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At least 253 records · Page 14

CMIP5 Climate Models Overestimate Cooling by Volcanic Aerosols

We compare projections of the observed hemispherical mean surface temperature (HadCRUT4.6.0.0) and the ensemble mean of CMIP5 climate models' simulations on a set of standard regression model forcing variables. We find that the volcanic aerosol regression coefficients of the CMIP5 simulations are consistently significantly larger (by 40–49%) than the volcanic aerosol coefficients of the observed temperature. The probability that the observed differences are caused just by chance is much less than 0.01. The overestimate is due to the climate models' response to volcanic aerosol radiative forcing. The largest overestimate occurs in the winter season of each hemisphere. We hypothesize that the models' parameterization of aerosol-cloud interactions within ice and mixed phase clouds is a likely source of this discrepancy. Furthermore, the models significantly underestimate the effect of solar variability on temperature for both hemispheres.

54 ENVIRONMENTAL SCIENCES↗

BLENDING STUDY FOR SRR SALT DISPOSITION INTEGRATION: TANK 50H SCALE-MODELING AND COMPUTER-MODELING FOR BLENDING PUMP DESIGN, PHASE 2

The Salt Disposition Integration (SDI) portfolio of projects provides the infrastructure within existing Liquid Waste facilities to support the startup and long term operation of the Salt Waste Processing Facility (SWPF). Within SDI, the Blend and Feed Project will equip existing waste tanks in the Tank Farms to serve as Blend Tanks where 300,000-800,000 gallons of salt solution will be blended in 1.3 million gallon tanks and qualified for use as feedstock for SWPF. Blending requires the miscible salt solutions from potentially multiple source tanks per batch to be well mixed without disturbing settled sludge solids that may be present in a Blend Tank. Disturbing solids may be problematic both from a feed quality perspective as well as from a process safety perspective where hydrogen release from the sludge is a potential flammability concern. To develop the necessary technical basis for the design and operation of blending equipment, Savannah River National Laboratory (SRNL) completed scaled blending and transfer pump tests and computational fluid dynamics (CFD) modeling. A 94 inch diameter pilot-scale blending tank, including tank internals such as the blending pump, transfer pump, removable cooling coils, and center column, were used in this research. The test tank represents a 1/10.85 scaled version of an 85 foot diameter, Type IIIA, nuclear waste tank that may be typical of Blend Tanks used in SDI. Specifically, Tank 50 was selected as the tank to be modeled per the SRR, Project Engineering Manager. SRNL blending tests investigated various fixed position, non-rotating, dual nozzle pump designs, including a blending pump model provided by the blend pump vendor, Curtiss Wright (CW). Primary research goals were to assess blending times and to evaluate incipient sludge disturbance for waste tanks. Incipient sludge disturbance was defined by SRR and SRNL as minor blending of settled sludge from the tank bottom into suspension due to blending pump operation, where the sludge level was shown to remain constant. To experimentally model the sludge layer, a very thin, pourable, sludge simulant was conservatively used for all testing. To experimentally model the liquid, supernate layer above the sludge in waste tanks, two salt solution simulants were used, which provided a bounding range of supernate properties. One solution was water (H{sub 2}O + NaOH), and the other was an inhibited, more viscous salt solution. The research performed and data obtained significantly advances the understanding of fluid mechanics, mixing theory and CFD modeling for nuclear waste tanks by benchmarking CFD results to actual experimental data. This research significantly bridges the gap between previous CFD models and actual field experiences in real waste tanks. A finding of the 2009, DOE, Slurry Retrieval, Pipeline Transport and Plugging, and Mixing Workshop was that CFD models were inadequate to assess blending processes in nuclear waste tanks. One recommendation from that Workshop was that a validation, or bench marking program be performed for CFD modeling versus experiment. This research provided experimental data to validate and correct CFD models as they apply to mixing and blending in nuclear waste tanks. Extensive SDI research was a significant step toward bench marking and applying CFD modeling. This research showed that CFD models not only agreed with experiment, but demonstrated that the large variance in actual experimental data accounts for misunderstood discrepancies between CFD models and experiments. Having documented this finding, SRNL was able to provide correction factors to be used with CFD models to statistically bound full scale CFD results. Through the use of pilot scale tests performed for both types of pumps and available engineering literature, SRNL demonstrated how to effectively apply CFD results to salt batch mixing in full scale waste tanks. In other words, CFD models were in error prior to development of experimental correction factors determined during this research, which provided a technique to use CFD models for salt batch mixing and transfer pump operations. This major scientific advance in mixing technology resulted in multi-million dollar cost savings to SRR. New techniques were developed for both experiment and analysis to complete this research. Supporting this success, research findings are summarized in the Conclusions section of this report, and technical recommendations for design and operation are included in this section of the report.

08 HYDROGEN↗

Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems

Abstract. Over the past 4 decades, a number of numerical models have been developed to quantify the magnitude, investigate the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH4) fluxes within terrestrial ecosystems. These CH4 models are also used for integrating multi-scale CH4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvement and application. Our key findings are that (1) the focus of CH4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls, and (3) significant data–model and model–model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Three areas for future improvements and applications of terrestrial CH4 models are that (1) CH4 models should more explicitly represent the mechanisms underlying land–atmosphere CH4 exchange, with an emphasis on improving and validating individual CH4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. These improvements in CH4 models would be beneficial for the Earth system models and further simulation of climate–carbon cycle feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Revisiting trends in the exchange current for hydrogen evolution

Nørskov and collaborators proposed a simple kinetic model to explain the volcano relation for the hydrogen evolution reaction on transition metal surfaces such that j 0 = k 0 f(ΔG H ) where j 0 is the exchange current density, f(ΔG H ) is a function of the hydrogen adsorption free energy ΔG H as computed from density functional theory, and k 0 is a universal rate constant. Herein, focusing on the hydrogen evolution reaction in acidic medium, we revisit the original experimental data and find that the fidelity of this kinetic model can be significantly improved by invoking metal-dependence on k 0 such that the logarithm of k 0 linearly depends on the absolute value of ΔG H . Here, we further confirm this relationship using additional experimental data points obtained from a critical review of the available literature. Our analyses show that the new model decreases the discrepancy between calculated and experimental exchange current density values by up to four orders of magnitude. Furthermore, we show the model can be further improved using machine learning and statistical inference methods that integrate additional material properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nitrogen Monitoring of West Hackberry 117 Cavern Wells

U.S. Strategic Petroleum Reserve (SPR) oil storage cavern West Hackberry 117 was tested under extended nitrogen monitoring following a successful mechanical integrity test in order to validate a newly developed hydrostatic column model to be used to differentiate between normal "tight" well behavior and small-leak behavior under nitrogen. High resolution wireline pressure and temperature data were collected during the test period and used in conjunction with the hydrostatic column model to predict the nitrogen/oil interface and the pressure along the entire fluid column from the bradenhead flange nominally at ground surface to bottom of brine pool. Results here and for other SPR caverns have shown that wells under long term nitrogen monitoring do not necessarily pressurize with a relative rate (P N2 /P brine) of 1. The theoretical relative pressure rate depends on the well configuration, pressure and the location of the nitrogen-oil interface and varies from well to well. For the case of WH117 the predicted rates were 0.73 for well A and 0.92 for well B. The measured relative pressurization rate for well B was consistent with the model prediction, while well A rate was found to be between 0.58-0.68. A number of possible reasons for the discrepancy between the model and measured rates of well A are possible. These include modeling inaccuracy, measurement inaccuracy or the possibility of the presence of a very small leak (below the latest calculated minimum detectable leak rate).

02 PETROLEUM↗

Nitrogen Monitoring of West Hackberry 117 Cavern Wells (Revision 1)

U.S. Strategic Petroleum Reserve (SPR) oil storage cavern West Hackberry 117 was tested under extended nitrogen monitoring following a successful mechanical integrity test in order to validate a newly developed hydrostatic column model to be used to differentiate between normal “tight” well behavior and small-leak behavior under nitrogen. High resolution wireline pressure and temperature data were collected during the test period and used in conjunction with the hydrostatic column model to predict the nitrogen/oil interface and the pressure along the entire fluid column from the bradenhead flange nominally at ground surface to bottom of brine pool. Results here and for other SPR caverns have shown that wells under long term nitrogen monitoring do not necessarily pressurize with a relative rate (P N2 /P brine ) of 1. The theoretical relative pressure rate depends on the well configuration, pressure and the location of the nitrogen-oil interface and varies from well to well. For the case of WH117 the predicted rates were 0.73 for well A and 0.92 for well B. The measured relative pressurization rate for well B was consistent with the model prediction, while well A rate was found to be between 0.58-0.68. A number of possible reasons for the discrepancy between the model and measured rates of well A are possible. These include modeling inaccuracy, measurement inaccuracy or the possibility of the presence of a very small leak (below the latest calculated minimum detectable leak rate).

54 ENVIRONMENTAL SCIENCES↗

THE KINEMATICS OF MULTIPLE-PEAKED Ly{alpha} EMISSION IN STAR-FORMING GALAXIES AT z {approx} 2-3

We present new results on the Ly{alpha} emission-line kinematics of 18 z {approx} 2-3 star-forming galaxies with multiple-peaked Ly{alpha} profiles. With our large spectroscopic database of UV-selected star-forming galaxies at these redshifts, we have determined that {approx}30% of such objects with detectable Ly{alpha} emission display multiple-peaked emission profiles. These profiles provide additional constraints on the escape of Ly{alpha} photons due to the rich velocity structure in the emergent line. Despite recent advances in modeling the escape of Ly{alpha} from star-forming galaxies at high redshifts, comparisons between models and data are often missing crucial observational information. Using Keck II NIRSPEC spectra of H{alpha} (z {approx} 2) and [O III]{lambda}5007 (z {approx} 3), we have measured accurate systemic redshifts, rest-frame optical nebular velocity dispersions, and emission-line fluxes for the objects in the sample. In addition, rest-frame UV luminosities and colors provide estimates of star formation rates and the degree of dust extinction. In concert with the profile sub-structure, these measurements provide critical constraints on the geometry and kinematics of interstellar gas in high-redshift galaxies. Accurate systemic redshifts allow us to translate the multiple-peaked Ly{alpha} profiles into velocity space, revealing that the majority (11/18) display double-peaked emission straddling the velocity-field zero point with stronger red-side emission. Interstellar absorption-line kinematics suggest the presence of large-scale outflows for the majority of objects in our sample, with an average measured interstellar absorption velocity offset of ({Delta}v{sub abs}) = -230 km s{sup -1}. A comparison of the interstellar absorption kinematics for objects with multiple- and single-peaked Ly{alpha} profiles indicate that the multiple-peaked objects are characterized by significantly narrower absorption line widths. We compare our data with the predictions of simple models for outflowing and infalling gas distributions around high-redshift galaxies. While popular 'shell' models provide a qualitative match with many of the observations of Ly{alpha} emission, we find that in detail there are important discrepancies between the models and data, as well as problems with applying the framework of an expanding thin shell of gas to explain high-redshift galaxy spectra. Our data highlight these inconsistencies, as well as illuminating critical elements for success in future models of outflow and infall in high-redshift galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

How strongly do hydrogen and water molecules stick to carbon nanomaterials?

The interaction strength of molecular hydrogen and water to carbon nanomaterials is relevant to, among many applications, hydrogen storage, water treatment, and water flow. Yet, accurate interaction energies for hydrogen and water with carbon nanotubes (CNTs) remain scarce despite the importance of having reliable benchmark data to inform experiments and to validate computational models. Here, benchmark fixed-node diffusion Monte Carlo (DMC) interaction energies are provided for hydrogen and water monomers inside and outside a typical zigzag CNT. The DMC interaction energies provide valuable insight into molecular interactions with CNTs in general and are also expected to be particularly relevant to gas uptake studies on CNTs. In addition, a selection of density functional theory (DFT) exchange-correlation (xc) functionals and force field potentials that ought to be suitable for these systems is compared. An unexpected variation is found in the performance of DFT van der Waals (vdW) models in particular. An analysis of the peculiar discrepancy between different vdW models indicates that medium-range correlation (at circa 3 to 5 Å) plays a key role inside CNTs and is poorly predicted by some vdW models. Using accurate reference information, this work reveals which xc functionals and force fields perform well for molecules interacting with CNTs. The results will be valuable to future work on these and related systems that involve molecules interacting with low-dimensional systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Whitepaper prepared for DOE Workshop on Integrated Simulations for Magnetic Fusion Energy Sciences: Topic E: Beyond interpretive simulations

Predictive simulations of magnetic confinement fusion and burning plasmas will require the quantification of all uncertainties and errors relating to the simulation capabilities. These include: discretization error (temporal and spatial); incomplete convergence error (nonlinear, linear, etc.); uncertainties in input data (initial conditions, boundary conditions, coefficients, thermo-physical properties, source terms, etc.); and uncertainties in the component models (the specific form and parameter values).13 Typically, there is a focus on model parameter uncertainties but uncertainties about which model to use and about the bias or discrepancy of a particular model (sometimes called model form error) often dominate parameter uncertainty. This whitepaper addresses the challenges of performing uncertainty quantification (UQ) for expensive computational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multifidelity multiobjective optimization for wake-steering strategies

Abstract. Wake steering is an emerging wind power plant control strategy where upstream turbines are intentionally yawed out of perpendicular alignment with the incoming wind, thereby “steering” wakes away from downstream turbines. However, trade-offs between the gains in power production and fatigue loads induced by this control strategy are the subject of continuing investigation. In this study, we present a multifidelity multiobjective optimization approach for exploring the Pareto front of trade-offs between power and loading during wake steering. A large eddy simulation is used as the high-fidelity model, where an actuator line representation is used to model wind turbine blades and a rainflow-counting algorithm is used to compute damage equivalent loads. A coarser simulation with a simpler loads model is employed as a supplementary low-fidelity model. Multifidelity Bayesian optimization is performed to iteratively learn both a surrogate of the low-fidelity model and an additive discrepancy function, which maps the low-fidelity model to the high-fidelity model. Each optimization uses the expected hypervolume improvement acquisition function, weighted by the total cost of a proposed model evaluation in the multifidelity case. The multifidelity approach is able to capture the logit function shape of the Pareto frontier at a computational cost only 30 % that of the single-fidelity approach. Additionally, we provide physical insights into the vortical structures in the wake that contribute to the Pareto front shape.

17 WIND ENERGY↗

Design and Performance of a Smartphone-based Cosmic Ray Observatory

This dissertation examines the feasibility of appropriating the global network of smartphones as an observatory for ultra-high-energy cosmic rays. An application and cloud-based data-acquisition system are first proposed for such an observatory, in which heterogenous devices self-calibrate and server feedback optimizes individual device triggers. Methods of monitoring and manually controlling this network are also examined. Detection efficiencies for cosmic muons, MeV-scale gamma rays, and 120 GeV protons are then measured for this trigger, with which a Monte Carlo pixel model is fine-tuned. Extending this model to cosmic ray showers, the effective area of the observatory for super-GZK primaries is shown to equal that of the Pierre Auger Observatory with a global participation rate under 0.1%, far below initial estimates presented in Ref. [83]. A vastly improved sensitivity to photons and more precise modeling of electrons are primarily responsible for this discrepancy, though more refined models of the combinatorial background may yet lead to more stringent requirements.

Swaney, Jeff↗

Verifying MCNP Models of the TEX High 240 Plutonium Benchmark

Computational modeling programs are invaluable tools that allow us to understand systems, safely develop new processes, and make reliable predictions about future designs. However, the effectiveness of these codes is limited by the degree to which their parameters match the real world. In the field of nuclear engineering, cross section data is one of these vital parameters. Accurate cross section data on important fissile and fissionable isotopes promotes the design of safer and more efficient fabrication, transportation, storage, and stockpiling of nuclear fuel. Unfortunately, there are knowledge gaps in data on key isotopes. In 2011, a multinational meeting hosted by the US Department of Energy Nuclear Criticality Safety Program ranked the priority of certain cross section data needs. In response, Lawrence Livermore National Lab (LLNL) designed the Thermal and Epithermal eXperiment (TEX) series of benchmark experiments. Benchmark experiments are used to validate current cross section data. They validate data by comparing the results of an actual experiment to the predicted results from a computational model. The data a benchmark applies to depends on the isotope and energy range the experiment’s neutron multiplication factor ( k eff ) is most sensitive to. The development and testing of the TEX High 240 Plutonium Benchmark will help validate 240 Pu cross section data. The configuration and materials of this benchmark are designed to be most sensitive to 240 Pu's intermediate energy range (from 0.625 ev to 100 keV ). MCNP® models of the assembly have been developed by LLNL and the results have been written in the final design report. In order for the discrepancies between benchmark models and experiments to be attributed to cross section inaccuracies, the accuracy of the models needs to be verified. The goal of this project is to verify of the results of LLNL's modeling by creating a new set of MCNP models and comparing the results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Magnetic Polarization Measurements of the Multi-modal Plasma Response to 3D fields in the EAST Tokamak

A multi-modal plasma response to applied non-axisymmetric fields has been found in EAST tokamak plasmas. Here, multi-modal means the radial and poloidal structure of an individually driven toroidal harmonic is not fixed. The signature of such a multi-modal response is the magnetic polarization (ratio of radial and poloidal components) of the plasma response field measured on the low field side device mid-plane. A difference in the 3D coil phasing (the relative phase of two coil arrays) dependencies between the two responses is observed in response to n=2 fields in the same plasma for which the n=1 responses are well synchronized. Neither the maximum radial nor the maximum poloidal field response to n=2 fields agrees with the best applied phasing for mitigating edge localized modes, suggesting that the edge plasma response is not a dominant component of either polarization. GPEC modeling reproduces the discrepant phasing dependences of the experimental measurements, and confirms the edge resonances are maximized by the coil phasing that mitigates ELMs in the experiments. The model confirms the measured plasma response is not dominated by resonant current drive from the external field. Instead, non-resonant contributions play a large role in the diagnostic signal for both toroidal harmonics n=1 and n=2. The analysis in this paper demonstrates the ability of 3D modeling to connect external magnetic sensor measurements to the internal plasma physics and accurately predict optimal applied 3D field configurations in multi-modal plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

BENCHMARK TESTS FOR MARKOV CHAIN MONTE CARLO FITTING OF EXOPLANET ECLIPSE OBSERVATIONS

Ground-based observations of exoplanet eclipses provide important clues to the planets' atmospheric physics, yet systematics in light curve analyses are not fully understood. It is unknown if measurements suggesting near-infrared flux densities brighter than models predict are real, or artifacts of the analysis processes. We created a large suite of model light curves, using both synthetic and real noise, and tested the common process of light curve modeling and parameter optimization with a Markov Chain Monte Carlo algorithm. With synthetic white noise models, we find that input eclipse signals are generally recovered within 10% accuracy for eclipse depths greater than the noise amplitude, and to smaller depths for higher sampling rates and longer baselines. Red noise models see greater discrepancies between input and measured eclipse signals, often biased in one direction. Finally, we find that in real data, systematic biases result even with a complex model to account for trends, and significant false eclipse signals may appear in a non-Gaussian distribution. To quantify the bias and validate an eclipse measurement, we compare both the planet-hosting star and several of its neighbors to a separately chosen control sample of field stars. Re-examining the Rogers et al. Ks-band measurement of CoRoT-1b finds an eclipse 3190{sup +370}{sub -440} ppm deep centered at {phi}{sub me} = 0.50418{sup +0.00197}{sub -0.00203}. Finally, we provide and recommend the use of selected data sets we generated as a benchmark test for eclipse modeling and analysis routines, and propose criteria to verify eclipse detections.

79 ASTRONOMY AND ASTROPHYSICS↗

Large Eddy Simulation of Low-Reynolds-Number Turbulent Flow of Low-Prandtl-Number Fluid in a Tight Lattice Bundle for Assessment of Reynolds-Averaged Navier-Stokes Turbulence Model

The MARVEL (Microreactor Applications Research Validation and Evaluation) microreactor utilizes natural circulation as core cooling mechanism and liquid metal as a primary coolant. Moreover, the reactor core has a pitch-to-diameter ratio of 1.056, which is considered a tight lattice configuration. Numerous studies have widely reported that Reynolds-Averaged Navier-Stokes (RANS) turbulence models inaccurately predict heat transfer in liquid metals and fail to capture flow pulsations that can occur within tight lattices, leading to further inaccuracies in simulation results. Therefore, evaluating the accuracy of RANS turbulence models in the thermal-hydraulic analysis of the MARVEL microreactor core is crucial for assessing reactor safety. In this study, a Large Eddy Simulation (LES) of the MARVEL microreactor core subchannel was conducted and compared with a RANS simulation to evaluate the accuracies and conservatism of the RANS model. The flow pulsation in a tight lattice predicted by LES enhanced the heat transfer, whereas the RANS model underpredicted it. Consequently, the RANS model predicted the peak cladding temperature higher than the LES model, but the discrepancy between the two approaches was not significant due to the good thermal characteristics of the liquid metal. It can be concluded that the steady-state RANS model is effective for the thermal analysis of liquid-metal-cooled MARVEL microreactor core and can provide conservative predictions from a safety analysis perspective.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DISCOVERY OF A HALO AROUND THE HELIX NEBULA NGC 7293 IN THE WISE ALL-SKY SURVEY

We report the discovery of an extended halo ({approx}40' in diameter) around the planetary nebula NGC 7293 (the Helix Nebula) observed in the 12 {mu}m band from the Wide-field Infrared Survey Explorer all-sky survey. The mid-infrared halo has an axisymmetric structure with a sharp boundary to the northeast and a more diffuse boundary to the southwest, suggesting an interaction between the stellar wind and the interstellar medium (ISM). The symmetry axis of the halo is well aligned with that of a northeast arc, suggesting that the two structures are physically associated. We have attempted to fit the observed geometry with a model of a moving steady-state stellar wind interacting with the ISM. Possible combinations of the ISM density and the stellar velocity are derived from these fittings. The discrepancies between the model and the observations suggest that the stellar mass loss has a more complicated history, including possible time and angle dependences.

79 ASTRONOMY AND ASTROPHYSICS↗

Bayesian Treed Calibration: An Application to Carbon Capture With AX Sorbent

In cases where field or experimental measurements are not available, computer models can model real physical or engineering systems to reproduce their outcomes. They are usually calibrated in light of experimental data to create a better representation of the real system. Statistical methods, based on Gaussian processes, for calibration and prediction have been especially important when the computer models are expensive and experimental data limited. In this paper, we develop the Bayesian treed calibration (BTC) as an extension of standard Gaussian process calibration methods to deal with non-stationarity computer models and/or their discrepancy from the field (or experimental) data. Our proposed method partitions both the calibration and observable input space, based on a binary tree partitioning, into sub-regions where existing model calibration methods can be applied to connect a computer model with the real system. The estimation of the parameters in the proposed model is carried out using Markov chain Monte Carlo (MCMC) computational techniques. Different strategies have been applied to improve mixing. We illustrate our method in two artificial examples and a real application that concerns the capture of carbon dioxide with AX amine based sorbents. The source code and the examples analyzed in this paper are available as part of the supplementary materials.

Bayesian tree↗

Sequential spectral line analysis for accurate density and temperature diagnosis of laboratory opacity measurements

The accuracy of iron opacity calculated in stellar interiors has been questioned since the discovery of the “solar problem” and the discrepancies between the measured and modeled iron opacity reported in 2015. Experimental opacity benchmarks require accurate temperature and density measurements, which were inferred by analyzing tracer magnesium spectra in those experiments. Could the observed discrepancy be explained by insufficient accuracy in the inferred temperature, density, and their uncertainties? Previous analyses may have yielded biased results due to three limitations: (1) simultaneous multi-line fitting, (2) approximations in line-shape models, and (3) exclusion of certain spectral lines due to insufficient background characterization. Notably, the first issue is a common concern for many inversion methods, including Bayesian inferences. We present a refined analysis method that overcomes these limitations, applied to three categories of iron opacity experiments (Anchor 1, 2, and 3). In particular, the sequential fitting method yields unbiased results with more realistic uncertainties by accounting for line inconsistencies in the parameter uncertainties. The average electron temperature and density values are 162 ± 6 eV and (7.0 ± 1.9) × 10 21 cm −3 for six Anchor 1 experiments, 189 ± 7 eV and (3.4 ± 0.3) × 10 22 cm −3 for 21 Anchor 2 experiments, and 201 ± 6 eV and (4.8 ± 1.1) × 10 22 cm −3 for nine Anchor 3 experiments. These results show ∼4% temperature and ∼20% density reproducibility over a decade, which also aligns with the inferred parameter uncertainties. In conclusion, the resulting temperature and density uncertainties lead to a quasi-continuum iron opacity variation of ±4%–7% for wavelengths below 9.5 Å, which is insufficient to explain the significant model-data discrepancies reported in 2015.

Absorption spectroscopy↗