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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

In Situ and Ex Situ NMR for Battery Research

A rechargeable battery stores readily convertible chemical energy to operate a variety of devices such as mobile phones, laptop computers, and electric automobiles, etc. A battery generally consists of four components, i.e., a cathode, an anode, a separator and electrolytes. The properties of these components jointly determine the safety, the lifetime, and the electrochemical performance, include but not limited to the power density and the charge, recharge time/rate associated with a battery system. Extensive amount of research is thus dedicated to understand the physical and chemical properties associated with each of the four components aimed at developing new generations of battery systems with greatly enhanced safety and electrochemical performance while at significantly reduced cost for large scale applications. Advanced characterization tools are prerequisite to fundamentally understand battery materials. Considering that some of the key electrochemical processes can only exist under in situ conditions, thus, can only be captured under a working battery conditions when electric wires are attached and current and voltage applied, in situ detection is critical. NMR, a non-invasive and atomic specific tool, is capable of detecting all phases, including crystalline, amorphous, liquid and gaseous phases simultaneously and is ideal for in situ detection on a working battery system. Ex situ NMR on the other hand can provide more detailed molecular or structural information on stable species with better spectral resolution and sensitivity. The combination of in situ and ex situ NMR, thus, offers a powerful tool for investigating the detailed electrochemistry in batteries.

Energy storage, batteries, multi nuclear NMR, 7Li,↗
DOE OSTI2022

First-principles ionized-impurity scattering and charge transport in doped materials

Scattering of carriers with ionized impurities governs charge transport in doped semiconductors. However, electron interactions with ionized impurities cannot be fully described with quantitative first-principles calculations, so their understanding relies primarily on simplified models. Here we show an ab initio approach to compute the interactions between electrons and ionized impurities or other charged defects. It includes the short- and long-range electron-defect (e-d) interactions on equal footing and allows for efficient interpolation of the e-d matrix elements. Here we combine the e-d and electron-phonon interactions in the Boltzmann transport equation to compute the carrier mobilities in doped silicon over a wide range of temperature and doping concentrations, seamlessly spanning the defect- and phonon-limited transport regimes. The individual contributions of the defect- and phonon-scattering mechanisms to the carrier relaxation times and mean-free paths are analyzed. Our method provides a powerful tool to study electronic interactions in doped materials. It broadens the scope of first-principles transport calculations, enabling studies of a wide range of doped semiconductors and oxides with application to electronics, energy, and quantum technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Identifying Genomic Islands with Deep Neural Networks

Background Horizontal gene transfer is the main source of adaptability for bacteria, through which genes are obtained from different sources including bacteria, archaea, viruses, and eukaryotes. This process promotes the rapid spread of genetic information across lineages, typically in the form of clusters of genes referred to as genomic islands (GIs). Different types of GIs exist, and are often classified by the content of their cargo genes or their means of integration and mobility. While various computational methods have been devised to detect different types of GIs, no single method is capable of detecting all types. Results We propose a method, which we call Shutter Island, that uses a deep learning model (Inception V3, widely used in computer vision) to detect genomic islands. The intrinsic value of deep learning methods lies in their ability to generalize. Via a technique called transfer learning, the model is pre-trained on a large generic dataset and then re-trained on images that we generate to represent genomic fragments. We demonstrate that this image-based approach generalizes better than the existing tools. Conclusions We used a deep neural network and an image-based approach to detect the most out of the correct GI predictions made by other tools, in addition to making novel GI predictions. The fact that the deep neural network was re-trained on only a limited number of GI datasets and then successfully generalized indicates that this approach could be applied to other problems in the field where data is still lacking or hard to curate.

Computer Vision↗
DOE OSTI2012

Contribution to Fusion Materials (Semiannual Report)

The objectives of this work are the following: (1) The application of micro and mesoscale modeling techniques to study dislocation properties in ferritic and W-based materials; and (2) The development of computational models and tools to study damage accumulation in >1 dpa (fusion-like) conditions, both for Fe and W-based alloys. The high-temperature strength of structural ferritic alloys (ferritic/martensitic steels, ODS steels, bcc refractory alloys) hinges on the thermal stability of second phase particles and their interactions with dislocations. Irradiation damage can modify the structure and stability of both the particles and dislocations, particularly by the introduction of gas atoms, point defects and point defect clusters. The three aspects of materials strength that we are studying are: (a) Computation of dislocation mobility functions (stress-velocity relations) as a function of temperature and dislocation character. This will be done via molecular dynamics (MD) simulations of single dislocation motion under applied shear stress. This is a fundamental input to dislocation dynamics (DD) simulations and also provides fundamental insights into the high-temperature plastic behavior of ferritic materials. (b) Simulations of dislocation-obstacle interactions using MD and DD. This subtask includes simulating the effect on dislocation glide of precipitates (e.g., α' Cr precipitates), ODS particles, and irradiation induced defect clusters (e.g. voids, dislocation loops, etc.). (c) Implementation of this information (dislocation mobilities and dislocation-defect interaction rules) into DD codes that will allow us to study plasticity of single crystals Fe alloys under relevant irradiation conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Development of Methodologies for Technology Deployment for Advanced Outage Control Centers that Improve Outage Coordination, Problem Resolution and Outage Risk Management

This research effort is a part of the Light-Water Reactor Sustainability (LWRS) Program, which is a research and development (R&D) program sponsored by Department of Energy (DOE) and performed in close collaboration with industry R&D programs that provides the technical foundations for licensing and managing the long-term, safe, and economical operation of current nuclear power plants. The LWRS program serves to help the U.S. nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of the plants and extension of the current operating licenses. The long term viability of existing nuclear power plants in the U.S. will depend upon maintaining high capacity factors, avoiding nuclear safety issues and reducing operating costs. The slow progress in the construction on new nuclear power plants has placed in increased importance on maintaining the output of the current fleet of nuclear power plants. Recently expanded natural gas production has placed increased economic pressure on nuclear power plants due to lower cost competition. Until recently, power uprate projects had steadily increased the total output of the U.S. nuclear fleet. Errors made during power plant upgrade projects have now removed three nuclear power plants from the U.S. fleet and economic considerations have caused the permanent shutdown of a fourth plant. Additionally, several utilities have cancelled power uprate projects citing economic concerns. For the past several years net electrical generation from U.S. nuclear power plants has been declining. One of few remaining areas where significant improvements in plant capacity factors can be made is in minimizing the duration of refueling outages. Managing nuclear power plant outages is a complex and difficult task. Due to the large number of complex tasks and the uncertainty that accompanies them, outage durations routinely exceed the planned duration. The ability to complete an outage on or near schedule depends upon the performance of the outage management organization. During an outage, the outage control center (OCC) is the temporary command center for outage managers and provides several critical functions for the successful execution of the outage schedule. Essentially, the OCC functions to facilitate information inflow, assist outage management in processing information and to facilitate the dissemination of information to stakeholders. Currently, outage management activities primarily rely on telephone communication, face to face reports of status and periodic briefings in the OCC. Much of the information displayed in OCCs is static and out of date requiring an evaluation to determine if it is still valid. Several advanced communication and collaboration technologies have shown promise for facilitating the information flow into, across and out of the OCC. Additionally, advances in the areas of mobile worker technologies, computer based procedures and electronic work packages can be leveraged to improve the availability of real time status to outage managers.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1983

Lidar remote measurements of Space Shuttle ground cloud emissions

The application of lidar remote sensing techniques to the measurement of spacecraft-booster-exhaust-cloud parameters is illustrated, using data obtained from the launch of STS-3. Mie-scatter measurements of plume and cloud particulates were made by a mobile unit with computer controlled elevation and azimuth coverage. Scattergraphs of typical STS-3 lidar data are presented and discussed. The potential use of DIAL techniques to measure the concentrations of HCl, N2H4, and NO2 is evaluated in terms of EPA overall-standard-deviation guidelines. It is shown that currently operational lidar systems can be modified to determine contamination or air pollution by these molecular species resulting from spacecraft launches.

Caputo, B.↗
NASA NTRS1994

SAVA 3: A testbed for integration and control of visual processes

The development of an experimental test-bed to investigate the integration and control of perception in a continuously operating vision system is described. The test-bed integrates a 12 axis robotic stereo camera head mounted on a mobile robot, dedicated computer boards for real-time image acquisition and processing, and a distributed system for image description. The architecture was designed to: (1) be continuously operating, (2) integrate software contributions from geographically dispersed laboratories, (3) integrate description of the environment with 2D measurements, 3D models, and recognition of objects, (4) capable of supporting diverse experiments in gaze control, visual servoing, navigation, and object surveillance, and (5) dynamically reconfiguarable.

Crowley, James L.↗
NASA NTRS2004

Making Wireless Networks Secure for NASA Mission Critical Applications using Virtual Private Network (VPN) Technology

With so many security issues involved with wireless networks, the technology has not been fully utilized in the area of mission critical applications. These applications would include the areas of telemetry, commanding, voice and video. Wireless networking would allow payload operators the mobility to take computers outside of the control room to their offices and anywhere else in the facility that the wireless network was extended. But the risk is too great of having someone sit just inside of your wireless network coverage and intercept enough of your network traffic to steal proprietary data from a payload experiment or worse yet hack back into your system and do even greater harm by issuing harmful commands. Wired Equivalent Privacy (WEP) is improving but has a ways to go before it can be trusted to protect mission critical data. Today s hackers are becoming more aggressive and innovative, and in order to take advantage of the benefits that wireless networking offer, appropriate security measures need to be in place that will thwart hackers. The Virtual Private Network (VPN) offers a solution to the security problems that have kept wireless networks from being used for mission critical applications. VPN provides a level of encryption that will ensure that data is protected while it is being transmitted over a wireless local area network (IAN). The VPN allows a user to authenticate to the site that the user needs to access. Once this authentication has taken place the network traffic between that site and the user is encapsulated in VPN packets with the Triple Data Encryption Standard (3DES). 3DES is an encryption standard that uses a single secret key to encrypt and decrypt data. The length of the encryption key is 168 bits as opposed to its predecessor DES that has a 56-bit encryption key. Even though 3DES is the common encryption standard for today, the Advance Encryption Standard (AES), which provides even better encryption at a lower cycle cost is growing acceptance. The user computer running the VPN client and the. target site that is running the . VPN firewall exchange this encryption key and therefore are the only ones that are able to decipher the data. The level of encryption offered by the VPN is making it possible for wireless networks to pass the strict security policies that have kept them from being used in the past. Now people will be able to benefit from the many advantages that wireless networking has to offer in the area of mission critical applications.

Nichols, Kelvin F.↗
NASA NTRS2004

Making Wireless Networks Secure for NASA Mission Critical Applications Using Virtual Private Network (VPN) Technology

With so many security issues involved with wireless networks, the technology has not been fully utilized in the area of mission critical applications. These applications would include the areas of telemetry, commanding, voice and video. Wireless networking would allow payload operators the mobility to take computers outside of the control room to their off ices and anywhere else in the facility that the wireless network was extended. But the risk is too great of having someone sit just inside of your wireless network coverage and intercept enough of your network traffic to steal proprietary data from a payload experiment or worse yet hack back into your system and do even greater harm by issuing harmful commands. Wired Equivalent Privacy (WEP) is improving but has a ways to go before it can be trusted to protect mission critical data. Today s hackers are becoming more aggressive and innovative, and in order to take advantage of the benefits that wireless networking offer, appropriate security measures need to be in place that will thwart hackers. The Virtual Private Network (VPN) offers a solution to the security problems that have kept wireless networks from being used for mission critical applications. VPN provides a level of encryption that will ensure that data is protected while it is being transmitted over a wireless local area network (LAN). The VPN allows a user to authenticate to the site that the user needs to access. Once this authentication has taken place the network traffic between that site and the user is encapsulated in VPN packets with the Triple Data Encryption Standard (3DES). 3DES is an encryption standard that uses a single secret key to encrypt and decrypt data. The length of the encryption key is 168 bits as opposed to its predecessor DES that has a 56-bit encryption key. Even though 3DES is the common encryption standard for today, the Advance Encryption Standard (AES), which provides even better encryption at a lower cycle cost is growing acceptance. The user computer running the VPN client and the target site that is running the VPN firewall exchange this encryption key and therefore are the only ones that are able to decipher the data. The level of encryption offered by the VPN is making it possible for wireless networks to pass the strict security policies that have kept them from being used in the past. Now people will be able to benefit from the many advantages that wireless networking has to offer in the area of mission critical applications.

Nichols, Kelvin F.↗
NASA NTRS2004

Adaptive Bio-Inspired Wireless Network Routing for Planetary Surface Exploration

Wireless mobile networks suffer connectivity loss when used in a terrain that has hills, and valleys when line of sight is interrupted or range is exceeded. To resolve this problem and achieve acceptable network performance, we have designed an adaptive, configurable, hybrid system to automatically route network packets along the best path between multiple geographically dispersed modules. This is very useful in planetary surface exploration, especially for ad-hoc mobile networks, where computational devices take an active part in creating a network infrastructure, and can actually be used to route data dynamically and even store data for later transmission between networks. Using inspiration from biological systems, this research proposes to use ant trail algorithms with multi-layered information maps (topographic maps, RF coverage maps) to determine the best route through ad-hoc network at real time. The determination of best route is a complex one, and requires research into the appropriate metrics, best method to identify the best path, optimizing traffic capacity, network performance, reliability, processing capabilities and cost. Real ants are capable of finding the shortest path from their nest to a food source without visual sensing through the use of pheromones. They are also able to adapt to changes in the environment using subtle clues. To use ant trail algorithms, we need to define the probability function. The artificial ant is, in this case, a software agent that moves from node to node on a network graph. The function to calculate the fitness (evaluate the better path) includes: length of the network edge, the coverage index, topology graph index, and pheromone trail left behind by other ant agents. Each agent modifies the environment in two different ways: 1) Local trail updating: As the ant moves between nodes it updates the amount of pheromone on the edge; and 2) Global trail updating: When all ants have completed a tour the ant that found the shortest route updates the edges in its path.

Alena, Richard I.↗
NASA NTRS2007

Wearable Environmental and Physiological Sensing Unit

The wearable environmental and physiological sensing unit (WEPS) is a prototype of systems to be worn by emergency workers (e.g., firefighters and members of hazardous-material response teams) to increase their level of safety. The WEPS includes sensors that measure a few key physiological and environmental parameters, a microcontroller unit that processes the digitized outputs of the sensors, and a radio transmitter that sends the processed sensor signals to a computer in a mobile command center for monitoring by a supervisor. The monitored parameters serve as real-time indications of the wearer s physical condition and level of activity, and of the degree and type of danger posed by the wearer s environment. The supervisor could use these indications to determine, for example, whether the wearer should withdraw in the face of an increasing hazard or whether the wearer should be rescued.

Spremo, Stevan↗
DOE OSTI2015

Design and Implementation of a Hall Effect Sensor Array Applied to Recycling Hard Drive Magnets

Rare earths are an important resource for many electronic components and technologies. Examples abound including Neodymium magnets used in mobile devices and computer hard drives (HDDs), and a variety of renewable energy technologies (e.g., wind turbines). Approximately 21,000 metric tons of Neodymium is processed annually with less than 1% being recycled. An economic system to assist in the recycling of magnet material from post-consumer goods, such as Neodymium Iron Boron magnets commonly found in hard drives is presented. A central component of this recycling measurement system uses an array of 128 Hall Effect sensors arranged in two columns to detect the magnetic flux lines orthogonal to the HDD. Results of using the system to scan planar shaped objects such as hard drives to identify and spatially locate rare-earth magnets for removal and recycling from HDDs are presented. Applications of the sensor array in other identification and localization of magnetic components and assemblies will be presented.

Hall Effect sensors↗
DOE OSTI2021

System and method for passive assay of holdup deposits in nuclear piping

Disclosed herein are a method, apparatus, and software for passive, non-destructive assay of holdup deposits in nuclear piping by in-pipe apparatus. A detector deployed within a pipe is collimated to observe radiation impinging radially inward from decay of deposits that lie on the pipe wall. A radiation detector is centered in the pipe and collimated by a pair of coaxial shielding discs disposed equidistant from the detector. This arrangement causes radiation from a truncated cylinder of pipe deposit within a field of regard to impinge on the detector, while precluding radiation emanating from pipe walls beyond the field of regard from reaching the detector. Hence, observations are unique to a known cylindrical length of pipe. The detector assembly is translated through pipes by an autonomous mobile robotic apparatus. Computer software controls the robotic apparatus, logs data, and post-processes to assay deposits.

Whittaker, William Lawrence↗
DOE OSTI2016

Resonant tunneling assisted propagation and amplification of plasmons in high electron mobility transistors

A rigorous theoretical and computational model is developed for the plasma-wave propagation in high electron mobility transistor structures with electron injection from a resonant tunneling diode at the gate. We discuss the conditions in which low-loss and sustainable plasmon modes can be supported in such structures. The developed analytical model is used to derive the dispersion relation for these plasmon-modes. A non-linear full-wave-hydrodynamic numerical solver is also developed using a finite difference time domain algorithm. The developed analytical solutions are validated via the numerical solution. We also verify previous observations that were based on a simplified transmission line model. It is shown that at high levels of negative differential conductance, plasmon amplification is indeed possible. The proposed rigorous models can enable accurate design and optimization of practical resonant tunnel diode-based plasma-wave devices for terahertz sources, mixers, and detectors, by allowing a precise representation of their coupling when integrated with other electromagnetic structures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2012

Methods of determining complete sensor requirements for autonomous mobility

A method of determining complete sensor requirements for autonomous mobility of an autonomous system includes computing a time variation of each behavior of a set of behaviors of the autonomous system, determining mobility sensitivity to each behavior of the autonomous system, and computing a change in mobility based upon the mobility sensitivity to each behavior and the time variation of each behavior. The method further includes determining the complete sensor requirements of the autonomous system through analysis of the relative magnitude of the change in mobility, the mobility sensitivity to each behavior, and the time variation of each behavior, wherein the relative magnitude of the change in mobility, the mobility sensitivity to each behavior, and the time variation of each behavior are characteristic of the stability of the autonomous system.

Curtis, Steven A.↗
NASA NTRS1987

Optimization of the computational load of a hypercube supercomputer onboard a mobile robot

A combinatorial optimization methodology is developed, which enables the efficient use of hypercube multiprocessors onboard mobile intelligent robots dedicated to time-critical missions. The methodology is implemented in terms of large-scale concurrent algorithms based either on fast simulated annealing, or on nonlinear asynchronous neural networks. In particular, analytic expressions are given for the effect of single-neuron perturbations on the systems' configuration energy. Compact neuromorphic data structures are used to model effects such as precedence constraints, processor idling times, and task-schedule overlaps. Results for a typical robot-dynamics benchmark are presented.

Barhen, Jacob↗
DOE OSTI2025

A Scalable Multi-Modal Framework for High-Fidelity Distributed Human Mobility Simulations

The development of data-driven models for human mobility in urban settings requires access to substantial and diverse real-world data. However, existing historical data often presents challenges such as limited volume, variety, and veracity, as well as missing data and privacy preservation concerns. Also, urban mobility modeling is inherently time-variant, complex, and multi-modal, encompassing everything from individual walking and running to private road travel and large-scale public transportation. These challenges call for innovative solutions to overcome data limitations and compute needs to model mobility behaviors accurately. To address these challenges, we propose a distributed, co-simulation-based architecture DURMOSim that integrates real-world data with scalable, high-fidelity simulations, demonstrating distributed co-simulation feasibility with existing mobility models. DURMOSim underpins a modular integration that would enable using any available mobility simulators for greater extensibility and scalability in performing various urban scenarios. In this paper, we present the design, implementation, and performance evaluation of DURMOSim, highlighting its capability to model population-scale mobility patterns. Our initial results show its ability to dynamically synchronize multiple simulation models at runtime with negligible computational overhead. We believe DURMOSim could be a robust tool for advancing urban mobility research and intelligent transportation systems.

Yoginath, Srikanth [ORNL] (ORCID:0000000184236050)↗
DOE OSTI2024

HumoNet: A Framework for Realistic Modeling and Simulation of Human Mobility Network

Understanding, analyzing, and predicting human mobility and dynamics are valuable to solving pressing problems, developing effective plans, and prescribing timely remedies. As a computational approach, realistic human mobility simulations allow us to understand, analyze, and predict complex systems, including human societies. Accurate simulations rely on (1) the model that captures interactions and behaviors of myriad entities in our society and (2) the mapping of model instances to real-world entities. Taking this into account, this paper introduces the Human Mobility Network simulation framework (HumoNet), an integrated patterns of life (POL) simulation framework that leverages real-world data layers including transportation networks, points of interest, populations, popularity, and human trajectories. HumoNet is a data informed model in which agents are equipped with activities, locomotion, and planning capabilities. To simulate realistic kinematic maneuvers of individuals in transportation networks, HumoNet harnesses a microscopic traffic simulator that provides interaction among vehicles and traffic objects. In this paper, we describe the framework, outline our methodologies, and discuss the data processing and challenges of each data layer. Through experiments, we demonstrate that our simulations capture key features of human mobility by comparing them to the literature and real data using standard measures of human mobility (i.e., the radius of gyration, number of locations visited, level of exploration) and metrics scoring (i.e., Jensen-Shannon divergence). We envision that the synthetic data produced by HumoNet will serve as a benchmark for analyzing epidemics, deploying EV charging networks, and validating AI/ML tasks such as location prediction.

Kim, Joon-Seok↗