Physics Database Research Articles

Design of a new physics database for FLUKA’s next generation

The physics database used by FLUKA dates back more than thirty years. It relies on legacy data structures that, although efficient, are increasingly complicated to maintain. The inception of a new generation of FLUKA code represents a great opportunity to modernize this database. This major upgrade implements a modularization of the data structures and a simplification of the formats. It comes along with the development of auxiliary scripts permitting extensive data testing and regular updating. Interfaces of the new database with both the existing generation of FLUKA as well as the new one are described, including the hierarchical object-oriented paradigm chosen to access data elements in the modernized codebase. Finally, perspectives are given to the extension of this work in terms of contents and features.

BISON-FIPD integration enhanced low-burnup SFR metallic fuel swelling model evaluation framework

Experiments indicated that metallic fuel in sodium-cooled fast reactors (SFRs) rapidly swells radially and axially at low burnup. Despite that, prior studies have been focused on describing high burnup axial fuel elongation. With recent conventional and non-conventional metallic fuel concepts being considered for license applications, understanding multidimensional fuel swelling at a wide range of burnup levels is important to fuel analysis and qualification activities. Here, we report the development and demonstration efforts of a low-burnup SFR metallic fuel swelling model evaluation framework using the BISON advanced fuel performance code. The framework leverages the Integral Fast Reactor (IFR) program X423 experiment data through the ongoing integration project to enable standardized and automated use of legacy metallic fuel irradiation data maintained in the SFR fuel irradiation and physics database (FIPD) for BISON metallic fuel model verification and validation. The performance of the framework was demonstrated using the two representative metallic fuel swelling model sets implemented in BISON, with a series of insights about future advanced swelling model development.

Factors Associated with Long-Term Prostate Cancer Survival after Palliative Radiotherapy to a Bone Metastasis and Contemporary Palliative Systemic Therapy: A Retrospective, Population-Based Study

Background: Radiation therapy (RT) is an established palliative treatment for bone metastases; however, little is known about post-radiation survival and factors which impact it. The aim of this study was to assess a population-based sample of metastatic prostate cancer patients receiving palliative radiation therapy to bone metastases and contemporary palliative systemic therapy and identify factors that impact long-term survival. Materials/methods: This retrospective, population-based, cohort study assessed all prostate cancer patients receiving palliative RT for bone metastases at a Canadian provincial Cancer program during a contemporary time period. Baseline patient, disease, and treatment characteristics were extracted from the provincial medical physics databases and the electronic medical record. Post-RT Survival intervals were defined as the time interval from the first fraction of palliative RT to death from any cause or date of the last known follow-up. The median survival of the cohort was used to dichotomize the cohort into short- and long-term survivors following RT. Univariable and multivariable hazard regression analyses were performed to identify variables associated with post-RT survival. Results: From 1 January 2018 until 31 December 2019, 545 palliative RT courses for bone metastases were delivered to n = 274 metastatic prostate cancer patients with a median age of 76 yrs (Interquartile range (IQR) 39–83) and a median follow-up of 10.6 months (range 0.2 to 47.9). The median survival of the cohort was 10.6 months (IQR 3.5–25 months). The ECOG performance status of the whole cohort was ≤2 in n = 200 (73%) and 3–4 in n = 67 (24.5%). The most commonly treated sites of bone metastasis were the pelvis and lower extremities n = 130 (47.4%), skull and spine n = 114 (41.6%), and chest and upper extremities n = 30 (10.9%). Most patients had CHAARTED high volume disease n = 239 (87.2%). On multivariable hazard regression analysis, an ECOG performance status of 3–4 (p = 0.02), CHAARTED high volume disease burden (p = 0.023), and non-receipt of systemic therapy (p = 0.006) were significantly associated with worse post-RT survival. Conclusion: Amongst metastatic prostate cancer patients treated with palliative radiotherapy to bone metastases and modern palliative systemic therapies, ECOG performance status, CHAARTED metastatic disease burden, and type of first-line palliative systemic therapy were significantly associated with post-RT survival durations.

Evaluation of BISON metallic fuel performance modeling against experimental measurements within FIPD and IMIS databases

Simulations were conducted using the BISON fuel performance code on an automated process to read initial and operating conditions from two databases—the Fuels Irradiation and Physics Database (FIPD) and Integral Fast Reactor Materials Information System (IMIS) database. These databases contain metallic fuel data from the Experimental Breeder Reactor-II (EBR-II) and the Fast Flux Test Facility (FFTF). The work demonstrates use of an integrated framework to access EBR-II fuel pin data for evaluating fuel performance models contained within BISON to predict fuel performance of next-generation metallic fuel systems. Between IMIS and FIPD, there is enough information to conduct 1,977 unique EBR-II metallic fuel pin histories from 29 different experiments, and 338 pins from FFTF MFF-3 and MFF-5 with varying levels of details between the two databases. Each of these fuel performance histories includes a high-resolution power history, flux history, coolant channel flow rates, and coolant channel temperatures, and new model developments in BISON since the initial demonstration of this integrated framework. Fission gas release (FGR), cumulative damage fraction, fuel axial swelling, FCCI wastage thickness, cladding profilometry, and burnup were all simulated in BISON and compared to post-irradiation examination (PIE) results to evaluate BISON fuel performance modeling. Implementation of new fuel performance models into a generic BISON input file coupled with IMIS and FIPD yielded results with a better representation of physics than the initial evaluation of the integrated framework. Cladding profilometry, FGR, and fuel axial swelling were found to be in good agreement with PIE measurements for most of the pins simulated. The chosen mechanical contact solver was found to significantly impact the axial fuel swelling and cladding strain predictions when used in conjunction with the U-Pu-Zr hot-pressing model since it bound the fuel to prevent further swelling and increased hydrostatic stresses. This work suggests that fuel performance modeling in BISON under steady-state conditions represents the PIE data well and should be reassessed when new PIE data become available in IMIS and FIPD databases and when improved physical models to better capture fuel performance are added to BISON.

Ideas and Tools for Error Detection in Opacity Databases

In this article, we propose several ideas and tools in order to check the reliability of radiative opacity and atomic physics databases. We first emphasize that it can be useful to verify that mathematical inequalities, which impose lower and upper bounds on the Rosseland and/or Planck mean opacities, are satisfied, either for pure elements or mixtures. In the second part, we discuss the intriguing law of anomalous numbers, also named Benford’s law, which enables one to detect errors in line-strength collections, required in order to perform fine-structure calculations. Finally, we point out and illustrate the importance of quantifying the uncertainties due to interpolations in the density-temperature opacity (or more generally atomic-data) tables and performing convergence checks, which are crucial in the accuracy-completeness compromise inherent in opacity computations.

Recommendations for soil sample preparation, pretreatment, and data conversion for texture classification in laser diffraction particle size analysis

With regard to the differences between soil particle size distribution (PSD) obtained by sieve-sedimentation methods (SSMs), e.g., the sieve-pipette method (SPM) and the laser diffraction method (LDM), usually, the clay fraction content in LDM measurements is lower than in SSM. Two groups of reasons can be identified for this. Firstly, differences resulting from the features of the methods themselves. Secondly, differences resulting from the soil sample preparation (after sampling) and pretreatment (disaggregation). These differences not only cause difficulties in the PSDs comparability but also make it difficult, and sometimes even impossible, to apply the LDM results to soil texture classification. The solution to this difficulty may be to use pedotransfer functions and standardization of measurement procedures. The aim of this work was to validate the pedotransfer function proposed by Makó et al. (2017) on a Polish soil physics database for recalculating the results from LDM to compare them with SPM results and assess how the soil preparation and pretreatment influenced the obtained PSD and resulting soil texture classification. Using the pedotransfer function, 74 % accuracy was achieved, which is comparable with the results of other pedotransfer functions reported in the literature. Comparing the PSD results for the methods of sample preparation found in the literature after sampling (analysis of fresh, air dry and oven-dried – in 105 °C – soil) and pretreatment before the measurement (breaking soil aggregates chemically and physically) allows recommending the conducting of LDM PSD measurements using air dry soils and soil ultrasound disaggregation.

BISON fuel performance modeling optimization for experiment X447 and X447A using axial swelling and cladding strain measurements

With the recent need to qualify new reactor designs, such as the Versatile Test Reactor, researchers need fuel performance calculations to determine the safety criteria of proposed designs. In order to validate the fuel performance results obtained by the fuel performance code BISON for new reactor designs, legacy fuel from EBR-II and Fast Flux Test Facility MFF with post-irradiation examination (PIE) data need to be used as validation cases to benchmark models. In this work, BISON has been paired with the Fuels Irradiation & Physics Database (FIPD) and the Integral Fast Reactor Materials Information System (IMIS) to supply PIE data for comparison with simulations of EBR-II experiments X447/X447A. X447/X447A were assessed by implementing models for a fuel-cladding chemical interaction (FCCI) within BISON and optimizing the friction coefficient between the fuel surface and the cladding, the anisotropic swelling factor, and the HT9 first thermal creep scalar (which scales the first term in the HT9 creep equation) to best match the PIE axial fuel swelling height and cladding profilometry for all pins in X447/X447A. The optimal values were found using a generic algorithm developed to select different values for the three parameters until end criteria was met and error couldn’t be reduced further. The BISON-simulated cladding profilometry was evaluated using a standard error of the estimate to account for the profile shape of the cladding profilometry. Optimal values for the friction coefficient, anisotropic fuel swelling factor, and HT9 first thermal creep scalar were found to best fit the BISON simulation results to the PIE measurements found in IMIS and FIPD. Possible improvements to current models to account for the underprediction of fuel swelling at low burnups and the overprediction of fuel swelling at higher burnups that is observed for the axial fuel swelling height are discussed. Although two pins in EBR-II, X447/X447A (DP70 and DP75), were known to fail due to FCCI, none of the pins simulated in BISON reached a cumulative damage fraction above 0.008 with FCCI correlations coupled in the BISON simulations. The error estimate generated for all pins in X447/X447A using optimal values was 209 µm, which is deemed acceptable.

Metallic fuel cladding degradation model development and evaluation for BISON

Fuel cladding chemical interaction (FCCI) and coolant cladding chemical interaction (CCCI), both consume stainless-steel cladding in sodium-cooled fast reactors (SFRs), and effectively degrade cladding mechanical performance through thickness reduction. Therefore, FCCI/CCCI and corresponding cladding degradation models are essential for advanced fuel performance codes, such as BISON, to reliably predict cladding behavior in SFRs. Here, we report the development and implementation efforts for BISON’s FCCI/CCCI correlations and cladding degradation models based on U.S. legacy metallic fuel data. The models were evaluated using Integral Fast Reactor (IFR) program X447/A experiment data supported by the ongoing integration project enabling coordinated application of BISON and EBR-II fuel irradiation and physics database (FIPD). The implemented models were demonstrated to improve BISON’s capabilities of predicting cladding damage and degradation behavior that is more consistent with post-irradiation examination observations. Additionally, some limitations of current BISON modules are identified, which are to be overcome through the BISON-FIPD integration efforts.

Initial demonstration of automated fuel performance modeling with 1977 EBR-II metallic fuel pins using BISON code with FIPD and IMIS databases

Using the BISON fuel performance code, simulations were conducted using an automated process to read initial and operating conditions from the Fuels Irradiation and Physics Database (FIPD) and Integral Fast Reactor materials information system (IMIS) database, which contains metallic fuel data from the Experimental Breeder Reactor-II (EBR-II). This work demonstrates use of an integrated framework to access the vast majority of EBR-II experimental fuel pin data to support rapid development of fuel performance models for next-generation metallic fuel systems. With this capability, validation for fuel qualification can be performed rapidly. Between IMIS and FIPD, there is enough information to conduct 1977 unique EBR-II metallic fuel pin histories from 24 different experiments, at varying levels of detail between the two databases. Each of these histories includes a high-resolution power history, flux history, coolant channel flow rates, and coolant channel temperatures. Fission gas release (FGR), cumulative damage fraction (CDF), fuel axial swelling, cladding profilometry, and burnup were all simulated in BISON. The results were compared to post-irradiation examination (PIE) results for the initial demonstration of automated BISON modeling. BISON simulations conducted with IMIS and FIPD were in rough agreement with PIE measurements and calculations. Cladding profilometry, FGR, and fuel axial swelling were found to be in rough agreement with PIE measurements, depending on the physics used within the BISON input files. The mechanical contact solver chosen was found to significantly impact axial fuel swelling and cladding strain predictions. CDF values were assessed to see whether pin failure may have been predicted (CDF ≥ 1). This work suggests that continued development of an automated tool for BISON should focus on inclusion of the Fast Flux Test Facility (FFTF) experimental data for a larger database for metallic fuel, improved physical models to better capture fuel performance, such as fuel-cladding interactions, and a more detailed comparison with available PIE data to further the BISON model development.

FIPD: The SFR metallic fuels irradiation & physics database

The DOE Advanced Reactor Technology (ART) program has supported efforts to recover and preserve metallic fuel data generated throughout the US sodium-cooled fast reactor (SFR) program. Those efforts have been focused on establishing databases of the experimental data that were mainly generated during the Integral Fast Reactor (IFR) program including data generated at Experimental Breeder Reactor-II (EBR-II), Fast Flux Test Facility (FFTF), and Transient Reactor Test Facility (TREAT) reactors, as well as out of pile data. The data is essential for future licensing activities of metallic fuel based advanced fast reactors. This paper describes the development of the SFR Metallic Fuels Irradiation & Physics Database (FIPD) and covers the scientific knowledge available in the database. The architecture of the FIPD is described by showing the available reactor operation data, fabrication, and post-irradiation examination (PIE) data, and other documents. The applications of the fuel database are also discussed.

Cladding Profilometry Analysis of Experimental Breeder Reactor-II Metallic Fuel Pins with HT9, D9, and SS316 Cladding

BISON finite element method fuel performance simulations were conducted using an existing automated process that couples the Fuels Irradiation & Physics Database (FIPD) and the Integral Fast Reactor Materials Information System database by writing input files and comparing the BISON output to post-irradiation fuel pin profilometry measurements contained within the databases. The importance of this work is to demonstrate the ability to benchmark fuel performance metallic fuel models within BISON using Experimental Breeder Reactor-II fuel pin data for a number of similar pins, while building off previous modeling efforts. Changes to the generic BISON input file include implementing pin specific axial power and flux profiles, pin specific fluences, frictional contact, and irradiation-induced volumetric swelling models for cladding. A statistical analysis of irradiation-induced volumetric swelling models for HT9, D9, and SS316 was performed for experiments X421/X421A, X441/X441A, and X486. Between these three experiments, there were 174 post-irradiation examination (PIE) profilometries used for validating the swelling models presented using a standard error of the estimate (SEE) method. Implementation of the volumetric swelling models for D9 and SS316 claddings was found to have a significant impact on the BISON profilometry simulated, where HT9 clad pins had an insignificant change due to low fluence values. BISON profilometry simulated for HT9, D9, and SS316 fuel pins agreed with PIE profilometry measurements, with assembly SEE values being 4.4 × 10−3 for X421A, 2.0 × 10−3 for X441A, and 2.8 × 10−3 for X486. D9 clad pins in X421/X421A had the highest SEE values, which is due to the BISON simulated profilometry being shifted axially. While this work accomplished its purpose to demonstrate the modeling of multiple fuel pins from the databases to help validate models, the results suggest that the continued development of metallic fuel models is necessary for qualifying new metallic fuel systems to better capture some physical performance phenomena, such as the hot pressing of U-Pu-Zr and the fuel cladding chemical interaction.

Digital core repository coupled with machine learning as a tool to classify and assess petrophysical rock properties

To make efficient use of image-based rock physics workflow, it is necessary to optimize different criteria, among which: quantity, representativeness, size and resolution. Advances in artificial intelligence give insights of databases potential. Deep learning methods not only enable to classify rock images, but could also help to estimate their petrophysical properties. In this study we prepare a set of thousands high-resolution 3D images captured in a set of four reservoir rock samples as a base for learning and training. The Voxilon software computes numerical petrophysical analysis. We identify different descriptors directly from 3D images used as inputs. We use convolutional neural network modelling with supervised training using TensorFlow framework. Using approximately fifteen thousand 2D images to drive the classification network, the test on thousand unseen images shows any error of rock type misclassification. The porosity trend provides good fit between digital benchmark datasets and machine learning tests. In a few minutes, database screening classifies carbonates and sandstones images and associates the porosity values and distribution. This work aims at conveying the potential of deep learning method in reservoir characterization to petroleum research, to illustrate how a smart image-based rock physics database at industrial scale can swiftly give access to rock properties.

Incorporating Uncertainties in Atomic Data into the Analysis of Solar and Stellar Observations: A Case Study in Fe xiii

Abstract Information about the physical properties of astrophysical objects cannot be measured directly but is inferred by interpreting spectroscopic observations in the context of atomic physics calculations. Ratios of emission lines, for example, can be used to infer the electron density of the emitting plasma. Similarly, the relative intensities of emission lines formed over a wide range of temperatures yield information on the temperature structure. A critical component of this analysis is understanding how uncertainties in the underlying atomic physics propagate to the uncertainties in the inferred plasma parameters. At present, however, atomic physics databases do not include uncertainties on the atomic parameters and there is no established methodology for using them even if they did. In this paper we develop simple models for uncertainties in the collision strengths and decay rates for Fe xiii and apply them to the interpretation of density-sensitive lines observed with the EUV (extreme ultraviolet) Imagining spectrometer (EIS) on Hinode. We incorporate these uncertainties in a Bayesian framework. We consider both a pragmatic Bayesian method where the atomic physics information is unaffected by the observed data, and a fully Bayesian method where the data can be used to probe the physics. The former generally increases the uncertainty in the inferred density by about a factor of 5 compared with models that incorporate only statistical uncertainties. The latter reduces the uncertainties on the inferred densities, but identifies areas of possible systematic problems with either the atomic physics or the observed intensities.

HEPData: a repository for high energy physics data

The Durham High Energy Physics Database (HEPData) has been built up over the past four decades as a unique open-access repository for scattering data from experimental particle physics papers. It comprises data points underlying several thousand publications. Over the last two years, the HEPData software has been completely rewritten using modern computing technologies as an overlay on the Invenio v3 digital library framework. The software is open source with the new site available at https://hepdata.net now replacing the previous site at http://hepdata.cedar.ac.uk. In this write-up, we describe the development of the new site and explain some of the advantages it offers over the previous platform.

Evolving landscape of low-energy nuclear physics publications

Evolution of low-energy nuclear physics publications over the last 120 years has been analyzed using nuclear physics databases. An extensive study of Nuclear Science References, Experimental Nuclear Reaction Data (EXFOR), and Evaluated Nuclear Structure Data File (ENSDF) contents provides a unique picture of refereed and non-refereed nuclear physics references. Significant fractional contributions of non-refereed reports, private communications and conference proceedings in EXFOR and ENSDF databases in the 1970's reflect extensive experimental campaigns and an insufficient number of research journals. This trend has been reversed in recent years because the number of measurements is much lower, while number of journals is higher. In addition, nuclear physics results are mainly published in a limited number of journals, such as Physical Review C and Nuclear Physics A. In the present work, historic publication trends and averages have been extracted and analyzed using nuclear data mining techniques. The results of this study and implications are discussed and conclusions presented.

Anatomy of the AGN in NGC 5548

(Abridged) The archetypal Seyfert 1 galaxy NGC 5548 was observed in 2013-2014 in the context of an extensive multiwavelength campaign, which revealed the source to be in an extraordinary state of persistent heavy obscuration. We re-analyzed the archival grating spectra obtained by XMM-Newton and Chandra between 1999 and 2007 in order to characterize the classic warm absorber (WA) using consistent models and up-to-date photoionization codes and atomic physics databases and to construct a baseline model that can be used as a template for the WA in the 2013 observations. The WA in NGC 5548 is composed of 6 distinct ionization phases outflowing in 4 kinematic regimes in the form of a stratified wind with several layers intersected by our line of sight. If the changes in the WA are solely due to ionization or recombination processes in response to variations in the ionizing flux among the different observations, we are able to estimate lower limits on the density of the WA, finding that the farthest components are less dense and have a lower ionization. These limits are used to put stringent upper limits on the distance of the WA components from the central ionizing source, with the lowest ionization phases <50, <20, and <5 pc, respectively, while the intermediately ionized components lie at <3.6 and <2.2 pc from the center, respectively. The highest ionization component is located at ~0.6 pc or closer to the AGN central engine. The mass outflow rate summed over all WA components is ~0.3 Msun/yr, about six times the nominal accretion rate of the source. The total kinetic luminosity injected into the ISM is a small fraction (~0.03%) of the bolometric luminosity of the source. After adding the contribution of the UV absorbers, this value augments to ~0.2% of the bolometric luminosity, well below the minimum amount of energy required by current feedback models to regulate galaxy evolution.

Implementation of a 3D halo neutral model in the TRANSP code and application to projected NSTX-U plasmas

A 3D halo neutral code developed at the Princeton Plasma Physics Laboratory and implemented for analysis using the TRANSP code is applied to projected National Spherical Torus eXperiment-Upgrade (NSTX-U plasmas). The legacy TRANSP code did not handle halo neutrals properly since they were distributed over the plasma volume rather than remaining in the vicinity of the neutral beam footprint as is actually the case. The 3D halo neutral code uses a ‘beam-in-a-box’ model that encompasses both injected beam neutrals and resulting halo neutrals. Upon deposition by charge exchange, a subset of the full, one-half and one-third beam energy components produce first generation halo neutrals that are tracked through successive generations until an ionization event occurs or the descendant halos exit the box. The 3D halo neutral model and neutral particle analyzer (NPA) simulator in the TRANSP code have been benchmarked with the Fast-Ion D-Alpha simulation (FIDAsim) code, which provides Monte Carlo simulations of beam neutral injection, attenuation, halo generation, halo spatial diffusion, and photoemission processes. When using the same atomic physics database, TRANSP and FIDAsim simulations achieve excellent agreement on the spatial profile and magnitude of beam and halo neutral densities and the NPA energy spectrum. The simulations show that the halo neutral density can be comparable to the beam neutral density. These halo neutrals can double the NPA flux, but they have minor effects on the NPA energy spectrum shape. The TRANSP and FIDAsim simulations also suggest that the magnitudes of beam and halo neutral densities are relatively sensitive to the choice of the atomic physics databases.

BEAMS3D Neutral Beam Injection Model**Notice: this manuscript has been authored by Princeton University under Contract Number DE-AC02-09CH11466 with the US Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript,

With the advent of applied 3D fields in Tokamaks and modern high performance stellarators, a need has arisen to address non-axisymmetric effects on neutral beam heating and fueling. We report on the development of a fully 3D neutral beam injection (NBI) model, BEAMS3D, which addresses this need by coupling 3D equilibria to a guiding center code capable of modeling neutral and charged particle trajectories across the separatrix and into the plasma core. Ionization, neutralization, charge-exchange, viscous slowing down, and pitch angle scattering are modeled with the ADAS atomic physics database. Elementary benchmark calculations are presented to verify the collisionless particle orbits, NBI model, frictional drag, and pitch angle scattering effects. A calculation of neutral beam heating in the NCSX device is performed, highlighting the capability of the code to handle 3D magnetic fields.

Structural analysis of the ITER Vacuum Vessel regarding 2012 ITER Project-Level Loads

A revision of the ITER Project-Level Load Specification (to be used for all systems of the ITER machine) was implemented in April 2012. This revision supports ITER's licensing by accommodating requests from the French regulator to maintain consistency with the plasma physics database and our present understanding of plasma transients and electro-magnetic (EM) loads, to investigate the possibility of removing unnecessary conservatism in the load requirements and to review the list and definition of incidental cases. The purpose of this paper is to present the impact of this 2012 revision of the ITER Project-Level Load Specification (LS) on the ITER Vacuum Vessel (VV) loads and the main structural margins required by the applicable French code, RCC-MR.

Atmospheric Imaging Assembly Response Functions: Solving the Fe viii Problems with Hinode EIS Bright Point Data

The Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory is a state-of-the-art imager with the potential to do unprecedented time-dependent multi-thermal analysis at every pixel on scales short compared to the radiative and conductive cooling times. Recent results, however, have identified missing spectral lines in the CHIANTI atomic physics data base, which is used to construct the instrument response functions. We have done differential emission measure analysis using simultaneous AIA and Hinode/EIS observations of six X-ray bright points. Our results not only support the conclusion that CHIANTI is incomplete near 131 angstroms, but more importantly, suggest that the peak temperature of the Fe VIII emissivity/response is likely to be closer to log T = 5.8 than to the current value of log T = 5.7. Using a revised emissivity/response calculation for Fe VIII, we find that the observed AIA 131-angstrom flux can be underestimated by about 1.25, which is smaller than previous comparisons.