Search NASA⌕ Search

SEARCH · Search NASA

Results for “sampling methods”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

A New Aerodynamic Data Dispersion Method for Launch Vehicle Design

A novel method for implementing aerodynamic data dispersion analysis is herein introduced. A general mathematical approach combined with physical modeling tailored to the aerodynamic quantity of interest enables the generation of more realistically relevant dispersed data and, in turn, more reasonable flight simulation results. The method simultaneously allows for the aerodynamic quantities and their derivatives to be dispersed given a set of non-arbitrary constraints, which stresses the controls model in more ways than with the traditional bias up or down of the nominal data within the uncertainty bounds. The adoption and implementation of this new method within the NASA Ares I Crew Launch Vehicle Project has resulted in significant increases in predicted roll control authority, and lowered the induced risks for flight test operations. One direct impact on launch vehicles is a reduced size for auxiliary control systems, and the possibility of an increased payload. This technique has the potential of being applied to problems in multiple areas where nominal data together with uncertainties are used to produce simulations using Monte Carlo type random sampling methods. It is recommended that a tailored physics-based dispersion model be delivered with any aerodynamic product that includes nominal data and uncertainties, in order to make flight simulations more realistic and allow for leaner spacecraft designs.

Pinier, Jeremy T.↗

Characterization of fault recovery through fault injection on FTMP

The development of fault-injection procedures and statistical analysis techniques to characterize the fault recovery of fault-tolerant systems is described. Pin-level fault-injection was conducted on a fault-tolerant microprocessor computer in order to generate data to assess the utility of current fault-injection sampling methods. The validity of common reliability-modeling assumptions concerning the statistical distribution of recovery times is investigated. A multiple comparison analysis for detecting behavior variations, and a distribution fitting for determining the best fit for the data were conducted. It is observed that the detection behavior is not homogeneous across all data sets, and that none of the factors under experimental control can account for the observed groupings of behavior. It is determined that no single distribution fits all the data sets, and that stratified random sampling and statistically robust parameter-estimation techniques are required to characterize fault detection time.

Finelli, George B.↗

Mineralogical Analysis of Calcium-Aluminum-Rich Inclusions Provides Insight Into Post-Formation Processes

Introduction: Calcium-aluminum inclusions (CAIs) are cm- to mm-sized intergrowths of refractory phases found in chondritic meteorites [1]. Their mineral compositions closely match the compositions of the solids thought to condense from an extremely hot (>1500K) gas with a bulk solar composition [2-4], suggesting that CAIs were the earliest solids within the Solar System [2-4]. These inclusions provide invaluable insights into the conditions and dynamics of the early Solar System. CAIs must be transported from their formation region near the protosun to the chondrite parent-body accretion region. The nature of their journey could affect how, when, and where the secondary processes recorded in these CAIs occurred [4]. Did these secondary processes occur in the solar nebula or during accretion with the parent body, or both? How were the CAIs affected by varying thermochemical processes? To better answer these questions, we have undertaken an in-depth, textural study of the secondary alteration of select CAI samples. Methods: We chose three CAIs that experienced a range of post-formation processing to gain better understanding of secondary alteration based on previous preliminary examination [5]. Representative CAIs were chosen from NWA 5508 (CV3), NWA 12772 (CV3), and Coolidge (CL4) carbonaceous chondrites. We used scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD) techniques for detailed chemical, mineralogical, and textural analysis of the CAIs. Backscattered electron (BSE) images and X-ray elemental maps were taken of Coolidge and NWA 5508 using the Lunar and Planetary Institute (LPI) Phenom SEM. The JEOL 7900F SEM at NASA Johnson Space Center (JSC) was used to obtain energy dispersive spectroscopy (EDS) chemical maps of all samples. High resolution EBSD analysis identified the mineral phases and textures, providing key information on their nature. Based on the SEM and EBSD data, minerals of interest were selected for quantitative chemical electron probe micro-analysis (EPMA) using the JEOL JXA-8530F at NASA JSC. Results and Discussion: The EDS maps show that the NWA 5508 and NWA 12772 CAIs designated “Saguaro” and “Hoopoe” respectively [5] are enriched in calcium while the Coolidge CAI designated “Cottonwood” is aluminum and magnesium rich. Saguaro. A ~1.5cm diameter igneous Type B CAI with a rounded shape. The dominant phases are melilite, spinel, and Al-Ti pyroxene with minor anorthite. Spinel is subhedral and occurs in clusters. Some of these clusters have a circular geometry which encloses other minerals, known as a palisade structure [6] (Fig. 1). Some palisades form near perfect circles while others are more irregular in shape. Melilite in Saguaro ranges in size from coarse (>250m) to fine-grained (5-7m) and forms intergrown laths. A third of the melilite grains exhibit simple twinning about their <001> axis. The spinel palisades and twinned melilite in Saguaro suggest an igneous history, and the lack of secondary minerals suggests minimal aqueous alteration. At some point in time after the initial condensation of the minerals and formation of the inclusion, the sample was remelted and quickly solidified. The formation of the palisades is still heavily debated. One hypothesis is that the palisades are the rims of smaller CAIs that accreted early on, essentially acting as xenoliths within the larger CAIs [7]. Another hypothesis suggests an igneous origin for palisade structures [6-8] wherein the melt traps gas bubbles, and the spinel nucleates on the surface of this bubble. Based on the WDS spot analyses of 41 melilite grains using EPMA, the data suggest that the composition inside and outside the palisades is nearly identical. This finding indicates that these palisades are likely not exogenous but rather formed from melt-vapor reactions. Our results are consistent with studies by Simon and Grossman,1997 [6] and Zhang et al. (2019) [8]. Hoopoe. A ~0.5cm compact Type A CAI with an irregular shape. The dominant mineral phases are melilite, spinel, and hibonite with minor amounts of anorthite, augite, and perovskite. The melilite ranges in size from ~500 to 50µm. The larger melilite grains have simple twinning along the <001> axis like melilite in Saguaro. Melilite in Hoopoe exhibits crystal-plastic strain with misorientation dominantly about the <010> and <110> axes. Spinel shows subhedral to euhedral morphology and appears in clusters. Hibonite grains are similar to spinel in habit and size but show more plastic strain. The two minerals are often found together with one appearing to replace the other. Perovskite appears in fine grained recrystallized regions alongside fine augite and spinel. The abundant strain and deformation features in the melilite and hibonite suggest that Hoopoe experienced shock. This shock could have occurred in the nebula [9] or from an impact of another body on the parent body asteroid. The appearance of fine-grained (<10m) areas of augite, perovskite, and spinel in the dominantly coarse-grained inclusion suggest recrystallization, possibly due to the sudden increase in pressure and temperature. Cottonwood. This ~0.5cm CAI exhibits distinct mineralogy and textures suggesting a high degree of alteration. It is irregular in shape. The dominant mineral phases are spinel and anorthite with minor amounts of augite and rutile. The two main texture types can be seen in Fig. 2. The first type consists of coarse euhedral to subhedral spinel and anorthite. The second includes fine grained spinel, anorthite, rutile, and iron sulfides. Within these fine-grained regions, the anorthite grains are clustered into domains exhibiting the same crystallographic orientation. Rutile exclusively occurs with fine anorthite indicating a potential relationship between the two. Cottonwood has a clear and unbroken Wark-Lovering [10] rim (Fig. 2) on one side that consists of a sequence of spinel followed by anorthite and an outer layer of augite. The abundance of the fine-grained regions containing iron oxides and iron sulfides, secondary phases such as rutile, and oriented anorthite grains is evidence for recrystallization associated with a high degree of thermal metamorphism. The EPMA analyses on both coarse- and fine-grained spinel show that the fine spinel grains are more enriched in Cr (1-2 wt. %) than their coarse counterparts (0.1-0.5 wt. %). The data suggest thermal metamorphism drove chemical exchange of the previously refractory inclusion, introducing chromium and iron as well as sulfur, which is moderately volatile. Conclusions: The three CAIs analyzed record distinct secondary nebular and parent body processes. Saguaro melted in the nebula as seen by the twinned melilite and spinel palisades. Hoopoe experienced intense shock which deformed its melilite and recrystallized perovskite, augite, and spinel in fine-grained regions. Cottonwood shows evidence of recrystallization and chemical changes consistent with thermal metamorphism occurring after accretion into the parent-body.

V E Burnette↗

The Profiled Feldman-Cousins Method for Confidence Interval Construction for the Nova 3-Flavor Oscillation Analysis

The small interaction cross-section of neutrinos makes experimental neutrino physics particularly responsive to technological advancements. A significant development leveraged by the NOvA experiment is large-scale parallel processing, enabling novel computational approaches to longstanding experimental challenges. Central to managing the resulting high-throughput data is NOvA’s implementation of the Freight Train model, designed for efficient data production and handling.This dissertation details the methodology and execution of the NOvA 2024 3-Flavor Oscillation Analysis, supported by a comprehensive dataset spanning ten years. It emphasizes frequentist results refined through the Feldman-Cousins (FC) technique, specifically addressing confidence interval corrections in parameter estimation. The computational intensity associated with Feldman-Cousins arises from extensive Monte Carlo simulations, which were substantially mitigated through parallel computing on the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC), employing the MPI framework.To further enhance computational efficiency, an Importance Sampling method is introduced and evaluated, demonstrating significant potential to reduce complexity, particularly in exploring extreme parameter space regions. This thesis presents both the successful application of advanced computational resources and the development of sophisticated statistical techniques, aiming to enhance the precision and scope of neutrino oscillation analyses.

Dye ajdye11190@gmail.com, Andrew Joseph [Mississip↗

First-Principles Statistical Mechanics Study of Magnetic Fluctuations and Order–Disorder in the Spinel LiNi 0.5 Mn 1.5 O 4 Cathode

While significant magnetic interactions exist in lithium transition metal oxides, commonly used as Li-ion cathodes, the interplay between magnetic couplings, disorder, and redox processes remains poorly understood. In this work, we focus on the high-voltage spinel LiNi 0.5 Mn 1.5 O 4 (LNMO) cathode as a model system on which to apply a computational framework that uses first principles-based statistical mechanics methods to predict the finite temperature magnetic properties of materials and provide insights into the complex interplay between magnetic and chemical degrees of freedom. Density functional theory calculations on multiple distinct Ni–Mn orderings within the LNMO system, including the ordered ground-state structure (space group P4332), reveal a preference for a ferrimagnetic arrangement of the Ni and Mn sublattices due to strong antiferromagnetic superexchange interactions between neighboring Mn 4+ and Ni 2+ ions and ferromagnetic Mn–Mn and Ni–Ni couplings, as revealed by magnetic cluster expansions. These results are consistent with qualitative predictions using the Goodenough-Kanamori-Anderson rules. Simulations of the finite temperature magnetic properties of LNMO are conducted using Metropolis Monte Carlo. We find that a “semiclassical” Monte Carlo sampling method based on the Heisenberg Hamiltonian accurately predicts experimental magnetic transition temperatures observed in magnetometry measurements. This study highlights the importance of a robust computational toolkit that accurately captures the complex chemomagnetic interactions and predicts finite temperature magnetic behavior to help analyze experimental magnetic and magnetic resonance spectroscopy data acquired ex situ and operando.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Relationship Of Size Distributions To Spectral (300 - 700 Nm) Extinction Parameterization Of Ambient In Situ Aerosols Measured During FIREX-AQ And The Influence Of Aerosol Composition

Hyperspectral (300 - 700 nm, 0.7 nm resolution) aerosol extinction spectra were measured at seven fires in six states in the western United States during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign in July and August 2019. Obtained using an in situ aerosol sampling method, these spectra are directly comparable to other in situ aerosol measurements such as size distribution and composition. A previous deployment of the in situ Spectral Aerosol Extinction (SpEx) instrument that measured fine mode aerosols (50% size cut of 1.3 µm particle diameter) around the Korean peninsula showed that over this spectral range 2nd order polynomials provided a better fit to the logarithmically transformed spectra than linear fits (representative of Ångström exponents). The two fit parameters (a1, a2) of the polynomials are related to the classic Ångström exponent but provide additional information via their two-dimensional parameter space. The previous work was limited by the lack of commensurate size distribution information. Here, using the FIREX-AQ spectra set it is possible to expand on the previous analysis in three specific ways: 1) size distribution information is available to further elucidate how size distribution maps into (a1, a2) space, 2) the sampled size distributions include larger particles than the Korean study, and 3) the FIREX-AQ data set exhibits smoke-related spectral features in the UV part of the spectrum that are not present in background air nor were they observed previously in the Korean study. The UV spectral features are particularly intriguing as they likely arise from the absorption component of the extinction measurement and therefore may be related to composition. The relationships between the ambient in situ aerosol size distributions, the extinction spectra, and composition will be presented.

Carolyn Jordan↗

Airborne eddy correlation gas flux measurements - Design criteria for optical techniques

Although several methods exist for the determination of the flux of an atmospheric species, the airborne eddy correlation method has the advantage of providing direct flux measurements that are representative of regional spatial domains. The design criteria pertinent to the construction of chemical instrumentation suitable for use in airborne eddy correlation flux measurements are discussed. A brief overview of the advantages and limitations of the current instrumentation used to obtain flux measurements for CO, CH4, O3, CO2, and water vapor are given. The intended height of the measurement within the convective boundary layer is also shown to be an important design criteria. The sensitivity, or resolution, which is required in the measurement of a scalar species to obtain an adequate species flux measurement is discussed. The relationship between the species flux resolution and the more commonly stated instrumental resolution is developed and it is shown that the standard error of the flux estimate is a complicated function of the atmospheric variability and the averaging time that is used. The use of the recently proposed intermittent sampling method to determine the species flux is examined. The application of this technique may provide an opportunity to expand the suite of trace gases for which direct flux measurements are possible.

Ritter, John A.↗

The SEDs and Host Galaxies of the Dustiest GRB Afterglows

The afterglows and host galaxies of long gamma-ray bursts (GRBs) offer unique opportunities to study star-forming galaxies in the high-z Universe, Until recently, however. the information inferred from GRB follow-up observations was mostly limited to optically bright afterglows. biasing all demographic studies against sight-lines that contain large amounts of dust. Aims. Here we present afterglow and host observations for a sample of bursts that are exemplary of previously missed ones because of high visual extinction (A(sub v) (Sup GRB) approx > 1 mag) along the sight-line. This facilitates an investigation of the properties, geometry and location of the absorbing dust of these poorly-explored host galaxies. and a comparison to hosts from optically-selected samples. Methods. This work is based on GROND optical/NIR and Swift/XRT X-ray observations of the afterglows, and multi-color imaging for eight GRB hosts. The afterglow and galaxy spectral energy distributions yield detailed insight into physical properties such as the dust and metal content along the GRB sight-line as well as galaxy-integrated characteristics like the host's stellar mass, luminosity. color-excess and star-formation rate. Results. For the eight afterglows considered in this study we report for the first time the redshift of GRBs 081109 (z = 0.97S7 +/- 0.0005). and the visual extinction towards GRBs 0801109 (A(sub v) (Sup GRB) = 3.4(sup +0.4) (sub -0.3) mag) and l00621A (A(sub v) (Sup GRB) = 3.8 +/- 0.2 mag), which are among the largest ever derived for GRB afterglows. Combined with non-extinguished GRBs. there is a strong anti-correlation between the afterglow's metals-to-dust ratio and visual extinction. The hosts of the dustiest afterglows are diverse in their properties, but on average redder(((R - K)(sub AB)) approximates 1.6 mag), more luminous ( approximates 0.9 L (sup *)) and massive ((log M(sup *) [M(solar]) approximates 9.8) than the hosts of optically-bright events. We hence probe a different galaxy population. suggesting that previous host samples miss most of the massive. chemically-evolved and metal-rich members. This also indicates that the dust along the sight-line is often related to host properties, and thus probably located in the diffuse ISM or interstellar clouds and not in the immediate GRB environment. Some of the hosts in our sample. are blue, young or of small stellar mass illustrating that even apparently non-extinguished galaxies possess very dusty sight-lines due to a patchy dust distribution. Conclusions. The afterglows and host galaxies of the dustiest GRBs provide evidence for a complex dust geometry in star-forming galaxies. In addition, they establish a population of luminous. massive and correspondingly chemically-evolved GRB hosts. This suggests that GRBs trace the global star-formation rate better than studies based on optically-selected host samples indicate, and the previously-claimed deficiency of high-mass host galaxies was at least partially a selection effect.

Kruhler, T.↗

Pulse-Echo Ultrasonic Imaging Method for Eliminating Sample Thickness Variation Effects

A pulse-echo, immersion method for ultrasonic evaluation of a material which accounts for and eliminates nonlevelness in the equipment set-up and sample thickness variation effects employs a single transducer and automatic scanning and digital imaging to obtain an image of a property of the material, such as pore fraction. The nonlevelness and thickness variation effects are accounted for by pre-scan adjustments of the time window to insure that the echoes received at each scan point are gated in the center of the window. This information is input into the scan file so that, during the automatic scanning for the material evaluation, each received echo is centered in its time window. A cross-correlation function calculates the velocity at each scan point, which is then proportionalized to a color or grey scale and displayed on a video screen.

Roth, Don J.↗

Pulse-echo ultrasonic imaging method for eliminating sample thickness variation effects

A pulse-echo, immersion method for ultrasonic evaluation of a material is discussed. It accounts for and eliminates nonlevelness in the equipment set-up and sample thickness variation effects employs a single transducer, automatic scanning and digital imaging to obtain an image of a property of the material, such as pore fraction. The nonlevelness and thickness variation effects are accounted for by pre-scan adjusments of the time window to insure that the echoes received at each scan point are gated in the center of the window. This information is input into the scan file so that, during the automatic scanning for the material evaluation, each received echo is centered in its time window. A cross-correlation function calculates the velocity at each scan point, which is then proportionalized to a color or grey scale and displayed on a video screen.

Roth, Don J.↗

Adaptive Interface-PINNs (AdaI-PINNs) for transient diffusion: Applications to forward and inverse problems in heterogeneous media

We model transient diffusion in heterogeneous materials using a novel physics-informed neural networks framework (PINNs) termed Adaptive interface physics-informed neural networks or AdaI-PINNs (Roy et al. arXiv preprint arXiv:2406.04626, 2024). AdaI-PINNs utilize different activation functions with trainable slopes tailored to each material region within the computational domain, allowing for a fully automated and adaptive PINNs approach to model interface problems with strongly and weakly discontinuous solutions. To enhance its performance in highly heterogeneous transient diffusion systems, we prescribe a suite of robust practices, including appropriate non-dimensionalization of equations, a biased sampling method, Glorot initialization, and the hard enforcement of boundary and initial conditions. Here we evaluate the efficacy of the proposed method on several benchmark forward and inverse problems. Comparative studies on one-dimensional and two-dimensional benchmark problems reveal that the modified AdaI-PINNs outperform its unmodified counterpart, achieving root-mean-square errors that are at least two orders of magnitude better in forward problems. For inverse problems, the maximum errors in the approximated diffusion coefficients by modified AdaI-PINNs are four orders of magnitude better than those of the unmodified version. Additionally, modified AdaI-PINNs demonstrate improved stability in problems with large material mismatches.

42 ENGINEERING↗

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

Active species in chloroaluminate ionic liquids catalyzing low-temperature polyolefin deconstruction

Abstract Chloroaluminate ionic liquids selectively transform (waste) polyolefins into gasoline-range alkanes through tandem cracking-alkylation at temperatures below 100 °C. Further improvement of this process necessitates a deep understanding of the nature of the catalytically active species and the correlated performance in the catalyzing critical reactions for the tandem polyolefin deconstruction with isoalkanes at low temperatures. Here, we address this requirement by determining the nuclearity of the chloroaluminate ions and their interactions with reaction intermediates, combining in situ 27 Al magic-angle spinning nuclear magnetic resonance spectroscopy, in situ Raman spectroscopy, Al K-edge X-ray absorption near edge structure spectroscopy, and catalytic activity measurement. Cracking and alkylation are facilitated by carbenium ions initiated by AlCl 3 - tert -butyl chloride (TBC) adducts, which are formed by the dissociation of Al 2 Cl 7 − in the presence of TBC. The carbenium ions activate the alkane polymer strands and advance the alkylation cycle through multiple hydride transfer reactions. In situ 1 H NMR and operando infrared spectroscopy demonstrate that the cracking and alkylation processes occur synchronously; alkenes formed during cracking are rapidly incorporated into the carbenium ion-mediated alkylation cycle. The conclusions are further supported by ab initio molecular dynamics simulations coupled with an enhanced sampling method, and model experiments using n-hexadecane as a feed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kekulé valence bond order in the honeycomb lattice optical Su-Schrieffer-Heeger model and its relevance to graphene

We perform sign-problem-free determinant quantum Monte Carlo simulations of the optical Su- Schrieffer-Heeger model on a half-filled honeycomb lattice. In particular, we investigate the model’s semi-metal (SM) to Kekulé Valence Bond Solid (KVBS) phase transition at zero and finite temper- atures as a function of phonon energy and interaction strength. Using hybrid Monte Carlo sampling methods we can simulate the model near the adiabatic regime, allowing us to access regions of parameter space relevant to graphene. Our simulations suggest that the SM-KVBS transition is weakly first-order at all temperatures, with graphene situated close to the phase boundary in the SM region of the phase diagram. Furthermore, our results highlight the important role bond-stretching phonon modes play in the formation of KVBS order in strained graphene-derived systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Optimization of Structurally Enhanced Solder Transient Liquid Phase Bonding

High temperature packaging technologies are a necessity for high temperature capable devices. SAC305 solder has an operational limit of 174°C imposed by creep effects which aligns well with current junction temperature limits of 175°C. Wide band gap semiconductor materials have the potential to reach junction temperatures of up to 800°C that are not currently attainable with significant reliability. Capitalizing on this potential will requires substrates and attachments that can operate well beyond the current 175°C standard. Silver sintering pastes have received widespread interest as a high temperature attachment alternative. However, the process requires high pressure bonding in an inert environment to achieve acceptable bond quality. Transient liquid phase (TLP) sintering is capable of good bond quality without pressure requirements but suffers from low thermal conductivity and only slightly reduced cost compared to silver sintering. SAC305 solder contains the same constituent materials for TLP as available copper-tin TLP sintering paste. By introducing engineered surface structures into the bond, intermetallic formation can be accelerated producing a bond similar to TLP sintering but in an ambient environment and for reduced cost. While this process has been demonstrated, it has not yet been optimized. Currently bonds are formed using a 75 μm stencil on substrate surface structures 24 μm tall, covering 19% of the bonding area. The process takes about 4 hours not including the formation of surface structures. Here, this study will center on the effects of stencil thickness and coating methods. Samples will be analyzed by scanning acoustic microscopy, die shear testing and cross sectional scanning acoustic microscopy.

42 ENGINEERING↗

Uncertainty Visualization of Critical Points of 2D Scalar Fields for Parametric and Nonparametric Probabilistic Models

This paper presents a novel end-to-end framework for closed-form computation and visualization of critical point uncertainty in 2D uncertain scalar fields. Critical points are fundamental topological descriptors used in the visualization and analysis of scalar fields. The uncertainty inherent in data (e.g., observational and experimental data, approximations in simulations, and compression), however, creates uncertainty regarding critical point positions. Uncertainty in critical point positions, therefore, cannot be ignored, given their impact on downstream data analysis tasks. Here, in this work, we study uncertainty in critical points as a function of uncertainty in data modeled with probability distributions. Although Monte Carlo (MC) sampling techniques have been used in prior studies to quantify critical point uncertainty, they are often expensive and are infrequently used in production-quality visualization software. We, therefore, propose a new end-to-end framework to address these challenges that comprises a threefold contribution. First, we derive the critical point uncertainty in closed form, which is more accurate and efficient than the conventional MC sampling methods. Specifically, we provide the closed-form and semianalytical (a mix of closed-form and MC methods) solutions for parametric (e.g., uniform, Epanechnikov) and nonparametric models (e.g., histograms) with finite support. Second, we accelerate critical point probability computations using a parallel implementation with the VTK-m library, which is platform portable. Finally, we demonstrate the integration of our implementation with the ParaView software system to demonstrate near-real-time results for real datasets.

97 MATHEMATICS AND COMPUTING↗

Broadband 920-nm mirror thin film damage competition

The 2023 Laser Damage conference thin-film damage competition was devoted to a survey on the state-of-the-art broadband near-IR multilayer dielectric (MLD) mirrors designed for ultra-short pulsed laser applications. The requirements for the coatings were a minimum reflection of 99.5% at 45-deg incidence angle for S-polarization from 830 nm to 1010 nm and group delay dispersion (GDD) < ± 50fs 2 . The participants were allowed to select the coating materials, coating design, and coating deposition method. Samples were damage tested at a single testing facility to enable direct comparison among the participants using a 25 ± 5 fs optical parametric chirped-pulse amplification (OPCPA) laser system operating at 5 Hz. The testing results from this set of 37 samples showed that dense coatings by ion-beam sputtering (IBS), magnetron sputtering (MS), and electron-beam ion assisted deposition (e-beam IAD) exhibited highest damage initiation onset (laser-induced damage threshold or LIDT) while e-beam coatings were low performers. In addition, multilayer coatings using tantala and/or hafnia as high index materials were top performers. Furthermore, this competition included for the first time the measurement of the damage growth onset (laser-induced damage growth threshold or LDGT). This latter performance metric plays an important role in establishing the safe operational conditions for larger aperture ultrashort pulsed lasers. Information pertaining to the morphology of the damage sites and their evolution under subsequent exposure to different laser fluences leading to damage growth is presented. Finally, not all coating samples in the survey met the GDD requirements stated above and associated measurements are discussed in the context of the present and past thin-film damage competitions focused on similar broadband near-IR MLD coatings.

23 broadband high reflectors↗

Multivariate Testing of Sampling Techniques to Address Class Imbalance in Building Use Type Classification

This study addresses the challenges inherent in building use type classification, particularly focusing on the issue of class imbalance in the training datasets for machine learning classifiers. We comprehensively analyze the efficacy of various class-balancing sampling techniques. Employing Monte Carlo simulations and Bayesian optimization, we evaluated the performance of multiple sampling methods, including Random Oversampling, Random Undersampling, SMOTE, Borderline-SMOTE, and ADASYN, across a dataset encompassing nine southeastern coastal states of the United States. Our findings reveal that simple random over- and undersampling techniques outperform more sophisticated methods. Additionally, we show inherent value in creating an imbalance in training data to effectively train a machine learning classifier for distinguishing between residential and nonresidential buildings. This study provides valuable guidance for future research on building use type classification research and lays essential groundwork for developing attribute-rich building stock datasets.

Adams, Daniel↗