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

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At least 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Real-Time Fine Grained Occupancy Estimation Using Depth Sensors on ARM Embedded Platforms

Occupancy estimation is an important primitive for a wide range of applications including building energy efficiency, safety, and security. In this paper, we explore the potential of using depth sensors to detect, estimate, identify, and track occupants in buildings. While depth sensors have been widely used for human detection and gesture recognition, computer vision algorithms are typically run on a powerful computer like XBOX or Intel R CoreTM i7 processor. In this work, we develop a prototype system called FORK using off-the-shelf components that performs the entire depth data processing on a cheaper and low power ARM processor in real-time. As ARM processors are extremely weak in running computer vision algorithms, FORK is designed to detect humans and track them in a very efficient way by leveraging a novel lightweight model based approach instead of traditional approaches based on histogram of oriented gradients (HOG) features. Unlike other camera based approaches, FORK is much less privacy invasive (even if the sensor is compromised). Based on a complete implementation, real-world deployment, and extensive evaluation at realistic scenarios, we observe that FORK achieves over 99% accuracy in real-time (4-9 FPS) in occupancy estimation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Embedded Systems for Intelligent Vehicle Research

Connected and automated vehicles are becoming more and more popular. Research and development in these fields will require new and unique test environments and strategies. Several things can be learned from prior history with specialized vehicle data bus applications. Data bus development and testing techniques for three real-world car and heavy truck vehicle data bus projects are presented in this paper, with an emphasis on hardware-in-the-loop system integration testing.

Barker, Alan↗
DOE OSTI2016

Architecture and Implementation of OpenPET Firmware and Embedded Software

OpenPET is an open source, modular, extendible, and high-performance platform suitable for multi-channel data acquisition and analysis. Due to the versatility of the hardware, firmware, and software architectures, the platform is capable of interfacing with a wide variety of detector modules not only in medical imaging but also in homeland security applications. Analog signals from radiation detectors share similar characteristics-a pulse whose area is proportional to the deposited energy and whose leading edge is used to extract a timing signal. As a result, a generic design method of the platform is adopted for the hardware, firmware, and software architectures and implementations. The analog front-end is hosted on a module called a Detector Board, where each board can filter, combine, timestamp, and process multiple channels independently. The processed data is formatted and sent through a backplane bus to a module called Support Board, where 1 Support Board can host up to eight Detector Board modules. The data in the Support Board, coming from 8 Detector Board modules, can be aggregated or correlated (if needed) depending on the algorithm implemented or runtime mode selected. It is then sent out to a computer workstation for further processing. The number of channels (detector modules), to be processed, mandates the overall OpenPET System Configuration, which is designed to handle up to 1,024 channels using 16-channel Detector Boards in the Standard System Configuration and 16,384 channels using 32-channel Detector Boards in the Large System Configuration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Graph Convolutional Network-Based Topology Embedded Deep Reinforcement Learning for Voltage Stability Control

Topological variations in power system is a common phenomenon and can impose significant challenges to traditional controllers of power system. Recent study revealed the strength of deep reinforcement learning (DRL) based approaches in power system preventive and corrective control. But topological variations are difficult to capture using classical fully connected neural network (FCN) model and has not been explicitly modeled in previous work. Hence, we develop a Graph Convolutional Network (GCN) based DRL framework to tackle topology changes in control design of power system. The GCN model exploits the graph structure of the power network and helps the DRL agent to embed the topology information during learning process. Our GCN based approach is evaluated using the IEEE-39 bus system and it outperforms the FCN-based DRL scheme in terms of training convergence and control performance considering grid topology changes.

Hossain, Ramij Raja↗
DOE OSTI2022

When One Cannot Bypass the Byproducts: Plastic Packaging Waste Embedded in Production and Export

While packaging is praised for reducing waste of perishable food products, packaging waste is a growing concern. Its least recyclable type, plastics waste, is increasingly polluting the marine environment and many developing countries are now refusing to take the waste from developed countries. Before responsibility can be established, one has to identify the key producers and consumers. This paper adjusts the packaging waste satellite account in EXIOBASE 3 by combining the official waste data published by the World Bank. Based on input-output methods, we find that the world's top suppliers of plastic packaging waste are the United States, China, and Brazil. Food and beverage products constitute the bulk of the problem. Yet, 21% of these countries' plastic packaging waste is induced export. At the global level, it is 25.8%. About 76.0% of export-induced plastic packaging waste corresponds to packaging of the exported goods that will ultimately be disposed of in the destination country; while the others correspond to the packaging used in their supply-chain and wasted domestically. We conclude that international efforts need to assign shared responsibility and promote improvement in plastic packaging recyclability.

environment responsibility↗
DOE OSTI2021

Embedded Error Bayesian Calibration of Thermal Decomposition of Organic Materials

Organic materials are an attractive choice for structural components due to their light weight and versatility. However, because they decompose at low temperatures relative to tradiational materials they pose a safety risk due to fire and loss of structural integrity. To quantify this risk, analysts use chemical kinetics models to describe the material pyrolysis and oxidation using thermogravimetric analysis. This process requires the calibration of many model parameters to closely match experimental data. Previous efforts in this field have largely been limited to finding a single best-fit set of parameters even though the experimental data may be very noisy. Furthermore the chemical kinetics models are often simplified representations of the true de- composition process. The simplification induces model-form errors that the fitting process cannot capture. In this work we propose a methodology for calibrating decomposition models to thermogravimetric analysis data that accounts for uncertainty in the model-form and experimental data simultaneously. The methodology is applied to the decomposition of a carbon fiber epoxy composite with a three-stage reaction network and Arrhenius kinetics. The results show a good overlap between the model predictions and thermogravimetric analysis data. Uncertainty bounds capture devia- tions of the model from the data. The calibrated parameter distributions are also presented. In conclusion, the distributions may be used in forward propagation of uncertainty in models that leverage this material.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effect of Thermal Expansion Coefficient, Viscosity and Melting Range in Simulation of PCM Embedded Heat Exchangers With and Without Fins

Phase change material heat exchangers (PCMHX) have an important role in integrating renewable energy systems. PCMHX can offer high storage density at various temperatures of interest and can be used for grid load shifting purposes. Numerical models enable engineers to estimate PCMHX performance for different design parameters and operating conditions. Modeling phase change phenomena is challenging due to the complex time-dependent nature of the process. The accuracy of models is highly sensitive to PCM thermo-physical properties. Thermal expansion coefficient (β), viscosity (μ) and melting temperature range (MR) of a PCM are important properties, especially when natural convection is not negligible. In PCMHX modeling, using less than accurate values for these properties can have significant impact on the simulation outcomes. These properties and discussions thereof are not readily available in the literature. This paper presents a brief review of the literature and a numerical study investigating the model sensitivity to the above-mentioned properties for PCMHX with and without fins. CFD is used to evaluate the charging (melting) phenomena. The study quantifies the impact of uncertainty in these properties on the melting rate and temperature profile. Constant wall temperature was considered as heat source with no heat loss to ambient. Here, the results show that β and μ has significant effect on the melting rate and evolution of the melting front. For a non-finned domain when comparing results for different published values of β and μ, the deviation in melting time can be up to 12.9% and 57.6% respectively. For high wall temperatures, change in melting range did not impact melting time. But when the wall temperature is reduced, up to 9.8% deviation in melting time is observed.

CFD↗
DOE OSTI2012

Charge trapping characteristics of Au nanocrystals embedded in remote plasma atomic layer-deposited Al{sub 2}O{sub 3} film as the tunnel and blocking oxides for nonvolatile memory applications

Remote plasma atomic layer deposited (RPALD) Al{sub 2}O{sub 3} films were investigated to apply as tunnel and blocking layers in the metal-oxide-semiconductor capacitor memory utilizing Au nanocrystals (NCs) for nonvolatile memory applications. The interface stability of an Al{sub 2}O{sub 3} film deposited by RPALD was studied to observe the effects of remote plasma on the interface. The interface formed during RPALD process has high oxidation states such as Si{sup +3} and Si{sup +4}, indicating that RPALD process can grow more stable interface which has a small amount of fixed oxide trap charge. The significant memory characteristics were also observed in this memory device through the electrical measurement. The memory device exhibited a relatively large memory window of 5.6 V under a 10/-10 V program/erase voltage and also showed the relatively fast programming/erasing speed and a competitive retention characteristic after 10{sup 4} s. These results indicate that Al{sub 2}O{sub 3} films deposited via RPALD can be applied as the tunnel and blocking oxides for next-generation flash memory devices.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Enhanced piezoresistive sensing of fiber-reinforced composites via embedded nanoparticles

Carbon fiber composites offer outstanding structural performance with high specific strength and are experiencing significant commercial adoption as the fiber price continues to decrease. Composite research efforts now need to focus on creating multifunctional composites, which can offer sensing capabilities in addition to structural attributes. This work focuses on creating multifunctional carbon fiber composites with structural health monitoring capabilities through the integration of piezoresistive nanoparticles on the surface of carbon fiber. Prior research introduced the development of coating silicon carbide nanoparticles on the surface of carbon fiber in a continuous feed-through process to achieve increased SHM sensitivity with enhanced interlaminar strength and tunable mechanical damping properties. One benefit of that coating process is the compatibility with various nanomaterials. This research capitalizes on that benefit by coating different nanoparticles, such as titanium dioxide, on carbon fiber to further enhance the sensing capabilities. A modification to the prior coating process is made in this research to enable significantly higher nanoparticle loading to be achieved. The resulting composites more accurately measure an applied force by responding with a more profound electrical resistance change. This research lays the foundation for efficiently integrating nanoparticles onto fibers leading to homogenously dispersed nanoparticles throughout a fiber reinforced composite for multifunctional performance.

Bowland, Christopher↗
DOE OSTI2014

Tuning the Electronic Absorption of Protein-Embedded All-trans-Retinal

Protein-chromophore interactions are a central component of a wide variety of critical biological processes such as color vision and photosynthesis. To understand the fundamental elements that contribute to spectral tuning of a chromophore inside the protein cavity, we redesigned human cellular retinol binding protein II (hCRBPII) to fully encapsulate all-trans-retinal and form a covalent bond as a protonated Schiff base. The system, using rational mutagenesis designed to alter the electrostatic environment within the binding pocket of the host protein, enabled regulation of the absorption maximum of the pigment in the range of 425 to 644 nanometers. Moreover, with only nine point mutations, the hCRBPII mutants induced a systematic shift in the absorption profile of all-trans-retinal of more than 200 nanometers across the visible spectrum.

Wang, Wenjing↗
DOE OSTI2013

A long-lived relativistic electron storage ring embedded in Earth's Outer Van Allen belt

Since their discovery over 50 years ago, the Earth’s Van Allen radiation belts are thought to consist of two distinct zones of trapped, highly energetic charged particles. The outer zone is comprised predominantly of mega-electron volt (MeV) electrons that wax and wane in intensity on time scales ranging from hours to days depending primarily on external forcing by the solar wind. Thus, the spatially separated inner zone is comprised of commingled high-energy electrons and very energetic positive ions (mostly protons), the latter being stable in intensity levels over years to decades. In situ energy-specific and temporally resolved spacecraft observations reveal an isolated third ring, or torus, of high-energy (E > 2 MeV) electrons that formed on 2 September 2012 and persisted largely unchanged in the geocentric radial range of 3.0 to ~3.5 Earth radii for over four weeks before being disrupted (and virtually annihilated) by a powerful interplanetary shock wave passage.

58 GEOSCIENCES↗