Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Embedded Systems”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nanocellulose as an embedding matrix and applications thereof

A versatile drug delivery system comprised of plant-based nanocellulose can be used for providing high loading and extended release for virtually any drug. This system is made from nanocrystalline cellulose chemically cross-linked to form a hydrogel. This versatile hydrogel-based drug delivery system can be functionalized to support extended release of oral dosing, relieving patient burden and increasing quality of life.

Ray, Anamika↗
DOE OSTI2022

Redox enzyme-embedded pyrene-poly(ethylenimine) hydrogel electrode for electrosynthesis

Devices, systems, and compositions of matter involving enzyme-mediated bioelectrocatalysis are disclosed and described. An enzyme electrode can include an electrode, a bioelectric material coupled to the electrode, the bioelectric material further including a water-permeable polymer matrix, a planar linker covalently coupled to the water-permeable polymer matrix and noncovalently coupled to the electrode, and electrochemically active oxidoreductase enzyme molecules functionally embedded in the water-permeable polymer matrix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Multi-wavelength photometry of the T Tauri binary V582 Mon (KH 15D): A new epoch of occultations

We present multi-wavelength (VRIJHK) observations of KH 15D obtained in 2012/2013, as well as a master table of standard photometry spanning the years 1967 to 2013. The system is a close, eccentric T Tauri binary embedded in an inclined precessing circumbinary (CB) ring. The most recent data show the continued rise of star B with respect to the trailing edge of the occulting horizon as the system's maximum brightness steadily increases. The wealth of data in time and wavelength domains allows us to track the long-term CCD color evolution of KH 15D. We find that the V – I behavior is consistent with direct and scattered light from the composite color of two stars with slightly different temperatures. There is no evidence for any reddening or bluing associated with extinction or scattering by interstellar-medium-size dust grains. Furthermore, we probe the system's faint phase behavior at near-infrared wavelengths in order to investigate extinction properties of the ring and signatures of a possible shepherding planet sometimes invoked to confine the CB ring at ∼5 AU. The wavelength independence of eclipse depth at second contact is consistent with the ring material being fully opaque to 2.2 μm. The color-magnitude diagrams demonstrate excess flux in J and H at low light levels, which may be due to the presence of a hot, young Jupiter-mass planet.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Wire Co-Extrusion with Big Area Additive Manufacturing

Oak Ridge National Laboratory’s Manufacturing Demonstration Facility is developing a system that will deposit and embed conductive and resistive elements within a printed bead of material. The system was implemented on a Big Area Additive Manufacturing (BAAM) system using a co-extruding nozzle. It has already been demonstrated that BAAM is useful for the tooling industry, but this could be a great improvement on an established application of BAAM parts. This system will provide the ability to control and monitor the surface of additively manufactured (AM) parts. It will also enable self-heating surfaces of AM parts, which is particularly useful in tooling applications. This system could even be used in the future for embedding other materials not found in pellet form in BAAM parts. This work will cover the development of the co-extrusion system and its integration with the dual-port nozzle and the BAAM system.

Atkins, Celeste↗
DOE OSTI2014

Active workflow system for near real-time extreme-scale science. In: PPAA '14 Proceedings of the first workshop on Parallel programming for analytics applications

In recent years, streaming-based data processing has been gaining substantial traction for dealing with overwhelming data generated by real-time applications, from both enterprise sources and scientific computing. In this work, however, we look at an emerging class of scientific data with Near Real-Time (NRT) requirement, in which data is typically generated in a bursty fashion with the near real-time constraints being applied primarily between bursts, rather than within a stream. A key challenge for this types of data sources is that the processing time per data element is not uniform, and not always feasible to predict. Given the observations on the increasing unpredictability of compute load and system dynamics, this work looks to adapt streaming-based approach to the context of this new class of large experiments and simulations that have complex run-time control and analysis issues. In particular, we deploy a novel two-tier scheme for handling the increasing unpredictability of runtime behaviors: Instead of relying on determining what and where to run the scientific workflows beforehand or partial dynamically, the decision will also be adaptively enhanced online according to system runtime status. This is enabled by embedding workflow along with data streams. Specifically, we break data outputs generated from experiments or simulations into multiple self-describing "chunks", which we call active data objects. As such, if there is a transient hotspot observed, a data object with unfinished workflow pipeline can break its previous schedule and search for a least loaded location to continue the execution. Our preliminary experiment results based on synthetic workloads demonstrate the proposed active workflow system as a very promising solution by outperforming the state-of-the-art semi-dynamic workflow schedulers with an improved workflow completion time, as well as a good scalability.

Zhang, Yanwei↗
DOE OSTI2019

DC to DC electrical transformer

An electrical transformer system using helical electrodes applied to a plasma. Systems and methods transform DC voltages and currents to different DC voltages and currents. Instead of using wires and iron cores similar to known transformers, the present DC to DC transformer system exploits plasma, helical electrodes, an axial magnetic field and radial magnetic field coils, with a control system to specify a radial magnetic field at the edge of a specified magnitude. A DC input voltage is applied, and an output is taken from electrodes at opposite the ends of the central apparatus. The system and apparatus contains a radial magnetic field embedded in the helical electrodes; the secondary current is taken from either solid or split (slotted) electrodes. Methods are disclosed for changing the output voltage and current relative to the input values. The system can function as either a stepup or a stepdown transformer.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Learning Implicit Models of Complex Dynamical Systems From Partial Observations [Slides]

Conclusions: certain data-driven models do implicitly what physics simulations do explicitly; theoretical underpinnings in Koopman theory, delay-coordinate embeddings, and Mori-Zwanzig formalism; best approach for given system with finite data an open question; physics-informed machine learning (PIML) emerging framework for combining explicit and implicit modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Experimental testing of additively manufactured embedded fiber optic smart devices for clean energy applications

Abstract An additively manufactured prototype smart device was created to investigate in-flow temperature distributions using embedded high-definition fiber optic sensors within a component for clean energy systems. The devices were created using Ultrasonic Additive Manufacturing to create a unique embedded pathway within a flow conditioner for the high-definition fiber optic sensors to be placed within. The fibers used allowed for temperature measurements to be taken every 0.65 mm along the fiber. The high-resolution fibers were thermally calibrated enable the 2D reconstruction of the temperature profile in the flow path of the structure. This is due to the temperature-related strain response of the material and strain measurements of the fibers. Hot airflow testing of these devices showed the ability to identify localized temperature differences in the flow. The observed strain response within the smart device had higher strain concentrations in the thicker web regions than in the thinner web regions. These higher strain regions resulted in higher uncertainties for the temperature responses. Further calibration is needed to improve the accuracy of the smart devices, specifically within the inner web structures of a flow straightening component. Further investigations of the devices within flow showed the temperature sensing to be independent of the effects of flow velocity. The devices were able to distinguish temperature differences within single and two-phase flow and showed local sensitivity to the temperature changes with the identification of hot and cold spots. The presented results showed the viability of the smart device for obtaining detailed temperature distributions using common industrial components. Eventually, the goal for these smart devices will be to withstand higher temperature and pressure environments such as those experienced in nuclear, fusion, and concentrated solar energy systems.

Donlan, Connor F. (ORCID:0000000223317882)↗
DOE OSTI2018

Multi-element germanium detectors for synchrotron applications

In this paper, we have developed a series of monolithic multi-element germanium detectors, based on sensor arrays produced by the Forschungzentrum Julich, and on Application-specific integrated circuits (ASICs) developed at Brookhaven. Devices have been made with element counts ranging from 64 to 384. These detectors are being used at NSLS-II and APS for a range of diffraction experiments, both monochromatic and energy-dispersive. Compact and powerful readout systems have been developed, based on the new generation of FPGA system-on-chip devices, which provide closely coupled multi-core processors embedded in large gate arrays. Finally, we will discuss the technical details of the systems, and present some of the results from them.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

US energy system transitions under cumulative emissions budgets

Cumulative emissions budgets are increasingly being used by decision makers and analysts to understand emissions reductions and associated transitions in the context of long-term goals such as limiting global mean temperature increase over the century to 1.5 or 2°C (IPCC, 2014). While previous studies have explored the implications of cumulative emissions budgets for the global economy, few studies have conducted regional and national-level analyses (Iyer et al., 2015; Riahi et al., 2015). This paper explores cumulative emissions budgets through 2050 consistent with the 1.5 and 2°C long-term temperature goals in the context of the United States. We employ a state-level model of the United States embedded within a global human-Earth system model (GCAM-USA) to study the implications of such budgets for the U.S. energy system (Iyer et al., 2017a; Iyer et al., 2017b). Our results show that achieving the stringent cumulative emissions budgets entails accelerated deployment of energy conserving technology, almost complete decarbonization of the power sector and increased electrification of buildings and industrial end-use sectors and decarbonization of transport employing a combination of electrification and the substitution of bioenergy for fossil fuels by the mid-century. We also find substantial state-level differences in the relative roles of these decarbonization strategies. Furthermore, our results highlight that increased ambition in the near-term will be valuable in setting the stage for smoother transformations in the future to achieve stringent cumulative emissions budgets consistent with long-term temperature goals established by the international community.

Feijoo, Felipe↗
DOE OSTI2013

SLOAVx: Scalable LOgarithmic AlltoallV Algorithm for Hierarchical Multicore Systems

Scientific applications use collective communication operations in Message Passing Interface (MPI) for global synchronization and data exchanges. Alltoall and AlltoallV are two important collective operations. They are used by MPI jobs to exchange messages among all of MPI processes. AlltoallV is a generalization of Alltoall, supporting messages of varying sizes. However, the existing MPI AlltoallV implementation has linear complexity, i.e., each process has to send messages to all other processes in the job. Such linear complexity can result in sub optimal scalability of MPI applications when they are deployed on millions of cores. To address above challenge, in this paper, we introduce a new Scalable LOgarithmic AlltoallV algorithm, named SLOAV, for MPI AlltoallV collective operation. SLOAV aims to achieve global exchange of small messages of different sizes in a logarithmic number of rounds. Furthermore, given the prevalence of multicore systems with shared memory, we design a hierarchical AlltoallV algorithm based on SLOAV by leveraging the advantages of shared memory, which is referred to as SLOAVx. Compared to SLOAV, SLOAVx significantly reduces the inter-node communication, thus improving the entire system performance and mitigating the impact of message latency. We have implemented and embedded both algorithms in Open MPI. Our evaluation on large-scale computer systems shows that for the 8-byte and 1024-process MPI Alltoallv operation, the SLOAV can reduce the latency by as much as 86.4%, when compared to the state-of-the-art, and SLOAVx can further optimize the SLOAV by up to 83.1% in terms of message latency on multicore systems. In addition, experiments with NAS Parallel Benchmark (NPB) demonstrate that our algorithms are very effective for real-world applications.

Computer Science↗
DOE OSTI2014

Accurate and systematically improvable density functional theory embedding for correlated wavefunctions

We analyze the sources of error in quantum embedding calculations in which an active subsystem is treated using wavefunction methods, and the remainder using density functional theory. We show that the embedding potential felt by the electrons in the active subsystem makes only a small contribution to the error of the method, whereas the error in the nonadditive exchange-correlation energy dominates. We test an MP2 correction for this term and demonstrate that the corrected embedding scheme accurately reproduces wavefunction calculations for a series of chemical reactions. Our projector-based embedding method uses localized occupied orbitals to partition the system; as with other local correlation methods, abrupt changes in the character of the localized orbitals along a reaction coordinate can lead to discontinuities in the embedded energy, but we show that these discontinuities are small and can be systematically reduced by increasing the size of the active region. Convergence of reaction energies with respect to the size of the active subsystem is shown to be rapid for all cases where the density functional treatment is able to capture the polarization of the environment, even in conjugated systems, and even when the partition cuts across a double bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Embedded arrays of vertically aligned carbon nanotube carpets and methods for making them

According to some embodiments, the present invention provides a system and method for supporting a carbon nanotube array that involve an entangled carbon nanotube mat integral with the array, where the mat is embedded in an embedding material. The embedding material may be depositable on a carbon nanotube. A depositable material may be metallic or nonmetallic. The embedding material may be an adhesive material. The adhesive material may optionally be mixed with a metal powder. The embedding material may be supported by a substrate or self-supportive. The embedding material may be conductive or nonconductive. The system and method provide superior mechanical and, when applicable, electrical, contact between the carbon nanotubes in the array and the embedding material. The optional use of a conductive material for the embedding material provides a mechanism useful for integration of carbon nanotube arrays into electronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Towards intelligent diagnostic system employing integration of mathematical and engineering model

The development of medical diagnostic system has been one of the main research fields during years. The goal of the medical diagnostic system is to place a nosological system that could ease the diagnostic evaluation normally performed by scientists and doctors. Efficient diagnostic evaluation is essentials and requires broad knowledge in order to improve conventional diagnostic system. Several approaches on developing the medical diagnostic system have been designed and tested since the earliest 60s. Attempts on improving their performance have been made which utilizes the fields of artificial intelligence, statistical analyses, mathematical model and engineering theories. With the availability of the microcomputer and software development as well as the promising aforementioned fields, medical diagnostic prototypes could be developed. In general, the medical diagnostic system consists of several stages, namely the 1) data acquisition, 2) feature extraction, 3) feature selection, and 4) classifications stages. Data acquisition stage plays an important role in converting the inputs measured from the real world physical conditions to the digital numeric values that can be manipulated by the computer system. One of the common medical inputs could be medical microscopic images, radiographic images, magnetic resonance image (MRI) as well as medical signals such as electrocardiogram (ECG) and electroencephalogram (EEG). Normally, the scientist or doctors have to deal with myriad of data and redundant to be processed. In order to reduce the complexity of the diagnosis process, only the significant features of the raw data such as peak value of the ECG signal or size of lesion in the mammogram images will be extracted and considered in the subsequent stages. Mathematical models and statistical analyses will be performed to select the most significant features to be classified. The statistical analyses such as principal component analysis and discriminant analysis as well as mathematical model of clustering technique have been widely used in developing the medical diagnostic systems. The selected features will be classified using mathematical models that embedded engineering theory such as artificial intelligence, support vector machine, neural network and fuzzy-neuro system. These classifiers will provide the diagnostic results without human intervention. Among many publishable researches, several prototypes have been developed namely NeuralPap, Neural Mammo, and Cervix Kit. The former system (NeuralPap) is an automatic intelligent diagnostic system for classifying and distinguishing between the normal and cervical cancerous cells. Meanwhile, the Cervix Kit is a portable Field-programmable gate array (FPGA)-based cervical diagnostic kit that could automatically diagnose the cancerous cell based on the images obtained during sampling test. Besides the cervical diagnostic system, the Neural Mammo system is developed to specifically aid the diagnosis of breast cancer using a fine needle aspiration image.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Geminal embedding scheme for optimal atomic basis set construction in correlated calculations

We introduce an efficient method to construct optimal and system adaptive basis sets for use in electronic structure and quantum Monte Carlo calculations. The method is based on an embedding scheme in which a reference atom is singled out from its environment, while the entire system (atom and environment) is described by a Slater determinant or its antisymmetrized geminal power (AGP) extension. The embedding procedure described here allows for the systematic and consistent contraction of the primitive basis set into geminal embedded orbitals (GEOs), with a dramatic reduction of the number of variational parameters necessary to represent the many-body wave function, for a chosen target accuracy. Within the variational Monte Carlo method, the Slater or AGP part is determined by a variational minimization of the energy of the whole system in presence of a flexible and accurate Jastrow factor, representing most of the dynamical electronic correlation. The resulting GEO basis set opens the way for a fully controlled optimization of many-body wave functions in electronic structure calculation of bulk materials, namely, containing a large number of electrons and atoms. We present applications on the water molecule, the volume collapse transition in cerium, and the high-pressure liquid hydrogen.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Residential HVAC Fault Data Collection Plan – Refrigerant Undercharge and Overcharge Faults

Heating, ventilation, and air-conditioning (HVAC) systems can develop faults due to poor installation practices or gradual wear and tear, leading to decreased HVAC system’s efficiency, compromised thermal comfort, and shortened equipment lifespan (EERE, 2018). Automated fault detection and diagnosis (AFDD) technologies offer a solution by identifying energy-wasting HVAC faults, such as inadequate indoor airflow and incorrect refrigerant charge, and guiding technicians to enhance system efficiency. In the realm of residential HVAC, AFDD can be implemented through various fault detection and diagnosis capabilities, sensor configurations, and target applications. These technologies typically fall into three categories: smart diagnostic tools, original equipment manufacturer (OEM)-embedded tools, and add-on tools. Smart diagnostic tools employ temporarily installed sensors to directly measure HVAC system characteristics, while OEM-embedded tools utilize factory-installed sensors to identify faults or assess system performance. However, both these types of AFDD technologies are often only accessible for high-end HVAC equipment or require additional sensor installation by qualified technicians, resulting in high investment costs and limited applicability for low-income residential buildings. On the other hand, add-on tools rely solely on data from smart thermostats and meters to detect faults by continuously analyzing equipment runtime or energy usage. As smart thermostat and meter costs decrease and their prevalence increases, these tools can be readily deployed in low-income residential buildings. However, they possess limited capabilities as they rely solely on basic trend analysis. Enhancing such tools with advanced machine learning algorithms can significantly improve their effectiveness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Embedded Sensors and Controls to Improve Component Performance and Reliability - Final Report

Oak Ridge National Laboratory has researched embedded instrumentation and controls (I&C) for extreme environments under the Department of Energy, Office of Nuclear Energy's Nuclear Energy Enabling Technology program. Advanced sensors and controls have the potential to dramatically increase the performance and efficiency of nuclear reactor components, however, the extreme environments of exiting and advanced reactor designs limit the options for sensors, actuators, and control designs. To address two of the extreme environment challenges to embedded I&C, the focus of this research is to fill technology gaps needed for electromagnetic systems that can operate at temperatures greater than 700 C in corrosive environments. A magnetically suspended, canned-rotor pump was chosen for the embedded I&C development platform because it is a system with a practical need in industry and because the sensors, actuators, and embedded I&C technologies needed to successfully build this platform will be widely applicable to any high-temperature components that utilize electromagnetic interactions. This design also eliminates the need for pump seals and mechanical bearings which are the main sources of pump failures and maintenance costs. During the project a conceptual design for the high-temperature magnetically suspended pump was developed and analyzed for manufacturability and reliability. Specifications for the materials, control system, sensors, mechanical performance, high-temperature wiring, and electromagnetic properties were developed for the conceptual design. The canned rotor design of the high-temperature pump presents unique fluid force characteristics arising from the thin fluid channel between the rotor and stator. A model of the fluid forces was developed and the impact of these forces on the stability and performance of magnetic bearing controllers was studied. Then a room temperature bench-scale magnetic testbed was designed and fabricated for testing the performance of sensors and electromagnetic actuators, modern control design techniques, closed-loop system identification, state estimation, and model uncertainty. Finally, a loop-scale testbed with submerged magnetic bearings was designed and fabricated. This testbed will be used to analyze the stability and performance of control system designs in response to the nonlinear and cross-coupling fluid effects between the shaft axes of motion, rotordynamics, gyroscopic effects, and impeller disturbances.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

THE SHAPE OF LONG OUTBURSTS IN U GEM TYPE DWARF NOVAE FROM AAVSO DATA

We search the American Association of Variable Star Observers (AAVSO) archives of the two best-studied dwarf novae in an attempt to find light curves for long outbursts that are extremely well characterized. The systems are U Gem and SS Cyg. Our goal is to search for embedded precursors such as those that have been found recently in the high-fidelity Kepler data for superoutbursts (SOs) of some members of the SU UMa subclass of dwarf novae. For the vast majority of AAVSO data, the combination of low data cadence and large errors associated with individual measurements precludes one from making any strong statement about the shape of the long outbursts. However, for a small number of outbursts, extensive long-term monitoring with digital photometry yields high-fidelity light curves. We report the discovery of embedded precursors in two of three candidate long outbursts. This is the first time that such embedded precursors have been found in dwarf novae above the period gap in other than kepler data, and reinforces van Paradijs' finding that long outbursts in dwarf novae above the period gap and SOs in systems below the period gap constitute a unified class. The thermal-tidal instability to account for SOs in the SU UMa stars predicts embedded precursors only for short orbital period dwarf novae, therefore the presence of embedded precursors in long orbital period systems-U Gem and SS Cyg-argues for a more general mechanism to explain long outbursts.

79 ASTRONOMY AND ASTROPHYSICS↗