Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “digital computing”

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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Vibration-Based Sensor Design: A Grey-Box Approach

Knowledge of the internal structure of an object or device under investigation proceeds from the basic idea of constructing its dynamic behavioral relations governed by a set of differential/algebraic equations that characterize its response. These equations can be partial differential equations leading to finite element or finite difference relations requiring a complex numerical solution on a super computer or ordinary differential equations requiring sophisticated numerical integration techniques to obtain the desired solution. Discrete dynamic systems evolving from digitized data acquisition are typically captured by sampled-data (continuous-to-discrete) representations characterized by a set of difference equations specifying the underlying system dynamics. In any case, with a mathematical description in hand, Grey-Box modeling techniques have evolved, concerned with the estimation of model parameters embedded in a prescribed set of equations (the system) governing its behavior, while capturing the underlying physical phenomenology of the problem at hand.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Data-Driven Passive Islanding Detection Scheme

This paper proposes a simple yet effective statistical parameters based passive islanding scheme. The proposed scheme relies only the voltage data, measured at the point of common coupling (PCC), and is comprised of three stages. The Stage-1 quickly computes what is termed as mean based coarse islanding detection (MID), Stage-2 computes the decaying DC detector (DDCD), and 3) finally, MID is used in conjunction with DDCD as per the statistical digital relay logic (SRDL) is devised in Stage-3 to distinguish between islanding events from non islanding events. Various tests are investigated on the Banshee's industrial Microgrid (MG), modelled in the Real Time Digital Simulator (RTDS), on the basis of the IEEE-1547, UL 1741 standards. The validation of the proposed islanding detection methodology (PIDM) in RTDS platform ensures the viability of the proposed scheme in practical systems. The test results reveal that the PIDM can detect islanding within 2 cycles, and results in a very small non detection zone (NDZ). Moreover, the scheme can very well be used for single-phase MG too as it relies only on the single phase voltage information.

anti-islanding protection↗
DOE OSTI2024

Advanced Data Science Model for Detecting Intelligent Malware

This study focused on developing a robust artificial intelligence (AI) model capable of detecting and characterizing advanced malware in Internet of Things (IoT) devices using network data. By analyzing network traffic with various machine learning (ML) models, our AI model can identify and characterize malicious activities to significantly improve malware detection accuracy and reliability as compared to traditional methods. The developed AI/ML model was trained using network data from IoT devices, leveraging classifiers such as Random Forest, Gradient Boosting, AdaBoost, and others to optimize detection performance. This project demonstrates a scalable framework for real-time malware detection and characterization in IoT networks, capable of identifying infected devices and facilitating the necessary steps to remove or isolate them, thereby preventing further infections. Although digital twin (DT) integration is not yet implemented in the current model, it represents a promising future enhancement. By creating a virtual replica of physical IoT devices, DT technology would allow for real-time monitoring and analysis without directly accessing operational technology, thus reducing the risk of compromising or reducing the performance of actual devices. This integration would further enhance the security of IoT ecosystems, combining AI technology to better flag and detect indications of malware-infected devices within a nuclear system environment.

42 ENGINEERING↗
DOE OSTI2014

SU-D-9A-03: STAMP: Simulator for Texture Analysis in MRI/PET

Purpose: To develop a convenient simulation platform to facilitate PET/MR image analysis with the prospect of gaining a better understanding of the influence of acquisition parameters on PET/MRI textural features. The simulation platform is demonstrated by showing textural variations of a representative case study using different image acquisition parameters. Methods: The simulation platform is composed of MRI simulators JEMRIS and SIMRI to achieve simulations of customized MRI sequences on sample tumor models. The PET simulator GATE is used to get 2D and 3D Monte Carlo acquisitions of voxelized PET sources using a phantom geometry and a customized scanner architecture. The platform incorporates a series of graphical user interfaces written in Matlab. Two GUIs are used to facilitate communication with the simulation executables installed on a computer cluster. A third GUI is used to collect and display the clinical and simulated images, as well as fused PET/MRI images, and perform computation of textural features.To illustrate the capabilities of this platform, one FDG-PET and T1-weighted (T1w) digitized tumor models were generated from clinical images of a soft-tissue sarcoma patient. Numerically simulated MR images were produced using 3 different echo times (TE) and 5 different repetition times (TR). PET 2D images were simulated using an OSEM algorithm with 1 to 32 iterations and a post-reconstruction Gaussian filter of 0, 2, 4 or 6 mm width. Results: STAMP was successfully used to produce numerically simulated FDG-PET and MRI images, and to calculate their corresponding textures. Three typical textures (GLCM-Contrast, GLSZM-ZSV and NGTDM-Coarseness) were found to vary by a range of 45% on average compared to reference scanning conditions in the case of FDG-PET, and by a range of 40% in the case of T1w MRI. Conclusion: We have successfully developed a Matlab-based simulation platform to facilitate PET/MRI texture image analysis for outcome prediction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

All Optical Neural Networks for Low Power Edge Computing

We developed a simplistic physics-based model of an all-optical neural network that mimics the encoder part of an autoencoder neural network for image compression. Our approach relies on the generation of a MATLAB-based model for both data compression and decompression and utilizes MATLAB's built-in autoencoder networks in combination with simple propagation of optical fields between layers constituting phase elements via Fourier transform. We optimize the phase elements using the particle swarm optimization technique and using our model, we demonstrate a compression ratio of 25% for 2828-pixel input images containing numeric digits from 0 to 9.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

MO-G-18A-01: Radiation Dose Reducing Strategies in CT, Fluoroscopy and Radiography

Advances in medical x-ray imaging have provided significant benefits to patient care. According to NCRP 160, there are more than 400 million x-ray procedures performed annually in the United States alone that contributes to nearly half of all the radiation exposure to the US population. Similar growth trends in medical x-ray imaging are observed worldwide. Apparent increase in number of medical x-ray imaging procedures, new protocols and the associated radiation dose and risk has drawn considerable attention. This has led to a number of technological innovations such as tube current modulation, iterative reconstruction algorithms, dose alerts, dose displays, flat panel digital detectors, high efficient digital detectors, storage phosphor radiography, variable filters, etc. that are enabling users to acquire medical x-ray images at a much lower radiation dose. Along with these, there are number of radiation dose optimization strategies that users can adapt to effectively lower radiation dose in medical x-ray procedures. The main objectives of this SAM course are to provide information and how to implement the various radiation dose optimization strategies in CT, Fluoroscopy and Radiography. Learning Objectives: To update impact of technological advances on dose optimization in medical imaging. To identify radiation optimization strategies in computed tomography. To describe strategies for configuring fluoroscopic equipment that yields optimal images at reasonable radiation dose. To assess ways to configure digital radiography systems and recommend ways to improve image quality at optimal dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

The miniJPAS survey quasar selection – I. Mock catalogues for classification

In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no representative sample of spectroscopically confirmed sources exists at present to train these ML algorithms, we rely on mock catalogues. In this first paper, we develop a pipeline to compute synthetic photometry of quasars, galaxies, and stars using spectra of objects targeted as quasars in the Sloan Digital Sky Survey . To match the same depths and signal-to-noise ratio distributions in all bands expected for miniJPAS point sources in the range 17.5 ≤ r < 24, we augment our sample of available spectra by shifting the original r-band magnitude distributions towards the faint end, ensure that the relative incidence rates of the different objects are distributed according to their respective luminosity functions, and perform a thorough modelling of the noise distribution in each filter, by sampling the flux variance either from Gaussian realizations with given widths, or from combinations of Gaussian functions. Finally, we also add in the mocks the patterns of non-detections which are present in all real observations. Although the mock catalogues presented in this work are a first step towards simulated data sets that match the properties of the miniJPAS observations, these mocks can be adapted to serve the purposes of other photometric surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Prospects for simulating a qudit-based model of (1+1)D scalar QED

We present a gauge invariant digitization of (1+1)d scalar quantum electrodynamics for an arbitrary spin truncation for qudit-based quantum computers. We provide a construction of the Trotter operator in terms of a universal qudit-gate set. Here, the cost savings of using a qutrit based spin-1 encoding versus a qubit encoding are illustrated. We show that a simple initial state could be simulated on current qutrit based hardware using noisy simulations for two different native gate set.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Registration of clinical volumes to beams-eye-view images for real-time tracking

Purpose: The authors combine the registration of 2D beam’s eye view (BEV) images and 3D planning computed tomography (CT) images, with relative, markerless tumor tracking to provide automatic absolute tracking of physician defined volumes such as the gross tumor volume (GTV). Methods: During treatment of lung SBRT cases, BEV images were continuously acquired with an electronic portal imaging device (EPID) operating in cine mode. For absolute registration of physician-defined volumes, an intensity based 2D/3D registration to the planning CT was performed using the end-of-exhale (EoE) phase of the four dimensional computed tomography (4DCT). The volume was converted from Hounsfield units into electron density by a calibration curve and digitally reconstructed radiographs (DRRs) were generated for each beam geometry. Using normalized cross correlation between the DRR and an EoE BEV image, the best in-plane rigid transformation was found. The transformation was applied to physician-defined contours in the planning CT, mapping them into the EPID image domain. A robust multiregion method of relative markerless lung tumor tracking quantified deviations from the EoE position. Results: The success of 2D/3D registration was demonstrated at the EoE breathing phase. By registering at this phase and then employing a separate technique for relative tracking, the authors are able to successfully track target volumes in the BEV images throughout the entire treatment delivery. Conclusions: Through the combination of EPID/4DCT registration and relative tracking, a necessary step toward the clinical implementation of BEV tracking has been completed. The knowledge of tumor volumes relative to the treatment field is important for future applications like real-time motion management, adaptive radiotherapy, and delivered dose calculations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Optical delay encoding for fast timing and detector signal multiplexing in PET

Purpose: The large number of detector channels in modern positron emission tomography (PET) scanners poses a challenge in terms of readout electronics complexity. Multiplexing schemes are typically implemented to reduce the number of physical readout channels, but often result in performance degradation. Novel methods of multiplexing in PET must be developed to avoid this data degradation. The preservation of fast timing information is especially important for time-of-flight PET. Methods: A new multiplexing scheme based on encoding detector interaction events with a series of extremely fast overlapping optical pulses with precise delays is demonstrated in this work. Encoding events in this way potentially allows many detector channels to be simultaneously encoded onto a single optical fiber that is then read out by a single digitizer. A two channel silicon photomultiplier-based prototype utilizing this optical delay encoding technique along with dual threshold time-over-threshold is demonstrated. Results: The optical encoding and multiplexing prototype achieves a coincidence time resolution of 160 ps full width at half maximum (FWHM) and an energy resolution of 13.1% FWHM at 511 keV with 3 × 3 × 5 mm{sup 3} LYSO crystals. All interaction information for both detectors, including timing, energy, and channel identification, is encoded onto a single optical fiber with little degradation. Conclusions: Optical delay encoding and multiplexing technology could lead to time-of-flight PET scanners with fewer readout channels and simplified data acquisition systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Coastal Ohio Wind Project for Reduced Barriers to Deployment of Offshore Wind Energy

The Coastal Ohio Wind Project was created to establish the viability of wind turbines on the coastal and offshore regions of Northern Ohio. The project’s main goal was to improve operational unit strategies used for environmental impact assessment of offshore turbines on lake wildlife by optimizing and fusing data from the multi-instrument surveillance system and providing an engineering analysis of potential design/operational alternatives for offshore wind turbines. The project also developed a general economic model for offshore WTG deployment to quantify potential revenue losses due to wind turbine shutdown related to ice and avian issues. In a previous phase of this project (Award Number: DE-FG36-06GO86096), we developed a surveillance system that was used to collect different parameters such as passage rates, flight paths, flight directions, and flight altitudes of nocturnal migrating species, movements of birds and bats, and bird calls for assessing patterns and peak passage rates during migration. To derive such parameters we used thermal IR imaging cameras, acoustic recorders, and marine radar Furuno (XANK250), which was coupled with a XIR3000B digitizing card from Russell Technologies and open source radR processing software. The integration yielded a development of different computational techniques and methods, which we further developed and optimized as a combined surveillance system. To accomplish this task we implemented marine radar calibration, optimization of processing parameters, and fusion of the multi-sensor data in order to make inferences about the potential avian targets. The main goal of the data fusion from the multi-sensor environment was aimed at reduction of uncertainties while providing acceptable confidence levels with detailed information about the migration patterns. Another component comprised of an assessment of wind resources in a near lake environment and an investigation of the effectiveness of ice coating materials to mitigate adverse effects of ice formation on wind turbine structures. Firstly, a Zephir LiDAR system was acquired and installed at Woodlands School in Huron, Ohio, which is located near Lake Erie. Wind resource data were obtained at ten measurement heights, 200m, 150m, 100m, 80m, 60m, 40m, 38m, 30m, 20m, and 10m. The Woodlands School’s wind turbine anemometer also measured the wind speed at the hub height. These data were collected for approximately one year. The hub anemometer data correlated well with the LiDAR wind speed measurements at the same height. The data also showed that on several days different power levels were recorded by the turbine at the same wind speed as indicated by the hub anemometer. The corresponding LiDAR data showed that this difference can be attributed to variability in the wind over the turbine rotor swept area, which the hub anemometer could not detect. The observation suggests that single point hub wind velocity measurements are inadequate to accurately estimate the power generated by a turbine at all times since the hub wind speed is not a good indicator of the wind speed over the turbine rotor swept area when winds are changing rapidly. To assess the effectiveness of ice coatings to mitigate the impact of ice on turbine structures, a closed-loop icing research tunnel (IRT) was designed and constructed. By controlling the temperature, air speed, water content and liquid droplet size, the tunnel enabled consistent and repeatable ice accretion under a variety of conditions with temperatures between approximately 0°C and -20°C and wind speeds up to 40 miles per hour in the tunnel’s test section. The tunnel’s cooling unit maintained the tunnel temperature within ±0.2°C. The coatings evaluated in the study were Boyd Coatings Research Company’s CRC6040R3, MicroPhase Coatings Inc.’s PhaseBreak TP, ESL and Flex coatings. Similar overall performance was observed in all coatings tested in that water droplets form on the test articles beginning at the stagnation region and spreading in the downstream direction in time. When comparing ice accumulation characteristics for the four coatings tested, for ice thickness during accumulation the CRC6040R3 had the least, followed by the ESL, Flex, and TP. However, when comparing the coatings’ ability to reduce ice adhesion, the Flex showed the highest adhesion reduction, followed by the ESL, TP and CRC 6040R3 coatings. The ice accumulated on the Flex coated surface shed under gravity when rotated 90 degrees following the tests while the other coatings required application of varying degrees of force to remove the ice. In conclusion, the ice coatings tested were not sufficient in preventing ice accumulation on all surfaces. However, Flex coating shows promise in mitigating ice on the rotor blades under the gravitational and centrifugal forces. Only the effect of gravity in shedding the ice was considered in this study. Further research will be needed to evaluate this coating on rotating blades in the icing tunnel to characterize its effectiveness. Lastly, the development of economic feasibility models used existing approaches adapted for offshore deployment in marine settings to one more suitable for Lake Erie deployment. Two different wind turbine models were tested and dynamic return on investment (ROI) model scenarios were generated. For the purpose of estimating power generation three bladed wind turbines of 3 MW capacity were selected including Model1- Leitwind LTW101-3.000-kW and Model2-Vostro V90-3.0 MW. The analysis were based on the revenue aspect of decision making of deploying wind turbines in the Ohio coastal region. The installation cost, maintenance and operational aspects were disregarded due to unavailability of data. The adjusted varying price (residential and industrial sector) and projected future price of electricity in different years suggested that the Leitwind model could generate $\$ $32.4 million of revenue in 25 years if the supply electricity is in the residential sector, while it would be $\$ $14.7million if the supply is in the industrial sector. For the Vostro model these figures are $\$ $28.6 million for residential sector and $\$ $12.9 million for industrial sector for 25 years.

17 WIND ENERGY↗
DOE OSTI2015

Responder Technology Alert Monthly (Oct-Nov 2014)

As part of technology foraging for the Responder Technology Alliance, established by the Department of Homeland Science and Technologies First Responders Group, this report summarizes technologies that are relevant in the area of “wearables,” with the potential for use by first responders. The content was collected over the previous month(s) and reproduced from a general Internet search using the term wearables. Additional information is available at the websites provided. This report is not meant to be an exhaustive list nor an endorsement of any technology described herein. Rather, it is meant to provide useful information about current developments in the areas wearable technology. The content is organized by technology function including: Sensors – Devices that detect physiological, particle, and chemical activity; Displays – Heads-up and body-worn visual displays; Power – Wearable power systems including chargers, batteries, self-powering or harvesting technologies, and power supplies; Integrated Communications – Voice and data communications systems utilizing Bluetooth, wireless, hands-free, ergonomically optimized systems, noise-filtering digital speakers or microphones, etc.; Exoskeletons – Whole or partial body suit that enhances mobility and physical performance; Wearable Computers – Body-worn data processing devices; General – Miscellaneous technologies as well as emerging trends or recent advances in the field of wearables.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

From the Starship Enterprise to Los Alamos National Laboratory: Artificial Intelligence and Machine Learning in the NSRC

Artificial Intelligence (AI) conjures up different emotions in different people. Some view it with fear, imagining a malevolent AI similar to Skynet in the Terminator movies. Others see something benevolent, such as the character Data in Star Trek: The Next Generation. Still others see it as a means to advance the frontiers of science, engineering, and technology to new levels not possible through traditional means. At the National Security Research Center (NSRC or the Center), we see AI as a tool to help us go through the monumental tasks we have in digitizing, cataloging, and searching our collections.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Parts & Pools: A Framework for Modular Design of Synthetic Gene Circuits

Published in 2008, Parts & Pools represents one of the first attempts to conceptualize the modular design of bacterial synthetic gene circuits with Standard Biological Parts (DNA segments) and Pools of molecules referred to as common signal carriers (e.g., RNA polymerases and ribosomes). The original framework for modeling bacterial components and designing prokaryotic circuits evolved over the last years and brought, first, to the development of an algorithm for the automatic design of Boolean gene circuits. This is a remarkable achievement since gene digital circuits have a broad range of applications that goes from biosensors for health and environment care to computational devices. More recently, Parts & Pools was enabled to give a proper formal description of eukaryotic biological circuit components. This was possible by employing a rule-based modeling approach, a technique that permits a faithful calculation of all the species and reactions involved in complex systems such as eukaryotic cells and compartments. In this way, Parts & Pools is currently suitable for the visual and modular design of synthetic gene circuits in yeast and mammalian cells too.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Grand challenges in the digitalisation of wind energy

The availability of large amounts of data is starting to impact how the wind energy community works. From turbine design to plant layout, construction, commissioning, and maintenance and operations, new processes and business models are springing up. This is the process of digitalisation, and it promises improved efficiency and greater insight, ultimately leading to increased energy capture and significant savings for wind plant operators, thus reducing the levelised cost of energy. Digitalisation is also impacting research, where it is both easing and speeding up collaboration, as well as making research results more accessible. This is the basis for innovations that can be taken up by end users. But digitalisation faces barriers. This paper uses a literature survey and the results from an expert elicitation to identify three common industry-wide barriers to the digitalisation of wind energy. Comparison with other networked industries and past and ongoing initiatives to foster digitalisation show that these barriers can only be overcome by wide-reaching strategic efforts, and so we see these as “grand challenges” in the digitalisation of wind energy. They are, first, creating FAIR data frameworks; secondly, connecting people and data to foster innovation; and finally, enabling collaboration and competition between organisations. The grand challenges in the digitalisation of wind energy thus include a mix of technical, cultural, and business aspects that will need collaboration between businesses, academia, and government to solve. Working to mitigate them is the beginning of a dynamic process that will position wind energy as an essential part of a global clean energy future.

17 WIND ENERGY↗