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At least 91 records · Page 5

Comparison of image noise and image quality between full-dose abdominal computed tomography scans reconstructed with weighted filtered back projection and half-dose scans reconstructed with improved sinogram-affirmed iterative reconstruction (SAFIRE*)

Purpose: To retrospectively compare the image noise, signal-to-noise ratio (SNR), and subjective image quality between CT images acquired with a dual-source, split-dose imaging protocol reconstructed at full and half doses with weighted filtered back projection (wFBP) and an improved sinogram-affirmed iterative reconstruction algorithm (SAFIRE*). Methods: Fifty-three consecutive patients underwent contrast-enhanced CT of the abdomen using a standardized dual-source, single energy CT protocol. Half-dose images were retrospectively generated using data from one detector only. Full-dose datasets were reconstructed with wFBP, while half-dose datasets were reconstructed with wFBP and SAFIRE* strengths 1–5. Region of interest analysis was performed to assess SNR and noise. Diagnostic acceptability, subjective noise, and spatial resolution were graded on a 10-point scale by two readers. Statistical analysis was carried out with repeated measures analysis of variance, Wilcoxon signed rank test, and Cohen’s κ test. Results: With the increasing strengths of SAFIRE*, a progressive reduction in noise and increase in SNR (p < 0.01) was observed. There was a statistically significant decrease in objective noise and increase in SNR in half-dose SAFIRE* strength 4 and 5 reconstructions compared to full-dose reconstructions using wFBP (p < 0.01). Qualitative analysis revealed a progressive increase in diagnostic acceptability, decrease in subjective noise and increase in spatial resolution for half-dose images reconstructed with the increasing strengths of SAFIRE* (p < 0.01). Conclusions: Half-dose CT images reconstructed with SAFIRE* at strength 4 and 5 have superior image quality compared to full-dose images reconstructed with wFBP. SAFIRE* potentially allows dose reductions in the order of 50% over wFBP.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

On the reliability of microvariability tests in quasars

Microvariations probe the physics and internal structure of quasars. Unpredictability and small flux variations make this phenomenon elusive and difficult to detect. Variance-based probes such as the C and F tests, or a combination of both, are popular methods to compare the light curves of the quasar and a comparison star. Recently, detection claims in some studies have depended on the agreement of the results of the C and F tests, or of two instances of the F-test, for rejecting the non-variation null hypothesis. However, the C-test is a non-reliable statistical procedure, the F-test is not robust, and the combination of tests with concurrent results is anything but a straightforward methodology. A priori power analysis calculations and post hoc analysis of Monte Carlo simulations show excellent agreement for the analysis of variance test to detect microvariations as well as the limitations of the F-test. Additionally, the combined tests yield correlated probabilities that make the assessment of statistical significance unworkable. However, it is possible to include data from several field stars to enhance the power in a single F-test, increasing the reliability of the statistical analysis. This would be the preferred methodology when several comparison stars are available. An example using two stars and the enhanced F-test is presented. These results show the importance of using adequate methodologies and avoiding inappropriate procedures that can jeopardize microvariability detections. Power analysis and Monte Carlo simulations are useful tools for research planning, as they can demonstrate the robustness and reliability of different research approaches.

79 ASTRONOMY AND ASTROPHYSICS↗

Transient analysis of advancing contact angle measurements on polished rock surfaces

We report that contact angle measurements for gas-liquid-rock systems are important for modeling multi-phase flow and transport in the subsurface. These data are needed in applications such as the extraction of oil and gas resources, geologic sequestration of carbon dioxide, contaminant fate and transport, and aquifer recharge through the vadose zone. Contact angles are frequently measured with the sessile drop method. Previous research has largely ignored the dynamic behavior of sessile droplets on geologic materials. This study investigates the dynamic behavior of sessile water droplets on prepared rock surfaces in the presence of air. Droplet diameter and advancing contact angle were determined at 0.5 s intervals for ~90 s on flat polished disks of Burlington limestone, Crossville sandstone, Mancos shale, Sierra White granite, Vermilion Bay granite, and Westerly granite using a Krüss DSA 30 Drop Shape Analyzer. The droplet diameter and advancing contact angle data sets were nonlinearly regressed against time using two different two-parameter models. The median coefficients of determination for the fits were 0.85 and 0.96, respectively. The resulting parameter estimates were used to compute the apparent equilibrium contact angle, θ e , for each disk following droplet diameter stabilization. Estimates of θ e ranged from 37.2° for Mancos shale to 75.6° for Burlington limestone. Analysis of variance indicated statistically significant differences in θ e between the rock types at the 95% confidence level. The variability of θe on the polished rock surfaces, as quantified by the coefficient of variation (CV) for θ e , varied between ~3 and ~9%; there were no significant differences in CV between the rock types. Neutron radiography indicated changes droplet morphology over time were due to the spontaneous imbibition of water into the rock matrix. Finally, the transient analysis employed in this study permits a more meaningful estimate of the equilibrium contact angle for rocks than taking the initial value or averaging over time as is frequently done.

58 GEOSCIENCES↗

HopBox: An image analysis pipeline to characterize hop cone morphology

Abstract Hop cone morphology can influence picking and drying ability, and color can impact consumer preference and may be indicative of quality. However, these characteristics are not generally evaluated in hop breeding programs due to the tedious nature of trait quantification and the extensive variation among cones within a genotype. We developed the HopBox, which is a simply constructed light box with a camera mount, and a publicly available image processing pipeline that identifies hop cones within color‐corrected images, reads a QR code within the image, and outputs data on hop cone length, width, area, perimeter, openness, weight, color, and density. The trained model was applied to images of 500 cones each from 15 replicated advanced hop genotypes from the USDA‐ARS breeding program in Prosser, Washington. Analysis of variance revealed significant ( p < 0.001) differences between genotypes for all traits measured, enabling breeders to discriminate between genotypes for selection purposes. Broad sense heritability for all traits ranged from 0.23 to 0.59. A random sampling of hop cones from the complete dataset revealed that imaging only 5–10 cones adequately captured genotypic variation and provided acceptable rank correlations ( r s > 0.75); however, increasing the sample size to 30 provided optimal precision. Instructions for constructing a HopBox and the code for the analysis pipeline are publicly available online and have wide applicability for hop breeding and research.

Altendorf, Kayla R.↗

Optimizing stadium evacuation by integrating geocomputation and affordance theory

Football is culturally and economically important in the United States, and football stadiums are part of the country's critical infrastructure, thus receiving government protection against hazard events. In this project, an agent-based evacuation model was implemented to optimize evacuation time from The University of Southern Mississippi's M.M. Roberts Stadium (football) by accounting for evacuees’ age, gender, physical fitness, alcohol consumption, and prior experience with hazard events. The findings revealed that (i) the age and gender of an individual impact his/her locomotion speed and (ii) evacuation route choice is influenced by evacuees’ perception of its safety and effectiveness. The estimated evacuation times for all evacuees to exit only the stadium and the stadium plus the surrounding campus were 20.82 and 165.01 minutes, respectively. Both of these times were shorter than the evacuation times determined by models employing location-unspecific locomotion speeds. One-way analysis of variance revealed that there were statistically significant differences between use of location-specific and location-unspecific within-stadium evacuation times (p ≤ 0.001 with α = 0.05). These results suggest that using local data is vital to accurately estimate evacuation time.

99 GENERAL AND MISCELLANEOUS↗

Comparison of Computed Tomography– and Magnetic Resonance Imaging–based Clinical Target Volume Contours at Brachytherapy for Cervical Cancer

Purpose: We prospectively compared computed tomography (CT)– and magnetic resonance imaging (MRI)–based high-risk clinical target volume (HR-CTV) contours at the time of brachytherapy for cervical cancer in an effort to identify patients who might benefit most from MRI-based planning. Methods and Materials: Thirty-seven patients who had undergone a pretreatment diagnostic MRI scan were included in the analysis. We delineated the HR-CTV on the brachytherapy CT and brachytherapy MRI scans independently for each patient. We then calculated the absolute volumes for each HR-CTV and the Dice coefficient of similarity (DC, a measure of spatial agreement) for the HR-CTV contours. We identified the clinical and tumor factors associated with (1) a discrepancy in volume between the CT HR-CTV and MRI HR-CTV contours; and (2) DC. The mean values were compared using 1-way analysis of variance or paired or unpaired t tests, as appropriate. Simple and multivariable linear regression analyses were used to model the effects of covariates on the outcomes. Results: Patients with International Federation of Gynecology and Obstetrics stage IB to IVA cervical cancer were treated with intracavitary brachytherapy using tandem and ovoid (n=33) or tandem and cylinder (n=4) applicators. The mean CT HR-CTV volume (44.1 cm{sup 3}) was larger than the mean MRI HR-CTV volume (35.1 cm{sup 3}; P<.0001, paired t test). On multivariable analysis, a higher body mass index (BMI) and tumor size ≥5 cm with parametrial invasion on the MRI scan at diagnosis were associated with an increased discrepancy in volume between the HR-CTV contours (P<.02 for both). In addition, the spatial agreement (as measured by DC) between the HR-CTV contours decreased with an increasing BMI (P=.013). Conclusions: We recommend MRI-based brachytherapy planning for patients with tumors >5 cm and parametrial invasion on MRI at diagnosis and for those with a high BMI.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Comparing gas composition from fast pyrolysis of live foliage measured in bench-scale and fire-scale experiments

Background: Fire models have used pyrolysis data from oxidising and non-oxidising environments for flaming combustion. In wildland fires pyrolysis, flaming and smouldering combustion typically occur in an oxidising environment (the atmosphere). Aims: Using compositional data analysis methods, determine if the composition of pyrolysis gases measured in non-oxidising and ambient (oxidising) atmospheric conditions were similar. Methods: Permanent gases and tars were measured in a fuel-rich (non-oxidising) environment in a flat flame burner (FFB). Permanent and light hydrocarbon gases were measured for the same fuels heated by a fire flame in ambient atmospheric conditions (oxidising environment). Log-ratio balances of the measured gases common to both environments (CO, CO 2 , CH 4 , H 2 , C 6 H 6 O (phenol), and other gases) were examined by principal components analysis (PCA), canonical discriminant analysis (CDA) and permutational multivariate analysis of variance (PERMANOVA). Key results: Mean composition changed between the non-oxidising and ambient atmosphere samples. PCA showed that flat flame burner (FFB) samples were tightly clustered and distinct from the ambient atmosphere samples. CDA found that the difference between environments was defined by the CO-CO 2 log-ratio balance. PERMANOVA and pairwise comparisons found FFB samples differed from the ambient atmosphere samples which did not differ from each other. Conclusion: Relative composition of these pyrolysis gases differed between the oxidising and non-oxidising environments. This comparison was one of the first comparisons made between bench-scale and field scale pyrolysis measurements using compositional data analysis. Implications: These results indicate the need for more fundamental research on the early time-dependent pyrolysis of vegetation in the presence of oxygen.

54 ENVIRONMENTAL SCIENCES↗

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach

In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle, knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. Thus when using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluating Composite Sampling Methods of Bacillus Spores at Low Concentrations

Restoring facility operations after the 2001 Amerithrax attacks took over three months to complete, highlighting the need to reduce remediation time. The most time intensive tasks were environmental sampling and sample analyses. Composite sampling allows disparate samples to be combined, with only a single analysis needed, making it a promising method to reduce response times. We developed a statistical experimental design to test three different composite sampling methods: 1) single medium single pass composite: a single cellulose sponge samples multiple coupons; 2) single medium multi-pass composite: a single cellulose sponge is used to sample multiple coupons; and 3) multi-medium post-sample composite: a single cellulose sponge samples a single surface, and then multiple sponges are combined during sample extraction. Five spore concentrations of Bacillus atrophaeus Nakamura spores were tested; concentrations ranged from 5 to 100 CFU/coupon (0.00775 to 0.155CFU/cm 2 , respectively). Study variables included four clean surface materials (stainless steel, vinyl tile, ceramic tile, and painted wallboard) and three grime coated/dirty materials (stainless steel, vinyl tile, and ceramic tile). Analysis of variance for the clean study showed two significant factors: composite method (p-value < 0.0001) and coupon material (p-value = 0.0008). Recovery efficiency (RE) was higher overall using the post-sample composite (PSC) method compared to single medium composite from both clean and grime coated materials. RE with the PSC method for concentrations tested (10 to 100 CFU/coupon) was similar for ceramic tile, painted wall board, and stainless steel for clean materials. RE was lowest for vinyl tile with both composite methods. Statistical tests for the dirty study showed RE was significantly higher for vinyl and stainless steel materials, but significantly lower for ceramic tile. These results suggest post-sample compositing can be used to reduce sample analysis time when responding to a Bacillus anthracis contamination event of clean or dirty surfaces.

59 BASIC BIOLOGICAL SCIENCES↗

STUDIES IN ASTRONOMICAL TIME SERIES ANALYSIS. VI. BAYESIAN BLOCK REPRESENTATIONS

This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it-an improved and generalized version of Bayesian Blocks-that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piecewise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by Arias-Castro et al. In the spirit of Reproducible Research all of the code and data necessary to reproduce all of the figures in this paper are included as supplementary material.

79 ASTRONOMY AND ASTROPHYSICS↗

Global Sensitivity Analysis of Large Distribution System with PVs using Deep Gaussian Process

Global sensitivity analysis (GSA) of the voltage to uncertain power injection variations plays an important role for appropriate Volt-VAR optimization. This paper proposes a data-driven GSA method for large-scale distribution systems with a large number of uncertain sources. Specifically, the deep Gaussian process is used to identify the mapping relationship between uncertain power injections and voltages. This allows us to resort to the analysis of variance framework to calculate the Sobol indices for GSA. Unlike the existing polynomial chaos expansion and Gaussian process-based approaches, our proposed method has much better scalability. Test results on the EPRI 1747-node K1 circuit with a different number and different probability distributions of uncertain sources demonstrate that the proposed method can achieve accurate GSA under various conditions.

14 SOLAR ENERGY↗

SU-F-J-102: Lower Esophagus Margin Implications Based On Rapid Computational Algorithm for SBRT

Purpose: To quantify inter-fraction esophagus-variation. Methods: Computed tomography and daily on-treatment 0.3-T MRI data sets for 7 patients were analyzed using a novel Matlab-based (Mathworks, Natick, MA) rapid computational method. Rigid registration was performed from the cricoid to the gastro-esophageal junction. CT and MR-based contours were compared at slice intervals of 3mm. Variation was quantified by “expansion,” defined as additional length in any radial direction from CT contour to MR contour. Expansion computations were performed with 360° of freedom in each axial slice. We partitioned expansions into left anterior, right anterior, right posterior, and left posterior quadrants (LA, RA, RP, and LP, respectively). Sample means were compared by analysis of variance (ANOVA) and Fisher’s Protected Least Significant Difference test. Results: Fifteen fractions and 1121 axial slices from 7 patients undergoing SBRT for primary lung cancer (3) and metastatic lung disease (4) were analyzed, generating 41,970 measurements. Mean LA, RA, RP, and LP expansions were 4.30±0.05 mm, 3.71±0.05mm, 3.17±0.07, and 3.98±0.06mm, respectively. 50.13% of all axial slices showed variation > 5 mm in one or more directions. Variation was greatest in lower esophagus with mean LA, RA, RP, and LP expansion (5.98±0.09 mm, 4.59±0.09 mm, 4.04±0.16 mm, and 5.41±0.16 mm, respectively). The difference was significant compared to mid and upper esophagus (p<.0001). The 95th percentiles of expansion for LA, RA, RP, LP were 13.36 mm, 9.97 mm, 11.29 mm, and 12.19 mm, respectively. Conclusion: Analysis of on-treatment MR imaging of the lower esophagus during thoracic SBRT suggests margin expansions of 13.36 mm LA, 9.97 mm RA, 11.29 mm RP, 12.19 mm LP would account for 95% of measurements. Our novel algorithm for rapid assessment of margin expansion for critical structures with 360° of freedom in each axial slice enables continuously adaptive patient-specific margins which may reduce overlap with high-dose regions.

60 APPLIED LIFE SCIENCES↗

An Analysis of Future Wind Energy Resources and Cost Uncertainties Across the United States

Wind power is a growing source of energy generation that relies on complex global atmospheric and earth system processes. There has been evidence of reductions in average wind speeds over land in North America since the 1980s, and several models project that average wind speeds will continue to decrease. Concurrently, the cost of wind energy systems in the United States has been decreasing since around 2010, a trend also projected to continue. There is considerable uncertainty in these future projections, with quantitative estimates of future wind resource and system costs varying widely. To study this, we run wind energy models with possible future system costs, turbine designs, and meteorological inputs from multiple downscaled earth system models over the contiguous United States. Changes in mean annual energy production from 2000-2019 to 2040-2059 can be as high as +10% in South Texas or as low as -20% in Iowa. Larger turbines and moderate reductions in system costs can offset the largest projected decreases in wind resource, but much uncertainty remains in the extent to which wind resources will change and to what extent system costs can be reduced. An analysis of variance shows, in several states in the Midwest, uncertainty in future wind resources can influence the cost of wind energy nearly as much as uncertainty in future system costs.

17 WIND ENERGY↗

Predicting the viscoplastic response of a crystallizing fluoropolymer using transient network theory

We employ a molecular theory of dynamic polymer networks to describe the viscoplastic response of rubbery FK-800, a thermoplastic copolymer of chlorotrifluoroethylene and vinylidene fluoride, over a broad range of thermal histories. The kinetics of crystallization at different annealing temperatures was modeled using a modified Avrami equation, whose parameters were found to evolve through simple relationships over the full temperature range of the rubbery state. By fitting experimental compression data, we discovered predictable trends for the physical parameters in our mechanical model over its full range of crystallinities (up to ≈20%) and provided insights based on molecular-level physics to justify them. Using this, an end-to-end model was developed to predict the yielding and post-yield behavior of rubbery FK-800 for arbitrary thermal histories. The model successfully predicted the highly nonlinear evolution of characteristic mechanical signatures (stiffness, yield point, post-yield drop) throughout the crystallization process. A statistical analysis of variance test was employed to determine that the measured variations in the mechanical behavior of rubbery FK-800 are primarily dictated by its fractional crystallinity, regardless of its exact thermal history.

36 MATERIALS SCIENCE↗

Combining simulations and data with deep learning and uncertainty quantification for advanced energy modeling

A novel and modern framework for energy modeling is developed in this paper with a focus on nuclear energy modeling and simulation. The framework combines multiphysics simulations and real data, with validation by uncertainty quantification tasks and facilitation by machine and deep learning methods. The hybrid framework is built on the basis of a wide range of physical models, real data, mathematical and statistical methods, and artificial intelligence techniques. The framework is demonstrated in different applications, including quantifying uncertainties in computer simulations, multiphysics coupling, analysis of variance using machine learning surrogate models, deep learning of time series phenomena, and propagating parametric uncertainties of nuclear data. The applications demonstrated are oriented to nuclear engineering simulations, even though majority of the methods are applicable to other energy sources (eg, renewable). Efficient utilization of this framework is expected to yield a much better understanding of the physical phenomena analyzed as well as an improvement in the performance of the energy design/model under construction.

42 ENGINEERING↗

Sequential experimental design based generalised ANOVA

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover, generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Can Angiotensin-Converting Enzyme Inhibitors Reduce the Incidence, Severity, and Duration of Radiation Proctitis?

Purpose: To determine whether participants taking angiotensin-converting enzyme inhibitors (ACEIs) and treated with radical radiation therapy with neoadjuvant/adjuvant hormone therapy have less incidence, severity, and duration of radiation proctitis. Methods and Materials: A propensity score analysis of 817 patients who underwent radical radiation therapy with neoadjuvant or adjuvant hormone therapy as primary line management in a cohort study during 2009 to 2013 was conducted. Patients were stratified as follows: group 1, hypertensive patients taking ACEIs (as a study group); group 2, nonhypertensive patients not taking ACEIs; and group 3, hypertensive patients not taking ACEIs (both as control groups). The incidence, severity, and duration of proctitis were the main outcome. χ{sup 2} tests, Mann-Whitney U tests, analysis of variance, risk ratio (RR), confidence interval (CI), Kaplan-Meier plots, and log-rank tests were used. Results: The mean age of the participants was 68.91 years, with a follow-up time of 3.38 years. Based on disease and age-matched comparison, there was a statistically significant difference of proctitis grading between the 3 groups: χ{sup 2} (8, n=308) = 72.52, P<.001. The Mann-Whitney U test indicated that grades of proctitis were significantly lower in hypertensive patients taking ACEIs than in nonhypertensive patients not taking ACEIs and hypertensive patients not taking ACEIs (P<.001). The risk ratio (RR) of proctitis in hypertensive patients taking ACEIs was significantly lower than in hypertensive patients not taking ACEIs (RR 0.40, 95% CI 0.30-0.53, P<.001) and in nonhypertensive patients not taking ACEIs (RR 0.58, 95% CI 0.44-0.77, P<.001). Time to event analysis revealed that hypertensive patients taking ACEIs were significantly different from the control groups (P<.0001). Furthermore, hypertensive patients taking ACEIs had significantly faster resolution of proctitis (P<.0001). Conclusion: Patients who were taking ACEIs were significantly less likely to have high-grade proctitis after radical radiation therapy with neoadjuvant or adjuvant hormone therapy (P<.001). The intake of ACEIs was significantly associated with a reduced risk of radiation-induced proctitis and also with acceleration of its resolution.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Optimizing aluminum oxide passivation layers—Laser-induced plasmas for layer formation, real-time diagnostics, and layer evaluation

Molten salts have beneficial thermophysical and electrolytic properties, but the aggressive nature of molten salts requires corrosion mitigation strategies, such as structural material surface treatment. In this study, a laser-induced breakdown spectroscopy (LIBS) system was used to simultaneously ablate and monitor de-excitation spectra to form and identify dense alumina passivation layers. Additionally, high-frequency (kHz) LIBS imaging allowed rapid elemental mapping and depth profiling for surface O/Al ratios via minimally destructive analysis. The paired t-test rejected the null hypothesis that air and Ar cover gases were equivalent (p = 0.00012), and the analysis of variance (ANOVA) showed that overlap between shots (p = 0.03112) and cover gas flow rate (p = 0.02729) were statistically significant. At 75% overlap, the O/Al ratio increased to 10% ± 2%, and 90% overlap rose further to 31% ± 2%. Regardless of overlap, tuning the gas flow from 0.5 to 2.5 L min −1 enhanced the O/Al ratio by 24% ± 4%. LIBS depth profiling showed a 3× increase in layer thickness from 75% to 90% overlap. Molecular band peaks of AlO, a precursor to Al 2 O 3 found during treatment, suggest that band intensity could be used for real-time Al 2 O 3 optimization. Ultimately, by adjusting laser spot overlap and cover gas flow rate, a 266 nm laser was shown to form Al 2 O 3 layers on an Al6061 sample, with cover gas flow rate primarily affecting the O/Al ratio and layer thickness correlating with laser spot overlap. This combination of molecular spectra collection, imaging, and depth profiling demonstrated the robust layer analysis capabilities of LIBS.

Corrosion↗