Two-mode squeezing over deployed fiber coexisting with conventional communications
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Chapman, Joseph↗
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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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KBase partners with community developers from several Department of Energy Science Focus Areas to increase functionality of tools and analysis
Several SFAs were selected for training on the KBase Software Development Kit (SDK) to integrate tools and data into the KBase platform. Overall, the collaborative effort was viewed as highly successful. Every SFA project was able to achieve their proposed targets for training and functionality, while also gaining an appreciation for the role KBase plays/could play in their future science plans. Both the SFA and KBase teams felt that continued collaboration would be beneficial, especially if the programs were able to jointly prioritize scope and readiness of future projects. This poster will outline the scope of functionality added by SFA community developers, and highlight points of intersection across these efforts.
59 BASIC BIOLOGICAL SCIENCES↗
Evolution of structure and transport properties of the Ba 8 Cu 16 P 30 clathrate-I framework with the introduction of Ga
Two type-I clathrates were synthesized by introducing Ga into the framework of the Ba 8 Cu 16 P 30 type-I clathrate. The introduction of minute amounts of Ga, 1.9% Ga/M total (where M total = Cu + Ga), resulted in the disturbance of the completely ordered Pbcn superstructure of Ba 8 Cu 16 P 30 . Ba 8 Cu 15.43(2) Ga 0.3 P 30.26(3) crystallizes in a partially ordered orthorhombic Pmna clathrate-I superstructure with five out of 15 framework sites being jointly occupied by metal+phosphorus. Increasing the Ga content resulted in all framework sites being occupied by metal + phosphorus in the archetype cubic Pm n clathrate-I crystal structure of Ba 8 Cu 14.5(3) Ga 1.3 P 30.2(4) with 8.2% Ga/M total . A combination of energy dispersive x-ray spectroscopy, inductively coupled plasma mass spectroscopy, and single crystal x-ray diffraction was used to determine the structures alongside the compositions. The positional disorder was verified by 31 P solid state NMR spectroscopy. Characterization of the transport properties indicated that the Ga-substituted samples exhibit higher Seebeck coefficients and electrical resistivities compared to its pristine counterpart, in line with the expected reduction of the hole concentration due to Ga/Cu substitution. Moderate improvements in the thermoelectric power factor and overall figure-of-merit were observed for samples with 6.9% and 3.8% Ga/M total as compared to those for the pristine Ba 8 Cu 16 P 30 clathrate. Finally, band structure calculations shed light on how Ga substitution affects the electronic structure and thermoelectric properties of studied clathrates.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Overview of the SCEC/USGS Community Stress Drop Validation Study Using the 2019 Ridgecrest Earthquake Sequence
We present initial findings from the ongoing Community Stress Drop Validation Study to compare spectral stress-drop estimates for earthquakes in the 2019 Ridgecrest, California, sequence. This study uses a unified dataset to independently estimate earthquake source parameters through various methods. Stress drop, which denotes the change in average shear stress along a fault during earthquake rupture, is a critical parameter in earthquake science, impacting ground motion, rupture simulation, and source physics. Spectral stress drop is commonly derived by fitting the amplitude-spectrum shape, but estimates can vary substantially across studies for individual earthquakes. Sponsored jointly by the U.S. Geological Survey and the Statewide (previously, Southern) California Earthquake Center our community study aims to elucidate sources of variability and uncertainty in earthquake spectral stress-drop estimates through quantitative comparison of submitted results from independent analyses. The dataset includes nearly 13,000 earthquakes ranging from M 1 to 7 during a two-week period of the 2019 Ridgecrest sequence, recorded within a 1° radius. Here, in this article, we report on 56 unique submissions received from 20 different groups, detailing spectral corner frequencies (or source durations), moment magnitudes, and estimated spectral stress drops. Methods employed encompass spectral ratio analysis, spectral decomposition and inversion, finite-fault modeling, ground-motion-based approaches, and combined methods. Initial analysis reveals significant scatter across submitted spectral stress drops spanning over six orders of magnitude. However, we can identify between-method trends and offsets within the data to mitigate this variability. Averaging submissions for a prioritized subset of 56 events shows reduced variability of spectral stress drop, indicating overall consistency in recovered spectral stress-drop values.
58 GEOSCIENCES↗
Differential Seismic Phase Detection Probability as a Potential Discriminant of Explosions and Earthquakes
Deep learning models trained to estimate the probability of seismic P and S phases are rapidly expanding the scale of local event detections. Here, we evaluate the potential for deep learning model output phase detection probabilities to contribute to event‐type classification, particularly discrimination of single‐fired borehole explosions and earthquakes at local distances (<300 km). Motivated by the empirical success of P/S amplitude ratios, we consider the difference between P and S pick probability output from previously developed phase detection models, P prob −S prob , as a discriminant. Test data include M L ∼1–4 earthquakes and explosions observed by common seismographs in ten geologically diverse localities. Depending on the picking model and training data, binary classification using P prob −S prob with at least three stations can achieve approximately equivalent classification accuracy as P/S amplitude ratios without requiring any customization. Joint classification with P/S and P prob −S prob improves accuracy for most quality control scenarios. Pick probabilities are an efficient attribute to consider in explosion discrimination because they can be automated byproducts of event detection. They avoid the binary choice of picking or not picking weakly visible S waves common to explosions.
Duan, Chenglong [Rice Univ., Houston, TX (United S↗
Chloride and Hydride Transfer as Keys to Catalytic Upcycling of Polyethylene into Liquid Alkanes
Abstract Transforming polyolefin waste into liquid alkanes through tandem cracking‐alkylation reactions catalyzed by Lewis‐acid chlorides offers an efficient route for single‐step plastic upcycling. Lewis acids in dichloromethane establish a polar environment that stabilizes carbenium ion intermediates and catalyzes hydride transfer, enabling breaking of polyethylene C−C bonds and forming C−C bonds in alkylation. Here, we show that efficient and selective deconstruction of low‐density polyethylene (LDPE) to liquid alkanes is achieved with anhydrous aluminum chloride (AlCl 3 ) and gallium chloride (GaCl 3 ). Already at 60 °C, complete LDPE conversion was achieved, while maintaining the selectivity for gasoline‐range liquid alkanes over 70 %. AlCl 3 showed an exceptional conversion rate of 5000 , surpassing other Lewis acid catalysts by two orders of magnitude. Through kinetic and mechanistic studies, we show that the rates of LDPE conversion do not correlate directly with the intrinsic strength of the Lewis acids or steric constraints that may limit the polymer to access the Lewis acid sites. Instead, the rates for the tandem processes of cracking and alkylation are primarily governed by the rates of initiation of carbenium ions and the subsequent intermolecular hydride transfer. Both jointly control the relative rates of cracking and alkylation, thereby determining the overall conversion and selectivity.
Zhang, Wei↗
Chloride and Hydride Transfer as Keys to Catalytic Upcycling of Polyethylene into Liquid Alkanes
Abstract Transforming polyolefin waste into liquid alkanes through tandem cracking‐alkylation reactions catalyzed by Lewis‐acid chlorides offers an efficient route for single‐step plastic upcycling. Lewis acids in dichloromethane establish a polar environment that stabilizes carbenium ion intermediates and catalyzes hydride transfer, enabling breaking of polyethylene C−C bonds and forming C−C bonds in alkylation. Here, we show that efficient and selective deconstruction of low‐density polyethylene (LDPE) to liquid alkanes is achieved with anhydrous aluminum chloride (AlCl 3 ) and gallium chloride (GaCl 3 ). Already at 60 °C, complete LDPE conversion was achieved, while maintaining the selectivity for gasoline‐range liquid alkanes over 70 %. AlCl 3 showed an exceptional conversion rate of 5000 , surpassing other Lewis acid catalysts by two orders of magnitude. Through kinetic and mechanistic studies, we show that the rates of LDPE conversion do not correlate directly with the intrinsic strength of the Lewis acids or steric constraints that may limit the polymer to access the Lewis acid sites. Instead, the rates for the tandem processes of cracking and alkylation are primarily governed by the rates of initiation of carbenium ions and the subsequent intermolecular hydride transfer. Both jointly control the relative rates of cracking and alkylation, thereby determining the overall conversion and selectivity.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Omics-driven onboarding of the carotenoid producing red yeast Xanthophyllomyces dendrorhous CBS 6938
Transcriptomics is a powerful approach for functional genomics and systems biology, yet it can also be used for genetic part discovery. Here, we derive constitutive and light-regulated promoters directly from transcriptomics data of the basidiomycete red yeast Xanthophyllomyces dendrorhous CBS 6938 (anamorph Phaffia rhodozyma) and use these promoters with other genetic elements to create a modular synthetic biology parts collection for this organism. X. dendrorhous is currently the sole biotechnologically relevant yeast in the Tremellomycete class-it produces large amounts of astaxanthin, especially under oxidative stress and exposure to light. Thus, we performed transcriptomics on X. dendrorhous under different wavelengths of light (red, green, blue, and ultraviolet) and oxidative stress. Differential gene expression analysis (DGE) revealed that terpenoid biosynthesis was primarily upregulated by light through crtI, while oxidative stress upregulated several genes in the pathway. Further gene ontology (GO) analysis revealed a complex survival response to ultraviolet (UV) where X. dendrorhous upregulates aromatic amino acid and tetraterpenoid biosynthesis and downregulates central carbon metabolism and respiration. The DGE data was also used to identify 26 constitutive and regulated genes, and then, putative promoters for each of the 26 genes were derived from the genome. Simultaneously, a modular cloning system for X. dendrorhous was developed, including integration sites, terminators, selection markers, and reporters. Each of the 26 putative promoters were integrated into the genome and characterized by luciferase assay in the dark and under UV light. The putative constitutive promoters were constitutive in the synthetic genetic context, but so were many of the putative regulated promoters. Notably, one putative promoter, derived from a hypothetical gene, showed ninefold activation upon UV exposure. Thus, this study reveals metabolic pathway regulation and develops a genetic parts collection for X. dendrorhous from transcriptomic data. Therefore, this study demonstrates that combining systems biology and synthetic biology into an omics-to-parts workflow can simultaneously provide useful biological insight and genetic tools for nonconventional microbes, particularly those without a related model organism. This approach can enhance current efforts to engineer diverse microbes.
60 APPLIED LIFE SCIENCES↗
Cosmological constraints from H ii starburst galaxy, quasar angular size, and other measurements
ABSTRACT We compare the constraints from two (2019 and 2021) compilations of H ii starburst galaxy (H iiG) data and test the model independence of quasar (QSO) angular size data using six spatially flat and non-flat cosmological models. We find that the new 2021 compilation of H iiG data generally provides tighter constraints and prefers lower values of cosmological parameters than those from the 2019 H iiG data. QSO data by themselves give relatively model-independent constraints on the characteristic linear size, lm, of the QSOs within the sample. We also use Hubble parameter [H(z)], baryon acoustic oscillation (BAO), Pantheon Type Ia supernova (SN Ia) apparent magnitude (SN-Pantheon), and DES-3 yr binned SN Ia apparent magnitude (SN-DES) measurements to perform joint analyses with H iiG and QSO angular size data, since their constraints are not mutually inconsistent within the six cosmological models we study. A joint analysis of H(z), BAO, SN-Pantheon, SN-DES, QSO, and the newest compilation of H iiG data provides almost model-independent summary estimates of the Hubble constant, $H_0=69.7\pm 1.2\ \rm {km\,s^{-1}\,Mpc^{-1}}$, the non-relativistic matter density parameter, $\Omega _{\rm m_0}=0.293\pm 0.021$, and lm = 10.93 ± 0.25 pc.
79 ASTRONOMY AND ASTROPHYSICS↗
Mapping the soil microbiome functions shaping wetland methane emissions
Accounting for only 8% of Earth’s land cover, freshwater wetlands remain the foremost contributors to global methane emissions. Yet the microorganisms and processes underlying methane emissions from wetland soils remain poorly understood. Over a five-year period, we surveyed the microbial membership and in situ methane measurements from over 700 samples in one of the most prolific methane-emitting wetlands in the United States. We constructed a catalog of 2,502 metagenome-assembled genomes (MAGs), with more than half of the 70 bacterial and archaeal phyla sampled containing novel lineages. Integration of these data with 133 soil metatranscriptomes provided a genome-resolved view of the biogeochemical specialization and versatility expressed over wetland soil spatial and temporal gradients. Centimeter-scale depth differences best explained patterns of microbial community structure and transcribed functionalities, even more than land cover or temporal information. Moreover, while extended flooding restructured soil redox, this perturbation failed to reconfigure the transcriptional profiles of methane-cycling microorganisms, contrasting with theoretically expected responses to hydrological perturbations. Co-expression analyses, coupled with depth-resolved methane measurements, revealed the metabolisms and trophic structures most predictive of methane hotspots. Mapping the spatiotemporal transcriptional patterns on this compendium of biogeochemically classified soil-derived genomes begins to untangle the microbial carbon, energy, and nutrient processing contributing to wetland methane production.
MAG↗
Roadmap on advanced and / real-time characterisation of solid state materials and devices for energy applications
A strong societal and political drive is motivating the development and optimization of novel energy conversion and storage systems for decarbonization. The successful implementation of solid state devices such as fuel cells and secondary batteries depends, however, on achieving ambitious targets in terms of performance, reliability and cost competitiveness. Research and technology are addressing these needs through a holistic approach including exploration of new materials and nanoarchitectures, as well as system engineering. These significant efforts require the support of appropriate characterization tools capable of assessing nanometer-scale phenomena such as concentration profiles of ionic and electronic charges, local chemical compositions and their evolution over time across interfaces. This roadmap provides an overview of selected advanced characterization techniques for energy materials and devices. Specific focus is put on in situ/operando methods for probing electrochemical phenomena in real-time under realistic working conditions. Experts in the field provide an extensive review of the current state of the art in 2025 and the current and future challenges for the characterization of local chemistry and kinetics in the bulk of the material, in nanoarchitectures (e.g. thin films) and at the interfaces (e.g. grain boundaries, phase contacts, solid/liquid and solid/gas interfaces) . The aim is to provide a detailed guide to the techniques, describing opportunities and bottlenecks for their practical deployment and examples of successful applications.
25 ENERGY STORAGE↗
Dependence of Cosmological Constraints on Gray Photometric Zero-point Uncertainties of Supernova Surveys
Abstract Type Ia supernova (SN) measurements of the Hubble constant, H 0 ; cosmic mass density, Ω M ; and dark energy equation-of-state parameter, w , rely on heterogeneous SN surveys across three decades of observation. These distinct surveys may have undiagnosed, relative photometric zero-point errors. We determine the sensitivities of the SH0ES+Pantheon+ cosmological constraints to unknown gray systematics in the photometric zero-point calibration between the 19 surveys that comprise the Pantheon+ SN compendium. Varying the surveys’ gray zero-points simultaneously with cosmological parameters, we determine that the SH0ES+Pantheon+ measurement of H 0 is robust against gray intersurvey photometric miscalibration. Specifically, uncalibrated intersurvey systematics could represent a source of uncertainty no larger than 0.39 km s −1 Mpc −1 for H 0 . This modest increase in H 0 uncertainty could not account for the 7 km s −1 Mpc −1 “Hubble tension” between the SH0ES measurement of H 0 and the Planck ΛCDM-based inference of H 0 . However, the SH0ES+Pantheon+ best-fit values of Ω M and w are not robust against gray zero-point error, slipping by up to 0.16 and −0.63. Because measurements of Ω M and w depend on intrasurvey cross-band calibration, the hypothetical gray miscalibration underestimates the sensitivity of these measurements to zero-point miscalibration. Because the Pantheon+ compendium contains many surveys that share low- z Hubble flow (HF) and Cepheid-paired SNe, intersurvey photometric calibration errors do not significantly impede the joint use of SH0ES and Pantheon+ to measure H 0 to 1% accuracy. However, H 0 constraints that rely on one HF survey but numerous galactic distance calibration surveys are susceptible to intersurvey photometric miscalibration.
79 ASTRONOMY AND ASTROPHYSICS↗
TESS Hunt for Young and Maturing Exoplanets (THYME). V. A Sub-Neptune Transiting a Young Star in a Newly Discovered 250 Myr Association
The detection and characterization of young planetary systems offer a direct path to study the processes that shape planet evolution. We report on the discovery of a sub-Neptune-sized planet orbiting the young star HD 110082 (TOI-1098). Transit events we initially detected during TESS Cycle 1 are validated with time-series photometry from Spitzer. High-contrast imaging and high-resolution, optical spectra are also obtained to characterize the stellar host and confirm the planetary nature of the transits. The host star is a late-F dwarf (M {sub ⋆} = 1.2M {sub ⊙}) with a low-mass, M dwarf binary companion (M {sub ⋆} = 0.26M {sub ⊙}) separated by nearly one arcminute (∼6200 au). Based on its rapid rotation and Lithium absorption, HD 110082 is young, but is not a member of any known group of young stars (despite proximity to the Octans association). To measure the age of the system, we search for coeval, phase-space neighbors and compile a sample of candidate siblings to compare with the empirical sequences of young clusters and to apply quantitative age-dating techniques. In doing so, we find that HD 110082 resides in a new young stellar association we designate MELANGE-1, with an age of 250{sub −70}{sup +50} Myr. Jointly modeling the TESS and Spitzer light curves, we measure a planetary orbital period of 10.1827 days and radius of R {sub p} = 3.2 ± 0.1R {sub ⊕}. HD 110082 b’s radius falls in the largest 12% of field-age systems with similar host-star mass and orbital period. This finding supports previous studies indicating that young planets have larger radii than their field-age counterparts.
47 OTHER INSTRUMENTATION↗
The Langmuir probe system in the Wendelstein 7-X test divertor
Here, the design and evaluation of the Langmuir probe system used in the first divertor operation phase of Wendelstein 7-X is described. The probes are integrated into the target plates and have individually facetted surfaces to keep the angle of incidence of the magnetic field within an appropriate range for different magnetic configurations. Multiple models for the derivation of plasma parameters from current–voltage characteristics are introduced. These are analyzed with regard to their assumptions and limitations, generalized, and adapted to our use case. A detailed comparison is made to determine the most suitable model. It is found that the choice of model has a large impact, for example, resulting in a change in the inferred temperatures of up to a factor two. This evaluation is implemented in a Bayesian modeling framework and automated to allow for joint analysis with other diagnostics and a replacement of ad hoc assumptions. We rigorously treat parameter uncertainties, revealing strong correlations between them. General and flexible model formulations permit an expansion to additional effects.
47 OTHER INSTRUMENTATION↗
Contrasting carbon dynamics in grazed and flood-prone grasslands on mineral and degraded peat soils
Ecosystem-scale methane (CH₄) flux measurements from grazed grasslands remain scarce, despite their importance for understanding grassland contributions to the global carbon budget. In this study, we present full annual budgets of both carbon dioxide (CO₂) and CH₄ derived from eddy covariance measurements at two contrasting grazed grasslands: a floodplain grassland at Marchegg, Austria, and an intensively grazed pasture at Sherman Barn, California. By combining continuous, year-round observations of CO₂ and CH₄, this study provides a rare, comparative assessment of greenhouse gas dynamics across distinct climatic, hydrological, and management regimes. Our results highlight how environmental conditions, grazing intensity, and hydrology jointly regulate CO₂ exchange and CH₄ emissions, underscoring the importance of including methane alongside net ecosystem exchange when evaluating grassland carbon balances. At Marchegg, characterized by seasonal flooding and moderate horse grazing on mineral soils, the ecosystem acted as a weak carbon sink in 2024, with a GWP 100 of 42.2 ± 113.4 g CO₂ eq m⁻². Net CO₂ uptake (–27.3 ± 30.2 g C m⁻² yr⁻¹) was partly offset by CH₄ emissions (1.6 ± 0.04 g C m⁻² yr⁻¹), which were strongly linked to soil moisture and inundation events. In contrast, Sherman Barn, a cattle pasture on degraded peat soils, was a consistent carbon source in 2019, with a GWP 100 of 567.6 ± 120.5 g CO₂ eq m⁻², associated with high ecosystem respiration during summer. The site released 125.3 ± 32.2 g C m⁻² yr⁻¹ of CO₂ and 3 ± 0.06 g C m⁻² yr⁻¹ of CH₄. Across both sites, net ecosystem exchange was primarily linked to photosynthetically active radiation and vegetation greenness, while CH₄ fluxes were related to soil moisture rather than grazing intensity. Flooding at Marchegg reduced CO₂ uptake but enhanced CH₄ emissions, highlighting the critical role of flood timing within the growing season. Moreover, inundation appeared to suppress the spread of invasive plant species, emphasizing the ecological value of dynamic hydrological regimes. Together, these findings reveal the complexity of grassland carbon budgets and the need for site-specific, year-round CO₂ and CH₄ monitoring to inform climate-adaptive management strategies.
Carbon sequestration↗
Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)
We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO2 EOR projects utilizing the water-alternating-gas (WAG) process. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.
02 PETROLEUM↗
Actuators
A shear force actuator is described, including: two substantially parallel first structural components disposed along a first axis; a plurality of substantially parallel second structural components disposed between and bridging the two first structural components; a plurality of joint sections each joining the second structural component with the first structural components at an oblique angle of between 0 and 90 degrees to define a plurality of cells, each capable of being connected with a fluid inflation or deflation source; an elastic surface covering the remaining surfaces of the cells in a fluid-tight manner, wherein at least one of the joint section, the first structural components, and the second structural components is elastic so that cell collapses upon removal of fluid from the cell to generate a linear force along the first axis.
Yang, Dian↗
Dark Energy Survey Year 1 Results: Cosmological constraints from cluster abundances and weak lensing
In this work we perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset. Our analysis uses the same shear and source photometric redshifts estimates as were used in the DES combined probes analysis. Our analysis results in surprisingly low values for $S_8 =\sigma_8(\Omega_{\rm m}/0.3)^{0.5}= 0.65\pm 0.04$, driven by a low matter density parameter, $\Omega_{\rm m}=0.179^{+0.031}_{-0.038}$, with $\sigma_8-\Omega_{\rm m}$ posteriors in $2.4\sigma$ tension with the DES Y1 3x2pt results, and in $5.6\sigma$ with the Planck CMB analysis. These results include the impact of post-unblinding changes to the analysis, which did not improve the level of consistency with other data sets compared to the results obtained at the unblinding. The fact that multiple cosmological probes (supernovae, baryon acoustic oscillations, cosmic shear, galaxy clustering and CMB anisotropies), and other galaxy cluster analyses all favor significantly higher matter densities suggests the presence of systematic errors in the data or an incomplete modeling of the relevant physics. Cross checks with X-ray and microwave data, as well as independent constraints on the observable--mass relation from SZ selected clusters, suggest that the discrepancy resides in our modeling of the weak lensing signal rather than the cluster abundance. Repeating our analysis using a higher richness threshold ($\lambda \ge 30$) significantly reduces the tension with other probes, and points to one or more richness-dependent effects not captured by our model.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗