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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.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

GMLS-Nets: A Framework for Learning from Unstructured Data

Data fields sampled on irregularly spaced points arise in many applications in the sciences and engineering. For regular grids, Convolutional Neural Networks (CNNs) have been successfully used to gaining benefits from weight sharing and invariances. We generalize CNNs by introducing methods for data on unstructured point clouds based on Generalized Moving Least Squares (GMLS). GMLS is a nonparametric technique for estimating linear bounded functionals from scattered data, and has recently been used in the literature for solving partial differential equations. By parameterizing the GMLS estimator, we obtain learning methods for operators with unstructured stencils. In GMLS-Nets the necessary calculations are local, readily parallelizable, and the estimator is supported by a rigorous approximation theory. We show how the framework may be used for unstructured physical data sets to perform functional regression to identify associated differential operators and to regress quantities of interest. The results suggest the architectures to be an attractive foundation for data-driven model development in scientific machine learning applications.

42 ENGINEERING↗
DOE OSTI2019

GMLS-Nets: Scientific Machine Learning Methods for Unstructured Data

Data fields sampled on irregularly spaced points arise in many applications in the sciences and engineering. For regular grids, Convolutional Neural Networks (CNNs) have been successfully used to gaining benefits from weight sharing and invariances. We generalize CNNs by introducing methods for data on unstructured point clouds based on Generalized Moving Least Squares (GMLS). GMLS is a nonparametric technique for estimating linear bounded functionals from scattered data, and has recently been used in the literature for solving partial differential equations. By parameterizing the GMLS estimator, we obtain learning methods for operators with unstructured stencils. In GMLS-Nets the necessary calculations are local, readily parallelizable, and the estimator is supported by a rigorous approximation theory. We show how the framework may be used for unstructured physical data sets to perform functional regression to identify associated differential operators and to regress quantities of interest. The results suggest the architectures to be an attractive foundation for data-driven model development in scientific machine learning applications

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

GMLS-Nets: A Framework for Learning from Unstructured Data

Data fields sampled on irregularly spaced points arise in many applications in the sciences and engineering. For regular grids, Convolutional Neural Networks (CNNs) have been successfully used to gaining benefits from weight sharing and invariances. We generalize CNNs by introducing methods for data on unstructured point clouds based on Generalized Moving Least Squares (GMLS). GMLS is a non-parametric technique for estimating linear bounded functionals from scattered data, and has recently been used in the literature for solving partial differential equations. By parameterizing the GMLS estimator, we obtain learning methods for operators with unstructured stencils. In GMLS-Nets the necessary calculations are local, readily parallelizable, and the estimator is supported by a rigorous approximation theory. We show how the framework may be used for unstructured physical data sets to perform functional regression to identify associated differential operators and to regress quantities of interest. The results suggest the architectures to be an attractive foundation for data-driven model development in scientific machine learning applications

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Topic modeling to discern irregular order patterns in unlabeled electronic health records

This paper presents an application of topic modeling on event sequences of Electronic Health Record (EHR) orders. Metaphorically, we approach clinical order event sequences of unlabeled data as if they are documents where words are the events that occurred in the history of an order. We demonstrate the approach leveraging Consult orders data. The details of the data preprocessing and the data structures are described along with the data sources. Latent Dirichlet Allocation (LDA) is leveraged to fit against the limited datasets prepared. Another open source tool – LDAvis is used for exploratory analysis of the LDA results. The preliminary results revealed some order patterns that are qualitatively evaluated as potential irregular transitions. The goal of this analysis is to provide unsupervised learning application to domain experts in the absence of labeled data where they can investigate captured patterns and identify irregular transitions of orders. Ultimately, such efforts will guide formalization of hazard detection algorithms that monitor EHR data to identify health information technology related hazards.

Ozmen, Ozgur↗
DOE OSTI2015

Nonlinear plasma experiments in geospace with gigawatts of RF power at HAARP

The ionosphere is the ionized uppermost layer of our atmosphere (from 70 – 500 km altitude) where free electron densities yield peak critical frequencies in the HF (3 – 30 MHz) range. The ionosphere thus provides a quiescent plasma target, stable on timescales of minutes, for a whole host of active plasma experiments. High power RF experiments on ionospheric plasma conducted in the U.S. have been reported since 1970. The largest HF transmitter built to date is the HAARP phased-array HF transmitter near Gakona, Alaska which can deliver up to 3.6 Gigawatts (ERP) of CW RF power in the range of 2.8 – 10 MHz to the ionosphere with microsecond pointing, power modulation, and frequency agility. With an ionospheric background thermal energy in the range of only 0.1 eV, this amount of power gives access to the highest regimes of the nonlinearity (RF intensity to thermal pressure) ratio. HAARP’s unique features have enabled the conduct of a number of unique nonlinear plasma experiments in the interaction region of overdense ionospheric plasma including generation of artificial aurorae, artificial ionization layers, VLF wave-particle interactions in the magnetosphere, parametric instabilities, stimulated electromagnetic emissions (SEE), strong Langmuir turbulence (SLT) and suprathermal electron acceleration. Diagnostics include the Modular UHF Ionospheric Radar (MUIR) sited at HAARP, the SuperDARN-Kodiak HF radar, spacecraft radio beacons, HF receivers to record stimulated electromagnetic emissions (SEE) and telescopes and cameras for optical emissions. We report on short timescale ponderomotive overshoot effects, artificial field-aligned irregularities (AFAI), the aspect angle dependence of the intensity of the HF-enhanced plasma line, and production of suprathermal electrons. One of the primary missions of HAARP, has been the generation of ELF (300 – 3000 Hz) and VLF (3 – 30 kHz) radio waves which are guided to global distances in the Earth-ionosphere waveguide. We review recent efforts to improve the efficiency of the generation ELF/VLF and develop alternative mechanisms that do not require a natural ionospheric current. Applications include the controlled study of ionospheric irregularities affecting spacecraft communication and navigation systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

MAPredict: Static Analysis Driven Memory Access Prediction Framework for Modern CPUs

Application memory access patterns are crucial in deciding how much traffic is served by the cache and forwarded to the dynamic random-access memory (DRAM). However, predicting such memory traffic is difficult because of the interplay of prefetchers, compilers, parallel execution, and innovations in manufacturer-specific micro-architectures. This research introduced MAPredict, a static analysis-driven framework that addresses these challenges to predict last-level cache (LLC)-DRAM traffic. By exploring and analyzing the behavior of modern Intel processors, MAPredict formulates cache-aware analytical models. MAPredict invokes these models to predict LLC-DRAM traffic by combining the application model, machine model, and user-provided hints to capture dynamic information. MAPredict successfully predicts LLC-DRAM traffic for different regular access patterns and provides the means to combine static and empirical observations for irregular access patterns. Evaluating 130 workloads from six applications on recent Intel micro-architectures, MAPredict yielded an average accuracy of 99% for streaming, 91% for strided, and 92% for stencil patterns. By coupling static and empirical methods, up to 97% average accuracy was obtained for random access patterns on different micro-architectures.

Monil, M. A. H.↗
DOE OSTI2013

SIPMaP: A Tool for Modeling Irregular Parallel Computations in the Super Instruction Architecture

Performance modeling is becoming an increasingly important part of the parallel application development process, particularly for expensive computations that will be run on very high-end systems where resources are scarce. We describe a performance modeling tool SIPMaP (Super Instruction Processor Modeling and Prediction) developed for the Super-Instruction Architecture (SIA). The SIA is designed for applications where the dominant data structures are large multi-dimensional arrays and it comprises a DSL, the Super-Instruction Assembly Language (SIAL) that supports expressing algorithms in terms of blocks (tiles), and its runtime system Super Instruction Processor (SIP) that manages distribution and disk storage of the arrays. SIPMaP generates performance models from the SIAL source code. In comparison with many applications where useful performance models have been developed and reported, these programs are irregular and have other difficult to model characteristics such as extensive overlapping of communication and computation.

Computer Science↗
DOE OSTI2016

Sci-Thur PM – Brachytherapy 06: 3D Printed Surface Applicators for High Dose Rate Brachytherapy

Purpose: The purpose of this work is to develop a new applicator for administering high dose rate (HDR) brachytherapy using 3D printing technology. Primary advantages of using a 3D printed applicator will be to offer a more streamlined approach for therapists and patients while achieving better conformity, reproducibility, and patient specific applicators. Methods: A phantom study was conducted to measure the effectiveness of a 3D printed surface applicator by analyzing tumours on three locations of the body: the foot, nose, and scalp. The applicator was designed using Eclipse and further modified using Blender to create the catheter tunnels before being printed on a Lulzbot Taz 5 3D printer. A radiation plan was made using Oncentra Brachytherapy for a control treatment option using Freiburg Flaps and one with the novel method of a 3D printed applicator. A comparative analysis was made using D90, D100, V100, V150, and V200 Results: The 3D printed applicator showed comparable dose coverage with significant improvements on highly irregular surfaces when analyzed against a plan made using Freiburg Flaps. Although both plans exhibited complete tumour coverage, the 3D applicator showed improvements in D90 and V150 and the 3D applicator had a dose homogeneity index (DHI) of 0.99 compared to a DHI of 0.97 for the control. Therapist prep time also dropped significantly due to the lack of need for a thermoplastic mesh. Conclusions: 3D printed applicators for treatment of superficial sites proved to offer more patient convenience, less prep time, better conformity and tighter margins.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1987

Nonuniform sampling techniques for antenna applications

A two-dimensional sampling technique, which can employ irregularly spaced samples (amplitude and phase) in order to generate the complete far-field patterns is presented. The technique implements a matrix inversion algorithm, which depends only on the nonuniform sampled data point locations and with no dependence on the actual field values at these points. A powerful simulation algorithm is presented to allow a real-life simulation of many reflector/feed configurations and to determine the usefulness of the nonuniform sampling technique for the copolar and cross-polar patterns. Additionally, an overlapped window concept and a generalized error simulation model are discussed to identify the stability of the technique for recovering the field data among the nonuniform sampled data. Numerical results are tailored for the pattern reconstruction of a 20-m offset reflector antenna operating at L-band. This reflector is planned to be used in a proposed measurement concept of large antenna aboard the Space Shuttle, whereby it would be almost impractical to accurately control the movement of the Shuttle with respect to the RF source in prescribed directions in order to generate uniform sampled points. Also, application of the nonuniform sampling technique to patterns obtained using near-field measured data is demonstrated. Finally, results of an actual far-field measurement are presented for the construction of patterns of a reflector antenna from a set of nonuniformly distributed measured amplitude and phase data.

Rahmat-Samii, Yahya↗
DOE OSTI2014

SU-E-T-601: Output Factor Calculation of Irregular Shape Electron Cutout at Extended SSD

Purpose: To calculate the output factor of irregular shape electron beam at extended SSD using modified lateral build-up-ratio method. Methods: Circular cutouts from 2.0cm diameter to maximum possible sizes were prepared for applicator cone size of 15×15cm. In addition, different irregular cutouts were prepared. Percentage depth dose (PDD) curves were measured for each cutout using 6, 9, 12 and 16-MeV at the standard SSD of 100cm. The scanning was done using Multidata system and Scanditronix diodes on 2100SC Varian LINAC. In addition, for each cutout and electron beam energy doses were measured at SSD values of 100, 105, 110, 115cm using EDR2 films and diodes. Results: The measured PDD were normalized to the depth of 1.0mm. The lateral build-up-ratio (LBR) and the lateral scatter parameter (sigma) were calculated for each circular cutout using the open 15X15-cm2 field as the reference field. Taking the linear increase of sigma with cutout size into account, PDD of the irregular cutouts were calculated at 100 cm SSD. Furthermore, using the dose measured at different SSDs, the effective SSD value for each circular cutout and electron beam energy was determined. Employing the LBR and the effective-SSD values of the circular cutouts along with the calculated PDD of the irregular cutouts, the output factors of the irregular cutout at different extended SSD values were calculated. Finally, the calculated output factors were compared with the measured values. Conclusion: In this research, it is shown that output factor of irregular shape electron beam at extended SSD can be determined by using the LBR and the effective SSD values of circular cutouts. The percentage difference of the calculated output factor from the measured output factor for irregular cutouts at extended SSD were within 3.0%.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

SU-E-T-248: Determining Output Factor of Irregular Electron Cutouts at Extended SSD

Purpose: To calculate the output factor (OPF) of any irregularly shaped electron beam at extended SSD Methods: Using Cerrobend block, circular cutouts with diameter ranging from 2.0cm to the maximum possible size for 15×15 applicator of Varian 2100C and 14×14 applicator of ELEKTA Synergy LINACs were prepared. In addition, two irregular cutouts were made. For each cutout, percentage depth dose (PDD) at standard SSD and point doses at different SSD were measured in water using Scanditronix diodes and PTW 0.125 cm{sup 3} ion-chambers, respectively. In addition, the distance at which electron fluence along the central axis becomes independent of cutout size was determined using EDR2 films. On each LINAC, electron beam energies of 6, 9, 12, and 15/20 MeV were used. Results: Using the open applicator as the reference field, the lateral buildup ratio (LBR) for each circular cutout as a function of depth was calculated. From the LBR value and radius of the cutout, the corresponding lateral spread parameter (σR(z)) was determined. Taking the cutout side dependence of σR(z)) into account, PDD of the irregular cutouts at the standard SSD were calculated. From the point dose measurement at different SSDs, the effective SSD of each cutout was calculated. Taking the calculated PDD of the irregular cutout and effective SSD (SSDeff) of the circular cutout into account, OPFs of the irregular cutout at extended SSD values were calculated. Finally, the calculated output factors were compared with the measured values. Conclusion: In this research, the improved LBR method has been generalized to calculate output factor of irregular cutouts at extended SSD. In a clinically useful region, the percentage difference between the measured and the calculated output factors of the irregular cutouts was within 2%. Similar results were obtained for all available electron energies of both Varian 2100C and ELEKTA Synergy machines.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

Environmental Impact Assessment in the Visegrad Group countries

Highlights: • Comparison and evaluation of EIA systems in the V4 countries are presented. • Strengths and weaknesses of EIA systems based on a questionnaire survey are stated. • The function and efficiency of the EIA application in the V4 countries are analysed. • Irregularities and shortcomings of EIA systems in the V4 should be eliminated. The Environmental Impact Assessment Directive (EIA Directive) has created a reference framework for the implementation of the system of Environmental Impact Assessment (EIA) into the legal systems of the Member States of the European Union, including the countries belonging to the Visegrad Group (V4): Poland, Slovakia, the Czech Republic and Hungary. The Directive was the basis for the introduction of compulsory stages of the EIA process in the V4. The stages were then adapted to national requirements, including thresholds of the qualifying criteria of projects at the screening and scoping stages. The EIA system in the analysed countries has been growing, changing and being modified together with the political and economic changes of the last 30 years. Although all Visegrad Group countries are members of the EU and should harmonize the provisions of the EIA Directive and its amendments, there still exist singularities in each country's national EIA legislation, in terms of complementarities among the V4 countries, access to information resources, protection of natural resources, mitigation of socio-environmental impacts, or transboundary impact assessment. The article compares and evaluates the EIA systems in the four countries, specifies similarities and differences in the implementation of administrative proceedings and points out opportunities to strengthen the system. It presents selected results of a study conducted in 2013 within the framework of the international project “Assessment of the quality of the environment in the V4 Countries” (AQE V4). This paper indicates examples of good practice in the EIA systems and the obtained results are compared regarding the amendments to the current European Union EIA Directive.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Real-Time Degradation Estimation Approach for Batteries in PV and Battery Hybrid Plant Operation

Conventional cyclic degradation assessment for batteries is often limited in its ability to provide real-time degradation information during operation, because the estimation of degradation is commonly performed after a specific evaluation period. Modified methods can provide real-time evaluation but at the cost of high computation complexity. This paper proposes a novel estimation method that addresses these limitations. It efficiently determines the incremental degradation of any two consecutive state-of-charge (SOC) samples during battery operation, thus enabling real-time estimation. To validate the proposed method, measurement data from lithium-ion phosphate (LFP) battery testing was adopted, and the results were compared with the conventional model and the measured capacity. The results demonstrate accuracy over the evaluation period in terms of cumulative degradation, and a reduced computation cost compared with other methods. This approach has benefits in various applications, especially in cases where batteries experience irregular charging and discharging stress cycles such as PV and battery hybrid plants.

Wang, Shumeng↗