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In this paper, we describe an adaptive network/routing algorithm that facilitates both coherent and non-coherent event-based cooperative signal processing.
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In coupled human and natural systems, developing an observation strategy which maximizes insight into both the natural system and the human system is a challenging multi-objective optimization problem. In this article, we describe the expansion of a flood risk observation system in Southeast Texas designed to improve our understanding of both physical and socioeconomic exposure to hydrological hazards at fine spatial scales, in the context of a structured hazard-exposure-vulnerability risk framework. We describe a new approach for assessing the spatial extent through which a flood sensor's observations can be assumed to be relevant, and estimate the population served within each sensor's area of information using downscaled socio-demographic data. As hydrological observations and modeling move to ever finer scale, assessing the information they contain in the context of both social and natural systems becomes increasingly important for developing actionable scientific insights.
At extreme temperatures, cryogenic and over 300 C, few electronic components are available to support intelligent data transfer over a common, linear combining medium. This innovation allows many sensors to operate on the same wire bus (or on the same airwaves or optical channel: any linearly combining medium), transmitting simultaneously, but individually recoverable at a node in a cooler part of the test area. This innovation has been demonstrated using room-temperature silicon microcircuits as proxy. The microcircuits have analog functionality comparable to componentry designed using silicon carbide. Given a common, linearly combining medium, multiple sending units may transmit information simultaneously. A listening node, using various techniques, can pick out the signal from a single sender, if it has unique qualities, e.g. a voice. The problem being solved is commonly referred to as the cocktail party problem. The human brain uses the cocktail party effect when it is able to recognize and follow a single conversation in a party full of talkers and other noise sources. High-temperature sensors have been used in silicon carbide electronic oscillator circuits. The frequency of the oscillator changes as a function of the changes in the sensed parameter, such as pressure. This change is analogous to changes in the pitch of a person s voice. The output of this oscillator and many others may be superimposed onto a single medium. This medium may be the power lines supplying current to the sensors, a third wire dedicated to data transmission, the airwaves through radio transmission, an optical medium, etc. However, with nothing to distinguish the identities of each source that is, the source separation this system is useless. Using digital electronic functions, unique codes or patterns are created and used to modulate the output of the sensor.
Technologies enabling long-term, wide-ranging measurement in hard-to-reach areas are a critical need for planetary science inquiry. Phenomena of interest include flows or variations in volatiles, gas composition or concentration, particulate density, or even simply temperature. Improved measurement of these processes enables understanding of exotic geologies and distributions or correlating indicators of trapped water or biological activity. However, such data is often needed in unsafe areas such as caves, lava tubes, or steep ravines not easily reached by current spacecraft and planetary robots. To address this capability gap, we have developed miniaturized, expendable sensors which can be ballistically lobbed from a robotic rover or static lander - or even dropped during a flyover. These projectiles can perform sensing during flight and after anchoring to terrain features. By augmenting exploration systems with these sensors, we can extend situational awareness, perform long-duration monitoring, and reduce utilization of primary mobility resources, all of which are crucial in surface missions. We call the integrated payload that includes a cold gas launcher, smart projectiles, planning software, network discovery, and science sensing: PHALANX. In this paper, we introduce the mission architecture for PHALANX and describe an exploration concept that pairs projectile sensors with a rover “mothership.” Science use cases explored include reconnaissance using ballistic cameras, volatiles detection, and building timelapse maps of temperature and illumination conditions. Strategies to autonomously coordinate constellations of deployed sensors to self-discover and localize with peer ranging (i.e. a “local GPS”) are summarized, thus providing communications infrastructure beyond-line-of-sight (BLOS) of the rover. Capabilities were demonstrated through both simulation and physical testing with a terrestrial prototype. The approach to developing a terrestrial prototype is discussed, including design of the launching mechanism, projectile optimization, micro-electronics fabrication, and sensor selection. Results from early testing and characterization of commercial-off-the-shelf (COTS) components are reported. Nodes were subjected to successful burn-in tests over 48 hours at full logging duty cycle. Integrated field tests were conducted in the Roverscape, a half-acre planetary analog environment at NASA Ames, where we tested up to 10 sensor nodes simultaneously coordinating with an exploration rover. Ranging accuracy has been demonstrated to be within +/-10cm over 20m using commodity radios when compared to high-resolution laser scanner ground truthing. Evolution of the design, including progressive miniaturization of the electronics and iterated modifications of the enclosure housing for streamlining and optimized radio performance are described. Finally, lessons learned to date, gaps toward eventual flight mission implementation, and continuing future development plans are discussed.
In this paper, we describe the architecture of both the PATS and SAP systems and how these two systems interoperate with each other forming a unified capability for deploying intelligence in hostile environments with the objective of providing actionable situational awareness of individuals. The SAP system works in concert with the UICDS information sharing middleware to provide data fusion from multiple sources. UICDS can then publish the sensor data using the OGC's Web Mapping Service, Web Feature Service, and Sensor Observation Service standards. The system described in the paper is able to integrate a spatially distributed sensor system, operating without the benefit of the Web infrastructure, with a remote monitoring and control system that is equipped to take advantage of SWE.
Methods for using modified single wall carbon nanotubes ("SWCNTs") to detect presence and/or concentration of a gas component, such as a halogen (e.g., Cl.sub.2), hydrogen halides (e.g., HCl), a hydrocarbon (e.g., C.sub.nH.sub.2n+2), an alcohol, an aldehyde or a ketone, to which an unmodified SWCNT is substantially non-reactive. In a first embodiment, a connected network of SWCNTs is coated with a selected polymer, such as chlorosulfonated polyethylene, hydroxypropyl cellulose, polystyrene and/or polyvinylalcohol, and change in an electrical parameter or response value (e.g., conductance, current, voltage difference or resistance) of the coated versus uncoated SWCNT networks is analyzed. In a second embodiment, the network is doped with a transition element, such as Pd, Pt, Rh, Ir, Ru, Os and/or Au, and change in an electrical parameter value is again analyzed. The parameter change value depends monotonically, not necessarily linearly, upon concentration of the gas component. Two general algorithms are presented for estimating concentration value(s), or upper or lower concentration bounds on such values, from measured differences of response values.
The National Biocomputation Center, a joint partnership between the Stanford University School of Medicine's Department of Surgery and NASA's Ames Research Center, is the test bed for much of NASA's research in telemedicine, the remote delivery of medical care. In early 2005, researchers at the National Biocomputation Center formed a spinoff company, Intelesense Technologies, to use the telemedicine sensors to provide integrated global monitoring systems. Intelesense uses the systems to better understand how environments and people are linked, monitor and protect natural resources, predict and adapt to environmental changes, provide for sustainable development, reduce the costs and impacts of natural disasters, and provide an effective and intelligent response to such disasters. Current projects range from protecting the environment to tracking emerging infectious diseases like avian influenza (bird flu) and helping people from around the world connect and interact with each other to better understand their environment and themselves.
Effective and secure carbon subsurface storage, involving the deep underground injection of CO 2 into geological formations where it is permanently trapped, is paramount to mitigating CO 2 emissions (Figure I). Ensuring the integrity of these storage sites and detecting potential leakage through the casing annulus necessitates robust monitoring. This work provides the first integrated demonstration of a wireless casing-annulus monitoring architecture that can operate in highly attenuating cement-brine environments relevant to CO 2 storage. This project focused on developing and validating a novel sensor system for integration with autonomous monitoring near the cement reservoir interface. The goal was a fully integrated Technology Readiness Level (TRL) 4/5 field validation of a distributed wireless intelligent sensor system providing real-time, direct subsurface formation measurements to enhance fluid movement monitoring in the cemented casing annulus. Achieving this objective required the development and integration of 1) wireless autonomous microsensor technology by California Institute of Technology (Caltech); 2) sensor packaging and emplacement technology by Research Triangle Institute (RTI); and 3) smart well completions using wireless active casing collars and NOV pipe by the Sandia National Lab (SNL). The collaboration with the Caltech team in this project aimed to develop millimeter-scale radio frequency identification (RFID) sensors capable of detecting CO 2 , pH, and/or methane levels. These sensors are engineered to be impervious to fluids, allowing them to be mixed with cement and installed within the casing annulus. They operate using RFID protocols at frequencies of 902–928 MHz for both power and communication. A Sandia National Laboratories’ team engaged their expertise in the development of a Smart Collar system designed for the wireless data collection from these RFID sensors embedded in the cement annulus and transmission of this information to the ground surface via IntelliPipe/IntelliServ NOV drill pipe. This is accomplished through inductive coupling at the collar, which facilitates data transfer through each segment of the pipe. Because the system cannot transmit a direct current signal to power the Smart Collar, both power and communication were implemented using alternating current and electromagnetic signals at varying frequencies. Furthermore, the developed microsensor technology had to be demonstrated and validated in comparison with reference transducer measurements in a field test site at The University of Texas at Austin (UT-Austin). Although the full sensor suite did not reach field-deployment readiness, the system-level integration achieved in this project establishes a validated pathway for future incorporation of advanced microsensors.
In January 2025, a series of fast-moving wildland-urban-interface (WUI) fires swept through the Los Angeles (LA) metropolitan area, causing severe air pollution. While the impacts of WUI fires on outdoor air quality have been extensively studied, indoor exposure remains less understood, despite most people sheltering indoors during WUI fires. Here, this study investigates the spatial and temporal patterns of indoor and outdoor PM 2.5 concentrations across the South Coast Air Basin, with a focus on LA County during the LA fires. Using high-resolution data from co-located indoor and outdoor PurpleAir (PA) sensors, we analyze hourly PM 2.5 levels and indoor/outdoor ratios. Outdoor PM 2.5 concentrations spiked sharply during the fires, reaching unhealthy levels exceeding 130 μg/m 3 , compared to the mean concentration (12 μg/m 3 ) during non-fire hours. Indoor concentrations also increased, though to a lesser extent, peaking around 60 μg/m 3 compared to a mean of 7 μg/m 3 during non-fire hours. This reflects the partial shielding that indoor environments provide from outdoor air pollution. The mean (0.42) and median (0.29) indoor/outdoor PM 2.5 ratios during LA fire hours were lower than the mean (0.93) and median (0.66) ratios during non-fire hours. Indoor/outdoor PM 2.5 ratios across sensors showed a wide distribution, reflecting differences in building characteristics and occupant behavior, such as indoor activities and the use of air purifiers. These findings emphasize the need for guidance and interventions to reduce indoor PM 2.5 exposure and protect public health during extreme WUI fire events.
Nuclear material accounting and control (NMAC) for nuclear security detects, deters, and resolves questions related to unauthorized removal (i.e. theft) or misuse of nuclear material. NMAC also serves as a key insider threat mitigation measure and aids in recovery of nuclear material that is missing. Effective nuclear security depends on NMAC for timely and accurate information about nuclear material types, quantities, and locations. Bulk nuclear material processing facilities, however, present unique challenges for effective NMAC due to the presence of large quantities of material in-process and the accumulation of residual material holdup within process equipment. These holdup accumulations can obscure accurate physical inventory taking and complicate efforts to resolve NMAC irregularities at the facility level. Bulk material monitoring systems often rely on material balance calculations and indirect measurement techniques, which may mask protracted theft of smaller amounts of nuclear material. These monitoring limitations have generated increased interest in continuous monitoring technologies, including distributed non-destructive assay (NDA) sensor networks capable of providing real-time or near-real-time measurement of material movement and accumulation within bulk processing environments. Recent advancements in distributed networks of NDA radiation detectors and sensing technologies provide an opportunity to address these limitations. Although such distributed sensor networks have been implemented in select facilities for IAEA Safeguards applications, their potential for supporting NMAC functions specifically tailored to nuclear security objectives remains largely unexplored. Furthermore, emerging list-mode data acquisition technologies have reached high technology readiness levels, enabling time-correlated detection of nuclear events across multiple temporal scales. These capabilities provide enhanced opportunities for accurate holdup measurement, continuous process monitoring, and improved detection of material theft or misuse over time. The increasing global expansion of civil nuclear power and development of related bulk material processing facilities, including those supporting high-assay low-enriched uranium (HALEU) and other advanced reactor fuel fabrication, further increases the need for advanced measurement and monitoring strategies for NMAC.
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AGU 2024 poster
Two bolides (2016 June 2 and 2019 April 4) were detected at multiple regional infrasound stations, with many of the locations receiving multiple detections. Analysis of the received signals was used to estimate the yield, location, and trajectory, as well as the type of shock that produced the received signal. The results from the infrasound analysis were compared with ground-truth information that was collected through other sensing modalities. This multimodal framework offers an expanded perspective on the processes governing bolide shock generation and propagation. The majority of signal features showed reasonable agreement between the infrasound-based interpretation and the other observational modalities, though the yield estimate from the 2019 bolide was significantly lower using the infrasound detections. There was also evidence suggesting that one of the detections was from a cylindrical shock that was initially propagating upward, which is unusual though not impossible.
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