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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Examining the role of glycoside hydrolases in local rheology of Pseudomonas aeruginosa biofilms

Current research strategies in the treatment of biofilm infections have focused on dispersal, in which bacteria are made to vacate the extracellular polymeric substance (EPS) surrounding them and return to a planktonic state where antimicrobial treatments are more effective. Glycoside hydrolases (GHs), which cleave bonds in EPS polysaccharides, have been shown to promote dispersal in Pseudomonas aeruginosa biofilms. The dispersal mechanism is possibly due to GHs’ ability to directly release bacteria from the EPS, disrupt EPS’ ability to regulate the environment, or reduce overall mechanical stability. In this work, passive microrheology is used to examine the relevance of the last mechanism by exploring the effects of three GHs (α-amylase, cellulase, and xylanase) known to disperse P. aeruginosa on local biofilm viscoelasticity. Compared to control studies in wild-type strains, it is found that treatment with all three GHs results in statistically relatively less elastic and stiffer biofilms, indicating that changes to mechanical stability may be a factor in effective dispersal. Both cellulase and xylanase were observed to have the greatest impact in creating a less stiff and elastic biofilm; these GHs have been observed to be effective at dispersal in the published results. Each GH was further tested on biofilms grown with strains that produced EPS missing specific polysaccharide components. Cellulase specifically targeted Psl, which forms the major structural and mechanical backbone of the EPS, explaining its efficacy in dispersal. However, xylanase did not appear to exhibit any affinity to any polysaccharide within the EPS based on the microrheology results. Overall, these results suggest that the local microrheology of the biofilms is impacted by GHs and that may be one of the factors that is causing the ability of these therapeutics to enhance dispersal.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Circular and linear polarization inverse SAR imaging of simple deterministic targets and statistically known randomly rough surfaces using constant and varying illumination

In order to study mechanisms of scattering and their relative contributions to synthetic aperture radar (SAR) and inverse SAR images, a special measurement facility has been constructed. It can be used to generate images in which the target is illuminated from a constant direction as the receiver is rotated in azimuth, and the target is illuminated from various directions as the receiver is rotated in azimuth. The imaging system performance is discussed, and images obtained using both approaches are compared, for a variety of simple targets and statistically known randomly rough surfaces.

Bredow, J. W.↗
DOE OSTI2024

Application of the immobilized low-activity waste glass corrosion model to the static dissolution of 24 statistically-designed alkali-borosilicate waste glasses

Glass corrosion models that capture the complex mechanisms of the glass-water reaction enable the prediction of nuclear waste glass durability in disposal scenarios. Parameterization of such models is challenging because of the need to capture changes in corrosion behavior with time, reaction conditions, and glass composition. In this report we describe and employ the immobilized low activity waste (ILAW) glass corrosion model (IGCM) in geochemical simulations of static dissolution tests, at two temperatures (40 °C and 90 °C), for a matrix of 24 enhanced low activity waste (eLAW) glasses statistically designed to cover a processable composition space defined by 8 major glass components (Al 2 O 3 , B 2 O 3 , CaO, Na 2 O, SiO 2 , SnO 2 , ZrO 2 , and Others as defined in the text). The IGCM includes a first-order chemical affinity term and an ion-exchange term that represents the net exchange of Na+ ions in the pristine glass with protons in aqueous solution. Constant, time-dependent, and time- and pH-dependent functional forms of the ion-exchange term are evaluated to reproduce the change in corrosion behavior with time in saturated, static dissolution tests. The agreement with measured aqueous concentrations of the main glass components (B, Na, and Si) improved significantly upon addition of a time-dependent term, which therefore constitutes a simple representation of the glass-water reaction progress. Due to the limited changes in pH in the static dissolution tests, past a short initial period of rapid increase, addition of a pH dependent term did not appreciably improve the fits, indicating that comprehensive model parameterization requires more than one type of glass corrosion test to capture a wide range of solution chemistries. IGCM parameters were found to be dependent on glass composition, and the parameter sets generated in this work will enable the development of composition–parameter correlation models that offer the promise of predicting IGCM parameters, and thus glass corrosion behavior, solely based on glass composition.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Probabilistic-learning-based stochastic surrogate model from small incomplete datasets for nonlinear dynamical systems

We consider a high-dimensional nonlinear computational model of a dynamical system, parameterized by a vector-valued control parameter, in the presence of uncertainties represented by an uncontrolled parameter modeled by a vector-valued random variable, and possibly with stochastic excitation. The objective is to construct a statistical surrogate model where the input is any deterministic value of the control parameter, and the output is a vector-valued observation of the computational model, which is a random vector whose probability measure is updated using a target dataset. To construct this statistical surrogate model, the stochastic response of the computational model must be built, which is a vector-valued time-discretized stochastic process in high dimension, depending on the control parameter. It is assumed that the computational cost of a single evaluation of the deterministic model is high. For the probabilistic updating, we consider a subset of the components of the observation of the computational model, defined as the “identification observation” of the computational model, for which a small target dataset is available. Therefore, the target dataset is associated with partial observability, corresponding to an incomplete data case. Given a prior probability model of the random control and uncontrolled parameters, a training dataset is constructed, consisting of realizations of the random triplet composed of the stochastic response, the random identification observation, and the random control parameter. Since the computational cost of a single evaluation of the deterministic model is assumed to be large, the training dataset is also of small size. The main challenges in this problem are the high dimensionality, partial observability leading to incomplete data in the target dataset for the identification observation of the computational model (which is not sufficient to identify the computational stochastic responses), and the availability of a small training dataset. To address these challenges, we propose a methodology based on statistical methods for constructing necessary reduced representations, direct probabilistic learning under constraints using probabilistic learning on manifolds (PLoM) constrained by the target dataset, and the use of a weak formulation of the Fourier transform of probability measures. Statistical conditioning is also employed to explore the learned dataset. The constructed predictive statistical surrogate model can be implemented in the context of online computation. Here, we apply this approach to a problem of nonlinear stochastic dynamics in high dimensions within the framework of deformable solids mechanics.

Engineering↗
NASA NTRS1998

New AFM Techniques for Investigating Molecular Growth Mechanisms of Protein Crystals

Atomic Force Microscopy (AFM) has emerged as a powerful technique for investigating protein crystal growth. Earlier AFM studies were among the first to demonstrate that these crystals grew by dislocation and 2D nucleation growth mechanisms [1]. These investigations were restricted to the micron range where only surface features, such as dislocation hillocks and 2D islands are visible. Most AFM instruments can scan at higher resolutions and have the potential to resolve individual protein molecules at nanometer ranges. Such scans are essential for determining the molecular packing arrangements on crystal faces and for probing the growth process at the molecular level. However, at this resolution the AFM tip influences the image produced, with the resulting image being a convolution of the tip shape and the surface morphology [2]. In most studies this problem is resolved by deconvoluting the image to obtain the true surface morphology. Although deconvolution routines work reasonably well for simple one- dimensional shapes, for complex surfaces this approach does not produce accurate results. In this study we devised a new approach which takes advantage of the precise molecular order of crystal surfaces, combined with the knowledge of individual molecular shapes from the crystallographic data of the protein and the AFM tip shape. This information is used to construct expected theoretical AFM images by convoluting the tip shape with the constructed crystal surface shape for a given surface packing arrangement. By comparing the images from actual AFM scans with the constructed ones for different possible surface packing arrangements, the correct packing arrangement can be conclusively determined. This approach was used in this study to determine the correct one from two possible packing arrangements on (I 10) faces of tetragonal lysozyme crystals. Another novel AFM technique was also devised to measure the dimension of individual growth units of the crystal faces. Measuring these units was not attempted before and most studies have assumed that the growth unit consisted of individual protein molecules. The linescan mode of AFM instruments allows the crystal surface to be scanned along a single line. By scanning across a growth step an image showing the motion of the step is obtained. Normally such an image shows a straight line for continuous and constant step velocity. In this study by increasing the scan rate and by decreasing the step velocity (by decreasing the supersaturation), we were able to capture images of individual growth events, shown by jump discontinuities in the step line. By suitable integration of the image the growth unit dimension in the scanned direction can be obtained. Since multiple units can be involved in the growth process it is necessary to collect a statistically relevant sample before drawing conclusions about the growth mechanism. This technique was successfully employed to obtain the dimensions of growth units for the (110) face, showing that they consisted of various aggregates corresponding to the 43 helices in the crystal structure.

Li, Huayu↗
NASA NTRS2002

A Statistical Comparison of PSC Model Simulations and POAM Observations

A better knowledge of PSC composition and formation mechanisms is important to better understand and predict stratospheric ozone depletion. Several past studies have attempted to compare modeling results with satellite observations. These comparisons have concentrated on case studies. In this paper we adopt a statistical approach. POAM PSC observations from several Arctic winters are categorized into Type Ia and Ib PSCs using a technique based on Strawa et al. The discrimination technique has been modified to employ the wavelengths dependence of the extinction signal at all wavelengths rather than only at 603 and 10 18 nm. Winter-long simulations for the 1999-2000 Arctic winter have been made using the IMPACT model. These simulations have been constrained by aircraft observations made during the SOLVE/THESEO 2000 campaign. A complete set of winter-long simulations was run for several different microphysical and PSC formation scenarios. The simulations give us perfect knowledge of PSC type (Ia, Ib, or II), composition, especially condensed phase HNO3 which is important for denitrification, and condensed phase H2O. Comparisons are made between the simulation and observation of PSC extinction at 1018 rim versus wavelength dependence, winter-long percentages of Ia and Ib occurrence, and temporal and altitude trends of the PSCs. These comparisons allow us to comment on how realistic some modeling scenarios are.

Strawa, A. W.↗
DOE OSTI2022

Mechanism for particle fractionalization and universal edge physics in quantum Hall fluids

Abstract Advancing a microscopic framework that rigorously unveils the underlying topological hallmarks of fractional quantum Hall (FQH) fluids is a prerequisite for making progress in the classification of strongly-coupled topological matter. We present a second-quantization framework that reveals an exact fusion mechanism for particle fractionalization in FQH fluids, and uncovers the fundamental structure behind the condensation of non-local operators characterizing topological order in the lowest-Landau-level. We show the first exact analytic computation of the quasielectron Berry connections leading to its fractional charge and exchange statistics, and perform Monte Carlo simulations that numerically confirm the fusion mechanism for quasiparticles. We express the sequence of (bosonic and fermionic) Laughlin second-quantized states, highlighting the lack of local condensation, and present a rigorous constructive subspace bosonization dictionary for the bulk fluid. Finally, we establish universal long-distance behavior of edge excitations by formulating a conjecture based on the DNA, or root state, of the FQH fluid.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1997

Determining Functional Reliability of Pyrotechnic Mechanical Devices

This paper describes a new approach for evaluating mechanical performance and predicting the mechanical functional reliability of pyrotechnic devices. Not included are other possible failure modes, such as the initiation of the pyrotechnic energy source. The requirement of hundreds or thousands of consecutive, successful tests on identical components for reliability predictions, using the generally accepted go/no-go statistical approach routinely ignores physics of failure. The approach described in this paper begins with measuring, understanding and controlling mechanical performance variables. Then, the energy required to accomplish the function is compared to that delivered by the pyrotechnic energy source to determine mechanical functional margin. Finally, the data collected in establishing functional margin is analyzed to predict mechanical functional reliability, using small-sample statistics. A careful application of this approach can provide considerable cost improvements and understanding over that of go/no-go statistics. Performance and the effects of variables can be defined, and reliability predictions can be made by evaluating 20 or fewer units. The application of this approach to a pin puller used on a successful NASA mission is provided as an example.

Bement, Laurence J.↗
DOE OSTI2021

Multiscale Modeling Meets Machine Learning: What Can We Learn?

Machine learning is increasingly recognized as a promising technology in the biological, biomedical, and behavioral sciences. There can be no argument that this technique is incredibly successful in image recognition with immediate applications in diagnostics including electrophysiology, radiology, or pathology, where we have access to massive amounts of annotated data. However, machine learning often performs poorly in prognosis, especially when dealing with sparse data. This is a field where classical physics-based simulation seems to remain irreplaceable. In this review, we identify areas in the biomedical sciences where machine learning and multiscale modeling can mutually benefit from one another: Machine learning can integrate physics-based knowledge in the form of governing equations, boundary conditions, or constraints to manage ill-posted problems and robustly handle sparse and noisy data; multiscale modeling can integrate machine learn- ing to create surrogate models, identify system dynamics and parameters, analyze sensitivities, and quantify uncertainty to bridge the scales and understand the emergence of function. With a view towards applications in the life sciences, we discuss the state of the art of combining machine learning and multiscale modeling, identify applications and opportunities, raise open questions, and address potential challenges and limitations. We anticipate that it will stimulate discussion within the community of computational mechanics and reach out to other disciplines including mathematics, statistics, computer science, artificial intelligence, biomedicine, systems biology, and precision medicine to join forces towards creating robust and efficient models for biological systems.

machine learning, multiscale modeling, physics-bas↗
DOE OSTI2024

Vascular Carbon/Carbon composites for concentrated solar power

Due to their exceptional mechanical and thermal properties under high temperature conditions, for the first time, a novel vascular (embedded channels) Carbon/Carbon (C/C) composite was developed for use as a modular concentrated solar power (CSP) gas receiver. The fabrication process involves the combination of the vaporization of sacrificial component (VaSC) technique with conventional methods to produce C/C composites with well preserved channels. Different heat treatments were evaluated together with X-ray diffraction (XRD) analysis to determine optimal fabrication conditions that maintains the material and channel’s integrity. Mechanical testing confirms that structural integrity is maintained, with statistical analyses indicating no compromise in flexural strength or modulus. Furthermore, this research introduces an innovative pathway for efficient CSP gas receivers, which can bridge the gap towards improved energy generation efficiency in next-gen CSP plants through higher operating temperatures with the use of C/C composites.

14 SOLAR ENERGY↗
DOE OSTI2025

Atomic-scale secondary electron imaging for heterogeneous catalysis research

Surface characterization at the atomic scale is essential for understanding the catalytic properties of supported metal nanoparticles. Secondary electron (SE) imaging in scanning transmission electron microscopy (STEM) provides three-dimensional surface topographic information, enabling the characterization of the size, morphology, and distribution of supported nanoparticles. Furthermore, real-time observation of catalyst materials in a gaseous environment would enhance the understanding of catalyst dynamics under operational conditions. Ongoing technical developments in SE-STEM and advancements in computational methods are expected to facilitate atomic-scale surface observations and enable more quantitative and statistical analyses. This progress will not only elucidate fundamental mechanisms at the atomic level but also provide comprehensive and universal insights into catalyst performances. Here, this minireview showcases the recent advancements and research findings in surface-sensitive SE imaging in STEM for the characterization of active catalyst materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Feedback in the dark: a critical examination of CMB bounds on primordial black holes

Abstract If present in the early universe, primordial black holes (PBHs) would have accreted matter and emitted high-energy photons, altering the statistical properties of the Cosmic Microwave Background (CMB). This mechanism has been used to constrain the fraction of dark matter that is in the form of PBHs to be much smaller than unity for PBH masses well above one solar mass. Moreover, the presence of dense dark matter mini-halos around the PBHs has been used to set even more stringent constraints, as these would boost the accretion rates.In this work, we critically revisit CMB constraints on PBHs taking into account the role of the local ionization of the gas around them. We discuss how the local increase in temperature around PBHs can prevent the dark matter mini-halos from strongly enhancing the accretion process, in some cases significantly weakening previously derived CMB constraints. We explore in detail the key ingredients of the CMB bound and derive a conservative limit on the cosmological abundance of massive PBHs.

Astronomy & Astrophysics↗
DOE OSTI2021

Angular Momentum Removal by Neutron and γ-Ray Emissions during Fission Fragment Decays

In this work, we investigate the angular momentum removal from fission fragments (FFs) through neutron and γ-ray emission, finding that about half the neutrons are emitted with angular momenta ≥ 1.5 ℏ and that the change in angular momentum after the emission of neutrons and statistical γ rays is significant, contradicting usual assumptions. Per fission event, in our simulations, the neutron and statistical γ-ray emissions change the spin of the fragment by 3.5 – 5 ℏ , with a large standard deviation comparable to the average value. Such wide angular momentum removal distributions can hide any underlying correlations in the fission fragment initial spin values. Within our model, we reproduce data on spin measurements from discrete transitions after neutron emissions, especially in the case of light FFs. The agreement further improves for the heavy fragments if one removes from the analysis the events that would produce isomeric states. Finally, we show that while in our model the initial FF spins do not follow a sawtoothlike behavior observed in recent measurements, the average FF spin computed after neutron and statistical γ emissions exhibits a shape that resembles a sawtooth. This suggests that the average FF spin measured after statistical emissions is not necessarily connected with the scission mechanism as previously implied.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data

Abstract. Geological records of past environmental change provide crucial insights into long-term climate variability, trends, non-stationarity, and nonlinear feedback mechanisms. However, reconstructing spatiotemporal fields from these records is statistically challenging due to their sparse, indirect, and noisy nature. Here, we present PaleoSTeHM, a scalable and modern framework for spatiotemporal hierarchical modeling of paleo-environmental data. This framework enables the implementation of flexible statistical models that rigorously quantify spatial and temporal variability from geological data while clearly distinguishing measurement and inferential uncertainty from process variability. We illustrate its application by reconstructing temporal and spatiotemporal paleo-sea-level changes across multiple locations. Using various modeling and analysis choices, PaleoSTeHM demonstrates the impact of different methods on inference results and computational efficiency. Our results highlight the critical role of model selection in addressing specific paleo-environmental questions, showcasing the PaleoSTeHM framework's potential to enhance the robustness and transparency of paleo-environmental reconstructions.

58 GEOSCIENCES↗
NASA NTRS1988

Nickel and chromium isotopes in Allende inclusions

High-precision nickel and chromium isotopic measurements were carried out on nine Allende inclusions. It is found that Ni-62, Ni-64, excesses are present in at least three of the samples. The results suggest that the most likely mechanism for the anomalies is a neutron-rich statistical equilibrium process. An indication of elevated Ni-60 is found in almost every inclusion measured. This effect is thought to be related to the decay of now extinct Fe-60. An upper limit of 1.6 X 10 to the -6th is calculated for the Fe-60/Fe-56 ratio at the time these Allende inclusions crystallized.

Birck, J. L.↗
NASA NTRS1988

Transfer and redistribution of polarized light in resonance lines. I - Quantum formulation with collisions

Equations are derived quantum mechanically for the radiative transfer of polarized light and statistical equilibrium governing the formation of resonance lines in nonhydrogenic species. Redistribution due to collisions is specifically included, but magnetic fields are neglected. The formulation accounts for excited level interference and optical pumping and is applicable to solar resonance lines such as Ca II H and K and Mg II h and k.

Streater, A.↗
NASA NTRS1996

An Experimental Determination of Losses in a 3-Port Wave Rotor

Wave rotors, used in a gas turbine topping cycle, offer a potential route to higher specific power and lower specific fuel consumption. In order to exploit this potential properly, it is necessary to have some realistic means of calculating wave rotor performance, taking losses into account, so that wave rotors can be designed for good performance. This in turn requires a knowledge of the loss mechanisms. The experiment reported here was designed as a statistical experiment to identify the losses due to finite passage opening time, friction, and leakage. For simplicity, the experiment used a 3-port, flow divider, wave cycle, but the results should be applicable to other cycles. A 12 inch diameter rotor was used, with two different lengths, 9 inches and 18 inches, and two different passage widths, 0.25 inch and 0.54 inch, in order to vary friction and opening time. To vary leakage, moveable end-walls were provided so that the rotor to end-wall gap could be adjusted. The experiment is described, and the results are presented, together with a parametric fit to the data. The fit shows that there will be an optimum passage width for a given wave rotor, since, as the passage width increases, friction losses decrease, but opening-time losses increase, and vice-versa. Leakage losses can be made small at reasonable gap sizes.

Wilson, Jack↗
NASA NTRS1996

Experiences From NASA/Langley's DMSS Project

There is a trend in institutions with high performance computing and data management requirements to explore mass storage systems with peripherals directly attached to a high speed network. The Distributed Mass Storage System (DMSS) Project at the NASA Langley Research Center (LaRC) has placed such a system into production use. This paper will present the experiences, both good and bad, we have had with this system since putting it into production usage. The system is comprised of: 1) National Storage Laboratory (NSL)/UniTree 2.1, 2) IBM 9570 HIPPI attached disk arrays (both RAID 3 and RAID 5), 3) IBM RS6000 server, 4) HIPPI/IPI3 third party transfers between the disk array systems and the supercomputer clients, a CRAY Y-MP and a CRAY 2, 5) a "warm spare" file server, 6) transition software to convert from CRAY's Data Migration Facility (DMF) based system to DMSS, 7) an NSC PS32 HIPPI switch, and 8) a STK 4490 robotic library accessed from the IBM RS6000 block mux interface. This paper will cover: the performance of the DMSS in the following areas: file transfer rates, migration and recall, and file manipulation (listing, deleting, etc.); the appropriateness of a workstation class of file server for NSL/UniTree with LaRC's present storage requirements in mind the role of the third party transfers between the supercomputers and the DMSS disk array systems in DMSS; a detailed comparison (both in performance and functionality) between the DMF and DMSS systems LaRC's enhancements to the NSL/UniTree system administration environment the mechanism for DMSS to provide file server redundancy the statistics on the availability of DMSS the design and experiences with the locally developed transparent transition software which allowed us to make over 1.5 million DMF files available to NSL/UniTree with minimal system outage

Source record↗