Search NASA⌕ Search

SEARCH · Search NASA

Results for “INGESTION”

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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The effects of allelochemical transfer on the dynamics of hosts, parasitoids, and competing hyperparasitoids

Allelochemicals produced by plants may be ingested by herbivorous insects and transferred to higher trophic levels with potentially deleterious effects. We develop a system of differential equations to investigate the effect of the transfer of allelochemicals, such as nicotine, on the population dynamics of a system of hosts, parasitoids, and two competing hyperparasitoids that attack different life stages of the parasitoids. We find both somewhat deleterious effects of nicotine on the larvae-attacking hyperparasitoids and increased attack rates for the pupae-attacking hyperparasitoids can promote coexistence. We also use an evolutionary game-theoretic approach to determine the optimal distribution of hyperparasitoid attacks among nicotine-producing and nicotine-free plants. With strong deleterious effects of nicotine and increased attack rates for the pupae-attacking hyperparasitoid, we find both species attack parasitoids on the nicotine-free plant but only pupae-attacking hyperparasitoids attack parasitoids on the nicotine-producing plant.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Calibrating constitutive models with full‐field data via physics informed neural networks

Abstract The calibration of solid constitutive models with full‐field experimental data is a long‐standing challenge, especially in materials that undergo large deformations. In this paper, we propose a physics‐informed deep‐learning framework for the discovery of hyperelastic constitutive model parameterizations given full‐field surface displacement data and global force‐displacement data. Contrary to the majority of recent literature in this field, we work with the weak form of the governing equations rather than the strong form to impose physical constraints upon the neural network predictions. The approach presented in this paper is computationally efficient, suitable for irregular geometric domains, and readily ingests displacement data without the need for interpolation onto a computational grid. A selection of canonical hyperelastic material models suitable for different material classes is considered including the Neo–Hookean, Gent, and Blatz–Ko constitutive models as exemplars for general non‐linear elastic behaviour, elastomer behaviour with finite strain lock‐up, and compressible foam behaviour, respectively. We demonstrate that physics informed machine learning is an enabling technology and may shift the paradigm of how full‐field experimental data are utilized to calibrate constitutive models under finite deformations.

Hamel, Craig M.↗
DOE OSTI2021

Evaluating the Effects of Transient Purge Flow on Stator-Rotor Seal Performance

Abstract As modern engine designs target higher efficiencies through increased turbine inlet temperatures, critical turbine components are at increased risk of damage from conditions exceeding material melting temperatures. In particular, improperly designed underplatform hardware components are susceptible to damage when hot main gas path flow is ingested into the stator-rotor cavity. While all turbines inherently experience transients during operation, a majority of publicly available turbine studies have been executed using steady operating conditions or inherently transient “blowdown” rigs. For this reason, routine transient events are not well understood. To address this need, the present study utilized a combined experimental and computational approach. The test article is a continuous-duration, one-stage test turbine operating with true-scale engine hardware and seal geometries at engine-representative flow conditions. The nature of the continuous-duration facility uniquely supports the direct assessment of transient events through its ability to transition between steady-state operating conditions. The effects of a transient purge flow were investigated in this study to identify general trends for transient events in a full-scale engine. Results from multiple measurement techniques in the wheelspace region show an interdependence of transient purge flow with a thermal lag of the underplatform hardware. Through experiments conducted at different coolant-to-main gas path temperature ratios, the use of pressure measurements as an indicator of fully purged behavior was introduced, and a thermally driven influence on rim seal performance was quantified. The computational results show good agreement with experimental pressure measurements and provide insight into the physical mechanisms that drive the relationship between pressure and sealing effectiveness measurements observed for the tested geometry.

Engineering↗
DOE OSTI2021

SQL and NoSQL Databases for Cyber Physical Production Systems in Internet of Things for Manufacturing (IoTfM)

Abstract In this paper, the design and performance differences between Relational Database Management Systems (RDBMS) and NoSQL Database Systems are examined, with attention to their applicability for real-world Internet of Things for manufacturing (IoTfM) data. While previous work has extensively compared SQL and NoSQL for both generalized and IoT uses, this work specifically examines the tradeoffs and performance differences for manufacturing applications by using a high-fidelity data set collected from a large US manufacturing firm. Growing an IoT system beyond the pilot stage requires scalable data storage; this work seeks to determine the impact of selected database systems on data write performance at scale. Payload size and message frequency were used as the primary characteristics to maintain model fidelity in simulated clients. As the number of simulated asset clients grow, the data write latency was calculated to determine how both database systems’ performance were affected. To isolate the RDBMS and NoSQL differences, a cloud environment was created using Amazon Web Services (AWS) with two identical data ingestion pipelines: writing data to an RDMBS (1) using AWS Aurora MySQL, and (2) using AWS DynamoDB NoSQL. The findings may provide guidance for further experimentation in large-scale manufacturing IoT implementations.

Gamero, David↗
DOE OSTI2016

Interfractional variation in bladder volume and its impact on cervical cancer radiotherapy: Clinical significance of portable bladder scanner

Purpose: A constant bladder volume (BV) is essential to direct the radiotherapy (RT) of pelvic tumors with precision. The purpose of this study was to investigate changes in BV and their impact on cervical cancer RT and to assess the clinical significance of a portable bladder scanner (BS) in achieving a constant BV. Methods: A standard bladder phantom (133 ml) and measurements of actual urine volume were both used as benchmarks to evaluate the accuracy of the BS. Comparisons of BS with computed tomography (CT), cone-beam CT (CBCT), and an ultrasound diagnostic device (iU22) were made. Twenty-two consecutive patients with cervical cancer treated with external beam radical RT were divided into an experimental group (13 patients) and a control group (9 patients). In the experimental group, the BV was measured multiple times by BS pre-RT until it was consistent with that found by planning CT. Then a CBCT was performed. The BV was measured again immediately post-RT, after which the patient’s urine was collected and recorded. In the control group, CBCT only was performed pre-RT. Interfractional changes in BV and their impact on cervical cancer RT were investigated in both groups. The time of bladder filling was also recorded and analyzed. Results: In measuring the volume of the standard bladder phantom, the BS deviated by 1.4% in accuracy. The difference between the measurements of the BS and the iU22 had no statistical significance (linear correlation coefficient 0.96, P < 0.05). The BV measured by the BS was strongly correlated with the actual urine volume (R = 0.95, P < 0.05), planning CT (R = 0.95, P < 0.05), or CBCT (R = 0.91, P < 0.05). Compared with the BV at the time of CT, its value changed by −36.1% [1 SD (standard deviation) 42.3%; range, −79.1%–29.4%] in the control group, and 5.2% (1 SD 21.5%; range, −13.3%–22.1%) in the experimental group during treatment. The change in BV affected the target position in the superior–inferior (SI) direction but had little or no effect in the anterior–posterior and right–left directions. Based on the collected data, the target displacement in the SI direction was reduced from 2.0 to 0.4 mm, while the CTV-to-PTV (CTV: clinical target volume; PTV: planning target volume) margin in the SI direction was reduced from 11.1 to 6.4 mm. The BV increased by 3.7 ± 1.0 ml/min (range, 1.7–4.7 ml/min), which depended on the amount of water ingested by the patient (R = 0.96, P < 0.05). No correlation was found between the rate of urinary inflow and the patient’s body mass. The authors were able to reduce the workload of measuring by using individual patient information including the patient’s age, the water-drinking amount, time at which water-drinking began, and patient’s diet. Conclusions: Changes in the BV have an influence on the RT of cervical cancer. A consistent and reproducible BV is acquired by using a portable BS, whereby the target displacement and CTV-to-PTV margin can be both reduced in the SI direction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-P-24: Radiological Disperse Device

Purpose: We are now living in a society of constant fear of terrorism. This topic is pertaining to give a general knowledge of what is a radiological dispersion device or RDD and in case of its detonation, what are the options open to public for a safe action in terms of reducing the exposure and knowing the proper steps. These RDD are also called dirty bombs. Methods: Compared to nuclear weapons, dirty bombs are easy to make. In order for a terrorist organization to construct and detonate a dirty bomb, it must acquire radioactive material by stealing it or buying it through legal or illegal channels. Possible RDD material could come from the millions of radioactive sources used in the industry, for medical purposes and in academic applications mainly for researches. These are, americium-{sup 241}, californium-{sup 252}, caesium-{sup 137}, cobalt-{sup 60}, iridium-{sup 192}, plutonium-{sup 238}, polonium-{sup 210}, radium-{sup 226} and strontium-{sup 90}. Results: Prompt detection of the type of radioactive material used will greatly assist advising people on the protective measures, like sheltering in place, or quickly leaving the immediate area. The effects of radiation are determined by:°the amount of radiation absorbed by body°the type of radiation °the distance from the radiation to an individual°the means of exposure absorbed by the skin, inhaled, or ingested; and length of time exposed. Conclusion: In any facility it is now much more important to keep a log list of all radioactive materials in use. In case there is a dirty bomb explosion, the chaos and economic cost could be enormous. The economic cost for the evaluation of the contamination, survey of people and surroundings and the after treatment, decontamination cost and effort will be a big challenge in any country. So awareness and preparation is the start to face this new type of challenge.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

3,3’-Diindolylmethane Exhibits Significant Metabolism After Oral Dosing in Humans

3,3’-Diindolylmethane (DIM), a major phytochemical derived from ingestion of cruciferous vegetables such as Brussels sprouts, is also a dietary supplement. In preclinical models, DIM is an effective cancer chemopreventive agent and has been studied in a number of clinical trials. Previous pharmacokinetic studies in preclinical and clinical models have not reported DIM metabolites in plasma or urine following oral dosing and the pharmacological actions of DIM on target tissues is assumed to be solely via the parent compound. Seven subjects (6 males and 1 female) ranging from 26-65 years of age, on a cruciferous vegetable-restricted diet prior to and during the study, took 2 BioResponse-DIM® 150 mg capsules (45.3 mg DIM/capsule) in the evening for one week with a final dose the morning of the first blood draw. A complete time course was performed with plasma and urine collected over 48 hours and analyzed by UPLC-MS/MS. In addition to parent DIM, two mono-hydroxylated (2-ox- and 3-methylenehydroxy-DIM) and 1 dihydroxylated (3-methylenehydroxy-2-ox-DIM) metabolites, along with their sulfate and glucuronide conjugates, were present in both plasma and urine. The results reported here are indicative of significant phase 1 and phase 2 metabolism and differ from previous pharmacokinetic studies in rodents and humans which reported only parent DIM present following oral administration.

Vermillion-Maier, Monica↗
DOE OSTI2021

Cellulosome Localization Patterns Vary across Life Stages of Anaerobic Fungi

Anaerobic fungi ( Neocallimastigomycota ) isolated from the guts of herbivores excel at degrading ingested plant matter, making them attractive potential platform organisms for converting waste biomass into valuable products, such as chemicals and fuels. Major contributors to their biomass-hydrolyzing power are the multienzyme cellulosome complexes that anaerobic fungi produce, but knowledge gaps in how cellulosome production is controlled by the cellular life cycle and how cells spatially deploy cellulosomes complicate the use of anaerobic fungi and their cellulosomes in industrial bioprocesses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Toward the Detection of Polyglot Files

Standardized file types play a key role in the development and use of computer software. However, it is possible to confound standardized file type processing by creating a file that is valid in multiple file types. The resulting polyglot (many languages) file can confuse file type identification, allowing elements of the file to evade analysis. This is especially problematic for malware detection systems that rely on file type identification for feature extraction. Although work has been done to identify file types using more comprehensive methods than file signatures, accurate identification of polyglot files remains an open problem. Since malware detection systems routinely perform file type-specific feature extraction, polyglot files need to be filtered out prior to ingestion by these systems. Otherwise, malicious content could pass through undetected. To address the problem of polyglot detection we assembled a data set using the mitra tool. We then evaluated the performance of the most commonly used file identification tools, including file, polydet, binwalk, and TrID. Our analysis demonstrates that existing file type detection tools fail to provide reliable polyglot detection. We then evaluated the ability of a range of machine and deep learning models to detect polyglot files. The most performant models were MalConv2 and Catboost, which demonstrated the highest recall on our data set with 95.16% and 95.45%, respectively. These models outperformed existing methods and could be incorporated into a malware detector’s file processing pipeline to filter out potentially malicious polyglots before file type-dependent feature extraction takes place.

Koch, Luke↗
DOE OSTI2022

Toward the Detection of Polyglot Files

Standardized file types play a key role in the development and use of computer software. However, it is possible to confound standardized file type processing by creating a file that is valid in multiple file types. The resulting polyglot (many languages) file can confuse file type identification, allowing elements of the file to evade analysis. This is especially problematic for malware detection systems that rely on file type identification for feature extraction. Although work has been done to identify file types using more comprehensive methods than file signatures, accurate identification of polyglot files remains an open problem. Since malware detection systems routinely perform file type-specific feature extraction, polyglot files need to be filtered out prior to ingestion by these systems. Otherwise, malicious content could pass through undetected. To address the problem of polyglot detection we assembled a data set using the mitra tool. We then evaluated the performance of the most commonly used file identification tools, including file, polydet, binwalk, and TrID. Our analysis demonstrates that existing file type detection tools fail to provide reliable polyglot detection. We then evaluated the ability of a range of machine and deep learning models to detect polyglot files. The most performant models were MalConv2 and Catboost, which demonstrated the highest recall on our data set with 95.16% and 95.45%, respectively. These models outperformed existing methods and could be incorporated into a malware detector’s file processing pipeline to filter out potentially malicious polyglots before file type-dependent feature extraction takes place.

Koch, Lucas↗
DOE OSTI2025

I/O in Machine Learning Applications on HPC Systems: A 360-degree Survey

Growing interest in Artificial Intelligence (AI) has resulted in a surge in demand for faster methods of Machine Learning (ML) model training and inference. This demand for speed has prompted the use of high performance computing (HPC) systems that excel in managing distributed workloads. Because data is the main fuel for AI applications, the performance of the storage and I/O subsystem of HPC systems is critical. In the past, HPC applications accessed large portions of data written by simulations or experiments or ingested data for visualizations or analysis tasks. ML workloads perform small reads spread across a large number of random files. This shift of I/O access patterns poses several challenges to modern parallel storage systems. In this paper, we survey I/O in ML applications on HPC systems, and target literature within a 6-year time window from 2019 to 2024. We define the scope of the survey, provide an overview of the common phases of ML, review available profilers and benchmarks, examine the I/O patterns encountered during offline data preparation, training, and inference, and explore I/O optimizations utilized in modern ML frameworks and proposed in recent literature. Lastly, we seek to expose research gaps that could spawn further R&D.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Slycat v 2.0

Slycat™ is a web-based system for analysis of large, high-dimensional data such as that produced by High Performance Computing (HPC) platforms. The Slycat™ server integrates data ingestion, scalable analysis, data management, and visualization with commodity web clients using a multi-tiered hierarchy of data and model storage. Analysis inputs are pushed or pulled into Slycat™, where models are generated and analysis artifacts are stored in a project database. These artifacts are the basis for visualizations that are delivered to users’ desktops through ordinary web browsers, eliminating the need to build and deploy platform-specific client applications. Slycat™ currently provides four types of analysis: canonical correlation analysis (CCA) to model relationships between inputs and output metrics, time series analysis featuring clustering and comparative visualization of waveforms, parameter space visualization including remote retrieval of images and movies from HPC disks, and VideoSwarm for modeling video similarities over time.

Letter, Matthew↗
DOE OSTI2013

Python-ARM Radar Toolkit

The Python-ARM Radar Toolkit (Py-ART) is a collection of radar quality control and retrieval codes which all work on two unifying Python objects: the PyRadar and PyGrid objects. By building ingests to several popular radar formats and then abstracting the interface Py-ART greatly simplifies data processing over several other available utilities. In addition Py-ART makes use of Numpy arrays as its primary storage mechanism enabling use of existing and extensive community software tools.

Jonathan Helmus, ScottCollis↗
DOE OSTI2017

Soil Carbon Data: long tail recovery

The software is intended to be part of an open source effort regarding soils data. The software provides customized data ingestion scripts for soil carbon related data sets and scripts for output databases that conform to common templates.

Source record↗
DOE OSTI2019

DynamiteNSM

DynamiteNSM is a free Network Security Monitor (NSM), built on top of several leading, enterprise-grade technologies. The tool provides network and cybersecurity operators with holistic insights into their networks while giving them the ability to deep-dive into lower-level activities. The solution presents powerful dashboards, giving comprehensive view into performance and threat-based metrics. Dynamite-NSM can be easily deployed in different environments including high-speed data centers, small-to-large enterprises, IoT & industrial networks, and even at home. Dynamite-NSM handles massive volumes of network traffic through scalable ingestion and optimized network sensors. The solution includes two key components: the agent and the monitor. The agent analyzes and forwards network events, while the monitor processes incoming events and displays analytic information. The monitor component builds upon the OpenSearch stack and is coupled with network packet inspection by Zeek and Suricata. Dynamite-NSM is designed to be deployed very quickly with minimal configuration. Unlike many other tools, it can be installed and managed with a standalone command-line utility. The system is inherently passive without disruption to the network. There is no need to install agents on every computer, perform network scans, or directly interact with network assets.

Becker, Jamin↗
DOE OSTI2020

Splash-ML v0.1

The Splash database and portal, also under development (https://lbl.wellspringsoftware.net/kms/invention/detail/3980/), ingests experimental data and references to datasets from a variety of sources, primarily lightsource beamlines. After deployment, it will contain a great deal of metadata and references to data from which many insights can be extracted.

McReynolds, Dylan↗
DOE OSTI2019

Diventi

Diventi provides a write optimized index of network logs such as netflow or zeek. The program will ingest various network traffic logs (zeek connection logs or NetflowV5, v9 or IPFix logs) and index each IP address and time of its activity. This database can then be queried for timely tracking of network activity. It currently uses the ft-index library from Percona but is adaptable to any key-value store that supports the Berkeley DB api.SAND2019-15037 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Kroeger, Thomas↗
DOE OSTI2012

MyEMSL

MyEMSL provides the following features: user-assisted upload of data from scientific instruments to an archive, tracking data though the upload process, providing metadata for recovery of uploaded data, providing users with access to the data. These features are supplied by a mixture of open source software and internally developed software. MyESML also provides a notification system that allows the system to communicate with users and other parts of the MyEMSL system. This allows the system to support automated workflows and user interaction. Reprocessing of already ingested data is also supported.

Glass, Kevin↗