Search NASA⌕ Search

SEARCH · Search NASA

Results for “Computer Science - Operating Systems”

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 1,765 records · Page 98

Hydrate-filled Fracture Formation at Keathley Canyon 151, Gulf of Mexico, and Implications for Non-vent Sites

Near-vertical hydrate-filled fractures are found in subseafloor marine muds, at both advective methane vent sites and at sites without obvious methane and fluid advection (non-vent sites). At non-vent sites, the mechanisms that transport methane to the fractures and control how hydrate-filled fractures form are not well understood. However, these mechanisms are important to establish, as most of Earth's natural gas hydrate is likely bound in marine mud systems. In this work, we focus on understanding the origin of hydrate and how fracture form at non-vent sites by examining previously hydrate-bearing fractures in conventional cores taken from Keathley Canyon 151, U.S. northern Gulf of Mexico, drilled by the Gas Hydrate Joint Industry Project in 2005. We combine information from well logs, sediment cores, and science party results and add new X-ray computed tomography of archival sections and scanning electron microcopy of core samples to develop a conceptual model. We propose that locally generated microbial methane is transported via diffusion from small pores in marine mud into biomineralized burrows with larger pore size in a process called short-range migration. Hydrate forms in burrows once the methane diffuses into them and the dissolved methane concentration exceeds the solubility threshold. When hydrate fills a burrow, heave from additional hydrate growth places stress on the burrow edges, expands the fracture, and creates additional void space in which methane can diffuse and continue forming hydrate. Fractures slowly propagate in the direction of maximum principal stress.

58 GEOSCIENCES↗

Optimization of X-ray tomography through a cooperative computing system in grid

Cooperative Computing implemented as Cooperative Computing System (CCS) in grid has been proved a considerably reliable technique to execute the tasks with real time constraints in a grid environment. This technique can be applied in many high performance distributed computing applications. HPC has a large number of applications in various fields of physics. One such application in radiation physics is X-ray tomography. X-Ray tomography contains numerous applications in various fields of science, technology and research. As the technology is changing from analog to digital in almost all the scenarios, this paper presents an idea towards the attachment of X-ray tomography assembly to HPC environment so as to obtain the highly reliable optimization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory

The ability to track simulated cancer cells through the circulatory system, important for developing a mechanistic understanding of metastatic spread, pushes the limits of today's supercomputers by requiring the simulation of large fluid volumes at cellular-scale resolution. To overcome this challenge, we introduce a new adaptive physics refinement (APR) method that captures cellular-scale interaction across large domains and leverages a hybrid CPU-GPU approach to maximize performance. Through algorithmic advances that integrate multi-physics and multi-resolution models, we establish a finely resolved window with explicitly modeled cells coupled to a coarsely resolved bulk fluid domain. In this work we present multiple validations of the APR framework by comparing against fully resolved fluid-structure interaction methods and employ techniques, such as latency hiding and maximizing memory bandwidth, to effectively utilize heterogeneous node architectures. Collectively, these computational developments and performance optimizations provide a robust and scalable framework to enable system-level simulations of cancer cell transport.

59 BASIC BIOLOGICAL SCIENCES↗

Novel Proposals for FAIR, Automated, Recommendable, and Robust Workflows

Lightning talks of the Workflows in Support of Large-Scale Science (WORKS) workshop are a venue where the workflow community (researchers, developers, and users) can discuss work in progress, emerging technologies and frameworks, and training and education materials. This paper summarizes the WORKS 2022 lightning talks, which cover five broad topics: data integrity of scientific workflows; a machine learning-based recommendation system; a Python toolkit for running dynamic ensembles of simulations; a cross-platform, high-performance computing utility for processing shell commands; and a meta(data) framework for reproducing hybrid workflows.

Abhinit, Ishan↗

Symposium: Quantum Theory, Quantum Materials, Quantum Computing (Final Report, DE-SC0022551)

Quantum mechanics is fundamental to understanding, predicting, and controlling many physical processes in a vast range of scientific and technological areas. In molecules and materials, the quantum mechanics of Coulombic many-body systems determines far more than the ground state and bulk properties. Quantum mechanics governs magnetism, electron and spin transport, chemical reactions and catalysis, superconductivity, photosynthesis, etc. Each plays a vital role in modern society. As digital technologies push both temporal and length-scale limits, fundamental quantum principles become the current focus for a new class of technologies: quantum computing, quantum sensing, quantum encryption, etc. This oncoming quantum information sciences wave is manifest recently in frontier foci of all six Department of Energy Office of Science programs. The Sanibel Symposium offers a proven, influential platform for facilitating and advancing cross-fertilization among theoretical and computational chemists and physicists, computer scientists, and materials engineers. The Symposia have a long, successful record of driving progress on theory and computation of materials, nanostructures, and their molecular constituents. The Symposia thus are well-suited for advancing the quantum information science thrust in the Office of Basic Energy Sciences (BES). With that QIS thrust as the focus, we propose five sessions of the 61st Sanibel Symposium on the theme Quantum Theory, Quantum Materials, Quantum Computing. From a longer perspective, this thematic program for 2022 is the second year of a five year plan of program segments addressed at challenges in quantum information sciences and quantum materials. The rest of the Symposium program will be of considerable relevance, with, for example, sessions on quantum molecular and material dynamics, and new directions in coupled cluster theory. New ideas for methods and applications can be expected to emerge from the stimulus of the formal presentations and informal discussions. The proposed award is targeted at students, post-docs, and junior scientists. Conscious effort, characteristic of the Sanibel Symposia, to stimulate the participation of women and under-represented minorities will continue.

36 MATERIALS SCIENCE↗

Modeling graphene sheet growth and dynamical matrix calculations using molecular dynamics

Molecular dynamics (MD) has been an incredibly useful tool to model physical processes that were synthesized experimentally but not fully understood. MD, through the use of semi-empirical inter-atomic potentials, has allowed understanding of different physical processes in materials science. Yet as well as providing useful insights into materials science, molecular dynamics has a wider range of usability. In this report, I will be detailing how MD can be used to study graphene formation from a carbon liquid which requires high temperatures and pressures. Beyond this, I will describe the usefulness of MD for understanding the physics for phonon transport quantum sensors. To do this, MD was employed to determine the dynamical matrix by treating atoms as coupled oscillators. An accurate understanding of the dynamical matrix of a system is required to calculate the non-equilibrium Green’s function used to describe the phonon transport within phonon wave-guides. I found that, across multiple pressures and temperatures, randomly placed carbon atoms will show evidence of pent-first formation with semi-empirical models. Density functional theory (DFT), on the other hand, was too computationally expensive to use for full scale MD simulations, but we have the possibility of training a machine learned interatomic potential to approximate DFT for carbon in the environments being studied for pent-first graphene sheet formation.

36 MATERIALS SCIENCE↗

Robust High-Throughput Phenotyping with Deep Segmentation Enabled by a Web-Based Annotator

The abilities of plant biologists and breeders to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation, and particularly to collect this data at a high-throughput scale with low cost. Although deep learning methods have demonstrated unprecedented potential to automate plant phenotyping, these methods commonly rely on large training sets that can be time-consuming to generate. Intelligent algorithms have therefore been proposed to enhance the productivity of these annotations and reduce human efforts. We propose a high-throughput phenotyping system which features a Graphical User Interface (GUI) and a novel interactive segmentation algorithm: Semantic-Guided Interactive Object Segmentation (SGIOS). By providing a user-friendly interface and intelligent assistance with annotation, this system offers potential to streamline and accelerate the generation of training sets, reducing the effort required by the user. Our evaluation shows that our proposed SGIOS model requires fewer user inputs compared to the state-of-art models for interactive segmentation. As a case study of the use of the GUI applied for genetic discovery in plants, we present an example of results from a preliminary genome-wide association study (GWAS) of in planta regeneration in Populus trichocarpa (poplar). We further demonstrate that the inclusion of a semantic prior map with SGIOS can accelerate the training process for future GWAS, using a sample of a dataset extracted from a poplar GWAS of in vitro regeneration. The capabilities of our phenotyping system surpass those of unassisted humans to rapidly and precisely phenotype our traits of interest. The scalability of this system enables large-scale phenomic screens that would otherwise be time-prohibitive, thereby providing increased power for GWAS, mutant screens, and other studies relying on large sample sizes to characterize the genetic basis of trait variation. Our user-friendly system can be used by researchers lacking a computational background, thus helping to democratize the use of deep segmentation as a tool for plant phenotyping.

54 ENVIRONMENTAL SCIENCES↗

A swarm intelligence-based approach to anomaly detection of dynamic systems

Here we propose a novel Swarm Intelligence-based approach for anomaly detection of dynamic systems. Specifically, we consider observation processes for dynamic systems from a foraging perspective, and ant foraging behavior-based search techniques are applied to the discovery of the ‘intrinsic communication topology’ of systems. The key idea exploited here is that systems can be viewed as ‘communication networks’ where interconnected elements communicate with one another through physical phenomena and the elements ‘process’ the communications through their dynamics; this defines the ‘intrinsic communication topology’ of the system. The behaviors of individual elements can be at least partially observed in the dynamics of other communicating system elements and, hence, condition changes will be reflected in changes in the intrinsic communications. Anomaly detection is then performed by observing the changes in the intrinsic communication topology by tracking graph similarity measures and using change point detection to determine when statistically significant changes have occurred. The performance of the proposed approach is investigated in simulation where we consider a system composed of multiple networks, each with different topologies and connection strengths, and where the individual networks comprising the system can be switched at arbitrary times. The proposed methodology is applied to this system to detect the switches between the networks and to discover the communication topologies associated with each of the network configurations.

97 MATHEMATICS AND COMPUTING↗

A Numerical Simulation of Transport Phenomena During the Horizontal Single Belt Casting Process Using an Inclined Feeding System

Horizontal single belt casting (HSBC) has great potential to replace current conventional continuous casting (CCC) processes for sheet metal production, by directly casting 3 to 1 mm sheet for the automobile industry. In the present paper, two-dimensional mathematical models were developed to study transport phenomena, for the case of an inclined wall feeding system for a liquid aluminum wrought alloy (AA6111). Based on the commercial software ANSYS FLUENT 14.5 and user-defined functions, a two-layer turbulence model was used to examine the fluid flow emanating from a slot nozzle set above a water-cooled, high-speed, steel belt. The Volume of Fluid (VOF) method was used to predict the shape of the melt-air interface. A transformed coordinate system (x′, y′) was established in order to analyze the fluid flow on the inclined wall of the feeding system. The total pressure gauge gradient (∂p{sub total}/∂x) was used to describe the behavior of the melt film inside the slot nozzle of the head box. The modeling results show that during the melt film falling process, the total gauge pressure varies within the slot nozzle, which can decrease the stability of the falling film. The first impingement between the falling film and the inclined refractory wall of the feeding system gives rise to a local oscillation, and this influences the stability of the melt film moving downwards. At the rear meniscus position between the inclined wall and the moving belt, there is a clear vibration of the air-melt interface, together with a recirculation zone. The weak vibration of the air-melt interface could be induced by the periodic variation of the melt-air interface. Moreover, the formation of tiny air pockets is predicted. Finally, on the inclined wall of the feeding system, a suitable length of the transition area is needed to avoid over-acceleration of the melt film due to the force of gravity.

36 MATERIALS SCIENCE↗

Probing atomic-scale symmetry breaking by rotationally invariant machine learning of multidimensional electron scattering

Abstract The 4D scanning transmission electron microscopy (STEM) method maps the structure and functionality of solids on the atomic scale, yielding information-rich data sets describing the interatomic electric and magnetic fields, structural and electronic order parameters, and other symmetry breaking distortions. A critical bottleneck is the dearth of analytical tools that can reduce complex 4D-STEM data to physically relevant descriptors. We propose an approach for the systematic exploration of 4D-STEM data using rotationally invariant variational autoencoders (rrVAE), which disentangle the general rotation of the object from other latent representations. The implementation of purely rotational rrVAE is discussed as are applications to simulated data for graphene and zincblende structures. The rrVAE analysis of experimental 4D-STEM data of defects in graphene is illustrated and compared to the classical center-of-mass analysis. This approach is universal for probing symmetry-breaking phenomena in complex systems and can be implemented for a broad range of diffraction methods.

36 MATERIALS SCIENCE↗

Sampling lattices in semi-grand canonical ensemble with autoregressive machine learning

Calculating thermodynamic potentials and observables efficiently and accurately is key for the application of statistical mechanics simulations to materials science. However, naive Monte Carlo approaches, on which such calculations are often dependent, struggle to scale to complex materials in many state-of-the-art disciplines such as the design of high entropy alloys or multi-component catalysts. To address this issue, we adapt sampling tools built upon machine learning-based generative modeling to the materials space by transforming them into the semi-grand canonical ensemble. Furthermore, we show that the resulting models are transferable across wide ranges of thermodynamic conditions and can be implemented with any internal energy model U, allowing integration into many existing materials workflows. We demonstrate the applicability of this approach to the simulation of benchmark systems (AgPd, CuAu) that exhibit diverse thermodynamic behavior in their phase diagrams. Finally, we discuss remaining challenges in model development and promising research directions for future improvements.

36 MATERIALS SCIENCE↗

Octahedral to tetrahedral bonding transitions in the local structure of phase change optical media Ge 2 Sb 2 Se 5 x Te 5-5 x with Se doping

Random access memories utilize fast, reversible switching between ordered and disordered states of matter in phase change materials (PCMs) such as Ge2Sb2Te5-5x. The short-range structure in the disordered phase has been described either as (i) a network of Ge tetrahedra or (ii) Peierls distorted Ge/Sb octahedra. The PCM transition was investigated in bulk Ge2Sb2Se5xTe5-5x (GSST), in which amorphization sets in with Se doping (x ≈ 0.85) upon quenching. GSST has a hexagonal crystalline ground state with Ge/Sb octahedral coordination, but the phase change transition to the amorphous state that is only observed when the system is quenched brings a short-range structure with sharp, tetrahedrally coordinated Ge/Sb correlations and shortened bonds that are distinctly different from the expected octahedral pairing.

97 MATHEMATICS AND COMPUTING↗

Development of the high energy engineering X-ray (HEX) superconducting wiggler, magnetic measurement, installation, and commissioning

The High energy Engineering X-ray (HEX) diffraction beamline at the National Synchrotron Light Source II (NSLS-II) at Brookhaven National Lab (BNL) is the first high-energy beamline capable of reaching 200 keV for a monochromatic beam. With the 3 GeV electron beam energy for the NSLS-II ring, only the superconducting wiggler (SCW) producing greater than 4 T peak field can cover these ranges with a sufficient number of photons. The 1.2 m-long HEX-SCW has a period length of 70 mm and a field strength on-axis of 4.3 T. It utilizes no liquid helium, and the vertical aperture size of the electron beam vacuum chamber is 8 mm. Unlike regular undulators/wigglers, there is no standard configuration for the magnetic measurement system for superconducting insertion devices. The NSLS-II Insertion Devices group has developed, in collaboration with the vacuum group, a novel in-vacuum Hall mapper with a 1.75 m in-vacuum linear motor and an in-vacuum flip coil system utilizing many commercial-off-the-shelf products. The measurements were conducted at the BNL, and the device was installed in the ring and commissioned. Here, this paper provides a description of the SCW and its magnetic measurement systems, as well as a brief account of the installation and commissioning efforts.

36 MATERIALS SCIENCE↗

SU-E-T-66: A Prototype for Couch Based Real-Time Dosimetry in External Beam Radiotherapy

Purpose: The main purpose of this study is to design a prototype for couch-based based real time dosimetry system in external beam radiotherapy Methods: A prototype of 100 ionization chambers was designed on a printed circuit board by etching the copper layer and each ionization chamber was wired to a 50 pin connector. The signals from the two 50 pin connectors collected from the ionization chambers were then transferred to a PXI module from National Instruments. The PXI module houses a current amplifier that amplifies the charge collected from the ionization chamber. The amplified signal is then sent to a digital multimeter module for converting the analog signal to digital signal. A software was designed in labview to read and display the signals obtained from the PXI module. A couch attachment frame was designed to house the 100 ionization chamber module. The frame was fixed underneath the treatment couch for measuring the dose during treatment. Resutls: The ionization chamber based prototype dosimetry was tested for simple radiotherapy treatment fields and found to be a useful device for measuring real time dosimetry at the treatment couch plane. This information could be used to assess the delivered dose to a patient during radiotherapy. It could be used as an invivo dosimeter during radiotherapy. Conclusion: In this study, a prototype for couch based real time dosimetry system was designed and tested. The prototype forms a basis for the development of large scale couch based real time dosimetry system that could be used to perform morning QA prior to treatment, assess real time doses delivered to patient and as a device to monitor the output of the treatment beam. Peter MacCallum Cancer Foundation.

60 APPLIED LIFE SCIENCES↗

Source strength verification and quality assurance of preloaded brachytherapy needles using a CMOS flat panel detector

Purpose: Current methods of low dose rate brachytherapy source strength verification for sources preloaded into needles consist of either assaying a small number of seeds from a separate sample belonging to the same lot used to load the needles or performing batch assays of a subset of the preloaded seed trains. Both of these methods are cumbersome and have the limitations inherent to sampling. The purpose of this work was to investigate an alternative approach that uses an image-based, autoradiographic system capable of the rapid and complete assay of all sources without compromising sterility. Methods: The system consists of a flat panel image detector, an autoclavable needle holder, and software to analyze the detected signals. The needle holder was designed to maintain a fixed vertical spacing between the needles and the image detector, and to collimate the emissions from each seed. It also provides a sterile barrier between the needles and the imager. The image detector has a sufficiently large image capture area to allow several needles to be analyzed simultaneously.Several tests were performed to assess the accuracy and reproducibility of source strengths obtained using this system. Three different seed models (Oncura 6711 and 9011 {sup 125}I seeds, and IsoAid Advantage {sup 103}Pd seeds) were used in the evaluations. Seeds were loaded into trains with at least 1 cm spacing. Results: Using our system, it was possible to obtain linear calibration curves with coverage factor k = 1 prediction intervals of less than ±2% near the centre of their range for the three source models. The uncertainty budget calculated from a combination of type A and type B estimates of potential sources of error was somewhat larger, yielding (k = 1) combined uncertainties for individual seed readings of 6.2% for {sup 125}I 6711 seeds, 4.7% for {sup 125}I 9011 seeds, and 11.0% for Advantage {sup 103}Pd seeds. Conclusions: This study showed that a flat panel detector dosimetry system is a viable option for source strength verification in preloaded needles, as it is capable of measuring all of the sources intended for implantation. Such a system has the potential to directly and efficiently estimate individual source strengths, the overall mean source strength, and the positions within the seed-spacer train.

60 APPLIED LIFE SCIENCES↗

TH-EF-BRB-07: Novel Hardware and Software Platform for Intermediate Energy 4π Radiotherapy

Purpose: To develop a robust and efficient platform for the optimization and robotic delivery of highly noncoplanar intensity modulated radiotherapy, which enables significant reduction of normal tissue toxicity and escalation of tumor dose. Methods: An innovative high-output compact 3 MV linac was designed for mounting onto a commercial robotic system in order to access the entire 4π beam solution space without moving the patient couch. The use of intermediate energy X-rays for radiotherapy was evaluated in comparison to clinical plans delivered using 6 MV X-rays and a state-of-the-art delivery system. Monte Carlo simulations of a 3 MV percent depth dose curve were performed for intermediate energy dose calculation. The beam model was used to create a convolution/superposition-based dose calculation engine for 3MV X-rays. The 4π greedy column generation algorithm was used for optimized beam selection and fluence map optimization. Results: A detailed design of the first 3 MV linac capable of producing a competitively high dose rate of >800 cGy/min at 100 cm was completed and verified through extensive simulation. The complete linac head including a multileaf collimator can access most of the 4π solution space including the posterior orientations without changing the couch height. When compared to 6 MV clinical plans, the proposed 3 MV 4π plans demonstrated significantly better dose compactness and normal tissue sparing in brain, prostate, and partial breast treatment plans. Conclusion: We demonstrate the design of a highly versatile radiotherapy machine to natively deliver non-coplanar 4π radiotherapy without the need to move the patient during treatment. This novel platform is efficient and capable of providing dosimetry that is 30–50% more compact than existing therapy platforms. The new system is projected to be cost effective due to improved treatment time and automation. NIH R43CA183390, NIH R01CA188300.

60 APPLIED LIFE SCIENCES↗

Exact reconstruction of gene regulatory networks using compressive sensing

We consider the problem of reconstructing a gene regulatory network structure from limited time series gene expression data, without any a priori knowledge of connectivity. We assume that the network is sparse, meaning the connectivity among genes is much less than full connectivity. We develop a method for network reconstruction based on compressive sensing, which takes advantage of the network’s sparseness. For the case in which all genes are accessible for measurement, and there is no measurement noise, we show that our method can be used to exactly reconstruct the network. For the more general problem, in which hidden genes exist and all measurements are contaminated by noise, we show that our method leads to reliable reconstruction. In both cases, coherence of the model is used to assess the ability to reconstruct the network and to design new experiments. We demonstrate that it is possible to use the coherence distribution to guide biological experiment design effectively. By collecting a more informative dataset, the proposed method helps reduce the cost of experiments. For each problem, a set of numerical examples is presented. The method provides a guarantee on how well the inferred graph structure represents the underlying system, reveals deficiencies in the data and model, and suggests experimental directions to remedy the deficiencies.

59 BASIC BIOLOGICAL SCIENCES↗