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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Identifying microturbulence regimes in a TCV discharge making use of physical constraints on particle and heat fluxes

Reducing the uncertainty on physical input parameters derived from experimental measurements is essential towards improving the reliability of gyrokinetic turbulence simulations. This can be achieved by introducing physical constraints. Amongst them, the zero particle flux condition is considered here. A first attempt is also made to match as well the experimental ion/electron heat flux ratio. This procedure is applied to the analysis of a particular Tokamak à Configuration Variable discharge. A detailed reconstruction of the zero particle flux hyper-surface in the multi-dimensional physical parameter space at fixed time of the discharge is presented, including the effect of carbon as the main impurity. Both collisionless and collisional regimes are considered. Hyper-surface points within the experimental error bars are found. In conclusion, the analysis is done performing gyrokinetic simulations with the local version of the GENE code, computing the fluxes with a Quasi-Linear (QL) model and validating the QL results with non-linear simulations in a subset of cases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Cosmology intertwined: A review of the particle physics, astrophysics, and cosmology associated with the cosmological tensions and anomalies

The standard Λ Cold Dark Matter (ΛCDM) cosmological model provides a good description of a wide range of astrophysical and cosmological data. However, there are a few big open questions that make the standard model look like an approximation to a more realistic scenario yet to be found. In this paper, we list a few important goals that need to be addressed in the next decade, taking into account the current discordances between the different cosmological probes, such as the disagreement in the value of the Hubble constant H 0 , the σ 8 – S 8 tension, and other less statistically significant anomalies. While these discordances can still be in part the result of systematic errors, their persistence after several years of accurate analysis strongly hints at cracks in the standard cosmological scenario and the necessity for new physics or generalisations beyond the standard model. In this paper, we focus on the 5.0 σ tension between the Planck CMB estimate of the Hubble constant H 0 and the SH0ES collaboration measurements. After showing the H 0 evaluations made from different teams using different methods and geometric calibrations, we list a few interesting new physics models that could alleviate this tension and discuss how the next decade's experiments will be crucial. Moreover, we focus on the tension of the Planck CMB data with weak lensing measurements and redshift surveys, about the value of the matter energy density Ω m , and the amplitude or rate of the growth of structure ( σ 8 , f σ 8 ). We list a few interesting models proposed for alleviating this tension, and we discuss the importance of trying to fit a full array of data with a single model and not just one parameter at a time. Additionally, we present a wide range of other less discussed anomalies at a statistical significance level lower than the H 0 – S 8 tensions which may also constitute hints towards new physics, and we discuss possible generic theoretical approaches that can collectively explain the non-standard nature of these signals. Finally, we give an overview of upgraded experiments and next-generation space missions and facilities on Earth that will be of crucial importance to address all these open questions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Use of Uncertainty in Modeling DFLAW Treatment at Hanford - 17115

Average or mean is understood by most; standard deviation (SD) is understood by few. Certainty is easy to model; uncertainty is not. The flowsheet simulation, described in this paper, placed uncertainties in the G2 model of the Hanford Tank Waste Treatment and Immobilization Plant's (WTP) Direct Feed Low-Activity Waste (DFLAW) process for performance and sensitivity evaluations. G2 is a dynamic material balance model that starts and proceeds with operating logic until all the feed is processed. Dynamic material balance is achieved by tracking the flows, storage, and change of all materials within the plant as time increments. Processing equipment and limitations of the flowsheet are modeled (e.g., equipment types, piping, volumes, flowrates, efficiencies, and physical and chemical environments that impact separations, phase equilibriums, and chemical reactions). Operating logic represents the rules and strategies of a running plant. The G2 model simulated both certainty and uncertainty scenarios for comparison purposes. For the uncertainty scenarios, process decisions were made using presumed values to simulate various operational measurement errors and process variabilities. Presumed means that the known G2 values are adjusted to replicate measurement errors and variabilities. These include: 1) volume measurement, 2) sample analysis, 3) melter decontamination factor (DF), 4) glass former weighing, and 5) glass former composition variations. The errors were randomly generated in accordance with SD values of measurement devices, laboratory methods, and glass former composition ranges. The G2 model runs give insight on the DFLAW process' controllability and the expected range of glass properties. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Analysis of solid uranium particulates on cotton swipes with an automated microextraction-ICP-MS system

Here, an automated microextraction method coupled to an inductively coupled plasma – mass spectrometer (ICP-MS) was developed for the direct analysis of solid uranium particulates on the surface of cotton swipes. The microextraction probe extracts particulates from the sample surface, in a flowing solvent, and directs the removed analyte to an ICP-MS for isotopic determination. The automated system utilizes a mechanical XY stage that is software controlled with the capability of saving and returning to specific locations and a camera focused to the swipe surface for optimal viewing of the extracted locations (i.e., material present). Here, particulates (n = 135) were extracted and measured by ICP-MS, including 35 depleted uranyl nitrate hexahydrate (UN) (used for mass bias corrections), 50 uranyl fluoride (UO 2 F 2 ), and 50 uranyl acetate (UAc) particulates. Blank extractions were performed on the cotton swipes between triplicate sample analyses. Between each swipe extraction, the probe was sent between two wells containing 10% and 5% HNO 3 to clean the probe head and to eliminate any analyte carryover between particulates. The measured 235 U/ 238 U and 234 U/ 238 U isotope ratios for the UO 2 F 2 particulates were 0.00725(8) and 0.000054(4), a percent relative difference (% RD) of –0.041% and –1.7% from the reference isotope ratios determined in-lab through multi-collector ICP-MS analysis of dissolved aliquots of the U material. The UAc samples had a measured 235 U/ 238 U isotope ratio of 0.00206(7), a –0.96% relative difference from the reference value of 0.00208(1). The 234 U/ 238 U and 236 U/ 238 U isotope ratios were 0.000008(1) and 0.000031(4), –5.1% RD and –4.3% RD, respectively. The automated sample stage enabled seamless and rapid particle analysis, leading to a significant increase in throughput versus what was previously possible. Additionally, the saved location capability reduced user sampling error as sampling locations were easily stored and recalled. Analysis of U particles on the swipe surface – including blanks, mass bias, and triplicate extractions – was completed in less than an hour without any sample preparation necessary.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

Groundtruthing Next-Gen Sequencing for Microbial Ecology–Biases and Errors in Community Structure Estimates from PCR Amplicon Pyrosequencing

Analysis of microbial communities by high-throughput pyrosequencing of SSU rRNA gene PCR amplicons has transformed microbial ecology research and led to the observation that many communities contain a diverse assortment of rare taxa–a phenomenon termed the Rare Biosphere. Multiple studies have investigated the effect of pyrosequencing read quality on operational taxonomic unit (OTU) richness for contrived communities, yet there is limited information on the fidelity of community structure estimates obtained through this approach. Given that PCR biases are widely recognized, and further unknown biases may arise from the sequencing process itself, a priori assumptions about the neutrality of the data generation process are at best unvalidated. Furthermore, post-sequencing quality control algorithms have not been explicitly evaluated for the accuracy of recovered representative sequences and its impact on downstream analyses, reducing useful discussion on pyrosequencing reads to their diversity and abundances. Here we report on community structures and sequences recovered for in vitro-simulated communities consisting of twenty 16S rRNA gene clones tiered at known proportions. PCR amplicon libraries of the V3–V4 and V6 hypervariable regions from the in vitro-simulated communities were sequenced using the Roche 454 GS FLX Titanium platform. Commonly used quality control protocols resulted in the formation of OTUs with >1% abundance composed entirely of erroneous sequences, while over-aggressive clustering approaches obfuscated real, expected OTUs. The pyrosequencing process itself did not appear to impose significant biases on overall community structure estimates, although the detection limit for rare taxa may be affected by PCR amplicon size and quality control approach employed. Meanwhile, PCR biases associated with the initial amplicon generation may impose greater distortions in the observed community structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Spatial frequency spectrum of the x-ray scatter distribution in CBCT projections

Purpose: X-ray scatter is a source of significant image quality loss in cone-beam computed tomography (CBCT). The use of Monte Carlo (MC) simulations separating primary and scattered photons has allowed the structure and nature of the scatter distribution in CBCT to become better elucidated. This work seeks to quantify the structure and determine a suitable basis function for the scatter distribution by examining its spectral components using Fourier analysis.Methods: The scatter distribution projection data were simulated using a CBCT MC model based on the EGSnrc code. CBCT projection data, with separated primary and scatter signal, were generated for a 30.6 cm diameter water cylinder [single angle projection with varying axis-to-detector distance (ADD) and bowtie filters] and two anthropomorphic phantoms (head and pelvis, 360 projections sampled every 1°, with and without a compensator). The Fourier transform of the resulting scatter distributions was computed and analyzed both qualitatively and quantitatively. A novel metric called the scatter frequency width (SFW) is introduced to determine the scatter distribution's frequency content. The frequency content results are used to determine a set basis functions, consisting of low-frequency sine and cosine functions, to fit and denoise the scatter distribution generated from MC simulations using a reduced number of photons and projections. The signal recovery is implemented using Fourier filtering (low-pass Butterworth filter) and interpolation. Estimates of the scatter distribution are used to correct and reconstruct simulated projections.Results: The spatial and angular frequencies are contained within a maximum frequency of 0.1 cm{sup −1} and 7/(2π) rad{sup −1} for the imaging scenarios examined, with these values varying depending on the object and imaging setup (e.g., ADD and compensator). These data indicate spatial and angular sampling every 5 cm and π/7 rad (∼25°) can be used to properly capture the scatter distribution, with reduced sampling possible depending on the imaging scenario. Using a low-pass Butterworth filter, tuned with the SFW values, to denoise the scatter projection data generated from MC simulations using 10{sup 6} photons resulted in an error reduction of greater than 85% for the estimating scatter in single and multiple projections. Analysis showed that the use of a compensator helped reduce the error in estimating the scatter distribution from limited photon simulations by more than 37% when compared to the case without a compensator for the head and pelvis phantoms. Reconstructions of simulated head phantom projections corrected by the filtered and interpolated scatter estimates showed improvements in overall image quality.Conclusions: The spatial frequency content of the scatter distribution in CBCT is found to be contained within the low frequency domain. The frequency content is modulated both by object and imaging parameters (ADD and compensator). The low-frequency nature of the scatter distribution allows for a limited set of sine and cosine basis functions to be used to accurately represent the scatter signal in the presence of noise and reduced data sampling decreasing MC based scatter estimation time. Compensator induced modulation of the scatter distribution reduces the frequency content and improves the fitting results.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-T-261: Plan Quality Assurance of VMAT Using Fluence Images Reconstituted From Log-Files

Purpose: A successful VMAT plan delivery includes precise modulations of dose rate, gantry rotational and multi-leaf collimator (MLC) shapes. One of the main problem in the plan quality assurance is dosimetric errors associated with leaf-positional errors are difficult to analyze because they vary with MU delivered and leaf number. In this study, we calculated integrated fluence error image (IFEI) from log-files and evaluated plan quality in the area of all and individual MLC leaves scanned. Methods: The log-file reported the expected and actual position for inner 20 MLC leaves and the dose fraction every 0.25 seconds during prostate VMAT on Elekta Synergy. These data were imported to in-house software that developed to calculate expected and actual fluence images from the difference of opposing leaf trajectories and dose fraction at each time. The IFEI was obtained by adding all of the absolute value of the difference between expected and actual fluence images corresponding. Results: In the area all MLC leaves scanned in the IFEI, the average and root mean square (rms) were 2.5 and 3.6 MU, the area of errors below 10, 5 and 3 MU were 98.5, 86.7 and 68.1 %, the 95 % of area was covered with less than error of 7.1 MU. In the area individual MLC leaves scanned in the IFEI, the average and rms value were 2.1 – 3.0 and 3.1 – 4.0 MU, the area of errors below 10, 5 and 3 MU were 97.6 – 99.5, 81.7 – 89.5 and 51.2 – 72.8 %, the 95 % of area was covered with less than error of 6.6 – 8.2 MU. Conclusion: The analysis of the IFEI reconstituted from log-file was provided detailed information about the delivery in the area of all and individual MLC leaves scanned.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Analysis of DESI × DES using the Lagrangian effective theory of LSS

In this work we use Lagrangian perturbation theory to analyze the harmonic space galaxy clustering signal of the Bright Galaxy Survey (BGS) and luminous red galaxies (LRGs) targeted by the dark energy spectroscopic instrument (DESI), combined with the galaxy-galaxy lensing signal measured around these galaxies using Dark Energy Survey Year 3 source galaxies. The BGS and LRG galaxies are extremely well characterized by DESI spectroscopy and, as a result, lens galaxy redshift uncertainty and photometric systematics contribute negligibly to the error budget of our “2 × 2-point” analysis. On the modeling side, this work represents the first application of the SPINOSAURUS code, implementing an effective field theory model for galaxy intrinsic alignments, and we additionally introduce a new scheme ( MAIAR ) for marginalizing over the large uncertainties in the redshift evolution of the intrinsic alignment signal. Furthermore, this is the first application of a hybrid effective field theory model for galaxy bias based on the A emulus 𝜈 simulations. Our main result is a measurement of the amplitude of the lensing signal, 𝑆 8 = 𝜎 8 ⁢(Ω 𝑚 /0.3) 0.5 = 0.85⁢0$^{+0.042}_{−0.050}$, consistent with values of this parameter derived from the primary cosmic microwave background. This constraint is artificially improved by a factor of 51% if we assume a more standard, but restrictive parametrization for the redshift evolution and sample dependence of the intrinsic alignment signal, and 63% if we additionally assume the nonlinear alignment model. Furthermore, we show that when fixing the cosmological model to the best-fit values from Planck PR4 there is > 5⁢𝜎 evidence for a deviation of the evolution of the intrinsic alignment signal from the functional form that is usually assumed in cosmic shear and galaxy-galaxy lensing studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

High order interpolation of magnetic fields with vector potential reconstruction for particle simulations

We propose a method for interpolating divergence-free continuous magnetic fields via vector potential reconstruction using Hermite interpolation, which ensures high-order continuity for applications requiring adaptive, high-order ordinary differential equation (ODE) integrators, such as the Dormand-Prince method. The method provides C(m) continuity and achieves high-order accuracy, making it particularly suited for particle trajectory integration and Poincaré section analysis under optimal integration order and timestep adjustments. Through numerical experiments, we demonstrate that the Hermite interpolation method preserves volume and continuity, which are critical for conserving toroidal canonical momentum and magnetic moment in guiding center simulations, especially over long-term trajectory integration. Furthermore, we analyze the impact of insufficient derivative continuity on Runge-Kutta schemes and show how it degrades accuracy at low error tolerances, introducing discontinuity-induced truncation errors. Lastly, we demonstrate performant Poincaré section analysis in two relevant settings of field data collocated from finite element meshes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Testing the dipole modulation model in CMBR

The hemispherical power asymmetry, observed in the CMBR data, has generally been interpreted in terms of the dipole modulation model for the temperature fluctuations. Here we point out that this model leads to several predictions, which can be directly tested in the current data. We suggest tests of the hemispherical power asymmetry both in real and multipole space. We find a significant signal of the dipole modulation model in WMAP and PLANCK data with our tests. The dipole amplitude and direction also agrees, within errors, with earlier results based on hemispherical analysis in multipole space. We also find evidence that the effective dipole modulation amplitude increases with the multipole l in the range l = 2−64.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

CAUSES: On the Role of Surface Energy Budget Errors to the Warm Surface Air Temperature Error Over the Central United States

Many weather forecasting and climate models simulate a warm surface air temperature (T2m) bias over mid-latitude continents during the summertime, especially over the Great Plains. We present here one of a series of papers from a multi-model intercomparison project (CAUSES: Cloud Above the United States and Errors at the Surface), which aims to evaluate the role of cloud, radiation, and precipitation biases in contributing to T2m bias using a short-term hindcast approach with observations mainly from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site during the period of April to August 2011. The present study examines the contribution of surface energy budget errors to the bias. All participating models simulate higher net shortwave and longwave radiative fluxes at the surface but there is no consistency on signs of biases in latent and sensible heat fluxes over the Central U.S. and ARM SGP. Nevertheless, biases in net shortwave and downward longwave fluxes, as well as surface evaporative fraction (EF) are the main contributors to T2m bias. Radiation biases are largely affected by cloud simulations, while EF is affected by soil moisture modulated by seasonal accumulated precipitation and evaporation. An approximate equation is derived to further quantify the magnitudes of radiation and EF contributions to T2m bias. Our analysis suggests that radiation errors are always an important source of T2m error for long-term climate runs with EF errors either of equal or lesser importance. However, for the short-term hindcasts, EF errors are more important provided a model has a substantial EF bias.

Ma, H. -Y.↗
DOE OSTI2017

Measured extent of agricultural expansion depends on analysis technique

Concern is rising that ecologically important, carbon-rich natural lands in the United States are losing ground to agriculture. We investigate how quantitative assessments of historical land use change to address this concern differ in their conclusions depending on the data set used. We examined land use change between 2006 and 2014 in 20 counties in the Prairie Pothole Region using the Cropland Data Layer, a modified Cropland Data Layer, data from the National Agricultural Imagery Program, and in-person ground-truthing. The Cropland Data Layer analyses overwhelmingly returned the largest amount of land use change with associated error that limits drawing conclusions from it. Analysis with visual imagery estimated a fraction of this land use change. Clearly, analysis technique drives understanding of the measured extent of land use change; different techniques produce vastly different results that would inform land management policy in strikingly different ways. As a result, best practice guidelines are needed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Optimizing group structures using hierarchical division

Creating group structures with few groups that give low errors is a difficult problem in reactor analysis. In recent years, automated optimization techniques have been applied to this task. We continue this trend by applying the hierarchical division algorithm to generate optimized group structures that minimize a cost function. At each stage, the algorithm adds a single group boundary to an existing group structure, dividing one group into two to increase the resolution of the group structure. The location of the added boundary is the one that gives the lowest error over all possible new boundary locations. Our implementation requires a beginning group structure, a set of candidate new boundary locations, and a set of reference reaction rates. As a proof of concept, we used WIMS-69 as the initial group structure, XMAS-172 as the ending group structures, and a 344-group reference group structure. Testing on two simple, homogenized reactor problems, we found that hierarchical division was able to reduce the error by a factor of around 5 with an increase of only 15% in the number of groups. Because hierarchical division can get stuck in local minima, it often reaches a plateau in its error reduction capability as many groups are added. Nevertheless, we find hierarchical division has strong potential to make good group structures into great group structures at a modest increase in computational cost. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Challenges in leveraging existing human performance data for quantifying the IDHEAS HRA method

Our article documents an exploratory study for collecting and using human performance data to inform human error probability (HEP) estimates for a new human reliability analysis (HRA) method, the IntegrateD Human Event Analysis System (IDHEAS). The method was based on cognitive models and mechanisms underlying human behaviour and employs a framework of 14 crew failure modes (CFMs) to represent human failures typical for human performance in nuclear power plant (NPP) internal, at-power events [1]. A decision tree (DT) was constructed for each CFM to assess the probability of the CFM occurring in different contexts. Data needs for IDHEAS quantification are discussed. Then, the data collection framework and process is described and how the collected data were used to inform HEP estimation is illustrated with two examples. Next, five major technical challenges are identified for leveraging human performance data for IDHEAS quantification. Furthermore, these challenges reflect the data needs specific to IDHEAS. More importantly, they also represent the general issues with current human performance data and can provide insight for a path forward to support HRA data collection, use, and exchange for HRA method development, implementation, and validation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Microsegregation Measurement: Methods and Applications

Microsegregation is chemical variation at the microstructural level in a solidified ingot, which can cause undesirable effects on material properties. Its formation is driven by different levels of solute elemental solubility between solid and liquid phases, resulting in solute buildup or depletion in the liquid phase during solidification. Characterization of microsegregation can be essential for understanding its formation and removing it through heat treatment. Measurement is frequently carried out via scanning electron microscope (SEM), though metallographic analysis, mechanical testing and optical radiography have been used. SEM analysis can consist of point measurements on single dendrites, line scans across or along dendrites, elemental maps, and extended line-based or grid-based analyses extending over many dendrites, which can generate large amounts of data. Line-based or grid-based data can be analyzed using scatterplots of element concentrations to visualize segregation behavior and sorting/ranking of data by a single element or a combination of elements, to give compositional profiles as a function of extent of solidification. For both qualitative and quantitative analyses, effects of phase transformations and secondary phases need to be considered as well as sorting of measurement errors when generating compositional profiles. Applications of analysis include determination of partition ratios, examination of solute–element interactions, determination of effects of cooling rate and back diffusion, applications to freckling studies, validations of modeling, and development of heat-treatment profiles.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Extended Forward Sensitivity Analysis for Uncertainty Quantification

Verification and validation (V&V) are playing more important roles to quantify uncertainties and realize high fidelity simulations in engineering system analyses, such as transients happened in a complex nuclear reactor system. Traditional V&V in the reactor system analysis focused more on the validation part or did not differentiate verification and validation. The traditional approach to uncertainty quantification is based on a 'black box' approach. The simulation tool is treated as an unknown signal generator, a distribution of inputs according to assumed probability density functions is sent in and the distribution of the outputs is measured and correlated back to the original input distribution. The 'black box' method mixes numerical errors with all other uncertainties. It is also not efficient to perform sensitivity analysis. Contrary to the 'black box' method, a more efficient sensitivity approach can take advantage of intimate knowledge of the simulation code. In these types of approaches equations for the propagation of uncertainty are constructed and the sensitivities are directly solved for as variables in the simulation. This paper presents the forward sensitivity analysis as a method to help uncertainty qualification. By including time step and potentially spatial step as special sensitivity parameters, the forward sensitivity method is extended as one method to quantify numerical errors. Note that by integrating local truncation errors over the whole system through the forward sensitivity analysis process, the generated time step and spatial step sensitivity information reflect global numerical errors. The discretization errors can be systematically compared against uncertainties due to other physical parameters. This extension makes the forward sensitivity method a much more powerful tool to help uncertainty qualification. By knowing the relative sensitivity of time and space steps with other interested physical parameters, the simulation is allowed to run at optimized time and space steps without affecting the confidence of the physical parameter sensitivity results. The time and space steps forward sensitivity analysis method can also replace the traditional time step and grid convergence study with much less computational cost. Several well defined benchmark problems with manufactured solutions are utilized to demonstrate the extended forward sensitivity analysis method. All the physical solutions, parameter sensitivity solutions, even the time step sensitivity in one case, have analytical forms, which allows the verification to be performed in the strictest sense.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

HUBBLE PARAMETER MEASUREMENT CONSTRAINTS ON DARK ENERGY

We use 21 Hubble parameter versus redshift data points from Simon et al., Gaztanaga et al., Stern et al., and Moresco et al. to place constraints on model parameters of constant and time-evolving dark energy cosmologies. The inclusion of the eight new measurements results in H(z) constraints more restrictive than those derived by Chen and Ratra. These constraints are now almost as restrictive as those that follow from current Type Ia supernova (SNIa) apparent magnitude versus redshift data, which now more carefully account for systematic uncertainties. This is a remarkable result. We emphasize, however, that SNIa data have been studied for a longer time than the H(z) data, possibly resulting in a better estimate of potential systematic errors in the SNIa case. A joint analysis of the H(z), baryon acoustic oscillation peak length scale, and SNIa data favors a spatially flat cosmological model currently dominated by a time-independent cosmological constant but does not exclude slowly evolving dark energy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A Markov chain Monte Carlo (MCMC) Bayesian inference approach to analyze apparent activation barriers and reaction orders from microreactor data

Statistical analysis of steady-state catalytic kinetic data is often limited by data sparsity due to the slow pace at which the data is collected. Data sparsity and limitations in statistical analysis make it difficult to differentiate between mechanistic models and catalytic sites. A Bayesian inference tool is reported for catalysis researchers to estimate error in the determination of reaction orders from steady state microreactor data. The benefits of a Bayesian inference approach are discussed, as an alternative to the more common frequentist approach. The approach incorporates prior knowledge of the system and the data collected to form an error estimate on reaction orders. We investigated the effects of three distinct data treatments—individual fitting of trials, pooled analysis, and constrained regression methods—on the precision and uncertainty of reaction order determinations. To assess the robustness of our findings, we conducted sensitivity analyses to evaluate the influence of Bayesian parameters on uncertainty estimation. Additionally, we utilized synthetic data to illustrate how data quality impacts the precision of uncertainty assessments. We show Bayesian analysis can obtain a more precise estimation of error with a sparse data set than a frequentist analysis. Finally, this work provides strong evidence that the adoption of Bayesian analysis of kinetic data may help researchers make more precise arguments as to the strength of their evidence for a particular mechanistic hypothesis, or in comparing across different catalysts.

42 ENGINEERING↗