Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “INTERNET”

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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

An Intelligent Distributed Ledger Construction Algorithm for IoT

Blockchain is the next generation of secure data management that creates near-immutable decentralized storage. Secure cryptography created a niche for blockchain to provide alternatives to well-known security compromises. However, design bottlenecks with traditional blockchain data structures scale poorly with increased network usage and are extremely computation-intensive. This made the technology difficult to combine with limited devices, like those in Internet of Things networks. In protocols like IOTA, replacement of blockchain's linked-list queue processing with a lightweight dynamic ledger showed remarkable throughput performance increase. However, current stochastic algorithms for ledger construction suffer distinct trade-offs between efficiency and security. This work proposed a machine-learning approach with a multi-arm bandit that resolved these issues and was designed for auditing on limited devices. This algorithm was tested in a reinforcement-learning environment simulating the IOTA ledger's construction with a decision tree. This study showed through regret analysis and experimentation that this approach was secure against impulse manipulation attacks while remaining energy-efficient. Although the IOTA protocol was a pioneer for lightweight distributed ledgers, it is expected that future blockchain protocols will adopt techniques similar to those presented in this work.

multi-arm bandit↗
NASA NTRS2023

Ad-Hawk Aerial Connectivity Network: An Integrated and Empirical System Evaluation

Wildfires in the United States have been increasing significantly in both frequency and size in recent decades, requiring unprecedented resource and communication efficiency on the part of wildfire management organizations. However, while the methodology and technology to combat wildfires have improved, the connectivity infrastructure in rural regions of the country is either incompatible with newer technology or altogether non-existent. Due to this, many modern communication methods are rendered useless in areas where a connection is needed most, complicating the overall fire management procedure. To improve communication and logistics between responders on the front lines and headquarters, a team of NASA research associates has developed the schematic for a rapidly deployable mobile ad-hoc internet-enabled Wi-Fi network that can bring stable internet access to any desired area. This paper contains the testing and analysis of the Ad-Hawk project conceived in the summer of 2022 and developed in the summer of 2023.

Wildfire↗
DOE OSTI2018

Google search patterns monitoring the daily health impact of heatwaves in England: How do the findings compare to established syndromic surveillance systems from 2013 to 2017?

Highlights: • Heat health-related Google search term frequency increased during heatwave events. • Google data correlated well with validated syndromic heat health indicators. • A similar timeliness was seen between daily Google and syndromic data in England. • Google search data could be of benefit in monitoring heat-related morbidity. One of the implications of climate change is a predicted increase in frequent and severe heatwaves. The impact of heatwaves on the health of the population is captured through real-time syndromic healthcare surveillance systems monitored daily in England during the summer months. Internet search data could potentially provide improved timeliness and help to assess the wider population health impact of heat by capturing a population sub-group who are symptomatic but do not seek healthcare. A retrospective observational study was carried out from June 2013 to September 2017 in England to compare daily trends in validated syndromic surveillance heat-related morbidity indicators against symptom-based heatwave related Google search terms. The degree of correlation was determined with Spearman correlation coefficients and lag assessment was carried out to determine timeliness. Daily increases in frequency in Google search terms during heatwave events correlated well with validated syndromic indicators. Correlation coefficients between search term frequency and syndromic indicators from 2013 to 2017 were highest with the telehealth service NHS 111 (range of 0.684–0.900 by search term). Lag analysis revealed a similar timeliness between the data sources, suggesting Google data did not provide a delayed or earlier signal in the context of England's syndromic surveillance systems. This work highlights the potential benefits for countries which lack established public health surveillance systems to monitor heat-related morbidity and the use of internet search data to assess the wider population health impact of exposure to heat.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Mars Polar Lander Mission Distributed Operations

The Mars Polar Lander (MPL) mission is the first planetary mission to use Internet-based distributed ground operations where scientists and engineers collaborate in daily mission operations from multiple geographically distributed locations via the Internet.

ground operations minipulator control internet pla↗
DOE OSTI2015

D and D decision model and mobile application for selection of fixative, strippable coating, and decontamination gel products - 15696

Deactivation and decommissioning (D and D) is the process of taking an active/excess/abandoned facility to a final disposition end state. D and D presents unique hazards that must be addressed from a safety, programmatic, environmental, and technological standpoint. This definition is especially applicable to Savannah River Site's 235-F facility. The facility was constructed in the 1950's as part of the weapons complex materials production and fabrication. The most significant quantities of residual contamination remaining in 235-F building is in the form of Plutonium-238. A Decision Model was created using MatLab to work hand-in-hand with a product list containing commercially available D and D products. This model was created to further enhance and accelerate the decontamination process. It is envisioned that D and D engineers will be able to use this Decision Model in the field via a mobile device. It allows the user to select four inputs to match their situation. The model searches the database and returns the products that fit the criteria selected by the user. This Decision Model will be made available in a web-based application and as a mobile application to ensure end users can access it when needed. The MatLab code recognizes what position in the text box is selected and then this input is converted to the corresponding string. The string is then compared with the information in the product list in the specified column in order to reduce processing time. Then the products that contain the string inputted are displayed on the table and are separated by category. The web-based version of the model will receive three specified criteria and sub-criteria from the user and update the table with products that fit each criteria. A web-based version of this Decision Model is under way and will be set up on the D and D KM-IT platform. There will be two versions of this mobile application: for devices with internet connection and for those that do not have internet connection. This will ensure end users have access to the Decision application at any time or place during the D and D process. A mobile version of the model will also be developed in the near future.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Future of Work with Robotics - 18599

The DOE Environmental Management mission continues with remaining tasks that are high-hazards to human workers and high-consequences to the nation, resulting in potentially high risks to project costs and schedules. This is the mission pull. At the same time, robotic technologies are hitting a turning point with increased productivity and reliability within society, supporting a technology push. Enabling this push are better computer processing following Moore's Law, breakthroughs in biometric and learning algorithms,and riding a wave of venture funding for intended commercialization of mechatronic and Internet of Thing (IOT) projects. There has been overall improvements in material technologies, algorithms, and software standardization with tools/libraries such as the Robot Operating System (ROS). The internet has made knowledge ubiquitous and the cell phone sector has pushed the boundaries of systems-on-chip technology. This current growth is a race between large global technology companies, and between countries that understand that there is a prize with increased commerce based on being a leader in the field of robotics and automation. This technological advances have placed this technology solidly within the next 4. Industrial Revolution being tracked by the World Economic Council. Policies and law can slow this progression down, but technological changes in adjacent fields will put additional pressure on human workers by being more economical and in saving lives. A fundamental issue is will this change be gradual or disruptive such as with the forecasted singularity. There is also a realization with automation that the transition of human workers to other fields may be temporary, but in the long run, workers may run out of viable work and long-term occupations. The obvious future of human jobs are most assured by those who can embrace the change through the design, development, installment, and maintenance of the technology. Younger workers can be re-educated while older humans can be re-trained. The goal of this paper is to explore all the forces that are enabling this revolution, investigating its many impacts, and speculating on the future of human jobs during nuclear remediation. Automation has made an impact to the manufacturing sector, and has since expanded to the retail and services sectors. The question is will this same automation transition, including robotics and artificial intelligence, occur to the environmental management and cleanup sector, and how should we prepare ourselves for this change. (author)

42 ENGINEERING↗
DOE OSTI2017

Cybersecurity and Optimization in Smart “Autonomous” Buildings

Significant resources have been invested in making buildings “smart” by digitizing, networking and automating key systems and operations. Smart autonomous buildings create new energy efficiency, economic and environmental opportunities. But as buildings become increasingly networked to the Internet, they can also become more vulnerable to various cyber threats. Automated and Internet-connected buildings systems, equipment, controls, and sensors can significantly increase cyber and physical vulnerabilities that threaten the confidentiality, integrity, and availability of critical systems in organizations. Securing smart autonomous buildings presents a national security and economic challenge to the nation. Ignoring this challenge threatens business continuity and the availability of critical infrastructures that are enabled by smart buildings. In this chapter, the authors address challenges and explore new opportunities in securing smart buildings that are enhanced by machine learning, cognitive sensing, artificial intelligence (AI) and smart-energy technologies. The chapter begins by identifying cyber-threats and challenges to smart autonomous buildings. Then it provides recommendations on how AI enabled solutions can help smart buildings and facilities better protect, detect and respond to cyber-physical threats and vulnerabilities. Next, the chapter will provide case studies that examine how combining AI with innovative smart-energy technologies can increase both cybersecurity and energy efficiency savings in buildings. The chapter will conclude by proposing recommendations for future cybersecurity and energy optimization research for examining AI enabled smart-energy technology.

Mylrea, Michael E.↗
DOE OSTI2019

Using data from connected thermostats to track large power outages in the United States

The detection of power outages is an essential activity for electric utilities. A large, national dataset of Internet-connected thermostats was used to explore and illustrate the ability of Internet-connected devices to geospatially track outages caused by hurricanes and other major weather events. The method was applied to nine major outage events, including hurricanes and windstorms. In one event, Hurricane Irma, a network of about 1000 thermostats provided quantitatively similar results to detailed utility data with respect to the number of homes without power and identification of the most severely affected regions. The method generated regionally uniform outage data that would give emergency authorities additional visibility into the scope and magnitude of outages. The network of thermostat-sensors also made it possible to calculate a higher resolution version of outage duration (or SAIDI) at a level of customer-level visibility that was not previously available.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A method to generate heating and cooling schedules based on data from connected thermostats

Internet-connected thermostats are a promising new source of temperature and operational data in homes because they record inside temperatures, setpoints, and HVAC runtimes every five minutes. Over 20 million Internet-connected thermostats have already been installed in American homes. Data from about 20,000 connected thermostats were collected and organized by climate zone, number of occupants, floor area, and day type. A method was developed to create up to 40 representative temperature schedules which, together, can more accurately capture the diversity of heating and cooling behaviors. These results are suitable for input into schedules for building energy simulation models. This information enables more realistic simulations of American heating and cooling behavior, leading to more accurate estimates of energy consumption and savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Extreme events, energy security and equality through micro- and macro-levels: Concepts, challenges and methods

Low-income households face long-standing challenges of energy insecurity and inequality (EII). During extreme events (e.g., disasters and pandemics) these challenges are especially severe for vulnerable populations reliant on energy for health, education, and well-being. However, many EII studies rarely incorporate the micro- and macro-perspectives of resilience and reliability of energy and internet infrastructure and social-psychological factors. To remedy this gap, we first address the impacts of extreme events on EII among vulnerable populations. Second, we evaluate the driving factors of EII and how they change during disasters. Third, we situate these inequalities within broader energy systems and pinpoint the importance of equitable infrastructure systems by examining infrastructure reliability and resilience and the role of renewable technologies. Then, we consider the factors influencing energy consumption, such as energy practices, socio-psychological factors, and internet access. Finally, we propose interdisciplinary research methods to study these issues during extreme events and provide recommendations.

Chen, CF↗
DOE OSTI2018

Toward a smart data transfer node

Scientific computing systems are becoming significantly more complex, with distributed teams and complex workflows spanning resources from telescopes and light sources to fast networks and Internet of Things sensor systems. In such settings, no single, centralized administrative team and software stack can coordinate and manage all resources used by a single application. Indeed, we have reached a critical limit in manageability using current human-in-the-loop techniques. We therefore argue that resources must begin to respond automatically, adapting and tuning their behavior in response to observed properties of scientific workflows. Over time, machine learning methods can be used to identify effective strategies for autonomic, goal-driven management behaviors that can be applied end-to-end across the scientific computing landscape. Using the data transfer nodes that are widely deployed in modern research networks as an example, we explore the architecture, methods, and algorithms needed for a smart data transfer node to support future scientific computing systems that self-tune and self-manage.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Low loss polypropylene-silicon composites for millimetre wave applications

Highlights: • Developed polypropylene-silicon composite. • The composite shows a decrease in loss tangent with increasing frequency. • The composite is useful for high frequency applications such as Internet of Things and 5th Generation wireless communication. - Abstract: Polypropylene-silicon composite laminates were fabricated via hot pressing and their dielectric properties up to 35 GHz were studied. The loss tangent was found to decrease with increasing frequency whereas an increasing trend of loss tangent has previously been reported in the literature for such composites. The decreasing trend of the loss tangent with frequency is due to the decreasing conductor loss of silicon (Si) and indicates the possibility for use in high frequency applications such as the Internet Of Things and 5 t h generation wireless communication. The composite containing 25 vol% of Si had a relative permittivity of 3.5 and a loss tangent of 0.001 at 35 GHz. The coefficient of thermal expansion and the thermal conductivity of 40 vol% Si loaded composites were 51 ppm/{sup o}C and 2.23 W/mK, respectively. The thermal conductivity of the composite increased by 163% and 913% for 25 and 40 vol% Si addition, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Design and fabrication of non silicon substrate based MEMS energy harvester for arbitrary surface applications

Internet of Things (IoT) uses MEMS sensor nodes and actuators to sense and control objects through Internet. IOT deploys millions of chemical battery driven sensors at different locations which are not reliable many times because of frequent requirement of charging & battery replacement in case of underground laying, placement at harsh environmental conditions, huge count and difference between demand (24 % per year) and availability (energy density growing rate 8% per year). Energy harvester fabricated on silicon wafers have been widely used in manufacturing MEMS structures. These devices require complex fabrication processes, costly chemicals & clean room. In addition to this silicon wafer based devices are not suitable for curved surfaces like pipes, human bodies, organisms, or other arbitrary surface like clothes, structure surfaces which does not have flat and smooth surface always. Therefore, devices based on rigid silicon wafers are not suitable for these applications. Flexible structures are the key solution for this problems. Energy transduction mechanism generates power from free surrounding vibrations or impact. Sensor nodes application has been purposefully selected due to discrete power requirement at low duty cycle. Such nodes require an average power budget in the range of about 0.1 microwatt to 1 mW over a period of 3-5 seconds. Energy harvester is the best alternate source in contrast with battery for sensor node application. Novel design of Energy Harvester based on cheapest flexible non silicon substrate i.e. cellulose acetate substrate have been modeled, simulated and analyzed on COMSOL multiphysics and fabricated using sol-gel spin coating setup. Single cantilever based harvester generates 60-75 mV peak electric potential at 22Hz frequency and approximately 22 µW power at 1K-Ohm load. Cantilever array can be employed for generating higher voltage by replicating this structure. This work covers design, optimization, fabrication of harvester and schottky diodes based voltage multiplier.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Security and Trust Metrics for Edge Computing

The present state of edge computing is an environment of different computing capabilities connected via a wide variety of communication paths. The energy grid is relying upon distributed energy devices connected at the edge of the internet. Consider the scenario where each edge device is customer-owned distributed energy resource (DER) that is connected via a trustworthy link to a grid service provider. Each DER keeps a local simple trust record of interactions. Information protection is provided by internet https standards, however, trust must be evaluated throughout operation. This paper presents a model for representing and evaluating trust in general and applied to the energy grid as a key example. Actors on the edge may interact with each other as well as with a central datacenter.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

The Empirical Effect of Fleet Optimization on Synchronization and Rebound Effects in Heat Pump Water Heaters

Demand response is a growing concept in light of the internet of things and an increasing need for grid flexibility. Water heaters are one of the preferred devices for providing demand response for grid services and peak management due to their capability to store energy. The efficient use of water heaters for demand response requires consideration of the associated load effects such as synchronization of device schedules and rebound effect. These effects present a significant challenge. Despite the importance of the mentioned effects for water heater queuing and scheduling, there has been no effort to quantify and empirically validate their impact. This study attempts to address this gap by offering two methods - Ward clustering and Euclidean K-means - to evaluate the extent of synchronization in a fleet of 42 water heaters in Atlanta, GA. Using the aforementioned methods on the measured data, we find evidence of convergence of water heater loads as a result of optimization compared to an idle period and analyzed their impact.

demand response↗
DOE OSTI2020

Understanding Impacts of Data Integrity Attacks on Transactive Control Systems

With the rapid growth of internet-connected smart devices capable of exchanging energy price information and adaptively controlling energy consumption of connected loads, the role of transactive control is expected to become more prominent in the modern grid. Transactive control systems integrate the wholesale and retail energy markets, and enable active participation of end users, thereby playing a key role in managing the rising number of distributed assets in the smart grid. The use of internet for the communication of data between the controllers at the building, distribution, and transmission levels makes the system susceptible to cyber-attacks. A skilled adversary can potentially manipulate the exchanged data with the intention of inflicting damage to the system. In this paper, four categories of metrics are put forth for evaluating the performance of the system when under data integrity attacks. A model for scaling-based data integrity attack has been described, and co-simulations have been performed on a 240 bus WECC transmission system model with detailed modeling of distribution systems at specific buses. Our results show that scaling-based data integrity attacks can have non-trivial impacts on the operational, financial, and comfort aspects of the transactive control system.

Smart grid, transactive control system, Buildings-↗
DOE OSTI2020

Open-Source Framework for Data Storage and Visualization of Real-Time Experiments

Digital real time simulators (DRTS) are increasingly being used for the evaluation of power hardware and controller hardware in the laboratory prior to field deployment. Although DRTS are capable of simulating large models in real-time, it is challenging to visualize the results of large models without overdrawing or confounding the viewer. This paper provides an open-source framework for users to visualize their DRTS-based hardware-in-the-loop (HIL) experimental results in real-time. This proposed framework can be used by experimental test beds that can push data through an internet protocol based network. The proposed framework includes three main components. First, it includes the DRTS that generates and pushes the data to a relay. Second, it includes an application that serves multiple purposes, from data storage, testing, and translation of the data to a publisher/subscriber protocol. Finally, it includes libraries and applications that can be used to visualize the data by subscribing to the relay. This framework is available in open source, and it is tested using the HIL platform developed for testing advanced distribution management systems.

advanced distribution management systems↗
DOE OSTI2024

Enhancing Network Anomaly Detection Using Graph Neural Networks

In the world of Internet of Things (IoT) networks, where devices are constantly communicating, keeping them secure from cyber threats is critical. This paper introduces a novel approach to detecting unusual and potentially harmful activities in these networks using graph neural networks (GNNs). We combine two specific types of GNNs-GraphSAGE and graph attention networks (GAT)-to create a model that understands and represents the behaviors and interactions in a network. GraphSAGE creates an embedding of network activities by examining local data interactions, while GAT directs the model's focus to the most critical interactions. By integrating these two methods in a single model that considers different types of interactions (both host and flow nodes), we aim to create a system that accurately represents the current state of a network and can also spot anomalies effectively while reducing false positives and negatives. Our innovative approach has demonstrated promising results, achieving an accuracy of 98% on the UNSW-NB15 dataset, significantly outperforming standalone GraphSAGE and GAT models. This underscores its potential as a robust framework for securing IoT networks against cyber threats and anomalies.

Marfo, William↗