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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Nonperturbative QCD corrections to the muon g-2

The value of the anomalous magnetic moment of the muon measured at Brookhaven National Lab disagrees with that predicted by the Standard Model by more than three standard deviations. This raises the prospects of discovering physics beyond the Standard Model if this discrepancy can be substantially verified. The uncertainty on the Standard Model result is dominated by hadronic corrections. The leading correction is currently estimated by a dispersive analysis of experimental measurements, but recent results have demonstrated that a fully theoretical and nonperturbative determination of this contribution can be obtained using the methods of lattice QCD. I will review the latest lattice calculations and discuss the prospects for a precise determination of the leading QCD correction to the muon g-2.

Renner, Dru↗
DOE OSTI2025

A Semi-Detailed Pyrolytic Gas-Phase Kinetic Model for the Volatiles of Polyethylene Thermal Degradation

This work presents a semi-detailed kinetic model to address the pyrolytic gas-phase reactivity of volatiles formed during thermal degradation of polyethylene (PE). The model builds on a validated multi-step condensed-phase model and employs validated lumping approaches. Short-chain compounds are modelled with high detail, while long-chain ones are described by surrogate species representative of diesel-cuts (NC16H32) and waxes (NC30H60). The reactivity of short chains is described through the comprehensive CRECK kinetic model, updated to align C5-C7 olefins based on recent literature experimental data. Due to the lack of experimental data for longer olefins, their reactivity is modeled by analogy to the shorter ones, ensuring an asymptotic behavior with increasing carbon numbers. The semi-detailed model is validated through experimental data on PE pyrolysis, assuming an instantaneous mixing of the inert inlet flow with released volatiles, followed by a segregated plug-flow behavior. Validation across different reactor setups confirms the model’s capability to predict detailed product distributions. Despite minor discrepancies, the proposed model effectively captures experimental trends. Further work will address modelling the reactivity in oxygen-containing environments.

kinetics↗
DOE OSTI2016

West African monsoon decadal variability and surface-related forcings: second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II)

The Sahel climate system had experienced one of the strongest interdecadal climate variabilities and the longest drought on the planet in the twentieth century. Most modeling studies on the decadal variability of the Sahel climate so far have focused on the role of anomalies in either sea surface temperature (SST), land surface processes, or aerosols concentration. The Second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II) is designed to improve understanding of the possible roles and feedback of SST, land use land cover change (LULCC), and aerosols forcings in the Sahel climate system at seasonal to decadal scales. The WAMME II strategy is to apply observationally based anomaly forcing, i.e., “idealized but realistic” forcing, in simulations by general circulation models’ (GCMs) and regional climate models’ (RCMs) to test the relative impacts of such forcings in producing/amplifying the Sahelian seasonal and decadal climate variability, including the 20th century drought. To test individual ocean’s SST effect, a special approach in the experimental design is taken to avoid undermine its effect. This is the first multi-model experiment specifically designed to simultaneously evaluate relative contributions of multiple-external forcings to the Sahel drought. This paper presents the major results and preliminary findings of the WAMME II SST experiment, including each ocean’s contribution to the global SST effect, as well as comparison of the SST effect with the LULCC effect. The common empirical orthogonal functions and other analyses are applied to assess and comprehend the discrepancies among the models. In general, the WAMME II models have reached a consensus on SST’s major contribution to the great Sahel drought and show that with the maximum possible SST forcing, it can produce up to 60% of the absolute amount of precipitation difference between the 1980s and the 1950s. This paper has 3 also delineated the role of SSTs in triggering and maintaining the Sahel drought, suggesting a potential predictability of WAM development linked to SST. Among different ocean basins, the Pacific and Indian Ocean SSTs have the greatest impact on the 1980s drought. The WAMME II, however, fails to reach a consensus on the role of the Mediterranean Sea SST. The changes in circulation, moisture flux convergence, and associated surface energy balances are the main mechanisms for the SST effect. The paper also compares the SST effect with the LULCC effects. It is shown that the prescribed land forcing produces about 40% of the precipitation difference between the 1980s and the 1950s, which is less than SST contribution but still of first order in the Sahel climate system. The role of land surface processes in responding to and amplifying the drought has also been identified. The results demonstrate that catastrophic consequences likely occur in the regional climate when SST anomalies in individual ocean basins and in land conditions combine synergistically to favor drought. Due to limited ensemble members, aerosol effects are not compared. Since the SST and land forcing in the real world are likely smaller than specified in this study, further investigations on the effects of aerosols as well as of other external forcings, such as greenhouse gases, and of atmospheric internal variability, are necessary. Moreover, although the WAMEE II models support a general consensus on SST and LULCC effects, there are still large discrepancies in how these models produce the Sahel drought in the 1980s. Better atmospheric observational and analysis data including more processes and components are necessary to validate and constrain models, and to guide further model development and improvement.

Xue, Yongkang (ORCID:0000000261699631)↗
DOE OSTI2014

L-shell dielectronic satellite transitions of Fe XVII

We have used the relativistic multi-reference Møller-Plesset perturbation theory to calculate the positions of the dielectronic satellite transitions involving doubly excited 3ℓ3ℓ' configurations that are associated with the X-ray spectrum of Fe XVII. A comparison of these positions with the wavelengths employed in astrophysical modeling codes shows discrepancies of up to 36 mÅ. Inspection of the spectrum of Capella recorded with the high energy transmission grating on the Chandra X-Ray Observatory reveals several features enhanced by Fe XVI lines formed by dielectronic recombination, one of which may be of future diagnostic use as it is fairly well isolated and in large part formed by dielectronic recombination.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Implications of a Pervasive Climate Model Bias for Low‐Cloud Feedback

Abstract How low clouds respond to warming constitutes a key uncertainty for climate projections. Here we observationally constrain low‐cloud feedback through a controlling factor analysis based on ridge regression. We find a moderately positive global low‐cloud feedback (0.45 W , 90% range 0.18–0.72 W ), about twice the mean value (0.22 W ) of 16 models from the Coupled Model Intercomparison Project. We link this discrepancy to a pervasive model mean‐state bias: models underestimate the low‐cloud response to warming because (a) they systematically underestimate present‐day tropical marine low‐cloud amount, and (b) the low‐cloud sensitivity to warming is proportional to this present‐day low‐cloud amount. Our results hence highlight the importance of reducing model biases in both the mean state of clouds and their sensitivity to environmental factors for accurate climate change projections.

58 GEOSCIENCES↗
DOE OSTI2019

Opacity: A window into High Energy Density Plasma Physics

Opacity is a fundamental property of matter and knowledge of it is required to understand the transport of radiation through a material. Exact knowledge of opacity is crucial in many fields such as astrophysics, which recently produced a white paper on the current state of astrophysical opacities [1], plasma physics, including inertial confinement fusion (ICF) and magnetic confinement fusion, high energy density physics (HEDP), the semiconductor industry [2] and stockpile stewardship. In industry, the accurate knowledge of the opacity of tin is important for extreme ultraviolet (EUV) lithography and the development of processors with smaller components. In astrophysics, Cepheid variable stars are used as “standard candles” for determining the distance to objects. Opacities of these stars are required to understand the relationship between their periodicity, luminosity and distance. Our sun is the most studied star and provides the basis of our understanding for other stars. Yet in significant ways the sun is poorly understood. In recent years, there has been a debate over the abundances of heavy elements (Z > 2) in the solar interior. Current solar atmosphere models [3] find a significantly lower abundance for C, N, and O compared to models used roughly a decade ago. Although solar evolution models have matured, a discrepancy still exists between spectroscopic solar models (which require opacities) with updated abundances, and solar properties inferred from helioseismology and neutrinos [4]. Despite its necessity, opacity is not solved, and is an open and active area of research needed for improving our understanding of plasma physics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Bayesian Model Calibration for Extrapolative Prediction via Gibbs Posteriors

The current standard Bayesian approach to model calibration, which assigns a Gaussian process prior to the discrepancy term, often suffers from issues of unidentifiability and computational complexity and instability. When the goal is to quantify uncertainty in physical parameters for extrapolative prediction, then there is no need to perform inference on the discrepancy term. With this in mind, we introduce Gibbs posteriors as an alternative Bayesian method for model calibration, which updates the prior with a loss function connecting the data to the parameter. The target of inference is the physical parameter value which minimizes the expected loss. We propose to tune the loss scale of the Gibbs posterior to maintain nominal frequentist coverage under assumptions of the form of model discrepancy, and present a bootstrap implementation for approximating coverage rates. Our approach is highly modular, allowing an analyst to easily encode a wide variety of such assumptions. Furthermore, we provide a principled method of combining posteriors calculated from data subsets. We apply our methods to data from an experiment measuring the material properties of tantalum.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Comparison and Limitations of DVH-Based NTCP Models Derived From 3D-CRT and IMRT Data for Prediction of Gastrointestinal Toxicities in Prostate Cancer Patients by Using Propensity Score Matched Pair Analysis

Purpose: This study compared normal tissue complication probability (NTCP) modeling of chronic gastrointestinal toxicities following prostate cancer treatment for 2 treatment modalities. Possible factors causing discrepancies in optimal NTCP model parameters between 3-dimensional conformal radiation therapy (3D-CRT) and intensity modulated RT (IMRT) were analyzed and discussed, including the impact of patient characteristics, image guidance, toxicity scoring bias, and NTCP model limitations. Methods and Materials: Rectal wall dose-volume histograms of 1115 patients treated for prostate cancer under an adaptive radiation therapy protocol were used to model gastrointestinal toxicity grade ≥2 (according to Common Terminology Criteria for Adverse Events). A total of 457 patients were treated with 3D-CRT and 658 with IMRT. 3D-CRT patients were matched to IMRT patients based on various patient characteristics, using a propensity score–based algorithm. Parameters of the Lyman equivalent uniform dose and cut-off dose logistic regression NTCP models were estimated for the 2 matched treatment modalities and the combined group. Results: After they were matched, the 3D-CRT and IMRT groups contained 275 and 550 patients with a large discrepancy of 28.7% versus 7.8% toxicities, respectively (P<.001). For both NTCP models, optimal parameters found for the 3D-CRT groups did not fit the IMRT patients well and vice versa. Models developed for the combined data overestimated NTCP for the IMRT patients and underestimated NTCP for the 3D-CRT group. Conclusions: Our analysis did not reveal a single definitive cause for discrepancies of model parameters between 3D-CRT and IMRT. Patient characteristics and bias in toxicity scoring, as well as image guidance alone, are unlikely causes of the large discrepancy of toxicities. Whether the cause was inherent to the specific NTCP models used in this study needs to be verified by future investigations. Because IMRT is increasingly used clinically, it is important that appropriate NTCP model parameters are determined for this treatment modality.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

COMPARISON OF EXPERIMENTS TO CFD MODELS FOR MIXING USING DUAL OPPOSING JETS IN TANKS WITH AND WITHOUT INTERNAL OBSTRUCTIONS

This paper documents testing methods, statistical data analysis, and a comparison of experimental results to CFD models for blending of fluids, which were blended using a single pump designed with dual opposing nozzles in an eight foot diameter tank. Overall, this research presents new findings in the field of mixing research. Specifically, blending processes were clearly shown to have random, chaotic effects, where possible causal factors such as turbulence, pump fluctuations, and eddies required future evaluation. CFD models were shown to provide reasonable estimates for the average blending times, but large variations -- or scatter -- occurred for blending times during similar tests. Using this experimental blending time data, the chaotic nature of blending was demonstrated and the variability of blending times with respect to average blending times were shown to increase with system complexity. Prior to this research, the variation in blending times caused discrepancies between CFD models and experiments. This research addressed this discrepancy, and determined statistical correction factors that can be applied to CFD models, and thereby quantified techniques to permit the application of CFD models to complex systems, such as blending. These blending time correction factors for CFD models are comparable to safety factors used in structural design, and compensate variability that cannot be theoretically calculated. To determine these correction factors, research was performed to investigate blending, using a pump with dual opposing jets which re-circulate fluids in the tank to promote blending when fluids are added to the tank. In all, eighty-five tests were performed both in a tank without internal obstructions and a tank with vertical obstructions similar to a tube bank in a heat exchanger. These obstructions provided scale models of vertical cooling coils below the liquid surface for a full scale, liquid radioactive waste storage tank. Also, different jet diameters and different horizontal orientations of the jets were investigated with respect to blending. Two types of blending tests were performed. The first set of eighty-one tests blended small quantities of tracer fluids into solution. Data from these tests were statistically evaluated to determine blending times for the addition of tracer solution to tanks, and blending times were successfully compared to Computational Fluid Dynamics (CFD) models. The second set of four tests blended bulk quantities of solutions of different density and viscosity. For example, in one test a quarter tank of water was added to a three quarters of a tank of a more viscous salt solution. In this case, the blending process was noted to significantly change due to stratification of fluids, and blending times increased substantially. However, CFD models for stratification and the variability of blending times for different density fluids was not pursued, and further research is recommended in the area of blending bulk quantities of fluids. All in all, testing showed that CFD models can be effectively applied if statistically validated through experimental testing, but in the absence of experimental validation CFD model scan be extremely misleading as a basis for design and operation decisions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

THE ORIGIN OF THE HOT GAS IN THE GALACTIC HALO: TESTING GALACTIC FOUNTAIN MODELS' X-RAY EMISSION

We test the X-ray emission predictions of galactic fountain models against XMM-Newton measurements of the emission from the Milky Way's hot halo. These measurements are from 110 sight lines, spanning the full range of Galactic longitudes. We find that a magnetohydrodynamical simulation of a supernova-driven interstellar medium, which features a flow of hot gas from the disk to the halo, reproduces the temperature but significantly underpredicts the 0.5-2.0 keV surface brightness of the halo (by two orders of magnitude, if we compare the median predicted and observed values). This is true for versions of the model with and without an interstellar magnetic field. We consider different reasons for the discrepancy between the model predictions and the observations. We find that taking into account overionization in cooled halo plasma, which could in principle boost the predicted X-ray emission, is unlikely in practice to bring the predictions in line with the observations. We also find that including thermal conduction, which would tend to increase the surface brightnesses of interfaces between hot and cold gas, would not overcome the surface brightness shortfall. However, charge exchange emission from such interfaces, not included in the current model, may be significant. The faintness of the model may also be due to the lack of cosmic ray driving, meaning that the model may underestimate the amount of material transported from the disk to the halo. In addition, an extended hot halo of accreted material may be important, by supplying hot electrons that could boost the emission of the material driven out from the disk. Additional model predictions are needed to test the relative importance of these processes in explaining the observed halo emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Predicting the performance of radiant technologies in attics: Reducing the discrepancies between attic specific and whole-building energy models

The use of radiant technology in attics aims to reduce the radiation component of heat transfer between the attic floor and roof decks, gables, and eaves. Recently, it has been shown that EnergyPlus underestimates the savings using radiant technologies in attic spaces. The aim of this study is to understand why EnergyPlus underestimates the performance of radiant technologies and provide a solution strategy that works within the current capabilities of EnergyPlus. The analysis uses three attic energy models as a baseline for comparison for EnergyPlus. Potential reasons for the discrepancies between the attic specific energy models and EnergyPlus are isolated and individually tested. A solution strategy is proposed using the Energy Management System (EMS) capabilities within EnergyPlus. This solution strategy produces similar results to the other attic specific energy models. This paper shows that the current capabilities of EnergyPlus are sufficient to simulate radiant technologies in attics. The methodology showcased in this paper serves as a guide for engineers and researchers who would like to predict the performance radiant technology in attics using the whole building energy software, EnergyPlus.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments

With more than a hundred elements in the periodic table, a large number of potential new materials exist to address the technological and societal challenges we face today; however, without some guidance, searching through this vast combinatorial space is frustratingly slow and expensive, especially for materials strongly influenced by processing. We train a machine learning (ML) model on previously reported observations, parameters from physiochemical theories, and make it synthesis method–dependent to guide high-throughput (HiTp) experiments to find a new system of metallic glasses in the Co-V-Zr ternary. Experimental observations are in good agreement with the predictions of the model, but there are quantitative discrepancies in the precise compositions predicted. We use these discrepancies to retrain the ML model. The refined model has significantly improved accuracy not only for the Co-V-Zr system but also across all other available validation data. We then use the refined model to guide the discovery of metallic glasses in two additional previously unreported ternaries. Although our approach of iterative use of ML and HiTp experiments has guided us to rapid discovery of three new glass-forming systems, it has also provided us with a quantitatively accurate, synthesis method–sensitive predictor for metallic glasses that improves performance with use and thus promises to greatly accelerate discovery of many new metallic glasses. We believe that this discovery paradigm is applicable to a wider range of materials and should prove equally powerful for other materials and properties that are synthesis path–dependent and that current physiochemical theories find challenging to predict.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bayesian calibration of irradiated graphite property models under high temperatures

Graphite under high temperatures and irradiation is central to advanced reactors. We develop a Bayesian calibration framework for graphite property models that explicitly represents model-data mismatch via a Gaussian-process discrepancy. The approach propagates uncertainty from parameters, experimental noise, and model form, with a hierarchical variance structure to capture group and cross-group noise. Using two predictive models across five grades (IG-110, NBG-18, PCEA, NBG-17, 2114) and four properties-irradiation-induced dimension change, creep, Young’s modulus change ratio, and coefficient of thermal expansion change ratio-we obtain average predictive-error reductions of 54%, 65%, 17%, and 17% when discrepancy is included. We illustrate engineering impact with a multiphysics model of a very-high-temperature reactor prismatic reflector brick, analyzing stresses under high fluence and temperature. Accounting for model discrepancy markedly improves predictive accuracy and provides a robust basis for reliable graphite component design in advanced reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2017

Twenty-First-Century Changes in U.S. Regional Heavy Precipitation Frequency Based on Resolved Atmospheric Patterns

Precipitation-gauge observations and atmospheric reanalysis are combined to develop an analogue method for detecting heavy precipitation events based on prevailing large-scale atmospheric conditions. Combinations of atmospheric variables for circulation (geopotential height and wind vector) and moisture (surface specific humidity, column and up to 500-hPa precipitable water) are examined to construct analogue schemes for the winter [December–February (DJF)] of the “Pacific Coast California” (PCCA) region and the summer [June–August (JJA)] of the Midwestern United States (MWST). The detection diagnostics of analogue schemes are calibrated with 1979–2005 and validated with 2006–14 NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA). All analogue schemes are found to significantly improve upon MERRA precipitation in characterizing the occurrence and interannual variations of observed heavy precipitation events in the MWST. When evaluated with the late twentieth-century climate model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5), all analogue schemes produce model medians of heavy precipitation frequency that are more consistent with observations and have smaller intermodel discrepancies than model-based precipitation. Under the representative concentration pathways (RCP) 4.5 and 8.5 scenarios, the CMIP5-based analogue schemes produce trends in heavy precipitation occurrence through the twenty-first century that are consistent with model-based precipitation, but with smaller intermodel disparity. The median trends in heavy precipitation frequency are positive for DJF over PCCA but are slightly negative for JJA over MWST. Overall, the analyses highlight the potential of the analogue as a powerful diagnostic tool for model deficiencies and its complementarity to an evaluation of heavy precipitation frequency based on model precipitation alone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

MEC modeling

2p-2h interactions are crucial for describing ν-Ar scattering, especially in the "dip region" between the Quasi-Elastic (QE) peak and Δ-resonance production. They involve the ejection of two nucleons, leading to two holes in the nuclear ground state. The underlying nuclear dynamics involve short-range correlations (SRC), long-range correlations (Random Phase Approximation, RPA), and the interplay of one- and two-body currents. Several models attempt to describe 2p-2h interactions like Valencia and SuSAv2-MEC. Despite progress, discrepancies exist between models and with data. I Will give an overview of 2p2h from the perspective of two Models Valencia and SuSAv2-MEC. I will introduce my current work to apply reweighting from SuSAv2 to Valencia on argon which will help improving the systematic uncertainty on MEC for SBN and DUNE.

Hassinin, Karim [Houston U.] (ORCID:00090009778353↗
DOE OSTI2022

Experimental and modeling studies of the plasma chemistry in a humid Ar radiofrequency atmospheric pressure plasma jet

Abstract While humid atmospheric pressure plasmas are extensively modeled, reaction set validation for these conditions remains limited. We present a detailed comparison of a modelling and experimental study with a goal to elucidate the plasma chemistry in a humid Ar radiofrequency-driven atmospheric pressure plasma jet. A large group of species including radicals (H, OH, O, HO 2 ) and long-lived species (H 2 , O 2 and H 2 O 2 ) in the jet effluent was experimentally quantified by molecular beam mass spectroscopy (MBMS). MBMS measurements of H 2 O 2 , OH and H were validated by direct comparison with a liquid phase colorimetric measurement, laser-induced fluorescence (LIF) and two-photon absorption LIF respectively. While an excellent agreement was found for OH and H 2 O 2 by both techniques, a significant difference was found for H and shown to be due to boundary layer effects at the MBMS sampling substrate. The measured O, OH, HO 2 and H 2 are in good agreement with the plug model while H and O 2 were underestimated and H 2 O 2 was overestimated by the model. The accuracy of both the used reaction set and the diagnostics, as well as the observed discrepancies between the modeling and experimental results, are critically assessed. The results presented in this work enable us to identify further data needs for describing H 2 O vapor chemistry in low-temperature plasmas.

Physics↗
DOE OSTI2021

Experimental Validation of Subsystem Models for a Novel Variable Displacement Hydraulic Motor

A novel, variable displacement, low-speed high-torque hydraulic motor is being developed that is expected to be highly efficient across a broad operating range. To ensure the final hardware achieves the expected performance, the models used in the development of the motor must be experimentally validated and revised, as necessary. The specific focus in this work is on mechanical energy loss models that were used to guide the design of a single-cylinder motor prototype and on experimental tests used for model validation. Ideally each model, whether friction loss in a piston/cylinder interface or energy loss due to leakage in a valve , would be individually validated by an independent test. This granular approach would remove any question of where the error lies and result in highly accurate models. However, many motor components have multiple forms of energy loss, creating difficulty in validating individual losses. Additionally, it is not physically realizable to divide many components into an individual model equivalent test. Testing the motor as a full assembly is possible, but pinpointing the source of discrepancies between the model and the hardware becomes difficult with dozens of models potentially being partially responsible. A compromise was found by separating the motor into functional component groups that are characterized by the type of loss and ability to test each subcomponent independently. By checking for correlation between test observations and model predictions, revisions could be implemented into the models. This allows future solutions to be more accurately predicted in the design phase to drive the design of better machines.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Measurement of nuclear interaction cross sections towards neutron-skin thickness determination

The accuracy of reaction theories used to extract properties of exotic nuclei from scattering experiments is often unknown or not quantified, but of utmost importance when, e.g., constraining the equation of state of asymmetric nuclear matter from observables as the neutron-skin thickness. In order to test the Glauber multiple-scattering model, the total interaction cross section of 12 C on carbon targets was measured at initial beam energies of 400, 550, 650, 800, and 1000 MeV/nucleon. The measurements were performed during the first experiment of the newly constructed R 3 B (Reaction with Relativistic Radioactive Beams) experiment after the start of FAIR Phase-0 at the GSI/FAIR facility with beam energies of 400, 550, 650, 800, and 1000 MeV/nucleon. The combination of the large-acceptance dipole magnet GLAD and a newly designed and highly efficient Time-of-Flight detector enabled a precise transmission measurement with several target thicknesses for each initial beam energy with an experimental uncertainty of ±0.4%. A comparison with the Glauber model revealed a discrepancy of around 3.1% at higher beam energies, which will serve as a crucial baseline for the model-dependent uncertainty in future fragmentation experiments.

Astronomy & Astrophysics↗