Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Data Digitization”

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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-E-T-226: Correction of a Standard Model-Based Dose Calculator Using Measurement Data

Purpose: To propose a hybrid method that combines advantages of the model-based and measurement-based method for independent dose calculation. Modeled-based dose calculation, such as collapsed-cone-convolution/superposition (CCCS) or the Monte-Carlo method, models dose deposition in the patient body accurately; however, due to lack of detail knowledge about the linear accelerator (LINAC) head, commissioning for an arbitrary machine is tedious and challenging in case of hardware changes. On the contrary, the measurement-based method characterizes the beam property accurately but lacks the capability of dose disposition modeling in heterogeneous media. Methods: We used a standard CCCS calculator, which is commissioned by published data, as the standard model calculator. For a given machine, water phantom measurements were acquired. A set of dose distributions were also calculated using the CCCS for the same setup. The difference between the measurements and the CCCS results were tabulated and used as the commissioning data for a measurement based calculator. Here we used a direct-ray-tracing calculator (ΔDRT). The proposed independent dose calculation consists of the following steps: 1. calculate D-model using CCCS. 2. calculate D-ΔDRT using ΔDRT. 3. combine Results: D=D-model+D-ΔDRT. Results: The hybrid dose calculation was tested on digital phantoms and patient CT data for standard fields and IMRT plan. The results were compared to dose calculated by the treatment planning system (TPS). The agreement of the hybrid and the TPS was within 3%, 3 mm for over 98% of the volume for phantom studies and lung patients. Conclusion: The proposed hybrid method uses the same commissioning data as those for the measurement-based method and can be easily extended to any non-standard LINAC. The results met the accuracy, independence, and simple commissioning criteria for an independent dose calculator.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Analyzing shear band formation with high resolution X-ray diffraction

Localization of crystallographic slip into shear bands during uniaxial compression of a copper single crystal is studied using very far-field high-energy diffraction microscopy (vff-HEDM). Diffracted intensity was collected in-situ as the crystal deformed using a unique mobile detector stage that provided access to multiple diffraction peaks with high-angular resolution. From the diffraction data, single crystal orientation pole figures (SCPFs) were generated and are used to track the evolution of the distribution of lattice orientation that develops as slip localizes. To aid the identification of 'signatures' of shear band formation and analyze the SCPF data, a model of slip-driven lattice reorientation within shear bands is introduced. Confidence is built in conclusions drawn from the SCPF data about the character of internal slip localization through comparisons with strain fields on the sample surface measured simultaneously using digital image correlation. From the diffraction data, we find that the active slip direction and slip plane are not directly aligned with the orientation of the shear bands that formed. In fact, by extracting the underlying slip system activity from the SCPF data, we show that intersecting shear bands measured on the surface of the sample arise from slip primarily on the same underlying single slip system. These new vff-HEDM results raise significant questions on the use of surface measurements for slip system activity estimation. (C) 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optimal sensor placement for reconstructing wind pressure field around buildings using compressed sensing

Deciding how to optimally deploy sensors in a large, complex, and spatially extended structure is critical to ensure that the surface pressure field is accurately captured for subsequent analysis and design. In some cases, reconstruction of missing data is required in downstream tasks such as the development of digital twins. Here, this paper presents a data-driven sparse sensor selection algorithm, aiming to provide the most information contents for reconstructing aerodynamic characteristics of wind pressures over tall building structures parsimoniously. The algorithm first fits a set of basis functions to the training data, then applies a computationally efficient QR algorithm that ranks existing pressure sensors in order of importance based on the state reconstruction to this tailored basis. The findings of this study show that the proposed algorithm successfully re- constructs the aerodynamic characteristics of tall buildings from sparse measurement locations, generating stable and optimal solutions across a range of conditions. As a result, this study serves as a promising first step toward leveraging the success of data-driven and machine learning algorithms to supplement traditional genetic algorithms currently used in wind engineering.

42 ENGINEERING↗
DOE OSTI2025

Quantum frequency resampling

In signal processing, resampling algorithms can modify the number of resources encoding a collection of data points. Downsampling reduces the cost of storage and communication, while upsampling interpolates new data from limited one, e.g., when resizing a digital image. We present a toolset of quantum algorithms to resample data encoded in the probabilities of a quantum register, using the quantum Fourier transform to adjust the number of high-frequency encoding qubits. We discuss advantage over classical resampling algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Harmonized Database of Western U.S. Water Rights (HarDWR) v.1

Abstract In the arid and semi-arid Western U.S., access to water is regulated through a legal system of water rights. Individuals, companies, organizations, municipalities, and tribal entities have documents that declare their water rights. State water regulatory agencies collate and maintain these records, which can be used in legal disputes over access to water. While these records are publicly available data in all Western U.S. states, the data have not yet been readily available in digital form from all states. Furthermore, there are many differences in data format, terminology, and definitions between state water regulatory agencies. Here, we have collected water rights data from 11 Western U.S. state agencies, harmonized terminology and use definitions, formatted them for consistency, and tied them to a Western U.S.-wide shapefile of water administrative boundaries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Data acquisition system for the Baikal-GVD neutrino telescope

The objective of the Baikal-GVD project is the construction of a km{sup 3}-scale neutrino telescope in Lake Baikal. The Gigaton Volume Detector consists of a large three-dimensional array of photo-multiplier tubes. The first GVD-cluster has been deployed and commissioned in April 2015. The data acquisition system (DAQ) of the detector takes care of the digitization of the photo-multiplier tube signals, data transmission, filtering and storage. The design and the implementation of the data acquisition system are described.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

TListSpectrum

TListSpectrum is a C++ class developed inside the CERN high-energy physics analysis C++ framework ROOT. This class structure was developed to assist in the processing, visualization, and analysis of list-mode or time-stamped radiation spectroscopy data. The class structure currently contains parsing and functionality to synthesize list-mode data from CAEN and Mirion Lynx radiation spectroscopy digital acquisition systems along with feature functionality to post-process data sets and build coincident data sets from the instrument.

Pierson, Bruce↗
DOE OSTI2023

Harmonized Database of Western U.S. Water Rights (HarDWR)

From Lisk et al. (in review): "In the arid and semi-arid western U.S., access to water is regulated through a legal system of water rights. Individuals, companies, organizations, municipalities, and tribal entities have documents that declare their water rights. State water regulatory agencies collate and maintain these records, which can be used in legal disputes over access to water. While these records are publicly available data in all western U.S. states, the data have not yet been readily available in digital form from all states. Furthermore, there are many differences in data format, terminology, and definitions between state water regulatory agencies. Here, we have collected water rights data from 11 western U.S. state agencies, harmonized terminology and use definitions, formatted them consistently, and tied them to a western U.S.-wide shapefile of water administrative boundaries. We demonstrate how these data enable consistent regional-scale western U.S. hydrologic and economic modeling."

Economics↗
DOE OSTI2024

Harmonized Database of Western U.S. Water Rights (HarDWR)

From Lisk et al. (2024): "In the arid and semi-arid western U.S., access to water is regulated through a legal system of water rights. Individuals, companies, organizations, municipalities, and tribal entities have documents that declare their water rights. State water regulatory agencies collate and maintain these records, which can be used in legal disputes over access to water. While these records are publicly available data in all western U.S. states, the data have not yet been readily available in digital form from all states. Furthermore, there are many differences in data format, terminology, and definitions between state water regulatory agencies. Here, we have collected water rights data from 11 western U.S. state agencies, harmonized terminology and use definitions, formatted them consistently, and tied them to a western U.S.-wide shapefile of water administrative boundaries. We demonstrate how these data enable consistent regional-scale western U.S. hydrologic and economic modeling."

Economics↗
DOE OSTI2018

Moving Beyond Data Paralysis to Effective use of Building Analytics

As digital controls and smart meters become commonplace in commercial buildings, facilities teams have access to overwhelming amounts of data. This data does not typically lead to insights and corrective actions unless it is analyzed and prioritized in automated ways. Analytic software has been commercially available for over 20 years, but only recently have these tools seen increased adoption. This monitoring infrastructure helps uncover hidden operational opportunities, which is enticing for decision makers looking for short paybacks. Rather than single project savings, monitoring-based commissioning (MBCx) provides tools and processes to implement persistent, continuous improvement. What was formerly a data onslaught is now becoming a controlled resource for improved energy management. In 2016, a Research and Industry Partnership program was launched to support the use of analytics and diagnostics technologies and MBCx practices. This program couples technical assistance to owners to help increase adoption with a data collection effort to inform industry. It includes the most comprehensive data available nationally on analytics installation and use. The first-year results are in, with data from 46 organizations representing over 185 million square feet and 2,300 buildings. These organizations have achieved a median year-over-year energy savings of $0.20/sq ft with a median first year technology implementation cost of $0.12/sq ft. The paper summarizes attributes of successful analytics and MBCx installations, and cost-effectiveness results. The research provides insight for utilities considering adopting analytics technologies into incentive programs, for analytics developers to improve the performance of their solutions, and for commercial building facility staff considering these technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

SU-F-J-183: Interior Region-Of-Interest Tomography by Using Inverse Geometry System

Purpose: The inverse geometry computed tomography (IGCT) composed of multiple source and small size detector has several merits such as reduction of scatter effect and large volumetric imaging within one rotation without cone-beam artifact, compared to conventional cone-beam computed tomography (CBCT). By using this multi-source characteristics, we intend to present a selective and multiple interior region-of-interest (ROI) imaging method by using a designed source on-off sequence of IGCT. Methods: All of the IGCT sources are operated one by one sequentially, and each projection in the shape of narrow cone-beam covers its own partial volume of full field of view (FOV) determined from system geometry. Thus, through controlling multi source operation, limited irradiation within ROI is possible and selective radon space data for ROI imaging can be acquired without additional X-ray filtration. With this feature, we designed a source on-off sequence for multi ROI-IGCT imaging, and projections of ROI-IGCT were generated by using the on-off sequence. Multi ROI-IGCT images were reconstructed by using filtered back-projection algorithm. All these imaging process of our study has been performed by utilizing digital phantom and patient CT data. ROI-IGCT images of the phantom were compared to CBCT image and the phantom data for the image quality evaluation. Results: Image quality of ROI-IGCT was comparable to that of CBCT. However, the distal axial-plane from the FOV center, large cone-angle region, ROI-IGCT showed uniform image quality without significant cone-beam artifact contrary to CBCT. Conclusion: ROI-IGCT showed comparable image quality and has the capability to provide multi ROI image within a rotation. Projection of ROI-IGCT is performed by selective irradiation, hence unnecessary imaging dose to non-interest region can be reduced. In this regard, it seems to be useful for diagnostic or image guidance purpose in radiotherapy such as low dose target localization and patient alignment. This research was supported by the Mid-career Researcher Program through NRF funded by the Ministry of Science, ICT & Future Planning of Korea (NRF-2014R1A2A1A10050270) and by the Radiation Technology R&D program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (No. 2013M2A2A7038291)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

ESTIMATING PHOTOMETRIC REDSHIFTS OF QUASARS VIA THE k-NEAREST NEIGHBOR APPROACH BASED ON LARGE SURVEY DATABASES

We apply one of the lazy learning methods, the k-nearest neighbor (kNN) algorithm, to estimate the photometric redshifts of quasars based on various data sets from the Sloan Digital Sky Survey (SDSS), the UKIRT Infrared Deep Sky Survey (UKIDSS), and the Wide-field Infrared Survey Explorer (WISE; the SDSS sample, the SDSS-UKIDSS sample, the SDSS-WISE sample, and the SDSS-UKIDSS-WISE sample). The influence of the k value and different input patterns on the performance of kNN is discussed. kNN performs best when k is different with a special input pattern for a special data set. The best result belongs to the SDSS-UKIDSS-WISE sample. The experimental results generally show that the more information from more bands, the better performance of photometric redshift estimation with kNN. The results also demonstrate that kNN using multiband data can effectively solve the catastrophic failure of photometric redshift estimation, which is met by many machine learning methods. Compared with the performance of various other methods of estimating the photometric redshifts of quasars, kNN based on KD-Tree shows superiority, exhibiting the best accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

An integrated data management and informatics framework for continuous drug product manufacturing processes: A case study on two pilot plants

The pharmaceutical industry continuously looks for ways to improve its development and manufacturing efficiency. In recent years, such efforts have been driven by the transition from batch to continuous manufacturing and digitalization in process development. To facilitate this transition, integrated data management and informatics tools need to be developed and implemented within the framework of Industry 4.0 technology. Here, in this regard, the work aims to guide the data integration development of continuous pharmaceutical manufacturing processes under the Industry 4.0 framework, improving digital maturity and enabling the development of digital twins. This paper demonstrates two instances where a data integration framework has been successfully employed in academic continuous pharmaceutical manufacturing pilot plants. Details of the integration structure and information flows are comprehensively showcased. Approaches to mitigate concerns in incorporating complex data streams, including integrating multiple process analytical technology tools and legacy equipment, connecting cloud data and simulation models, and safeguarding cyber-physical security, are discussed. Critical challenges and opportunities for practical considerations are highlighted.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

GOOML - Real World Applications of Machine Learning in Geothermal Operations

GOOML (Geothermal Operational Optimization with Machine Learning) is a machine-learning based framework that enables geothermal power plant operators to explore optimization opportunities for their assets in an efficient and robust digital environment. Backed by real-world data sources, thermodynamic constraints and steamfield intelligence, the GOOML environment provides new tools to explore how to best operate steamfields as well as test new scenarios and configurations prior to implementation in the field. To prove the effectiveness of GOOML, we have undertaken optimization experiments using reinforcement learning (RL) to generate operational suggestions using a balance of mass-take targets, sustainability considerations and net generation. Our experiments use the GOOML construct to explore different field parameters and perform multiple reinforcement learning experiments. Like a comprehensive laboratory workbench, we can change out components of a steamfield to perform testing under a variety of conditions (restrict mass, increase pressure, reroute steam, etc.). This flexibility allows us to explore conditions that would require significant infrastructure changes in a real-world setting at a fraction of the cost and time in a digital environment. The results highlight the benefits of using digital twins and advanced data analytics for the geothermal industry.

forecasting↗
DOE OSTI2017

Galaxy–Galaxy Weak-lensing Measurements from SDSS. I. Image Processing and Lensing Signals

We present our image processing pipeline that corrects the systematics introduced by the point-spread function (PSF). Using this pipeline, we processed Sloan Digital Sky Survey (SDSS) DR7 imaging data in r band and generated a galaxy catalog containing the shape information. Based on our shape measurements of the galaxy images from SDSS DR7, we extract the galaxy–galaxy (GG) lensing signals around foreground spectroscopic galaxies binned in different luminosities and stellar masses. We estimated the systematics, e.g., selection bias, PSF reconstruction bias, PSF dilution bias, shear responsivity bias, and noise rectification bias, which in total is between −9.1% and 20.8% at 2 σ levels. The overall GG lensing signals we measured are in good agreement with Mandelbaum et al. The reduced χ {sup 2} between the two measurements in different luminosity bins are from 0.43 to 0.83. Larger reduced χ {sup 2} from 0.60 to 1.87 are seen for different stellar mass bins, which is mainly caused by the different stellar mass estimator. The results in this paper with higher signal-to-noise ratio are due to the larger survey area than SDSS DR4, confirming that more luminous/massive galaxies bear stronger GG lensing signals. We divide the foreground galaxies into red/blue and star-forming/quenched subsamples and measure their GG lensing signals. We find that, at a specific stellar mass/luminosity, the red/quenched galaxies have stronger GG lensing signals than their counterparts, especially at large radii. These GG lensing signals can be used to probe the galaxy–halo mass relations and their environmental dependences in the halo occupation or conditional luminosity function framework.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Fractal dimension of optical cirrus in Stripe82

ABSTRACT The geometric characteristics of dust clouds provide important information on the physical processes that structure such clouds. One of such characteristics is the 2D fractal dimension D of a cloud projected on to the sky plane. In previous studies, which were mostly based on infrared (IR) data, the fractal dimension of individual clouds was found to be in a range from 1.1 to 1.7 with a preferred value of 1.2–1.4. In this work, we use data from Stripe82 of the Sloan Digital Sky Survey to measure the fractal dimension of the cirrus clouds. This is done here for the first time for optical data with significantly better resolution as compared to IR data. To determine the fractal dimension, the perimeter-area method is employed. We also consider IR (IRAS and Herschel) counterparts of the corresponding optical fields to compare the results between the optical and IR. We find that the averaged fractal dimension across all clouds in the optical is $\langle D \rangle =1.69^{+0.05}_{-0.05}$ which is significantly larger than the fractal dimension of its IR counterparts $\langle D\rangle =1.38^{+0.07}_{-0.06}$. We examine several reasons for this discrepancy (choice of masking and minimal contour level, image and angular resolution, etc.) and find that for approximately half of our fields the different angular resolution (point spread function) of the optical and IR data can explain the difference between the corresponding fractal dimensions. For the other half of the fields, the fractal dimensions of the IR and visual data remain inconsistent, which can be associated with physical properties of the clouds, but further physical simulations are required to prove it.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Digital Twin Empowered PV Power Prediction

The accurate prediction of photovoltaic (PV) power generation is significant to ensure the economic and safe operation of power systems. To this end, the paper proposes a new digital twin (DT) empowered PV power prediction framework that is capable of ensuring reliable data transmission and employing the DT to achieve high accuracy of power prediction. With this framework, considering potential data contamination in the collected PV data, a generative adversarial network is employed to restore the historical data set, which offers a prerequisite to ensure accurate mapping from the physical space to the digital space. Further, a new DT empowered PV power prediction method is proposed. Therein, we model a DT that encompasses a digital physical model for reflecting the physical operation mechanism and a neural network model (i.e., a parallel network of convolution and bidirectional long-short-term memory model) for capturing the hidden spatial-temporal features. The proposed method enables the use of the DT to take advantages of the digital physical model and the neural network model, resulting in enhanced prediction accuracy. Finally, a real data set is conducted to access the effectiveness of the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2013

EXPLORING THE VARIABLE SKY WITH LINEAR. III. CLASSIFICATION OF PERIODIC LIGHT CURVES

We describe the construction of a highly reliable sample of ∼7000 optically faint periodic variable stars with light curves obtained by the asteroid survey LINEAR across 10,000 deg{sup 2} of the northern sky. The majority of these variables have not been cataloged yet. The sample flux limit is several magnitudes fainter than most other wide-angle surveys; the photometric errors range from ∼0.03 mag at r = 15 to ∼0.20 mag at r = 18. Light curves include on average 250 data points, collected over about a decade. Using Sloan Digital Sky Survey (SDSS) based photometric recalibration of the LINEAR data for about 25 million objects, we selected ∼200,000 most probable candidate variables with r < 17 and visually confirmed and classified ∼7000 periodic variables using phased light curves. The reliability and uniformity of visual classification across eight human classifiers was calibrated and tested using a catalog of variable stars from the SDSS Stripe 82 region and verified using an unsupervised machine learning approach. The resulting sample of periodic LINEAR variables is dominated by 3900 RR Lyrae stars and 2700 eclipsing binary stars of all subtypes and includes small fractions of relatively rare populations such as asymptotic giant branch stars and SX Phoenicis stars. We discuss the distribution of these mostly uncataloged variables in various diagrams constructed with optical-to-infrared SDSS, Two Micron All Sky Survey, and Wide-field Infrared Survey Explorer photometry, and with LINEAR light-curve features. We find that the combination of light-curve features and colors enables classification schemes much more powerful than when colors or light curves are each used separately. An interesting side result is a robust and precise quantitative description of a strong correlation between the light-curve period and color/spectral type for close and contact eclipsing binary stars (β Lyrae and W UMa): as the color-based spectral type varies from K4 to F5, the median period increases from 5.9 hr to 8.8 hr. These large samples of robustly classified variable stars will enable detailed statistical studies of the Galactic structure and physics of binary and other stars and we make these samples publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗