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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Embedded Model Error Representation for Bayesian Model Calibration

Model error estimation remains one of the key challenges in uncertainty quantification and predictive science. For computational models of complex physical systems, model error, also known as structural error or model inadequacy, is often the largest contributor to the overall predictive uncertainty. This work builds on a recently developed framework of embedded, internal model correction, in order to represent and quantify structural errors, together with model parameters,within a Bayesian inference context. We focus specifically on a Polynomial Chaos representation with additive modification of existing model parameters, enabling a non-intrusive procedure for efficient approximate likelihood construction, model error estimation, and disambiguation of model and data errors’ contributions to predictive uncertainty. The framework is demonstrated on several synthetic examples, as well as on a chemical ignition problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Embedded Model Error Representation for Bayesian Model Calibration

Model error estimation remains one of the key challenges in uncertainty quantification and predictive science. For computational models of complex physical systems, model error, also known as structural error or model inadequacy,is often the largest contributor to the overall predictive uncertainty. This work builds on a recently developed framework of embedded, internal model correction, in order to represent and quantify structural errors, together with model parameters, within a Bayesian inference context. We focus specifically on a Polynomial Chaos representation with additive modification of existing model parameters, enabling a non-intrusive procedure for efficient approximate likelihood construction, model error estimation, and disambiguation of model and data errors' contributions to predictive uncertainty. As a result, the framework is demonstrated on several synthetic examples, as well as on a chemical ignition problem

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Ultrasonic Phased Arrays and Interactive Reflectivity Tomography for Nondestructive Inspection of Injection and Production Wells in Geothermal Energy Systems (Quarterly Research Performance Progress Report (2015 Q3))

For the past quarter, we have placed our effort in implementing the first version of the Model-Based Iterative Reconstruction (MBIR) algorithm, assembling and testing the electronics, designing transducers mounts, and defining our laboratory test samples. We have successfully developed the first implementation of MBIR for ultrasound imaging. The current algorithm was tested with synthetic data and we are currently making new modifications for the reconstruction of real ultrasound data. Beside assembling and testing the electronics, we developed a LabView graphic user interface (GUI) to fully control the ultrasonic phased array, adjust the time-delays of the transducers, and store the measured reflections. As part of preparing for a laboratory-scale demonstration, the design and fabrication of the laboratory samples has begun. Three cement blocks with embedded objects will be fabricated, characterized, and used to demonstrate the capabilities of the system. During the next quarter, we will continue to improve the current MBIR forward model and integrate the reconstruction code with the LabView GUI. In addition, we will define focal laws for the ultrasonic phased array and perform the laboratory demonstration. We expect to perform laboratory demonstration by the end of October 2015.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Anomalous elasticity, fluctuations and disorder in elastic membranes

Motivated by freely suspended graphene and polymerized membranes in soft and biological matter we present a detailed study of a tensionless elastic sheet in the presence of thermal fluctuations and quenched disorder. The manuscript is based on an extensive draft dating back to 1993, that was circulated privately. It presents the general theoretical framework and calculational details of numerous results, partial forms of which have been published in brief Letters (Le Doussal and Radzihovsky, 1992; 1993). The experimental realization atom-thin graphene sheets (Novoselov et al., 2004) have driven a resurgence in this fascinating subject, making our dated predictions and their detailed derivations timely. To this end we analyze the statistical mechanics of a generalized D-dimensional elastic “membrane” embedded in d dimensions using a self-consistent screening approximation (SCSA), that has proved to be unprecedentedly accurate in this system, exact in three complementary limits: (i) d→∞, (ii) D→4, and (iii) D=d. Focusing on the critical “flat” phase, for a homogeneous two-dimensional (D=2) membrane embedded in three dimensions (d=3), we predict its universal roughness exponent ζ=0.590, length-scale dependent elastic moduli exponents η=0.821 and η{sub u}=0.358, and an anomalous Poisson ratio, σ = - 1/3. In the presence of random uncorrelated heterogeneity the membrane exhibits a glassy wrinkled ground state, characterized by ζ'=0.775,η' = 0.449,η{sub u}'=1.101 and a Poisson ratio σ ' = - 1/3. Motivated by a number of physical realizations (charged impurities, disclinations and dislocations) we also study power-law correlated quenched disorder that leads to a variety of distinct glassy wrinkled phases. Finally, neglecting self-avoiding interaction we demonstrate that at high temperature a “phantom” sheet undergoes a continuous crumpling transition, characterized by a radius of gyration exponent, ν=0.732 and η=0.535. Many of these universal predictions have received considerable support from simulations. We hope that this detailed presentation of the SCSA theory will be useful to further theoretical developments and corresponding experimental investigations on freely suspended graphene.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Systems and methods for customizing kernel machines with deep neural networks

A method including receiving an input data set. The input data set can include one of a feature domain set or a kernel matrix. The method also can include constructing dense embeddings using: (i) Nyström approximations on the input data set when the input data set comprises the kernel matrix, and (ii) clustered Nyström approximations on the input data set when the input data set comprises the feature domain set. The method additionally can include performing representation learning on each of the dense embeddings using a multi-layer fully-connected network for each of the dense embeddings to generate latent representations corresponding to each of the dense embeddings. The method further can include applying a fusion layer to the latent representations corresponding to the dense embeddings to generate a combined representation. The method additionally can include performing classification on the combined representation. Other embodiments of related systems and methods are also disclosed.

Song, Huan↗
DOE OSTI2018

AOI [3]: Smart Refractory Sensor Systems for Wireless Monitoring of Temperature, Health, and Degradation of Slagging Gasifiers

The objective of the work was to develop refractory “smart bricks”, which would contain embedded temperature, strain/stress, and spallation sensors throughout the volume of highchromia (-Cr 2 O 3 ) refractory brick. The proposed work included work to interconnect the sensors to the reactor exterior, where the sensor signals may be processed by low-power electronics and transmitted wirelessly to a central processing hub. The data processing and wireless transmitter hardware was specifically designed to be isolated (with low power consumption) and to be adaptable to future implementation of energy-harvesting strategies for extended life. Finally, the collected data was incorporated into a model to estimate refractory degradation, a technique that could help monitor the health of the refractory in real-time. The long-term goal of this program was to demonstrate high-temperature, wireless sensor arrays for in situ three-dimensional (3-D) refractory monitoring or mapping for slagging gasification systems. The research was in collaboration with HarbisonWalker International (HWI) Technology Center in West Mifflin, PA. HWI is a leading developer and manufacturer of ceramic refractory products for high-temperature applications. The work completed focused on the following areas: 1) Investigation of the chemical stability, microstructural evolution, grain growth kinetics, degree of homogeneity (quantitative image analysis), and electrical properties of refractory oxide-silicide composites at temperatures between 750-1450ºC; 2) Fabrication of silicide-alumina composite and oxide thermocouples and thermistor preforms and the development of techniques to embed them into high-chromia refractory bricks to form “smart bricks”; 3) Utilization of commercial off-the-shelf discrete components to prototype circuits for interfacing between smart brick sensors and the wireless sensor network. The prototypes were then used to design an integrated circuit for thermistor, thermocouple, and capacitive-based smart brick sensor interfacing; 4) Interfacing of the smart bricks with embedded sensors with wireless motes thus yielding a complete signal chain. This end-to-end data collection system was tested on a furnace heated to 1350°C; 5) Development of a slag penetration model and a nonlinear unknown input filter for the data from the embedded sensors for estimating temperature and extent of slag penetration.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Occupant comfort and behavior: High-resolution data from a 6-month field study of personal comfort systems with 37 real office workers

Personal Comfort Systems (PCS) provide individual occupants local heating and cooling to meet their comfort needs without affecting others in the same space. It saves energy by relaxing ambient temperature requirements for the HVAC system. Aside from these benefits, PCS offers a wealth of data that can describe how individuals interact with heating/cooling devices in their own environment. Recently developed Internet-connected PCS chairs have unlocked this opportunity by generating continuous streams of heating and cooling usage data, along with occupancy status and environmental measurements via embedded sensors. The data allow individuals' comfort and behavior to be learned, and can inform centralized systems to provide ‘just the right’ amount of conditioning to meet occupant needs. In summer 2016, we carried out a study with PCS chairs involving 37 occupants in an office building in California. During the study period, we collected >5 million chair usage data-points and 4500 occupant survey responses, as well as continuous measurements of environmental and HVAC system conditions. The data analysis shows that (1) local temperatures experienced by individual occupants vary quite widely across different parts of the building, even within the same thermal zone; (2) occupants often have different thermal preferences even under the same thermal conditions; (3) PCS control behavior can dynamically describe individuals' thermal preferences; (4) PCS chairs produce much higher comfort satisfaction (96%) than typically achieved in buildings. We conclude that PCS not only provide personalized comfort solutions but also offer individualized feedback that can improve comfort analytics and control decisions in buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Learning physics-based reduced-order models from data using nonlinear manifolds

Here we present a novel method for learning reduced-order models of dynamical systems using nonlinear manifolds. First, we learn the manifold by identifying nonlinear structure in the data through a general representation learning problem. The proposed approach is driven by embeddings of low-order polynomial form. A projection onto the nonlinear manifold reveals the algebraic structure of the reduced-space system that governs the problem of interest. The matrix operators of the reduced-order model are then inferred from the data using operator inference. Numerical experiments on a number of nonlinear problems demonstrate the generalizability of the methodology and the increase in accuracy that can be obtained over reduced-order modeling methods that employ a linear subspace approximation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Technical aspects of real time positron emission tracking for gated radiotherapy

Purpose: Respiratory motion can lead to treatment errors in the delivery of radiotherapy treatments. Respiratory gating can assist in better conforming the beam delivery to the target volume. We present a study of the technical aspects of a real time positron emission tracking system for potential use in gated radiotherapy. Methods: The tracking system, called PeTrack, uses implanted positron emission markers and position sensitive gamma ray detectors to track breathing motion in real time. PeTrack uses an expectation–maximization algorithm to track the motion of fiducial markers. A normalized least mean squares adaptive filter predicts the location of the markers a short time ahead to account for system response latency. The precision and data collection efficiency of a prototype PeTrack system were measured under conditions simulating gated radiotherapy. The lung insert of a thorax phantom was translated in the inferior–superior direction with regular sinusoidal motion and simulated patient breathing motion (maximum amplitude of motion ±10 mm, period 4 s). The system tracked the motion of a {sup 22}Na fiducial marker (0.34 MBq) embedded in the lung insert every 0.2 s. The position of the was marker was predicted 0.2 s ahead. For sinusoidal motion, the equation used to model the motion was fitted to the data. The precision of the tracking was estimated as the standard deviation of the residuals. Software was also developed to communicate with a Linac and toggle beam delivery. In a separate experiment involving a Linac, 500 monitor units of radiation were delivered to the phantom with a 3 × 3 cm photon beam and with 6 and 10 MV accelerating potential. Radiochromic films were inserted in the phantom to measure spatial dose distribution. In this experiment, the period of motion was set to 60 s to account for beam turn-on latency. The beam was turned off when the marker moved outside of a 5-mm gating window. Results: The precision of the tracking in the IS direction was 0.53 mm for a sinusoidally moving target, with an average count rate ∼250 cps. The average prediction error was 1.1 ± 0.6 mm when the marker moved according to irregular patient breathing motion. Across all beam deliveries during the radiochromic film measurements, the average prediction error was 0.8 ± 0.5 mm. The maximum error was 2.5 mm and the 95th percentile error was 1.5 mm. Clear improvement of the dose distribution was observed between gated and nongated deliveries. The full-width at halfmaximum of the dose profiles of gated deliveries differed by 3 mm or less than the static reference dose distribution. Monitoring of the beam on/off times showed synchronization with the location of the marker within the latency of the system. Conclusions: PeTrack can track the motion of internal fiducial positron emission markers with submillimeter precision. The system can be used to gate the delivery of a Linac beam based on the position of a moving fiducial marker. This highlights the potential of the system for use in respiratory-gated radiotherapy.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

The general dispersion relation of induced streaming instabilities in quantum outflow systems

In this manuscript the dispersion relations of streaming instabilities, by using the unique property (neutralized in charge and current by default) of plasma shells colliding, have been generalized and studied. This interesting property for interpenetrating beams enables one to find the general dispersion relations without any restrictions used in the previous works in this area. In our previous work [H. Mehdian et al., ApJ. 801, 89 (2015)], employing the plasma shell concept and boost frame method, the general dispersion relation for filamentation instability has been derived in the relativistic classical regime. But in this paper, using the above mentioned concepts, the general dispersion relations (for each of streaming instabilities, filamentation, two-stream and multi-stream) in the non-relativistic quantum regime have been derived by employing the quantum fluid equations together with Maxwell equations. The derived dispersion relations enable to describe any arbitrary system of interacting two and three beams, justified neutralization condition, by choosing the inertial reference frame embedded on the one of the beams. Furthermore, by the numerical and analytical study of these dispersion relations, many new features of streaming instabilities (E.g. their cut-off wave numbers and growth rates) in terms of all involved parameters have been illustrated. The obtained results in this paper can be used to describe many astrophysical systems and laboratory astrophysics setting, such as collision of non-parallel plasma shells over a background plasma or the collision of three neutralized plasma slabs, and justifying the many plasma phenomena such as particle accelerations and induced fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Pixelated CZT Technology for the Detection, Identification, and Localization of Gamma-Ray Sources - 18311

Radioactive waste-management applications require good measurements to qualitatively and quantitatively characterize waste materials. Often these measurements must be done in situ, and the user wishes to learn something of the isotopic and spatial distribution of the source. Therefore, there is a need for a portable instrument that can map radioactive contamination and quantify sources. This presentation introduces several instruments that have been applied to this task, along with example measurements in relevant applications. All instruments are based on 3D-position-sensitive CdZnTe (CZT) detectors. This technology routinely achieves better than 1.1% FWHM energy resolution at 662 keV and operates at room temperature with a startup time under 2 minutes. All are packaged in portable enclosures with WiFi and Bluetooth capabilities for wireless communication. These capabilities allow the technology to be used in more advanced measurements in the field. A unique capability of these detectors is the ability to image the spatial distribution of gamma rays from a single stationary measurement. The first product, Polaris-H, has been in use at commercial nuclear power plants since 2013. The system, currently used at over 50% of the US nuclear-power fleet, integrates a 3D-position-sensitive CZT detector, associated readout electronics, an embedded computer, a battery with over 7-hour life, an optical camera, and a laser range finder in a portable water-proof enclosure. The system connects wirelessly to a tablet which displays a gamma-ray spectrum and isotope-specific images of the gamma-ray distribution in all directions in real time. The CZT detectors have a dynamic range from 50 keV up to 3 MeV. Coded aperture or pinhole imaging is used for energies below 250 keV, and Compton imaging is used for energies above 250 keV. List-mode data is saved to an external USB memory stick to enable more advanced analysis, including isotopic activity analysis, via H3D's post-processing software. Additional systems based on the same architecture have been developed to optimize the technology for other applications. These include Polaris-H Quad, which provides over 3 times the sensitivity for applications involving weaker sources, and Polaris-H Shield, which uses a collimator to provide images and isotope information over a narrower field of view in order to measure weaker sources in the presence of stronger sources of the same isotope. H3D has also developed custom systems that have been mounted on robots and drones that enable remote operation of the technology. Results from the measurements collected at commercial nuclear power plants and other applicable sites will be presented to show how these instruments can be used to detect, identify, and localize gamma-ray sources. Advanced analysis techniques to show the accurate quantification of the gamma-ray source will also be presented. Applications range from characterizing simple objects, to locating hottest points, estimating contamination distributions on an isotope-by-isotope basis, and differentiating scatter and direct emissions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Coarse-grained models using local-density potentials optimized with the relative entropy: Application to implicit solvation

Bottom-up multiscale techniques are frequently used to develop coarse-grained (CG) models for simulations at extended length and time scales but are often limited by a compromise between computational efficiency and accuracy. The conventional approach to CG nonbonded interactions uses pair potentials which, while computationally efficient, can neglect the inherently multibody contributions of the local environment of a site to its energy, due to degrees of freedom that were coarse-grained out. This effect often causes the CG potential to depend strongly on the overall system density, composition, or other properties, which limits its transferability to states other than the one at which it was parameterized. Here, we propose to incorporate multibody effects into CG potentials through additional nonbonded terms, beyond pair interactions, that depend in a mean-field manner on local densities of different atomic species. This approach is analogous to embedded atom and bond-order models that seek to capture multibody electronic effects in metallic systems. We show that the relative entropy coarse-graining framework offers a systematic route to parameterizing such local density potentials. We then characterize this approach in the development of implicit solvation strategies for interactions between model hydrophobes in an aqueous environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Perspective on Many-Body Methods for Molecular Polaritonic Systems

Recent advances in strong light–matter interactions have revealed a wealth of new physical phenomena in molecules embedded in optical cavities, including modified chemical reactivity, altered excitation spectra, and novel quantum correlations. To describe these effects from first-principles, the field of ab initio quantum electrodynamics (QED) has emerged as a compelling extension of quantum chemistry that treats electronic and photonic degrees of freedom on equal footing. In this Perspective, we review the growing landscape of many-body QED methods, including Hartree–Fock, density functional theory (QEDFT), time-dependent DFT (QED-TDDFT), configuration interaction (QED-CI), complete active space (QED-CASSCF), coupled cluster (QED-CC), quantum Monte Carlo (QED-QMC), and density matrix renormalization group (QED-DMRG), highlighting recent developments and implementations. We further explore real-time methods, gradient and Hessian formalisms, and the integration of nonadiabatic nuclear dynamics. Applications range from benchmark simulations of polaritonic chemistry to quantum simulations on emerging quantum hardware. We conclude by outlining future directions for theory development and interdisciplinary efforts at the interface of quantum chemistry, condensed matter, and quantum optics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Hierarchical-embedding autoencoder with a predictor as efficient architecture for learning time-evolution in multi-scale turbulent flows

We introduce a scale-aware, data-driven deep learning modeling framework for accurately predicting the time evolution of multi-scale turbulent plasma and liquid flows. The approach is motivated by the idea of scale separation. Structures of vastly different length scales emerge in these systems, and interactions between these structures occur only locally. To exploit this structure, the flow state is transformed by a hierarchical, fully convolutional autoencoder, not into a single embedding layer as in conventional convolutional surrogate models, but into a series of embedding layers. A stepwise training strategy ensures that fine-scale features are encoded on a high-resolution grid, while larger structures are represented on progressively coarser layers. The time evolution predictor advances all embedding layers in sync, capturing local interactions between features at the same scale as well as between all scales. This approach enables efficient modeling of multi-scale systems since negligible interactions between distant, small-scale structures do not need to be directly modeled. Our hierarchical-embedding autoencoder with a predictor framework is evaluated on canonical examples of multi-scale turbulence: two-dimensional Kolmogorov flow and Hasegawa–Wakatani plasma turbulence. In both cases, the proposed framework significantly improves predictive accuracy relative to conventional convolutional network architectures. A significant improvement in prediction accuracy was observed for crucial statistical characteristics of the Hasegawa–Wakatani plasma as well as for individual trajectories of the Kolmogorov flow turbulence. Importantly, the model's rollout for the Hasegawa–Wakatani problem demonstrates a four-order-of-magnitude speedup compared to traditional numerical solvers.

Khrabry, Alexander I. [Princeton Univ., NJ (United↗
DOE OSTI2015

Phase-Space Detection of Cyber Events

Energy Delivery Systems (EDS) are a network of processes that produce, transfer and distribute energy. EDS are increasingly dependent on networked computing assets, as are many Industrial Control Systems. Consequently, cyber-attacks pose a real and pertinent threat, as evidenced by Stuxnet, Shamoon and Dragonfly. Hence, there is a critical need for novel methods to detect, prevent, and mitigate effects of such attacks. To detect cyber-attacks in EDS, we developed a framework for gathering and analyzing timing data that involves establishing a baseline execution profile and then capturing the effect of perturbations in the state from injecting various malware. The data analysis was based on nonlinear dynamics and graph theory to improve detection of anomalous events in cyber applications. The goal was the extraction of changing dynamics or anomalous activity in the underlying computer system. Takens' theorem in nonlinear dynamics allows reconstruction of topologically invariant, time-delay-embedding states from the computer data in a sufficiently high-dimensional space. The resultant dynamical states were nodes, and the state-to-state transitions were links in a mathematical graph. Alternatively, sequential tabulation of executing instructions provides the nodes with corresponding instruction-to-instruction links. Graph theorems guarantee graph-invariant measures to quantify the dynamical changes in the running applications. Results showed a successful detection of cyber events.

cyber anomaly detection↗
DOE OSTI2016

Exploring Lithium-Cobalt-Nickel Oxide Spinel Electrodes for ≥3.5 V Li-Ion Cells

Recent reports have indicated that a manganese oxide spinel component, when embedded in a relatively small concentration in layered xLi2MnO3(1-x)LiMO2 (M=Ni, Mn, Co) electrode systems, can act as a stabilizer that increases their capacity, rate capability, cycle life, and first-cycle efficiency. These findings prompted us to explore the possibility of exploiting lithiated cobalt oxide spinel stabilizers by taking advantage of (1) the low mobility of cobalt ions relative to manganese and nickel ions in close-packed oxides and (2) their higher potential (~3.6 V vs. Li0) relative to manganese oxide spinels (~2.9 V vs. Li0) for the spinel-to-lithiated spinel electrochemical reaction. In particular, we have revisited the structural and electrochemical properties of lithiated spinels in the LiCo1-xNixO2 (0x0.2) system, first reported almost 25 years ago, by means of high-resolution (synchrotron) X-ray diffraction, transmission electron microscopy, nuclear magnetic resonance spectroscopy, electrochemical cell tests, and theoretical calculations. The results provide a deeper understanding of the complexity of intergrown layered/lithiated spinel LiCo1-xNixO2 structures, when prepared in air between 400 and 800 C, and the impact of structural variations on their electrochemical behavior. These structures, when used in low concentration, offer the possibility of improving the cycling stability, energy, and power of high energy (≥3.5 V) lithium-ion cells.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2017

A modified Embedded-Atom Method interatomic potential for uranium-silicide

Uranium-silicide (U-Si) fuels are being pursued as a possible accident tolerant fuel (ATF). U-Si fuels benefit from higher thermal conductivity and higher fissile density compared to UO2. In order to perform engineering scale nuclear fuel performance simulations, the material properties of the fuel must be known. Currently, the experimental data available for U-Si fuels is rather limited. Thus, multiscale modeling efforts are underway to address this gap in knowledge. In this study, a semi-empirical Modified Embedded Atom Method (MEAM) potential is presented for the description of the U-Si system. The potential accurately describes not only the primary phase of interest (U3Si2), but also a variety of U-Si phases across the composition spectrum.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗