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At least 1,279 records · Page 71

Improving air leakage prediction of buildings using the fan pressurization method with the Weighted Line of Organic Correlation

In many countries, the fan pressurization method is the most frequently chosen approach for measuring the air leakage of houses. The measurements are usually performed at pressures that far exceed pressures to which buildings are exposed to under normal conditions. A fit of these tests to the power-law formulation allows an extrapolation to data points outside the measured pressure range. With the Ordinary Least Square (OLS) fitting method, the pressure exponent and flow coefficient can be determined. However, the measurement results are highly sensitive to uncertainties induced by external factors like changing wind conditions during the tests, which is neglected by OLS. This may lead to errors in the prediction of flows at lower pressures. The Weighted Line of Organic Correlation (WLOC) is an alternative approach and takes measurement uncertainty into account. In this paper, a statistical analysis of an extensive data set of pressurization measurements has been performed. Both regression techniques have been compared for almost 7500 fan pressurization measurements of six houses in 109 different house leak configurations. The variability in predicting pressure exponent and flow coefficient for both WLOC and OLS regression was analyzed using probability density functions. It was found that the Weighted Line of Organic Correlation significantly decreases the uncertainty in predicting pressure exponent, flow coefficient, and other low-pressure air leakage metrics compared to the Ordinary Least Square fitting. Here, the authors highly recommend the implementation of WLOC in current measurement standards and test equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Influence of clay mineral weathering on green rust formation at iron-reducing conditions

Green rusts (GR) are important drivers for trace metal and nutrient cycling in suboxic environments. We investigated whether green rusts would incorporate aluminum (Al) or other elements from naturally-formed clay minerals containing easily-weatherable clay minerals (e.g. mica, interlayered clays). We isolated the clay minerals from a Matapeake silt loam soil by removal of silt and sand, organic matter, and reducible oxides to study mechanisms of interaction between Fe(II) and soil-sourced clay minerals. We conducted batch Fe(II) sorption experiments at multiple near-neutral pHs (6.5–7.5) and reaction times (2h–365 days). Mineral transformations were characterized by selective extractions, X-ray diffraction (XRD), and Fe X-ray absorption spectroscopy (XAS) analyzed by shell-fitting and linear combination fitting (LCF) with natural and synthetic standards. Clay mineral fraction contained a mixture of quartz, kaolinite, interlayered vermiculite, mica, and chlorite with significant structural Fe (2.6% wt). Uptake of Fe(II) increased with pH and kinetics were rapid until 5 days, followed by slow continuous Fe(II) uptake. Citrate-bicarbonate desorption kinetics from Fe(II) sorbed clay released more Al and silicon (Si) compared with unreacted soil clay fraction whereas magnesium (Mg) and potassium (K) were unaffected. Citrate-bicarbonate extracted Fe contained more Fe(II) than an ideal GR with an Fe(II)/Fe(III) molar ratio of 5.50. Analysis of the Fe EXAFS by both LCF and shell fitting was best modeled as a combination of Fe(III)-clay reduction to Fe(II) and precipitation of GR and Fe(II)-Al LDH. After 7 days of Fe(II) sorption, LCF identified 55.2% total Fe in clay, 33.4% GR(Cl) and 11.4% Fe(II)-Al LDH. Further, these results provide novel evidence of Fe(II)-Al LDHs precipitating on naturally-formed soil clay minerals as a minor phase to GR. The geochemical implications are that GRs formed in soils and sediments should be considered to have Al and Si as well as Mg substitutions affecting their structure and reactivity.

58 GEOSCIENCES↗

DIGS: deep inference of galaxy spectra with neural posterior estimation

Abstract With the advent of billion-galaxy surveys with complex data, the need of the hour is to efficiently model galaxy spectral energy distributions (SEDs) with robust uncertainty quantification. The combination of simulation-based inference (SBI) and amortized neural posterior estimation (NPE) has been successfully used to analyse simulated and real galaxy photometry both precisely and efficiently. In this work, we utilise this combination and build on existing literature to analyse simulated noisy galaxy spectra. Here, we demonstrate a proof-of-concept study of spectra that is (a) an efficient analysis of galaxy SEDs and inference of galaxy parameters with physically interpretable uncertainties; and (b) amortized calculations of posterior distributions of said galaxy parameters at the modest cost of a few galaxy fits with Markov chain Monte Carlo (MCMC) methods. We utilise the SED generator and inference framework Prospector to generate simulated spectra, and train a dataset of 2 × 10 6 spectra (corresponding to a five-parameter SED model) with NPE. We show that SBI—with its combination of fast and amortized posterior estimations—is capable of inferring accurate galaxy stellar masses and metallicities. Our uncertainty constraints are comparable to or moderately weaker than traditional inverse-modelling with Bayesian MCMC methods (e.g. 0.17 and 0.26 dex in stellar mass and metallicity for a given galaxy, respectively). We also find that our inference framework conducts rapid SED inference (0.9–1.2 × 10 5 galaxy spectra via SBI/NPE at the cost of 1 MCMC-based fit). With this work, we set the stage for further work that focuses of SED fitting of galaxy spectra with SBI, in the era of JWST galaxy survey programs and the wide-field Roman Space Telescope spectroscopic surveys.

spectroscopy↗

Development of high pressure gas systems

This paper presents a report on the latest advances and technology in the design, construction, testing, and operation of high pressure gas bimetallic pipe systems and high pressure gas tube fittings facilitating greater alinement and manufacturing tolerances, and the supercleaning of high pressure gas systems under field conditions. The following specific topics are discussed: - Analysis of noncorrosive steels versus bimetallic, high strength steels - Analysis of various protective finishes versus bimetallic piping - Testing of high pressure systems - Pipe liner adhesion properties under varying operating conditions - Modified flared tube fittings taking into account pressure ranges, materials, costs involved in manufacture, various methods employed to permit sealing of the fitting while meeting cleanliness requirements - Cleaning requirements appertaining to high pressure gas systems and a discussion of investigations on the effects of velocity and temperature as related to various cleaning chemicals. The presentation concludes with a discussion on the possible applications of materials and methods in commercial industry.

Fitting↗

A two-year program of aerobics and weight training enhances bone mineral density of young women

Previous research suggests that physical activity may have a beneficial effect on bone mineral density (BMD) in women. This relationship was explored in a 2-year, randomized, intervention trial investigating the efficacy of exercise and calcium supplementation on increasing peak bone mass in young women. One hundred and twenty-seven subjects (ages of 20-35 years) were randomly assigned either to an exercise program that contained both aerobics and weight training components or to a stretching program. Calcium supplementation (up to 1500 mg/day including dietary intake) or placebo was given in a double-blinded design to all subjects. Spinal trabecular BMD was determined using quantitative computed tomography (QCT). Spinal integral, femoral neck, and trochanteric BMD were measured by dual X-ray absorptiometry (DXA) and calcaneal BMD by single photon absorptiometry (SPA). Fitness variables included maximal aerobic capacity (VO2max), and isokinetic muscle performance of the trunk and thigh. Measurements were made at baseline, 1 year, and 2 years. Sixty-three subjects (32 exercise, 31 stretching) completed the study, and all the measured bone parameters indicated a positive influence of the exercise intervention. There were significant positive differences in BMD between the exercise and stretching groups for spinal trabecular (2.5%), femoral neck (2.4%), femoral trochanteric (2.3%), and calcaneal (6.4%) measurements. The exercise group demonstrated a significant gain in BMD for spinal integral (1.3 +/- 2.8%, p < 0.02), femoral trochanteric (2.6 +/- 6.1%, p < 0.05), and calcaneal (5.6 +/- 5.1, p < 0.01) measurements. In contrast to exercise, the calcium intervention had no positive effect on any of the bone parameters. In regard to fitness parameters, the exercise group completed the study with significant gains in VO2max and isokinetic (peak torque) values for the knee flexion and extension and trunk extension. This study indicates that over a 2-year period, a combined regimen of aerobics and weight training has beneficial effects on BMD and fitness parameters in young women. However, the addition of daily calcium supplementation does not add significant benefit to the intervention.

Randomized Controlled Trial↗

Wing Shape Sensing from Measured Strain

A new two-step theory is investigated for predicting the deflection and slope of an entire structure using strain measurements at discrete locations. In the first step, a measured strain is fitted using a piecewise least-squares curve fitting method together with the cubic spline technique. These fitted strains are integrated twice to obtain deflection data along the fibers. In the second step, computed deflection along the fibers are combined with a finite element model of the structure in order to interpolate and extrapolate the deflection and slope of the entire structure through the use of the System Equivalent Reduction and Expansion Process. The theory is first validated on a computational model, a cantilevered rectangular plate wing. The theory is then applied to test data from a cantilevered swept-plate wing model. Computed results are compared with finite element results, results using another strainbased method, and photogrammetry data. For the computational model under an aeroelastic load, maximum deflection errors in the fore and aft, lateral, and vertical directions are -3.2%, 0.28%, and 0.09%, respectively; and maximum slope errors in roll and pitch directions are 0.28% and -3.2%, respectively. For the experimental model, deflection results at the tip are shown to be accurate to within 3.8% of the photogrammetry data and are accurate to within 2.2% in most cases. In general, excellent matching between target and computed values are accomplished in this study. Future refinement of this theory will allow it to monitor the deflection and health of an entire aircraft in real time, allowing for aerodynamic load computation, active flexible motion control, and active induced drag reduction.

shape sensing↗

Mitigation of Silver Ion Loss from Solution by Polymer Coating of Metal Surfaces, Part IV

Ionic silver (Ag+) biocide is a leading candidate to provide residual microbial control in spacecraft potable water systems, but suffers from rapid concentration loss due to interactions with the metallic storage containers and tubing. One approach to resolve this problem is the coating of metal surfaces with an inert barrier film. In previous reports, we have described our investigations addressing Ag+ loss mitigation and adhesion performance of parylene barrier coatings on coupons of several metal alloys and 316Ltubing under static immersion. In such conditions, parylene-C and -AF4 coatings have shown excellent Ag+loss mitigation and mixed long-term adhesion performance, depending on parylene species and substrate surface chemistry/structure. In Part IV of this series, we report on our work to investigate the performance of parylene-C barrier coatings, under more challenging and realistic conditions, in order to evaluate potential suitability for use. The resilience and associated Ag+ loss with Parylene-C coating on½” (12.7 mm)316L tubing and fittings under medium-term immersion and repeated fitting dis/reassembly were investigated. Potential mechanical challenges to barrier coatings in spacecraft potable water systems were investigated, with two main focuses being identified: liquid flow/pressure cycling in tubing and cyclic operation of bellows in positive-expulsion storage tanks. Two corresponding testbeds for experimental characterization of coating performance were developed. In the Flow/Pressure Testbed System, Ag+ solution will be pumped through internally coated 316L tubing, with optional pressure cycling. In the Bellows Tank Testbed System, an internally coated edge-welded 316L bellows containing Ag+ solution will be cyclically extended and compressed, analogous to the operation of bellows tanks used for potable water storage and delivery on the International Space Station. The design and operation of these testbeds are described. Finally, the Ag+ adsorption and saturation behaviors of Kalrez and Viton, for potential use as seal materials in fittings and other connections, were characterized in limited experiments.

mitigation↗

Spin Waves and Magnetic Exchange Hamiltonian in CrSBr

Abstract CrSBr is an air‐stable two‐dimensional (2D) van der Waals semiconducting magnet with great technological promise, but its atomic‐scale magnetic interactions—crucial information for high‐frequency switching—are poorly understood. An experimental study is presented to determine the CrSBr magnetic exchange Hamiltonian and bulk magnon spectrum. The A ‐type antiferromagnetic order using single crystal neutron diffraction is confirmed here. The magnon dispersions are also measured using inelastic neutron scattering and rigorously fit the excitation modes to a spin wave model. The magnon spectrum is well described by an intra‐plane ferromagnetic Heisenberg exchange model with seven nearest in‐plane exchanges. This fitted exchange Hamiltonian enables theoretical predictions of CrSBr behavior: as one example, the fitted Hamiltonian is used to predict the presence of chiral magnon edge modes with a spin‐orbit enhanced CrSBr heterostructure.

2D materials↗

Effects of random forest modeling decisions on biogeochemical time series predictions

Abstract Random forests (RF) are an increasingly popular machine learning approach used to model biogeochemical processes in the Earth system. While RF models are robust to many assumptions that complicate deterministic models, there are several important parameterization decisions for appropriate use and optimal model fit. We explored the role that parameter decisions, including training/testing data splitting strategies, variable selection, and hyperparameters play on RF goodness‐of‐fit by constructing models using 1296 unique parameter combinations to predict concentrations of nitrate, a key nutrient for biogeochemical cycling in aquatic ecosystems. Models were built on long‐term, publicly available water quality and meteorology time series collected by the National Estuarine Research Reserve monitoring network for two contrasting ecosystems representing freshwater and brackish estuaries. We found that accounting for temporal dependence when splitting data into training and testing subsets was key for avoiding over‐estimation of model predictive power. In addition, variable selection, the ratio of training to testing data, and to a lesser degree, variables per split and number of trees, were significant parameters for optimizing RF goodness‐of‐fit. We also explored how model parameter decisions influenced interpretation of the relative importance of predictors to the model, and model predictor‐dependent variable relationships, with results suggesting that both data structure and model parameterization influence these factors. Because much of the current RF literature is written for the computational and statistical science communities, the primary goal of this study is to provide guidelines for aquatic scientists new to machine learning to apply RF techniques appropriately to aquatic biogeochemical datasets.

54 ENVIRONMENTAL SCIENCES↗

Multimodal, microspectroscopic speciation of legacy phosphorus in two US mid-Atlantic agricultural soils

To understand phosphorus (P) mobility in agricultural soils and its potential environmental risk, it is essential to directly measure solid phase P speciation. Often, bulk P K-edge X-ray absorption near edge structure (XANES) spectroscopy followed by linear combination fitting (LCF) is utilized to determine the solid P phases in soil. However, this method may limit results to only a few major phases. Additionally, XANES spectra for different P species may have very similar features, leading to an over- or underestimate of their contribution to LCF. Here, an improved P speciation by pairing multimodal microbeam-X-ray fluorescence (µ-XRF) mapping coupled with µ-XANES (microbeam-X-ray absorption near edge structure) analysis to directly speciate major and minor P phases on the micron scale is provided. We combined maps of both tender (P, sulfur, aluminum, and silicon) and hard energy (calcium, iron [Fe], and manganese) elements to evaluate the elemental co-locations with P. To better account for uncertainty assigning XANES peaks to individual compounds, a more quantitative fingerprinting by “spectral feature analysis” was completed. With this analysis, an R-factor is reported for the fit. These results were compared to traditional LCF. Pre-edge fitting results revealed the presence of a two-component pre-edge feature for phosphate adsorbed to ferrihydrite. Additionally, phytate co-precipitated with ferrihydrite (Phytate-Fe-Cop) had a pre-edge feature, indicating direct association with Fe. Lastly, a unique P species associated with manganese oxide was identified in the soil via multimodal mapping and µ-XANES. These results allow for better prediction of P dissolution and mobility.

36 MATERIALS SCIENCE↗

On the implications of positive W mass shift

We investigate the phenomenological implications of the recent W mass measurement by the CDF collaboration, which exhibits tension with the standard model (SM) electroweak fit. Performing the fit to the electroweak observables within the SM effective field theory, we find that the new physics that contributes either to the determination of the electroweak vacuum expectation value, or to the oblique parameters, can improve the agreement with data. The best description is obtained from a fit where flavor universality is not required in the new physics operators, with 2 to 3 σ indications for several nonzero Wilson coefficients. We point out that top partners with order TeV masses could lead to the observed shift in the W mass.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High pressure raman spectroscopy and X-ray diffraction of K2Ca(CO3)2 bütschliite: multiple pressure-induced phase transitions in a double carbonate

Abstract The crystal structure and bonding environment of K 2 Ca(CO 3 ) 2 bütschliite were probed under isothermal compression via Raman spectroscopy to 95 GPa and single crystal and powder X-ray diffraction to 12 and 68 GPa, respectively. A second order Birch-Murnaghan equation of state fit to the X-ray data yields a bulk modulus, $${K}_{0}=46.9$$ K 0 = 46.9 GPa with an imposed value of $${K}_{0}^{\prime}= 4$$ K 0 ′ = 4 for the ambient pressure phase. Compression of bütschliite is highly anisotropic, with contraction along the c -axis accounting for most of the volume change. Bütschliite undergoes a phase transition to a monoclinic C 2/ m structure at around 6 GPa, mirroring polymorphism within isostructural borates. A fit to the compression data of the monoclinic phase yields $${V}_{0}=322.2$$ V 0 = 322.2 Å 3 $$,$$ , $${K}_{0}=24.8$$ K 0 = 24.8 GPa and $${K}_{0}^{\prime}=4.0$$ K 0 ′ = 4.0 using a third order fit; the ability to access different compression mechanisms gives rise to a more compressible material than the low-pressure phase. In particular, compression of the C 2/ m phase involves interlayer displacement and twisting of the [CO 3 ] units, and an increase in coordination number of the K + ion. Three more phase transitions, at ~ 28, 34, and 37 GPa occur based on the Raman spectra and powder diffraction data: these give rise to new [CO 3 ] bonding environments within the structure.

36 MATERIALS SCIENCE↗

Epigenetic effects associated with salmonid supplementation and domestication

Abstract Several studies have demonstrated lower fitness of salmonids born and reared in a hatchery setting compared to those born in nature, yet broad-scale genome-wide genetic differences between hatchery-origin and natural-origin fish have remained largely undetected. Recent research efforts have focused on using epigenetic tools to explore the role of heritable changes outside of genetic variation in response to hatchery rearing. We synthesized the results from salmonid studies that have directly compared methylation differences between hatchery-origin and natural-origin fish. Overall, the majority of studies found substantial differences in methylation patterns and overlap in functional genomic regions between hatchery-origin and natural-origin fish which have been replicated in parallel across geographical locations. Epigenetic differences were consistently found in the sperm of hatchery-origin versus natural-origin fish along with evidence for maternal effects, providing a potential source of multigenerational transmission. While there were clear epigenetic differences in gametic lines between hatchery-origin and natural-origin fish, only a limited number explored the potential mechanisms explaining these differences. We outline opportunities for epigenetics to inform salmonid breeding and rearing practices and to mitigate for fitness differences between hatchery-origin and natural-origin fish. We then provide possible explanations and avenues of future epigenetics research in salmonid supplementation programs, including: 1) further exploration of the factors in early development shaping epigenetic differences, 2) understanding the functional genomic changes that are occurring in response to epigenetic changes, 3) elucidating the relationship between epigenetics, phenotypic variation, and fitness, and 4) determining heritability of epigenetic marks along with persistence of marks across generations.

Koch, Ilana J. (ORCID:0000000335943108)↗

Direct uranium enrichment assay in gaseous uranium hexafluoride with laser induced breakdown spectroscopy

A set of eleven U atomic emission lines, between 421.099 and 421.460 nm, were characterized for direct enrichment assay of gaseous UF 6 samples with laser induced breakdown spectroscopy (LIBS). Several iterative, multivariate nonlinear spectral-fitting algorithms were evaluated for their efficacies to extract the enrichment information from the measured LIBS spectra. Furthermore, wavelength-dependent weight factors, which take into consideration of the spectral-line position in the fitting model, the determined isotopic ratio, and the isotopic shift of the emission line, are essential for the spectral-fitting model to function adequately. The analytical accuracies and precision were typically within 0.5% in absolute [ 235 U/( 235 U + 238 U)] ratios.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Characterization of the atomic-level structure of γ-alumina and (111) Pt/γ-alumina interfaces

The atomic-level structure of platinum/γ-alumina interfaces is characterized in a model system of dense γ-alumina embedded with faceted Pt NPs produced by implantation of platinum ions into sapphire followed by thermal annealing in air at 800 °C. Aberration-corrected scanning transmission electron microscopy (STEM) was used to collect atomic-resolution images, which are compared to STEM image simulations of two experimentally-based bulk models of γ-alumina by Smrčok et al. and Zhou and Snyder. A density functional theory (DFT) based model of (111) interfaces with different chemical terminations (O, Al 1 , Al 2 ) of the γ-alumina developed by Oware Sarfo et al. is also compared to experimental STEM data from Pt/γ-alumina interfaces. Further, the Smrčok γ-alumina model provides a better fit than the Zhou structure to the bulk of the γ-alumina. The oxygen-terminated Oware Sarfo model best fits the experimental data and is a very good model close to the interface. However, the fit of the interface model to the experimental data is poorer beyond the third atomic layer in the γ-alumina. This is attributed to compromises required in the design of the model to limit the cell size and computational time for DFT calculations. Understanding the accuracy and limits of the structural models of γ-alumina and Pt/γ-alumina interfaces is important to further the understanding of the structure/property relationships in this system.

36 MATERIALS SCIENCE↗

Improved natural convection heat transfer correlations for reactor cavity cooling systems of high-temperature gas-cooled reactors: From computational fluid dynamics to Pronghorn

The Reactor Cavity Cooling System (RCCS) is a common reactor safety system in High Temperature Gas Cooled Reactors (HTGR) that removes heat from the Reactor Pressure Vessel (RPV) by radiation ($\sim 80\%$) and natural convection ($\sim 20\%$). For simulation of accident scenarios of HTGRs, intermediate fidelity and system codes models must be employed for limiting the models' execution time. While accurate quantification of the radiative heat transfer is available in these models, quantification of natural convection must rely on correlations of questionable accuracy for the Nusselt number. Commonly used correlations are based in experiments performed at low Rayleigh numbers and/or using isothermal walls in simplified geometries. Here, this work improves on the accuracy of natural convection heat transfer correlations in support for HTGR designs. These correlations include both local and average Nusselt numbers as a function of the global Rayleigh number, the local Rayleigh number, and the temperature profile at the hot wall of the RCCS. In the absence of dedicated experiments and the difficulty of performing high-fidelity simulations at realistic Rayleigh numbers, the data to fit the correlations are generated with Computational Fluid Dynamics (CFD) using Reynolds Averaged Navier-Stokes (RANS) models. First, a careful selection of the RANS turbulence model is performed by comparing the results obtained with different RANS turbulence models against high fidelity simulations of natural convection at $Ra \ 1 \times 10^{11}$ in a rectangular cavity. Next, the selected model is used to perform simulations of an HTGR cavity at different high Rayleigh numbers $\in [6.1 \times 10^{11},2.9 \times 10^{13}]$ to encompass several HTGR designs, assuming an isothermal RPV wall. The results obtained are used to fit a correlation for the average and space-varying Nusselt number as a function of the global and local Rayleigh numbers via a sparsity-promoting least-squares method. The selected RANS model is then used to perform simulations of a PBMR 400 HTGR cavity with the temperature profiles at the RPV wall obtained during a PLOFC transient. We use the results obtained to fit a temperature-dependent correction to the space-varying Nusselt number with the sparsity-promoting least-squares method. The results obtained in this work, enable system-level codes, such as Pronghorn, to perform higher-fidelity simulations of the heat exchange process in the RCCS while still maintaining a low computational cost.

42 ENGINEERING↗

A sensitivity analysis to predict the neutronics behavior of samples irradiated in the VTR rabbit system

We report a low-order neutronics model is developed to carry out hundreds of simulations efficiently and investigate the neutronics behavior of samples being irradiated in a test reactor setting under different geometrical constraints. The low-order model allowed for simulations that yield the expected neutronics behavior of any irradiated sample in any environment and allows for the calculation of highly accurate spatially averaged statistics and idealized spatial distributions in the neutron flux. Several benchmarks are performed to evaluate the performance and limitations of the low-order model revealing many important findings. The low-order model predicted the LHGR in the EBR-II driver fuel to within 2.34% by only simulating the fuel rod by itself, which served as a validation for the model. Sensitivity studies investigated 3% enriched UO 2 and U-10Zr being irradiated in the Versatile Test Reactor rabbit system. The analyses investigated a range of combinations of 15 radii and 5 heights for each sample in the rabbit system. Similar data sets are also provided for irradiations in the Advanced Test Reactor’s B-10 irradiation position, which is a thermal neutron spectrum environment. Generalized fits and fit coefficients are obtained for sample heating, reaction rate densities, and local multiplication rate characteristics, allowing the predictions of the neutronics behavior of the samples based on their geometrical constraints. The analyses and fits laid the groundwork for developing a user-end Multiphysics analysis framework to assist and accelerate irradiation experiment design and optimization.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Frhodo: A program for simulating chemical kinetic measurements and optimizing kinetic mechanisms

Chemical kinetic simulations are frequently used to extract kinetic and mechanistic information from experimental data by fitting simulations to the data. For simple systems of consecutive single channel reactions this is a relatively straightforward task. However, as the complexity of the system increases and particularly for systems involving competitive multi-channel reactions manually optimizing a mechanism to obtain the best fits to a range of experimental data quickly becomes a time-intensive and challenging process, especially when rate coefficients have pressure and temperature dependencies. There is considerable potential for exploiting automated optimization methods to rapidly screen reaction mechanisms and optimize the fit by adjusting rate coefficients within well-defined constraints. A new chemical kinetics simulation program, Frhodo, has been developed for this purpose. The program allows either manual simulation of individual experiments or fully automated optimization against a range of experimental data by adjusting user selected reactions within user defined constraints. Frhodo incorporates machine learning-based optimization routines that work by either minimizing standardized residuals or through Bayesian parameter estimation. Frhodo's optimization capabilities are demonstrated by reexamining two previously studied systems of relevance to combustion. Dissociation of diacetyl followed by recombination of methyl radicals is an example of a sequence of single channel, consecutive reactions. Pyrolysis of 2-methyl furan exemplifies multi-channel, unimolecular reactions that are often encountered and have temperature and pressure dependencies in the rate coefficients of the channels and branching ratios between them. For both systems the optimization routines resulted in solutions similar to the original studies. Finally, comments are made on the strengths and limitations of the approach.

0D simulation↗