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DOE OSTI2020

Understanding asymmetries using integrated simulations of capsule implosions in low gas-fill hohlraums at the National Ignition Facility

Current capsule implosions at the National Ignition Facility (NIF) using high-density-carbon ablators and laser energies close to 2 MJ have shown neutron yields in excess of 50 kJ. Improving on this performance requires understanding of the different degradation mechanisms. For many NIF implosions, nuclear diagnostic signatures have inferred residual hot-spot velocities that correlate with fuel areal density variations consistent with a low-order mode-1 asymmetry. A current working hypothesis attributes these asymmetries to a combination of beam to beam variations in the laser delivery and possibly coupling to target features, such as the diagnostic holes needed for x-ray imaging. Recently, a new source has been identified, thickness variation in the ablator shell. To gain better understanding and eventually mitigate the causes of <ρR> asymmetries, 3D integrated simulations using the actual delivered laser powers are needed. To capture the effect of the diagnostic holes (DHs) using direct numerical simulation would require significantly large computational resources. Instead, our 3D simulations make use of a subgrid model developed using highly-resolved 2D simulations that include several details of the DH engineering complexity. Simulations of NIF shots using hohlraums without DHs, to isolate the effect of beam-to-beam variations, reproduce fairly well the observed nuclear diagnostic signatures. Similarly, reasonable agreement between data and simulations is also obtained in the presence of diagnostic holes. To account for the remaining discrepancies a sensitivity study of ablator thickness variation showed that 1% thickness asymmetries are comparable in effect to 1% peak drive mode-1 asymmetries. Furthermore, this study identified sensitivity to variations in the imbedded doped layer (needed to shield the DT ice from the high energy x-rays generated in the hohlraum) thickness even when the inner and outer surface of the ablator are perfectly spherical.

radiation hydrodynamics↗

DOE OSTI2024

Luminosity and beam-induced background studies for the Cool Copper Collider

A high-energy electron-positron collider has been widely recognized by the particle physics community to be the next crucial step for detailed studies of the Higgs boson and other fundamental particles and processes. Several proposals for such colliders, either linear or circular, are currently under evaluation. Any such collider will be required to reach high lumimosities, in order to collect enough data at a reasonable time scale, while at the same time coping with high rates of background particles produced from beam-beam interactions during the collisions. In this paper, we analyze the luminosity and beam-beam interaction characteristics of the Cool Copper Collider ( C 3 ) and perform a comparison with other linear collider proposals. We conclude that C 3 can reach the same or higher collision rates as the other proposals, without having to cope with higher beam-induced background fluxes. Thus, C 3 emerges as an attractive option for a future electron-positron collider, benefiting from the collective advancements in beam delivery and final focus system technologies developed by other linear collider initiatives. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Effective shell-model interaction for nuclei “southeast” of 100 Sn

We construct an effective shell-model interaction for the valence space spanned by single-particle neutron and single-hole proton states in 100 Sn. Starting from chiral nucleon-nucleon and three-nucleon forces and single-reference coupled-cluster theory for 100 Sn we apply a second similarity transformation that decouples the valence space. The particle-particle components of the resulting effective interaction can be used in shell model calculations for neutron deficient tin isotopes. The hole-hole interaction can be used to calculate the N=50 isotones south of 100 Sn, and the full particle-hole interaction describes nuclei in the region southeast of 100 Sn. We compute low-lying excited states in selected nuclei southeast of 100 Sn, and find reasonable agreement with data. The presented techniques can also be applied to construct effective shell-model interactions for other regions of the nuclear chart.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Automated prediction of lattice parameters from X-ray powder diffraction patterns

A key step in the analysis of powder X-ray diffraction (PXRD) data is the accurate determination of unit-cell lattice parameters. This step often requires significant human intervention and is a bottleneck that hinders efforts towards automated analysis. This work develops a series of one-dimensional convolutional neural networks (1D-CNNs) trained to provide lattice parameter estimates for each crystal system. A mean absolute percentage error of approximately 10% is achieved for each crystal system, which corresponds to a 100- to 1000-fold reduction in lattice parameter search space volume. The models learn from nearly one million crystal structures contained within the Inorganic Crystal Structure Database and the Cambridge Structural Database and, due to the nature of these two complimentary databases, the models generalize well across chemistries. A key component of this work is a systematic analysis of the effect of different realistic experimental non-idealities on model performance. It is found that the addition of impurity phases, baseline noise and peak broadening present the greatest challenges to learning, while zero-offset error and random intensity modulations have little effect. However, appropriate data modification schemes can be used to bolster model performance and yield reasonable predictions, even for data which simulate realistic experimental non-idealities. In order to obtain accurate results, a new approach is introduced which uses the initial machine learning estimates with existing iterative whole-pattern refinement schemes to tackle automated unit-cell solution.

42 ENGINEERING↗

DOE OSTI2021

Segmentation of Deposition Periods: An Opportunity to Improve PV Soiling Extraction

Soiling profiles are commonly assumed to have sawtooth shapes, made of alternating cleaning events and soiling deposition periods. The rates at which soiling deposit on the PV modules are considered to be constant for each period. In reality, events such as changes in climatic conditions can lead to a sudden variation in soiling deposition rate. These changes cannot be reproduced if cleanings are the only events modelled to extract soiling profiles directly from PV performance data. For this reason, in this work, the use of change points and segmented regression is proposed to improve the extraction of soiling profiles through the model of up to two deposition rates per period in between cleanings. The results show that the quality of soiling extraction can be enhanced compared to a cleanings-only identification approach if both cleanings and change points are considered.

monitoring↗

DOE OSTI2020

Analytical Investigation of the Role of Lateral Mixing in the Evolution of Nonprecipitating Cumulus. Part I: Developing Clouds

Evolution of nonprecipitating cumulus clouds (Cu) at the developing stage under the influence of lateral entrainment and mixing is studied analytically using a minimalistic analytical model. We present a model of an ascending cloud volume (a model of developing Cu) whose structure is determined by the processes of droplet diffusion growth/evaporation and entrainment mixing in the horizontal direction. Spatial and time changes of liquid water content, the adiabatic fraction, droplet concentration, and the mean volume droplet radius are calculated. It is shown that the existence of a nondiluted core in a growing cumulus cloud significantly depends on the cloud width and vertical velocity. While at the updraft velocity of 2 m s −1 the core of a 400-m-wide cloud becomes diluted at distances of a few hundred meters above cloud base, the core of a cloud of 1000-m width remains nondiluted at distances up to 1500 m above cloud base. The explanation of this result is simple: the increase in cloud width and the decrease in the updraft velocity increase the time during which the cloud is diluted due to mixing. Since lateral mixing synchronously decreases both the cloud water content and droplet concentration, the variation of the mean volume droplet radius is low inside the cloud. The approximate quantitative condition for cloud formation in updraft is derived. It is shown that a cloud can arise when its vertical velocity exceeds a critical value. To produce clouds, narrow turbulent plumes should ascend at higher velocity as compared to wider plumes. High humidity of the environment air is favorable for formation of clouds from plumes. The comparison of the obtained results with previously published observational data indicates a reasonable agreement. The results can be useful for parameterization purposes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment

Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.

16 TIDAL AND WAVE POWER↗

DOE OSTI2020

Fibre-optic based DAS technology for Long-term Seismic Monitoring of Carbon Capture and Storage Projects

Long-term seismic monitoring of carbon capture and storage projects (CCS) is needed to verify that the injected gas is safely stored in the subsurface until permanence can be assured. Conventional surface seismic monitoring techniques are usually expensive, require highly invasive surface operations, and need significant time investments on the part of personnel for both the field effort and processing the acquired data. For these reasons, permanent reservoir monitoring (PRM) technologies are preferred, as they can offer a cost-effective solution for long-term monitoring. In this context, we have developed and trialed the use of distributed acoustic sensing (DAS) coupled to permanent rotary sources, called surface orbital vibrators (SOV), with the objective to build a continuous monitoring array for CCS projects.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Connecting Minds: AI Use Cases to Bridge Power Systems and Large Language Models for Practical Applications

Recent advances in artificial intelligence (AI) and development of large language models (LLMs) present the opportunity to develop a new generation of power systems applications. In contrast with early power system AI applications based on structured numerical data, LLMs offer unique capabilities to perform logical reasoning using text documents, unstructured data, and application programming interface (API) calls to computational software. This paper seeks to bridge the knowledge gap between power systems engineers and LLM developers through a crosscutting explanation of use cases, characteristics, requirements, practical considerations from the perspectives of both LLM capabilities and industry needs. Specific focus is given to applications that can be realistically deployed by electric utilities. After introducing the architecture of LLMs and unique challenges of the power systems domain, this paper proposes twenty representative LLM applications grouped into categories of 1) power system operations, 2) asset management, 3) system planning and analytics, and 4) energy management and protection systems. Five use cases are presented within each category with descriptions of the motivation, objectives, approaches, example inputs / outputs, and benefits of each use case.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Release of Evaluated 235 U(n,f) Average Prompt Fission Neutron Multiplicities Including the CGMF Model

This report documents an evaluation of the average prompt fission neutron multiplicity, $\overline{v}_p$, of 235 U from 200 keV to 15 MeV that is a potential release candidate for the upcoming U.S. nuclear data library, ENDF/B-VIII.1. This evaluation had to be re-done from "scratch", as the input to the $\overline{v}_p$ evaluation of the previous library, ENDF/B-VIII.0, was lost. That means that all available experimental data were re-analyzed and uncertainties were re-estimated. Another major difference to ENDF/B-VIII.0 is that this evaluation includes model information from the Hauser-Feshbach fission fragment decay code CGMF, while ENDF/B-VIII.0 is based purely on experimental data. CGMF links several fission quantities with each other; $\overline{v}_p$ is predicted by assumptions made on, e.g., pre-neutron emission yields as a function of mass, the total kinetic energy, or spin and parity of fission fragments. This allows to perform two types of validation for the new 235 U $\overline{v}_p$: On the one hand, one can employ evaluated CGMF parameters obtained from fitting to experimental 235 U $\overline{v}_p$ to predict yields as a function of mass, the average total kinetic energy, or the mean energy of the prompt fission neutron spectrum. These model-predicted values can then be compared to experimental and evaluated data. The model-predicted fission-observable values using evaluated parameters obtained here are reasonably close to experimental data indicating the evaluated 235 U(n,f) $\overline{v}_p$ are physical. On the other hand, one can validate 235 U $\overline{v}_p$ with respect to integral responses such as fast ICSBEP critical assemblies or LLNL pulsed spheres. LLNL pulsed-sphere neutron-leakage spectra are minimally impacted by the new 235 U $\overline{v}_p$ as these experimental data are shape data and the $\overline{v}_p$ would mostly lead to a change in normalization of the data as the spheres are relatively thin (0.7 and 1.5 mean-free path) and, thus, mostly depend on 235 U $\overline{v}_p$ from 12-15 MeV. The change in the predicted effective neutron multiplication factor, k eff , of selected ICSBEP critical assemblies, however, is large compared to values using ENDF/B-VIII.0 and experimental k eff : The average bias is 108 pcm across all studied k eff values versus 12 pcm for ENDF/B-VIII.0. A reasonable performance in simulating keff (mean bias of 14 pcm) can be retained by tweaking 235 U $\overline{v}_p$ from 3-5 MeV, and combining it with a recent 235 U PFNS evaluation that is also a ENDF/B-VIII.1 release candidate.

235U↗

DOE OSTI2022

Evaluated 238 U(n,f) Average Prompt Fission Neutron Multiplicities Including the CGMF Model

This report documents an evaluation of the average prompt fission neutron multiplicity, $\overline{v}_p$, of 238 U from 800 keV to MeV. This evaluation had to be re-done from “scratch” as the input to previous $\overline{v}_p$ evaluations, specifically ENDF/B-VIII.0, was not found. That means that all available experimental data were re-analyzed and uncertainties were re-estimated. The new evaluated 238 U $\overline{v}_p$ based on only experimental data differs distinctly from ENDF/B-VIII.0 $\overline{v}_p$ from 2 to 4.5 MeV, and from 6 to 7 MeV, and is otherwise similar. The difference from 2 to 4.5 MeV stems from the fact that ENDF/B-VIII.0 was tweaked in this energy range to data of Frehaut, while two other, equally trustworthy, data sets would indicate an evaluated 238 U $\overline{v}_p$ that is up to 2% higher. Also, second chance fission in ENDF/B-VIII.0 was smoothed over from 6–7 MeV. Another major difference to ENDF/B-VIII.0 is that one of the evaluations presented here includes model information from the Hauser-Feshbach fission fragment decay code CGMF, while ENDF/B-VIII.0 is based purely on experimental data. CGMF links several fission quantities with each other; $\overline{v}_p$ is predicted by assumptions made on, e.g., pre-neutron emission yields as a function of mass, the total kinetic energy, or spin and parity of fission fragments. This allows to validate the new 238 U $\overline{v}_p$ by using CGMF parameters obtained from fitting to experimental 238 U $\overline{v}_p$ to predict yields as a function of mass, the average total kinetic energy, or the mean energy of the prompt fission neutron spectrum. These model-predicted values can then be compared to experimental and evaluated data. The model-predicted fission-observable values using evaluated parameters obtained here are reasonably close to experimental data for some observables, but are farther away from experimental data related to TKE observables. In addition to that, the evaluated 238 U(n,f) $\overline{v}_p$ shows similar deviations from ENDF/B-VIII.0 as for the evaluation with only experimental data. This difference is expected to lead to changes in simulated effective neutron multiplication factor, $k_{eff}$ of ICSBEP critical assemblies that are sensitive to 238 U in the fast range (BigTen, Flattop, Flattop-Pu). These changes in $k_{eff}$ need to be counter-balanced. Chi-Nu PFNS experimental data are expected to be released in the next few months that might lead to the needed changes in the PFNS. Until then, we hold off in benchmarking the new 238 U(n,f) $\overline{v}_p$ as well as submitting it to ENDF/B-VIII.1. Also, new high-precision 238 U $\overline{v}_p$ are expected to be measured by the CEA in the next two years that will shed further light on question on 238 U $\overline{v}_p$ from 2–4.5 and 6–7 MeV.

238U↗

DOE OSTI2024

Characterizing Hydraulic Fracture Propagation Before Fracture Hits

Estimating the distance from hydraulic fracture tip to monitor well can be very useful for fracture characterization, well spacing optimization, and preventing parent-child well interference. Heart-shape signal is referred to as the extensional precursor of fracture hit recorded by cross-well strain measurements and can be served as a vital tool to make such estimation. This study incorporates the 3D Displacement Discontinuity Method to understand the impact of fracture geometry and monitor well offset on the heart-shape signal’s characteristics. Results from numerical simulation and analytical solutions reveal a strong linear correlation between the spatial extent of heart shape signal and fracture tip distance. This relationship was further developed to predict tip distance using field data from the Hydraulic Fracture Test Site 2. A reasonable approximation result from field data further validates the methodology. In addition, it is worth noting that the estimation accuracy depends on the ratio between fracture dimension and tip distance. The findings of this study offer a novel approach for real-time monitoring and characterizing hydraulic fracture propagation, which can be further used for well spacing optimization in unconventional and Enhanced Geothermal System reservoir development, as well as cap rock integrity monitoring for carbon sequestration projects.

Jin, Ge↗

DOE OSTI2021

Evaluating fine-resolution, regional outputs of a variable resolution global climate model

Climate models have been used to study water resources and regional hydrologic responses to climate change, but climate model outputs must be downscaled to provide relevant regional data. However, the accuracy of this regional data is limited by uncertainties across and within downscaling methods, uncertainty across global outputs, and discontinuities at downscaled boundaries. A new alternative to traditional downscaling is a variable resolution model that incorporates fine-resolution regions directly into a coarse-resolution, global climate simulation in order to capture contiguous dynamics across resolution boundaries. In this study, we used the Variable-Resolution Community Earth System Model (VR-CESM) to generate one-eighth degree (14 km) fine-resolution outputs for the western U.S. and eastern China from 1970-2006. We focus our evaluation on precipitaiton, temperature, snow pack, solar radiation, and wind. We compare the model outputs with remote-sensing-based precipitation data, and both reanalysis and gridded weather station data for precipitation and temperature. VR-CESM generally has a cold bias in winter and a warm bias in summer in the western U.S., which compensate each other to reduce the annual bias. In eastern China, however, the sign of temperature biases are more consistent throughout the year with cold biases in the higher mountains and warm biases throughout most of the rest of the region. Precipitation biases are dependent upon reference data, and show slight overestimation in high mountain regions in both the U.S. and China with respect to gridded weather station data. Simulated snow cover in the western U.S. is reasonable compared to remote sensing data, but snow cover and snow water equivalent have larger biases when compared to reanalysis data. In eastern China there are widespread snow cover biases compared to remote sensing data. VR-CESM underestimates downward shortwave radiation to a greater degree in summer than in winter, and underestimates surface layer windspeed over mountains to a greater degree than in other areas. Comparison between VR-CESM and a coarser simulation (1-degree Beijing Climate Center model) shows reduced precipitation biases in the mountainous regions with finer resolution, indicating the value of variable-resolution modeling for reigonal studies.

Di Vittorio, Alan↗

DOE OSTI2020

On the decaying-sterile-neutrino solution to the electron (anti)neutrino appearance anomalies

We explore the hypothesis that the unexplained data from LSND and MiniBooNE are evidence for a new, heavy neutrino mass-eigenstate that mixes with the muon-type neutrino and decays into an electron-type neutrino and a new, very light scalar particle. We consider two different decay scenarios, one with Majorana neutrinos, one with Dirac neutrinos; both fit the data equally well. We find a reasonable, albeit not excellent, fit to the data of MiniBooNE and LSND. The decaying-sterile-neutrino hypothesis, however, cleanly evades constraints from disappearance searches and precision measurements of leptonic meson decays, as long as $1~{\rm MeV}\gtrsim m_4\gtrsim 10$~keV. The SBN program at Fermilab should be able to definitively test the decaying-sterile-neutrino hypothesis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Correlating transcription and protein expression profiles of immune biomarkers following lipopolysaccharide exposure in lung epithelial cells

Universal and early recognition of pathogens occurs through recognition of evolutionarily conserved pathogen associated molecular patterns (PAMPs) by innate immune receptors and the consequent secretion of cytokines and chemokines. The intrinsic complexity of innate immune signaling and associated signal transduction challenges our ability to obtain physiologically relevant, reproducible and accurate data from experimental systems. One of the reasons for the discrepancy in observed data is the choice of measurement strategy. Immune signaling is regulated by the interplay between pathogen-derived molecules with host cells resulting in cellular expression changes. However, these cellular processes are often studied by the independent assessment of either the transcriptome or the proteome. Correlation between transcription and protein analysis is lacking in a variety of studies. In order to methodically evaluate the correlation between transcription and protein expression profiles associated with innate immune signaling, we measured cytokine and chemokine levels following exposure of human cells to the PAMP lipopolysaccharide (LPS) from the Gram-negative pathogen Pseudomonas aeruginosa . Expression of 84 messenger RNA (mRNA) transcripts and 69 proteins, including 35 overlapping targets, were measured in human lung epithelial cells. We evaluated 50 biological replicates to determine reproducibility of outcomes. Following pairwise normalization, 16 mRNA transcripts and 6 proteins were significantly upregulated following LPS exposure, while only five (CCL2, CSF3, CXCL5, CXCL8/IL8, and IL6) were upregulated in both transcriptomic and proteomic analysis. This lack of correlation between transcription and protein expression data may contribute to the discrepancy in the immune profiles reported in various studies. The use of multiomic assessments to achieve a systems-level understanding of immune signaling processes can result in the identification of host biomarker profiles for a variety of infectious diseases and facilitate countermeasure design and development.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials

Abstract Background To facilitate in silico studies that investigate digital mammography (DM) and breast tomosynthesis (DBT), models replicating the variety in imaging performance of the DM and DBT systems, observed across manufacturers are needed. Purpose The main purpose of this work is to develop generic physics models for direct and indirect detector technology used in commercially available systems, with the goal of making them available open source to manufacturers to further tweak and develop the exact in silico replicas of their systems. Methods We recently reported on an in silico version of the SIEMENS Mammomat Inspiration DM/DBT system using an open‐source GPU‐accelerated Monte Carlo x‐ray imaging simulation code (MC‐GPU). We build on the previous version of the MC‐GPU codes to mimic the imaging performances of two other Food and Drug Administration (FDA)‐approved DM/DBT systems, such as Hologic Selenia Dimensions (HSD) and the General Electric Senographe Pristina (GSP) systems. In this work, we developed a hybrid technique to model the optical spread and signal crosstalk observed in the GSP and HSD systems. MC simulations are used to track each x‐ray photon till its first interaction within the x‐ray detector. On the other hand, the signal spread in the x‐ray detectors is modeled using previously developed analytical equations. This approach allows us to preserve the modeling accuracy offered by MC methods in the patient body, while speeding up secondary carrier transport (either electron–hole pairs or optical photons) using analytical equations in the detector. The analytical optical spread model for the indirect detector includes the depth‐dependent spread and collection of optical photons and relies on a pre‐computed set of point response functions that describe the optical spread as a function of depth. To understand the capabilities of the computational x‐ray detector models, we compared image quality metrics like modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), simulated with our models against measured data. Please note that the purpose of these comparisons with measured data would be to gauge if the model developed as part of this work could replicate commercially used direct and indirect technology in general and not to achieve perfect fits with measured data. Results We found that the simulated image quality metrics such as MTF, NNPS, and DQE were in reasonable agreement with experimental data. To demonstrate the imaging performance of the three DM/DBT systems, we integrated the detector models with the VICTRE pipeline and simulated DM images of a fatty breast model containing a spiculated mass and a calcium oxalate cluster. In general, we found that the images generated using the indirect model appeared more blurred with a different noise texture and contrast as compared to the systems with direct detectors. Conclusions We have presented computational models of three commercially available FDA‐approved DM/DBT systems, which implement both direct and indirect detector technology. The updated versions of the MC‐GPU codes that can be used to replicate three systems are available in open source format through GitHub.

Sengupta, Aunnasha↗

DOE OSTI2024

Heart Shape to Fracture Distance: Characterizing Hydraulic Fracture Propagation before Hits

Estimating the distance from the hydraulic fracture tip to the monitor well can be useful for fracture characterization, well spacing optimization, and preventing parent-child well interference. A heart-shaped signal is referred to as the extensional precursor of a fracture hit recorded by crosswell strain measurements and can serve as a vital tool for such estimation. This study incorporates the 3D displacement discontinuity method (DDM) to understand the impact of fracture geometry and monitor well offset on the heart-shaped signal’s characteristics. Results from numerical simulation and analytical solutions reveal a strong linear correlation between the spatial extent of the heart-shaped signal and the fracture tip distance. This relationship was further developed to predict tip distance using field data from the Hydraulic Fracture Test Site 2 (HFTS2). A reasonable approximation result from field data further validates the methodology. In addition, it is worth noting that the estimation accuracy depends on the ratio between fracture dimension and tip distance. The findings of this study offer a novel approach for real-time monitoring and characterizing hydraulic fracture propagation, which can be further used for well spacing optimization in unconventional and enhanced geothermal system reservoir development, as well as caprock integrity monitoring for carbon sequestration projects.

58 GEOSCIENCES↗

DOE OSTI2024

Methods for Incorporating Model Uncertainty into Exoplanet Atmospheric Analysis

A key goal of exoplanet spectroscopy is to measure atmospheric properties, such as abundances of chemical species, in order to connect them to our understanding of atmospheric physics and planet formation. In this new era of high-quality JWST data, it is paramount that these measurement methods are robust. When comparing atmospheric models to observations, multiple candidate models may produce reasonable fits to the data. Typically, conclusions are reached by selecting the best-performing model according to some metric. This ignores model uncertainty in favor of specific model assumptions, potentially leading to measured atmospheric properties that are overconfident and/or incorrect. In this paper, we compare three ensemble methods for addressing model uncertainty by combining posterior distributions from multiple analyses: Bayesian model averaging, a variant of Bayesian model averaging using leave-one-out predictive densities, and stacking of predictive distributions. We demonstrate these methods by fitting the Hubble Space Telescope (HST) + Spitzer transmission spectrum of the hot Jupiter HD 209458b using models with different cloud and haze prescriptions. All of our ensemble methods lead to uncertainties on retrieved parameters that are larger but more realistic and consistent with physical and chemical expectations. Since they have not typically accounted for model uncertainty, uncertainties of retrieved parameters from HST spectra have likely been underreported. We recommend stacking as the most robust model combination method. Our methods can be used to combine results from independent retrieval codes and from different models within one code. They are also widely applicable to other exoplanet analysis processes, such as combining results from different data reductions.

79 ASTRONOMY AND ASTROPHYSICS↗