measured onset of laminar-turbulent transition during the experiments can be correlated with the linear amplification of Tollmien- Schlichting (TS) and stationary crossflow (CF) instabilities in the swept wing boundary layer. Here, we examine the effects of the simplifying approximations in both basic state computation and the stability analysis, with the goal of quantifying the resulting changes in the N-factor correlations. Specifically, the basic states are computed by using full Navier-Stokes equations and the stability analysis is performed by using a nonorthogonal coordinate system that allows a clear distinction between planar TS and CF instabilities. Furthermore, the effects of curvature and nonparallel mean flow have been included in the stability computations based on the parabolized stability equations (PSE). The fully turbulent Reynolds-Averaged-Navier-Stokes (RANS) mean flow solutions show good agreement with the measured wall pressure distribution. Viscous-inviscid interactive effects are observed to be important because the shock fronts along the suction surface are influenced by the imposed transition front. The stability results confirm the previous findings related to TS amplification within the inboard region of the wing and the dominance of stationary CF modes in the outboard region. However, given the close proximity of the measured transition front and the dual shock system within the outer part of the wing, the onset of transition may well be shock limited within the outboard region. In general, the transition criterion based on the dual N-factor method with N TS = N CF = 6 is reasonably successful at correlating with the measured transition fronts at Re MAC = 15 million and AoA = 1.5, 2 degrees; however, the low values of the correlating N-factors at Re MAC = 17.5 million support the hypothesis that the measured transition at the higher Reynolds number may have been strongly influenced by the merging of turbulent wedges that originate from surface imperfections near the leading edge.

Boundary layer transition↗
NASA NTRS2021

Aerosol Absorption in Global Models From AeroCom Phase III

Aerosol-induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates, precipitation, and cloud formation. Presently, the total amount of aerosol absorption is poorly constrained, and the main absorbing aerosol species (black carbon (BC), organic aerosols (OA), and mineral dust) are diversely quantified in global climate models. As part of the third phase of the Aerosol Comparisons between Observations and Models (AeroCom) intercomparison initiative (AeroCom phase III), we here document the distribution and magnitude of aerosol absorption in current global aerosol models and quantify the sources of intermodel spread, highlighting the difficulties of attributing absorption to different species. In total, 15 models have provided total present-day absorption at 550 nm (using year 2010 emissions), 11 of which have provided absorption per absorbing species. The multi-model global annual mean total absorption aerosol optical depth (AAOD) is 0.0054 (0.0020 to 0.0098; 550 nm), with the range given as the minimum and maximum model values. This is 28 % higher compared to the 0.0042 (0.0021 to 0.0076) multi-model mean in AeroCom phase II (using year 2000 emissions), but the difference is within 1 standard deviation, which, in this study, is 0.0023 (0.0019 in Phase II). Of the summed component AAOD, 60 % (range 36 %–84 %) is estimated to be due to BC, 31 % (12 %–49 %) is due to dust, and 11 % (0 %–24 %) is due to OA; however, the components are not independent in terms of their absorbing efficiency. In models with internal mixtures of absorbing aerosols, a major challenge is the lack of a common and simple method to attribute absorption to the different absorbing species. Therefore, when possible, the models with internally mixed aerosols in the present study have performed simulations using the same method for estimating absorption due to BC, OA, and dust, namely by removing it and comparing runs with and without the absorbing species. We discuss the challenges of attributing absorption to different species; we compare burden, refractive indices, and density; and we contrast models with internal mixing to models with external mixing. The model mean BC mass absorption coefficient (MAC) value is 10.1 (3.1 to 17.7) m 2 g −1 (550 nm), and the model mean BC AAOD is 0.0030 (0.0007 to 0.0077). The difference in lifetime (and burden) in the models explains as much of the BC AAOD spread as the difference in BC MAC values. The difference in the spectral dependency between the models is striking. Several models have an absorption Ångstrøm exponent (AAE) close to 1, which likely is too low given current knowledge of spectral aerosol optical properties. Most models do not account for brown carbon and underestimate the spectral dependency for OA.

Aerosol absorption↗
NASA NTRS2022

The Abundances of F, Cl, and H2O in 4Vesta from Eucrites

The abundance and distribution of magmatic volatiles (i.e., H, C, N, F, S, and Cl) within the silicate portion of a differentiated planetary body has important consequences on its thermochemical evolution. However, the abundances of magmatic volatiles within differentiated bodies are difficult to quantify, and they are often depleted by varying degrees relative to CI chondrites. The mechanisms of depletion are not well constrained and could relate to intrinsic volatile depletion of the building blocks that formed the bodies, high temperature processes that result from accretion, post-accretion loss through parent body geological processes and large-scale impacts, and/or redistribution within a parent body through processes like core formation [1–4]. In the present study, we aim to constrain the abundances of F, Cl, and H2O in eucrites to better understand the magnitude of volatile depletion on 4Vesta. To accomplish this objective, we report electron microprobe analyses of apatite from seven unbrecciated, non-cumulate eucrites (i.e., CMS 04049,GRA 98098, LEW 88010, MAC 02522, MAC 041169,QUE 94484, and QUE 97053) and two monomict, non-cumulate eucrites (i.e., Berthoud and Stannern). In combination with previously published data on eucrite-hosted apatite, we determine Cl/F and H2O/F ratios in bulk rock eucrites through the application of apatite-based melt hygrometry and chlorometry [e.g., 5–7].Additionally, we estimate the bulk rock abundances of F in six non-cumulate eucrites (i.e., GRA 98098, MAC041169, PCA 91078, QUE 97053, Stannern, and Berthoud), which we combine with previously published bulk rock F data on non-cumulate eucrites[8] to constrain the abundances of F, Cl, and H2O in 4Vesta using appropriately paired volatile/refractory element ratios for F, followed by Cl/F and H2O/F ratios for Cl and H2O, respectively.

F M McCubbin↗
NASA NTRSDate not supplied

Estimation of Timing Performance with Pulsed Laser Links for Small Satellite PNT

Satellite constellations are growing in size and in utility for applications as diverse as providing reliable, low-latency internet service to rural areas orEarth science missions.This expansion of satellite constellations brings attention to the need for responsive and reliable satellite communication.Current research in the PrecisionSpace Systems Laboratory at the University of Florida focuses on using pulsed laser communications as the method of relaying time signals instead of the radio frequency (RF)signals.The upcoming CLICK (CubeSat Laser Infrared CrosslinK) missions (Massachusetts Institute of Technology, University of Florida, NASA Ames Research Center) will demonstrate a spacecraft-to-spacecraft laser communication link and time-transfer.For pre-flight technology assessment of missions such as CLICK, a simulation of a spacecraft constellation in Earth orbit has been created to estimate clock synchronization and precision orbit determination based on measured instrumentation performance.We have developed a novel MATLAB-based numerical simulator to model spacecraft-to-spacecraft laser time-transfer and estimate the offset between the spacecraft clocks over time.This simulation includes timing errors associated with laser pulse generation and detection, as well as non-Gaussian clock drift models.The two on-board clocks modeled are a cesium-based Chip-Scale Atomic Clock (CSAC) and a rubidium-based Miniature Atomic Clock (MAC), both produced by Microchip.An example case of two spacecraft in a circular, low-Earth orbit receiving GPS position, GPS timing, and laser pulse time-of-flight measurements is simulated.The positions and velocities of the two spacecraft at a reference epoch and the constant clock model coefficients are estimated.Polynomial models of different orders were used as clock models. The effect of clock model order on the root-mean-square (RMS) of the clock error is apparent in the case using GPS and lasing measurements, showing that the clock model improves with increasing clock model order. Results compare the estimated clock model of a mission operation that only uses GPS measurements and a mission operation that uses both GPS and laser pulse time-of-flight measurements between spacecraft referenced to their on-board CSACs or on-board MACs. Including lasing measurements reduces the RMS clock model error by approximately 80% of the RMS of the cases with only GPS measurements.This simulation tool can be used to optimize the lasing operations schedule based on mission timing performance objectives. During this presentation, I will discuss the details of the simulation and clock model estimation, as well as discuss the results.I will compare the results of incorporating lasing timing measurements to using only GPS measurements and the outcomes of using different orders of polynomials.

Timing Performance↗
NASA NTRS1993

Origin of water masers in W49N

It is proposed that H2O masers in star-forming regions occur early in the expansion of thin shells swept up by high-velocity winds from young massive stars. In W49N, confinement of the shell by a density distribution with an axial cavity can explain both the velocity field and the shape of the mass distribution. A modified version of the thin-shell code of Mac Low and McCray (1988), including radiation cooling, is used to model dynamically the expanding shell.

Mac Low, Mordecai-Mark↗
NASA NTRS2006

Maximum von Mises Stress in the Loading Environment of Mass Acceleration Curve

Method for calculating stress due to acceleration loading: 1) Part has been designed by FEA and hand calculation in one critical loading direction judged by the analyst; 2) Maximum stress can be due to loading in another direction; 3) Analysis procedure to be presented determines: a) The maximum Mises stress at any point; and b) The direction of maximum loading associated with the "stress". Concept of Mass Acceleration Curves (MAC): 1) Developed by JPL to perform preliminary structural sizing (i.e. Mariners, Voyager, Galileo, Pathfinder, MER,...MSL); 2) Acceleration of physical masses are bounded by a curve; 3) G-levels of vibro-acoustic and transient environments; 4) Convergent process before the couple loads cycle; and 5) Semi-empirical method to effectively bound the loads, not a simulation of the actual response.

von Mises stress↗
NASA NTRS2016

Deja Vu All Over Again: The Reappearance of Supernova Refsdal

In Hubble Space Telescope (HST) imaging taken on 2014 November 10, four images of supernova (SN) Refsdal(redshift z1.49) appeared in an Einstein-cross-like configuration (images S1S4) around an early-type galaxy in the cluster MACS J1149.5+2223 (z0.54). Almost all lens models of the cluster have predicted that the SN should reappear within a year in a second host-galaxy image created by the clusters potential. In HST observations taken on 2015 December 11, we find a new source at the predicted position of the new image of SN Refsdal approximately 8 from the previous images S1S4. This marks the first time the appearance of a SN at a particular time and location in the sky was successfully predicted in advance! We use these data and the light curve from the first four observed images of SN Refsdal to place constraints on the relative time delay and magnification of the new image (SX) compared to images S1S4. This enables us, for the first time, to test blind lens model predictions of both magnifications and time delays for a lensed SN. We find that the timing and brightness of the new image are consistent with the blind predictions of a fraction of the models. The reappearance illustrates the discriminatory power of this blind test and its utility to uncover sources of systematic uncertainty. From planned HST photometry, we expect to reach a precision of 12 on the time delay between S1S4 and SX.

galaxies: clusters: general – galaxies: individu↗
DOE OSTI2025

Structure Prediction of Ionic Epitaxial Interfaces with Ogre Demonstrated for Colloidal Heterostructures of Lead Halide Perovskites

Colloidal epitaxial heterostructures are nanoparticles composed of two different materials connected at an interface, which can exhibit properties different from those of their individual components. Combining dissimilar materials offers exciting opportunities to create a wide variety of functional heterostructures. However, assessing structural compatibility–the main prerequisite for epitaxial growth–is challenging when pairing complex materials with different lattice parameters and crystal structures. This complicates both the selection of target heterostructures for synthesis and the assignment of interface models when new heterostructures are obtained. Here, we demonstrate Ogre as a powerful tool to accelerate the design and characterization of colloidal heterostructures. To this end, we implemented developments tailored for the high-efficiency prediction of epitaxial interfaces between ionic/polar materials, which encompass most colloidal semiconductors. These include the use of pre-screening candidate models based on charge balance at the interface and the use of a classical potential for fast energy evaluations, with parameters automatically calculated based on the input bulk structures. These developments are validated for perovskite-based CsPbBr 3 /Pb 4 S 3 Br 2 heterostructures, where Ogre produces interface models in excellent agreement with density functional theory and experiments. Furthermore, we use Ogre to rationalize the templating effect of CsPbCl 3 on the growth of lead sulfochlorides, where perovskite seeds induce the formation of Pb 4 S 3 Cl 2 rather than Pb 3 S 2 Cl 2 due to better epitaxial compatibility. Finally, combining Ogre simulations with experimental data enables us to unravel the structure and composition of the hitherto unsolved CsPbBr 3 /Bi x Pb y S z interface, and to assign a structure to several other reported metal halide- and oxide-based interfaces. The Ogre package is available on GitHub or via the OgreInterface desktop application, available for Windows, Linux, and Mac.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Dual blockade of IL-10 and PD-1 leads to control of SIV viral rebound following analytical treatment interruption

Human immunodeficiency virus (HIV) persistence during antiretroviral therapy (ART) is associated with heightened plasma interleukin-10 (IL-10) levels and PD-1 expression. We hypothesized that IL-10 and PD-1 blockade would lead to control of viral rebound following analytical treatment interruption (ATI). Twenty-eight ART-treated, simian immunodeficiency virus (SIV)mac 239 -infected rhesus macaques (RMs) were treated with anti-IL-10, anti-IL-10 plus anti-PD-1 (combo) or vehicle. ART was interrupted 12 weeks after introduction of immunotherapy. Durable control of viral rebound was observed in nine out of ten combo-treated RMs for >24 weeks post-ATI. Induction of inflammatory cytokines, proliferation of effector CD8 + T cells in lymph nodes and reduced expression of BCL-2 in CD4 + T cells pre-ATI predicted control of viral rebound. Twenty-four weeks post-ATI, lower viral load was associated with higher frequencies of memory T cells expressing TCF-1 and of SIV-specific CD4 + and CD8 + T cells in blood and lymph nodes of combo-treated RMs. These results map a path to achieve long-lasting control of HIV and/or SIV following discontinuation of ART.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Accessible, uniform protein property prediction with a scikit-learn based toolset AIDE

Summary Protein property prediction via machine learning with and without labeled data is becoming increasingly powerful, yet methods are disparate and capabilities vary widely over applications. The software presented here, “Artificial Intelligence Driven protein Estimation (AIDE)”, enables instantiating, optimizing, and testing many zero-shot and supervised property prediction methods for variants and variable length homologs in a single, reproducible notebook or script by defining a modular, standardized application programming interface (API), i.e. drop-in compatible with scikit-learn transformers and pipelines. Availability and implementation AIDE is an installable, importable python package inheriting from scikit-learn classes and API and is installable on Windows, Mac, and Linux. Many of the wrapped models internal to AIDE will be effectively inaccessible without a GPU, and some assume CUDA. The newest stable, tested version can be found at https://github.com/beckham-lab/aide_predict and a full user guide and API reference can be found at https://beckham-lab.github.io/aide_predict/. Static versions of both at the time of writing can be found on Zenodo.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Irreducible Bhabha background in the detection of muonium-antimuonium conversion

Experiments such as MACS and the proposed MACE study muonium-antimuonium conversion by the energies of the final state 𝑒 ± . The 𝑒 + and 𝑒 − from an antimuonium decay tend to be nonrelativistic and relativistic, respectively, and vice versa for muonium. However, these 𝑒 ± can exchange their energies by hard Bhabha scattering, causing muonium to fake an antimuonium decay signal. We compute the rate for this background and find that, while negligible for MACE, it will become larger than the signal for conversion probabilities less than 10 −18 .

muonium↗
DOE OSTI2026

ObstacleSense: Low-Power Neuromorphic Vision for Corridor Obstacle Awareness in Low-Level ADAS

The automotive industry’s pursuit of Level 5 autonomy is constrained by substantial perception-compute power requirements, often reaching 1, 000 + watts in full autonomy stacks. Reducing this energy burden requires rethinking perception not only at the high-end autonomy level, but also at the foundational Advanced Driver Assistance Systems (ADAS) level where low-power, safety-critical sensing can have broad impact. Neuromorphic vision provides a promising starting point: HD Dynamic Vision Sensors (DVS) can operate below 100 mW at the sensor level by reporting only asynchronous brightness changes. However, low-power sensing alone is insufficient if downstream perception reintroduces dense, energy-intensive computation. In particular, many event-driven object-detection pipelines still rely on CNN backbones, while purely spiking alternatives often trade away accuracy or ignore deployment constraints. We introduce ObstacleSense, a highly compact, CNN-free hybrid ANN–SNN framework for Level 0–1 forward-corridor obstacle awareness. Instead of performing full-scene object detection with a convolutional feature backbone, ObstacleSense targets the safety-critical question of whether the ego corridor is occupied and how far the nearest obstacle is. The architecture combines polarity-conditioned event encoding, lightweight temporal spiking dynamics, axial spatial mixing, and coarse-to-fine range estimation within a regular fixed-grid compute pattern. This design avoids the dense CNN backbone commonly used in event-based detection while maintaining a small state footprint suitable for eventual small-FPGA deployment. Before hardware mapping, we evaluate the software implementation using a model-side power proxy derived from MACs, weight and activation traffic, and spiking state updates under shared FP16 assumptions. On simulated CARLA event corpora, the deployment-oriented model achieves 0.9464 objectness F1, 0.9978 grid-level mAP, and 0.8987 m distance Mean Absolute Error at an estimated 1.92 mW proxy cost, while maintaining performance on unseen generalization test sequences.

Johnson-Scott, Zac [ORNL]↗
DOE OSTI2025

Accessible Content Optimization for Research Needs (ACORN)

ACORN employs a set of automated processes for informing and/or enforcing defined content schemas to create standardized and highly structured data. Because of its standardized data source, ACORN easily applies computer automation to generate communication assets such as PDFs, Powerpoint presentations, and web pages. Built using the memory-safe Rust programming language, ACORN is portable and accessible for use on any Windows, Mac, or Linux machine.

Wohlgemuth, JasonHoward [Oak Ridge National Labora↗
DOE OSTI2025

Extratropical Cloud Feedback Constrained by Cloud Sources and Sinks in Cyclones

Constraining cloud feedback in global climate models (GCMs) using observations is important for establishing accurate predictions of future climate. Uncertainty in shortwave cloud feedback (SW FB ) dominates uncertainty in total cloud feedback. Recent studies show a shift toward more positive extratropical SW FB in the latest generations of GCMs leading to the emergence of very high equilibrium climate sensitivity (ECS). In this study, we use precipitation efficiency and albedo susceptibility to constrain liquid water path (LWP) response to warming and SW FB in the Southern Ocean (SO; 50°–80°S). We analyze precipitation in extratropical cyclones (ECs) to learn about extratropical condensed water sink processes, combined with observations of clouds and moisture convergence, and use the analysis to better understand and constrain SW FB . We utilize a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model, version 6 (CAM6), to provide a constraint on SW FB based on observations from Clouds and the Earth’s Radiant Energy System (CERES) and Multisensor Advanced Climatology of LWP (MAC-LWP). We apply Gaussian process regression to emulate the model response to all parameters perturbed in the PPE. Confronting the emulator output with observations provides a new estimated response of Earth to global warming. Furthermore, our new estimates of SO LWP reduce the PPE range by 66%–72%, which results in a shortwave cloud radiative effect estimated range that is 27%–34% less than the PPE range. Observations suggest a more positive SO SW FB than the Community Earth System Model, version 2 (CESM2), and consequently do not reject the high climate sensitivity GCMs emerging from the Coupled Model Intercomparison Project phase 6 (CMIP6).

Atmosphere↗
DOE OSTI2024

A Novel Framework to Evaluate the Costs and Potential of Bioenergy in Decarbonization of the U.S. Economy

The long-term strategy of the United States targets reaching economy-wide net-zero emissions by 2050 and a carbon-neutral electricity grid by 2035 (U.S. Department of State and U.S. Executive Office of the President, 2021). Meeting these targets would require considerable changes to the energy system. Some key characteristics of illustrative net-zero energy systems include increased penetration of renewable energy and carbon sources, use of CO2 capture and storage (CCS) in hard-to-abate sectors, and a greater role for energy carriers such as electricity and hydrogen (Davis et al, 2018). Another common feature of such energy systems is the need for carbon dioxide removal (CDR) approaches (Horowitz et al, 2022). Across all these characteristics of net-zero energy systems, bioenergy and biomass feedstock is anticipated to play an important role. Biomass feedstock serves as a renewable carbon source. This can enable conversion of such feedstock into fuels and energy carriers for hard-to-abate sectors such as aviation. Indeed, the U.S. Government has a target to meet all jet fuel demand by 2050 from sustainable aviation fuel (SAF), where biofuel pathways are likely to have an important role (EERE, 2020). Bioenergy is also highly versatile with the possibility to convert feedstock into electricity, hydrogen, liquid fuels, heat or high-value products, based on biomass type, demand and technology availability (Clarke et al, 2022). Combination of bioenergy with CCS can also nominally deliver CDR (Fuhrman et al, 2023). As such, the share of bioenergy is expected to grow by at least five time across scenarios studied for the long-term strategy of the U.S. between 2020 and 2050 (Horowitz et al, 2022). Notwithstanding the role of bioenergy in the energy systems, its deployment, costs and scalability are influenced by a number of factors. Some of these factors pertain to policy interventions such as imposition of a binding decarbonization target either at an economy-wide level or the sectoral level. Resource availability and type of biomass feedstock also varies considerably across regions. From a technological perspective, the readiness of bioenergy conversion pathways is subject to high variability. This influences the costs of deployment. Moreover, the sourcing of feedstock, grid carbon intensity, and co-product handling approaches all affect the life cycle efficacy of bioenergy. The latter, in turn, is particularly important in determining the extent to which bioenergy with CCS or BECCS can effectively deliver CDR (Fajardy and Mac Dowell, 2017).

air emission↗
DOE OSTI2024

Bryan Mound Collar Compression Study

This report presents a study of collar compression for the wells at the Bryan Mound site. The study includes a comprehensive review of all available Multi-Arm Caliper (MAC) logs from the site, which has been used to identify specific wells that are experiencing casing restrictions at collar joints. Additional site-wide analysis of Bryan Mound well temperature data, proximity to sulphur wells, pulsed eddy current (PEC) logs, and a general spatial analysis has been included.

02 PETROLEUM↗