Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Adaptive Sampling”

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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Two-dimensional second harmonic dispersion interferometer

An interferometer having a fundamental beam generator, a first second harmonic generator, a waveplate, a second second harmonic generator, a harmonic separator, and a polarizing beam splitter, mounted uniaxially, (i.e., the components are aligned along one optical axis), wherein the interferometer is adapted to change a diameter of a beam to match a diameter of a sample, and to change the diameter of the beam back to its original diameter.

Wessel, Frank Joseph↗
DOE OSTI2014

MCNP6 Elevation Scaling of Cosmic Ray Backgrounds - Paper 29

The galactic cosmic-ray (GCR) source option was implemented in the all-energy, all-particle transport code MCNP62 in 2010. This source option along with other newly added features to MCNP6 have been used to produce increasingly accurate global cosmic and terrestrial background flux data files (background.dat).3 This data file is produced on a grid and is read and sampled by MCNP6 whenever a user invokes the background source option. The most recent adaptation of this data file, Version 4, will be completed in 2014. This paper reports on current progress toward enhancements that have been made to the modeling and simulation of these background spectra, in particular the elevation scaling used to produce more accurate spectra at off-grid locations. Cosmic radiation continuously bombards Earth with various particles, such as protons, alpha particles, and heavier nuclei, some of which are deflected by the Earth's shielding magnetic field. Particles that carry sufficient momentum can overcome the deflection and penetrate into the atmosphere. The sufficient momentum is dependent on the terrestrial coordinates due to the shape of the Earth's magnetic field and the Lorentz force's proportionality to the sine of the angle between the velocity vector of the incoming particle and the magnetic field direction. As the particles propagate through the atmosphere, collisions with atmospheric molecules generate secondary particles such as neutrons, protons, photons, muons, pions, and other exotic particles. These secondary particles often have sufficient energy to undergo additional nuclear interactions, and so on, forming what is known as a cascade shower. The particles in the cascade shower are constantly undergoing energy losses due to interactions, especially charged particles whose paths are bent into helical trajectories around magnetic field lines. These energy losses make the integral flux of the cosmic background at the ground level highly dependent on the atmospheric depth traveled by the incident particle and its progeny, and therefore dependent on the elevation of the ground where the cascade deposits its energy. For relatively small depth changes of approximately 100 g/cm{sup 2} or less, the ground-level cosmic flux follows an exponential model. The tabulation of background particle fluxes on the surface of the earth is important for a variety of reasons, one of which is the design of nuclear material detection systems. This method is also useful in producing user-specified effective attenuation lengths for particles. Attenuation lengths are an essential parameter used to compare particle spectra from different locations, elevations, and energy ranges. Traditionally these attenuation lengths are inferred from measured data. Now with the ability to simulate an accurate galactic cosmic ray source and transport it and its shower through a modeled atmosphere, these attenuation lengths can be calculated for any set of conditions. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Accelerating Markov Chain Monte Carlo sampling with diffusion models

Global fits of physics models require efficient methods for exploring high-dimensional and/or multimodal posterior functions. We introduce a novel method for accelerating Markov Chain Monte Carlo (MCMC) sampling by pairing a Metropolis-Hastings algorithm with a diffusion model that can draw global samples with the aim of approximating the posterior. We briefly review diffusion models in the context of image synthesis before providing a streamlined diffusion model tailored towards low-dimensional data arrays. We then present our adapted Metropolis-Hastings algorithm which combines local proposals with global proposals taken from a diffusion model that is regularly trained on the samples produced during the MCMC run. Our approach leads to a significant reduction in the number of likelihood evaluations required to obtain an accurate representation of the Bayesian posterior across several analytic functions, as well as for a physical example based on a global fit of parton distribution functions. Our method is extensible to other MCMC techniques, and we briefly compare our method to similar approaches based on normalising flows. A code implementation can be found at https://github.com/NickHunt-Smith/MCMC-diffusion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Shortest Microlensing Event with a Bound Planet: KMT-2016-BLG-2605

With a planet–host mass ratio q = 0.012 ± 0.001, KMT-2016-BLG-2605 has the shortest Einstein timescale, t {sub E} = 3.41 ± 0.13 days, of any planetary microlensing event to date. This prompts us to examine the full sample of seven short (t {sub E} < 7 days) planetary events with good q measurements. We find that six have clustered Einstein radii θ {sub E} = 115 ± 20 μas and lens–source relative proper motions μ {sub rel} ≃ 9.5 ± 2.5 mas yr{sup -1}. For the seventh, these two quantities could not be measured. These distributions are consistent with a Galactic bulge population of very low mass (VLM) hosts near the hydrogen-burning limit. This conjecture could be verified by imaging at first adaptive optics light on next-generation (30 m) telescopes. Based on a preliminary assessment of the sample, “planetary” companions (i.e., below the deuterium-burning limit) are divided into “genuine planets,” formed in their disks by core accretion, and VLM brown dwarfs, which form like stars. We discuss techniques for expanding the sample, which include taking account of the peculiar “anomaly-dominated” morphology of the KMT-2016-BLG-2605 light curve.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Portable and Cost-Effective Device for Reliable Detection of Counterfeit and Non-compliant Refrigerants in Diverse Applications

Counterfeit refrigerants pose significant challenges to safety, system reliability, and operational effectiveness due to their harmful contaminants or incompatible chemical compositions. Utilizing these noncompliant products can lead to reduced efficiency, equipment failures, and expensive repairs. Additionally, heightened demand for alternative refrigerants during the industry's transition has created supply gaps, enabling counterfeit products to proliferate. Accurate detection and analysis tools are therefore essential to verify refrigerant authenticity and ensure system integrity in diverse applications. This paper presents the development of a portable device designed for reliable identification and detailed analysis of refrigerant composition. By integrating precision gas sampling, controlled pressure regulation, and automated sensor technology, the device not only detects deviations from standard refrigerant properties but also provides a comprehensive composition breakdown. Pre-calibrated sensors measure the refrigerant gas to identify specific concentrations and contaminants, with an intuitive LED-based indicator system ensuring quick interpretation of results. The user-friendly interface enables operators to select refrigerant types for targeted testing, further enhancing accuracy and usability for field technicians. Comprehensive testing was conducted on mildly flammable A2L refrigerants, showcasing the device’s robustness and adaptability in analyzing composition and detecting discrepancies. The device demonstrated consistent accuracy across a range of refrigerant samples, affirming its reliability in diverse operational environments. Its design minimizes contamination risks during sampling and provides detailed composition results within 90 seconds, ensuring efficient and precise analysis. With a projected price point under $150, the proposed solution delivers affordability alongside its lightweight portability and straightforward operation. Unlike complex and costly alternatives, such as gas chromatography systems, this device provides an accessible option for technicians, customs personnel, and industry operators in need of quick and effective refrigerant verification. Compatible with both current formulations and emerging refrigerant technologies, the device addresses critical counterfeit detection needs across a range of applications. By delivering accurate composition analysis and counterfeit identification, this innovation enhances system performance, safety, and operational reliability in crucial industries.

Cheekatamarla, Praveen [ORNL] (ORCID:0000000248827↗
DOE OSTI2020

Protein Conformational States—A First Principles Bayesian Method

Automated identification of protein conformational states from simulation of an ensemble of structures is a hard problem because it requires teaching a computer to recognize shapes. We adapt the naïve Bayes classifier from the machine learning community for use on atom-to-atom pairwise contacts. The result is an unsupervised learning algorithm that samples a ‘distribution’ over potential classification schemes. We apply the classifier to a series of test structures and one real protein, showing that it identifies the conformational transition with >95% accuracy in most cases. A nontrivial feature of our adaptation is a new connection to information entropy that allows us to vary the level of structural detail without spoiling the categorization. This is confirmed by comparing results as the number of atoms and time-samples are varied over 1.5 orders of magnitude. Further, the method’s derivation from Bayesian analysis on the set of inter-atomic contacts makes it easy to understand and extend to more complex cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

High-Resolution Sampling of a River Plume Front with Uncrewed Underwater and Aerial Vehicles

Sampling fast-propagating oceanic features is inherently challenging and demands versatile instrumentation and innovative strategies. This paper introduces a novel sampling strategy designed to capture such phenomena, exemplified by a river plume front. Our method revolves around modifying the preprogrammed pathway of an uncrewed underwater vehicle (UUV) to dynamically track and three-dimensionally sample the evolution of the front. To enable the UUV to follow the feature, we adapt the use of a drifting gateway buoy to be positioned and trapped at the front’s convergence zone, allowing underway navigation relative to the buoy. In our demonstration, we showcase the effectiveness of this strategy by successfully conducting over 30 crossings of a river plume front within a 6-h window. The UUV sensors allowed a comprehensive assessment of key front characteristics, including density, velocity, and turbulence. Supplemental drone footage contributed to the overall picture and facilitated the transformation of the dataset into a front-following reference frame. This article provides an in-depth description of the deployment strategy and required postcollection data processing, including frontal crossing detection, the assessment of the frontal orientation from drone footage, and defining the plume bottom boundaries using backscatter intensity contours.

autonomous observations↗
DOE OSTI2025

Determination of a suitable molar absorption coefficient (ε) for lignin analysis of fibrous plants using the CASA method

In this study, the benchmarking and applicability of the CASA method for the analysis of fibrous plants, such as flax, hemp, and jute, is evaluated. Lignin is a phenolic biopolymer present in plant cell walls and is composed of three primary monomeric units, designated G, S, and H. Various factors, such as the genetic variability, influence the relative proportions of these units in plant samples. Recently, the cysteine-assisted sulfuric acid (CASA) method has been introduced as a rapid method for the quantification of lignin in wood samples. The aim of this study is to establish a suitable molar absorption coefficient (ε, L·g –1 ·cm –1 ) to adapt the CASA method for use with annual plant fibers. This investigation was motivated by the technical advantages of the CASA method, including higher throughput, lower reaction temperatures, and ecological benefits due to the absence of carcinogenic, mutagenic, or reprotoxic (CMR) substances and the need for minimal sample quantities. In this method, lignin solubilization is facilitated by cysteine, which is an amino acid that enhances the reaction kinetics, using a one-hour incubation period. However, as with any spectrophotometric technique, the CASA method depends on a molar absorption coefficient (ε) that varies according to the ratio of the aromatic units within the polymer. To evaluate the suitability of CASA for quantifying lignin in economically significant plant fibers, we investigate the impact of the unit ratios on the accuracy of ε. The results are compared with those of two widely recognized lignin analytical methods: the Klason method, which is a gravimetric reference method, and the acetyl bromide soluble lignin method, which is the most commonly used spectrophotometric approach. The final ε obtained in this study reveals a relative difference in lignin content ranging from –8 % to +9 % based on a comparison between the CASA and Klason methods across different industrial hemp varieties. As a result, using known G:S ratios in annual fibrous plants, ε can be estimated from our results.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Rapid fusion method for determination of plutonium isotopes in large rice samples

A new rapid fusion method for the determination of plutonium in large rice samples has been developed at the Savannah River National Laboratory (Aiken, SC, USA) that can be used to determine very low levels of plutonium isotopes in rice. The recent accident at Fukushima Nuclear Power Plant in March, 2011 reinforces the need to have rapid, reliable radiochemical analyses for radionuclides in environmental and food samples. Public concern regarding foods, particularly foods such as rice in Japan, highlights the need for analytical techniques that will allow very large sample aliquots of rice to be used for analysis so that very low levels of plutonium isotopes may be detected. The new method to determine plutonium isotopes in large rice samples utilizes a furnace ashing step, a rapid sodium hydroxide fusion method, a lanthanum fluoride matrix removal step, and a column separation process with TEVA Resin cartridges. The method can be applied to rice sample aliquots as large as 5 kg. Plutonium isotopes can be determined using alpha spectrometry or inductively-coupled plasma mass spectrometry (ICP-MS). The method showed high chemical recoveries and effective removal of interferences. The rapid fusion technique is a rugged sample digestion method that ensures that any refractory plutonium particles are effectively digested. The MDA for a 5 kg rice sample using alpha spectrometry is 7E-5 mBq g{sup -1}. The method can easily be adapted for use by ICP-MS to allow detection of plutonium isotopic ratios.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Kinetic analysis of Cas12a and Cas13a RNA-Guided nucleases for development of improved CRISPR-Based diagnostics

Bacterial CRISPR systems provide acquired immunity against invading nucleic acids by activating RNA-programmable RNases and DNases. Cas13a and Cas12a enzymes bound to CRISPR RNA (crRNA) recognize specific nucleic acid targets, initiating cleavage of the targets as well as non-target (trans) nucleic acids. Here, we examine the kinetics of single-turnover target and multi-turnover trans-nuclease activities of both enzymes. High-turnover, non-specific Cas13a trans-RNase activity is coupled to rapid binding of target RNA. By contrast, low-turnover Cas12a trans-nuclease activity is coupled to relatively slow cleavage of target DNA, selective for DNA over RNA, indifferent to base identity, and preferential for single-stranded substrates. Combining multiple crRNA increases detection sensitivity of targets, an approach we use to quantify pathogen DNA in samples from patients suspected of Buruli ulcer disease. Results reveal that these enzymes are kinetically adapted to play distinct roles in bacterial adaptive immunity and show how kinetic analysis can be applied to CRISPR-based diagnostics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

The multi-purpose three-axis spectrometer (TAS) MIRA at FRM II

The cold-neutron three-axis spectrometer MIRA is an instrument optimized for low-energy excitations. Its excellent intrinsic $Q$-resolution makes it ideal for studying incommensurate magnetic systems (elastic and inelastic). MIRA is at the forefront of using advanced neutron focusing optics such as elliptic guides, which enable the investigation of small samples under extreme conditions. Another advantage of MIRA is the modular assembly allowing for instrumental adaption to the needs of the experiment within a few hours. The development of new methods such as the spin-echo technique MIEZE is another important application at MIRA. Finally, scientific topics include the investigation of complex inter-metallic alloys and spectroscopy on incommensurate magnetic structures.

36 MATERIALS SCIENCE↗
DOE OSTI2015

A COMPARISON OF SPECTROSCOPIC VERSUS IMAGING TECHNIQUES FOR DETECTING CLOSE COMPANIONS TO KEPLER OBJECTS OF INTEREST

Kepler planet candidates require both spectroscopic and imaging follow-up observations to rule out false positives and detect blended stars. Traditionally, spectroscopy and high-resolution imaging have probed different host star companion parameter spaces, the former detecting tight binaries and the latter detecting wider bound companions as well as chance background stars. In this paper, we examine a sample of 11 Kepler host stars with companions detected by two techniques—near-infrared adaptive optics and/or optical speckle interferometry imaging, and a new spectroscopic deblending method. We compare the companion effective temperatures (T{sub eff}) and flux ratios (F{sub B}/F{sub A}, where A is the primary and B is the companion) derived from each technique and find no cases where both companion parameters agree within 1σ errors. In 3/11 cases the companion T{sub eff} values agree within 1σ errors, and in 2/11 cases the companion F{sub B}/F{sub A} values agree within 1σ errors. Examining each Kepler system individually considering multiple avenues (isochrone mapping, contrast curves, probability of being bound), we suggest two cases for which the techniques most likely agree in their companion detections (detect the same companion star). Overall, our results support the advantage that the spectroscopic deblending technique has for finding very close-in companions (θ ≲ 0.″02–0.″05) that are not easily detectable with imaging. However, we also specifically show how high-contrast AO and speckle imaging observations detect companions at larger separations (θ ≥ 0.″02–0.″05) that are missed by the spectroscopic technique, provide additional information for characterizing the companion and its potential contamination (e.g., position angle, separation, magnitude differences), and cover a wider range of primary star effective temperatures. The investigation presented here illustrates the utility of combining the two techniques to reveal higher-order multiples in known planet-hosting systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Improving the Parameterization of Cloud and Rain Microphysics in E3SM using Novel Observationally-Constrained Bayesian Approach (Final Technical Report)

In this project, we sought to develop new cloud and rain microphysics frameworks within the Energy Exascale Earth System Model (E3SM). This work encompassed two primary avenues of research: 1) Further development of a Bayesian-based scheme called BOSS (Bayesian Observationally-constrained Statistical-physical Scheme) to represent cloud and rain microphysics, testing it in realistic high-resolution cloud models, and implementing it in E3SM; 2) Development of a methodology utilizing machine learning to enable computationally tractable use of tractable use of Markov chain Monte Carlo sampling for Bayesian parameter estimation in Earth system and cloud models. In this project, we adapted the BOSS microphysics scheme, originally formulated for rain-only, to include all liquid-phase microphysical processes for cloud and rain, in particular the processes that mediate between these two categories, for example the conversion from cloud to rain through collision and coalescence of drops. We constrained the scheme via comparison and testing against a detailed model that explicitly represents the evolution of cloud and rain particles, called a bin microphysics scheme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Developing compact tuning fork thermometers for sub-mK temperatures and high magnetic fields

There is a growing demand for experiments on calorimetric and thermal transport measurements at ultra-low temperatures below 1 mK and high magnetic fields up to 16 T. Particularly, milligram-sized solid samples are of great interest. Here, we present the development of scalable thermometers based on quartz tuning fork resonators immersed in liquid 3 He and adapt hydrodynamic models to provide an improved description of temperature dependence in the high viscosity regime between 1 and 10mK. We demonstrate successful thermometer operation and discuss the feasibility of fast and compact thermal probes suitable for small samples.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Precision Local Burnup Assessment Through Dynamic Peak Fitting in Atom Probe Tomography for Depleted, Enriched, and Irradiated Metallic and Ceramic Fuels

Abstract Burnup estimation in nuclear fuels is vital for evaluating fuel performance, transportation, and safe fuel storage. Accurate assessments of burnup from service period and spent fuels involve tracking the consumption of fissile isotopes of uranium (U) offering a direct insight into energy changes within the fuels especially for thermal spectrum reactors. In current approach, mass spectroscopic technique in atom probe tomography (APT) is utilized for accurate quantification of U isotopes. Quantification of U peaks in mass spectrum is performed on asymmetric shapes due to delayed signals, known as thermal tails, particularly for poorly conducting samples analyzed in laser mode. In this study, we introduce a novel quantification tool for isotopic analysis from APT datasets by developing a fitting algorithm based on shapes of the peaks. A MATLAB-based dynamic peak fitting toolbox is developed and designed to adapt to various peak shapes, ensuring accurate quantification of U isotopes. The effectiveness of this approach is demonstrated in standard Ni-Cr sample, depleted and enriched U samples, and U-based fuels with different burnup levels. The viability of this approach for isotopic quantification is demonstrated on both metallic and ceramic fuels.

Burnup↗
DOE OSTI2024

Fungal diversity and function in metagenomes sequenced from extreme environments

Fungi are increasingly recognized as key players in various extreme environments. Here we present an analysis of publicly-sourced metagenomes from global extreme environments, focusing on fungal taxonomy and function. The majority of 855 selected metagenomes contained scaffolds assigned to fungi. Relative abundance of fungi was as high as 10% of protein-coding genes with taxonomic annotation, with up to 289 fungal genera per sample. Despite taxonomic clustering by environment, fungal communities were more dissimilar than archaeal and bacterial communities, both for within- and between-environment comparisons. Relatively abundant fungal classes in extreme environments included Dothideomycetes, Eurotiomycetes, Leotiomycetes, Pezizomycetes, Saccharomycetes, and Sordariomycetes. Broad generalists and prolific aerial spore formers were the most relatively abundant fungal genera detected in most of the extreme environments, bringing up the question of whether they are actively growing in those environments or just surviving as spores. More specialized fungi were common in some environments, such as zoosporic taxa in cryosphere water and hot springs. Relative abundances of genes involved in adaptation to general, thermal, oxidative, and osmotic stress were greatest in soda lake, acid mine drainage, and cryosphere water samples.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Meissner-London Susceptibility of Superconducting Right Circular Cylinders in an Axial Magnetic Field

Analysis of magnetic susceptibility of nonellipsoidal samples is a long-standing problem in experimental studies of magnetism and superconductivity. Here the quantitative description of the Meissner-London response (no Abrikosov vortices) of right circular cylinders in an axial magnetic field is given. Three-dimensional adaptive finite-element modeling is used to calculate the total magnetic moment ( m ) in a wide range of London penetration depth ( λ ) to sample size ( a ) ratios, λ /a. Furthermore, by fitting numerical solutions, the closed-form empirical magnetic susceptibility is obtained involving only sample dimensions and λ, thus providing a recipe for determining the London penetration depth from the precision measurements of the magnetic susceptibility. Detailed protocols of the experimental data analysis using the developed approach are given. The results can be readily extended to the most frequently used cuboid-shaped samples.

3-dimensional systems↗
DOE OSTI2017

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we develop a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.

58 GEOSCIENCES↗