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DOE OSTI2024

Distributed and Secure Spectrum Sharing for 5G and 6G Networks

Secure spectrum sharing or spectrum co-existence of multiple 5G networks and future 6G networks is a powerful enabler technology. The National Spectrum Strategy (NSS) published by the White House in November, 2023, and the subsequent NSS implementation plan led by the National Telecommunication and Information Administration (NTIA) is the driver of a national effort to enable co-existence of government incumbents and commercial networks in selected spectrum bands. Cellular networks such as 5G & 6G and non-cellular Wi-Fi 6E & 7 are the prominent wireless technologies considered for co-existence with incumbent wireless links. Security of the spectrum sharing solutions is a must to make this transformation of spectrum use possible, specially for mission critical communications. However, current spectrum sharing solutions rely on centralized data bases with inherent vulnerabilities. This paper focuses on secure spectrum sharing among multiple 5G networks using unlicensed and shared frequency bands. It presents an innovative AI/ML based distributed spectrum sharing approach that can be autonomously used by multiple networks. Each sharing network uses its own observation of the Radio Frequency (RF) environment, which consists of RF measurements reported from the 5G User Equipment (UE), to adjust the transmission power levels for secure co-existence. Data is presented to illustrate the superior performance of this solution compared to other spectrum sharing solutions where each network can utilize usage data of the other networks. Finally it discusses how this efficient spectrum sharing solution can evolve in the future for the 6G networks.

5G↗

DOE OSTI2018

A Magnetoencephalographic/Encephalographic (MEG/EEG) Brain-Computer Interface Driver for Interactive iOS Mobile Videogame Applications Utilizing the Hadoop Ecosystem, MongoDB, and Cassandra NoSQL Databases

In Phase I, we collected data on five subjects yielding over 90% positive performance in Magnetoencephalographic (MEG) mid-and post-movement activity. In addition, a driver was developed that substituted the actions of the Brain Computer Interface (BCI) as mouse button presses for real-time use in visual simulations. The process was interfaced to a flight visualization demonstration utilizing left or right brainwave thought movement, the user experiences, the aircraft turning in the chosen direction, or on iOS Mobile Warfighter Videogame application. The BCI’s data analytics of a subject’s MEG brain waves and flight visualization performance videogame analytics were stored and analyzed using the Hadoop Ecosystem as a quick retrieval data warehouse. In Phase II portion of the project involves the Emotiv Encephalographic (EEG) Wireless Brain–Computer interfaces (BCIs) allow for people to establish a novel communication channel between the human brain and a machine, in this case, an iOS Mobile Application(s). The EEG BCI utilizes advanced and novel machine learning algorithms, as well as the Spark Directed Acyclic Graph (DAG), Cassandra NoSQL database environment, and also the competitor NoSQL MongoDB database for housing BCI analytics of subject’s response and users’ intent illustrated for both MEG/EEG brainwave signal acquisition. The wireless EEG signals that were acquired from the OpenVibe and the Emotiv EPOC headset can be connected via Bluetooth to an iPhone utilizing a thin Client architecture. The use of NoSQL databases were chosen because of its schema-less architecture and Map Reduce computational paradigm algorithm for housing a user’s brain signals from each referencing sensor. Thus, in the near future, if multiple users are playing on an online network connection and an MEG/EEG sensor fails, or if the connection is lost from the smartphone and the webserver due to low battery power or failed data transmission, it will not nullify the NoSQL document-oriented (MongoDB) or column-oriented Cassandra databases. Additionally, NoSQL databases have fast querying and indexing methodologies, which are perfect for online game analytics and technology. In Phase II, we collected data on five MEG subjects, yielding over 90% positive performance on iOS Mobile Applications with Objective-C and C++, however on EEG signals utilized on three subjects with the Emotiv wireless headsets and (n < 10) subjects from the OpenVibe EEG database the Variational Bayesian Factor Analysis Algorithm (VBFA) yielded below 60% performance and we are currently pursuing extending the VBFA algorithm to work in the time-frequency domain referred to as VBFA-TF to enhance EEG performance in the near future. The novel usage of NoSQL databases, Cassandra and MongoDB, were the primary main enhancements of the BCI Phase II MEG/EEG brain signal data acquisition, queries, and rapid analytics, with MapReduce and Spark DAG demonstrating future implications for next generation biometric MEG/EEG NoSQL databases.

McClay, Wilbert↗

DOE OSTI2020

Wireless Instrumented RB Experiment Preliminary Design and Analysis

The ability to deploy new nuclear fuels for current or future reactor concepts requires carefully designed experiments to generate data to support fuel qualification. Ideally these experiments would include state of-the-art sensing to maximize the amount of in situ data that can be collected during operation. Furthermore, advanced reactor systems can take advantage of integrated in-core sensing technologies to maximize fuel utilization, reduce unnecessary conservativism in design margins, and improve operator’s understanding of limiting peaking factors. Before any novel sensing technologies can be readily adopted for nuclear applications, they must first demonstrate acceptable performance in test reactors. This report summarizes the preliminary design and analysis of the most highly instrumented irradiation experiment ever performed in the removable beryllium (RB) positions of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). The Wireless Instrumented RB Experiment 2021 (WIRE-21) will test a wide range of sensors including wireless sensors being developed by Westinghouse Electric Company (WEC) that could provide in situ measurements of peak fuel temperatures and fuel rod pressurization due to fission gas release. The ability to wirelessly transmit a signal through the fuel rod’s cladding is critical to improving fuel monitoring capabilities without requiring signal penetrations through the cladding pressure boundary, which would significantly impact fuel fabrication, handling, and operation. Other sensors that will be tested in WIRE-21 include an array of thermocouples, self-powered neutron detectors (SPNDs), and spatially distributed fiber-optic temperature sensors. More generally, WIRE-21 will establish a flexible irradiation vehicle design to allow accelerated, economical testing of advanced sensor technologies while leveraging the extremely high neutron flux that is available in HFIR. This report summarizes the mechanical design for WIRE-21, the experimental test matrix, initial neutronic and thermal design analyses, and the active monitoring and control system enhancements necessary to support testing of advanced sensor technologies. The containment for WIRE-21 is similar to previous RB irradiation vehicles but includes a few modifications, most notably the use of integrated compression seals to pass a larger number of sensor leads through the experiment’s pressure boundary. In addition to the sensor leads, inert gas lines are passed into the experiment to enable active temperature control and the ability to pneumatically actuate a bellows-driven pressure sensor. WIRE-21 is targeting temperatures (300–350°C) and neutron fluence levels (~10 22 n/cm 2 ) relevant to light water reactors (LWRs), but the flexible design of the experiment vehicle allows much higher operating temperatures (>1,100°C). Neutronic calculations determine the neutron flux conditions as well as the nuclear heating within the experiments. These results are used as inputs to detailed thermal finite element calculations, which are required to evaluate the complex, three-dimensional heat transfer that occurs within WEC’s wireless sensor enclosures. Initial results show that the temperatures of the sensors’ enclosures and the metal bellows can be operated near the temperature range of LWR coolants and cladding while simultaneously increasing the temperature of a surrogate fuel material to values in the range of 800–1200°C to simulate centerline fuel temperatures during LWR operation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Sizing Considerations for EV Dynamic Wireless Charging Systems with Integrated Energy Storage

Roadways with dynamic wireless charging systems (DWCS) enable charge-sustaining in-motion EV charging, which can reduce charging idle time while increasing range capabilities. Spatially distributed transmitter coils are controlled in response to traffic load that varies significantly minute to minute with high power levels, very short charging time, and low system utilization like wind turbine power. Traffic load estimation and localized analysis may guide effective sizing and topology adoption for feasible and scalable DWCS deployment. DWCS traffic load approximation is reviewed with measured Automated Traffic Recorder (ATR) data and statistical distributions being used to create a synthetic load analyzed using proposed metrics quantifying system utilization over time. Lumped coil section segmentation is compared between second-based distance and spatial density analysis methods, offering 17-27% greater system utilization. A peak load shifting method is proposed for traffic redirection across two tracks with optional BESS integration increasing system utilization by 50-60% depending on time-based and power reserve-based sizing and control.

Lewis, Donovin D.↗

DOE OSTI2017

Stability of Pt/Al 2 O 3 -Based Electrode Langasite SAW Sensors with Al 2 O 3 Capping Layer and Yttria-Stabilized Zirconia Sensing Layer

Surface acoustic wave (SAW) devices have been shown recently to be an appropriate technology for harsh environment sensor applications, such as those in the automotive, aerospace, power plant, and metallurgic industries. Usages include temperature, pressure, torque, strain, gas, liquid, biochemical, and mass sensors in structural health monitoring, industrial process monitoring, environment checking and control, and condition based maintenance. For harsh environment high-temperature applications, battery-free wireless operation associated with sensor robustness, small profile, and mass fabrication capability make SAW sensors a very attractive solution. For high-temperature (< 800°C) gas sensor applications, the stability of SAW sensor platform including protective and sensing film layers must be guaranteed over time and under temperature cycling conditions. This paper reports on the performance and stability of langasite SAW resonator (SAWR) sensor platform using PtAl2O3-based electrode, with atomic layer deposited (ALD) Al2O3 protective layer and yttria-stabilized zirconia (YSZ) gas sensing layer. The effect of 50nm thick Al2O3 or YSZ layers on SAWR sensor resonant frequency and temperature sensitivity responses were investigated. Temperature sensitivities of SAWR sensors with and without ALD Al2O3 protective layer have been compared with numerical predictions for a bare substrate. Measured temperature sensitivities of SAWR sensors with and without the YSZ sensing layers have been compared against each other. In addition, the stability of the SAWR sensor frequency responses have been monitored during multiple 110-hour temperature cycling (over 620 hours in total) from 300°C to 750°C. The measured frequency deviation at 750ºC over six of these 110-hour cycling tests was 0.05%. The results obtained confirm that the presence of the ALD Al2O3 protective layer or the YSZ sensing layer do not compromise the stability of high-temperature harsh environment SAWR sensors, validating their use for the aforementioned applications.

42 ENGINEERING↗

NASA NTRS2004

Electromagnetic Propagation Prediction Inside Aircraft Cabins

Electromagnetic propagation models for signal strength prediction within aircraft cabins are essential for evaluating and designing a wireless communication system to be implemented onboard aircraft. A model was developed using Wireless Valley's SitePlanner; which is commercial grade software intended for predictions within office buildings. The performance of the model was evaluated through a comparison with test data measurements taken on several aircraft. The comparison concluded that the model can accurately predict power propagation within the cabin. This model can enhance researchers understanding of power propagation within aircraft cabins and will aid in future research.

Hankins, Genevieve↗

NASA NTRS2004

Modular Wireless Data-Acquisition and Control System

A modular wireless data-acquisition and control system, now in operation at Kennedy Space Center, offers high performance at relatively low cost. The system includes a central station and a finite number of remote stations that communicate with each other through low-power radio frequency (RF) links. Designed to satisfy stringent requirements for reliability, integrity of data, and low power consumption, this system could be reproduced and adapted to use in a broad range of settings.

Perotti, Jose↗

DOE OSTI2024

Miniaturized Magnetoelastic Sensor System

This article describes the design, assembly, and implementation of a hand-held, magnetic-field-based sensor system that can be adapted for a variety of sensing applications. The miniaturized system is based on Chemical Identification by Magneto-Elastic Sensing (ChIMES) technology, which uses three concentric solenoid coils to wirelessly interrogate a sensor body comprised of a response material coupled to a magnetoelastic wire. The response material expands when it encounters a target, imposing mechanical stress on the wire and altering its magnetic permeability. The sensor bodies are passive, requiring no external power source, and they are small, measuring about 15 mm in length and 3.0 mm in diameter. Up to four sensor bodies can be configured as an evenly-spaced linear array. The sensor system operates by applying a low-frequency, current-stabilized, filtered triangle wave to a uniform-density excitation coil to switch the magnetic domains within the wire. Further, the responses from the sensors are picked up by a detection coil as stress-induced changes in the Faraday voltage, and the strong magnetic field induced by the excitation coil in the detection coil is nullified by a cancellation coil reverse-wound in series with the detection coil. The responses of the sensors in an array are separated in time by a linear gradient dc biasing coil. The sensors can be interrogated through metallic and nonmetallic barriers. The signals from the detection coil and the excitation coil are digitized by a pair of bipolar analog-to-digital converters (ADCs). A Raspberry Pi single-board computer (SBC) and associated software perform data acquisition and control all aspects of the sensor system hardware. The program allows the user to select the number of sensors in the array, the type of signal that is being collected, and the number of samples to take. The program also allows for signal processing of the sensor data, such as baseline correction. The program can differentiate sensor peaks from each other and calculate the magnitude of each sensor response with less than 1% error. The data are then displayed along with a graph of the signal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1995

Portable Computer Technology (PCT) Research and Development Program Phase 2

The subject of this project report, focused on: (1) Design and development of two Advanced Portable Workstation 2 (APW 2) units. These units incorporate advanced technology features such as a low power Pentium processor, a high resolution color display, National Television Standards Committee (NTSC) video handling capabilities, a Personal Computer Memory Card International Association (PCMCIA) interface, and Small Computer System Interface (SCSI) and ethernet interfaces. (2) Use these units to integrate and demonstrate advanced wireless network and portable video capabilities. (3) Qualification of the APW 2 systems for use in specific experiments aboard the Mir Space Station. A major objective of the PCT Phase 2 program was to help guide future choices in computing platforms and techniques for meeting National Aeronautics and Space Administration (NASA) mission objectives. The focus being on the development of optimal configurations of computing hardware, software applications, and network technologies for use on NASA missions.

Castillo, Michael↗

NASA NTRS2016

Wireless Nanoionic-Based Radio Frequency Switch

A nanoionic switch connected to one or more rectenna modules is disclosed. The rectenna module is configured to receive a wireless signal and apply a first bias to change a state of the nanoionic switch from a first state to a second state. The rectenna module can receive a second wireless signal and apply a second bias to change the nanoionic switch from the second state back to the first state. The first bias is generally opposite of the first bias. The rectenna module accordingly permits operation of the nanoionic switch without onboard power.

Nessel, James A.↗

NASA NTRS2017

Advanced Wireless Sensor Nodes - MSFC

NASA field center Marshall Space Flight Center (Huntsville, AL), has invested in advanced wireless sensor technology development. Developments for a wireless microcontroller back-end were primarily focused on the commercial Synapse Wireless family of devices. These devices have many useful features for NASA applications, good characteristics and the ability to be programmed Over-The-Air (OTA). The effort has focused on two widely used sensor types, mechanical strain gauges and thermal sensors. Mechanical strain gauges are used extensively in NASA structural testing and even on vehicle instrumentation systems. Additionally, thermal monitoring with many types of sensors is extensively used. These thermal sensors include thermocouples of all types, resistive temperature devices (RTDs), diodes and other thermal sensor types. The wireless thermal board will accommodate all of these types of sensor inputs to an analog front end. The analog front end on each of the sensors interfaces to the Synapse wireless microcontroller, based on the Atmel Atmega128 device. Once the analog sensor output data is digitized by the onboard analog to digital converter (A/D), the data is available for analysis, computation or transmission. Various hardware features allow custom embedded software to manage battery power to enhance battery life. This technology development fits nicely into using numerous additional sensor front ends, including some of the low-cost printed circuit board capacitive moisture content sensors currently being developed at Auburn University.

Varnavas, Kosta↗

NASA NTRS2017

IMAPS Device Packaging Conference 2017 - Engineered Micro Systems & Devices Track

Varnavas, Kosta↗

NASA NTRS2017

Wireless Nanoionic-Based Radio Frequency Switch

Nessel, James A.↗

DOE OSTI2018

High-Temperature Microwave Acoustic Vibration Sensor

High-temperature vibration sensors are desired in a number of contemporary harsh-environment applications, namely: power plants, metallurgy, aerospace, and defense. The detection of vibrations in these applications is important for providing condition-based maintenance (CBM) for electronic, mechanical, and structural systems, thus reducing operating and maintenance costs, improving industry efficiency, and increasing safety. Microwave surface acoustic wave resonator (MSAWR) sensors have the potential of being used as high-temperature vibration sensors due to their proven harsh-environment operation, small size, battery-free, and wireless capability. This paper explores the MSAWR as a vibration sensor mounted and tested up to 500°C. A 193MHz langasite-based MSAWR sensor was attached to a custom-designed constant-stress Inconel cantilever test beam using a high-temperature capable Al 2 O 3 -based adhesive. The beam was mounted in a box furnace and exposed to vibrations using a stainless-steel rod attached to a vibration generator outside the furnace. Here, the resulting measurements at high-temperatures reported in this paper confirm the viability of the MSAWR sensor to detect both vibration frequency and magnitude for high temperature industrial, defense, aerospace, and power sector applications.

42 ENGINEERING↗

NASA NTRS1999

STS-96 Mission Highlights

In this second part of a three-part video mission-highlights set, on-orbit spacecrew activities performed on the STS-96 Space Shuttle Orbiter Discovery and the International Space Station are reviewed. The flight crew consists of Kent V. Rominger, Commander; Rick D. Husband, Pilot; and Mission Specialists Ellen Ochoa, Tamara E. Jernigan, Daniel T. Barry, Julie Payette (Canadian), and Valery Ivanovich Tokarev (Russian). The primary goals of this mission were to work on logistics and resupply the International Space Station. This second part in the mission series features video from Flight Day 4-7 (FD 4-7). FD 4 of STS-96 presents astronauts Tammy Jernigan and Dan Barry completing the second longest space walk in shuttle history. Footage includes Jernigan and Barry transferring and installing two cranes from the shuttle's payload bay to locations on the outside of the station. The astronauts enter the International Space Station delivering supplies and prepare the outpost to receive its first resident crew, scheduled to arrive in early 2000 on FD 5. The video also captures the crew involved in logistics transfer activities within the Discovery/ISS orbiting complex. FD 6 includes footage of Valery Tokarev and Canadian astronaut Julie Payette charging out the final six battery recharge controller units for two of Zarya's power-producing batteries and all crew members' involvement in logistics transfer activities from the SPACEHAB module to designated locations in the International Space Station. With the transfer work of FD 6 all but complete, the astronauts conduct some additional work, installing parts of a wireless strain gauge system that will help engineers track the effects of adding modules to the station throughout its assembly. Moving the few remaining items from Discovery to the ISS, then closing a series of hatches within the station's modules leading back to the shuttle are the primary activities contained in FD 7. Final coverage features Discovery's astronauts finishing their work inside the International Space Station, closing all of the hatches and readying the shuttle's small thrusters to be fired to raise the entire complex's orbit in preparation for the undocking and departure set for FD 8.

Source record↗

NASA NTRS2009

Carbon Nanotube Based Chemical Sensors for Space and Terrestrial Applications

A nanosensor technology has been developed using nanostructures, such as single walled carbon nanotubes (SWNTs), on a pair of interdigitated electrodes (IDE) processed with a silicon-based microfabrication and micromachining technique. The IDE fingers were fabricated using photolithography and thin film metallization techniques. Both in-situ growth of nanostructure materials and casting of the nanostructure dispersions were used to make chemical sensing devices. These sensors have been exposed to nitrogen dioxide, acetone, benzene, nitrotoluene, chlorine, and ammonia in the concentration range of ppm to ppb at room temperature. The electronic molecular sensing of carbon nanotubes in our sensor platform can be understood by intra- and inter-tube electron modulation in terms of charge transfer mechanisms. As a result of the charge transfer, the conductance of p-type or hole-richer SWNTs in air will change. Due to the large surface area, low surface energy barrier and high thermal and mechanical stability, nanostructured chemical sensors potentially can offer higher sensitivity, lower power consumption and better robustness than the state-of-the-art systems, which make them more attractive for defense and space applications. Combined with MEMS technology, light weight and compact size sensors can be made in wafer scale with low cost. Additionally, a wireless capability of such a sensor chip can be used for networked mobile and fixed-site detection and warning systems for military bases, facilities and battlefield areas.

Li, Jing↗

DOE OSTI2013

DQE of wireless digital detectors: Comparative performance with differing filtration schemes

Purpose: Wireless flat panel detectors are gaining increased usage in portable medical imaging. Two such detectors were evaluated and compared with a conventional flat-panel detector using the formalism of the International Electrotechnical Commission (IEC 62220-1) for measuring modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE) using two different filtration schemes.Methods: Raw images were acquired for three image receptors (DRX-1C and DRX-1, Carestream Health; Inc., Pixium 4600, Trixell) using a radiographic system with a well-characterized output (Philips Super80 CP, Philips Healthcare). Free in-air exposures were measured using a calibrated radiation meter (Unfors Mult-O-Meter Type 407, Unfors Instruments AB). Additional aluminum filtration and a new alternative combined copper-aluminum filtration were used to conform the x ray output to IEC-specified beam quality definitions RQA5 and RQA9. Using the IEC 62220-1 formalism, each detector was evaluated at X{sub N}/2, X{sub N}, and 2X{sub N}, where the normal exposure level to the detector surface (X{sub N}) was set to 8.73 μGy (1.0 mR). The prescribed edge test device was used to evaluate the MTF, while the NNPS was measured using uniform images. The DQE was then calculated from the MTF and NNPS and compared across detectors, exposures, and filtration schemes.Results: The three DR systems had largely comparable MTFs with DRX-1 demonstrating lower values above 1.0 cycles/mm. At each exposure, DRX-1C and Pixium detectors demonstrated better noise performance than that of DRX-1. Zero-frequency DQEs for DRX-1C, Pixium, and DRX-1 detectors were approximately 74%, 63%, and 38% for RQA5 and 50%, 42%, and 28% for RQA9, respectively.Conclusions: DRX-1C detector exhibited superior DQE performance compared to Pixium and DRX-1. In terms of filtration, the alternative filtration was found to provide comparable performance in terms of rank ordering of different detectors with the added convenience of being less bulky for in-the-field measurements.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

Self-Sustainable IoT-Based Remote Sensing Powered by Energy Harvesting Using Stacked Piezoelectric Transducer and Thermoelectric Generator

We propose a self-powered remote multi-sensing system for traffic sensing which is powered by the collective energy harvested from the mechanical vibration of the road caused by the passing vehicles and from the temperature gradient between the asphalt of the road and the soil underneath. A stacked piezoelectric transducer converts mechanical vibrations into electrical energy and a thermoelectric generator harvests the thermal energy from the thermal gradient. Electrical energy signals from the stacked piezoelectric transducer and the thermoelectric generators are converted into usable DC power to recharge the battery using AC-DC and DC-DC converters working simultaneously. The multi-sensing system comprises an embedded system with a microcontroller that acquires data from the sensors and sends the sensory data to an IoT transceiver which transmits the data as RF packets to an ethernet gateway. The gateway converts the RF packets into Internet Protocol (IP) packets and sends them to a remote server. Laboratory and road-testing results showed over 98% sensory data accuracy with the system functioning solely powered by the energy harvested from the alternative energy sources. The successful maximum transmission distance obtained between the IoT, and the gateway was approximately 1 mile, which is a considerable transmission distance achieved in an urban environment. Successful operation of the self-powered multi-sensing system under both laboratory and road conditions contributes considerably to the fields of energy harvesting and self-powered remote sensing systems. The energy flow chart and efficiency for the steps in the system were found to be mechanical power from vehicles to the energy harvester of 0.25%, stacked PZT transducer efficiency was found to be 37%, and for the TEGs the efficiency is 11%. AC-to-DC and DC-to-DC converters’ efficiencies were found to be 90% and 11%. The wireless communication RF transceiver efficiency was found to be 62.5%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗