Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Mobile computing”

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

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

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Simulation of Electric Potentials and Ion Motion in Planar Electrode Structures for Lossless Ion Manipulations (SLIM)

Here we report a conceptual study and computational evaluation of novel planar electrode Structures for Lossless Ion Manipulations (SLIM). Planar electrode SLIM devices were designed that allow for flexible ion confinement, transport and storage using a combination of RF and DC fields. Effective potentials can be generated that provide near ideal regions for confining ions in the presence of a gas. Ion trajectory simulations using SIMION 8.1 demonstrated the capability for lossless ion motion in these devices over a wide m/z range and a range of electric fields at low pressures (e.g. a few torr). More complex ion manipulations, e.g. turning ions by 90° and dynamically switching selected ion species into orthogonal channels, are also feasible. Lastly, the performance of SLIM devices at ~4 torr pressure for performing ion mobility based separations (IMS) is computationally evaluated and compared to initial experimental results, and both of which agree closely with experimental and theoretical IMS performance for a conventional drift tube design.

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

A self-consistent first-principle based approach to model carrier mobility in organic materials

Transport through thin organic amorphous films, utilized in OLEDs and OPVs, has been a challenge to model by using ab-initio methods. Charge carrier mobility depends strongly on the disorder strength and reorganization energy, both of which are significantly affected by the details in environment of each molecule. Here we present a multi-scale approach to describe carrier mobility in which the materials morphology is generated using DEPOSIT, a Monte Carlo based atomistic simulation approach, or, alternatively by molecular dynamics calculations performed with GROMACS. From this morphology we extract the material specific hopping rates, as well as the on-site energies using a fully self-consistent embedding approach to compute the electronic structure parameters, which are then used in an analytic expression for the carrier mobility. We apply this strategy to compute the carrier mobility for a set of widely studied molecules and obtain good agreement between experiment and theory varying over several orders of magnitude in the mobility without any freely adjustable parameters. The work focuses on the quantum mechanical step of the multi-scale workflow, explains the concept along with the recently published workflow optimization, which combines density functional with semi-empirical tight binding approaches. This is followed by discussion on the analytic formula and its agreement with established percolation fits as well as kinetic Monte Carlo numerical approaches. Finally, we skatch an unified multi-disciplinary approach that integrates materials science simulation and high performance computing, developed within EU project MMM@HPC.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Ab initio calculation of carrier mobility in semiconductors including ionized-impurity scattering

The past decade has seen the emergence of ab initio computational methods for calculating phonon-limited carrier mobilities in semiconductors with predictive accuracy. More realistic calculations ought to take into account additional scattering mechanisms such as, for example, impurity and grain-boundary scattering. Here, in this paper, we investigate the effect of ionized-impurity scattering on the carrier mobility. We model the analytical impurity potential parameterized from first principles by a collection of randomly distributed Coulomb scattering centers, and we include this relaxation channel into the ab initio Boltzmann transport equation, as implemented in the EPW code. We demonstrate this methodology by considering silicon, silicon carbide, and gallium phosphide, for which detailed experimental data are available. Our calculations agree well with experiments over a broad range of temperatures and impurity concentrations. For each compound investigated here, we compare the relative importance of electron-phonon scattering and ionized-impurity scattering, and we critically assess the reliability of Matthiessen's rule. We also show that an accurate description of dielectric screening and carrier effective masses can improve quantitative agreement with experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Accelerating discrete dislocation dynamics simulations with graph neural networks

Discrete dislocation dynamics (DDD) is a widely employed computational method to study plasticity at the mesoscale that connects the motion of dislocation lines to the macroscopic response of crystalline materials. However, the computational cost of DDD simulations remains a bottleneck that limits its range of applicability. Here, we introduce a new DDD-GNN framework in which the expensive time-integration of dislocation motion is entirely substituted by a graph neural network (GNN) model trained on DDD trajectories. As a first application, we demonstrate the feasibility and potential of our method on a simple yet relevant model of a dislocation line gliding through an array of obstacles. We show that the DDD-GNN model is stable and reproduces very well unseen ground-truth DDD simulation responses for a range of straining rates and obstacle densities, without the need to explicitly compute nodal forces or dislocation mobilities during time-integration. Our approach opens new promising avenues to accelerate DDD simulations and to incorporate more complex dislocation motion behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2016

MultispeQ Beta: a tool for large-scale plant phenotyping connected to the open PhotosynQ network

Large-scale high-throughput plant phenotyping (sometimes called phenomics) is becoming increasingly important in plant biology and agriculture and is essential to cutting-edge plant breeding and management approaches needed to meet the food and fuel needs for the next century. Currently, the application of these approaches is severely limited by the availability of appropriate instrumentation and by the ability to communicate experimental protocols, results and analyses. To address these issues, we have developed a low-cost, yet sophisticated open-source scientific instrument designed to enable communities of researchers, plant breeders, educators, farmers and citizen scientists to collect high-quality field data on a large scale. The MultispeQ provides measurements in the field or laboratory of both, environmental conditions (light intensity and quality, temperature, humidity, CO 2 levels, time and location) and useful plant phenotypes, including photosynthetic parameters—photosystem II quantum yield (Φ II ), non-photochemical exciton quenching (NPQ), photosystem II photoinhibition, light-driven proton translocation and thylakoid proton motive force, regulation of the chloroplast ATP synthase and potentially many others—and leaf chlorophyll and other pigments. Plant phenotype data are transmitted from the MultispeQ to mobile devices, laptops or desktop computers together with key metadata that gets saved to the PhotosynQ platform (https://photosynq.org) and provides a suite of web-based tools for sharing, visualization, filtering, dissemination and analyses. We present validation experiments, comparing MultispeQ results with established platforms, and show that it can be usefully deployed in both laboratory and field settings. We present evidence that MultispeQ can be used by communities of researchers to rapidly measure, store and analyse multiple environmental and plant properties, allowing for deeper understanding of the complex interactions between plants and their environment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

IRIS: A Portable Runtime System Exploiting Multiple Heterogeneous Programming Systems

Across embedded, mobile, enterprise, and HPC systems, computer architectures are becoming more heterogeneous and complex. This complexity is causing a crisis in programming systems and performance portability. Several programming systems are working to address these challenges, but the increasing architectural diversity is forcing software stacks and applications to specialize for each architecture. As we show, all of these approaches critically depend on their runtime system for discovery, execution, scheduling, and data orchestration. To address this challenge, we believe that a more agile and proactive runtime system is essential to increase performance portability and improve user productivity. In this regard, we have designed and implemented IRIS: a portable runtime system exploiting multiple heterogeneous programming systems. IRIS can discover available resources, manage multiple diverse programming systems (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, OpenMP) simultaneously in the same execution, respect data dependencies, orchestrate data movement proactively, and provide for user-configurable scheduling. Our evaluation on three architectures, ranging from Qualcomm Snapdragon to a Summit supercomputer node, shows that IRIS improves portability across a wide range of diverse heterogeneous architectures with negligible overhead.

Kim, Jungwon↗
DOE OSTI2022

Interdigitated electrode geometry variation and external quantum efficiency of GaN/AlGaN-based metal-semiconductor-metal UV photodetectors

Aluminum gallium-nitride (Al x Ga 1–x N)-based metal–semiconductor–metal (MSM) ultraviolet photodetectors photodetectors (PD’s) have been successfully designed and fabricated using conventional photolithography techniques and tested experimentally to study their spectral sensitivity across different Al content, x, with x varying from 0 to 0.3. (Al)GaN-based UV PD’s have wide and tunable direct band gaps. The ability to easily select the photodetected wavelength by simply varying the aluminum content of GaN thin film (Al x Ga 1–x N) is a significant advantage of these group III–V compounds. Typically, MSM PD’s grown on (Al)GaN thin films result in ultrafast photodetection because of their highly mobile carriers. These devices are limited by the carrier transit time due to the negligible capacitance presented by the interdigitated fingers. Various electrode geometries were fabricated to investigate the influence of metal contact shapes on the devices’ performance indices with emphasis on the response speed and bias-voltage–independent efficiency. Here, coupled with the independently measured Hall mobility and electric field, we computed the carrier transit time of the devices to be as short as 1.31 ps and the bias-voltage–independent external quantum efficiencies were as high as 70% at 60 V for n-doped and intrinsic devices when operated in the reverse bias regime. Here, (Al x )Ga 1–x N photodetectors were designed to explore spectral sensitivity by altering x from 0 to 0.3.

42 ENGINEERING↗
DOE OSTI2015

Responder Technology Alert Monthly (Oct-Nov 2014)

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

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2014

Automated work packages architecture: An initial set of human factors and instrumentation and controls requirements

The work management process in current fleets of national nuclear power plants is so highly dependent on large technical staffs and quality of work instruction, i.e., paper-based, that this puts nuclear energy at somewhat of a long-term economic disadvantage and increase the possibility of human errors. Technologies like mobile portable devices and computer-based procedures can play a key role in improving the plant work management process, thereby increasing productivity and decreasing cost. Automated work packages are a fundamentally an enabling technology for improving worker productivity and human performance in nuclear power plants work activities because virtually every plant work activity is accomplished using some form of a work package. As part of this year’s research effort, automated work packages architecture is identified and an initial set of requirements identified, that are essential and necessary for implementation of automated work packages in nuclear power plants.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Data on the comprehensive first-principles diffusion study of the aluminum-magnesium system

First-principles calculation of diffusion coefficients between Mg and Al is investigated comprehensively using density functional theory (DFT). The effect of different uncertainty sources arising from first principles calculations has been investigated systematically. These sources include the diffusion model, energetic, entropic and attempt frequency calculations. Variation in self and impurity diffusion coefficients of Mg and Al in stable phases are quantified using different DFT settings and compared with the experiments. Using the optimal DFT settings, diffusion coefficients in metastable phases of Al and Mg are predicted. The dataset refers to “An integrated experimental and computational study of diffusion and atomic mobility of the aluminum-magnesium system” [1].

36 MATERIALS SCIENCE↗
DOE OSTI2012

Mobile Ice Nucleus Spectrometer

This first year report presents results from a computational fluid dynamics (CFD) study to assess the flow and temperature profiles within the mobile ice nucleus spectrometer.

Kulkarni, Gourihar R.↗
DOE OSTI2018

Workflow-based automatic processing for Internet of Floating Things crowdsourced data

Data from sensors incorporated into mobile devices, such as networked navigational sensors, can be used to capture detailed environmental information. We describe here a workflow and framework for using sensors on boats to construct unique new datasets of underwater topography (bathymetry). Starting with a large number of measurements of position, depth, etc., obtained from such an Internet of Floating Things, we illustrate how, with a specialized protocol, data can be communicated to cloud resources, even when using delayed, intermittent, or disconnected networks. We then propose a method for automatic sensor calibration based on a novel reputation approach. Sampled depth data are interpolated efficiently on a cloud computing platform in order to provide a continuously updated bathymetric database. Our prototype implementation uses the FACE-IT Galaxy workflow engine to manage network communication and exploits the computational power of GPGPUs in a virtualized cloud environment, working with a CUDA-parallel algorithm, for efficient data processing. We report on an initial evaluation involving data from a sailing vessel in Italian coastal waters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Feasibility Study of Implementing a Mobile Collaborative Information Platform for International Safeguards Inspections

In response to the growing pervasiveness of mobile technologies such as tablets and smartphones, the International Atomic Energy Agency and the U.S. Department of Energy National Laboratories have been exploring the potential use of these platforms for international safeguards activities. Specifically of interest are information systems (software, and accompanying servers and architecture) deployed on mobile devices to increase the situational awareness and productivity of an IAEA safeguards inspector in the field, while simultaneously reducing paperwork and pack weight of safeguards equipment. Exploratory development in this area has been met with skepticism regarding the ability to overcome technology deployment challenges for IAEA safeguards equipment. This report documents research conducted to identify potential challenges for the deployment of a mobile collaborative information system to the IAEA, and proposes strategies to mitigate those challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Tracking Error Learning Control for Precise Mobile Robot Path Tracking in Outdoor Environment

This article presents a Tracking-Error Learning Control (TELC) algorithm for precise mobile robot path tracking in off-road terrain. In traditional tracking error-based control approaches, feedback and feedforward controllers are designed based on the nominal model which cannot capture the uncertainties, disturbances and changing working conditions so that they cannot ensure precise path tracking performance in the outdoor environment. In TELC algorithm, the feedforward control actions are updated by using the tracking error dynamics and the plant-model mismatch problem is thus discarded. Therefore, the feedforward controller gradually eliminates the feedback controller from the control of the system once the mobile robot has been ontrack. In addition to the proof of the stability, it is proven that the cost functions do not have local minima so that the coefficients in TELC algorithm guarantee that the global minimum is reached. The experimental results show that the TELC algorithm results in better path tracking performance than the traditional tracking error-based control method. The mobile robot controlled by TELC algorithm can track a target path precisely with less than 10 cm error in off-road terrain.

42 ENGINEERING↗
DOE OSTI2019

A computational survey of semiconductors for power electronics

Power electronics (PE) are used to control and convert electrical energy in a wide range of applications from consumer products to large-scale industrial equipment. While Si-based power devices account for the vast majority of the market, wide band gap semiconductors such as SiC, GaN, and Ga 2 O 3 are starting to gain ground. However, these emerging materials face challenges due to either non-negligible defect densities, high synthesis and processing costs, or poor thermal properties. Here, we report on a broad computational survey aimed to identify promising materials for future power electronic devices beyond SiC, GaN, and Ga 2 O 3 . We consider 863 oxides, sulfides, nitrides, carbides, silicides, and borides that exhibit finite calculated band gaps. We utilize ab initio methods in conjunction with models for intrinsic carrier mobility, and critical breakdown field to compute the widely used Baliga figure of merit. We also compute the lattice thermal conductivity and use it as an additional screening parameter. In addition to correctly identifying known PE materials, our survey has revealed a number of promising candidates exhibiting the desirable combination of high figure of merit and high lattice thermal conductivity, which we propose for further experimental investigations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

FedADMP: A Joint Anomaly Detection and Mobility Prediction Framework via Federated Learning

With the proliferation of mobile devices and smart cameras, detecting anomalies and predicting their mobility are critical for enhancing safety in ubiquitous computing systems. Due to data privacy regulations and limited communication bandwidth, it is infeasible to collect, transmit, and store all data from mobile devices at a central location. To overcome this challenge, we propose FedADMP, a federated learning based joint Anomaly Detection and Mobility Prediction framework. FedADMP adaptively splits the training process between the server and clients to reduce computation loads on clients. To protect the privacy of user data, clients in FedADMP upload only intermediate model parameters to the cloud server. We also develop a differential privacy method to prevent the cloud server and external attackers from inferring private information during the model upload procedure. Extensive experiments using real-world datasets show that FedADMP consistently outperforms existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Technical Assistance

DOE-TTO Annual Merit Review presentation on the Technical Assistance task, covering FY25-26. Includes an overview of what technical assistance is and highlights three key projects: (1) FLeet CNG Infrastructure Clean Cities TA request, (2) 3D Mobile App for Emergency Responders (for EVs) Pilot Project, and (3) Smart Playbook for Fleets AFDC content development.

33 ADVANCED PROPULSION SYSTEMS↗