Dependable Wireless Sensor Networks for Prognostics and Health Management: A Survey

DTIC Science & Technology

2014-10-02

sensor network has many advantages. First of all, the absence of wires gives sensor networks the ability to cover a large scale surveillance area...system/component health state. Usually, this information is gathered through independent sensors or a wired network of sensors. The use of a wireless

A Networked Sensor System for the Analysis of Plot-Scale Hydrology.

PubMed

Villalba, German; Plaza, Fernando; Zhong, Xiaoyang; Davis, Tyler W; Navarro, Miguel; Li, Yimei; Slater, Thomas A; Liang, Yao; Liang, Xu

2017-03-20

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments.

A Networked Sensor System for the Analysis of Plot-Scale Hydrology

PubMed Central

Villalba, German; Plaza, Fernando; Zhong, Xiaoyang; Davis, Tyler W.; Navarro, Miguel; Li, Yimei; Slater, Thomas A.; Liang, Yao; Liang, Xu

2017-01-01

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments. PMID:28335534

Distributed coaxial cable crack sensors for crack mapping in RC

NASA Astrophysics Data System (ADS)

Greene, Gary G.; Belarbi, Abdeldjelil; Chen, Genda; McDaniel, Ryan

2005-05-01

New type of distributed coaxial cable sensors for health monitoring of large-scale civil infrastructure was recently proposed and developed by the authors. This paper shows the results and performance of such sensors mounted on near surface of two flexural beams and a large scale reinforced concrete box girder that was subjected to twenty cycles of combined shear and torsion. The main objectives of this health monitoring study was to correlate the sensor's response to strain in the member, and show that magnitude of the signal's reflection coefficient is related to increases in applied load, repeated cycles, cracking, crack mapping, and yielding. The effect of multiple adjacent cracks, and signal loss was also investigated.

Large Scale Triboelectric Nanogenerator and Self-Powered Pressure Sensor Array Using Low Cost Roll-to-Roll UV Embossing

PubMed Central

Dhakar, Lokesh; Gudla, Sudeep; Shan, Xuechuan; Wang, Zhiping; Tay, Francis Eng Hock; Heng, Chun-Huat; Lee, Chengkuo

2016-01-01

Triboelectric nanogenerators (TENGs) have emerged as a potential solution for mechanical energy harvesting over conventional mechanisms such as piezoelectric and electromagnetic, due to easy fabrication, high efficiency and wider choice of materials. Traditional fabrication techniques used to realize TENGs involve plasma etching, soft lithography and nanoparticle deposition for higher performance. But lack of truly scalable fabrication processes still remains a critical challenge and bottleneck in the path of bringing TENGs to commercial production. In this paper, we demonstrate fabrication of large scale triboelectric nanogenerator (LS-TENG) using roll-to-roll ultraviolet embossing to pattern polyethylene terephthalate sheets. These LS-TENGs can be used to harvest energy from human motion and vehicle motion from embedded devices in floors and roads, respectively. LS-TENG generated a power density of 62.5 mW m−2. Using roll-to-roll processing technique, we also demonstrate a large scale triboelectric pressure sensor array with pressure detection sensitivity of 1.33 V kPa−1. The large scale pressure sensor array has applications in self-powered motion tracking, posture monitoring and electronic skin applications. This work demonstrates scalable fabrication of TENGs and self-powered pressure sensor arrays, which will lead to extremely low cost and bring them closer to commercial production. PMID:26905285

A fiber-optic ice detection system for large-scale wind turbine blades

NASA Astrophysics Data System (ADS)

Kim, Dae-gil; Sampath, Umesh; Kim, Hyunjin; Song, Minho

2017-09-01

Icing causes substantial problems in the integrity of large-scale wind turbines. In this work, a fiber-optic sensor system for detection of icing with an arrayed waveguide grating is presented. The sensor system detects Fresnel reflections from the ends of the fibers. The transition in Fresnel reflection due to icing gives peculiar intensity variations, which categorizes the ice, the water, and the air medium on the wind turbine blades. From the experimental results, with the proposed sensor system, the formation of icing conditions and thickness of ice were identified successfully in real time.

A Survey on Virtualization of Wireless Sensor Networks

PubMed Central

Islam, Md. Motaharul; Hassan, Mohammad Mehedi; Lee, Ga-Won; Huh, Eui-Nam

2012-01-01

Wireless Sensor Networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization. PMID:22438759

A survey on virtualization of Wireless Sensor Networks.

PubMed

Islam, Md Motaharul; Hassan, Mohammad Mehedi; Lee, Ga-Won; Huh, Eui-Nam

2012-01-01

Wireless Sensor Networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization.

Scaling Laws for NanoFET Sensors

NASA Astrophysics Data System (ADS)

Wei, Qi-Huo; Zhou, Fu-Shan

2008-03-01

In this paper, we report our numerical studies of the scaling laws for nanoplate field-effect transistor (FET) sensors by simplifying the nanoplates as random resistor networks. Nanowire/tube FETs are included as the limiting cases where the device width goes small. Computer simulations show that the field effect strength exerted by the binding molecules has significant impact on the scaling behaviors. When the field effect strength is small, nanoFETs have little size and shape dependence. In contrast, when the field-effect strength becomes stronger, there exists a lower detection threshold for charge accumulation FETs and an upper detection threshold for charge depletion FET sensors. At these thresholds, the nanoFET devices undergo a transition between low and large sensitivities. These thresholds may set the detection limits of nanoFET sensors. We propose to eliminate these detection thresholds by employing devices with very short source-drain distance and large width.

Gaussian processes for personalized e-health monitoring with wearable sensors.

PubMed

Clifton, Lei; Clifton, David A; Pimentel, Marco A F; Watkinson, Peter J; Tarassenko, Lionel

2013-01-01

Advances in wearable sensing and communications infrastructure have allowed the widespread development of prototype medical devices for patient monitoring. However, such devices have not penetrated into clinical practice, primarily due to a lack of research into "intelligent" analysis methods that are sufficiently robust to support large-scale deployment. Existing systems are typically plagued by large false-alarm rates, and an inability to cope with sensor artifact in a principled manner. This paper has two aims: 1) proposal of a novel, patient-personalized system for analysis and inference in the presence of data uncertainty, typically caused by sensor artifact and data incompleteness; 2) demonstration of the method using a large-scale clinical study in which 200 patients have been monitored using the proposed system. This latter provides much-needed evidence that personalized e-health monitoring is feasible within an actual clinical environment, at scale, and that the method is capable of improving patient outcomes via personalized healthcare.

Autonomous management of a recursive area hierarchy for large scale wireless sensor networks using multiple parents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cree, Johnathan Vee; Delgado-Frias, Jose

Large scale wireless sensor networks have been proposed for applications ranging from anomaly detection in an environment to vehicle tracking. Many of these applications require the networks to be distributed across a large geographic area while supporting three to five year network lifetimes. In order to support these requirements large scale wireless sensor networks of duty-cycled devices need a method of efficient and effective autonomous configuration/maintenance. This method should gracefully handle the synchronization tasks duty-cycled networks. Further, an effective configuration solution needs to recognize that in-network data aggregation and analysis presents significant benefits to wireless sensor network and should configuremore » the network in a way such that said higher level functions benefit from the logically imposed structure. NOA, the proposed configuration and maintenance protocol, provides a multi-parent hierarchical logical structure for the network that reduces the synchronization workload. It also provides higher level functions with significant inherent benefits such as but not limited to: removing network divisions that are created by single-parent hierarchies, guarantees for when data will be compared in the hierarchy, and redundancies for communication as well as in-network data aggregation/analysis/storage.« less

An ultrasensitive strain sensor with a wide strain range based on graphene armour scales.

PubMed

Yang, Yi-Fan; Tao, Lu-Qi; Pang, Yu; Tian, He; Ju, Zhen-Yi; Wu, Xiao-Ming; Yang, Yi; Ren, Tian-Ling

2018-06-12

An ultrasensitive strain sensor with a wide strain range based on graphene armour scales is demonstrated in this paper. The sensor shows an ultra-high gauge factor (GF, up to 1054) and a wide strain range (ε = 26%), both of which present an advantage compared to most other flexible sensors. Moreover, the sensor is developed by a simple fabrication process. Due to the excellent performance, this strain sensor can meet the demands of subtle, large and complex human motion monitoring, which indicates its tremendous application potential in health monitoring, mechanical control, real-time motion monitoring and so on.

Kinota: An Open-Source NoSQL implementation of OGC SensorThings for large-scale high-resolution real-time environmental monitoring

NASA Astrophysics Data System (ADS)

Miles, B.; Chepudira, K.; LaBar, W.

2017-12-01

The Open Geospatial Consortium (OGC) SensorThings API (STA) specification, ratified in 2016, is a next-generation open standard for enabling real-time communication of sensor data. Building on over a decade of OGC Sensor Web Enablement (SWE) Standards, STA offers a rich data model that can represent a range of sensor and phenomena types (e.g. fixed sensors sensing fixed phenomena, fixed sensors sensing moving phenomena, mobile sensors sensing fixed phenomena, and mobile sensors sensing moving phenomena) and is data agnostic. Additionally, and in contrast to previous SWE standards, STA is developer-friendly, as is evident from its convenient JSON serialization, and expressive OData-based query language (with support for geospatial queries); with its Message Queue Telemetry Transport (MQTT), STA is also well-suited to efficient real-time data publishing and discovery. All these attributes make STA potentially useful for use in environmental monitoring sensor networks. Here we present Kinota(TM), an Open-Source NoSQL implementation of OGC SensorThings for large-scale high-resolution real-time environmental monitoring. Kinota, which roughly stands for Knowledge from Internet of Things Analyses, relies on Cassandra its underlying data store, which is a horizontally scalable, fault-tolerant open-source database that is often used to store time-series data for Big Data applications (though integration with other NoSQL or rational databases is possible). With this foundation, Kinota can scale to store data from an arbitrary number of sensors collecting data every 500 milliseconds. Additionally, Kinota architecture is very modular allowing for customization by adopters who can choose to replace parts of the existing implementation when desirable. The architecture is also highly portable providing the flexibility to choose between cloud providers like azure, amazon, google etc. The scalable, flexible and cloud friendly architecture of Kinota makes it ideal for use in next-generation large-scale and high-resolution real-time environmental monitoring networks used in domains such as hydrology, geomorphology, and geophysics, as well as management applications such as flood early warning, and regulatory enforcement.

Satellite-based peatland mapping: potential of the MODIS sensor.

Treesearch

D. Pflugmacher; O.N. Krankina; W.B. Cohen

2006-01-01

Peatlands play a major role in the global carbon cycle but are largely overlooked in current large-scale vegetation mapping efforts. In this study, we investigated the potential of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to capture extent and distribution of peatlands in the St. Petersburg region of Russia.

A multilayer membrane amperometric glucose sensor fabricated using planar techniques for large-scale production.

PubMed

Matsumoto, T; Saito, S; Ikeda, S

2006-03-23

This paper reports on a multilayer membrane amperometric glucose sensor fabricated using planar techniques. It is characterized by good reproducibility and suitable for large-scale production. The glucose sensor has 82 electrode sets formed on a single glass substrate, each with a platinum working electrode (WE), a platinum counter electrode (CE) and an Ag/AgCl reference electrode (RE). The electrode sets are coated with a membrane consisting of five layers: gamma-aminopropyltriethoxysilane (gamma-APTES), Nafion, glucose oxidase (GOX), gamma-APTES and perfluorocarbon polymer (PFCP), in that order. Tests have shown that the sensor has acceptably low dispersion (relative standard deviation, R.S.D.=42.9%, n=82), a wide measurement range (1.11-111 mM) and measurement stability over a 27-day period. Measurements of the glucose concentration in a control human urine sample demonstrated that the sensor has very low dispersion (R.S.D.=2.49%, n=10).

Scaling laws for nanoFET sensors

NASA Astrophysics Data System (ADS)

Zhou, Fu-Shan; Wei, Qi-Huo

2008-01-01

The sensitive conductance change of semiconductor nanowires and carbon nanotubes in response to the binding of charged molecules provides a novel sensing modality which is generally denoted as nanoFET sensors. In this paper, we study the scaling laws of nanoplate FET sensors by simplifying nanoplates as random resistor networks with molecular receptors sitting on lattice sites. Nanowire/tube FETs are included as the limiting cases where the device width goes small. Computer simulations show that the field effect strength exerted by the binding molecules has significant impact on the scaling behaviors. When the field effect strength is small, nanoFETs have little size and shape dependence. In contrast, when the field effect strength becomes stronger, there exists a lower detection threshold for charge accumulation FETs and an upper detection threshold for charge depletion FET sensors. At these thresholds, the nanoFET devices undergo a transition between low and large sensitivities. These thresholds may set the detection limits of nanoFET sensors, while they could be eliminated by designing devices with very short source-drain distance and large width.

A Hybrid, Large-Scale Wireless Sensor Network for Real-Time Acquisition and Tracking

DTIC Science & Technology

2007-06-01

multicolor, Quantum Well Infrared Photodetector ( QWIP ), step-stare, large-format Focal Plane Array (FPA) is proposed and evaluated through performance...Photodetector ( QWIP ), step-stare, large-format Focal Plane Array (FPA) is proposed and evaluated through performance analysis. The thesis proposes...7 1. Multi-color IR Sensors - Operational Advantages ...........................8 2. Quantum-Well IR Photodetector ( QWIP

A Rapid Process for Fabricating Gas Sensors

PubMed Central

Hsiao, Chun-Ching; Luo, Li-Siang

2014-01-01

Zinc oxide (ZnO) is a low-toxicity and environmentally-friendly material applied on devices, sensors or actuators for “green” usage. A porous ZnO film deposited by a rapid process of aerosol deposition (AD) was employed as the gas-sensitive material in a CO gas sensor to reduce both manufacturing cost and time, and to further extend the AD application for a large-scale production. The relative resistance change (ΔR/R) of the ZnO gas sensor was used for gas measurement. The fabricated ZnO gas sensors were measured with operating temperatures ranging from 110 °C to 180 °C, and CO concentrations ranging from 100 ppm to 1000 ppm. The sensitivity and the response time presented good performance at increasing operating temperatures and CO concentrations. AD was successfully for applied for making ZnO gas sensors with great potential for achieving high deposition rates at low deposition temperatures, large-scale production and low cost. PMID:25010696

Review of infrared technology in The Netherlands

NASA Astrophysics Data System (ADS)

de Jong, Arie N.

1993-11-01

The use of infrared sensors in the Netherlands is substantial. Users can be found in a variety of disciplines, military as well as civil. This need for IR sensors implied a long history on IR technology and development. The result was a large technological-capability allowing the realization of IR hardware: specialized measuring equipment, engineering development models, prototype and production sensors for different applications. These applications range from small size, local radiometry up to large space-borne imaging. Large scale production of IR sensors has been realized for army vehicles. IR sensors have been introduced now in all of the armed forces. Facilities have been built to test the performance of these sensors. Models have been developed to predict the performance of a new sensor. A great effort has been spent on atmospheric research, leading to knowledge upon atmospheric- and background limitations of IR sensors.

Secure Data Aggregation with Fully Homomorphic Encryption in Large-Scale Wireless Sensor Networks.

PubMed

Li, Xing; Chen, Dexin; Li, Chunyan; Wang, Liangmin

2015-07-03

With the rapid development of wireless communication technology, sensor technology, information acquisition and processing technology, sensor networks will finally have a deep influence on all aspects of people's lives. The battery resources of sensor nodes should be managed efficiently in order to prolong network lifetime in large-scale wireless sensor networks (LWSNs). Data aggregation represents an important method to remove redundancy as well as unnecessary data transmission and hence cut down the energy used in communication. As sensor nodes are deployed in hostile environments, the security of the sensitive information such as confidentiality and integrity should be considered. This paper proposes Fully homomorphic Encryption based Secure data Aggregation (FESA) in LWSNs which can protect end-to-end data confidentiality and support arbitrary aggregation operations over encrypted data. In addition, by utilizing message authentication codes (MACs), this scheme can also verify data integrity during data aggregation and forwarding processes so that false data can be detected as early as possible. Although the FHE increase the computation overhead due to its large public key size, simulation results show that it is implementable in LWSNs and performs well. Compared with other protocols, the transmitted data and network overhead are reduced in our scheme.

Flexible strain sensor based on carbon nanotube rubber composites

NASA Astrophysics Data System (ADS)

Kim, Jin-Ho; Kim, Young-Ju; Baek, Woon Kyung; Lim, Kwon Taek; Kang, Inpil

2010-04-01

Electrically conducting rubber composites (CRC) with carbon nanotubes (CNTs) filler have received much attention as potential materials for sensors. In this work, Ethylene propylene diene M-class rubber (EPDM)/CNT composites as a novel nano sensory material were prepared to develop flexible strain sensors that can measure large deformation of flexible structures. The EPDM/CNT composites were prepared by using a Brabender mixer with multi-walled CNTs and organo-clay. A strain sensor made of EPDM/CNT composite was attached to the surface of a flexible beam and change of resistance of the strain sensor was measured with respect to the beam deflection. Resistance of the sensor was change quite linearly under the bending and compressive large beam deflection. Upon external forces, CRC deformation takes place with the micro scale change of inter-electrical condition in rubber matrix due to the change of contact resistance, and CRC reveals macro scale piezoresistivity. It is anticipated that the CNT/EPDM fibrous strain sensor can be eligible to develop a biomimetic artificial neuron that can continuously sense deformation, pressure and shear force.

A wireless soil moisture sensor powered by solar energy.

PubMed

Jiang, Mingliang; Lv, Mouchao; Deng, Zhong; Zhai, Guoliang

2017-01-01

In a variety of agricultural activities, such as irrigation scheduling and nutrient management, soil water content is regarded as an essential parameter. Either power supply or long-distance cable is hardly available within field scale. For the necessity of monitoring soil water dynamics at field scale, this study presents a wireless soil moisture sensor based on the impedance transform of the frequency domain. The sensor system is powered by solar energy, and the data can be instantly transmitted by wireless communication. The sensor electrodes are embedded into the bottom of a supporting rod so that the sensor can measure soil water contents at different depths. An optimal design with time executing sequence is considered to reduce the energy consumption. The experimental results showed that the sensor is a promising tool for monitoring moisture in large-scale farmland using solar power and wireless communication.

Large Format Transition Edge Sensor Microcalorimeter Arrays

NASA Technical Reports Server (NTRS)

Chervenak, J. A.; Adams, J. A.; Bandler, S. b.; Busch, S. E.; Eckart, M. E.; Ewin, A. E.; Finkbeiner, F. M.; Kilbourne, C. A.; Kelley, R. L.; Porst, J. P.;

Wafer-scale pixelated detector system

DOEpatents

Fahim, Farah; Deptuch, Grzegorz; Zimmerman, Tom

2017-10-17

A large area, gapless, detection system comprises at least one sensor; an interposer operably connected to the at least one sensor; and at least one application specific integrated circuit operably connected to the sensor via the interposer wherein the detection system provides high dynamic range while maintaining small pixel area and low power dissipation. Thereby the invention provides methods and systems for a wafer-scale gapless and seamless detector systems with small pixels, which have both high dynamic range and low power dissipation.

Direct measurements of local bed shear stress in the presence of pressure gradients

NASA Astrophysics Data System (ADS)

Pujara, Nimish; Liu, Philip L.-F.

2014-07-01

This paper describes the development of a shear plate sensor capable of directly measuring the local mean bed shear stress in small-scale and large-scale laboratory flumes. The sensor is capable of measuring bed shear stress in the range 200 Pa with an accuracy up to 1 %. Its size, 43 mm in the flow direction, is designed to be small enough to give spatially local measurements, and its bandwidth, 75 Hz, is high enough to resolve time-varying forcing. Typically, shear plate sensors are restricted to use in zero pressure gradient flows because secondary forces on the edge of the shear plate caused by pressure gradients can introduce large errors. However, by analysis of the pressure distribution at the edges of the shear plate in mild pressure gradients, we introduce a new methodology for correcting for the pressure gradient force. The developed sensor includes pressure tappings to measure the pressure gradient in the flow, and the methodology for correction is applied to obtain accurate measurements of bed shear stress under solitary waves in a small-scale wave flume. The sensor is also validated by measurements in a turbulent flat plate boundary layer in open channel flow.

An Integrative Structural Health Monitoring System for the Local/Global Responses of a Large-Scale Irregular Building under Construction

PubMed Central

Park, Hyo Seon; Shin, Yunah; Choi, Se Woon; Kim, Yousok

2013-01-01

In this study, a practical and integrative SHM system was developed and applied to a large-scale irregular building under construction, where many challenging issues exist. In the proposed sensor network, customized energy-efficient wireless sensing units (sensor nodes, repeater nodes, and master nodes) were employed and comprehensive communications from the sensor node to the remote monitoring server were conducted through wireless communications. The long-term (13-month) monitoring results recorded from a large number of sensors (75 vibrating wire strain gauges, 10 inclinometers, and three laser displacement sensors) indicated that the construction event exhibiting the largest influence on structural behavior was the removal of bents that were temporarily installed to support the free end of the cantilevered members during their construction. The safety of each member could be confirmed based on the quantitative evaluation of each response. Furthermore, it was also confirmed that the relation between these responses (i.e., deflection, strain, and inclination) can provide information about the global behavior of structures induced from specific events. Analysis of the measurement results demonstrates the proposed sensor network system is capable of automatic and real-time monitoring and can be applied and utilized for both the safety evaluation and precise implementation of buildings under construction. PMID:23860317

Secure Data Aggregation with Fully Homomorphic Encryption in Large-Scale Wireless Sensor Networks

PubMed Central

Li, Xing; Chen, Dexin; Li, Chunyan; Wang, Liangmin

2015-01-01

With the rapid development of wireless communication technology, sensor technology, information acquisition and processing technology, sensor networks will finally have a deep influence on all aspects of people’s lives. The battery resources of sensor nodes should be managed efficiently in order to prolong network lifetime in large-scale wireless sensor networks (LWSNs). Data aggregation represents an important method to remove redundancy as well as unnecessary data transmission and hence cut down the energy used in communication. As sensor nodes are deployed in hostile environments, the security of the sensitive information such as confidentiality and integrity should be considered. This paper proposes Fully homomorphic Encryption based Secure data Aggregation (FESA) in LWSNs which can protect end-to-end data confidentiality and support arbitrary aggregation operations over encrypted data. In addition, by utilizing message authentication codes (MACs), this scheme can also verify data integrity during data aggregation and forwarding processes so that false data can be detected as early as possible. Although the FHE increase the computation overhead due to its large public key size, simulation results show that it is implementable in LWSNs and performs well. Compared with other protocols, the transmitted data and network overhead are reduced in our scheme. PMID:26151208

Autonomous smart sensor network for full-scale structural health monitoring

NASA Astrophysics Data System (ADS)

Rice, Jennifer A.; Mechitov, Kirill A.; Spencer, B. F., Jr.; Agha, Gul A.

2010-04-01

The demands of aging infrastructure require effective methods for structural monitoring and maintenance. Wireless smart sensor networks offer the ability to enhance structural health monitoring (SHM) practices through the utilization of onboard computation to achieve distributed data management. Such an approach is scalable to the large number of sensor nodes required for high-fidelity modal analysis and damage detection. While smart sensor technology is not new, the number of full-scale SHM applications has been limited. This slow progress is due, in part, to the complex network management issues that arise when moving from a laboratory setting to a full-scale monitoring implementation. This paper presents flexible network management software that enables continuous and autonomous operation of wireless smart sensor networks for full-scale SHM applications. The software components combine sleep/wake cycling for enhanced power management with threshold detection for triggering network wide tasks, such as synchronized sensing or decentralized modal analysis, during periods of critical structural response.

Large-Scale Wireless Temperature Monitoring System for Liquefied Petroleum Gas Storage Tanks.

PubMed

Fan, Guangwen; Shen, Yu; Hao, Xiaowei; Yuan, Zongming; Zhou, Zhi

2015-09-18

Temperature distribution is a critical indicator of the health condition for Liquefied Petroleum Gas (LPG) storage tanks. In this paper, we present a large-scale wireless temperature monitoring system to evaluate the safety of LPG storage tanks. The system includes wireless sensors networks, high temperature fiber-optic sensors, and monitoring software. Finally, a case study on real-world LPG storage tanks proves the feasibility of the system. The unique features of wireless transmission, automatic data acquisition and management, local and remote access make the developed system a good alternative for temperature monitoring of LPG storage tanks in practical applications.

Embedded Electro-Optic Sensor Network for the On-Site Calibration and Real-Time Performance Monitoring of Large-Scale Phased Arrays

DTIC Science & Technology

2005-07-09

This final report summarizes the progress during the Phase I SBIR project entitled Embedded Electro - Optic Sensor Network for the On-Site Calibration...network based on an electro - optic field-detection technique (the Electro - optic Sensor Network, or ESN) for the performance evaluation of phased

System and Method for Dynamic Aeroelastic Control

NASA Technical Reports Server (NTRS)

Suh, Peter M. (Inventor)

2015-01-01

The present invention proposes a hardware and software architecture for dynamic modal structural monitoring that uses a robust modal filter to monitor a potentially very large-scale array of sensors in real time, and tolerant of asymmetric sensor noise and sensor failures, to achieve aircraft performance optimization such as minimizing aircraft flutter, drag and maximizing fuel efficiency.

Development of a Shipboard Remote Control and Telemetry Experimental System for Large-Scale Model’s Motions and Loads Measurement in Realistic Sea Waves

PubMed Central

Jiao, Jialong; Ren, Huilong; Adenya, Christiaan Adika; Chen, Chaohe

2017-01-01

Wave-induced motion and load responses are important criteria for ship performance evaluation. Physical experiments have long been an indispensable tool in the predictions of ship’s navigation state, speed, motions, accelerations, sectional loads and wave impact pressure. Currently, majority of the experiments are conducted in laboratory tank environment, where the wave environments are different from the realistic sea waves. In this paper, a laboratory tank testing system for ship motions and loads measurement is reviewed and reported first. Then, a novel large-scale model measurement technique is developed based on the laboratory testing foundations to obtain accurate motion and load responses of ships in realistic sea conditions. For this purpose, a suite of advanced remote control and telemetry experimental system was developed in-house to allow for the implementation of large-scale model seakeeping measurement at sea. The experimental system includes a series of technique sensors, e.g., the Global Position System/Inertial Navigation System (GPS/INS) module, course top, optical fiber sensors, strain gauges, pressure sensors and accelerometers. The developed measurement system was tested by field experiments in coastal seas, which indicates that the proposed large-scale model testing scheme is capable and feasible. Meaningful data including ocean environment parameters, ship navigation state, motions and loads were obtained through the sea trial campaign. PMID:29109379

Organic field effect transistor with ultra high amplification

NASA Astrophysics Data System (ADS)

Torricelli, Fabrizio

2016-09-01

High-gain transistors are essential for the large-scale circuit integration, high-sensitivity sensors and signal amplification in sensing systems. Unfortunately, organic field-effect transistors show limited gain, usually of the order of tens, because of the large contact resistance and channel-length modulation. Here we show organic transistors fabricated on plastic foils enabling unipolar amplifiers with ultra-gain. The proposed approach is general and opens up new opportunities for ultra-large signal amplification in organic circuits and sensors.

Sub-Scale Analysis of New Large Aircraft Pool Fire-Suppression

DTIC Science & Technology

2016-01-01

discrete ordinates radiation and single step Khan and Greeves soot model provided radiation and soot interaction. Agent spray dynamics were...Notable differences observed showed a modeled increase in the mockup surface heat-up rate as well as a modeled decreased rate of soot production...488 K SUPPRESSION STARTED  Large deviation between sensors due to sensor alignment challenges and asymmetric fuel surface ignition  Unremarkable

Automated Decomposition of Model-based Learning Problems

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Millar, Bill

1996-01-01

A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.

Bioinspired principles for large-scale networked sensor systems: an overview.

PubMed

Jacobsen, Rune Hylsberg; Zhang, Qi; Toftegaard, Thomas Skjødeberg

2011-01-01

Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy.

Smart sensors II; Proceedings of the Seminar, San Diego, CA, July 31, August 1, 1980

NASA Astrophysics Data System (ADS)

Barbe, D. F.

1980-01-01

Topics discussed include technology for smart sensors, smart sensors for tracking and surveillance, and techniques and algorithms for smart sensors. Papers are presented on the application of very large scale integrated circuits to smart sensors, imaging charge-coupled devices for deep-space surveillance, ultra-precise star tracking using charge coupled devices, and automatic target identification of blurred images with super-resolution features. Attention is also given to smart sensors for terminal homing, algorithms for estimating image position, and the computational efficiency of multiple image registration algorithms.

SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data.

PubMed

Salehi, Ali; Jimenez-Berni, Jose; Deery, David M; Palmer, Doug; Holland, Edward; Rozas-Larraondo, Pablo; Chapman, Scott C; Georgakopoulos, Dimitrios; Furbank, Robert T

2015-01-01

To our knowledge, there is no software or database solution that supports large volumes of biological time series sensor data efficiently and enables data visualization and analysis in real time. Existing solutions for managing data typically use unstructured file systems or relational databases. These systems are not designed to provide instantaneous response to user queries. Furthermore, they do not support rapid data analysis and visualization to enable interactive experiments. In large scale experiments, this behaviour slows research discovery, discourages the widespread sharing and reuse of data that could otherwise inform critical decisions in a timely manner and encourage effective collaboration between groups. In this paper we present SensorDB, a web based virtual laboratory that can manage large volumes of biological time series sensor data while supporting rapid data queries and real-time user interaction. SensorDB is sensor agnostic and uses web-based, state-of-the-art cloud and storage technologies to efficiently gather, analyse and visualize data. Collaboration and data sharing between different agencies and groups is thereby facilitated. SensorDB is available online at http://sensordb.csiro.au.

A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks

PubMed Central

Zhang, Gongxuan; Wang, Yongli; Wang, Tianshu

2018-01-01

We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach. PMID:29734718

A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks.

PubMed

Vajdi, Ahmadreza; Zhang, Gongxuan; Zhou, Junlong; Wei, Tongquan; Wang, Yongli; Wang, Tianshu

2018-05-04

We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach.

In-situ device integration of large-area patterned organic nanowire arrays for high-performance optical sensors

PubMed Central

Wu, Yiming; Zhang, Xiujuan; Pan, Huanhuan; Deng, Wei; Zhang, Xiaohong; Zhang, Xiwei; Jie, Jiansheng

2013-01-01

Single-crystalline organic nanowires (NWs) are important building blocks for future low-cost and efficient nano-optoelectronic devices due to their extraordinary properties. However, it remains a critical challenge to achieve large-scale organic NW array assembly and device integration. Herein, we demonstrate a feasible one-step method for large-area patterned growth of cross-aligned single-crystalline organic NW arrays and their in-situ device integration for optical image sensors. The integrated image sensor circuitry contained a 10 × 10 pixel array in an area of 1.3 × 1.3 mm2, showing high spatial resolution, excellent stability and reproducibility. More importantly, 100% of the pixels successfully operated at a high response speed and relatively small pixel-to-pixel variation. The high yield and high spatial resolution of the operational pixels, along with the high integration level of the device, clearly demonstrate the great potential of the one-step organic NW array growth and device construction approach for large-scale optoelectronic device integration. PMID:24287887

Large-Scale Wireless Temperature Monitoring System for Liquefied Petroleum Gas Storage Tanks

PubMed Central

Fan, Guangwen; Shen, Yu; Hao, Xiaowei; Yuan, Zongming; Zhou, Zhi

2015-01-01

Temperature distribution is a critical indicator of the health condition for Liquefied Petroleum Gas (LPG) storage tanks. In this paper, we present a large-scale wireless temperature monitoring system to evaluate the safety of LPG storage tanks. The system includes wireless sensors networks, high temperature fiber-optic sensors, and monitoring software. Finally, a case study on real-world LPG storage tanks proves the feasibility of the system. The unique features of wireless transmission, automatic data acquisition and management, local and remote access make the developed system a good alternative for temperature monitoring of LPG storage tanks in practical applications. PMID:26393596

Evaluation of Smartphone Inertial Sensor Performance for Cross-Platform Mobile Applications

PubMed Central

Kos, Anton; Tomažič, Sašo; Umek, Anton

2016-01-01

Smartphone sensors are being increasingly used in mobile applications. The performance of sensors varies considerably among different smartphone models and the development of a cross-platform mobile application might be a very complex and demanding task. A publicly accessible resource containing real-life-situation smartphone sensor parameters could be of great help for cross-platform developers. To address this issue we have designed and implemented a pilot participatory sensing application for measuring, gathering, and analyzing smartphone sensor parameters. We start with smartphone accelerometer and gyroscope bias and noise parameters. The application database presently includes sensor parameters of more than 60 different smartphone models of different platforms. It is a modest, but important start, offering information on several statistical parameters of the measured smartphone sensors and insights into their performance. The next step, a large-scale cloud-based version of the application, is already planned. The large database of smartphone sensor parameters may prove particularly useful for cross-platform developers. It may also be interesting for individual participants who would be able to check-up and compare their smartphone sensors against a large number of similar or identical models. PMID:27049391

Bioinspired Principles for Large-Scale Networked Sensor Systems: An Overview

PubMed Central

Jacobsen, Rune Hylsberg; Zhang, Qi; Toftegaard, Thomas Skjødeberg

2011-01-01

Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy. PMID:22163841

Fusion of sensor geometry into additive strain fields measured with sensing skin

NASA Astrophysics Data System (ADS)

Downey, Austin; Sadoughi, Mohammadkazem; Laflamme, Simon; Hu, Chao

2018-07-01

Recently, numerous studies have been conducted on flexible skin-like membranes for the cost effective monitoring of large-scale structures. The authors have proposed a large-area electronic consisting of a soft elastomeric capacitor (SEC) that transduces a structure’s strain into a measurable change in capacitance. Arranged in a network configuration, SECs deployed onto the surface of a structure could be used to reconstruct strain maps. Several regression methods have been recently developed with the purpose of reconstructing such maps, but all these algorithms assumed that each SEC-measured strain located at its geometric center. This assumption may not be realistic since an SEC measures the average strain value of the whole area covered by the sensor. One solution is to reduce the size of each SEC, but this would also increase the number of required sensors needed to cover the large-scale structure, therefore increasing the need for the power and data acquisition capabilities. Instead, this study proposes an algorithm that accounts for the sensor’s strain averaging feature by adjusting the strain measurements and constructing a full-field strain map using the kriging interpolation method. The proposed algorithm fuses the geometry of an SEC sensor into the strain map reconstruction in order to adaptively adjust the average kriging-estimated strain of the area monitored by the sensor to the signal. Results show that by considering the sensor geometry, in addition to the sensor signal and location, the proposed strain map adjustment algorithm is capable of producing more accurate full-field strain maps than the traditional spatial interpolation method that considered only signal and location.

The “Wireless Sensor Networks for City-Wide Ambient Intelligence (WISE-WAI)” Project

PubMed Central

Casari, Paolo; Castellani, Angelo P.; Cenedese, Angelo; Lora, Claudio; Rossi, Michele; Schenato, Luca; Zorzi, Michele

2009-01-01

This paper gives a detailed technical overview of some of the activities carried out in the context of the “Wireless Sensor networks for city-Wide Ambient Intelligence (WISE-WAI)” project, funded by the Cassa di Risparmio di Padova e Rovigo Foundation, Italy. The main aim of the project is to demonstrate the feasibility of large-scale wireless sensor network deployments, whereby tiny objects integrating one or more environmental sensors (humidity, temperature, light intensity), a microcontroller and a wireless transceiver are deployed over a large area, which in this case involves the buildings of the Department of Information Engineering at the University of Padova. We will describe how the network is organized to provide full-scale automated functions, and which services and applications it is configured to provide. These applications include long-term environmental monitoring, alarm event detection and propagation, single-sensor interrogation, localization and tracking of objects, assisted navigation, as well as fast data dissemination services to be used, e.g., to rapidly re-program all sensors over-the-air. The organization of such a large testbed requires notable efforts in terms of communication protocols and strategies, whose design must pursue scalability, energy efficiency (while sensors are connected through USB cables for logging and debugging purposes, most of them will be battery-operated), as well as the capability to support applications with diverse requirements. These efforts, the description of a subset of the results obtained so far, and of the final objectives to be met are the scope of the present paper. PMID:22408513

Sensor Measurement Strategies for Monitoring Offshore Wind and Wave Energy Devices

NASA Astrophysics Data System (ADS)

O'Donnell, Deirdre; Srbinovsky, Bruno; Murphy, Jimmy; Popovici, Emanuel; Pakrashi, Vikram

2015-07-01

While the potential of offshore wind and wave energy devices is well established and accepted, operations and maintenance issues are still not very well researched or understood. In this regard, scaled model testing has gained popularity over time for such devices at various technological readiness levels. The dynamic response of these devices are typically measured by different instruments during such scaled tests but agreed sensor choice, measurement and placement guidelines are still not in place. This paper compared the dynamic responses of some of these sensors from a scaled ocean wave testing to highlight the importance of sensor measurement strategies. The possibility of using multiple, cheaper sensors of seemingly inferior performance as opposed to the deployment of a small number of expensive and accurate sensors are also explored. An energy aware adaptive sampling theory is applied to highlight the possibility of more efficient computing when large volumes of data are available from the tested structures. Efficient sensor measurement strategies are expected to have a positive impact on the development of an device at different technological readiness levels while it is expected to be helpful in reducing operation and maintenance costs if such an approach is considered for the devices when they are in operation.

SMOS soil moisture validation with U.S. in situ newworks

USDA-ARS?s Scientific Manuscript database

Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors using a variety of retrieval methods. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. Since it is a new sensor u...

A Fluidically Tunable Metasurface Absorber for Flexible Large-Scale Wireless Ethanol Sensor Applications.

PubMed

Kim, Hyung Ki; Lee, Dongju; Lim, Sungjoon

2016-08-06

In this paper, a novel flexible tunable metasurface absorber is proposed for large-scale remote ethanol sensor applications. The proposed metasurface absorber consists of periodic split-ring-cross resonators (SRCRs) and microfluidic channels. The SRCR patterns are inkjet-printed on paper using silver nanoparticle inks. The microfluidic channels are laser-etched on polydimethylsiloxane (PDMS) material. The proposed absorber can detect changes in the effective permittivity for different liquids. Therefore, the absorber can be used for a remote chemical sensor by detecting changes in the resonant frequencies. The performance of the proposed absorber is demonstrated with full-wave simulation and measurement results. The experimental results show the resonant frequency increases from 8.9 GHz to 10.04 GHz when the concentration of ethanol is changed from 0% to 100%. In addition, the proposed absorber shows linear frequency shift from 20% to 80% of the different concentrations of ethanol.

A Review of Current Neuromorphic Approaches for Vision, Auditory, and Olfactory Sensors.

PubMed

Vanarse, Anup; Osseiran, Adam; Rassau, Alexander

2016-01-01

Conventional vision, auditory, and olfactory sensors generate large volumes of redundant data and as a result tend to consume excessive power. To address these shortcomings, neuromorphic sensors have been developed. These sensors mimic the neuro-biological architecture of sensory organs using aVLSI (analog Very Large Scale Integration) and generate asynchronous spiking output that represents sensing information in ways that are similar to neural signals. This allows for much lower power consumption due to an ability to extract useful sensory information from sparse captured data. The foundation for research in neuromorphic sensors was laid more than two decades ago, but recent developments in understanding of biological sensing and advanced electronics, have stimulated research on sophisticated neuromorphic sensors that provide numerous advantages over conventional sensors. In this paper, we review the current state-of-the-art in neuromorphic implementation of vision, auditory, and olfactory sensors and identify key contributions across these fields. Bringing together these key contributions we suggest a future research direction for further development of the neuromorphic sensing field.

Resolving uncertainties in the urban air quality, climate, and vegetation nexus through citizen science, satellite imagery, and atmospheric modeling

NASA Astrophysics Data System (ADS)

Jenerette, D.; Wang, J.; Chandler, M.; Ripplinger, J.; Koutzoukis, S.; Ge, C.; Castro Garcia, L.; Kucera, D.; Liu, X.

2017-12-01

Large uncertainties remain in identifying the distribution of urban air quality and temperature risks across neighborhood to regional scales. Nevertheless, many cities are actively expanding vegetation with an expectation to moderate both climate and air quality risks. We address these uncertainties through an integrated analysis of satellite data, atmospheric modeling, and in-situ environmental sensor networks maintained by citizen scientists. During the summer of 2017 we deployed neighborhood-scale networks of air temperature and ozone sensors through three campaigns across urbanized southern California. During each five-week campaign we deployed six sensor nodes that included an EPA federal equivalent method ozone sensor and a suite of meteorological sensors. Each node was further embedded in a network of 100 air temperature sensors that combined a randomized design developed by the research team and a design co-created by citizen scientists. Between 20 and 60 citizen scientists were recruited for each campaign, with local partners supporting outreach and training to ensure consistent deployment and data gathering. We observed substantial variation in both temperature and ozone concentrations at scales less than 4km, whole city, and the broader southern California region. At the whole city scale the average spatial variation with our ozone sensor network just for city of Long Beach was 26% of the mean, while corresponding variation in air temperature was only 7% of the mean. These findings contrast with atmospheric model estimates of variation at the regional scale of 11% and 1%. Our results show the magnitude of fine-scale variation underestimated by current models and may also suggest scaling functions that can connect neighborhood and regional variation in both ozone and temperature risks in southern California. By engaging citizen science with high quality sensors, satellite data, and real-time forecasting, our results help identify magnitudes of climate and air quality risk variation across scales and can guide individual decisions and urban policies surrounding vegetation to moderate these risks.

Performance of Large Format Transition Edge Sensor Microcalorimeter Arrays

NASA Technical Reports Server (NTRS)

Chervenak, J. A.; Adams, J. A.; Bandler, S. B.; Busch, S. E.; Eckart, M. E.; Ewin, A. E.; Finkbeiner, F. M.; Kilbourne, C. A.; Kelley, R. L.; Porst, J. P.;

Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

PubMed Central

Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor

2014-01-01

Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications. PMID:24678277

Switching algorithm for maglev train double-modular redundant positioning sensors.

PubMed

He, Ning; Long, Zhiqiang; Xue, Song

2012-01-01

High-resolution positioning for maglev trains is implemented by detecting the tooth-slot structure of the long stator installed along the rail, but there are large joint gaps between long stator sections. When a positioning sensor is below a large joint gap, its positioning signal is invalidated, thus double-modular redundant positioning sensors are introduced into the system. This paper studies switching algorithms for these redundant positioning sensors. At first, adaptive prediction is applied to the sensor signals. The prediction errors are used to trigger sensor switching. In order to enhance the reliability of the switching algorithm, wavelet analysis is introduced to suppress measuring disturbances without weakening the signal characteristics reflecting the stator joint gap based on the correlation between the wavelet coefficients of adjacent scales. The time delay characteristics of the method are analyzed to guide the algorithm simplification. Finally, the effectiveness of the simplified switching algorithm is verified through experiments.

Switching Algorithm for Maglev Train Double-Modular Redundant Positioning Sensors

PubMed Central

He, Ning; Long, Zhiqiang; Xue, Song

2012-01-01

High-resolution positioning for maglev trains is implemented by detecting the tooth-slot structure of the long stator installed along the rail, but there are large joint gaps between long stator sections. When a positioning sensor is below a large joint gap, its positioning signal is invalidated, thus double-modular redundant positioning sensors are introduced into the system. This paper studies switching algorithms for these redundant positioning sensors. At first, adaptive prediction is applied to the sensor signals. The prediction errors are used to trigger sensor switching. In order to enhance the reliability of the switching algorithm, wavelet analysis is introduced to suppress measuring disturbances without weakening the signal characteristics reflecting the stator joint gap based on the correlation between the wavelet coefficients of adjacent scales. The time delay characteristics of the method are analyzed to guide the algorithm simplification. Finally, the effectiveness of the simplified switching algorithm is verified through experiments. PMID:23112657

Thermal Testing and Integration: Magnetospheric MultiScale (MMS) Observatories with Digital 1-Wire Sensors

NASA Technical Reports Server (NTRS)

Solimani, Jason A.; Rosanova, Santino

2015-01-01

Thermocouples require two thin wires to be routed out of the spacecraft to connect to the ground support equipment used to monitor and record the temperature data. This large number of wires that exit the observatory complicates integration and creates an undesirable heat path during testing. These wires exiting the spacecraft need to be characterized as a thermal short that will not exist during flight. To minimize complexity and reduce thermal variables from these ground support equipment (GSE) wires, MMS pursued a hybrid path for temperature monitoring, utilizing thermocouples and digital 1-wire temperature sensors. Digital 1-wire sensors can greatly reduce harness mass, length and complexity as they can be spliced together. For MMS, 350 digital 1-wire sensors were installed on the spacecraft with only 18 wires exiting as opposed to a potential 700 thermocouple wires. Digital 1-wire sensors had not been used in such a large scale at NASAGSFC prior to the MMS mission. During the MMS thermal vacuum testing a lessons learned matrix was formulated that will assist future integration of 1-wires into thermal testing and one day into flight.

Implementation of Cyberinfrastructure and Data Management Workflow for a Large-Scale Sensor Network

NASA Astrophysics Data System (ADS)

Jones, A. S.; Horsburgh, J. S.

2014-12-01

Monitoring with in situ environmental sensors and other forms of field-based observation presents many challenges for data management, particularly for large-scale networks consisting of multiple sites, sensors, and personnel. The availability and utility of these data in addressing scientific questions relies on effective cyberinfrastructure that facilitates transformation of raw sensor data into functional data products. It also depends on the ability of researchers to share and access the data in useable formats. In addition to addressing the challenges presented by the quantity of data, monitoring networks need practices to ensure high data quality, including procedures and tools for post processing. Data quality is further enhanced if practitioners are able to track equipment, deployments, calibrations, and other events related to site maintenance and associate these details with observational data. In this presentation we will describe the overall workflow that we have developed for research groups and sites conducting long term monitoring using in situ sensors. Features of the workflow include: software tools to automate the transfer of data from field sites to databases, a Python-based program for data quality control post-processing, a web-based application for online discovery and visualization of data, and a data model and web interface for managing physical infrastructure. By automating the data management workflow, the time from collection to analysis is reduced and sharing and publication is facilitated. The incorporation of metadata standards and descriptions and the use of open-source tools enhances the sustainability and reusability of the data. We will describe the workflow and tools that we have developed in the context of the iUTAH (innovative Urban Transitions and Aridregion Hydrosustainability) monitoring network. The iUTAH network consists of aquatic and climate sensors deployed in three watersheds to monitor Gradients Along Mountain to Urban Transitions (GAMUT). The variety of environmental sensors and the multi-watershed, multi-institutional nature of the network necessitate a well-planned and efficient workflow for acquiring, managing, and sharing sensor data, which should be useful for similar large-scale and long-term networks.

Three-dimensional estimates of tree canopies: Scaling from high-resolution UAV data to satellite observations

NASA Astrophysics Data System (ADS)

Sankey, T.; Donald, J.; McVay, J.

2015-12-01

High resolution remote sensing images and datasets are typically acquired at a large cost, which poses big a challenge for many scientists. Northern Arizona University recently acquired a custom-engineered, cutting-edge UAV and we can now generate our own images with the instrument. The UAV has a unique capability to carry a large payload including a hyperspectral sensor, which images the Earth surface in over 350 spectral bands at 5 cm resolution, and a lidar scanner, which images the land surface and vegetation in 3-dimensions. Both sensors represent the newest available technology with very high resolution, precision, and accuracy. Using the UAV sensors, we are monitoring the effects of regional forest restoration treatment efforts. Individual tree canopy width and height are measured in the field and via the UAV sensors. The high-resolution UAV images are then used to segment individual tree canopies and to derive 3-dimensional estimates. The UAV image-derived variables are then correlated to the field-based measurements and scaled to satellite-derived tree canopy measurements. The relationships between the field-based and UAV-derived estimates are then extrapolated to a larger area to scale the tree canopy dimensions and to estimate tree density within restored and control forest sites.

Sap flow sensors: construction, quality control and comparison.

PubMed

Davis, Tyler W; Kuo, Chen-Min; Liang, Xu; Yu, Pao-Shan

2012-01-01

This work provides a design for two types of sensors, based on the thermal dissipation and heat ratio methods of sap flow calculation, for moderate to large scale deployments for the purpose of monitoring tree transpiration. These designs include a procedure for making these sensors, a quality control method for the final products, and a complete list of components with vendors and pricing information. Both sensor designs were field tested alongside a commercial sap flow sensor to assess their performance and show the importance for quality controlling the sensor outputs. Results show that for roughly 2% of the cost of commercial sensors, self-made sap flow sensors can provide acceptable estimates of the sap flow measurements compared to the commercial sensors.

A low-frequency chip-scale optomechanical oscillator with 58 kHz mechanical stiffening and more than 100th-order stable harmonics.

PubMed

Huang, Yongjun; Flores, Jaime Gonzalo Flor; Cai, Ziqiang; Yu, Mingbin; Kwong, Dim-Lee; Wen, Guangjun; Churchill, Layne; Wong, Chee Wei

2017-06-29

For the sensitive high-resolution force- and field-sensing applications, the large-mass microelectromechanical system (MEMS) and optomechanical cavity have been proposed to realize the sub-aN/Hz 1/2 resolution levels. In view of the optomechanical cavity-based force- and field-sensors, the optomechanical coupling is the key parameter for achieving high sensitivity and resolution. Here we demonstrate a chip-scale optomechanical cavity with large mass which operates at ≈77.7 kHz fundamental mode and intrinsically exhibiting large optomechanical coupling of 44 GHz/nm or more, for both optical resonance modes. The mechanical stiffening range of ≈58 kHz and a more than 100 th -order harmonics are obtained, with which the free-running frequency instability is lower than 10 -6 at 100 ms integration time. Such results can be applied to further improve the sensing performance of the optomechanical inspired chip-scale sensors.

Microfabrication techniques for integrated sensors and microsystems.

PubMed

Wise, K D; Najafi, K

1991-11-29

Integrated sensors and actuators are rapidly evolving to provide an important link between very large scale integrated circuits and nonelectronic monitoring and control applications ranging from biomedicine to automated manufacturing. As they continue to expand, entire microsystems merging electrical, mechanical, thermal, optical, magnetic, and perhaps chemical components should be possible on a common substrate.

Scalable Microfabrication Procedures for Adhesive-Integrated Flexible and Stretchable Electronic Sensors.

PubMed

Kang, Dae Y; Kim, Yun-Soung; Ornelas, Gladys; Sinha, Mridu; Naidu, Keerthiga; Coleman, Todd P

2015-09-16

New classes of ultrathin flexible and stretchable devices have changed the way modern electronics are designed to interact with their target systems. Though more and more novel technologies surface and steer the way we think about future electronics, there exists an unmet need in regards to optimizing the fabrication procedures for these devices so that large-scale industrial translation is realistic. This article presents an unconventional approach for facile microfabrication and processing of adhesive-peeled (AP) flexible sensors. By assembling AP sensors on a weakly-adhering substrate in an inverted fashion, we demonstrate a procedure with 50% reduced end-to-end processing time that achieves greater levels of fabrication yield. The methodology is used to demonstrate the fabrication of electrical and mechanical flexible and stretchable AP sensors that are peeled-off their carrier substrates by consumer adhesives. In using this approach, we outline the manner by which adhesion is maintained and buckling is reduced for gold film processing on polydimethylsiloxane substrates. In addition, we demonstrate the compatibility of our methodology with large-scale post-processing using a roll-to-roll approach.

Nano-imprint gold grating as refractive index sensor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumari, Sudha; Mohapatra, Saswat; Moirangthem, Rakesh S.

Large scale of fabrication of plasmonic nanostructures has been a challenging task due to time consuming process and requirement of expensive nanofabrication tools such as electron beam lithography system, focused ion beam system, and extreme UV photolithography system. Here, we present a cost-effective fabrication technique so called soft nanoimprinting to fabricate nanostructures on the larger sample area. In our fabrication process, a commercially available optical DVD disc was used as a template which was imprinted on a polymer glass substrate to prepare 1D polymer nano-grating. A homemade nanoimprinting setup was used in this fabrication process. Further, a label-free refractive indexmore » sensor was developed by utilizing the properties of surface plasmon resonance (SPR) of a gold coated 1D polymer nano-grating. Refractive index sensing was tested by exposing different solutions of glycerol-water mixture on the surface of gold nano-grating. The calculated bulk refractive index sensitivity was found to be 751nm/RIU. We believed that our proposed SPR sensor could be a promising candidate for developing low-cost refractive index sensor with high sensitivity on a large scale.« less

Scalable Microfabrication Procedures for Adhesive-Integrated Flexible and Stretchable Electronic Sensors

PubMed Central

Kang, Dae Y.; Kim, Yun-Soung; Ornelas, Gladys; Sinha, Mridu; Naidu, Keerthiga; Coleman, Todd P.

2015-01-01

New classes of ultrathin flexible and stretchable devices have changed the way modern electronics are designed to interact with their target systems. Though more and more novel technologies surface and steer the way we think about future electronics, there exists an unmet need in regards to optimizing the fabrication procedures for these devices so that large-scale industrial translation is realistic. This article presents an unconventional approach for facile microfabrication and processing of adhesive-peeled (AP) flexible sensors. By assembling AP sensors on a weakly-adhering substrate in an inverted fashion, we demonstrate a procedure with 50% reduced end-to-end processing time that achieves greater levels of fabrication yield. The methodology is used to demonstrate the fabrication of electrical and mechanical flexible and stretchable AP sensors that are peeled-off their carrier substrates by consumer adhesives. In using this approach, we outline the manner by which adhesion is maintained and buckling is reduced for gold film processing on polydimethylsiloxane substrates. In addition, we demonstrate the compatibility of our methodology with large-scale post-processing using a roll-to-roll approach. PMID:26389915

Nanowire-nanopore transistor sensor for DNA detection during translocation

NASA Astrophysics Data System (ADS)

Xie, Ping; Xiong, Qihua; Fang, Ying; Qing, Quan; Lieber, Charles

2011-03-01

Nanopore sequencing, as a promising low cost, high throughput sequencing technique, has been proposed more than a decade ago. Due to the incompatibility between small ionic current signal and fast translocation speed and the technical difficulties on large scale integration of nanopore for direct ionic current sequencing, alternative methods rely on integrated DNA sensors have been proposed, such as using capacitive coupling or tunnelling current etc. But none of them have been experimentally demonstrated yet. Here we show that for the first time an amplified sensor signal has been experimentally recorded from a nanowire-nanopore field effect transistor sensor during DNA translocation. Independent multi-channel recording was also demonstrated for the first time. Our results suggest that the signal is from highly localized potential change caused by DNA translocation in none-balanced buffer condition. Given this method may produce larger signal for smaller nanopores, we hope our experiment can be a starting point for a new generation of nanopore sequencing devices with larger signal, higher bandwidth and large-scale multiplexing capability and finally realize the ultimate goal of low cost high throughput sequencing.

Sensor-Aware Recognition and Tracking for Wide-Area Augmented Reality on Mobile Phones

PubMed Central

Chen, Jing; Cao, Ruochen; Wang, Yongtian

2015-01-01

Wide-area registration in outdoor environments on mobile phones is a challenging task in mobile augmented reality fields. We present a sensor-aware large-scale outdoor augmented reality system for recognition and tracking on mobile phones. GPS and gravity information is used to improve the VLAD performance for recognition. A kind of sensor-aware VLAD algorithm, which is self-adaptive to different scale scenes, is utilized to recognize complex scenes. Considering vision-based registration algorithms are too fragile and tend to drift, data coming from inertial sensors and vision are fused together by an extended Kalman filter (EKF) to achieve considerable improvements in tracking stability and robustness. Experimental results show that our method greatly enhances the recognition rate and eliminates the tracking jitters. PMID:26690439

Sensor-Aware Recognition and Tracking for Wide-Area Augmented Reality on Mobile Phones.

PubMed

Chen, Jing; Cao, Ruochen; Wang, Yongtian

2015-12-10

Wide-area registration in outdoor environments on mobile phones is a challenging task in mobile augmented reality fields. We present a sensor-aware large-scale outdoor augmented reality system for recognition and tracking on mobile phones. GPS and gravity information is used to improve the VLAD performance for recognition. A kind of sensor-aware VLAD algorithm, which is self-adaptive to different scale scenes, is utilized to recognize complex scenes. Considering vision-based registration algorithms are too fragile and tend to drift, data coming from inertial sensors and vision are fused together by an extended Kalman filter (EKF) to achieve considerable improvements in tracking stability and robustness. Experimental results show that our method greatly enhances the recognition rate and eliminates the tracking jitters.

Marine Vehicle Sensor Network Architecture and Protocol Designs for Ocean Observation

PubMed Central

Zhang, Shaowei; Yu, Jiancheng; Zhang, Aiqun; Yang, Lei; Shu, Yeqiang

2012-01-01

The micro-scale and meso-scale ocean dynamic processes which are nonlinear and have large variability, have a significant impact on the fisheries, natural resources, and marine climatology. A rapid, refined and sophisticated observation system is therefore needed in marine scientific research. The maneuverability and controllability of mobile sensor platforms make them a preferred choice to establish ocean observing networks, compared to the static sensor observing platform. In this study, marine vehicles are utilized as the nodes of mobile sensor networks for coverage sampling of a regional ocean area and ocean feature tracking. A synoptic analysis about marine vehicle dynamic control, multi vehicles mission assignment and path planning methods, and ocean feature tracking and observing techniques is given. Combined with the observation plan in the South China Sea, we provide an overview of the mobile sensor networks established with marine vehicles, and the corresponding simulation results. PMID:22368475

A Ubiquitous Sensor Network Platform for Integrating Smart Devices into the Semantic Sensor Web

PubMed Central

de Vera, David Díaz Pardo; Izquierdo, Álvaro Sigüenza; Vercher, Jesús Bernat; Gómez, Luis Alfonso Hernández

2014-01-01

Ongoing Sensor Web developments make a growing amount of heterogeneous sensor data available to smart devices. This is generating an increasing demand for homogeneous mechanisms to access, publish and share real-world information. This paper discusses, first, an architectural solution based on Next Generation Networks: a pilot Telco Ubiquitous Sensor Network (USN) Platform that embeds several OGC® Sensor Web services. This platform has already been deployed in large scale projects. Second, the USN-Platform is extended to explore a first approach to Semantic Sensor Web principles and technologies, so that smart devices can access Sensor Web data, allowing them also to share richer (semantically interpreted) information. An experimental scenario is presented: a smart car that consumes and produces real-world information which is integrated into the Semantic Sensor Web through a Telco USN-Platform. Performance tests revealed that observation publishing times with our experimental system were well within limits compatible with the adequate operation of smart safety assistance systems in vehicles. On the other hand, response times for complex queries on large repositories may be inappropriate for rapid reaction needs. PMID:24945678

A ubiquitous sensor network platform for integrating smart devices into the semantic sensor web.

PubMed

de Vera, David Díaz Pardo; Izquierdo, Alvaro Sigüenza; Vercher, Jesús Bernat; Hernández Gómez, Luis Alfonso

2014-06-18

Ongoing Sensor Web developments make a growing amount of heterogeneous sensor data available to smart devices. This is generating an increasing demand for homogeneous mechanisms to access, publish and share real-world information. This paper discusses, first, an architectural solution based on Next Generation Networks: a pilot Telco Ubiquitous Sensor Network (USN) Platform that embeds several OGC® Sensor Web services. This platform has already been deployed in large scale projects. Second, the USN-Platform is extended to explore a first approach to Semantic Sensor Web principles and technologies, so that smart devices can access Sensor Web data, allowing them also to share richer (semantically interpreted) information. An experimental scenario is presented: a smart car that consumes and produces real-world information which is integrated into the Semantic Sensor Web through a Telco USN-Platform. Performance tests revealed that observation publishing times with our experimental system were well within limits compatible with the adequate operation of smart safety assistance systems in vehicles. On the other hand, response times for complex queries on large repositories may be inappropriate for rapid reaction needs.

Low-cost Photoacoustic-based Measurement System for Carbon Dioxide Fluxes with the Potential for large-scale Monitoring

NASA Astrophysics Data System (ADS)

Scholz, L. T.; Bierer, B.; Ortiz Perez, A.; Woellenstein, J.; Sachs, T.; Palzer, S.

2016-12-01

The determination of carbon dioxide (CO2) fluxes between ecosystems and the atmosphere is crucial for understanding ecological processes on regional and global scales. High quality data sets with full uncertainty estimates are needed to evaluate model simulations. However, current flux monitoring techniques are unsuitable to provide reliable data of a large area at both a detailed level and an appropriate resolution, at best in combination with a high sampling rate. Currently used sensing technologies, such as non-dispersive infrared (NDIR) gas analyzers, cannot be deployed in large numbers to provide high spatial resolution due to their costs and complex maintenance requirements. Here, we propose a novel CO2 measurement system, whose gas sensing unit is made up of low-cost, low-power consuming components only, such as an IR-LED and a photoacoustic detector. The sensor offers a resolution of < 50 ppm in the interesting concentration range up to 5000 ppm and an almost linear and fast sensor response of just a few seconds. Since the sensor can be applied in-situ without special precautions, it allows for environmental monitoring in a non-invasive way. Its low energy consumption enables long-term measurements. The low overall costs favor the manufacturing in large quantities. This allows the operation of multiple sensors at a reasonable price and thus provides concentration measurements at any desired spatial coverage and at high temporal resolution. With appropriate 3D configuration of the units, vertical and horizontal fluxes can be determined. By applying a closely meshed wireless sensor network, inhomogeneities as well as CO2 sources and sinks in the lower atmosphere can be monitored. In combination with sensors for temperature, pressure and humidity, our sensor paves the way towards the reliable and extensive monitoring of ecosystem-atmosphere exchange rates. The technique can also be easily adapted to other relevant greenhouse gases.

Turbofan engine demonstration of sensor failure detection

NASA Technical Reports Server (NTRS)

Merrill, Walter C.; Delaat, John C.; Abdelwahab, Mahmood

1991-01-01

In the paper, the results of a full-scale engine demonstration of a sensor failure detection algorithm are presented. The algorithm detects, isolates, and accommodates sensor failures using analytical redundancy. The experimental hardware, including the F100 engine, is described. Demonstration results were obtained over a large portion of a typical flight envelope for the F100 engine. They include both subsonic and supersonic conditions at both medium and full, nonafter burning, power. Estimated accuracy, minimum detectable levels of sensor failures, and failure accommodation performance for an F100 turbofan engine control system are discussed.

Twitter web-service for soft agent reporting in persistent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2010-04-01

Persistent surveillance is an intricate process requiring monitoring, gathering, processing, tracking, and characterization of many spatiotemporal events occurring concurrently. Data associated with events can be readily attained by networking of hard (physical) sensors. Sensors may have homogeneous or heterogeneous (hybrid) sensing modalities with different communication bandwidth requirements. Complimentary to hard sensors are human observers or "soft sensors" that can report occurrences of evolving events via different communication devices (e.g., texting, cell phones, emails, instant messaging, etc.) to the command control center. However, networking of human observers in ad-hoc way is rather a difficult task. In this paper, we present a Twitter web-service for soft agent reporting in persistent surveillance systems (called Web-STARS). The objective of this web-service is to aggregate multi-source human observations in hybrid sensor networks rapidly. With availability of Twitter social network, such a human networking concept can not only be realized for large scale persistent surveillance systems (PSS), but also, it can be employed with proper interfaces to expedite rapid events reporting by human observers. The proposed technique is particularly suitable for large-scale persistent surveillance systems with distributed soft and hard sensor networks. The efficiency and effectiveness of the proposed technique is measured experimentally by conducting several simulated persistent surveillance scenarios. It is demonstrated that by fusion of information from hard and soft agents improves understanding of common operating picture and enhances situational awareness.

A Review of Current Neuromorphic Approaches for Vision, Auditory, and Olfactory Sensors

PubMed Central

Vanarse, Anup; Osseiran, Adam; Rassau, Alexander

2016-01-01

Conventional vision, auditory, and olfactory sensors generate large volumes of redundant data and as a result tend to consume excessive power. To address these shortcomings, neuromorphic sensors have been developed. These sensors mimic the neuro-biological architecture of sensory organs using aVLSI (analog Very Large Scale Integration) and generate asynchronous spiking output that represents sensing information in ways that are similar to neural signals. This allows for much lower power consumption due to an ability to extract useful sensory information from sparse captured data. The foundation for research in neuromorphic sensors was laid more than two decades ago, but recent developments in understanding of biological sensing and advanced electronics, have stimulated research on sophisticated neuromorphic sensors that provide numerous advantages over conventional sensors. In this paper, we review the current state-of-the-art in neuromorphic implementation of vision, auditory, and olfactory sensors and identify key contributions across these fields. Bringing together these key contributions we suggest a future research direction for further development of the neuromorphic sensing field. PMID:27065784

Obtaining high-resolution stage forecasts by coupling large-scale hydrologic models with sensor data

NASA Astrophysics Data System (ADS)

Fries, K. J.; Kerkez, B.

2017-12-01

We investigate how "big" quantities of distributed sensor data can be coupled with a large-scale hydrologic model, in particular the National Water Model (NWM), to obtain hyper-resolution forecasts. The recent launch of the NWM provides a great example of how growing computational capacity is enabling a new generation of massive hydrologic models. While the NWM spans an unprecedented spatial extent, there remain many questions about how to improve forecast at the street-level, the resolution at which many stakeholders make critical decisions. Further, the NWM runs on supercomputers, so water managers who may have access to their own high-resolution measurements may not readily be able to assimilate them into the model. To that end, we ask the question: how can the advances of the large-scale NWM be coupled with new local observations to enable hyper-resolution hydrologic forecasts? A methodology is proposed whereby the flow forecasts of the NWM are directly mapped to high-resolution stream levels using Dynamical System Identification. We apply the methodology across a sensor network of 182 gages in Iowa. Of these sites, approximately one third have shown to perform well in high-resolution flood forecasting when coupled with the outputs of the NWM. The quality of these forecasts is characterized using Principal Component Analysis and Random Forests to identify where the NWM may benefit from new sources of local observations. We also discuss how this approach can help municipalities identify where they should place low-cost sensors to most benefit from flood forecasts of the NWM.

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks.

PubMed

Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio

2008-11-24

Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

Demodulation algorithm for optical fiber F-P sensor.

PubMed

Yang, Huadong; Tong, Xinglin; Cui, Zhang; Deng, Chengwei; Guo, Qian; Hu, Pan

2017-09-10

The demodulation algorithm is very important to improving the measurement accuracy of a sensing system. In this paper, the variable step size hill climbing search method will be initially used for the optical fiber Fabry-Perot (F-P) sensing demodulation algorithm. Compared with the traditional discrete gap transformation demodulation algorithm, the computation is greatly reduced by changing step size of each climb, which could achieve nano-scale resolution, high measurement accuracy, high demodulation rates, and large dynamic demodulation range. An optical fiber F-P pressure sensor based on micro-electro-mechanical system (MEMS) has been fabricated to carry out the experiment, and the results show that the resolution of the algorithm can reach nano-scale level, the sensor's sensitivity is about 2.5  nm/KPa, which is similar to the theoretical value, and this sensor has great reproducibility.

NASA: Assessments of Selected Large-Scale Projects

DTIC Science & Technology

2011-03-01

REPORT DATE MAR 2011 2. REPORT TYPE 3. DATES COVERED 00-00-2011 to 00-00-2011 4. TITLE AND SUBTITLE Assessments Of Selected Large-Scale Projects...Volatile EvolutioN MEP Mars Exploration Program MIB Mishap Investigation Board MMRTG Multi Mission Radioisotope Thermoelectric Generator MMS Magnetospheric...probes designed to explore the Martian surface, to satellites equipped with advanced sensors to study the earth , to telescopes intended to explore the

Large Scale Density Estimation of Blue and Fin Whales (LSD)

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Large Scale Density Estimation of Blue and Fin Whales ...sensors, or both. The goal of this research is to develop and implement a new method for estimating blue and fin whale density that is effective over...develop and implement a density estimation methodology for quantifying blue and fin whale abundance from passive acoustic data recorded on sparse

Use of piezoelectric foil for flow diagnostics

NASA Technical Reports Server (NTRS)

Carraway, Debra L.; Bertelrud, Arild

1989-01-01

A laboratory investigation was conducted to characterize two piezoelectric-film sensor configurations, a rigidly mounted sensor and a sensor mounted over an air cavity. The sensors are evaluated for sensitivity and frequency response, and methods to optimize data are presented. The cavity-mounted sensor exhibited a superior frequency response and was more sensitive to normal pressure fluctuations and less sensitive to vibrations through the structure. Both configurations were sensitive to large-scale structural vibrations. Flight-test data are shown for cavity-mounted sensors, illustrating practical aspects to consider when designing sensors for application in such harsh environments. The relation of the data to skin friction and maximum shear stress, transition detection, and turbulent viscous layers is derived through analysis of the flight data.

A Low Collision and High Throughput Data Collection Mechanism for Large-Scale Super Dense Wireless Sensor Networks.

PubMed

Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Gaura, Elena; Brusey, James; Zhang, Xuekun; Dutkiewicz, Eryk

2016-07-18

Super dense wireless sensor networks (WSNs) have become popular with the development of Internet of Things (IoT), Machine-to-Machine (M2M) communications and Vehicular-to-Vehicular (V2V) networks. While highly-dense wireless networks provide efficient and sustainable solutions to collect precise environmental information, a new channel access scheme is needed to solve the channel collision problem caused by the large number of competing nodes accessing the channel simultaneously. In this paper, we propose a space-time random access method based on a directional data transmission strategy, by which collisions in the wireless channel are significantly decreased and channel utility efficiency is greatly enhanced. Simulation results show that our proposed method can decrease the packet loss rate to less than 2 % in large scale WSNs and in comparison with other channel access schemes for WSNs, the average network throughput can be doubled.

Comparison of fractal dimensions based on segmented NDVI fields obtained from different remote sensors.

NASA Astrophysics Data System (ADS)

Alonso, C.; Benito, R. M.; Tarquis, A. M.

2012-04-01

Satellite image data have become an important source of information for monitoring vegetation and mapping land cover at several scales. Beside this, the distribution and phenology of vegetation is largely associated with climate, terrain characteristics and human activity. Various vegetation indices have been developed for qualitative and quantitative assessment of vegetation using remote spectral measurements. In particular, sensors with spectral bands in the red (RED) and near-infrared (NIR) lend themselves well to vegetation monitoring and based on them [(NIR - RED) / (NIR + RED)] Normalized Difference Vegetation Index (NDVI) has been widespread used. Given that the characteristics of spectral bands in RED and NIR vary distinctly from sensor to sensor, NDVI values based on data from different instruments will not be directly comparable. The spatial resolution also varies significantly between sensors, as well as within a given scene in the case of wide-angle and oblique sensors. As a result, NDVI values will vary according to combinations of the heterogeneity and scale of terrestrial surfaces and pixel footprint sizes. Therefore, the question arises as to the impact of differences in spectral and spatial resolutions on vegetation indices like the NDVI. The aim of this study is to establish a comparison between two different sensors in their NDVI values at different spatial resolutions. Scaling analysis and modeling techniques are increasingly understood to be the result of nonlinear dynamic mechanisms repeating scale after scale from large to small scales leading to non-classical resolution dependencies. In the remote sensing framework the main characteristic of sensors images is the high local variability in their values. This variability is a consequence of the increase in spatial and radiometric resolution that implies an increase in complexity that it is necessary to characterize. Fractal and multifractal techniques has been proven to be useful to extract such complexities from remote sensing images and will applied in this study to see the scaling behavior for each sensor in generalized fractal dimensions. The studied area is located in the provinces of Caceres and Salamanca (east of Iberia Peninsula) with an extension of 32 x 32 km2. The altitude in the area varies from 1,560 to 320 m, comprising natural vegetation in the mountain area (forest and bushes) and agricultural crops in the valleys. Scaling analysis were applied to Landsat-5 and MODIS TERRA to the normalized derived vegetation index (NDVI) on the same region with one day of difference, 13 and 12 of July 2003 respectively. From these images the area of interest was selected obtaining 1024 x 1024 pixels for Landsat image and 128 x 128 pixels for MODIS image. This implies that the resolution for MODIS is 250x250 m. and for Landsat is 30x30 m. From the reflectance data obtained from NIR and RED bands, NDVI was calculated for each image focusing this study on 0.2 to 0.5 ranges of values. Once that both NDVI fields were obtained several fractal dimensions were estimated in each one segmenting the values in 0.20-0.25, 0.25-0.30 and so on to rich 0.45-0.50. In all the scaling analysis the scale size length was expressed in meters, and not in pixels, to make the comparison between both sensors possible. Results are discussed. Acknowledgements This work has been supported by the Spanish MEC under Projects No. AGL2010-21501/AGR, MTM2009-14621 and i-MATH No. CSD2006-00032

Nanoposition sensors with superior linear response to position and unlimited travel ranges

NASA Astrophysics Data System (ADS)

Lee, Sheng-Chiang; Peters, Randall D.

2009-04-01

With the advancement in nanotechnology, the ability of positioning/measuring at subnanometer scale has been one of the most critical issues for the nanofabrication industry and researchers using scanning probe microscopy. Commercial nanopositioners have achieved direct measurements at the scale of 0.01 nm with capacitive sensing metrology. However, the commercial sensors have small dynamic ranges (up to only a few hundred micrometers) and are relatively large in size (centimeters in the transverse directions to the motion), which is necessary for healthy signal detections but making it difficult to use on smaller devices. This limits applications in which large materials (on the scale of centimeters or greater) are handled with needs of subnanometer resolutions. What has been done in the past is to combine the fine and coarse translation stages with different dynamic ranges to simultaneously achieve long travel range and high spatial resolution. In this paper, we present a novel capacitive position sensing metrology with ultrawide dynamic range from subnanometer to literally any practically desired length for a translation stage. This sensor will greatly simplify the task and enhance the performance of direct metrology in a hybrid translational stage covering translation tasks from subnanometer to centimeters.

Sensing of minute airflow motions near walls using pappus-type nature-inspired sensors

PubMed Central

Mikulich, Vladimir

2017-01-01

This work describes the development and use of pappus-like structures as sensitive sensors to detect minute air-flow motions. We made such sensors from pappi taken from nature-grown seed, whose filiform hairs’ length-scale is suitable for the study of large-scale turbulent convection flows. The stem with the pappus on top is fixated on an elastic membrane on the wall and tilts under wind-load proportional to the velocity magnitude in direction of the wind, similar as the biological sensory hairs found in spiders, however herein the sensory hair has multiple filiform protrusions at the tip. As the sensor response is proportional to the drag on the tip and a low mass ensures a larger bandwidth, lightweight pappus structures similar as those found in nature with documented large drag are useful to improve the response of artificial sensors. The pappus of a Dandelion represents such a structure which has evolved to maximize wind-driven dispersion, therefore it is used herein as the head of our sensor. Because of its multiple hairs arranged radially around the stem it generates uniform drag for all wind directions. While still being permeable to the flow, the hundreds of individual hairs on the tip of the sensor head maximize the drag and minimize influence of pressure gradients or shear-induced lift forces on the sensor response as they occur in non-permeable protrusions. In addition, the flow disturbance by the sensor itself is limited. The optical recording of the head-motion allows continuously remote-distance monitoring of the flow fluctuations in direction and magnitude. Application is shown for the measurement of a reference flow under isothermal conditions to detect the early occurrence of instabilities. PMID:28658272

Formulation and Optimization of Robust Sensor Placement Problems for Drinking Water Contamination Warning Systems

DOE PAGES

Watson, Jean-Paul; Murray, Regan; Hart, William E.

2009-11-13

We report that the sensor placement problem in contamination warning system design for municipal water distribution networks involves maximizing the protection level afforded by limited numbers of sensors, typically quantified as the expected impact of a contamination event; the issue of how to mitigate against high-consequence events is either handled implicitly or ignored entirely. Consequently, expected-case sensor placements run the risk of failing to protect against high-consequence 9/11-style attacks. In contrast, robust sensor placements address this concern by focusing strictly on high-consequence events and placing sensors to minimize the impact of these events. We introduce several robust variations of themore » sensor placement problem, distinguished by how they quantify the potential damage due to high-consequence events. We explore the nature of robust versus expected-case sensor placements on three real-world large-scale distribution networks. We find that robust sensor placements can yield large reductions in the number and magnitude of high-consequence events, with only modest increases in expected impact. Finally, the ability to trade-off between robust and expected-case impacts is a key unexplored dimension in contamination warning system design.« less

ShakeMapple : tapping laptop motion sensors to map the felt extents of an earthquake

NASA Astrophysics Data System (ADS)

Bossu, Remy; McGilvary, Gary; Kamb, Linus

2010-05-01

There is a significant pool of untapped sensor resources available in portable computer embedded motion sensors. Included primarily to detect sudden strong motion in order to park the disk heads to prevent damage to the disks in the event of a fall or other severe motion, these sensors may also be tapped for other uses as well. We have developed a system that takes advantage of the Apple Macintosh laptops' embedded Sudden Motion Sensors to record earthquake strong motion data to rapidly build maps of where and to what extent an earthquake has been felt. After an earthquake, it is vital to understand the damage caused especially in urban environments as this is often the scene for large amounts of damage caused by earthquakes. Gathering as much information from these impacts to determine where the areas that are likely to be most effected, can aid in distributing emergency services effectively. The ShakeMapple system operates in the background, continuously saving the most recent data from the motion sensors. After an earthquake has occurred, the ShakeMapple system calculates the peak acceleration within a time window around the expected arrival and sends that to servers at the EMSC. A map plotting the felt responses is then generated and presented on the web. Because large-scale testing of such an application is inherently difficult, we propose to organize a broadly distributed "simulated event" test. The software will be available for download in April, after which we plan to organize a large-scale test by the summer. At a specified time, participating testers will be asked to create their own strong motion to be registered and submitted by the ShakeMapple client. From these responses, a felt map will be produced representing the broadly-felt effects of the simulated event.

Ionospheric Multi-Point Measurements Using Tethered Satellite Sensors

NASA Technical Reports Server (NTRS)

Gilchrist, B. E.; Heelis, R. A.; Raitt, W. J.

1998-01-01

Many scientific questions concerning the distribution of electromagnetic fields and plasma structures in the ionosphere require measurements over relatively small temporal and spatial scales with as little ambiguity as possible. It is also often necessary to differentiate several geophysical parameters between horizontal and vertical gradients unambiguously. The availability of multiple tethered satellites or sensors, so-called "pearls-on-a-string," may make the necessary measurements practical. In this report we provide two examples of scientific questions which could benefit from such measurements (1) high-latitude magnetospheric-ionospheric coupling; and, (2) plasma structure impact on large and small-scale electrodynamics. Space tether state-of-the-art and special technical considerations addressing mission lifetime, sensor pointing, and multi-stream telemetry are reviewed.

Remote maintenance monitoring system

NASA Technical Reports Server (NTRS)

Simpkins, Lorenz G. (Inventor); Owens, Richard C. (Inventor); Rochette, Donn A. (Inventor)

1992-01-01

A remote maintenance monitoring system retrofits to a given hardware device with a sensor implant which gathers and captures failure data from the hardware device, without interfering with its operation. Failure data is continuously obtained from predetermined critical points within the hardware device, and is analyzed with a diagnostic expert system, which isolates failure origin to a particular component within the hardware device. For example, monitoring of a computer-based device may include monitoring of parity error data therefrom, as well as monitoring power supply fluctuations therein, so that parity error and power supply anomaly data may be used to trace the failure origin to a particular plane or power supply within the computer-based device. A plurality of sensor implants may be rerofit to corresponding plural devices comprising a distributed large-scale system. Transparent interface of the sensors to the devices precludes operative interference with the distributed network. Retrofit capability of the sensors permits monitoring of even older devices having no built-in testing technology. Continuous real time monitoring of a distributed network of such devices, coupled with diagnostic expert system analysis thereof, permits capture and analysis of even intermittent failures, thereby facilitating maintenance of the monitored large-scale system.

Micro/Nanofibre Optical Sensors: Challenges and Prospects

PubMed Central

Tong, Limin

2018-01-01

Micro/nanofibres (MNFs) are optical fibres with diameters close to or below the vacuum wavelength of visible or near-infrared light. Due to its wavelength- or sub-wavelength scale diameter and relatively large index contrast between the core and cladding, an MNF can offer engineerable waveguiding properties including optical confinement, fractional evanescent fields and surface intensity, which is very attractive to optical sensing on the micro and nanometer scale. In particular, the waveguided low-loss tightly confined large fractional evanescent fields, enabled by atomic level surface roughness and extraordinary geometric and material uniformity in a glass MNF, is one of its most prominent merits in realizing optical sensing with high sensitivity and great versatility. Meanwhile, the mesoporous matrix and small diameter of a polymer MNF, make it an excellent host fibre for functional materials for fast-response optical sensing. In this tutorial, we first introduce the basics of MNF optics and MNF optical sensors, and review the progress and current status of this field. Then, we discuss challenges and prospects of MNF sensors to some extent, with several clues for future studies. Finally, we conclude with a brief outlook for MNF optical sensors.

A Tactile Sensor Network System Using a Multiple Sensor Platform with a Dedicated CMOS-LSI for Robot Applications †

PubMed Central

Shao, Chenzhong; Tanaka, Shuji; Nakayama, Takahiro; Hata, Yoshiyuki; Bartley, Travis; Muroyama, Masanori

2017-01-01

Robot tactile sensation can enhance human–robot communication in terms of safety, reliability and accuracy. The final goal of our project is to widely cover a robot body with a large number of tactile sensors, which has significant advantages such as accurate object recognition, high sensitivity and high redundancy. In this study, we developed a multi-sensor system with dedicated Complementary Metal-Oxide-Semiconductor (CMOS) Large-Scale Integration (LSI) circuit chips (referred to as “sensor platform LSI”) as a framework of a serial bus-based tactile sensor network system. The sensor platform LSI supports three types of sensors: an on-chip temperature sensor, off-chip capacitive and resistive tactile sensors, and communicates with a relay node via a bus line. The multi-sensor system was first constructed on a printed circuit board to evaluate basic functions of the sensor platform LSI, such as capacitance-to-digital and resistance-to-digital conversion. Then, two kinds of external sensors, nine sensors in total, were connected to two sensor platform LSIs, and temperature, capacitive and resistive sensing data were acquired simultaneously. Moreover, we fabricated flexible printed circuit cables to demonstrate the multi-sensor system with 15 sensor platform LSIs operating simultaneously, which showed a more realistic implementation in robots. In conclusion, the multi-sensor system with up to 15 sensor platform LSIs on a bus line supporting temperature, capacitive and resistive sensing was successfully demonstrated. PMID:29061954

A Tactile Sensor Network System Using a Multiple Sensor Platform with a Dedicated CMOS-LSI for Robot Applications.

PubMed

Shao, Chenzhong; Tanaka, Shuji; Nakayama, Takahiro; Hata, Yoshiyuki; Bartley, Travis; Nonomura, Yutaka; Muroyama, Masanori

2017-08-28

Robot tactile sensation can enhance human-robot communication in terms of safety, reliability and accuracy. The final goal of our project is to widely cover a robot body with a large number of tactile sensors, which has significant advantages such as accurate object recognition, high sensitivity and high redundancy. In this study, we developed a multi-sensor system with dedicated Complementary Metal-Oxide-Semiconductor (CMOS) Large-Scale Integration (LSI) circuit chips (referred to as "sensor platform LSI") as a framework of a serial bus-based tactile sensor network system. The sensor platform LSI supports three types of sensors: an on-chip temperature sensor, off-chip capacitive and resistive tactile sensors, and communicates with a relay node via a bus line. The multi-sensor system was first constructed on a printed circuit board to evaluate basic functions of the sensor platform LSI, such as capacitance-to-digital and resistance-to-digital conversion. Then, two kinds of external sensors, nine sensors in total, were connected to two sensor platform LSIs, and temperature, capacitive and resistive sensing data were acquired simultaneously. Moreover, we fabricated flexible printed circuit cables to demonstrate the multi-sensor system with 15 sensor platform LSIs operating simultaneously, which showed a more realistic implementation in robots. In conclusion, the multi-sensor system with up to 15 sensor platform LSIs on a bus line supporting temperature, capacitive and resistive sensing was successfully demonstrated.

An integrated probe design for measuring food quality in a microwave environment

NASA Astrophysics Data System (ADS)

O'Farrell, M.; Sheridan, C.; Lewis, E.; Zhao, W. Z.; Sun, T.; Grattan, K. T. V.

2007-07-01

The work presented describes the development of a novel integrated optical sensor system for the simultaneous and online measurement of the colour and temperature of food as it cooks in a large-scale microwave and hybrid oven systems. The integrated probe contains two different sensor concepts, one to monitor temperature and based on Fibre Bragg Grating (FBG) technology and a second for meat quality, based on reflection spectroscopy in the visible wavelength range. The combination of the two sensors into a single probe requires a careful configuration of the sensor approaches in the creation of an integrated probe design.

Fiber Optic Sensor Embedment Study for Multi-Parameter Strain Sensing

PubMed Central

Drissi-Habti, Monssef; Raman, Venkadesh; Khadour, Aghiad; Timorian, Safiullah

2017-01-01

The fiber optic sensors (FOSs) are commonly used for large-scale structure monitoring systems for their small size, noise free and low electrical risk characteristics. Embedded fiber optic sensors (FOSs) lead to micro-damage in composite structures. This damage generation threshold is based on the coating material of the FOSs and their diameter. In addition, embedded FOSs are aligned parallel to reinforcement fibers to avoid micro-damage creation. This linear positioning of distributed FOS fails to provide all strain parameters. We suggest novel sinusoidal sensor positioning to overcome this issue. This method tends to provide multi-parameter strains in a large surface area. The effectiveness of sinusoidal FOS positioning over linear FOS positioning is studied under both numerical and experimental methods. This study proves the advantages of the sinusoidal positioning method for FOS in composite material’s bonding. PMID:28333117

Large scale electromechanical transistor with application in mass sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Leisheng; Li, Lijie, E-mail: L.Li@swansea.ac.uk

Nanomechanical transistor (NMT) has evolved from the single electron transistor, a device that operates by shuttling electrons with a self-excited central conductor. The unfavoured aspects of the NMT are the complexity of the fabrication process and its signal processing unit, which could potentially be overcome by designing much larger devices. This paper reports a new design of large scale electromechanical transistor (LSEMT), still taking advantage of the principle of shuttling electrons. However, because of the large size, nonlinear electrostatic forces induced by the transistor itself are not sufficient to drive the mechanical member into vibration—an external force has to bemore » used. In this paper, a LSEMT device is modelled, and its new application in mass sensing is postulated using two coupled mechanical cantilevers, with one of them being embedded in the transistor. The sensor is capable of detecting added mass using the eigenstate shifts method by reading the change of electrical current from the transistor, which has much higher sensitivity than conventional eigenfrequency shift approach used in classical cantilever based mass sensors. Numerical simulations are conducted to investigate the performance of the mass sensor.« less

Towards the Development of THz-Sensors for the Detection of African Trypanosomes

NASA Astrophysics Data System (ADS)

Knieß, Robert; Wagner, Carolin B.; Ulrich Göringer, H.; Mueh, Mario; Damm, Christian; Sawallich, Simon; Chmielak, Bartos; Plachetka, Ulrich; Lemme, Max

2018-03-01

Human African trypanosomiasis (HAT) is a neglected tropical disease (NTD) for which adequate therapeutic and diagnostic measures are still lacking. Causative agent of HAT is the African trypanosome, a single-cell parasite, which propagates in the blood and cerebrospinal fluid of infected patients. Although different testing methods for the pathogen exist, none is robust, reliable and cost-efficient enough to support large-scale screening and control programs. Here we propose the design of a new sensor-type for the detection of infective-stage trypanosomes. The sensor exploits the highly selective binding capacity of nucleic acid aptamers to the surface of the parasite in combination with passive sensor structures to allow an electromagnetic remote read-out using terahertz (THz)-radiation. The short wavelength provides a superior interaction with the parasite cells than longer wavelengths, which is essential for a high sensitivity. We present two different sensor structures using both, micro- and nano-scale elements, as well as different measurement principles.

Structural Health Monitoring on Turbine Engines Using Microwave Blade Tip Clearance Sensors

NASA Technical Reports Server (NTRS)

Woike, Mark; Abdul-Aziz, Ali; Clem, Michelle

2014-01-01

The ability to monitor the structural health of the rotating components, especially in the hot sections of turbine engines, is of major interest to aero community in improving engine safety and reliability. The use of instrumentation for these applications remains very challenging. It requires sensors and techniques that are highly accurate, are able to operate in a high temperature environment, and can detect minute changes and hidden flaws before catastrophic events occur. The National Aeronautics and Space Administration (NASA) has taken a lead role in the investigation of new sensor technologies and techniques for the in situ structural health monitoring of gas turbine engines. As part of this effort, microwave sensor technology has been investigated as a means of making high temperature non-contact blade tip clearance, blade tip timing, and blade vibration measurements for use in gas turbine engines. This paper presents a summary of key results and findings obtained from the evaluation of two different types of microwave sensors that have been investigated for use possible in structural health monitoring applications. The first is a microwave blade tip clearance sensor that has been evaluated on a large scale Axial Vane Fan, a subscale Turbofan, and more recently on sub-scale turbine engine like disks. The second is a novel microwave based blade vibration sensor that was also used in parallel with the microwave blade tip clearance sensors on the experiments with the sub-scale turbine engine disks.

Structural health monitoring on turbine engines using microwave blade tip clearance sensors

NASA Astrophysics Data System (ADS)

Woike, Mark; Abdul-Aziz, Ali; Clem, Michelle

2014-04-01

The ability to monitor the structural health of the rotating components, especially in the hot sections of turbine engines, is of major interest to the aero community in improving engine safety and reliability. The use of instrumentation for these applications remains very challenging. It requires sensors and techniques that are highly accurate, are able to operate in a high temperature environment, and can detect minute changes and hidden flaws before catastrophic events occur. The National Aeronautics and Space Administration (NASA) has taken a lead role in the investigation of new sensor technologies and techniques for the in situ structural health monitoring of gas turbine engines. As part of this effort, microwave sensor technology has been investigated as a means of making high temperature non-contact blade tip clearance, blade tip timing, and blade vibration measurements for use in gas turbine engines. This paper presents a summary of key results and findings obtained from the evaluation of two different types of microwave sensors that have been investigated for possible use in structural health monitoring applications. The first is a microwave blade tip clearance sensor that has been evaluated on a large scale Axial Vane Fan, a subscale Turbofan, and more recently on sub-scale turbine engine like disks. The second is a novel microwave based blade vibration sensor that was also used in parallel with the microwave blade tip clearance sensors on the same experiments with the sub-scale turbine engine disks.

InfoSymbiotics/DDDAS - The power of Dynamic Data Driven Applications Systems for New Capabilities in Environmental -, Geo-, and Space- Sciences

NASA Astrophysics Data System (ADS)

Darema, F.

2016-12-01

InfoSymbiotics/DDDAS embodies the power of Dynamic Data Driven Applications Systems (DDDAS), a concept whereby an executing application model is dynamically integrated, in a feed-back loop, with the real-time data-acquisition and control components, as well as other data sources of the application system. Advanced capabilities can be created through such new computational approaches in modeling and simulations, and in instrumentation methods, and include: enhancing the accuracy of the application model; speeding-up the computation to allow faster and more comprehensive models of a system, and create decision support systems with the accuracy of full-scale simulations; in addition, the notion of controlling instrumentation processes by the executing application results in more efficient management of application-data and addresses challenges of how to architect and dynamically manage large sets of heterogeneous sensors and controllers, an advance over the static and ad-hoc ways of today - with DDDAS these sets of resources can be managed adaptively and in optimized ways. Large-Scale-Dynamic-Data encompasses the next wave of Big Data, and namely dynamic data arising from ubiquitous sensing and control in engineered, natural, and societal systems, through multitudes of heterogeneous sensors and controllers instrumenting these systems, and where opportunities and challenges at these "large-scales" relate not only to data size but the heterogeneity in data, data collection modalities, fidelities, and timescales, ranging from real-time data to archival data. In tandem with this important dimension of dynamic data, there is an extended view of Big Computing, which includes the collective computing by networked assemblies of multitudes of sensors and controllers, this range from the high-end to the real-time seamlessly integrated and unified, and comprising the Large-Scale-Big-Computing. InfoSymbiotics/DDDAS engenders transformative impact in many application domains, ranging from the nano-scale to the terra-scale and to the extra-terra-scale. The talk will address opportunities for new capabilities together with corresponding research challenges, with illustrative examples from several application areas including environmental sciences, geosciences, and space sciences.

Detecting the Influence of Spreading in Social Networks with Excitable Sensor Networks

PubMed Central

Pei, Sen; Tang, Shaoting; Zheng, Zhiming

2015-01-01

Detecting spreading outbreaks in social networks with sensors is of great significance in applications. Inspired by the formation mechanism of humans’ physical sensations to external stimuli, we propose a new method to detect the influence of spreading by constructing excitable sensor networks. Exploiting the amplifying effect of excitable sensor networks, our method can better detect small-scale spreading processes. At the same time, it can also distinguish large-scale diffusion instances due to the self-inhibition effect of excitable elements. Through simulations of diverse spreading dynamics on typical real-world social networks (Facebook, coauthor, and email social networks), we find that the excitable sensor networks are capable of detecting and ranking spreading processes in a much wider range of influence than other commonly used sensor placement methods, such as random, targeted, acquaintance and distance strategies. In addition, we validate the efficacy of our method with diffusion data from a real-world online social system, Twitter. We find that our method can detect more spreading topics in practice. Our approach provides a new direction in spreading detection and should be useful for designing effective detection methods. PMID:25950181

GeoCENS: a geospatial cyberinfrastructure for the world-wide sensor web.

PubMed

Liang, Steve H L; Huang, Chih-Yuan

2013-10-02

The world-wide sensor web has become a very useful technique for monitoring the physical world at spatial and temporal scales that were previously impossible. Yet we believe that the full potential of sensor web has thus far not been revealed. In order to harvest the world-wide sensor web's full potential, a geospatial cyberinfrastructure is needed to store, process, and deliver large amount of sensor data collected worldwide. In this paper, we first define the issue of the sensor web long tail followed by our view of the world-wide sensor web architecture. Then, we introduce the Geospatial Cyberinfrastructure for Environmental Sensing (GeoCENS) architecture and explain each of its components. Finally, with demonstration of three real-world powered-by-GeoCENS sensor web applications, we believe that the GeoCENS architecture can successfully address the sensor web long tail issue and consequently realize the world-wide sensor web vision.

GeoCENS: A Geospatial Cyberinfrastructure for the World-Wide Sensor Web

PubMed Central

Liang, Steve H.L.; Huang, Chih-Yuan

2013-01-01

The world-wide sensor web has become a very useful technique for monitoring the physical world at spatial and temporal scales that were previously impossible. Yet we believe that the full potential of sensor web has thus far not been revealed. In order to harvest the world-wide sensor web's full potential, a geospatial cyberinfrastructure is needed to store, process, and deliver large amount of sensor data collected worldwide. In this paper, we first define the issue of the sensor web long tail followed by our view of the world-wide sensor web architecture. Then, we introduce the Geospatial Cyberinfrastructure for Environmental Sensing (GeoCENS) architecture and explain each of its components. Finally, with demonstration of three real-world powered-by-GeoCENS sensor web applications, we believe that the GeoCENS architecture can successfully address the sensor web long tail issue and consequently realize the world-wide sensor web vision. PMID:24152921

Preliminary Assessment of Microwave Readout Multiplexing Factor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Croce, Mark Philip; Koehler, Katrina Elizabeth; Rabin, Michael W.

2017-01-23

Ultra-high resolution microcalorimeter gamma spectroscopy is a new non-destructive assay technology for measurement of plutonium isotopic composition, with the potential to reduce total measurement uncertainty to a level competitive with destructive analysis methods [1-4]. Achieving this level of performance in practical applications requires not only the energy resolution now routinely achieved with transition-edge sensor microcalorimeter arrays (an order of magnitude better than for germanium detectors) but also high throughput. Microcalorimeter gamma spectrometers have not yet achieved detection efficiency and count rate capability that is comparable to germanium detectors, largely because of limits from existing readout technology. Microcalorimeter detectors must bemore » operated at low temperature to achieve their exceptional energy resolution. Although the typical 100 mK operating temperatures can be achieved with reliable, cryogen-free systems, the cryogenic complexity and heat load from individual readout channels for large sensor arrays is prohibitive. Multiplexing is required for practical systems. The most mature multiplexing technology at present is time-division multiplexing (TDM) [3, 5-6]. In TDM, the sensor outputs are switched by applying bias current to one SQUID amplifier at a time. Transition-edge sensor (TES) microcalorimeter arrays as large as 256 pixels have been developed for X-ray and gamma-ray spectroscopy using TDM technology. Due to bandwidth limits and noise scaling, TDM is limited to a maximum multiplexing factor of approximately 32-40 sensors on one readout line [8]. Increasing the size of microcalorimeter arrays above the kilopixel scale, required to match the throughput of germanium detectors, requires the development of a new readout technology with a much higher multiplexing factor.« less

Deployment Design of Wireless Sensor Network for Simple Multi-Point Surveillance of a Moving Target

PubMed Central

Tsukamoto, Kazuya; Ueda, Hirofumi; Tamura, Hitomi; Kawahara, Kenji; Oie, Yuji

2009-01-01

In this paper, we focus on the problem of tracking a moving target in a wireless sensor network (WSN), in which the capability of each sensor is relatively limited, to construct large-scale WSNs at a reasonable cost. We first propose two simple multi-point surveillance schemes for a moving target in a WSN and demonstrate that one of the schemes can achieve high tracking probability with low power consumption. In addition, we examine the relationship between tracking probability and sensor density through simulations, and then derive an approximate expression representing the relationship. As the results, we present guidelines for sensor density, tracking probability, and the number of monitoring sensors that satisfy a variety of application demands. PMID:22412326

Aquatic Nitrate Retention at River Network Scales Across Flow Conditions Determined Using Nested In Situ Sensors

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Mulukutla, G. K.; Cook, C.; Carey, R. O.

2017-11-01

Nonpoint pollution sources are strongly influenced by hydrology and are therefore sensitive to climate variability. Some pollutants entering aquatic ecosystems, e.g., nitrate, can be mitigated by in-stream processes during transport through river networks. Whole river network nitrate retention is difficult to quantify with observations. High frequency, in situ nitrate sensors, deployed in nested locations within a single watershed, can improve estimates of both nonpoint inputs and aquatic retention at river network scales. We deployed a nested sensor network and associated sampling in the urbanizing Oyster River watershed in coastal New Hampshire, USA, to quantify storm event-scale loading and retention at network scales. An end member analysis used the relative behavior of reactive nitrate and conservative chloride to infer river network fate of nitrate. In the headwater catchments, nitrate and chloride concentrations are both increasingly diluted with increasing storm size. At the mouth of the watershed, chloride is also diluted, but nitrate tended to increase. The end member analysis suggests that this pattern is the result of high retention during small storms (51-78%) that declines to zero during large storms. Although high frequency nitrate sensors did not alter estimates of fluxes over seasonal time periods compared to less frequent grab sampling, they provide the ability to estimate nitrate flux versus storm size at event scales that is critical for such analyses. Nested sensor networks can improve understanding of the controls of both loading and network scale retention, and therefore also improve management of nonpoint source pollution.

Wearable sensor-based objective assessment of motor symptoms in Parkinson's disease.

PubMed

Ossig, Christiana; Antonini, Angelo; Buhmann, Carsten; Classen, Joseph; Csoti, Ilona; Falkenburger, Björn; Schwarz, Michael; Winkler, Jürgen; Storch, Alexander

2016-01-01

Effective management and development of new treatment strategies of motor symptoms in Parkinson's disease (PD) largely depend on clinical rating instruments like the Unified PD rating scale (UPDRS) and the modified abnormal involuntary movement scale (mAIMS). Regarding inter-rater variability and continuous monitoring, clinical rating scales have various limitations. Patient-administered questionnaires such as the PD home diary to assess motor stages and fluctuations in late-stage PD are frequently used in clinical routine and as clinical trial endpoints, but diary/questionnaire are tiring, and recall bias impacts on data quality, particularly in patients with cognitive dysfunction or depression. Consequently, there is a strong need for continuous and objective monitoring of motor symptoms in PD for improving therapeutic regimen and for usage in clinical trials. Recent advances in battery technology, movement sensors such as gyroscopes, accelerometers and information technology boosted the field of objective measurement of movement in everyday life and medicine using wearable sensors allowing continuous (long-term) monitoring. This systematic review summarizes the current wearable sensor-based devices to objectively assess the various motor symptoms of PD.

Technical instrumentation R&D for ILD SiW ECAL large scale device

NASA Astrophysics Data System (ADS)

Balagura, V.

2018-03-01

Calorimeters with silicon detectors have many unique features and are proposed for several world-leading experiments. We describe the R&D program of the large scale detector element with up to 12 000 readout channels for the International Large Detector (ILD) at the future e+e‑ ILC collider. The program is focused on the readout front-end electronics embedded inside the calorimeter. The first part with 2 000 channels and two small silicon sensors has already been constructed, the full prototype is planned for the beginning of 2018.

A model for ionic polymer metal composites as sensors

NASA Astrophysics Data System (ADS)

Bonomo, C.; Fortuna, L.; Giannone, P.; Graziani, S.; Strazzeri, S.

2006-06-01

This paper introduces a comprehensive model of sensors based on ionic polymer metal composites (IPMCs) working in air. Significant quantities ruling the sensing properties of IPMC-based sensors are taken into account and the dynamics of the sensors are modelled. A large amount of experimental evidence is given for the excellent agreement between estimations obtained using the proposed model and the observed signals. Furthermore, the effect of sensor scaling is investigated, giving interesting support to the activities involved in the design of sensing devices based on these novel materials. We observed that the need for a wet environment is not a key issue for IPMC-based sensors to work well. This fact allows us to put IPMC-based sensors in a totally different light to the corresponding actuators, showing that sensors do not suffer from the same drawbacks.

Surface acoustic impediography: a new technology for fingerprint mapping and biometric identification: a numerical study

NASA Astrophysics Data System (ADS)

Schmitt, Rainer M.; Scott, W. Guy; Irving, Richard D.; Arnold, Joe; Bardons, Charles; Halpert, Daniel; Parker, Lawrence

2004-09-01

A new type of fingerprint sensor is presented. The sensor maps the acoustic impedance of the fingerprint pattern by estimating the electrical impedance of its sensor elements. The sensor substrate, made of 1-3 piezo-ceramic, which is fabricated inexpensively at large scales, can provide a resolution up to 50 μm over an area of 20 x 25 mm2. Using FE modeling the paper presents the numerical validation of the basic principle. It evaluates an optimized pillar aspect ratio, estimates spatial resolution and the point spread function for a 100 μm and 50 μm pitch model. In addition, first fingerprints obtained with the prototype sensor are presented.

Development and Ground-Test Validation of Fiber Optic Sensor Attachment Techniques for Hot Structures Applications

NASA Technical Reports Server (NTRS)

Piazza, Anthony; Hudson, Larry D.; Richards, W. Lance

2005-01-01

Fiber Optic Strain Measurements: a) Successfully attached silica fiber optic sensors to both metallics and composites; b) Accomplished valid EFPI strain measurements to 1850 F; c) Successfully attached EFPI sensors to large scale hot-structures; and d) Attached and thermally validated FBG bond and epsilon(sub app). Future Development a) Improve characterization of sensors on C-C and C-SiC substrates; b) Apply application to other composites such as SiC-SiC; c) Assist development of interferometer based Sapphire sensor currently being conducted under a Phase II SBIR; and d) Complete combined thermal/mechanical testing of FBG on composite substrates in controlled laboratory environment.

Moon-based Earth Observation for Large Scale Geoscience Phenomena

NASA Astrophysics Data System (ADS)

Guo, Huadong; Liu, Guang; Ding, Yixing

2016-07-01

The capability of Earth observation for large-global-scale natural phenomena needs to be improved and new observing platform are expected. We have studied the concept of Moon as an Earth observation in these years. Comparing with manmade satellite platform, Moon-based Earth observation can obtain multi-spherical, full-band, active and passive information,which is of following advantages: large observation range, variable view angle, long-term continuous observation, extra-long life cycle, with the characteristics of longevity ,consistency, integrity, stability and uniqueness. Moon-based Earth observation is suitable for monitoring the large scale geoscience phenomena including large scale atmosphere change, large scale ocean change,large scale land surface dynamic change,solid earth dynamic change,etc. For the purpose of establishing a Moon-based Earth observation platform, we already have a plan to study the five aspects as follows: mechanism and models of moon-based observing earth sciences macroscopic phenomena; sensors' parameters optimization and methods of moon-based Earth observation; site selection and environment of moon-based Earth observation; Moon-based Earth observation platform; and Moon-based Earth observation fundamental scientific framework.

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks

PubMed Central

Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio

2008-01-01

Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper. PMID:27873941

Structure of high and low shear-stress events in a turbulent boundary layer

NASA Astrophysics Data System (ADS)

Gomit, G.; de Kat, R.; Ganapathisubramani, B.

2018-01-01

Simultaneous particle image velocimetry (PIV) and wall-shear-stress sensor measurements were performed to study structures associated with shear-stress events in a flat plate turbulent boundary layer at a Reynolds number Reτ≈4000 . The PIV field of view covers 8 δ (where δ is the boundary layer thickness) along the streamwise direction and captures the entire boundary layer in the wall-normal direction. Simultaneously, wall-shear-stress measurements that capture the large-scale fluctuations were taken using a spanwise array of hot-film skin-friction sensors (spanning 2 δ ). Based on this combination of measurements, the organization of the conditional wall-normal and streamwise velocity fluctuations (u and v ) and of the Reynolds shear stress (-u v ) can be extracted. Conditional averages of the velocity field are computed by dividing the histogram of the large-scale wall-shear-stress fluctuations into four quartiles, each containing 25% of the occurrences. The conditional events corresponding to the extreme quartiles of the histogram (positive and negative) predominantly contribute to a change of velocity profile associated with the large structures and in the modulation of the small scales. A detailed examination of the Reynolds shear-stress contribution related to each of the four quartiles shows that the flow above a low wall-shear-stress event carries a larger amount of Reynolds shear stress than the other quartiles. The contribution of the small and large scales to this observation is discussed based on a scale decomposition of the velocity field.

A Novel Method for Proximity Detection of Moving Targets Using a Large-Scale Planar Capacitive Sensor System

PubMed Central

Ye, Yong; Deng, Jiahao; Shen, Sanmin; Hou, Zhuo; Liu, Yuting

2016-01-01

A novel method for proximity detection of moving targets (with high dielectric constants) using a large-scale (the size of each sensor is 31 cm × 19 cm) planar capacitive sensor system (PCSS) is proposed. The capacitive variation with distance is derived, and a pair of electrodes in a planar capacitive sensor unit (PCSU) with a spiral shape is found to have better performance on sensitivity distribution homogeneity and dynamic range than three other shapes (comb shape, rectangular shape, and circular shape). A driving excitation circuit with a Clapp oscillator is proposed, and a capacitance measuring circuit with sensitivity of 0.21 Vp−p/pF is designed. The results of static experiments and dynamic experiments demonstrate that the voltage curves of static experiments are similar to those of dynamic experiments; therefore, the static data can be used to simulate the dynamic curves. The dynamic range of proximity detection for three projectiles is up to 60 cm, and the results of the following static experiments show that the PCSU with four neighboring units has the highest sensitivity (the sensitivities of other units are at least 4% lower); when the attack angle decreases, the intensity of sensor signal increases. This proposed method leads to the design of a feasible moving target detector with simple structure and low cost, which can be applied in the interception system. PMID:27196905

Implementation of Fiber Optic Sensing System on Sandwich Composite Cylinder Buckling Test

NASA Technical Reports Server (NTRS)

Pena, Francisco; Richards, W. Lance; Parker, Allen R.; Piazza, Anthony; Schultz, Marc R.; Rudd, Michelle T.; Gardner, Nathaniel W.; Hilburger, Mark W.

2018-01-01

The National Aeronautics and Space Administration (NASA) Engineering and Safety Center Shell Buckling Knockdown Factor Project is a multicenter project tasked with developing new analysis-based shell buckling design guidelines and design factors (i.e., knockdown factors) through high-fidelity buckling simulations and advanced test technologies. To validate these new buckling knockdown factors for future launch vehicles, the Shell Buckling Knockdown Factor Project is carrying out structural testing on a series of large-scale metallic and composite cylindrical shells at the NASA Marshall Space Flight Center (Marshall Space Flight Center, Alabama). A fiber optic sensor system was used to measure strain on a large-scale sandwich composite cylinder that was tested under multiple axial compressive loads up to more than 850,000 lb, and equivalent bending loads over 22 million in-lb. During the structural testing of the composite cylinder, strain data were collected from optical cables containing distributed fiber Bragg gratings using a custom fiber optic sensor system interrogator developed at the NASA Armstrong Flight Research Center. A total of 16 fiber-optic strands, each containing nearly 1,000 fiber Bragg gratings, measuring strain, were installed on the inner and outer cylinder surfaces to monitor the test article global structural response through high-density real-time and post test strain measurements. The distributed sensing system provided evidence of local epoxy failure at the attachment-ring-to-barrel interface that would not have been detected with conventional instrumentation. Results from the fiber optic sensor system were used to further refine and validate structural models for buckling of the large-scale composite structures. This paper discusses the techniques employed for real-time structural monitoring of the composite cylinder for structural load introduction and distributed bending-strain measurements over a large section of the cylinder by utilizing unique sensing capabilities of fiber optic sensors.

Acoustic Emission Measurement with Fiber Bragg Gratings for Structure Health Monitoring

NASA Technical Reports Server (NTRS)

Banks, Curtis E.; Walker, James L.; Russell, Sam; Roth, Don; Mabry, Nehemiah; Wilson, Melissa

2010-01-01

Structural Health monitoring (SHM) is a way of detecting and assessing damage to large scale structures. Sensors used in SHM for aerospace structures provide real time data on new and propagating damage. One type of sensor that is typically used is an acoustic emission (AE) sensor that detects the acoustic emissions given off from a material cracking or breaking. The use of fiber Bragg grating (FBG) sensors to provide acoustic emission data for damage detection is studied. In this research, FBG sensors are used to detect acoustic emissions of a material during a tensile test. FBG sensors were placed as a strain sensor (oriented parallel to applied force) and as an AE sensor (oriented perpendicular to applied force). A traditional AE transducer was used to collect AE data to compare with the FBG data. Preliminary results show that AE with FBGs can be a viable alternative to traditional AE sensors.

Challenges and the state of the technology for printed sensor arrays for structural monitoring

NASA Astrophysics Data System (ADS)

Joshi, Shiv; Bland, Scott; DeMott, Robert; Anderson, Nickolas; Jursich, Gregory

2017-04-01

Printed sensor arrays are attractive for reliable, low-cost, and large-area mapping of structural systems. These sensor arrays can be printed on flexible substrates or directly on monitored structural parts. This technology is sought for continuous or on-demand real-time diagnosis and prognosis of complex structural components. In the past decade, many innovative technologies and functional materials have been explored to develop printed electronics and sensors. For example, an all-printed strain sensor array is a recent example of a low-cost, flexible and light-weight system that provides a reliable method for monitoring the state of aircraft structural parts. Among all-printing techniques, screen and inkjet printing methods are well suited for smaller-scale prototyping and have drawn much interest due to maturity of printing procedures and availability of compatible inks and substrates. Screen printing relies on a mask (screen) to transfer a pattern onto a substrate. Screen printing is widely used because of the high printing speed, large selection of ink/substrate materials, and capability of making complex multilayer devices. The complexity of collecting signals from a large number of sensors over a large area necessitates signal multiplexing electronics that need to be printed on flexible substrate or structure. As a result, these components are subjected to same deformation, temperature and other parameters for which sensor arrays are designed. The characteristics of these electronic components, such as transistors, are affected by deformation and other environmental parameters which can lead to erroneous sensed parameters. The manufacturing and functional challenges of the technology of printed sensor array systems for structural state monitoring are the focus of this presentation. Specific examples of strain sensor arrays will be presented to highlight the technical challenges.

Optimized ratiometric calcium sensors for functional in vivo imaging of neurons and T lymphocytes.

PubMed

Thestrup, Thomas; Litzlbauer, Julia; Bartholomäus, Ingo; Mues, Marsilius; Russo, Luigi; Dana, Hod; Kovalchuk, Yuri; Liang, Yajie; Kalamakis, Georgios; Laukat, Yvonne; Becker, Stefan; Witte, Gregor; Geiger, Anselm; Allen, Taylor; Rome, Lawrence C; Chen, Tsai-Wen; Kim, Douglas S; Garaschuk, Olga; Griesinger, Christian; Griesbeck, Oliver

2014-02-01

The quality of genetically encoded calcium indicators (GECIs) has improved dramatically in recent years, but high-performing ratiometric indicators are still rare. Here we describe a series of fluorescence resonance energy transfer (FRET)-based calcium biosensors with a reduced number of calcium binding sites per sensor. These 'Twitch' sensors are based on the C-terminal domain of Opsanus troponin C. Their FRET responses were optimized by a large-scale functional screen in bacterial colonies, refined by a secondary screen in rat hippocampal neuron cultures. We tested the in vivo performance of the most sensitive variants in the brain and lymph nodes of mice. The sensitivity of the Twitch sensors matched that of synthetic calcium dyes and allowed visualization of tonic action potential firing in neurons and high resolution functional tracking of T lymphocytes. Given their ratiometric readout, their brightness, large dynamic range and linear response properties, Twitch sensors represent versatile tools for neuroscience and immunology.

Laser-absorption sensing of gas composition of products from coal gasification

NASA Astrophysics Data System (ADS)

Jeffries, Jay B.; Sur, Ritobrata; Sun, Kai; Hanson, Ronald K.

2014-06-01

A prototype in-situ laser-absorption sensor for the real-time composition measurement (CO, CH4, H2O and CO2) of synthesis gas products of coal gasification (called here syngas) was designed, tested in the laboratory, and demonstrated during field-measurement campaigns in a pilot-scale entrained flow gasifier at the University of Utah and in an engineering-scale, fluidized-bed transport gasifier at the National Carbon Capture Center (NCCC). The prototype design and operation were improved by the lessons learned from each field test. Laser-absorption measurements are problematic in syngas flows because efficient gasifiers operate at elevated pressures (10-50 atm) where absorption transitions are collision broadened and absorption transitions that are isolated at 1 atm become blended into complex features, and because syngas product streams can contain significant particulate, producing significant non-absorption scattering losses of the transmission of laser light. Thus, the prototype sensor used a new wavelength-scanned, wavelength-modulation spectroscopy strategy with 2f-detection and 1f-normalization (WMS-2f/1f) that can provide sensitive absorption measurements of species with spectra blended by collision broadening even in the presence of large non-absorption laser transmission losses (e.g., particulate scattering, beam steering, etc.). The design of the sensor for detection of CO, CH4, H2O and CO2 was optimized for the specific application of syngas monitoring at the output of large-scale gasifiers. Sensor strategies, results and lessons learned from these field measurement campaigns are discussed.

A spatial length scale analysis of turbulent temperature and velocity fluctuations within and above an orchard canopy

USGS Publications Warehouse

Wang, Y.S.; Miller, D.R.; Anderson, D.E.; Cionco, R.M.; Lin, J.D.

1992-01-01

Turbulent flow within and above an almond orchard was measured with three-dimensional wind sensors and fine-wire thermocouple sensors arranged in a horizontal array. The data showed organized turbulent structures as indicated by coherent asymmetric ramp patterns in the time series traces across the sensor array. Space-time correlation analysis indicated that velocity and temperature fluctuations were significantly correlated over a transverse distance more than 4m. Integral length scales of velocity and temperature fluctuations were substantially greater in unstable conditions than those in stable conditions. The coherence spectral analysis indicated that Davenport's geometric similarity hypothesis was satisfied in the lower frequency region. From the geometric similarity hypothesis, the spatial extents of large ramp structures were also estimated with the coherence functions.

Field test of optical and electrical fire detectors in simulated fire scenes in a cable tunnel

NASA Astrophysics Data System (ADS)

Fan, Dian; Ding, Hongjun; Wang, Dorothy Y.; Jiang, Desheng

2014-06-01

This paper presents the testing results of three types of fire detectors: electrical heat sensing cable, optical fiber Raman temperature sensing detector, and optical fiber Bragg grating (FBG) temperature sensing detector, in two simulated fire scenes in a cable tunnel. In the small-scale fire with limited thermal radiation and no flame, the fire alarm only comes from the heat sensors which directly contact with the heat source. In the large-scale fire with about 5 °C/min temperature rising speed within a 3-m span, the fire alarm response time of the fiber Raman sensor and FBG sensors was about 30 seconds. The test results can be further used for formulating regulation for early fire detection in cable tunnels.

Energy harvesting: small scale energy production from ambient sources

NASA Astrophysics Data System (ADS)

Yeatman, Eric M.

2009-03-01

Energy harvesting - the collection of otherwise unexploited energy in the local environment - is attracting increasing attention for the powering of electronic devices. While the power levels that can be reached are typically modest (microwatts to milliwatts), the key motivation is to avoid the need for battery replacement or recharging in portable or inaccessible devices. Wireless sensor networks are a particularly important application: the availability of essentially maintenance free sensor nodes, as enabled by energy harvesting, will greatly increase the feasibility of large scale networks, in the paradigm often known as pervasive sensing. Such pervasive sensing networks, used to monitor buildings, structures, outdoor environments or the human body, offer significant benefits for large scale energy efficiency, health and safety, and many other areas. Sources of energy for harvesting include light, temperature differences, and ambient motion, and a wide range of miniature energy harvesters based on these sources have been proposed or demonstrated. This paper reviews the principles and practice in miniature energy harvesters, and discusses trends, suitable applications, and possible future developments.

Real-time Bayesian anomaly detection in streaming environmental data

NASA Astrophysics Data System (ADS)

Hill, David J.; Minsker, Barbara S.; Amir, Eyal

2009-04-01

With large volumes of data arriving in near real time from environmental sensors, there is a need for automated detection of anomalous data caused by sensor or transmission errors or by infrequent system behaviors. This study develops and evaluates three automated anomaly detection methods using dynamic Bayesian networks (DBNs), which perform fast, incremental evaluation of data as they become available, scale to large quantities of data, and require no a priori information regarding process variables or types of anomalies that may be encountered. This study investigates these methods' abilities to identify anomalies in eight meteorological data streams from Corpus Christi, Texas. The results indicate that DBN-based detectors, using either robust Kalman filtering or Rao-Blackwellized particle filtering, outperform a DBN-based detector using Kalman filtering, with the former having false positive/negative rates of less than 2%. These methods were successful at identifying data anomalies caused by two real events: a sensor failure and a large storm.

New technology of underground structures the framework of restrained urban conditions

NASA Astrophysics Data System (ADS)

Pleshko, Mikhail; Pankratenko, Alexander; Revyakin, Alexey; Shchekina, Ekaterina; Kholodova, Svetlana

2018-03-01

In the paper was indicated the essentiality of large-scale underground space development and high-rise construction of cities in Russia. The basic elements of transport facilities construction effective technology without traffic restriction are developed. Unlike the well-known solutions, it offers the inclusion of an advanced lining in the construction that strengthens the soil mass. The fundamental principles of methods for determining stress in advanced support and monitoring of underground construction, providing the application of pressure sensors, strain sensors and displacement sensors are considered.

Atmospheric transformation of multispectral remote sensor data. [Great Lakes

NASA Technical Reports Server (NTRS)

Turner, R. E. (Principal Investigator)

1977-01-01

The author has identified the following significant results. The effects of earth's atmosphere were accounted for, and a simple algorithm, based upon a radiative transfer model, was developed to determine the radiance at earth's surface free of atmospheric effects. Acutal multispectral remote sensor data for Lake Erie and associated optical thickness data were used to demonstrate the effectiveness of the atmospheric transformation algorithm. The basic transformation was general in nature and could be applied to the large scale processing of multispectral aircraft or satellite remote sensor data.

High performance architecture design for large scale fibre-optic sensor arrays using distributed EDFAs and hybrid TDM/DWDM

NASA Astrophysics Data System (ADS)

Liao, Yi; Austin, Ed; Nash, Philip J.; Kingsley, Stuart A.; Richardson, David J.

2013-09-01

A distributed amplified dense wavelength division multiplexing (DWDM) array architecture is presented for interferometric fibre-optic sensor array systems. This architecture employs a distributed erbium-doped fibre amplifier (EDFA) scheme to decrease the array insertion loss, and employs time division multiplexing (TDM) at each wavelength to increase the number of sensors that can be supported. The first experimental demonstration of this system is reported including results which show the potential for multiplexing and interrogating up to 4096 sensors using a single telemetry fibre pair with good system performance. The number can be increased to 8192 by using dual pump sources.

ORNL Demonstrates Large-Scale Technique to Produce Quantum Dots

ScienceCinema

Graham, David; Moon, Ji-Won

2018-01-16

A method to produce significant amounts of semiconducting nanoparticles for light-emitting displays, sensors, solar panels and biomedical applications has gained momentum with a demonstration by researchers at Oak Ridge National Laboratory.

Domain-Adapted Convolutional Networks for Satellite Image Classification: A Large-Scale Interactive Learning Workflow

DOE PAGES

Lunga, Dalton D.; Yang, Hsiuhan Lexie; Reith, Andrew E.; ...

2018-02-06

Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including dates, sensor position, lighting condition, and sensor types, often translate into class distribution shifts introducing complex nonlinear factors and hamper the potential impact of machine learning classifiers. Here, this article investigates the challenge of exploiting satellite images using convolutional neural networks (CNN) for settlement classification where the class distribution shifts are significant. We present a large-scale human settlement mapping workflow based-off multiple modules to adapt a pretrained CNN to address themore » negative impact of distribution shift on classification performance. To extend a locally trained classifier onto large spatial extents areas we introduce several submodules: First, a human-in-the-loop element for relabeling of misclassified target domain samples to generate representative examples for model adaptation; second, an efficient hashing module to minimize redundancy and noisy samples from the mass-selected examples; and third, a novel relevance ranking module to minimize the dominance of source example on the target domain. The workflow presents a novel and practical approach to achieve large-scale domain adaptation with binary classifiers that are based-off CNN features. Experimental evaluations are conducted on areas of interest that encompass various image characteristics, including multisensors, multitemporal, and multiangular conditions. Domain adaptation is assessed on source–target pairs through the transfer loss and transfer ratio metrics to illustrate the utility of the workflow.« less

Domain-Adapted Convolutional Networks for Satellite Image Classification: A Large-Scale Interactive Learning Workflow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lunga, Dalton D.; Yang, Hsiuhan Lexie; Reith, Andrew E.

Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including dates, sensor position, lighting condition, and sensor types, often translate into class distribution shifts introducing complex nonlinear factors and hamper the potential impact of machine learning classifiers. Here, this article investigates the challenge of exploiting satellite images using convolutional neural networks (CNN) for settlement classification where the class distribution shifts are significant. We present a large-scale human settlement mapping workflow based-off multiple modules to adapt a pretrained CNN to address themore » negative impact of distribution shift on classification performance. To extend a locally trained classifier onto large spatial extents areas we introduce several submodules: First, a human-in-the-loop element for relabeling of misclassified target domain samples to generate representative examples for model adaptation; second, an efficient hashing module to minimize redundancy and noisy samples from the mass-selected examples; and third, a novel relevance ranking module to minimize the dominance of source example on the target domain. The workflow presents a novel and practical approach to achieve large-scale domain adaptation with binary classifiers that are based-off CNN features. Experimental evaluations are conducted on areas of interest that encompass various image characteristics, including multisensors, multitemporal, and multiangular conditions. Domain adaptation is assessed on source–target pairs through the transfer loss and transfer ratio metrics to illustrate the utility of the workflow.« less

Conductive polymer nanowire gas sensor fabricated by nanoscale soft lithography

NASA Astrophysics Data System (ADS)

Tang, Ning; Jiang, Yang; Qu, Hemi; Duan, Xuexin

2017-12-01

Resistive devices composed of one-dimensional nanostructures are promising candidates for the next generation of gas sensors. However, the large-scale fabrication of nanowires is still challenging, which restricts the commercialization of such devices. Here, we report a highly efficient and facile approach to fabricating poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) nanowire chemiresistive gas sensors by nanoscale soft lithography. Well-defined sub-100 nm nanowires are fabricated on silicon substrate, which facilitates device integration. The nanowire chemiresistive gas sensor is demonstrated for NH3 and NO2 detection at room temperature and shows a limit of detection at ppb level, which is compatible with nanoscale PEDOT:PSS gas sensors fabricated with the conventional lithography technique. In comparison with PEDOT:PSS thin-film gas sensors, the nanowire gas sensor exhibits higher sensitivity and a much faster response to gas molecules.

Conductive polymer nanowire gas sensor fabricated by nanoscale soft lithography.

PubMed

Tang, Ning; Jiang, Yang; Qu, Hemi; Duan, Xuexin

2017-12-01

Resistive devices composed of one-dimensional nanostructures are promising candidates for the next generation of gas sensors. However, the large-scale fabrication of nanowires is still challenging, which restricts the commercialization of such devices. Here, we report a highly efficient and facile approach to fabricating poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) nanowire chemiresistive gas sensors by nanoscale soft lithography. Well-defined sub-100 nm nanowires are fabricated on silicon substrate, which facilitates device integration. The nanowire chemiresistive gas sensor is demonstrated for NH 3 and NO 2 detection at room temperature and shows a limit of detection at ppb level, which is compatible with nanoscale PEDOT:PSS gas sensors fabricated with the conventional lithography technique. In comparison with PEDOT:PSS thin-film gas sensors, the nanowire gas sensor exhibits higher sensitivity and a much faster response to gas molecules.

Wake-up transceivers for structural health monitoring of bridges

NASA Astrophysics Data System (ADS)

Kumberg, T.; Kokert, J.; Younesi, V.; Koenig, S.; Reindl, L. M.

2016-04-01

In this article we present a wireless sensor network to monitor the structural health of a large-scale highway bridge in Germany. The wireless sensor network consists of several sensor nodes that use wake-up receivers to realize latency free and low-power communication. The sensor nodes are either equipped with very accurate tilt sensor developed by Northrop Grumman LITEF GmbH or with a Novatel OEM615 GNSS receiver. Relay nodes are required to forward measurement data to a base station located on the bridge. The base station is a gateway that transmits the local measurement data to a remote server where it can be further analyzed and processed. Further on, we present an energy harvesting system to supply the energy demanding GNSS sensor nodes to realize long term monitoring.

Highly stretchable and wearable graphene strain sensors with controllable sensitivity for human motion monitoring.

PubMed

Park, Jung Jin; Hyun, Woo Jin; Mun, Sung Cik; Park, Yong Tae; Park, O Ok

2015-03-25

Because of their outstanding electrical and mechanical properties, graphene strain sensors have attracted extensive attention for electronic applications in virtual reality, robotics, medical diagnostics, and healthcare. Although several strain sensors based on graphene have been reported, the stretchability and sensitivity of these sensors remain limited, and also there is a pressing need to develop a practical fabrication process. This paper reports the fabrication and characterization of new types of graphene strain sensors based on stretchable yarns. Highly stretchable, sensitive, and wearable sensors are realized by a layer-by-layer assembly method that is simple, low-cost, scalable, and solution-processable. Because of the yarn structures, these sensors exhibit high stretchability (up to 150%) and versatility, and can detect both large- and small-scale human motions. For this study, wearable electronics are fabricated with implanted sensors that can monitor diverse human motions, including joint movement, phonation, swallowing, and breathing.

Development of Nanomechanical Sensors for Breast Cancer Biomarkers

DTIC Science & Technology

2008-06-01

semiconductor industry in developing large scale integrated circuits at very lost cost can lead to similar breakthroughs in array sensors for biomolecules of...insulated from the serum or buffer. The entire device is mounted onto a semiconductor chip carrier, for easy integration with electronics. Figure 3...Keithley 2400 source meter. The ac modulation and the dc bias are added by a noninverting summing circuit, which is integrated with the preamplifier

Complexity, Robustness, and Multistability in Network Systems with Switching Topologies: A Hierarchical Hybrid Control Approach

DTIC Science & Technology

2015-05-22

sensor networks for managing power levels of wireless networks ; air and ground transportation systems for air traffic control and payload transport and... network systems, large-scale systems, adaptive control, discontinuous systems 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF...cover a broad spectrum of ap- plications including cooperative control of unmanned air vehicles, autonomous underwater vehicles, distributed sensor

Integrating optical finger motion tracking with surface touch events.

PubMed

MacRitchie, Jennifer; McPherson, Andrew P

2015-01-01

This paper presents a method of integrating two contrasting sensor systems for studying human interaction with a mechanical system, using piano performance as the case study. Piano technique requires both precise small-scale motion of fingers on the key surfaces and planned large-scale movement of the hands and arms. Where studies of performance often focus on one of these scales in isolation, this paper investigates the relationship between them. Two sensor systems were installed on an acoustic grand piano: a monocular high-speed camera tracking the position of painted markers on the hands, and capacitive touch sensors attach to the key surfaces which measure the location of finger-key contacts. This paper highlights a method of fusing the data from these systems, including temporal and spatial alignment, segmentation into notes and automatic fingering annotation. Three case studies demonstrate the utility of the multi-sensor data: analysis of finger flexion or extension based on touch and camera marker location, timing analysis of finger-key contact preceding and following key presses, and characterization of individual finger movements in the transitions between successive key presses. Piano performance is the focus of this paper, but the sensor method could equally apply to other fine motor control scenarios, with applications to human-computer interaction.

Integrating optical finger motion tracking with surface touch events

PubMed Central

MacRitchie, Jennifer; McPherson, Andrew P.

2015-01-01

This paper presents a method of integrating two contrasting sensor systems for studying human interaction with a mechanical system, using piano performance as the case study. Piano technique requires both precise small-scale motion of fingers on the key surfaces and planned large-scale movement of the hands and arms. Where studies of performance often focus on one of these scales in isolation, this paper investigates the relationship between them. Two sensor systems were installed on an acoustic grand piano: a monocular high-speed camera tracking the position of painted markers on the hands, and capacitive touch sensors attach to the key surfaces which measure the location of finger-key contacts. This paper highlights a method of fusing the data from these systems, including temporal and spatial alignment, segmentation into notes and automatic fingering annotation. Three case studies demonstrate the utility of the multi-sensor data: analysis of finger flexion or extension based on touch and camera marker location, timing analysis of finger-key contact preceding and following key presses, and characterization of individual finger movements in the transitions between successive key presses. Piano performance is the focus of this paper, but the sensor method could equally apply to other fine motor control scenarios, with applications to human-computer interaction. PMID:26082732

Three Dimensional Distribution of Sensitive Field and Stress Field Inversion of Force Sensitive Materials under Constant Current Excitation.

PubMed

Zhao, Shuanfeng; Liu, Min; Guo, Wei; Zhang, Chuanwei

2018-02-28

Force sensitive conductive composite materials are functional materials which can be used as the sensitive material of force sensors. However, the existing sensors only use one-dimensional electrical properties of force sensitive conductive materials. Even in tactile sensors, the measurement of contact pressure is achieved by large-scale arrays and the units of a large-scale array are also based on the one-dimensional electrical properties of force sensitive materials. The main contribution of this work is to study the three-dimensional electrical properties and the inversion method of three-dimensional stress field of a force sensitive material (conductive rubber), which pushes the application of force sensitive material from one dimensional to three-dimensional. First, the mathematical model of the conductive rubber current field distribution under a constant force is established by the effective medium theory, and the current field distribution model of conductive rubber with different geometry, conductive rubber content and conductive rubber relaxation parameters is deduced. Secondly, the inversion method of the three-dimensional stress field of conductive rubber is established, which provides a theoretical basis for the design of a new tactile sensor, three-dimensional stress field and space force based on force sensitive materials.

A Game Theory Algorithm for Intra-Cluster Data Aggregation in a Vehicular Ad Hoc Network

PubMed Central

Chen, Yuzhong; Weng, Shining; Guo, Wenzhong; Xiong, Naixue

2016-01-01

Vehicular ad hoc networks (VANETs) have an important role in urban management and planning. The effective integration of vehicle information in VANETs is critical to traffic analysis, large-scale vehicle route planning and intelligent transportation scheduling. However, given the limitations in the precision of the output information of a single sensor and the difficulty of information sharing among various sensors in a highly dynamic VANET, effectively performing data aggregation in VANETs remains a challenge. Moreover, current studies have mainly focused on data aggregation in large-scale environments but have rarely discussed the issue of intra-cluster data aggregation in VANETs. In this study, we propose a multi-player game theory algorithm for intra-cluster data aggregation in VANETs by analyzing the competitive and cooperative relationships among sensor nodes. Several sensor-centric metrics are proposed to measure the data redundancy and stability of a cluster. We then study the utility function to achieve efficient intra-cluster data aggregation by considering both data redundancy and cluster stability. In particular, we prove the existence of a unique Nash equilibrium in the game model, and conduct extensive experiments to validate the proposed algorithm. Results demonstrate that the proposed algorithm has advantages over typical data aggregation algorithms in both accuracy and efficiency. PMID:26907272

A Game Theory Algorithm for Intra-Cluster Data Aggregation in a Vehicular Ad Hoc Network.

PubMed

Chen, Yuzhong; Weng, Shining; Guo, Wenzhong; Xiong, Naixue

2016-02-19

Vehicular ad hoc networks (VANETs) have an important role in urban management and planning. The effective integration of vehicle information in VANETs is critical to traffic analysis, large-scale vehicle route planning and intelligent transportation scheduling. However, given the limitations in the precision of the output information of a single sensor and the difficulty of information sharing among various sensors in a highly dynamic VANET, effectively performing data aggregation in VANETs remains a challenge. Moreover, current studies have mainly focused on data aggregation in large-scale environments but have rarely discussed the issue of intra-cluster data aggregation in VANETs. In this study, we propose a multi-player game theory algorithm for intra-cluster data aggregation in VANETs by analyzing the competitive and cooperative relationships among sensor nodes. Several sensor-centric metrics are proposed to measure the data redundancy and stability of a cluster. We then study the utility function to achieve efficient intra-cluster data aggregation by considering both data redundancy and cluster stability. In particular, we prove the existence of a unique Nash equilibrium in the game model, and conduct extensive experiments to validate the proposed algorithm. Results demonstrate that the proposed algorithm has advantages over typical data aggregation algorithms in both accuracy and efficiency.

A new framework to increase the efficiency of large-scale solar power plants.

NASA Astrophysics Data System (ADS)

Alimohammadi, Shahrouz; Kleissl, Jan P.

2015-11-01

A new framework to estimate the spatio-temporal behavior of solar power is introduced, which predicts the statistical behavior of power output at utility scale Photo-Voltaic (PV) power plants. The framework is based on spatio-temporal Gaussian Processes Regression (Kriging) models, which incorporates satellite data with the UCSD version of the Weather and Research Forecasting model. This framework is designed to improve the efficiency of the large-scale solar power plants. The results are also validated from measurements of the local pyranometer sensors, and some improvements in different scenarios are observed. Solar energy.

Sparse Measurement Systems: Applications, Analysis, Algorithms and Design

ERIC Educational Resources Information Center

Narayanaswamy, Balakrishnan

2011-01-01

This thesis deals with "large-scale" detection problems that arise in many real world applications such as sensor networks, mapping with mobile robots and group testing for biological screening and drug discovery. These are problems where the values of a large number of inputs need to be inferred from noisy observations and where the…

How well could existing sensors detect the deployment of a solar radiation management (SRM) geoengineering effort?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hurd, Alan J.

2016-04-29

While the stated reason for asking this question is “to understand better our ability to warn policy makers in the unlikely event of an unanticipated SRM geoengineering deployment or large-scale field experiment”, my colleagues and I felt that motives would be important context because the scale of any meaningful SRM deployment would be so large that covert deployment seems impossible. However, several motives emerged that suggest a less-than-global effort might be important.

Remote sensing of exposure to NO2: Satellite versus ground-based measurement in a large urban area

NASA Astrophysics Data System (ADS)

Bechle, Matthew J.; Millet, Dylan B.; Marshall, Julian D.

2013-04-01

Remote sensing may be a useful tool for exploring spatial variability of air pollution exposure within an urban area. To evaluate the extent to which satellite data from the Ozone Monitoring Instrument (OMI) can resolve urban-scale gradients in ground-level nitrogen dioxide (NO2) within a large urban area, we compared estimates of surface NO2 concentrations derived from OMI measurements and US EPA ambient monitoring stations. OMI, aboard NASA's Aura satellite, provides daily afternoon (˜13:30 local time) measurements of NO2 tropospheric column abundance. We used scaling factors (surface-to-column ratios) to relate satellite column measurements to ground-level concentrations. We compared 4138 sets of paired data for 25 monitoring stations in the South Coast Air Basin of California for all of 2005. OMI measurements include more data gaps than the ground monitors (60% versus 5% of available data, respectively), owing to cloud contamination and imposed limits on pixel size. The spatial correlation between OMI columns and corrected in situ measurements is strong (r = 0.93 for annual average data), indicating that the within-urban spatial signature of surface NO2 is well resolved by the satellite sensor. Satellite-based surface estimates employing scaling factors from an urban model provide a reliable measure (annual mean bias: -13%; seasonal mean bias: <1% [spring] to -22% [fall]) of fine-scale surface NO2. We also find that OMI provides good spatial density in the study region (average area [km2] per measurement: 730 for the satellite sensor vs. 1100 for the monitors). Our findings indicate that satellite observations of NO2 from the OMI sensor provide a reliable measure of spatial variability in ground-level NO2 exposure for a large urban area.

Towards a cross-platform software framework to support end-to-end hydrometeorological sensor network deployment

NASA Astrophysics Data System (ADS)

Celicourt, P.; Sam, R.; Piasecki, M.

2016-12-01

Global phenomena such as climate change and large scale environmental degradation require the collection of accurate environmental data at detailed spatial and temporal scales from which knowledge and actionable insights can be derived using data science methods. Despite significant advances in sensor network technologies, sensors and sensor network deployment remains a labor-intensive, time consuming, cumbersome and expensive task. These factors demonstrate why environmental data collection remains a challenge especially in developing countries where technical infrastructure, expertise and pecuniary resources are scarce. In addition, they also demonstrate the reason why dense and long-term environmental data collection has been historically quite difficult. Moreover, hydrometeorological data collection efforts usually overlook the (critically important) inclusion of a standards-based system for storing, managing, organizing, indexing, documenting and sharing sensor data. We are developing a cross-platform software framework using the Python programming language that will allow us to develop a low cost end-to-end (from sensor to publication) system for hydrometeorological conditions monitoring. The software framework contains provision for sensor, sensor platforms, calibration and network protocols description, sensor programming, data storage, data publication and visualization and more importantly data retrieval in a desired unit system. It is being tested on the Raspberry Pi microcomputer as end node and a laptop PC as the base station in a wireless setting.

Field-scale moisture estimates using COSMOS sensors: a validation study with temporary networks and leaf-area-indices

USDA-ARS?s Scientific Manuscript database

The Cosmic-ray Soil Moisture Observing System (COSMOS) is a new and innovative method for estimating surface and near surface soil moisture at large (~700 m) scales. This system accounts for liquid water within its measurement volume. Many of the sites used in the early validation of the system had...

Convergence of microclimate in residential landscapes across diverse cities in the United States

Treesearch

Sharon J. Hall; J. Learned; B. Ruddell; K.L. Larson; J. Cavender-Bares; N. Bettez; P.M. Groffman; Morgan Grove; J.B. Heffernan; S.E. Hobbie; J.L. Morse; C. Neill; K.C. Nelson; Jarlath O' Neil-Dunne; L. Ogden; D.E. Pataki; W.D. Pearse; C. Polsky; R. Roy Chowdhury; M.K. Steele; T.L.E. Trammell

2016-01-01

The urban heat island (UHI) is a well-documented pattern of warming in cities relative to rural areas. Most UHI research utilizes remote sensing methods at large scales, or climate sensors in single cities surrounded by standardized land cover. Relatively few studies have explored continental-scale climatic patterns within common urban microenvironments such as...

Sensor fusion of cameras and a laser for city-scale 3D reconstruction.

PubMed

Bok, Yunsu; Choi, Dong-Geol; Kweon, In So

2014-11-04

This paper presents a sensor fusion system of cameras and a 2D laser sensorfor large-scale 3D reconstruction. The proposed system is designed to capture data on afast-moving ground vehicle. The system consists of six cameras and one 2D laser sensor,and they are synchronized by a hardware trigger. Reconstruction of 3D structures is doneby estimating frame-by-frame motion and accumulating vertical laser scans, as in previousworks. However, our approach does not assume near 2D motion, but estimates free motion(including absolute scale) in 3D space using both laser data and image features. In orderto avoid the degeneration associated with typical three-point algorithms, we present a newalgorithm that selects 3D points from two frames captured by multiple cameras. The problemof error accumulation is solved by loop closing, not by GPS. The experimental resultsshow that the estimated path is successfully overlaid on the satellite images, such that thereconstruction result is very accurate.

Research on quantitative relationship between NIIRS and the probabilities of discrimination

NASA Astrophysics Data System (ADS)

Bai, Honggang

2011-08-01

There are a large number of electro-optical (EO) and infrared (IR) sensors used on military platforms including ground vehicle, low altitude air vehicle, high altitude air vehicle, and satellite systems. Ground vehicle and low-altitude air vehicle (rotary and fixed-wing aircraft) sensors typically use the probabilities of discrimination (detection, recognition, and identification) as design requirements and system performance indicators. High-altitude air vehicles and satellite sensors have traditionally used the National Imagery Interpretation Rating Scale (NIIRS) performance measures for guidance in design and measures of system performance. Recently, there has a large effort to make strategic sensor information available to tactical forces or make the information of targets acquisition can be used by strategic systems. In this paper, the two techniques about the probabilities of discrimination and NIIRS for sensor design are presented separately. For the typical infrared remote sensor design parameters, the function of the probability of recognition and NIIRS scale as the distance R is given to Standard NATO Target and M1Abrams two different size targets based on the algorithm of predicting the field performance and NIIRS. For Standard NATO Target, M1Abrams, F-15, and B-52 four different size targets, the conversion from NIIRS to the probabilities of discrimination are derived and calculated, and the similarities and differences between NIIRS and the probabilities of discrimination are analyzed based on the result of calculation. Comparisons with preliminary calculation results show that the conversion between NIIRS and the probabilities of discrimination is probable although more validation experiments are needed.

Monolithic pixel development in TowerJazz 180 nm CMOS for the outer pixel layers in the ATLAS experiment

NASA Astrophysics Data System (ADS)

Berdalovic, I.; Bates, R.; Buttar, C.; Cardella, R.; Egidos Plaja, N.; Hemperek, T.; Hiti, B.; van Hoorne, J. W.; Kugathasan, T.; Mandic, I.; Maneuski, D.; Marin Tobon, C. A.; Moustakas, K.; Musa, L.; Pernegger, H.; Riedler, P.; Riegel, C.; Schaefer, D.; Schioppa, E. J.; Sharma, A.; Snoeys, W.; Solans Sanchez, C.; Wang, T.; Wermes, N.

2018-01-01

The upgrade of the ATLAS tracking detector (ITk) for the High-Luminosity Large Hadron Collider at CERN requires the development of novel radiation hard silicon sensor technologies. Latest developments in CMOS sensor processing offer the possibility of combining high-resistivity substrates with on-chip high-voltage biasing to achieve a large depleted active sensor volume. We have characterised depleted monolithic active pixel sensors (DMAPS), which were produced in a novel modified imaging process implemented in the TowerJazz 180 nm CMOS process in the framework of the monolithic sensor development for the ALICE experiment. Sensors fabricated in this modified process feature full depletion of the sensitive layer, a sensor capacitance of only a few fF and radiation tolerance up to 1015 neq/cm2. This paper summarises the measurements of charge collection properties in beam tests and in the laboratory using radioactive sources and edge TCT. The results of these measurements show significantly improved radiation hardness obtained for sensors manufactured using the modified process. This has opened the way to the design of two large scale demonstrators for the ATLAS ITk. To achieve a design compatible with the requirements of the outer pixel layers of the tracker, a charge sensitive front-end taking 500 nA from a 1.8 V supply is combined with a fast digital readout architecture. The low-power front-end with a 25 ns time resolution exploits the low sensor capacitance to reduce noise and analogue power, while the implemented readout architectures minimise power by reducing the digital activity.

Detection of Steel Fatigue Cracks with Strain Sensing Sheets Based on Large Area Electronics

PubMed Central

Yao, Yao; Glisic, Branko

2015-01-01

Reliable early-stage damage detection requires continuous monitoring over large areas of structure, and with sensors of high spatial resolution. Technologies based on Large Area Electronics (LAE) can enable direct sensing and can be scaled to the level required for Structural Health Monitoring (SHM) of civil structures and infrastructure. Sensing sheets based on LAE contain dense arrangements of thin-film strain sensors, associated electronics and various control circuits deposited and integrated on a flexible polyimide substrate that can cover large areas of structures. This paper presents the development stage of a prototype strain sensing sheet based on LAE for crack detection and localization. Two types of sensing-sheet arrangements with size 6 × 6 inch (152 × 152 mm) were designed and manufactured, one with a very dense arrangement of sensors and the other with a less dense arrangement of sensors. The sensing sheets were bonded to steel plates, which had a notch on the boundary, so the fatigue cracks could be generated under cyclic loading. The sensors within the sensing sheet that were close to the notch tip successfully detected the initialization of fatigue crack and localized the damage on the plate. The sensors that were away from the crack successfully detected the propagation of fatigue cracks based on the time history of the measured strain. The results of the tests have validated the general principles of the proposed sensing sheets for crack detection and identified advantages and challenges of the two tested designs. PMID:25853407

An accurate and computationally efficient algorithm for ground peak identification in large footprint waveform LiDAR data

NASA Astrophysics Data System (ADS)

Zhuang, Wei; Mountrakis, Giorgos

2014-09-01

Large footprint waveform LiDAR sensors have been widely used for numerous airborne studies. Ground peak identification in a large footprint waveform is a significant bottleneck in exploring full usage of the waveform datasets. In the current study, an accurate and computationally efficient algorithm was developed for ground peak identification, called Filtering and Clustering Algorithm (FICA). The method was evaluated on Land, Vegetation, and Ice Sensor (LVIS) waveform datasets acquired over Central NY. FICA incorporates a set of multi-scale second derivative filters and a k-means clustering algorithm in order to avoid detecting false ground peaks. FICA was tested in five different land cover types (deciduous trees, coniferous trees, shrub, grass and developed area) and showed more accurate results when compared to existing algorithms. More specifically, compared with Gaussian decomposition, the RMSE ground peak identification by FICA was 2.82 m (5.29 m for GD) in deciduous plots, 3.25 m (4.57 m for GD) in coniferous plots, 2.63 m (2.83 m for GD) in shrub plots, 0.82 m (0.93 m for GD) in grass plots, and 0.70 m (0.51 m for GD) in plots of developed areas. FICA performance was also relatively consistent under various slope and canopy coverage (CC) conditions. In addition, FICA showed better computational efficiency compared to existing methods. FICA's major computational and accuracy advantage is a result of the adopted multi-scale signal processing procedures that concentrate on local portions of the signal as opposed to the Gaussian decomposition that uses a curve-fitting strategy applied in the entire signal. The FICA algorithm is a good candidate for large-scale implementation on future space-borne waveform LiDAR sensors.

Large Scale Gaussian Processes for Atmospheric Parameter Retrieval and Cloud Screening

NASA Astrophysics Data System (ADS)

Camps-Valls, G.; Gomez-Chova, L.; Mateo, G.; Laparra, V.; Perez-Suay, A.; Munoz-Mari, J.

2017-12-01

Current Earth-observation (EO) applications for image classification have to deal with an unprecedented big amount of heterogeneous and complex data sources. Spatio-temporally explicit classification methods are a requirement in a variety of Earth system data processing applications. Upcoming missions such as the super-spectral Copernicus Sentinels EnMAP and FLEX will soon provide unprecedented data streams. Very high resolution (VHR) sensors like Worldview-3 also pose big challenges to data processing. The challenge is not only attached to optical sensors but also to infrared sounders and radar images which increased in spectral, spatial and temporal resolution. Besides, we should not forget the availability of the extremely large remote sensing data archives already collected by several past missions, such ENVISAT, Cosmo-SkyMED, Landsat, SPOT, or Seviri/MSG. These large-scale data problems require enhanced processing techniques that should be accurate, robust and fast. Standard parameter retrieval and classification algorithms cannot cope with this new scenario efficiently. In this work, we review the field of large scale kernel methods for both atmospheric parameter retrieval and cloud detection using infrared sounding IASI data and optical Seviri/MSG imagery. We propose novel Gaussian Processes (GPs) to train problems with millions of instances and high number of input features. Algorithms can cope with non-linearities efficiently, accommodate multi-output problems, and provide confidence intervals for the predictions. Several strategies to speed up algorithms are devised: random Fourier features and variational approaches for cloud classification using IASI data and Seviri/MSG, and engineered randomized kernel functions and emulation in temperature, moisture and ozone atmospheric profile retrieval from IASI as a proxy to the upcoming MTG-IRS sensor. Excellent compromise between accuracy and scalability are obtained in all applications.

Demonstration of Technologies for Remote and in Situ Sensing of Atmospheric Methane Abundances - a Controlled Release Experiment

NASA Astrophysics Data System (ADS)

Aubrey, A. D.; Thorpe, A. K.; Christensen, L. E.; Dinardo, S.; Frankenberg, C.; Rahn, T. A.; Dubey, M.

2013-12-01

It is critical to constrain both natural and anthropogenic sources of methane to better predict the impact on global climate change. Critical technologies for this assessment include those that can detect methane point and concentrated diffuse sources over large spatial scales. Airborne spectrometers can potentially fill this gap for large scale remote sensing of methane while in situ sensors, both ground-based and mounted on aerial platforms, can monitor and quantify at small to medium spatial scales. The Jet Propulsion Laboratory (JPL) and collaborators recently conducted a field test located near Casper, WY, at the Rocky Mountain Oilfield Test Center (RMOTC). These tests were focused on demonstrating the performance of remote and in situ sensors for quantification of point-sourced methane. A series of three controlled release points were setup at RMOTC and over the course of six experiment days, the point source flux rates were varied from 50 LPM to 2400 LPM (liters per minute). During these releases, in situ sensors measured real-time methane concentration from field towers (downwind from the release point) and using a small Unmanned Aerial System (sUAS) to characterize spatiotemporal variability of the plume structure. Concurrent with these methane point source controlled releases, airborne sensor overflights were conducted using three aircraft. The NASA Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) participated with a payload consisting of a Fourier Transform Spectrometer (FTS) and an in situ methane sensor. Two imaging spectrometers provided assessment of optical and thermal infrared detection of methane plumes. The AVIRIS-next generation (AVIRIS-ng) sensor has been demonstrated for detection of atmospheric methane in the short wave infrared region, specifically using the absorption features at ~2.3 μm. Detection of methane in the thermal infrared region was evaluated by flying the Hyperspectral Thermal Emission Spectrometer (HyTES), retrievals which interrogate spectral features in the 7.5 to 8.5 μm region. Here we discuss preliminary results from the JPL activities during the RMOTC controlled release experiment, including capabilities of airborne sensors for total columnar atmospheric methane detection and comparison to results from ground measurements and dispersion models. Potential application areas for these remote sensing technologies include assessment of anthropogenic and natural methane sources over wide spatial scales that represent significant unconstrained factors to the global methane budget.

Electrical conductivity of nanocomposites based on carbon nanotubes: a 3D multiscale modeling approach

NASA Astrophysics Data System (ADS)

Grabowski, Krzysztof; Zbyrad, Paulina; Staszewski, Wieslaw J.; Uhl, Tadeusz; Wiatr, Kazimierz; Packo, Pawel

2016-04-01

Remarkable electrical properties of carbon nanotubes (CNT) have lead to increased interest in studying CNT- based devices. Many of current researches are devoted to using all kinds of carbon nanomaterials in the con- struction of sensory elements. One of the most common applications is the development of high performance, large scale sensors. Due to the remarkable conductivity of CNT's such devices represent very high sensitivity. However, there are no sufficient tools for studying and designing such sensors. The main objective of this paper is to develop and validate a multiscale numerical model for a carbon nanotubes based sensor. The device utilises the change of electrical conductivity of a nanocomposite material under applied deformation. The nanocomposite consists of a number of CNTs dispersed in polymer matrix. The paper is devoted to the analysis of the impact of spatial distribution of carbon nanotubes in polymer matrix on electrical conductivity of the sensor. One of key elements is also to examine the impact of strain on electric charge ow in such anisotropic composite structures. In the following work a multiscale electro-mechanical model for CNT - based nanocomposites is proposed. The model comprises of two length scales, namely the meso- and the macro-scale for mechanical and electrical domains. The approach allows for evaluation of macro-scale mechanical response of a strain sensor. Electrical properties of polymeric material with certain CNT fractions were derived considering electrical properties of CNTs, their contact and the tunnelling effect.

As-Grown Gallium Nitride Nanowire Electromechanical Resonators

NASA Astrophysics Data System (ADS)

Montague, Joshua R.

Technological development in recent years has led to a ubiquity of micro- and nano-scale electromechanical devices. Sensors for monitoring temperature, pressure, mass, etc., are now found in nearly all electronic devices at both the industrial and consumer levels. As has been true for integrated circuit electronics, these electromechanical devices have continued to be scaled down in size. For many nanometer-scale structures with large surface-to-volume ratio, dissipation (energy loss) becomes prohibitively large causing a decreasing sensitivity with decreasing sensor size. In this work, gallium nitride (GaN) nanowires are investigated as singly-clamped (cantilever) mechanical resonators with typical mechanical quality factors, Q (equal to the ratio of resonance frequency to peak full-width-at-half-maximum-power) and resonance frequencies, respectively, at or above 30,000, and near 1 MHz. These Q values---in vacuum at room temperature---indicate very low levels of dissipation; they are essentially the same as those for bulk quartz crystal resonators that form the basis of simple clocks and mass sensors. The GaN nanowires have lengths and diameters, respectively, of approximately 15 micrometers and hundreds of nanometers. As-grown GaN nanowire Q values are larger than other similarly-sized, bottom-up, cantilever resonators and this property makes them very attractive for use as resonant sensors. We demonstrate the capability of detecting sub-monolayer levels of atomic layer deposited (ALD) films, and the robust nature of the GaN nanowires structure that allows for their 'reuse' after removal of such layers. In addition to electron microscope-based measurement techniques, we demonstrate the successful capacitive detection of a single nanowire using microwave homodyne reflectometry. This technique is then extended to allow for simultaneous measurements of large ensembles of GaN nanowires on a single sample, providing statistical information about the distribution of individual nanowire properties. We observe nanowire-to-nanowire variations in the temperature dependence of GaN nanowire resonance frequency and in the observed mechanical dissipation. We also use this ensemble measurement technique to demonstrate unique, very low-loss resonance behavior at low temperatures. The low dissipation (and corresponding large Q values) observed in as-grown GaN nanowires also provides a unique opportunity for studying fundamental energy loss mechanisms in nano-scale objects. With estimated mass sensitivities on the level of zeptograms (10-21 g) in a one second averaging time, GaN nanowires may be a significant addition to the field of resonant sensors and worthy of future research and device integration.

Sensing sheets based on large area electronics for fatigue crack detection

NASA Astrophysics Data System (ADS)

Yao, Yao; Glisic, Branko

2015-03-01

Reliable early-stage damage detection requires continuous structural health monitoring (SHM) over large areas of structure, and with high spatial resolution of sensors. This paper presents the development stage of prototype strain sensing sheets based on Large Area Electronics (LAE), in which thin-film strain gauges and control circuits are integrated on the flexible electronics and deposited on a polyimide sheet that can cover large areas. These sensing sheets were applied for fatigue crack detection on small-scale steel plates. Two types of sensing-sheet interconnects were designed and manufactured, and dense arrays of strain gauge sensors were assembled onto the interconnects. In total, four (two for each design type) strain sensing sheets were created and tested, which were sensitive to strain at virtually every point over the whole sensing sheet area. The sensing sheets were bonded to small-scale steel plates, which had a notch on the boundary so that fatigue cracks could be generated under cyclic loading. The fatigue tests were carried out at the Carleton Laboratory of Columbia University, and the steel plates were attached through a fixture to the loading machine that applied cyclic fatigue load. Fatigue cracks then occurred and propagated across the steel plates, leading to the failure of these test samples. The strain sensor that was close to the notch successfully detected the initialization of fatigue crack and localized the damage on the plate. The strain sensor that was away from the crack successfully detected the propagation of fatigue crack based on the time history of measured strain. Overall, the results of the fatigue tests validated general principles of the strain sensing sheets for crack detection.

Design of a Six Degree of Freedom Thrust Sensor for a Hybrid Rocket

NASA Astrophysics Data System (ADS)

McGehee, Tripp

2005-03-01

A hybrid rocket is composed of a solid fuel and a separate liquid or gaseous oxidizer. These rockets may be throttled like liquid rockets, are safer than solid rockets, and are much less complex than liquid rockets. However, hybrid rockets produce thrust oscillations that are not practical for large scale use. A lab scale hybrid rocket at the University of Arkansas at Little Rock (UALR) Hybrid Rocket Facility is used to develop sensors to measure physical properties of hybrid rockets. Research is currently being conducted to design a six degree of freedom force sensor to measure the thrust and torque in all three spatial dimensions. The current design mounts the rocket in a rigid cage and connects the cage to a solid table by six sensor legs. The legs utilize strain gauges and a Wheatstone bridge to produce a voltage proportional to the force on the leg. A detailed description of the cage design and the design process will be given.

Design of a Minimum Surface-Effect Tendon-Based Microactuator for Micromanipulation

NASA Technical Reports Server (NTRS)

Goldfarb, Michael; Lipsey, James H.

1997-01-01

A piezoelectric (PZT) stack-based actuator was developed to provide a means of actuation with dynamic characteristics appropriate for small-scale manipulation. In particular, the design incorporates a highly nonlinear, large-ratio transmission that provides approximately two orders of magnitude motion amplification from the PZT stack. In addition to motion amplification, the nonlinear transmission was designed via optimization methods to distort the highly non-uniform properties of a piezoelectric actuator so that the achievable actuation force is nearly constant throughout the actuator workspace. The package also includes sensors that independently measure actuator output force and displacement, so that a manipulator structure need not incorporate sensors nor the associated wires. Specifically, the actuator was designed to output a maximum force of at least one Newton through a stroke of at least one millimeter. For purposes of small-scale precision position and/or force control, the actuator/sensor package was designed to eliminate stick-slip friction and backlash. The overall dimensions of the actuator/sensor package are approximately 40 x 65 x 25 mm.

Onboard Image Processing System for Hyperspectral Sensor

PubMed Central

Hihara, Hiroki; Moritani, Kotaro; Inoue, Masao; Hoshi, Yoshihiro; Iwasaki, Akira; Takada, Jun; Inada, Hitomi; Suzuki, Makoto; Seki, Taeko; Ichikawa, Satoshi; Tanii, Jun

2015-01-01

Onboard image processing systems for a hyperspectral sensor have been developed in order to maximize image data transmission efficiency for large volume and high speed data downlink capacity. Since more than 100 channels are required for hyperspectral sensors on Earth observation satellites, fast and small-footprint lossless image compression capability is essential for reducing the size and weight of a sensor system. A fast lossless image compression algorithm has been developed, and is implemented in the onboard correction circuitry of sensitivity and linearity of Complementary Metal Oxide Semiconductor (CMOS) sensors in order to maximize the compression ratio. The employed image compression method is based on Fast, Efficient, Lossless Image compression System (FELICS), which is a hierarchical predictive coding method with resolution scaling. To improve FELICS’s performance of image decorrelation and entropy coding, we apply a two-dimensional interpolation prediction and adaptive Golomb-Rice coding. It supports progressive decompression using resolution scaling while still maintaining superior performance measured as speed and complexity. Coding efficiency and compression speed enlarge the effective capacity of signal transmission channels, which lead to reducing onboard hardware by multiplexing sensor signals into a reduced number of compression circuits. The circuitry is embedded into the data formatter of the sensor system without adding size, weight, power consumption, and fabrication cost. PMID:26404281

Graphene nanoribbon field effect transistor for nanometer-size on-chip temperature sensor

NASA Astrophysics Data System (ADS)

Banadaki, Yaser M.; Srivastava, Ashok; Sharifi, Safura

2016-04-01

Graphene has been extensively investigated as a promising material for various types of high performance sensors due to its large surface-to-volume ratio, remarkably high carrier mobility, high carrier density, high thermal conductivity, extremely high mechanical strength and high signal-to-noise ratio. The power density and the corresponding die temperature can be tremendously high in scaled emerging technology designs, urging the on-chip sensing and controlling of the generated heat in nanometer dimensions. In this paper, we have explored the feasibility of a thin oxide graphene nanoribbon (GNR) as nanometer-size temperature sensor for detecting local on-chip temperature at scaled bias voltages of emerging technology. We have introduced an analytical model for GNR FET for 22nm technology node, which incorporates both thermionic emission of high-energy carriers and band-to-band-tunneling (BTBT) of carriers from drain to channel regions together with different scattering mechanisms due to intrinsic acoustic phonons and optical phonons and line-edge roughness in narrow GNRs. The temperature coefficient of resistivity (TCR) of GNR FET-based temperature sensor shows approximately an order of magnitude higher TCR than large-area graphene FET temperature sensor by accurately choosing of GNR width and bias condition for a temperature set point. At gate bias VGS = 0.55 V, TCR maximizes at room temperature to 2.1×10-2 /K, which is also independent of GNR width, allowing the design of width-free GNR FET for room temperature sensing applications.

Toward a theoretical framework for trustworthy cyber sensing

NASA Astrophysics Data System (ADS)

Xu, Shouhuai

2010-04-01

Cyberspace is an indispensable part of the economy and society, but has been "polluted" with many compromised computers that can be abused to launch further attacks against the others. Since it is likely that there always are compromised computers, it is important to be aware of the (dynamic) cyber security-related situation, which is however challenging because cyberspace is an extremely large-scale complex system. Our project aims to investigate a theoretical framework for trustworthy cyber sensing. With the perspective of treating cyberspace as a large-scale complex system, the core question we aim to address is: What would be a competent theoretical (mathematical and algorithmic) framework for designing, analyzing, deploying, managing, and adapting cyber sensor systems so as to provide trustworthy information or input to the higher layer of cyber situation-awareness management, even in the presence of sophisticated malicious attacks against the cyber sensor systems?

Battlespace Awareness: Heterogeneous Sensor Maps of Large Scale, Complex Environments

DTIC Science & Technology

2017-06-13

reference frames enable a system designer to describe the position of any sensor or platform at any point of time. This section introduces the...analysis to evaluate the quality of reconstructions created by our algorithms. CloudCompare is an open-source tool designed for this purpose [65]. In...structure of the data. The data term seeks to keep the proposed solution (u) similar to the originally observed values ( f ). A systems designer must

Novel Sensor for the In Situ Measurement of Uranium Fluxes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hatfield, Kirk

2015-02-10

The goal of this project was to develop a sensor that incorporates the field-tested concepts of the passive flux meter to provide direct in situ measures of flux for uranium and groundwater in porous media. Measurable contaminant fluxes [J] are essentially the product of concentration [C] and groundwater flux or specific discharge [q ]. The sensor measures [J] and [q] by changes in contaminant and tracer amounts respectively on a sorbent. By using measurement rather than inference from static parameters, the sensor can directly advance conceptual and computational models for field scale simulations. The sensor was deployed in conjunction withmore » DOE in obtaining field-scale quantification of subsurface processes affecting uranium transport (e.g., advection) and transformation (e.g., uranium attenuation) at the Rifle IFRC Site in Rifle, Colorado. Project results have expanded our current understanding of how field-scale spatial variations in fluxes of uranium, groundwater and salient electron donor/acceptors are coupled to spatial variations in measured microbial biomass/community composition, effective field-scale uranium mass balances, attenuation, and stability. The coupling between uranium, various nutrients and micro flora can be used to estimate field-scale rates of uranium attenuation and field-scale transitions in microbial communities. This research focuses on uranium (VI), but the sensor principles and design are applicable to field-scale fate and transport of other radionuclides. Laboratory studies focused on sorbent selection and calibration, along with sensor development and validation under controlled conditions. Field studies were conducted at the Rifle IFRC Site in Rifle, Colorado. These studies were closely coordinated with existing SBR (formerly ERSP) projects to complement data collection. Small field tests were conducted during the first two years that focused on evaluating field-scale deployment procedures and validating sensor performance under controlled field conditions. In the third and fourth year a suite of larger field studies were conducted. For these studies, the uranium flux sensor was used with uranium speciation measurements and molecular-biological tools to characterize microbial community and active biomass at synonymous wells distributed in a large grid. These field efforts quantified spatial changes in uranium flux and field-scale rates of uranium attenuation (ambient and stimulated), uranium stability, and quantitatively assessed how fluxes and effective reaction rates were coupled to spatial variations in microbial community and active biomass. Analyses of data from these field experiments were used to generate estimates of Monod kinetic parameters that are ‘effective’ in nature and optimal for modeling uranium fate and transport at the field-scale. This project provided the opportunity to develop the first sensor that provides direct measures of both uranium (VI) and groundwater flux. A multidisciplinary team was assembled to include two geochemists, a microbiologist, and two quantitative contaminant hydrologists. Now that the project is complete, the sensor can be deployed at DOE sites to evaluate field-scale uranium attenuation, source behavior, the efficacy of remediation, and off-site risk. Because the sensor requires no power, it can be deployed at remote sites for periods of days to months. The fundamental science derived from this project can be used to advance the development of predictive models for various transport and attenuation processes in aquifers. Proper development of these models is critical for long-term stewardship of contaminated sites in the context of predicting uranium source behavior, remediation performance, and off-site risk.« less

High-Temperature Strain Sensing for Aerospace Applications

NASA Technical Reports Server (NTRS)

Piazza, Anthony; Richards, Lance W.; Hudson, Larry D.

2008-01-01

Thermal protection systems (TPS) and hot structures are utilizing advanced materials that operate at temperatures that exceed abilities to measure structural performance. Robust strain sensors that operate accurately and reliably beyond 1800 F are needed but do not exist. These shortcomings hinder the ability to validate analysis and modeling techniques and hinders the ability to optimize structural designs. This presentation examines high-temperature strain sensing for aerospace applications and, more specifically, seeks to provide strain data for validating finite element models and thermal-structural analyses. Efforts have been made to develop sensor attachment techniques for relevant structural materials at the small test specimen level and to perform laboratory tests to characterize sensor and generate corrections to apply to indicated strains. Areas highlighted in this presentation include sensors, sensor attachment techniques, laboratory evaluation/characterization of strain measurement, and sensor use in large-scale structures.

First-time demonstration of measuring concrete prestress levels with metal packaged fibre optic sensors

NASA Astrophysics Data System (ADS)

Mckeeman, I.; Fusiek, G.; Perry, M.; Johnston, M.; Saafi, M.; Niewczas, P.; Walsh, M.; Khan, S.

2016-09-01

In this work we present the first large-scale demonstration of metal packaged fibre Bragg grating sensors developed to monitor prestress levels in prestressed concrete. To validate the technology, strain and temperature sensors were mounted on steel prestressing strands in concrete beams and stressed up to 60% of the ultimate tensile strength of the strand. We discuss the methods and calibration procedures used to fabricate and attach the temperature and strain sensors. The use of induction brazing for packaging the fibre Bragg gratings and welding the sensors to prestressing strands eliminates the use of epoxy, making the technique suitable for high-stress monitoring in an irradiated, harsh industrial environment. Initial results based on the first week of data after stressing the beams show the strain sensors are able to monitor prestress levels in ambient conditions.

Performance of a novel wafer scale CMOS active pixel sensor for bio-medical imaging.

PubMed

Esposito, M; Anaxagoras, T; Konstantinidis, A C; Zheng, Y; Speller, R D; Evans, P M; Allinson, N M; Wells, K

2014-07-07

Recently CMOS active pixels sensors (APSs) have become a valuable alternative to amorphous silicon and selenium flat panel imagers (FPIs) in bio-medical imaging applications. CMOS APSs can now be scaled up to the standard 20 cm diameter wafer size by means of a reticle stitching block process. However, despite wafer scale CMOS APS being monolithic, sources of non-uniformity of response and regional variations can persist representing a significant challenge for wafer scale sensor response. Non-uniformity of stitched sensors can arise from a number of factors related to the manufacturing process, including variation of amplification, variation between readout components, wafer defects and process variations across the wafer due to manufacturing processes. This paper reports on an investigation into the spatial non-uniformity and regional variations of a wafer scale stitched CMOS APS. For the first time a per-pixel analysis of the electro-optical performance of a wafer CMOS APS is presented, to address inhomogeneity issues arising from the stitching techniques used to manufacture wafer scale sensors. A complete model of the signal generation in the pixel array has been provided and proved capable of accounting for noise and gain variations across the pixel array. This novel analysis leads to readout noise and conversion gain being evaluated at pixel level, stitching block level and in regions of interest, resulting in a coefficient of variation ⩽1.9%. The uniformity of the image quality performance has been further investigated in a typical x-ray application, i.e. mammography, showing a uniformity in terms of CNR among the highest when compared with mammography detectors commonly used in clinical practice. Finally, in order to compare the detection capability of this novel APS with the technology currently used (i.e. FPIs), theoretical evaluation of the detection quantum efficiency (DQE) at zero-frequency has been performed, resulting in a higher DQE for this detector compared to FPIs. Optical characterization, x-ray contrast measurements and theoretical DQE evaluation suggest that a trade off can be found between the need of a large imaging area and the requirement of a uniform imaging performance, making the DynAMITe large area CMOS APS suitable for a range of bio-medical applications.

Carbon Nanotube Integration with a CMOS Process

PubMed Central

Perez, Maximiliano S.; Lerner, Betiana; Resasco, Daniel E.; Pareja Obregon, Pablo D.; Julian, Pedro M.; Mandolesi, Pablo S.; Buffa, Fabian A.; Boselli, Alfredo; Lamagna, Alberto

2010-01-01

This work shows the integration of a sensor based on carbon nanotubes using CMOS technology. A chip sensor (CS) was designed and manufactured using a 0.30 μm CMOS process, leaving a free window on the passivation layer that allowed the deposition of SWCNTs over the electrodes. We successfully investigated with the CS the effect of humidity and temperature on the electrical transport properties of SWCNTs. The possibility of a large scale integration of SWCNTs with CMOS process opens a new route in the design of more efficient, low cost sensors with high reproducibility in their manufacture. PMID:22319330

Multiple sensor fault diagnosis for dynamic processes.

PubMed

Li, Cheng-Chih; Jeng, Jyh-Cheng

2010-10-01

Modern industrial plants are usually large scaled and contain a great amount of sensors. Sensor fault diagnosis is crucial and necessary to process safety and optimal operation. This paper proposes a systematic approach to detect, isolate and identify multiple sensor faults for multivariate dynamic systems. The current work first defines deviation vectors for sensor observations, and further defines and derives the basic sensor fault matrix (BSFM), consisting of the normalized basic fault vectors, by several different methods. By projecting a process deviation vector to the space spanned by BSFM, this research uses a vector with the resulted weights on each direction for multiple sensor fault diagnosis. This study also proposes a novel monitoring index and derives corresponding sensor fault detectability. The study also utilizes that vector to isolate and identify multiple sensor faults, and discusses the isolatability and identifiability. Simulation examples and comparison with two conventional PCA-based contribution plots are presented to demonstrate the effectiveness of the proposed methodology. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Full-color digitized holography for large-scale holographic 3D imaging of physical and nonphysical objects.

PubMed

Matsushima, Kyoji; Sonobe, Noriaki

2018-01-01

Digitized holography techniques are used to reconstruct three-dimensional (3D) images of physical objects using large-scale computer-generated holograms (CGHs). The object field is captured at three wavelengths over a wide area at high densities. Synthetic aperture techniques using single sensors are used for image capture in phase-shifting digital holography. The captured object field is incorporated into a virtual 3D scene that includes nonphysical objects, e.g., polygon-meshed CG models. The synthetic object field is optically reconstructed as a large-scale full-color CGH using red-green-blue color filters. The CGH has a wide full-parallax viewing zone and reconstructs a deep 3D scene with natural motion parallax.

Guided growth of large-scale, horizontally aligned arrays of single-walled carbon nanotubes and their use in thin-film transistors.

PubMed

Kocabas, Coskun; Hur, Seung-Hyun; Gaur, Anshu; Meitl, Matthew A; Shim, Moonsub; Rogers, John A

2005-11-01

A convenient process for generating large-scale, horizontally aligned arrays of pristine, single-walled carbon nanotubes (SWNTs) is described. The approach uses guided growth, by chemical vapor deposition (CVD), of SWNTs on miscut single-crystal quartz substrates. Studies of the growth reveal important relationships between the density and alignment of the tubes, the CVD conditions, and the morphology of the quartz. Electrodes and dielectrics patterned on top of these arrays yield thin-film transistors that use the SWNTs as effective thin-film semiconductors. The ability to build high-performance devices of this type suggests significant promise for large-scale aligned arrays of SWNTs in electronics, sensors, and other applications.

Monitoring water use and crop condition in California vineyards at multiple scales using multi-sensor satellite data fusion

USDA-ARS?s Scientific Manuscript database

Recent weather patterns have left California’s agricultural areas in severe drought. Given the reduced water availability in much of California it is critical to be able to measure water use and crop condition over large areas, but also in fine detail at scales of individual fields to support water...

Satellite-based characterization of climatic conditions before large-scale general flowering events in Peninsular Malaysia

PubMed Central

Azmy, Muna Maryam; Hashim, Mazlan; Numata, Shinya; Hosaka, Tetsuro; Noor, Nur Supardi Md.; Fletcher, Christine

2016-01-01

General flowering (GF) is a unique phenomenon wherein, at irregular intervals, taxonomically diverse trees in Southeast Asian dipterocarp forests synchronize their reproduction at the community level. Triggers of GF, including drought and low minimum temperatures a few months previously has been limitedly observed across large regional scales due to lack of meteorological stations. Here, we aim to identify the climatic conditions that trigger large-scale GF in Peninsular Malaysia using satellite sensors, Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), to evaluate the climatic conditions of focal forests. We observed antecedent drought, low temperature and high photosynthetic radiation conditions before large-scale GF events, suggesting that large-scale GF events could be triggered by these factors. In contrast, we found higher-magnitude GF in forests where lower precipitation preceded large-scale GF events. GF magnitude was also negatively influenced by land surface temperature (LST) for a large-scale GF event. Therefore, we suggest that spatial extent of drought may be related to that of GF forests, and that the spatial pattern of LST may be related to that of GF occurrence. With significant new findings and other results that were consistent with previous research we clarified complicated environmental correlates with the GF phenomenon. PMID:27561887

Satellite-based characterization of climatic conditions before large-scale general flowering events in Peninsular Malaysia.

PubMed

Azmy, Muna Maryam; Hashim, Mazlan; Numata, Shinya; Hosaka, Tetsuro; Noor, Nur Supardi Md; Fletcher, Christine

2016-08-26

General flowering (GF) is a unique phenomenon wherein, at irregular intervals, taxonomically diverse trees in Southeast Asian dipterocarp forests synchronize their reproduction at the community level. Triggers of GF, including drought and low minimum temperatures a few months previously has been limitedly observed across large regional scales due to lack of meteorological stations. Here, we aim to identify the climatic conditions that trigger large-scale GF in Peninsular Malaysia using satellite sensors, Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), to evaluate the climatic conditions of focal forests. We observed antecedent drought, low temperature and high photosynthetic radiation conditions before large-scale GF events, suggesting that large-scale GF events could be triggered by these factors. In contrast, we found higher-magnitude GF in forests where lower precipitation preceded large-scale GF events. GF magnitude was also negatively influenced by land surface temperature (LST) for a large-scale GF event. Therefore, we suggest that spatial extent of drought may be related to that of GF forests, and that the spatial pattern of LST may be related to that of GF occurrence. With significant new findings and other results that were consistent with previous research we clarified complicated environmental correlates with the GF phenomenon.

Cascading failure in the wireless sensor scale-free networks

NASA Astrophysics Data System (ADS)

Liu, Hao-Ran; Dong, Ming-Ru; Yin, Rong-Rong; Han, Li

2015-05-01

In the practical wireless sensor networks (WSNs), the cascading failure caused by a failure node has serious impact on the network performance. In this paper, we deeply research the cascading failure of scale-free topology in WSNs. Firstly, a cascading failure model for scale-free topology in WSNs is studied. Through analyzing the influence of the node load on cascading failure, the critical load triggering large-scale cascading failure is obtained. Then based on the critical load, a control method for cascading failure is presented. In addition, the simulation experiments are performed to validate the effectiveness of the control method. The results show that the control method can effectively prevent cascading failure. Project supported by the Natural Science Foundation of Hebei Province, China (Grant No. F2014203239), the Autonomous Research Fund of Young Teacher in Yanshan University (Grant No. 14LGB017) and Yanshan University Doctoral Foundation, China (Grant No. B867).

Mapping of the Resistance of a Superconducting Transition Edge Sensor as a Function of Temperature, Current, and Applied Magnetic Field

NASA Technical Reports Server (NTRS)

Zhang, Shou; Eckart, Megan E.; Jaeckel, Felix; Kripps, Kari L.; McCammon, Dan; Zhou, Yu; Morgan, Kelsey M.

2017-01-01

We have measured the resistance R (T, I, B(sub ext) of a superconducting transition edge sensor over the entire transition region on a fine scale, producing a four-dimensional map of the resistance surface. The dimensionless temperature and current sensitivities (alpha equivalence partial derivative log R/partial derivative log T|(sub I) and beta equivalence partial derivative log R/partial derivative log I|(sub T) of the TES resistance have been determined at each point. alpha and beta are closely related to the sensor performance, but show a great deal of complex, large amplitude fine structure over large portions of the surface that is sensitive to the applied magnetic field. We discuss the relation of this structure to the presence of Josephson weak link fringes.

Heterogeneous collaborative sensor network for electrical management of an automated house with PV energy.

PubMed

Castillo-Cagigal, Manuel; Matallanas, Eduardo; Gutiérrez, Alvaro; Monasterio-Huelin, Félix; Caamaño-Martín, Estefaná; Masa-Bote, Daniel; Jiménez-Leube, Javier

2011-01-01

In this paper we present a heterogeneous collaborative sensor network for electrical management in the residential sector. Improving demand-side management is very important in distributed energy generation applications. Sensing and control are the foundations of the "Smart Grid" which is the future of large-scale energy management. The system presented in this paper has been developed on a self-sufficient solar house called "MagicBox" equipped with grid connection, PV generation, lead-acid batteries, controllable appliances and smart metering. Therefore, there is a large number of energy variables to be monitored that allow us to precisely manage the energy performance of the house by means of collaborative sensors. The experimental results, performed on a real house, demonstrate the feasibility of the proposed collaborative system to reduce the consumption of electrical power and to increase energy efficiency.

Wafer-scale epitaxial graphene on SiC for sensing applications

NASA Astrophysics Data System (ADS)

Karlsson, Mikael; Wang, Qin; Zhao, Yichen; Zhao, Wei; Toprak, Muhammet S.; Iakimov, Tihomir; Ali, Amer; Yakimova, Rositza; Syväjärvi, Mikael; Ivanov, Ivan G.

2015-12-01

The epitaxial graphene-on-silicon carbide (SiC-G) has advantages of high quality and large area coverage owing to a natural interface between graphene and SiC substrate with dimension up to 100 mm. It enables cost effective and reliable solutions for bridging the graphene-based sensors/devices from lab to industrial applications and commercialization. In this work, the structural, optical and electrical properties of wafer-scale graphene grown on 2'' 4H semi-insulating (SI) SiC utilizing sublimation process were systemically investigated with focus on evaluation of the graphene's uniformity across the wafer. As proof of concept, two types of glucose sensors based on SiC-G/Nafion/Glucose-oxidase (GOx) and SiC-G/Nafion/Chitosan/GOx were fabricated and their electrochemical properties were characterized by cyclic voltammetry (CV) measurements. In addition, a few similar glucose sensors based on graphene by chemical synthesis using modified Hummer's method were also fabricated for comparison.

A pH-responsive molecular switch with tricolor luminescence.

PubMed

Ahn, Hyungmin; Hong, Jaewan; Kim, Sung Yeon; Choi, Ilyoung; Park, Moon Jeong

2015-01-14

We developed a new ratiometric pH sensor based on poly(N-phenylmaleimide) (PPMI)-containing block copolymer that emits three different fluorescent colors depending on the pH. The strong solvatochromism and tautomerism of the PPMI derivatives enabled precise pH sensing for almost the entire range of the pH scale. Theoretical calculations have predicted largely dissimilar band gaps for the keto, enol, and enolate tautomers of PPMI owing to low-dimensional conjugation effects. The tunable emission wavelength and intensity of our sensors, as well as the reversible color switching with high-luminescent contrast, were achieved using rational molecular design of PPMI analogues as an innovative platform for accurate H(+) detection. The self-assembly of block copolymers on the nanometer length scale was particularly highlighted as a novel prospective means of regulating fluorescence properties while avoiding the self-quenching phenomenon, and this system can be used as a fast responsive pH sensor in versatile device forms.

Micro-sensors for in-situ meteorological measurements

NASA Technical Reports Server (NTRS)

Crisp, David; Kaiser, William J.; Vanzandt, Thomas R.; Tillman, James E.

1993-01-01

Improved in-situ meteorological measurements are needed for monitoring the weather and climate of the terrestrial and Martian atmospheres. We have initiated a program to assess the feasibility and utility of micro-sensors for precise in-situ meteorological measurements in these environments. Sensors are being developed for measuring pressure, temperature, wind velocity, humidity, and aerosol amounts. Silicon micro-machining and large scale integration technologies are being used to make sensors that are small, rugged, lightweight, and require very little power. Our long-term goal is to develop very accurate miniaturized sensors that can be incorporated into complete instrument packages or 'micro weather stations,' and deployed on a variety of platforms. If conventional commercially available silicon production techniques can be used to fabricate these sensor packages, it will eventually be possible to mass-produce them at low cost. For studies of the Earth's troposphere and stratosphere, they could be deployed on aircraft, dropsondes, radiosondes, or autonomous surface stations at remote sites. Improved sensor accuracy and reduced sensor cost are the primary challenges for these applications. For studies of the Martian atmosphere, these sensor packages could be incorporated into the small entry probes and surface landers that are being planned for the Mars Environmental SURvey (MESUR) Mission. That decade-long program will deploy a global network of small stations on the Martian surface for monitoring meteorological and geological processes. Low mass, low power, durability, large dynamic range and calibration stability are the principal challenges for this application. Our progress on each of these sensor types is presented.

Large-scale Estimates of Leaf Area Index from Active Remote Sensing Laser Altimetry

NASA Astrophysics Data System (ADS)

Hopkinson, C.; Mahoney, C.

2016-12-01

Leaf area index (LAI) is a key parameter that describes the spatial distribution of foliage within forest canopies which in turn control numerous relationships between the ground, canopy, and atmosphere. The retrieval of LAI has demonstrated success by in-situ (digital) hemispherical photography (DHP) and airborne laser scanning (ALS) data; however, field and ALS acquisitions are often spatially limited (100's km2) and costly. Large-scale (>1000's km2) retrievals have been demonstrated by optical sensors, however, accuracies remain uncertain due to the sensor's inability to penetrate the canopy. The spaceborne Geoscience Laser Altimeter System (GLAS) provides a possible solution in retrieving large-scale derivations whilst simultaneously penetrating the canopy. LAI retrieved by multiple DHP from 6 Australian sites, representing a cross-section of Australian ecosystems, were employed to model ALS LAI, which in turn were used to infer LAI from GLAS data at 5 other sites. An optimally filtered GLAS dataset was then employed in conjunction with a host of supplementary data to build a Random Forest (RF) model to infer predictions (and uncertainties) of LAI at a 250 m resolution across the forested regions of Australia. Predictions were validated against ALS-based LAI from 20 sites (R2=0.64, RMSE=1.1 m2m-2); MODIS-based LAI were also assessed against these sites (R2=0.30, RMSE=1.78 m2m-2) to demonstrate the strength of GLAS-based predictions. The large-scale nature of current predictions was also leveraged to demonstrate large-scale relationships of LAI with other environmental characteristics, such as: canopy height, elevation, and slope. The need for such wide-scale quantification of LAI is key in the assessment and modification of forest management strategies across Australia. Such work also assists Australia's Terrestrial Ecosystem Research Network, in fulfilling their government issued mandates.

Low power sensor network for wireless condition monitoring

NASA Astrophysics Data System (ADS)

Richter, Ch.; Frankenstein, B.; Schubert, L.; Weihnacht, B.; Friedmann, H.; Ebert, C.

2009-03-01

For comprehensive fatigue tests and surveillance of large scale structures, a vibration monitoring system working in the Hz and sub Hz frequency range was realized and tested. The system is based on a wireless sensor network and focuses especially on the realization of a low power measurement, signal processing and communication. Regarding the development, we met the challenge of synchronizing the wireless connected sensor nodes with sufficient accuracy. The sensor nodes ware realized by compact, sensor near signal processing structures containing components for analog preprocessing of acoustic signals, their digitization, algorithms for data reduction and network communication. The core component is a digital micro controller which performs the basic algorithms necessary for the data acquisition synchronization and the filtering. As a first application, the system was installed in a rotor blade of a wind power turbine in order to monitor the Eigen modes over a longer period of time. Currently the sensor nodes are battery powered.

In-situ Monitoring of Internal Local Temperature and Voltage of Proton Exchange Membrane Fuel Cells

PubMed Central

Lee, Chi-Yuan; Fan, Wei-Yuan; Hsieh, Wei-Jung

2010-01-01

The distribution of temperature and voltage of a fuel cell are key factors that influence performance. Conventional sensors are normally large, and are also useful only for making external measurements of fuel cells. Centimeter-scale sensors for making invasive measurements are frequently unable to accurately measure the interior changes of a fuel cell. This work focuses mainly on fabricating flexible multi-functional microsensors (for temperature and voltage) to measure variations in the local temperature and voltage of proton exchange membrane fuel cells (PEMFC) that are based on micro-electro-mechanical systems (MEMS). The power density at 0.5 V without a sensor is 450 mW/cm2, and that with a sensor is 426 mW/cm2. Since the reaction area of a fuel cell with a sensor is approximately 12% smaller than that without a sensor, but the performance of the former is only 5% worse. PMID:22163556

In-situ monitoring of internal local temperature and voltage of proton exchange membrane fuel cells.

PubMed

Lee, Chi-Yuan; Fan, Wei-Yuan; Hsieh, Wei-Jung

2010-01-01

The distribution of temperature and voltage of a fuel cell are key factors that influence performance. Conventional sensors are normally large, and are also useful only for making external measurements of fuel cells. Centimeter-scale sensors for making invasive measurements are frequently unable to accurately measure the interior changes of a fuel cell. This work focuses mainly on fabricating flexible multi-functional microsensors (for temperature and voltage) to measure variations in the local temperature and voltage of proton exchange membrane fuel cells (PEMFC) that are based on micro-electro-mechanical systems (MEMS). The power density at 0.5 V without a sensor is 450 mW/cm(2), and that with a sensor is 426 mW/cm(2). Since the reaction area of a fuel cell with a sensor is approximately 12% smaller than that without a sensor, but the performance of the former is only 5% worse.

Low-Power, Chip-Scale, Carbon Dioxide Gas Sensors for Spacesuit Monitoring

NASA Technical Reports Server (NTRS)

Rani, Asha; Shi, Chen; Thomson, Brian; Debnath, Ratan; Wen, Boamei; Motayed, Abhishek; Chullen, Cinda

2018-01-01

N5 Sensors, Inc. through a Small Business Technology Transfer (STTR) contract award has been developing ultra-small, low-power carbon dioxide (CO2) gas sensors, suited for monitoring CO2 levels inside NASA spacesuits. Due to the unique environmental conditions within the spacesuits, such as high humidity, large temperature swings, and operating pressure swings, measurement of key gases relevant to astronaut's safety and health such as(CO2), is quite challenging. Conventional non-dispersive infrared absorption based CO2 sensors present challenges inside the spacesuits due to size, weight, and power constraints, along with the ability to sense CO2 in a high humidity environment. Unique chip-scale, nanoengineered chemiresistive gas-sensing architecture has been developed for this application, which can be operated in a typical space-suite environmental conditions. Unique design combining the selective adsorption properties of the nanophotocatalytic clusters of metal-oxides and metals, provides selective detection of CO2 in high relative humidity conditions. All electronic design provides a compact and low-power solution, which can be implemented for multipoint detection of CO2 inside the spacesuits. This paper will describe the sensor architecture, development of new photocatalytic material for better sensor response, and advanced structure for better sensitivity and shorter response times.

Integrated monitoring of wind plant systems

NASA Astrophysics Data System (ADS)

Whelan, Matthew J.; Janoyan, Kerop D.; Qiu, Tong

2008-03-01

Wind power is a renewable source of energy that is quickly gaining acceptance by many. Advanced sensor technologies have currently focused solely on improving wind turbine rotor aerodynamics and increasing of the efficiency of the blade design and concentration. Alternatively, potential improvements in wind plant efficiency may be realized through reduction of reactionary losses of kinetic energy to the structural and substructural systems supporting the turbine mechanics. Investigation of the complete dynamic structural response of the wind plant is proposed using a large-scale, high-rate wireless sensor network. The wireless network enables sensors to be placed across the sizable structure, including the rotating blades, without consideration of cabling issues and the economic burden associated with large spools of measurement cables. A large array of multi-axis accelerometers is utilized to evaluate the modal properties of the system as well as individual members and would enable long-term structural condition monitoring of the wind turbine as well. Additionally, environmental parameters, including wind speed, temperature, and humidity, are wirelessly collected for correlation. Such a wireless system could be integrated with electrical monitoring sensors and actuators and incorporated into a remote multi-turbine centralized plant monitoring and control system.

Effect of thermal stability/complex terrain on wind turbine model(s): a wind tunnel study to address complex atmospheric conditions

NASA Astrophysics Data System (ADS)

Guala, M.; Hu, S. J.; Chamorro, L. P.

2011-12-01

Turbulent boundary layer measurements in both wind tunnel and in the near-neutral atmospheric surface layer revealed in the last decade the significant contribution of the large scales of motions to both turbulent kinetic energy and Reynolds stresses, for a wide range of Reynolds number. These scales are known to grow throughout the logarithmic layer and to extend several boundary layer heights in the streamwise direction. Potentially, they are a source of strong unsteadiness in the power output of wind turbines and in the aerodynamic loads of wind turbine blades. However, the large scales in realistic atmospheric conditions deserves further study, with well controlled boundary conditions. In the atmospheric wind tunnel of the St. Anthony Falls Laboratory, with a 16 m long test section and independently controlled incoming flow and floor temperatures, turbulent boundary layers in a range of stability conditions, from the stratified to the convective case, can be reproduced and monitored. Measurements of fluctuating temperature, streamwise and wall normal velocity components are simultaneously obtained by an ad hoc calibrated and customized triple-wire sensor. A wind turbine model with constant loading DC motor, constant tip speed ratio, and a rotor diameter of 0.128m is used to mimic a large full scale turbine in the atmospheric boundary layer. Measurements of the fluctuating voltage generated by the DC motor are compared with measurements of the blade's angular velocity by laser scanning, and eventually related to velocity measurements from the triple-wire sensor. This study preliminary explores the effect of weak stability and complex terrain (through a set of spanwise aligned topographic perturbations) on the large scales of the flow and on the fluctuations in the wind turbine(s) power output.

Research on a Novel Low Modulus OFBG Strain Sensor for Pavement Monitoring

PubMed Central

Wang, Chuan; Hu, Qingli; Lu, Qiyu

2012-01-01

Because of the fatigue and deflection damage of asphalt pavement, it is very important for researchers to monitor the strain response of asphalt layers in service under vehicle loads, so in this paper a novel polypropylene based OFBG (Optical Fiber Bragg Gratings) strain sensor with low modulus and large strain sensing scale was designed and fabricated. PP with MA-G-PP is used to package OFBG. The fabrication techniques, the physical properties and the sensing properties were tested. The experimental results show that this kind of new OFBG strain sensor is a wonderful sensor with low modulus (about 1 GPa) and good sensitivity, which would meet the needs for monitoring some low modulus materials or structures. PMID:23112584

Integration of Metal Oxide Nanowires in Flexible Gas Sensing Devices

PubMed Central

Comini, Elisabetta

2013-01-01

Metal oxide nanowires are very promising active materials for different applications, especially in the field of gas sensors. Advances in fabrication technologies now allow the preparation of nanowires on flexible substrates, expanding the potential market of the resulting sensors. The critical steps for the large-scale preparation of reliable sensing devices are the elimination of high temperatures processes and the stretchability of the entire final device, including the active material. Direct growth on flexible substrates and post-growth procedures have been successfully used for the preparation of gas sensors. The paper will summarize the procedures used for the preparation of flexible and wearable gas sensors prototypes with an overlook of the challenges and the future perspectives concerning this field. PMID:23955436

Superconducting Detector Arrays for Astrophysics

NASA Technical Reports Server (NTRS)

Chervenak, James

2008-01-01

The next generation of astrophysics instruments will feature an order of magnitude more photon sensors or sensors that have an order of magnitude greater sensitivity. Since detector noise scales with temperature, a number of candidate technologies have been developed that use the intrinsic advantages of detector systems that operate below 1 Kelvin. Many of these systems employ of the superconducting phenomena that occur in metals at these temperatures to build ultrasensitive detectors and low-noise, low-power readout architectures. I will present one such system in use today to meet the needs of the astrophysics community at millimeter and x-ray wavelengths. Our group at NASA in collaboration with Princeton, NIST, Boulder and a number of other groups is building large format arrays of superconducting transition edge sensors (TES) read out with multiplexed superconducting quantum interference devices (SQUID). I will present the high sensitivity we have achieved in multiplexed x-ray sensors with the TES technology and describe the construction of a 1000-sensor TES/SQUID array for microwave measurements. With our collaboration's deployment of a kilopixel TES array for 2 mm radiation at the Atacarna Cosmology Telescope in November 2007, we have first images of the lensed Cosmic Microwave Background at fine angular scales.

Distributed resource allocation under communication constraints

NASA Astrophysics Data System (ADS)

Dodin, Pierre; Nimier, Vincent

2001-03-01

This paper deals with a study of the multi-sensor management problem for multi-target tracking. The collaboration between many sensors observing the same target means that they are able to fuse their data during the information process. Then one must take into account this possibility to compute the optimal association sensors-target at each step of time. In order to solve this problem for real large scale system, one must both consider the information aspect and the control aspect of the problem. To unify these problems, one possibility is to use a decentralized filtering algorithm locally driven by an assignment algorithm. The decentralized filtering algorithm we use in our model is the filtering algorithm of Grime, which relaxes the usual full-connected hypothesis. By full-connected, one means that the information in a full-connected system is totally distributed everywhere at the same moment, which is unacceptable for a real large scale system. We modelize the distributed assignment decision with the help of a greedy algorithm. Each sensor performs a global optimization, in order to estimate other information sets. A consequence of the relaxation of the full- connected hypothesis is that the sensors' information set are not the same at each step of time, producing an information dis- symmetry in the system. The assignment algorithm uses a local knowledge of this dis-symmetry. By testing the reactions and the coherence of the local assignment decisions of our system, against maneuvering targets, we show that it is still possible to manage with decentralized assignment control even though the system is not full-connected.

Exploring Google Earth Engine platform for big data processing: classification of multi-temporal satellite imagery for crop mapping

NASA Astrophysics Data System (ADS)

Shelestov, Andrii; Lavreniuk, Mykola; Kussul, Nataliia; Novikov, Alexei; Skakun, Sergii

2017-02-01

Many applied problems arising in agricultural monitoring and food security require reliable crop maps at national or global scale. Large scale crop mapping requires processing and management of large amount of heterogeneous satellite imagery acquired by various sensors that consequently leads to a “Big Data” problem. The main objective of this study is to explore efficiency of using the Google Earth Engine (GEE) platform when classifying multi-temporal satellite imagery with potential to apply the platform for a larger scale (e.g. country level) and multiple sensors (e.g. Landsat-8 and Sentinel-2). In particular, multiple state-of-the-art classifiers available in the GEE platform are compared to produce a high resolution (30 m) crop classification map for a large territory ( 28,100 km2 and 1.0 M ha of cropland). Though this study does not involve large volumes of data, it does address efficiency of the GEE platform to effectively execute complex workflows of satellite data processing required with large scale applications such as crop mapping. The study discusses strengths and weaknesses of classifiers, assesses accuracies that can be achieved with different classifiers for the Ukrainian landscape, and compares them to the benchmark classifier using a neural network approach that was developed in our previous studies. The study is carried out for the Joint Experiment of Crop Assessment and Monitoring (JECAM) test site in Ukraine covering the Kyiv region (North of Ukraine) in 2013. We found that Google Earth Engine (GEE) provides very good performance in terms of enabling access to the remote sensing products through the cloud platform and providing pre-processing; however, in terms of classification accuracy, the neural network based approach outperformed support vector machine (SVM), decision tree and random forest classifiers available in GEE.

Using Accelerometers to Measure Physical Activity in Large-Scale Epidemiologic Studies: Issues and Challenges

PubMed Central

Lee, I-Min; Shiroma, Eric J

2013-01-01

Background Current guidelines for aerobic activity require that adults carry out ≥150 minutes/week of moderate-intensity physical activity, with a large body of epidemiologic evidence showing this level of activity to decrease the incidence of many chronic diseases. Less is known about whether light-intensity activities also have such benefits, and whether sedentary behavior is an independent predictor of increased risks of these chronic diseases, as imprecise assessments of these behaviours and cross-sectional study designs have limited knowledge to date. Methods Recent technological advances in assessment methods have made the use of movement sensors, such as the accelerometer, feasible for use in longitudinal, large-scale epidemiologic studies. Several such studies are collecting sensor-assessed, objective measures of physical activity with the aim of relating these to the development of clinical endpoints. This is a relatively new area of research; thus, in this paper, we use the Women’s Health Study (WHS) as a case study to illustrate challenges related to data collection, data processing, and analyses of the vast amount of data collected. Results The WHS plans to collect 7 days of accelerometer-assessed physical activity and sedentary behavior in ~18,000 women aged ≥62 years. Several logistical challenges exist in collecting data; nonetheless as of 31 August 2013, 11,590 women have already provided some data. Additionally, the WHS experience on data reduction and data analyses can help inform other similar large-scale epidemiologic studies. Conclusions Important data on the health effects of light-intensity activity and sedentary behaviour will emerge from large-scale epidemiologic studies collecting objective assessments of these behaviours. PMID:24297837

Scalable sensor management for automated fusion and tactical reconnaissance

NASA Astrophysics Data System (ADS)

Walls, Thomas J.; Wilson, Michael L.; Partridge, Darin C.; Haws, Jonathan R.; Jensen, Mark D.; Johnson, Troy R.; Petersen, Brad D.; Sullivan, Stephanie W.

2013-05-01

The capabilities of tactical intelligence, surveillance, and reconnaissance (ISR) payloads are expanding from single sensor imagers to integrated systems-of-systems architectures. Increasingly, these systems-of-systems include multiple sensing modalities that can act as force multipliers for the intelligence analyst. Currently, the separate sensing modalities operate largely independent of one another, providing a selection of operating modes but not an integrated intelligence product. We describe here a Sensor Management System (SMS) designed to provide a small, compact processing unit capable of managing multiple collaborative sensor systems on-board an aircraft. Its purpose is to increase sensor cooperation and collaboration to achieve intelligent data collection and exploitation. The SMS architecture is designed to be largely sensor and data agnostic and provide flexible networked access for both data providers and data consumers. It supports pre-planned and ad-hoc missions, with provisions for on-demand tasking and updates from users connected via data links. Management of sensors and user agents takes place over standard network protocols such that any number and combination of sensors and user agents, either on the local network or connected via data link, can register with the SMS at any time during the mission. The SMS provides control over sensor data collection to handle logging and routing of data products to subscribing user agents. It also supports the addition of algorithmic data processing agents for feature/target extraction and provides for subsequent cueing from one sensor to another. The SMS architecture was designed to scale from a small UAV carrying a limited number of payloads to an aircraft carrying a large number of payloads. The SMS system is STANAG 4575 compliant as a removable memory module (RMM) and can act as a vehicle specific module (VSM) to provide STANAG 4586 compliance (level-3 interoperability) to a non-compliant sensor system. The SMS architecture will be described and results from several flight tests and simulations will be shown.

Air Pollution Monitoring and Mining Based on Sensor Grid in London

PubMed Central

Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John

2008-01-01

In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a two-layer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm. PMID:27879895

Multi-Stress Monitoring System with Fiber-Optic Mandrels and Fiber Bragg Grating Sensors in a Sagnac Loop

PubMed Central

Kim, Hyunjin; Sampath, Umesh; Song, Minho

2015-01-01

Fiber Bragg grating sensors are placed in a fiber-optic Sagnac loop to combine the grating temperature sensors and the fiber-optic mandrel acoustic emission sensors in single optical circuit. A wavelength-scanning fiber-optic laser is used as a common light source for both sensors. A fiber-optic attenuator is placed at a specific position in the Sagnac loop in order to separate buried Bragg wavelengths from the Sagnac interferometer output. The Bragg wavelength shifts are measured with scanning band-pass filter demodulation and the mandrel output is analyzed by applying a fast Fourier transform to the interference signal. This hybrid-scheme could greatly reduce the size and the complexity of optical circuitry and signal processing unit, making it suitable for low cost multi-stress monitoring of large scale power systems. PMID:26230700

A fiber Bragg grating acceleration sensor for ground surveillance

NASA Astrophysics Data System (ADS)

Jiang, Shaodong; Zhang, Faxiang; Lv, Jingsheng; Ni, Jiasheng; Wang, Chang

2017-10-01

Ground surveillance system is a kind of intelligent monitoring equipment for detecting and tracking the ground target. This paper presents a fiber Bragg grating (FBG) acceleration sensor for ground surveillance, which has the characteristics of no power supply, anti-electromagnetic interference, easy large-scale networking, and small size. Which make it able to achieve the advantage of the ground surveillance system while avoiding the shortcoming of the electric sensing. The sensor has a double cantilever beam structure with a sensitivity of 1000 pm/g. Field experiment has been carried out on a flood beach to examine the sensor performance. The result shows that the detection distance on the walking of personnel reaches 70m, and the detection distance on the ordinary motor vehicle reaches 200m. The performance of the FBG sensor can satisfy the actual needs of the ground surveillance system.

Air Pollution Monitoring and Mining Based on Sensor Grid in London.

PubMed

Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John

2008-06-01

In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a twolayer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm.

Proceedings of the Aircraft Wake Vortices Conference Held in Washington, DC on October 29 - 31, 1991. Volume 1, Papers 1-29.

DTIC Science & Technology

1992-06-01

Large scale data collection activities began with the installation of several sensor systems at the John F. Kennedy International Airport ( JFK ) in June... airport in 1989 (Figure 2). It assists the controllers in the management of the arrival traffic by the provision of an optimized plan for the incoming...Vzf t GOAL ---- > MINIMIZE jVref -Vesti BY OPTIMIZING SENSOR PARAMETERS AND TAKING IN ACCOUNT CUMBERNESS AND ENVIRONMENTAL CONSTRAINTS AIRPORT TESTS

All-Digital Time-Domain CMOS Smart Temperature Sensor with On-Chip Linearity Enhancement.

PubMed

Chen, Chun-Chi; Chen, Chao-Lieh; Lin, Yi

2016-01-30

This paper proposes the first all-digital on-chip linearity enhancement technique for improving the accuracy of the time-domain complementary metal-oxide semiconductor (CMOS) smart temperature sensor. To facilitate on-chip application and intellectual property reuse, an all-digital time-domain smart temperature sensor was implemented using 90 nm Field Programmable Gate Arrays (FPGAs). Although the inverter-based temperature sensor has a smaller circuit area and lower complexity, two-point calibration must be used to achieve an acceptable inaccuracy. With the help of a calibration circuit, the influence of process variations was reduced greatly for one-point calibration support, reducing the test costs and time. However, the sensor response still exhibited a large curvature, which substantially affected the accuracy of the sensor. Thus, an on-chip linearity-enhanced circuit is proposed to linearize the curve and achieve a new linearity-enhanced output. The sensor was implemented on eight different Xilinx FPGA using 118 slices per sensor in each FPGA to demonstrate the benefits of the linearization. Compared with the unlinearized version, the maximal inaccuracy of the linearized version decreased from 5 °C to 2.5 °C after one-point calibration in a range of -20 °C to 100 °C. The sensor consumed 95 μW using 1 kSa/s. The proposed linearity enhancement technique significantly improves temperature sensing accuracy, avoiding costly curvature compensation while it is fully synthesizable for future Very Large Scale Integration (VLSI) system.

All-Digital Time-Domain CMOS Smart Temperature Sensor with On-Chip Linearity Enhancement

PubMed Central

Chen, Chun-Chi; Chen, Chao-Lieh; Lin, Yi

2016-01-01

This paper proposes the first all-digital on-chip linearity enhancement technique for improving the accuracy of the time-domain complementary metal-oxide semiconductor (CMOS) smart temperature sensor. To facilitate on-chip application and intellectual property reuse, an all-digital time-domain smart temperature sensor was implemented using 90 nm Field Programmable Gate Arrays (FPGAs). Although the inverter-based temperature sensor has a smaller circuit area and lower complexity, two-point calibration must be used to achieve an acceptable inaccuracy. With the help of a calibration circuit, the influence of process variations was reduced greatly for one-point calibration support, reducing the test costs and time. However, the sensor response still exhibited a large curvature, which substantially affected the accuracy of the sensor. Thus, an on-chip linearity-enhanced circuit is proposed to linearize the curve and achieve a new linearity-enhanced output. The sensor was implemented on eight different Xilinx FPGA using 118 slices per sensor in each FPGA to demonstrate the benefits of the linearization. Compared with the unlinearized version, the maximal inaccuracy of the linearized version decreased from 5 °C to 2.5 °C after one-point calibration in a range of −20 °C to 100 °C. The sensor consumed 95 μW using 1 kSa/s. The proposed linearity enhancement technique significantly improves temperature sensing accuracy, avoiding costly curvature compensation while it is fully synthesizable for future Very Large Scale Integration (VLSI) system. PMID:26840316

Laureates

Science.gov Websites

, multi-scale observing systems under challenging field conditions to document unexpectedly large soil CO2 pleased to recognize the Building Technology and Urban Systems Division's Retro-commissioning Sensor synthetic biology while providing novel approaches for crop engineering to support Berkeley Lab and DOE's

Sensor Network Demonstration for In Situ Decommissioning - 13332

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lagos, L.; Varona, J.; Awwad, A.

2013-07-01

Florida International University's (FIU's) Applied Research Center is currently supporting the Department of Energy's (DOE) Environmental Management Office of D and D and Facility Engineering program. FIU is supporting DOE's initiative to improve safety, reduce technical risks, and limit uncertainty within D and D operations by identifying technologies suitable to meet specific facility D and D requirements, assessing the readiness of those technologies for field deployment, and conducting feasibility studies and large scale demonstrations of promising technologies. During FY11, FIU collaborated with Savannah River National Laboratory in the development of an experimental test site for the demonstration of multiple sensormore » systems for potential use in the in situ decommissioning process. In situ decommissioning is a process in which the above ground portion of a facility is dismantled and removed, and the underground portion is filled with a cementious material such as grout. In such a scenario, the question remains on how to effectively monitor the structural health of the grout (cracking, flexing, and sinking), as well as track possible migration of contaminants within and out of the grouted monolith. The right types of sensors can aid personnel in better understanding the conditions within the entombed structure. Without sensors embedded in and around the monolith, it will be very difficult to estimate structural integrity and contaminant transport. Yet, to fully utilize the appropriate sensors and the provided data, their performance and reliability must be evaluated outside a laboratory setting. To this end, a large scale experimental setup and demonstration was conducted at FIU. In order to evaluate a large suite of sensor systems, FIU personnel designed and purchased a pre-cast concrete open-top cube, which served as a mock-up of an in situ DOE decommissioned facility. The inside of the cube measures 10 ft x 10 ft x 8 ft. In order to ensure that the individual sensors would be immobilized during the grout pouring activities, a set of nine sensor racks were designed. The 270 sensors provided by Idaho National Laboratory (INL), Mississippi State University (MSU), University of Houston (UH), and University of South Carolina (USC) were secured to these racks based on predetermined locations. Once sensor racks were installed inside the test cube, connected and debugged, approximately 32 cubic yards of special grout material was used to entomb the sensors. MSU provided and demonstrated four types of fiber loop ring-down (FLR) sensors for detection of water, temperature, cracks, and movement of fluids. INL provided and demonstrated time differenced 3D electrical resistivity tomography (ERT), advanced tensiometers for moisture content, and thermocouples for temperature measurements. University of Houston provided smart aggregate (SA) sensors, which detect crack severity and water presence. An additional UH sensor system demonstrated was a Fiber Bragg Grating (FBG) fiber optic system measuring strain, presence of water, and temperature. USC provided a system which measured acoustic emissions during cracking, as well as temperature and pH sensors. All systems were connected to a Sensor Remote Access System (SRAS) data networking and collection system designed, developed and provided by FIU. The purpose of SRAS was to collect and allow download of the raw sensor data from all the sensor system, as well as allow upload of the processed data and any analysis reports and graphs. All this information was made available to the research teams via the Deactivation and Decommissioning Knowledge Management and Information Tool (D and D KM-IT). As a current research effort, FIU is performing an energy analysis, and transferring several sensor systems to a Photovoltaic (PV) System to continuously monitor energy consumption parameters and overall power demands. Also, One final component of this research is focusing on developing an integrated data network to capture, log and analyze sensor system data in near real time from a single interface. FIU personnel and DOE Fellows monitored the progress and condition of the sensors for a period of six months. During this time, the sensors recorded data pertaining to strain, compression, temperature, crack detection, moisture presence, fluid mobility, shock resistance, monolith movement, and electrical resistivity. In addition, FIU regularly observed the curing process of the grout and documented the cube condition via the nine racks of sensors. The sensors held up throughout the curing process, withstood the natural elements for six months, and monitored the integrity of the grout. The large scale experiment and demonstration conducted at FIU was the first of its kind to demonstrate the feasibility of state of the art sensors for in situ decommissioning applications. These efforts successfully measured the durability, performance, and precision of the sensors in question as well as monitored and recorded the curing process of the selected grout material under natural environmental conditions. The current energy analysis work is resulting in data on the constraints placed by some of the sensor systems on a power network that requires high reliability and low losses. In addition, a sensor system demonstration has determined that it is feasible to develop an integrated data network where data can be accessed in near real-time from all systems, thereby allowing for larger-scale integrated system testing to be performed. Information collected during the execution of this research project will aid decision makers in the identification of sensors to be used in nuclear facilities selected for in situ decommissioning. (authors)« less

Data Exploration using Unsupervised Feature Extraction for Mixed Micro-Seismic Signals

NASA Astrophysics Data System (ADS)

Meyer, Matthias; Weber, Samuel; Beutel, Jan

2017-04-01

We present a system for the analysis of data originating in a multi-sensor and multi-year experiment focusing on slope stability and its underlying processes in fractured permafrost rock walls undertaken at 3500m a.s.l. on the Matterhorn Hörnligrat, (Zermatt, Switzerland). This system incorporates facilities for the transmission, management and storage of large-scales of data ( 7 GB/day), preprocessing and aggregation of multiple sensor types, machine-learning based automatic feature extraction for micro-seismic and acoustic emission data and interactive web-based visualization of the data. Specifically, a combination of three types of sensors are used to profile the frequency spectrum from 1 Hz to 80 kHz with the goal to identify the relevant destructive processes (e.g. micro-cracking and fracture propagation) leading to the eventual destabilization of large rock masses. The sensors installed for this profiling experiment (2 geophones, 1 accelerometers and 2 piezo-electric sensors for detecting acoustic emission), are further augmented with sensors originating from a previous activity focusing on long-term monitoring of temperature evolution and rock kinematics with the help of wireless sensor networks (crackmeters, cameras, weather station, rock temperature profiles, differential GPS) [Hasler2012]. In raw format, the data generated by the different types of sensors, specifically the micro-seismic and acoustic emission sensors, is strongly heterogeneous, in part unsynchronized and the storage and processing demand is large. Therefore, a purpose-built signal preprocessing and event-detection system is used. While the analysis of data from each individual sensor follows established methods, the application of all these sensor types in combination within a field experiment is unique. Furthermore, experience and methods from using such sensors in laboratory settings cannot be readily transferred to the mountain field site setting with its scale and full exposure to the natural environment. Consequently, many state-of-the-art algorithms for big data analysis and event classification requiring a ground truth dataset cannot be applied. The above mentioned challenges require a tool for data exploration. In the presented system, data exploration is supported by unsupervised feature learning based on convolutional neural networks, which is used to automatically extract common features for preliminary clustering and outlier detection. With this information, an interactive web-tool allows for a fast identification of interesting time segments on which segment-selective algorithms for visualization, feature extraction and statistics can be applied. The combination of manual labeling based and unsupervised feature extraction provides an event catalog for classification of different characteristic events related to internal progression of micro-crack in steep fractured bedrock permafrost. References Hasler, A., S. Gruber, and J. Beutel (2012), Kinematics of steep bedrock permafrost, J. Geophys. Res., 117, F01016, doi:10.1029/2011JF001981.

Heterogeneous Collaborative Sensor Network for Electrical Management of an Automated House with PV Energy

PubMed Central

Castillo-Cagigal, Manuel; Matallanas, Eduardo; Gutiérrez, Álvaro; Monasterio-Huelin, Félix; Caamaño-Martín, Estefaná; Masa-Bote, Daniel; Jiménez-Leube, Javier

2011-01-01

In this paper we present a heterogeneous collaborative sensor network for electrical management in the residential sector. Improving demand-side management is very important in distributed energy generation applications. Sensing and control are the foundations of the “Smart Grid” which is the future of large-scale energy management. The system presented in this paper has been developed on a self-sufficient solar house called “MagicBox” equipped with grid connection, PV generation, lead-acid batteries, controllable appliances and smart metering. Therefore, there is a large number of energy variables to be monitored that allow us to precisely manage the energy performance of the house by means of collaborative sensors. The experimental results, performed on a real house, demonstrate the feasibility of the proposed collaborative system to reduce the consumption of electrical power and to increase energy efficiency. PMID:22247680

Differentially Private Distributed Sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fink, Glenn A.

The growth of the Internet of Things (IoT) creates the possibility of decentralized systems of sensing and actuation, potentially on a global scale. IoT devices connected to cloud networks can offer Sensing and Actuation as a Service (SAaaS) enabling networks of sensors to grow to a global scale. But extremely large sensor networks can violate privacy, especially in the case where IoT devices are mobile and connected directly to the behaviors of people. The thesis of this paper is that by adapting differential privacy (adding statistically appropriate noise to query results) to groups of geographically distributed sensors privacy could bemore » maintained without ever sending all values up to a central curator and without compromising the overall accuracy of the data collected. This paper outlines such a scheme and performs an analysis of differential privacy techniques adapted to edge computing in a simulated sensor network where ground truth is known. The positive and negative outcomes of employing differential privacy in distributed networks of devices are discussed and a brief research agenda is presented.« less

Design of Force Sensor Leg for a Rocket Thrust Detector

NASA Astrophysics Data System (ADS)

Woten, Douglas; McGehee, Tripp; Wright, Anne

2005-03-01

A hybrid rocket is composed of a solid fuel and a separate liquid or gaseous oxidizer. These rockets may be throttled like liquid rockets, are safer than solid rockets, and are much less complex than liquid rockets. However, hybrid rockets produce thrust oscillations that are not practical for large scale use. A lab scale hybrid rocket at the University of Arkansas at Little Rock (UALR) Hybrid Rocket Facility is used to develop sensors to measure physical properties of hybrid rockets. Research is currently being conducted to design a six degree of freedom force sensor to measure the thrust and torque in all three spacial dimensions. The detector design uses six force sensor legs. Each leg utilizes strain gauges and a Wheatstone bridge to produce a voltage propotional to the force on the leg. The leg was designed using the CAD software ProEngineer and ProMechanica. Computer models of the strains on the single leg will be presented. A prototype leg was built and was tested in an INSTRON and results will be presented.

Fabrication and Characterization of Flexible and Miniaturized Humidity Sensors Using Screen-Printed TiO2 Nanoparticles as Sensitive Layer

PubMed Central

Dubourg, Georges; Segkos, Apostolos; Katona, Jaroslav; Radović, Marko; Savić, Slavica; Crnojević-Bengin, Vesna

2017-01-01

This paper describes the fabrication and the characterization of an original example of a miniaturized resistive-type humidity sensor, printed on flexible substrate in a large-scale manner. The fabrication process involves laser ablation for the design of interdigitated electrodes on PET (Poly-Ethylene Terephthalate) substrate and a screen-printing process for the deposition of the sensitive material, which is based on TiO2 nanoparticles. The laser ablation process was carefully optimized to obtain micro-scale and well-resolved electrodes on PET substrate. A functional paste based on cellulose was prepared in order to allow the precise screen-printing of the TiO2 nanoparticles as sensing material on the top of the electrodes. The current against voltage (I–V) characteristic of the sensor showed good linearity and potential for low-power operation. The results of a humidity-sensing investigation and mechanical testing showed that the fabricated miniaturized sensors have excellent mechanical stability, sensing characteristics, good repeatability, and relatively fast response/recovery times operating at room temperature. PMID:28800063

Comparison of Three Soil Moisture Sensor Types Under Field Conditions Based on the Marena, Oklahoma, In Situ Sensor Testbed (MOISST)

NASA Astrophysics Data System (ADS)

Zhang, N.; Quiring, S. M.; Ochsner, T. E.

2017-12-01

Each soil moisture monitoring network commonly adopts different sensor technologies. This results in different measurement units, depths and impedes large-scale soil moisture applications that seek to integrate data from multiple networks. Therefore, a comprehensive comparison of different sensors to identify the best approach for integrating and homogenizing measurements from different sensors is required. This study compares three commonly used sensors, including Stevens Water Hydra Probes, Campbell Scientific CS616 TDR and CS 229-L heat dissipation sensors based on data from May 2010 to December 2012 from the Marena, Oklahoma, In Situ Sensor Testbed (MOISST). All sensors are installed at common depths of 5, 10, 20, 50, 100 cm. The results reveal that the differences between the three sensors tends to increase with depth. The CDF plots showed CS 229 is most sensitive to moisture variation in dry condition and most easily saturated in wet condition, followed by Hydra probe and CS616. Our results show that calculating percentiles is a good normalization method for standardizing measurements from different sensors. Our preliminary results demonstrate that CDF matching can be used to convert measurements from one sensor to another.

An overview of sensor calibration inter-comparison and applications

USGS Publications Warehouse

Xiong, Xiaoxiong; Cao, Changyong; Chander, Gyanesh

2010-01-01

Long-term climate data records (CDR) are often constructed using observations made by multiple Earth observing sensors over a broad range of spectra and a large scale in both time and space. These sensors can be of the same or different types operated on the same or different platforms. They can be developed and built with different technologies and are likely operated over different time spans. It has been known that the uncertainty of climate models and data records depends not only on the calibration quality (accuracy and stability) of individual sensors, but also on their calibration consistency across instruments and platforms. Therefore, sensor calibration inter-comparison and validation have become increasingly demanding and will continue to play an important role for a better understanding of the science product quality. This paper provides an overview of different methodologies, which have been successfully applied for sensor calibration inter-comparison. Specific examples using different sensors, including MODIS, AVHRR, and ETM+, are presented to illustrate the implementation of these methodologies.

Remote Imaging Applied to Schistosomiasis Control: The Anning River Project

NASA Technical Reports Server (NTRS)

Seto, Edmund Y. W.; Maszle, Don R.; Spear, Robert C.; Gong, Peng

1997-01-01

The use of satellite imaging to remotely detect areas of high risk for transmission of infectious disease is an appealing prospect for large-scale monitoring of these diseases. The detection of large-scale environmental determinants of disease risk, often called landscape epidemiology, has been motivated by several authors (Pavlovsky 1966; Meade et al. 1988). The basic notion is that large-scale factors such as population density, air temperature, hydrological conditions, soil type, and vegetation can determine in a coarse fashion the local conditions contributing to disease vector abundance and human contact with disease agents. These large-scale factors can often be remotely detected by sensors or cameras mounted on satellite or aircraft platforms and can thus be used in a predictive model to mark high risk areas of transmission and to target control or monitoring efforts. A review of satellite technologies for this purpose was recently presented by Washino and Wood (1994) and Hay (1997) and Hay et al. (1997).

Effects of Spectral Band Differences between Landsat 8 Operational Land Imager (OLI) and Sentinel 2A Multispectral Instrument (MSI)

NASA Astrophysics Data System (ADS)

Micijevic, E.; Haque, M. O.

2015-12-01

In satellite remote sensing, Landsat sensors are recognized for providing well calibrated satellite images for over four decades. This image data set provides an important contribution to detection and temporal analysis of land changes. Landsat 8 (L8), the latest satellite of the Landsat series, was designed to continue its legacy as well as to embrace advanced technology and satisfy the demand of the broader scientific community. Sentinel 2A (S2A), a European satellite launched in June 2015, is designed to keep data continuity of Landsat and SPOT like satellites. The S2A MSI sensor is equipped with spectral bands similar to L8 OLI and includes some additional ones. Compared to L8 OLI, green and near infrared MSI bands have narrower bandwidths, whereas coastal-aerosol (CA) and cirrus have larger bandwidths. The blue and red MSI bands cover higher wavelengths than the matching OLI bands. Although the spectral band differences are not large, their combination with the spectral signature of a studied target can largely affect the Top Of Atmosphere (TOA) reflectance seen by the sensors. This study investigates the effect of spectral band differences between S2A MSI and L8 OLI sensors. The differences in spectral bands between sensors can be assessed by calculating Spectral Band Adjustment Factors (SBAF). For radiometric calibration purposes, the SBAFs for the calibration test site are used to bring the two sensors to the same radiometric scale. However, the SBAFs are target dependent and different sensors calibrated to the same radiometric scale will (correctly!) measure different reflectance for the same target. Thus, when multiple sensors are used to study a given target, the sensor responses need to be adjusted using SBAFs specific to that target. Comparison of the SBAFs for S2A MSI and L8 OLI based on various vegetation spectral profiles revealed variations in radiometric responses as high as 15%. Depending on target under study, these differences could be even higher.

Estimating Snow Water Equivalent over the American River in the Sierra Nevada Basin Using Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Welch, S. C.; Kerkez, B.; Glaser, S. D.; Bales, R. C.; Rice, R.

2011-12-01

We have designed a basin-scale (>2000 km2) instrument cluster, made up of 20 local-scale (1-km footprint) wireless sensor networks (WSNs), to measure patterns of snow depth and snow water equivalent (SWE) across the main snowmelt producing area within the American River basin. Each of the 20 WSNs has on the order of 25 wireless nodes, with over 10 nodes actively sensing snow depth, and thus snow accumulation and melt. When combined with existing snow density measurements and full-basin satellite snowcover data, these measurements are designed to provide dense ground-truth snow properties for research and real-time SWE for water management. The design of this large-scale network is based on rigorous testing of previous, smaller-scale studies, permitting for the development of methods to significantly, and efficiently scale up network operations. Recent advances in WSN technology have resulted in a modularized strategy that permits rapid future network deployment. To select network and sensor locations, various sensor placement approaches were compared, including random placement, placement of WSNs in locations that have captured the historical basin mean, as well as a placement algorithm leveraging the covariance structure of the SWE distribution. We show that that the optimal network locations do not exhibit a uniform grid, but rather follow strategic patterns based on physiographic terrain parameters. Uncertainty estimates are also provided to assess the confidence in the placement approach. To ensure near-optimal coverage of the full basin, we validated each placement approach with a multi-year record of SWE derived from reconstruction of historical satellite measurements.

Next generation sensing platforms for extended deployments in large-scale, multidisciplinary, adaptive sampling and observational networks

NASA Astrophysics Data System (ADS)

Cross, J. N.; Meinig, C.; Mordy, C. W.; Lawrence-Slavas, N.; Cokelet, E. D.; Jenkins, R.; Tabisola, H. M.; Stabeno, P. J.

2016-12-01

New autonomous sensors have dramatically increased the resolution and accuracy of oceanographic data collection, enabling rapid sampling over extremely fine scales. Innovative new autonomous platofrms like floats, gliders, drones, and crawling moorings leverage the full potential of these new sensors by extending spatiotemporal reach across varied environments. During 2015 and 2016, The Innovative Technology for Arctic Exploration Program at the Pacific Marine Environmental Laboratory tested several new types of fully autonomous platforms with increased speed, durability, and power and payload capacity designed to deliver cutting-edge ecosystem assessment sensors to remote or inaccessible environments. The Expendable Ice-Tracking (EXIT) gloat developed by the NOAA Pacific Marine Environmental Laboratory (PMEL) is moored near bottom during the ice-free season and released on an autonomous timer beneath the ice during the following winter. The float collects a rapid profile during ascent, and continues to collect critical, poorly-accessible under-ice data until melt, when data is transmitted via satellite. The autonomous Oculus sub-surface glider developed by the University of Washington and PMEL has a large power and payload capacity and an enhanced buoyancy engine. This 'coastal truck' is designed for the rapid water column ascent required by optical imaging systems. The Saildrone is a solar and wind powered ocean unmanned surface vessel (USV) developed by Saildrone, Inc. in partnership with PMEL. This large-payload (200 lbs), fast (1-7 kts), durable (46 kts winds) platform was equipped with 15 sensors designed for ecosystem assessment during 2016, including passive and active acoustic systems specially redesigned for autonomous vehicle deployments. The senors deployed on these platforms achieved rigorous accuracy and precision standards. These innovative platforms provide new sampling capabilities and cost efficiencies in high-resolution sensor deployment, including reconnaissance for annual fisheries and marine mammal surveys; better linkages between sustained observing platforms; and adaptive deployments that can easily target anomalies as they arise.

ROADNET: A Real-time Data Aware System for Earth, Oceanographic, and Environmental Applications

NASA Astrophysics Data System (ADS)

Vernon, F.; Hansen, T.; Lindquist, K.; Ludascher, B.; Orcutt, J.; Rajasekar, A.

2003-12-01

The Real-time Observatories, Application, and Data management Network (ROADNet) Program aims to develop an integrated, seamless, and transparent environmental information network that will deliver geophysical, oceanographic, hydrological, ecological, and physical data to a variety of users in real-time. ROADNet is a multidisciplinary, multinational partnership of researchers, policymakers, natural resource managers, educators, and students who aim to use the data to advance our understanding and management of coastal, ocean, riparian, and terrestrial Earth systems in Southern California, Mexico, and well off shore. To date, project activity and funding have focused on the design and deployment of network linkages and on the exploratory development of the real-time data management system. We are currently adapting powerful "Data Grid" technologies to the unique challenges associated with the management and manipulation of real-time data. Current "Grid" projects deal with static data files, and significant technical innovation is required to address fundamental problems of real-time data processing, integration, and distribution. The technologies developed through this research will create a system that dynamically adapt downstream processing, cataloging, and data access interfaces when sensors are added or removed from the system; provide for real-time processing and monitoring of data streams--detecting events, and triggering computations, sensor and logger modifications, and other actions; integrate heterogeneous data from multiple (signal) domains; and provide for large-scale archival and querying of "consolidated" data. The software tools which must be developed do not exist, although limited prototype systems are available. This research has implications for the success of large-scale NSF initiatives in the Earth sciences (EarthScope), ocean sciences (OOI- Ocean Observatories Initiative), biological sciences (NEON - National Ecological Observatory Network) and civil engineering (NEES - Network for Earthquake Engineering Simulation). Each of these large scale initiatives aims to collect real-time data from thousands of sensors, and each will require new technologies to process, manage, and communicate real-time multidisciplinary environmental data on regional, national, and global scales.

Large scale tracking algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett

2015-01-01

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For highermore » resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.« less

Distributed wavefront reconstruction with SABRE for real-time large scale adaptive optics control

NASA Astrophysics Data System (ADS)

Brunner, Elisabeth; de Visser, Cornelis C.; Verhaegen, Michel

2014-08-01

We present advances on Spline based ABerration REconstruction (SABRE) from (Shack-)Hartmann (SH) wavefront measurements for large-scale adaptive optics systems. SABRE locally models the wavefront with simplex B-spline basis functions on triangular partitions which are defined on the SH subaperture array. This approach allows high accuracy through the possible use of nonlinear basis functions and great adaptability to any wavefront sensor and pupil geometry. The main contribution of this paper is a distributed wavefront reconstruction method, D-SABRE, which is a 2 stage procedure based on decomposing the sensor domain into sub-domains each supporting a local SABRE model. D-SABRE greatly decreases the computational complexity of the method and removes the need for centralized reconstruction while obtaining a reconstruction accuracy for simulated E-ELT turbulences within 1% of the global method's accuracy. Further, a generalization of the methodology is proposed making direct use of SH intensity measurements which leads to an improved accuracy of the reconstruction compared to centroid algorithms using spatial gradients.

Multi-pose system for geometric measurement of large-scale assembled rotational parts

NASA Astrophysics Data System (ADS)

Deng, Bowen; Wang, Zhaoba; Jin, Yong; Chen, Youxing

2017-05-01

To achieve virtual assembly of large-scale assembled rotational parts based on in-field geometric data, we develop a multi-pose rotative arm measurement system with a gantry and 2D laser sensor (RAMSGL) to measure and provide the geometry of these parts. We mount a 2D laser sensor onto the end of a six-jointed rotative arm to guarantee the accuracy and efficiency, combine the rotative arm with a gantry to measure pairs of assembled rotational parts. By establishing and using the D-H model of the system, the 2D laser data is turned into point clouds and finally geometry is calculated. In addition, we design three experiments to evaluate the performance of the system. Experimental results show that the system’s max length measuring deviation using gauge blocks is 35 µm, max length measuring deviation using ball plates is 50 µm, max single-point repeatability error is 25 µm, and measurement scope is from a radius of 0 mm to 500 mm.

The Atacama B-Mode Search: CMB Polarimetry with Transition-Edge-Sensor Bolometers

NASA Astrophysics Data System (ADS)

Essinger-Hileman, T.; Appel, J. W.; Beal, J. A.; Cho, H. M.; Fowler, J.; Halpern, M.; Hasselfield, M.; Irwin, K. D.; Marriage, T. A.; Niemack, M. D.; Page, L.; Parker, L. P.; Pufu, S.; Staggs, S. T.; Stryzak, O.; Visnjic, C.; Yoon, K. W.; Zhao, Y.

2009-12-01

The Atacama B-mode Search (ABS) experiment is a 145 GHz polarimeter designed to measure the B-mode polarization of the Cosmic Microwave Background (CMB) at large angular scales. The ABS instrument will ship to the Atacama Desert of Chile fully tested and ready to observe in 2010. ABS will image large-angular-scale CMB polarization anisotropies onto a focal plane of 240 feedhorn-coupled, transition-edge sensor (TES) polarimeters, using a cryogenic crossed-Dragone design. The ABS detectors, which are fabricated at NIST, use orthomode transducers to couple orthogonal polarizations of incoming radiation onto separate TES bolometers. The incoming radiation is modulated by an ambient-temperature half-wave plate in front of the vacuum window at an aperture stop. Preliminary detector characterization indicates that the ABS detectors can achieve a sensitivity of 300 μK√s in the field. This paper describes the ABS optical design and detector readout scheme, including feedhorn design and performance, magnetic shielding, focal plane architecture, and cryogenic electronics.

Fully Integrated, Miniature, High-Frequency Flow Probe Utilizing MEMS Leadless SOI Technology

NASA Technical Reports Server (NTRS)

Ned, Alex; Kurtz, Anthony; Shang, Tonghuo; Goodman, Scott; Giemette. Gera (d)

2013-01-01

This work focused on developing, fabricating, and fully calibrating a flowangle probe for aeronautics research by utilizing the latest microelectromechanical systems (MEMS), leadless silicon on insulator (SOI) sensor technology. While the concept of angle probes is not new, traditional devices had been relatively large due to fabrication constraints; often too large to resolve flow structures necessary for modern aeropropulsion measurements such as inlet flow distortions and vortices, secondary flows, etc. Mea surements of this kind demanded a new approach to probe design to achieve sizes on the order of 0.1 in. (.3 mm) diameter or smaller, and capable of meeting demanding requirements for accuracy and ruggedness. This approach invoked the use of stateof- the-art processing techniques to install SOI sensor chips directly onto the probe body, thus eliminating redundancy in sensor packaging and probe installation that have historically forced larger probe size. This also facilitated a better thermal match between the chip and its mount, improving stability and accuracy. Further, the leadless sensor technology with which the SOI sensing element is fabricated allows direct mounting and electrical interconnecting of the sensor to the probe body. This leadless technology allowed a rugged wire-out approach that is performed at the sensor length scale, thus achieving substantial sensor size reductions. The technology is inherently capable of high-frequency and high-accuracy performance in high temperatures and harsh environments.

Unsupervised Machine Learning for Developing Personalised Behaviour Models Using Activity Data.

PubMed

Fiorini, Laura; Cavallo, Filippo; Dario, Paolo; Eavis, Alexandra; Caleb-Solly, Praminda

2017-05-04

The goal of this study is to address two major issues that undermine the large scale deployment of smart home sensing solutions in people's homes. These include the costs associated with having to install and maintain a large number of sensors, and the pragmatics of annotating numerous sensor data streams for activity classification. Our aim was therefore to propose a method to describe individual users' behavioural patterns starting from unannotated data analysis of a minimal number of sensors and a "blind" approach for activity recognition. The methodology included processing and analysing sensor data from 17 older adults living in community-based housing to extract activity information at different times of the day. The findings illustrate that 55 days of sensor data from a sensor configuration comprising three sensors, and extracting appropriate features including a "busyness" measure, are adequate to build robust models which can be used for clustering individuals based on their behaviour patterns with a high degree of accuracy (>85%). The obtained clusters can be used to describe individual behaviour over different times of the day. This approach suggests a scalable solution to support optimising the personalisation of care by utilising low-cost sensing and analysis. This approach could be used to track a person's needs over time and fine-tune their care plan on an ongoing basis in a cost-effective manner.

Unsupervised Machine Learning for Developing Personalised Behaviour Models Using Activity Data

PubMed Central

Fiorini, Laura; Cavallo, Filippo; Dario, Paolo; Eavis, Alexandra; Caleb-Solly, Praminda

2017-01-01

The goal of this study is to address two major issues that undermine the large scale deployment of smart home sensing solutions in people’s homes. These include the costs associated with having to install and maintain a large number of sensors, and the pragmatics of annotating numerous sensor data streams for activity classification. Our aim was therefore to propose a method to describe individual users’ behavioural patterns starting from unannotated data analysis of a minimal number of sensors and a ”blind” approach for activity recognition. The methodology included processing and analysing sensor data from 17 older adults living in community-based housing to extract activity information at different times of the day. The findings illustrate that 55 days of sensor data from a sensor configuration comprising three sensors, and extracting appropriate features including a “busyness” measure, are adequate to build robust models which can be used for clustering individuals based on their behaviour patterns with a high degree of accuracy (>85%). The obtained clusters can be used to describe individual behaviour over different times of the day. This approach suggests a scalable solution to support optimising the personalisation of care by utilising low-cost sensing and analysis. This approach could be used to track a person’s needs over time and fine-tune their care plan on an ongoing basis in a cost-effective manner. PMID:28471405

Multigrid preconditioned conjugate-gradient method for large-scale wave-front reconstruction.

PubMed

Gilles, Luc; Vogel, Curtis R; Ellerbroek, Brent L

2002-09-01

We introduce a multigrid preconditioned conjugate-gradient (MGCG) iterative scheme for computing open-loop wave-front reconstructors for extreme adaptive optics systems. We present numerical simulations for a 17-m class telescope with n = 48756 sensor measurement grid points within the aperture, which indicate that our MGCG method has a rapid convergence rate for a wide range of subaperture average slope measurement signal-to-noise ratios. The total computational cost is of order n log n. Hence our scheme provides for fast wave-front simulation and control in large-scale adaptive optics systems.

Imaging detectors and electronics—a view of the future

NASA Astrophysics Data System (ADS)

Spieler, Helmuth

2004-09-01

Imaging sensors and readout electronics have made tremendous strides in the past two decades. The application of modern semiconductor fabrication techniques and the introduction of customized monolithic integrated circuits have made large-scale imaging systems routine in high-energy physics. This technology is now finding its way into other areas, such as space missions, synchrotron light sources, and medical imaging. I review current developments and discuss the promise and limits of new technologies. Several detector systems are described as examples of future trends. The discussion emphasizes semiconductor detector systems, but I also include recent developments for large-scale superconducting detector arrays.

A Study on the Performance of Low Cost MEMS Sensors in Strong Motion Studies

NASA Astrophysics Data System (ADS)

Tanırcan, Gulum; Alçık, Hakan; Kaya, Yavuz; Beyen, Kemal

2017-04-01

Recent advances in sensors have helped the growth of local networks. In recent years, many Micro Electro Mechanical System (MEMS)-based accelerometers have been successfully used in seismology and earthquake engineering projects. This is basically due to the increased precision obtained in these downsized instruments. Moreover, they are cheaper alternatives to force-balance type accelerometers. In Turkey, though MEMS-based accelerometers have been used in various individual applications such as magnitude and location determination of earthquakes, structural health monitoring, earthquake early warning systems, MEMS-based strong motion networks are not currently available in other populated areas of the country. Motivation of this study comes from the fact that, if MEMS sensors are qualified to record strong motion parameters of large earthquakes, a dense network can be formed in an affordable price at highly populated areas. The goals of this study are 1) to test the performance of MEMS sensors, which are available in the inventory of the Institute through shake table tests, and 2) to setup a small scale network for observing online data transfer speed to a trusted in-house routine. In order to evaluate the suitability of sensors in strong motion related studies, MEMS sensors and a reference sensor are tested under excitations of sweeping waves as well as scaled earthquake recordings. Amplitude response and correlation coefficients versus frequencies are compared. As for earthquake recordings, comparisons are carried out in terms of strong motion(SM) parameters (PGA, PGV, AI, CAV) and elastic response of structures (Sa). Furthermore, this paper also focuses on sensitivity and selectivity for sensor performances in time-frequency domain to compare different sensing characteristics and analyzes the basic strong motion parameters that influence the design majors. Results show that the cheapest MEMS sensors under investigation are able to record the mid-frequency dominant SM parameters PGV and CAV with high correlation. PGA and AI, the high frequency components of the ground motion, are underestimated. Such a difference, on the other hand, does not manifest itself on intensity estimations. PGV and CAV values from the reference and MEMS sensors converge to the same seismic intensity level. Hence a strong motion network with MEMS sensors could be a modest option to produce PGV-based damage impact of an urban area under large magnitude earthquake threats in the immediate vicinity.

Small, fast, and tough: Shrinking down integrated elastomer transducers

NASA Astrophysics Data System (ADS)

Rosset, Samuel; Shea, Herbert R.

2016-09-01

We review recent progress in miniaturized dielectric elastomer actuators (DEAs), sensors, and energy harvesters. We focus primarily on configurations where the large strain, high compliance, stretchability, and high level of integration offered by dielectric elastomer transducers provide significant advantages over other mm or μm-scale transduction technologies. We first present the most active application areas, including: tunable optics, soft robotics, haptics, micro fluidics, biomedical devices, and stretchable sensors. We then discuss the fabrication challenges related to miniaturization, such as thin membrane fabrication, precise patterning of compliant electrodes, and reliable batch fabrication of multilayer devices. We finally address the impact of miniaturization on strain, force, and driving voltage, as well as the important effect of boundary conditions on the performance of mm-scale DEAs.

Sensor for In-Motion Continuous 3D Shape Measurement Based on Dual Line-Scan Cameras

PubMed Central

Sun, Bo; Zhu, Jigui; Yang, Linghui; Yang, Shourui; Guo, Yin

2016-01-01

The acquisition of three-dimensional surface data plays an increasingly important role in the industrial sector. Numerous 3D shape measurement techniques have been developed. However, there are still limitations and challenges in fast measurement of large-scale objects or high-speed moving objects. The innovative line scan technology opens up new potentialities owing to the ultra-high resolution and line rate. To this end, a sensor for in-motion continuous 3D shape measurement based on dual line-scan cameras is presented. In this paper, the principle and structure of the sensor are investigated. The image matching strategy is addressed and the matching error is analyzed. The sensor has been verified by experiments and high-quality results are obtained. PMID:27869731

Miniaturized Bio-and Chemical-Sensors for Point-of-Care Monitoring of Chronic Kidney Diseases

PubMed Central

Tricoli, Antonio

2018-01-01

This review reports the latest achievements in point-of-care (POC) sensor technologies for the monitoring of ammonia, creatinine and urea in patients suffering of chronic kidney diseases (CKDs). Abnormal levels of these nitrogen biomarkers are found in the physiological fluids, such as blood, urine and sweat, of CKD patients. Delocalized at-home monitoring of CKD biomarkers via integration of miniaturized, portable, and low cost chemical- and bio-sensors in POC devices, is an emerging approach to improve patients’ health monitoring and life quality. The successful monitoring of CKD biomarkers, performed on the different body fluids by means of sensors having strict requirements in term of size, cost, large-scale production capacity, response time and simple operation procedures for use in POC devices, is reported and discussed. PMID:29565315

Miniaturized Bio-and Chemical-Sensors for Point-of-Care Monitoring of Chronic Kidney Diseases.

PubMed

Tricoli, Antonio; Neri, Giovanni

2018-03-22

This review reports the latest achievements in point-of-care (POC) sensor technologies for the monitoring of ammonia, creatinine and urea in patients suffering of chronic kidney diseases (CKDs). Abnormal levels of these nitrogen biomarkers are found in the physiological fluids, such as blood, urine and sweat, of CKD patients. Delocalized at-home monitoring of CKD biomarkers via integration of miniaturized, portable, and low cost chemical- and bio-sensors in POC devices, is an emerging approach to improve patients' health monitoring and life quality. The successful monitoring of CKD biomarkers, performed on the different body fluids by means of sensors having strict requirements in term of size, cost, large-scale production capacity, response time and simple operation procedures for use in POC devices, is reported and discussed.

Advances in Multi-Sensor Scanning and Visualization of Complex Plants: the Utmost Case of a Reactor Building

NASA Astrophysics Data System (ADS)

Hullo, J.-F.; Thibault, G.; Boucheny, C.

2015-02-01

In a context of increased maintenance operations and workers generational renewal, a nuclear owner and operator like Electricité de France (EDF) is interested in the scaling up of tools and methods of "as-built virtual reality" for larger buildings and wider audiences. However, acquisition and sharing of as-built data on a large scale (large and complex multi-floored buildings) challenge current scientific and technical capacities. In this paper, we first present a state of the art of scanning tools and methods for industrial plants with very complex architecture. Then, we introduce the inner characteristics of the multi-sensor scanning and visualization of the interior of the most complex building of a power plant: a nuclear reactor building. We introduce several developments that made possible a first complete survey of such a large building, from acquisition, processing and fusion of multiple data sources (3D laser scans, total-station survey, RGB panoramic, 2D floor plans, 3D CAD as-built models). In addition, we present the concepts of a smart application developed for the painless exploration of the whole dataset. The goal of this application is to help professionals, unfamiliar with the manipulation of such datasets, to take into account spatial constraints induced by the building complexity while preparing maintenance operations. Finally, we discuss the main feedbacks of this large experiment, the remaining issues for the generalization of such large scale surveys and the future technical and scientific challenges in the field of industrial "virtual reality".

Piezoresistive Strain Sensors Made from Carbon Nanotubes Based Polymer Nanocomposites

PubMed Central

Alamusi; Hu, Ning; Fukunaga, Hisao; Atobe, Satoshi; Liu, Yaolu; Li, Jinhua

2011-01-01

In recent years, nanocomposites based on various nano-scale carbon fillers, such as carbon nanotubes (CNTs), are increasingly being thought of as a realistic alternative to conventional smart materials, largely due to their superior electrical properties. Great interest has been generated in building highly sensitive strain sensors with these new nanocomposites. This article reviews the recent significant developments in the field of highly sensitive strain sensors made from CNT/polymer nanocomposites. We focus on the following two topics: electrical conductivity and piezoresistivity of CNT/polymer nanocomposites, and the relationship between them by considering the internal conductive network formed by CNTs, tunneling effect, aspect ratio and piezoresistivity of CNTs themselves, etc. Many recent experimental, theoretical and numerical studies in this field are described in detail to uncover the working mechanisms of this new type of strain sensors and to demonstrate some possible key factors for improving the sensor sensitivity. PMID:22346667

Distributed wireless sensing for methane leak detection technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klein, Levente; van Kesse, Theodor

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less

Distributed wireless sensing for fugitive methane leak detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klein, Levente J.; van Kessel, Theodore; Nair, Dhruv

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less

Distributed wireless sensing for fugitive methane leak detection

DOE PAGES

Klein, Levente J.; van Kessel, Theodore; Nair, Dhruv; ...

2017-12-11

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less

Occupancy mapping and surface reconstruction using local Gaussian processes with Kinect sensors.

PubMed

Kim, Soohwan; Kim, Jonghyuk

2013-10-01

Although RGB-D sensors have been successfully applied to visual SLAM and surface reconstruction, most of the applications aim at visualization. In this paper, we propose a noble method of building continuous occupancy maps and reconstructing surfaces in a single framework for both navigation and visualization. Particularly, we apply a Bayesian nonparametric approach, Gaussian process classification, to occupancy mapping. However, it suffers from high-computational complexity of O(n(3))+O(n(2)m), where n and m are the numbers of training and test data, respectively, limiting its use for large-scale mapping with huge training data, which is common with high-resolution RGB-D sensors. Therefore, we partition both training and test data with a coarse-to-fine clustering method and apply Gaussian processes to each local clusters. In addition, we consider Gaussian processes as implicit functions, and thus extract iso-surfaces from the scalar fields, continuous occupancy maps, using marching cubes. By doing that, we are able to build two types of map representations within a single framework of Gaussian processes. Experimental results with 2-D simulated data show that the accuracy of our approximated method is comparable to previous work, while the computational time is dramatically reduced. We also demonstrate our method with 3-D real data to show its feasibility in large-scale environments.

Distributed electrochemical sensors: recent advances and barriers to market adoption.

PubMed

Hoekstra, Rafael; Blondeau, Pascal; Andrade, Francisco J

2018-07-01

Despite predictions of their widespread application in healthcare and environmental monitoring, electrochemical sensors are yet to be distributed at scale, instead remaining largely confined to R&D labs. This contrasts sharply with the situation for physical sensors, which are now ubiquitous and seamlessly embedded in the mature ecosystem provided by electronics and connectivity protocols. Although chemical sensors could be integrated into the same ecosystem, there are fundamental issues with these sensors in the three key areas of analytical performance, usability, and affordability. Nevertheless, advances are being made in each of these fields, leading to hope that the deployment of automated and user-friendly low-cost electrochemical sensors is on the horizon. Here, we present a brief survey of key challenges and advances in the development of distributed electrochemical sensors for liquid samples, geared towards applications in healthcare and wellbeing, environmental monitoring, and homeland security. As will be seen, in many cases the analytical performance of the sensor is acceptable; it is usability that is the major barrier to commercial viability at this moment. Were this to be overcome, the issue of affordability could be addressed. Graphical Abstract ᅟ.

Hardware Architecture and Cutting-Edge Assembly Process of a Tiny Curved Compound Eye

PubMed Central

Viollet, Stéphane; Godiot, Stéphanie; Leitel, Robert; Buss, Wolfgang; Breugnon, Patrick; Menouni, Mohsine; Juston, Raphaël; Expert, Fabien; Colonnier, Fabien; L'Eplattenier, Géraud; Brückner, Andreas; Kraze, Felix; Mallot, Hanspeter; Franceschini, Nicolas; Pericet-Camara, Ramon; Ruffier, Franck; Floreano, Dario

2014-01-01

The demand for bendable sensors increases constantly in the challenging field of soft and micro-scale robotics. We present here, in more detail, the flexible, functional, insect-inspired curved artificial compound eye (CurvACE) that was previously introduced in the Proceedings of the National Academy of Sciences (PNAS, 2013). This cylindrically-bent sensor with a large panoramic field-of-view of 180° × 60° composed of 630 artificial ommatidia weighs only 1.75 g, is extremely compact and power-lean (0.9 W), while it achieves unique visual motion sensing performance (1950 frames per second) in a five-decade range of illuminance. In particular, this paper details the innovative Very Large Scale Integration (VLSI) sensing layout, the accurate assembly fabrication process, the innovative, new fast read-out interface, as well as the auto-adaptive dynamic response of the CurvACE sensor. Starting from photodetectors and microoptics on wafer substrates and flexible printed circuit board, the complete assembly of CurvACE was performed in a planar configuration, ensuring high alignment accuracy and compatibility with state-of-the art assembling processes. The characteristics of the photodetector of one artificial ommatidium have been assessed in terms of their dynamic response to light steps. We also characterized the local auto-adaptability of CurvACE photodetectors in response to large illuminance changes: this feature will certainly be of great interest for future applications in real indoor and outdoor environments. PMID:25407908

Machine learning for large-scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures.

PubMed

Kubota, Ken J; Chen, Jason A; Little, Max A

2016-09-01

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, "wearable," sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that "learn" from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Power Grid Data Analysis with R and Hadoop

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hafen, Ryan P.; Gibson, Tara D.; Kleese van Dam, Kerstin

This book chapter presents an approach to analysis of large-scale time-series sensor information based on our experience with power grid data. We use the R-Hadoop Integrated Programming Environment (RHIPE) to analyze a 2TB data set and present code and results for this analysis.

Autonomous UAV-Based Mapping of Large-Scale Urban Firefights

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snarski, S; Scheibner, K F; Shaw, S

2006-03-09

This paper describes experimental results from a live-fire data collect designed to demonstrate the ability of IR and acoustic sensing systems to detect and map high-volume gunfire events from tactical UAVs. The data collect supports an exploratory study of the FightSight concept in which an autonomous UAV-based sensor exploitation and decision support capability is being proposed to provide dynamic situational awareness for large-scale battalion-level firefights in cluttered urban environments. FightSight integrates IR imagery, acoustic data, and 3D scene context data with prior time information in a multi-level, multi-step probabilistic-based fusion process to reliably locate and map the array of urbanmore » firing events and firepower movements and trends associated with the evolving urban battlefield situation. Described here are sensor results from live-fire experiments involving simultaneous firing of multiple sub/super-sonic weapons (2-AK47, 2-M16, 1 Beretta, 1 Mortar, 1 rocket) with high optical and acoustic clutter at ranges up to 400m. Sensor-shooter-target configurations and clutter were designed to simulate UAV sensing conditions for a high-intensity firefight in an urban environment. Sensor systems evaluated were an IR bullet tracking system by Lawrence Livermore National Laboratory (LLNL) and an acoustic gunshot detection system by Planning Systems, Inc. (PSI). The results demonstrate convincingly the ability for the LLNL and PSI sensor systems to accurately detect, separate, and localize multiple shooters and the associated shot directions during a high-intensity firefight (77 rounds in 5 sec) in a high acoustic and optical clutter environment with no false alarms. Preliminary fusion processing was also examined that demonstrated an ability to distinguish co-located shooters (shooter density), range to <0.5 m accuracy at 400m, and weapon type.« less

Scaling of surface energy fluxes using remotely sensed data

NASA Astrophysics Data System (ADS)

French, Andrew Nichols

Accurate estimates of evapotranspiration (ET) across multiple terrains would greatly ease challenges faced by hydrologists, climate modelers, and agronomists as they attempt to apply theoretical models to real-world situations. One ET estimation approach uses an energy balance model to interpret a combination of meteorological observations taken at the surface and data captured by remote sensors. However, results of this approach have not been accurate because of poor understanding of the relationship between surface energy flux and land cover heterogeneity, combined with limits in available resolution of remote sensors. The purpose of this study was to determine how land cover and image resolution affect ET estimates. Using remotely sensed data collected over El Reno, Oklahoma, during four days in June and July 1997, scale effects on the estimation of spatially distributed ET were investigated. Instantaneous estimates of latent and sensible heat flux were calculated using a two-source surface energy balance model driven by thermal infrared, visible-near infrared, and meteorological data. The heat flux estimates were verified by comparison to independent eddy-covariance observations. Outcomes of observations taken at coarser resolutions were simulated by aggregating remote sensor data and estimated surface energy balance components from the finest sensor resolution (12 meter) to hypothetical resolutions as coarse as one kilometer. Estimated surface energy flux components were found to be significantly dependent on observation scale. For example, average evaporative fraction varied from 0.79, using 12-m resolution data, to 0.93, using 1-km resolution data. Resolution effects upon flux estimates were related to a measure of landscape heterogeneity known as operational scale, reflecting the size of dominant landscape features. Energy flux estimates based on data at resolutions less than 100 m and much greater than 400 m showed a scale-dependent bias. But estimates derived from data taken at about 400-m resolution (the operational scale at El Reno) were susceptible to large error due to mixing of surface types. The El Reno experiments show that accurate instantaneous estimates of ET require precise image alignment and image resolutions finer than landscape operational scale. These findings are valuable for the design of sensors and experiments to quantify spatially-varying hydrologic processes.

Engineering a Large Scale Indium Nanodot Array for Refractive Index Sensing.

PubMed

Xu, Xiaoqing; Hu, Xiaolin; Chen, Xiaoshu; Kang, Yangsen; Zhang, Zhiping; B Parizi, Kokab; Wong, H-S Philip

2016-11-23

In this work, we developed a simple method to fabricate 12 × 4 mm 2 large scale nanostructure arrays and investigated the feasibility of indium nanodot (ND) array with different diameters and periods for refractive index sensing. Absorption resonances at multiple wavelengths from the visible to the near-infrared range were observed for various incident angles in a variety of media. Engineering the ND array with a centered square lattice, we successfully enhanced the sensitivity by 60% and improved the figure of merit (FOM) by 190%. The evolution of the resonance dips in the reflection spectra, of square lattice and centered square lattice, from air to water, matches well with the results of Lumerical FDTD simulation. The improvement of sensitivity is due to the enhancement of local electromagnetic field (E-field) near the NDs with centered square lattice, as revealed by E-field simulation at resonance wavelengths. The E-field is enhanced due to coupling between the two square ND arrays with [Formula: see text]x period at phase matching. This work illustrates an effective way to engineer and fabricate a refractive index sensor at a large scale. This is the first experimental demonstration of poor-metal (indium) nanostructure array for refractive index sensing. It also demonstrates a centered square lattice for higher sensitivity and as a better basic platform for more complex sensor designs.

Characterizing Impacts of Land Grabbing on Terrestrial Vegetation and Ecohydrologic change in Mozambique through Multiple-sensor Remote Sensing and Models

NASA Astrophysics Data System (ADS)

Flores, A. N.; Lakshmi, V.; Al-Barakat, R.; Maksimowicz, M.

2017-12-01

Land grabbing, the acquisition of large areas of land by external entities, results from interactions of complex global economic, social, and political processes. These transactions are controversial because they can result in large-scale disruptions to historical land uses, including increased intensity of agricultural practices and significant conversions in land cover. These large-scale disruptions have the potential to impact surface water and energy balance because vegetation controls the partitioning of incoming energy into latent and sensible heat fluxes and precipitation into runoff and infiltration. Because large-scale land acquisitions can impact local ecosystem services, it is important to document changes in terrestrial vegetation associated with these acquisitions to support the assessment of associated impacts on regional surface water and energy balance, spatiotemporal scales of those changes, and interactions and feedbacks with other processes, particularly in the atmosphere. We use remote sensing data from multiple satellite platforms to diagnose and characterize changes in terrestrial vegetation and ecohydrology in Mozambique during periods that bracket periods associated with significant. The Advanced very High Resolution Radiometer (AVHRR) sensor provides long-term continuous data that can document historical seasonal cycles of vegetation greenness. These data are augmented with analyses from Landsat multispectral data, which provides significantly higher spatial resolution. Here we quantify spatiotemporal changes in vegetation are associated with periods of significant land acquisitions in Mozambique. This analysis complements a suite of land-atmosphere modeling experiments designed to deduce potential changes in land surface water and energy budgets associated with these acquisitions. This work advance understanding of how telecouplings between global economic and political forcings and regional hydrology and climate.

Underwater Sensor Network Redeployment Algorithm Based on Wolf Search

PubMed Central

Jiang, Peng; Feng, Yang; Wu, Feng

2016-01-01

This study addresses the optimization of node redeployment coverage in underwater wireless sensor networks. Given that nodes could easily become invalid under a poor environment and the large scale of underwater wireless sensor networks, an underwater sensor network redeployment algorithm was developed based on wolf search. This study is to apply the wolf search algorithm combined with crowded degree control in the deployment of underwater wireless sensor networks. The proposed algorithm uses nodes to ensure coverage of the events, and it avoids the prematurity of the nodes. The algorithm has good coverage effects. In addition, considering that obstacles exist in the underwater environment, nodes are prevented from being invalid by imitating the mechanism of avoiding predators. Thus, the energy consumption of the network is reduced. Comparative analysis shows that the algorithm is simple and effective in wireless sensor network deployment. Compared with the optimized artificial fish swarm algorithm, the proposed algorithm exhibits advantages in network coverage, energy conservation, and obstacle avoidance. PMID:27775659

Soil specific re-calibration of water content sensors for a field-scale sensor network

NASA Astrophysics Data System (ADS)

Gasch, Caley K.; Brown, David J.; Anderson, Todd; Brooks, Erin S.; Yourek, Matt A.

2015-04-01

Obtaining accurate soil moisture data from a sensor network requires sensor calibration. Soil moisture sensors are factory calibrated, but multiple site specific factors may contribute to sensor inaccuracies. Thus, sensors should be calibrated for the specific soil type and conditions in which they will be installed. Lab calibration of a large number of sensors prior to installation in a heterogeneous setting may not be feasible, and it may not reflect the actual performance of the installed sensor. We investigated a multi-step approach to retroactively re-calibrate sensor water content data from the dielectric permittivity readings obtained by sensors in the field. We used water content data collected since 2009 from a sensor network installed at 42 locations and 5 depths (210 sensors total) within the 37-ha Cook Agronomy Farm with highly variable soils located in the Palouse region of the Northwest United States. First, volumetric water content was calculated from sensor dielectric readings using three equations: (1) a factory calibration using the Topp equation; (2) a custom calibration obtained empirically from an instrumented soil in the field; and (3) a hybrid equation that combines the Topp and custom equations. Second, we used soil physical properties (particle size and bulk density) and pedotransfer functions to estimate water content at saturation, field capacity, and wilting point for each installation location and depth. We also extracted the same reference points from the sensor readings, when available. Using these reference points, we re-scaled the sensor readings, such that water content was restricted to the range of values that we would expect given the physical properties of the soil. The re-calibration accuracy was assessed with volumetric water content measurements obtained from field-sampled cores taken on multiple dates. In general, the re-calibration was most accurate when all three reference points (saturation, field capacity, and wilting point) were represented in the sensor readings. We anticipate that obtaining water retention curves for field soils will improve the re-calibration accuracy by providing more precise estimates of saturation, field capacity, and wilting point. This approach may serve as an alternative method for sensor calibration in lieu of or to complement pre-installation calibration.

Significant enhancement of magnetoresistance with the reduction of particle size in nanometer scale

PubMed Central

Das, Kalipada; Dasgupta, P.; Poddar, A.; Das, I.

2016-01-01

The Physics of materials with large magnetoresistance (MR), defined as the percentage change of electrical resistance with the application of external magnetic field, has been an active field of research for quite some times. In addition to the fundamental interest, large MR has widespread application that includes the field of magnetic field sensor technology. New materials with large MR is interesting. However it is more appealing to vast scientific community if a method describe to achieve many fold enhancement of MR of already known materials. Our study on several manganite samples [La1−xCaxMnO3 (x = 0.52, 0.54, 0.55)] illustrates the method of significant enhancement of MR with the reduction of the particle size in nanometer scale. Our experimentally observed results are explained by considering model consisted of a charge ordered antiferromagnetic core and a shell having short range ferromagnetic correlation between the uncompensated surface spins in nanoscale regime. The ferromagnetic fractions obtained theoretically in the nanoparticles has been shown to be in the good agreement with the experimental results. The method of several orders of magnitude improvement of the magnetoresistive property will have enormous potential for magnetic field sensor technology. PMID:26837285

Multiwavelength active-optics Shack-Hartmann sensor for monitoring seeing and turbulence outer scale

NASA Astrophysics Data System (ADS)

Martinez, P.

2014-12-01

Context. Real-time seeing and outer-scale estimation at the location of the focus of a telescope is fundamental for predicting the adaptive-optics system's dimensioning and performance, as well as for the operational aspects of instruments. Aims: This study attempts to take advantage of multiwavelength long-exposure images to instantaneously and simultaneously derive the turbulence outer scale and seeing from the full width at half maximum (FWHM) of seeing-limited images taken at the focus of a telescope. These atmospheric parameters are commonly measured in most observatories by different methods located away from the telescope platform, thus differing from the effective estimates at the focus of a telescope, mainly because of differences in pointing orientation, height above the ground, or local seeing bias (dome contribution). Methods: Long-exposure images can either be provided directly by any multiwavelength scientific imager or spectrograph or, alternatively from a modified active-optics Shack-Hartmann sensor (AOSH). From measuring the AOSH sensor spot point spread function FWHMs simultaneously at different wavelengths, one can estimate the instantaneous outer scale in addition to seeing. Results: Multiwavelength long-exposure images provide access to accurate estimates of r0 and L0 by adequate means as long as precise FWHMs can be obtained. Although AOSH sensors are specified to measure not spot sizes but slopes, real-time r0, and L0 measurements from spot FWHMs can be obtained at the critical location where they are needed with major advantages over scientific instrument images: insensitivity to the telescope field stabilization, and continuous availability. Conclusions: Assuming an alternative optical design that allows simultaneous multiwavelength images, the AOSH sensor benefits from all the advantages of real-time seeing and outer scale monitoring. With the substantial interest in the design of extremely large telescopes, such a system could be of considerable importance.

On distributed wavefront reconstruction for large-scale adaptive optics systems.

PubMed

de Visser, Cornelis C; Brunner, Elisabeth; Verhaegen, Michel

2016-05-01

The distributed-spline-based aberration reconstruction (D-SABRE) method is proposed for distributed wavefront reconstruction with applications to large-scale adaptive optics systems. D-SABRE decomposes the wavefront sensor domain into any number of partitions and solves a local wavefront reconstruction problem on each partition using multivariate splines. D-SABRE accuracy is within 1% of a global approach with a speedup that scales quadratically with the number of partitions. The D-SABRE is compared to the distributed cumulative reconstruction (CuRe-D) method in open-loop and closed-loop simulations using the YAO adaptive optics simulation tool. D-SABRE accuracy exceeds CuRe-D for low levels of decomposition, and D-SABRE proved to be more robust to variations in the loop gain.

Distributed sensor networks: a cellular nonlinear network perspective.

PubMed

Haenggi, Martin

2003-12-01

Large-scale networks of integrated wireless sensors become increasingly tractable. Advances in hardware technology and engineering design have led to dramatic reductions in size, power consumption, and cost for digital circuitry, and wireless communications. Networking, self-organization, and distributed operation are crucial ingredients to harness the sensing, computing, and computational capabilities of the nodes into a complete system. This article shows that those networks can be considered as cellular nonlinear networks (CNNs), and that their analysis and design may greatly benefit from the rich theoretical results available for CNNs.

Structural analysis of stratocumulus convection

NASA Technical Reports Server (NTRS)

Siems, S. T.; Baker, M. B.; Bretherton, C. S.

1990-01-01

The 1 and 20 Hz data are examined from the Electra flights made on July 5, 1987. The flight legs consisted of seven horizontal turbulent legs at the inversion, midcloud, and below clouds, plus 4 soundings made within the same period. The Rosemont temperature sensor and the top and bottom dewpoint sensors were used to measure temperature and humidity at 1 Hz. Inversion structure and entrainment; local dynamics and large scale forcing; convective elements; and decoupling of cloud and subcloud are discussed in relationship to the results of the Electra flight.

A Large-Scale Study of Fingerprint Matching Systems for Sensor Interoperability Problem

PubMed Central

Hussain, Muhammad; AboAlSamh, Hatim; AlZuair, Mansour

2018-01-01

The fingerprint is a commonly used biometric modality that is widely employed for authentication by law enforcement agencies and commercial applications. The designs of existing fingerprint matching methods are based on the hypothesis that the same sensor is used to capture fingerprints during enrollment and verification. Advances in fingerprint sensor technology have raised the question about the usability of current methods when different sensors are employed for enrollment and verification; this is a fingerprint sensor interoperability problem. To provide insight into this problem and assess the status of state-of-the-art matching methods to tackle this problem, we first analyze the characteristics of fingerprints captured with different sensors, which makes cross-sensor matching a challenging problem. We demonstrate the importance of fingerprint enhancement methods for cross-sensor matching. Finally, we conduct a comparative study of state-of-the-art fingerprint recognition methods and provide insight into their abilities to address this problem. We performed experiments using a public database (FingerPass) that contains nine datasets captured with different sensors. We analyzed the effects of different sensors and found that cross-sensor matching performance deteriorates when different sensors are used for enrollment and verification. In view of our analysis, we propose future research directions for this problem. PMID:29597286

A Large-Scale Study of Fingerprint Matching Systems for Sensor Interoperability Problem.

PubMed

AlShehri, Helala; Hussain, Muhammad; AboAlSamh, Hatim; AlZuair, Mansour

2018-03-28

The fingerprint is a commonly used biometric modality that is widely employed for authentication by law enforcement agencies and commercial applications. The designs of existing fingerprint matching methods are based on the hypothesis that the same sensor is used to capture fingerprints during enrollment and verification. Advances in fingerprint sensor technology have raised the question about the usability of current methods when different sensors are employed for enrollment and verification; this is a fingerprint sensor interoperability problem. To provide insight into this problem and assess the status of state-of-the-art matching methods to tackle this problem, we first analyze the characteristics of fingerprints captured with different sensors, which makes cross-sensor matching a challenging problem. We demonstrate the importance of fingerprint enhancement methods for cross-sensor matching. Finally, we conduct a comparative study of state-of-the-art fingerprint recognition methods and provide insight into their abilities to address this problem. We performed experiments using a public database (FingerPass) that contains nine datasets captured with different sensors. We analyzed the effects of different sensors and found that cross-sensor matching performance deteriorates when different sensors are used for enrollment and verification. In view of our analysis, we propose future research directions for this problem.

A Feasibility Study on Numerical Modeling of Large-Scale Naval Fluid-Filled Structure: Contact-Impact Problems

DTIC Science & Technology

2011-02-01

capabilities for airbags , sensors, and seatbelts have tailored the code for applications in the automotive industry. Currently the code contains...larger intervals. In certain contact scenarios where contacting parts are moving relative to each other in a rapid fashion, such as airbag deployment

SCIMITAR: Scalable Stream-Processing for Sensor Information Brokering

DTIC Science & Technology

2013-11-01

IaaS) cloud frameworks including Amazon Web Services and Eucalyptus . For load testing, we used The Grinder [9], a Java load testing framework that...internal Eucalyptus cluster which we could not scale as large as the Amazon environment due to a lack of computation resources. We recreated our

Personalized medicine: from genotypes, molecular phenotypes and the quantified self, towards improved medicine.

PubMed

Dudley, Joel T; Listgarten, Jennifer; Stegle, Oliver; Brenner, Steven E; Parts, Leopold

2015-01-01

Advances in molecular profiling and sensor technologies are expanding the scope of personalized medicine beyond genotypes, providing new opportunities for developing richer and more dynamic multi-scale models of individual health. Recent studies demonstrate the value of scoring high-dimensional microbiome, immune, and metabolic traits from individuals to inform personalized medicine. Efforts to integrate multiple dimensions of clinical and molecular data towards predictive multi-scale models of individual health and wellness are already underway. Improved methods for mining and discovery of clinical phenotypes from electronic medical records and technological developments in wearable sensor technologies present new opportunities for mapping and exploring the critical yet poorly characterized "phenome" and "envirome" dimensions of personalized medicine. There are ambitious new projects underway to collect multi-scale molecular, sensor, clinical, behavioral, and environmental data streams from large population cohorts longitudinally to enable more comprehensive and dynamic models of individual biology and personalized health. Personalized medicine stands to benefit from inclusion of rich new sources and dimensions of data. However, realizing these improvements in care relies upon novel informatics methodologies, tools, and systems to make full use of these data to advance both the science and translational applications of personalized medicine.

Closed-loop feedback control for microfluidic systems through automated capacitive fluid height sensing.

PubMed

Soenksen, L R; Kassis, T; Noh, M; Griffith, L G; Trumper, D L

2018-03-13

Precise fluid height sensing in open-channel microfluidics has long been a desirable feature for a wide range of applications. However, performing accurate measurements of the fluid level in small-scale reservoirs (<1 mL) has proven to be an elusive goal, especially if direct fluid-sensor contact needs to be avoided. In particular, gravity-driven systems used in several microfluidic applications to establish pressure gradients and impose flow remain open-loop and largely unmonitored due to these sensing limitations. Here we present an optimized self-shielded coplanar capacitive sensor design and automated control system to provide submillimeter fluid-height resolution (∼250 μm) and control of small-scale open reservoirs without the need for direct fluid contact. Results from testing and validation of our optimized sensor and system also suggest that accurate fluid height information can be used to robustly characterize, calibrate and dynamically control a range of microfluidic systems with complex pumping mechanisms, even in cell culture conditions. Capacitive sensing technology provides a scalable and cost-effective way to enable continuous monitoring and closed-loop feedback control of fluid volumes in small-scale gravity-dominated wells in a variety of microfluidic applications.

An Assessment of Stream Confluence Flow Dynamics using Large Scale Particle Image Velocimetry Captured from Unmanned Aerial Systems

NASA Astrophysics Data System (ADS)

Lewis, Q. W.; Rhoads, B. L.

2017-12-01

The merging of rivers at confluences results in complex three-dimensional flow patterns that influence sediment transport, bed morphology, downstream mixing, and physical habitat conditions. The capacity to characterize comprehensively flow at confluences using traditional sensors, such as acoustic Doppler velocimeters and profiles, is limited by the restricted spatial resolution of these sensors and difficulties in measuring velocities simultaneously at many locations within a confluence. This study assesses two-dimensional surficial patterns of flow structure at a small stream confluence in Illinois, USA, using large scale particle image velocimetry (LSPIV) derived from videos captured by unmanned aerial systems (UAS). The method captures surface velocity patterns at high spatial and temporal resolution over multiple scales, ranging from the entire confluence to details of flow within the confluence mixing interface. Flow patterns at high momentum ratio are compared to flow patterns when the two incoming flows have nearly equal momentum flux. Mean surface flow patterns during the two types of events provide details on mean patterns of surface flow in different hydrodynamic regions of the confluence and on changes in these patterns with changing momentum flux ratio. LSPIV data derived from the highest resolution imagery also reveal general characteristics of large-scale vortices that form along the shear layer between the flows during the high-momentum ratio event. The results indicate that the use of LSPIV and UAS is well-suited for capturing in detail mean surface patterns of flow at small confluences, but that characterization of evolving turbulent structures is limited by scale considerations related to structure size, image resolution, and camera instability. Complementary methods, including camera platforms mounted at fixed positions close to the water surface, provide opportunities to accurately characterize evolving turbulent flow structures in confluences.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sword, Charles Keith

A scanner system and method for acquisition of position-based ultrasonic inspection data are described. The scanner system includes an inspection probe and a first non-contact linear encoder having a first sensor and a first scale to track inspection probe position. The first sensor is positioned to maintain a continuous non-contact interface between the first sensor and the first scale and to maintain a continuous alignment of the first sensor with the inspection probe. The scanner system may be used to acquire two-dimensional inspection probe position data by including a second non-contact linear encoder having a second sensor and a secondmore » scale, the second sensor positioned to maintain a continuous non-contact interface between the second sensor and the second scale and to maintain a continuous alignment of the second sensor with the first sensor.« less

Connecting the snowpack to the internet of things: an IPv6 architecture for providing real-time measurements of hydrologic systems

NASA Astrophysics Data System (ADS)

Kerkez, B.; Zhang, Z.; Oroza, C.; Glaser, S. D.; Bales, R. C.

2012-12-01

We describe our improved, robust, and scalable architecture by which to rapidly instrument large-scale watersheds, while providing the resulting data in real-time. Our system consists of more than twenty wireless sensor networks and thousands of sensors, which will be deployed in the American River basin (5000 sq. km) of California. The core component of our system is known as a mote, a tiny, ultra-low-power, embedded wireless computer that can be used for any number of sensing applications. Our new generation of motes is equipped with IPv6 functionality, effectively giving each sensor in the field its own unique IP address, thus permitting users to remotely interact with the devices without going through intermediary services. Thirty to fifty motes will be deployed across 1-2 square kilometer regions to form a mesh-based wireless sensor network. Redundancy of local wireless links will ensure that data will always be able to traverse the network, even if hash wintertime conditions adversely affect some network nodes. These networks will be used to develop spatial estimates of a number of hydrologic parameters, focusing especially on snowpack. Each wireless sensor network has one main network controller, which is responsible with interacting with an embedded Linux computer to relay information across higher-powered, long-range wireless links (cell modems, satellite, WiFi) to neighboring networks and remote, offsite servers. The network manager is also responsible for providing an Internet connection to each mote. Data collected by the sensors can either be read directly by remote hosts, or stored on centralized servers for future access. With 20 such networks deployed in the American River, our system will comprise an unprecedented cyber-physical architecture for measuring hydrologic parameters in large-scale basins. The spatiotemporal density and real-time nature of the data is also expected to significantly improve operational hydrology and water resource management in the basin.

Gas sensors boosted by two-dimensional h-BN enabled transfer on thin substrate foils: towards wearable and portable applications.

PubMed

Ayari, Taha; Bishop, Chris; Jordan, Matthew B; Sundaram, Suresh; Li, Xin; Alam, Saiful; ElGmili, Youssef; Patriarche, Gilles; Voss, Paul L; Salvestrini, Jean Paul; Ougazzaden, Abdallah

2017-11-09

The transfer of GaN based gas sensors to foreign substrates provides a pathway to enhance sensor performance, lower the cost and extend the applications to wearable, mobile or disposable systems. The main keys to unlocking this pathway is to grow and fabricate the sensors on large h-BN surface and to transfer them to the flexible substrate without any degradation of the performances. In this work, we develop a new generation of AlGaN/GaN gas sensors with boosted performances on a low cost flexible substrate. We fabricate 2-inch wafer scale AlGaN/GaN gas sensors on sacrificial two-dimensional (2D) nano-layered h-BN without any delamination or cracks and subsequently transfer sensors to an acrylic surface on metallic foil. This technique results in a modification of relevant device properties, leading to a doubling of the sensitivity to NO 2 gas and a response time that is more than 6 times faster than before transfer. This new approach for GaN-based sensor design opens new avenues for sensor improvement via transfer to more suitable substrates, and is promising for next-generation wearable and portable opto-electronic devices.

Dual-Doppler lidar observation of horizontal convective rolls and near-surface streaks

NASA Astrophysics Data System (ADS)

Iwai, Hironori; Ishii, Shoken; Tsunematsu, Nobumitsu; Mizutani, Kohei; Murayama, Yasuhiro; Itabe, Toshikazu; Yamada, Izumi; Matayoshi, Naoki; Matsushima, Dai; Weiming, Sha; Yamazaki, Takeshi; Iwasaki, Toshiki

2008-07-01

Dual-Doppler lidar and heliborne sensors were used to investigate the three-dimensional (3D) structure of the wind field over Sendai Airport in June 2007. The 3D structures of several-hundred-meter-scale horizontal convective rolls (HCRs) in the sea-breeze layer were observed by the dual-Doppler lidar. The scale of the HCRs determined by the heliborne sensors roughly agreed with that determined by the dual-Doppler lidar. Analysis of the dual-Doppler lidar data showed that the region of upward flow in the HCRs originated in near-surface low-speed streaks. This structure is consistent with the results of large-eddy simulations of the atmospheric boundary layer. The aspect ratios of the HCRs were close to those predicted by linear theories.

Emerging tools for continuous nutrient monitoring networks: Sensors advancing science and water resources protection

USGS Publications Warehouse

Pellerin, Brian; Stauffer, Beth A; Young, Dwane A; Sullivan, Daniel J.; Bricker, Suzanne B.; Walbridge, Mark R; Clyde, Gerard A; Shaw, Denice M

2016-01-01

Sensors and enabling technologies are becoming increasingly important tools for water quality monitoring and associated water resource management decisions. In particular, nutrient sensors are of interest because of the well-known adverse effects of nutrient enrichment on coastal hypoxia, harmful algal blooms, and impacts to human health. Accurate and timely information on nutrient concentrations and loads is integral to strategies designed to minimize risk to humans and manage the underlying drivers of water quality impairment. Using nitrate sensors as an example, we highlight the types of applications in freshwater and coastal environments that are likely to benefit from continuous, real-time nutrient data. The concurrent emergence of new tools to integrate, manage and share large data sets is critical to the successful use of nutrient sensors and has made it possible for the field of continuous nutrient monitoring to rapidly move forward. We highlight several near-term opportunities for Federal agencies, as well as the broader scientific and management community, that will help accelerate sensor development, build and leverage sites within a national network, and develop open data standards and data management protocols that are key to realizing the benefits of a large-scale, integrated monitoring network. Investing in these opportunities will provide new information to guide management and policies designed to protect and restore our nation’s water resources.

Electrical Design and Evaluation of Asynchronous Serial Bus Communication Network of 48 Sensor Platform LSIs with Single-Ended I/O for Integrated MEMS-LSI Sensors.

PubMed

Shao, Chenzhong; Tanaka, Shuji; Nakayama, Takahiro; Hata, Yoshiyuki; Muroyama, Masanori

2018-01-15

For installing many sensors in a limited space with a limited computing resource, the digitization of the sensor output at the site of sensation has advantages such as a small amount of wiring, low signal interference and high scalability. For this purpose, we have developed a dedicated Complementary Metal-Oxide-Semiconductor (CMOS) Large-Scale Integration (LSI) (referred to as "sensor platform LSI") for bus-networked Micro-Electro-Mechanical-Systems (MEMS)-LSI integrated sensors. In this LSI, collision avoidance, adaptation and event-driven functions are simply implemented to relieve data collision and congestion in asynchronous serial bus communication. In this study, we developed a network system with 48 sensor platform LSIs based on Printed Circuit Board (PCB) in a backbone bus topology with the bus length being 2.4 m. We evaluated the serial communication performance when 48 LSIs operated simultaneously with the adaptation function. The number of data packets received from each LSI was almost identical, and the average sampling frequency of 384 capacitance channels (eight for each LSI) was 73.66 Hz.

Sensor selection cost optimisation for tracking structurally cyclic systems: a P-order solution

NASA Astrophysics Data System (ADS)

Doostmohammadian, M.; Zarrabi, H.; Rabiee, H. R.

2017-08-01

Measurements and sensing implementations impose certain cost in sensor networks. The sensor selection cost optimisation is the problem of minimising the sensing cost of monitoring a physical (or cyber-physical) system. Consider a given set of sensors tracking states of a dynamical system for estimation purposes. For each sensor assume different costs to measure different (realisable) states. The idea is to assign sensors to measure states such that the global cost is minimised. The number and selection of sensor measurements need to ensure the observability to track the dynamic state of the system with bounded estimation error. The main question we address is how to select the state measurements to minimise the cost while satisfying the observability conditions. Relaxing the observability condition for structurally cyclic systems, the main contribution is to propose a graph theoretic approach to solve the problem in polynomial time. Note that polynomial time algorithms are suitable for large-scale systems as their running time is upper-bounded by a polynomial expression in the size of input for the algorithm. We frame the problem as a linear sum assignment with solution complexity of ?.

Autonomous solutions for powering wireless sensor nodes in rivers

NASA Astrophysics Data System (ADS)

Kamenar, E.; Maćešić, S.; Gregov, G.; Blažević, D.; Zelenika, S.; Marković, K.; Glažar, V.

2015-05-01

There is an evident need for monitoring pollutants and/or other conditions in river flows via wireless sensor networks. In a typical wireless sensor network topography, a series of sensor nodes is to be deployed in the environment, all wirelessly connected to each other and/or their gateways. Each sensor node is composed of active electronic devices that have to be constantly powered. In general, batteries can be used for this purpose, but problems may occur when they have to be replaced. In the case of large networks, when sensor nodes can be placed in hardly accessible locations, energy harvesting can thus be a viable powering solution. The possibility to use three different small-scale river flow energy harvesting principles is hence thoroughly studied in this work: a miniaturized underwater turbine, a so-called `piezoelectric eel' and a hybrid turbine solution coupled with a rigid piezoelectric beam. The first two concepts are then validated experimentally in laboratory as well as in real river conditions. The concept of the miniaturised hydro-generator is finally embedded into the actual wireless sensor node system and its functionality is confirmed.

Principles and practical implementation for high resolution multi-sensor QPE

NASA Astrophysics Data System (ADS)

Chandra, C. V.; Lim, S.; Cifelli, R.

2011-12-01

The multi-sensor Quantitative Precipitation Estimation (MPE) is a principle and a practical concept and is becoming a well-known term in the scientific circles of hydrology and atmospheric science. The main challenge in QPE is that precipitation is a highly variable quantity with extensive spatial and temporal variability at multiple scales. There are MPE products produced from satellites, radars, models and ground sensors. There are MPE products at global scale (Heinemann et al. 2002), continental scale (Seo et al. 2010; Zhang et al. 2011) and regional scale (Kitzmiller et al. 2011). Lots of the MPE products are used to alleviate the problems of one type of sensor by another. Some multi-sensor products are used to move across scales. This paper looks at a comprehensive view of the "concept of multi sensor precipitation estimate", from different perspectives. This paper delineates the MPE problem into three categories namely, a) Scale based MPE, b) MPE for accuracy enhancement and coverage and c) Integrative across scales. For example, by introducing dual polarization radar data to the MPE system, QPE can be improved significantly. In last decade, dual polarization radars are becoming an important tool for QPE in operational networks. Dual polarization radars offer an advantage to interpret more accurate physical models by providing information of the size, shape, phase and orientation of hydrometers (Bringi and Chandrasekar 2001). In addition, these systems have the ability to provide measurements that are immune to absolute radar calibration and partial beam blockage as well as help in data quality enhancement. By integrating these characteristics of dual polarization radar, QPE performance can be improved in comparison of single polarization radar based QPE (Cifelli and Chandrasekar 2010). Dual-polarization techniques have been applied to S and C band radar systems for several decades and higher frequency system such as X band are now widely available to the radar community. One solution to the dilemma of precipitation variability across scales can be to supplement existing long-range radar networks with short-range higher frequency systems (X band). The smaller X band systems provide more portability and higher data resolution, and networks of these systems may be a cost-effective option for improved rainfall estimation for radar networks with large separation distances (McLaughlin et al. 2009). This paper will describe the principles of the MPE concept and implementation issues of within the context of the classification described above.

Online estimation of the wavefront outer scale profile from adaptive optics telemetry

NASA Astrophysics Data System (ADS)

Guesalaga, A.; Neichel, B.; Correia, C. M.; Butterley, T.; Osborn, J.; Masciadri, E.; Fusco, T.; Sauvage, J.-F.

2017-02-01

We describe an online method to estimate the wavefront outer scale profile, L0(h), for very large and future extremely large telescopes. The stratified information on this parameter impacts the estimation of the main turbulence parameters [turbulence strength, Cn2(h); Fried's parameter, r0; isoplanatic angle, θ0; and coherence time, τ0) and determines the performance of wide-field adaptive optics (AO) systems. This technique estimates L0(h) using data from the AO loop available at the facility instruments by constructing the cross-correlation functions of the slopes between two or more wavefront sensors, which are later fitted to a linear combination of the simulated theoretical layers having different altitudes and outer scale values. We analyse some limitations found in the estimation process: (I) its insensitivity to large values of L0(h) as the telescope becomes blind to outer scales larger than its diameter; (II) the maximum number of observable layers given the limited number of independent inputs that the cross-correlation functions provide and (III) the minimum length of data required for a satisfactory convergence of the turbulence parameters without breaking the assumption of statistical stationarity of the turbulence. The method is applied to the Gemini South multiconjugate AO system that comprises five wavefront sensors and two deformable mirrors. Statistics of L0(h) at Cerro Pachón from data acquired during 3 yr of campaigns show interesting resemblance to other independent results in the literature. A final analysis suggests that the impact of error sources will be substantially reduced in instruments of the next generation of giant telescopes.

A review of sensing technologies for small and large-scale touch panels

NASA Astrophysics Data System (ADS)

Akhtar, Humza; Kemao, Qian; Kakarala, Ramakrishna

2017-06-01

A touch panel is an input device for human computer interaction. It consists of a network of sensors, a sampling circuit and a micro controller for detecting and locating a touch input. Touch input can come from either finger or stylus depending upon the type of touch technology. These touch panels provide an intuitive and collaborative workspace so that people can perform various tasks with the use of their fingers instead of traditional input devices like keyboard and mouse. Touch sensing technology is not new. At the time of this writing, various technologies are available in the market and this paper reviews the most common ones. We review traditional designs and sensing algorithms for touch technology. We also observe that due to its various strengths, capacitive touch will dominate the large-scale touch panel industry in years to come. In the end, we discuss the motivation for doing academic research on large-scale panels.

Citizen sensors for SHM: use of accelerometer data from smartphones.

PubMed

Feng, Maria; Fukuda, Yoshio; Mizuta, Masato; Ozer, Ekin

2015-01-29

Ubiquitous smartphones have created a significant opportunity to form a low-cost wireless Citizen Sensor network and produce big data for monitoring structural integrity and safety under operational and extreme loads. Such data are particularly useful for rapid assessment of structural damage in a large urban setting after a major event such as an earthquake. This study explores the utilization of smartphone accelerometers for measuring structural vibration, from which structural health and post-event damage can be diagnosed. Widely available smartphones are tested under sinusoidal wave excitations with frequencies in the range relevant to civil engineering structures. Large-scale seismic shaking table tests, observing input ground motion and response of a structural model, are carried out to evaluate the accuracy of smartphone accelerometers under operational, white-noise and earthquake excitations of different intensity. Finally, the smartphone accelerometers are tested on a dynamically loaded bridge. The extensive experiments show satisfactory agreements between the reference and smartphone sensor measurements in both time and frequency domains, demonstrating the capability of the smartphone sensors to measure structural responses ranging from low-amplitude ambient vibration to high-amplitude seismic response. Encouraged by the results of this study, the authors are developing a citizen-engaging and data-analytics crowdsourcing platform towards a smartphone-based Citizen Sensor network for structural health monitoring and post-event damage assessment applications.

3D-FBK Pixel Sensors: Recent Beam Tests Results with Irradiated Devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Micelli, A.; /INFN, Trieste /Udine U.; Helle, K.

2012-04-30

The Pixel Detector is the innermost part of the ATLAS experiment tracking device at the Large Hadron Collider, and plays a key role in the reconstruction of the primary vertices from the collisions and secondary vertices produced by short-lived particles. To cope with the high level of radiation produced during the collider operation, it is planned to add to the present three layers of silicon pixel sensors which constitute the Pixel Detector, an additional layer (Insertable B-Layer, or IBL) of sensors. 3D silicon sensors are one of the technologies which are under study for the IBL. 3D silicon technology ismore » an innovative combination of very-large-scale integration and Micro-Electro-Mechanical-Systems where electrodes are fabricated inside the silicon bulk instead of being implanted on the wafer surfaces. 3D sensors, with electrodes fully or partially penetrating the silicon substrate, are currently fabricated at different processing facilities in Europe and USA. This paper reports on the 2010 June beam test results for irradiated 3D devices produced at FBK (Trento, Italy). The performance of these devices, all bump-bonded with the ATLAS pixel FE-I3 read-out chip, is compared to that observed before irradiation in a previous beam test.« less

Ultra-high gain diffusion-driven organic transistor.

PubMed

Torricelli, Fabrizio; Colalongo, Luigi; Raiteri, Daniele; Kovács-Vajna, Zsolt Miklós; Cantatore, Eugenio

2016-02-01

Emerging large-area technologies based on organic transistors are enabling the fabrication of low-cost flexible circuits, smart sensors and biomedical devices. High-gain transistors are essential for the development of large-scale circuit integration, high-sensitivity sensors and signal amplification in sensing systems. Unfortunately, organic field-effect transistors show limited gain, usually of the order of tens, because of the large contact resistance and channel-length modulation. Here we show a new organic field-effect transistor architecture with a gain larger than 700. This is the highest gain ever reported for organic field-effect transistors. In the proposed organic field-effect transistor, the charge injection and extraction at the metal-semiconductor contacts are driven by the charge diffusion. The ideal conditions of ohmic contacts with negligible contact resistance and flat current saturation are demonstrated. The approach is general and can be extended to any thin-film technology opening unprecedented opportunities for the development of high-performance flexible electronics.

Ultra-high gain diffusion-driven organic transistor

NASA Astrophysics Data System (ADS)

Torricelli, Fabrizio; Colalongo, Luigi; Raiteri, Daniele; Kovács-Vajna, Zsolt Miklós; Cantatore, Eugenio

2016-02-01

Emerging large-area technologies based on organic transistors are enabling the fabrication of low-cost flexible circuits, smart sensors and biomedical devices. High-gain transistors are essential for the development of large-scale circuit integration, high-sensitivity sensors and signal amplification in sensing systems. Unfortunately, organic field-effect transistors show limited gain, usually of the order of tens, because of the large contact resistance and channel-length modulation. Here we show a new organic field-effect transistor architecture with a gain larger than 700. This is the highest gain ever reported for organic field-effect transistors. In the proposed organic field-effect transistor, the charge injection and extraction at the metal-semiconductor contacts are driven by the charge diffusion. The ideal conditions of ohmic contacts with negligible contact resistance and flat current saturation are demonstrated. The approach is general and can be extended to any thin-film technology opening unprecedented opportunities for the development of high-performance flexible electronics.

Static characterization of a soft elastomeric capacitor for non destructive evaluation applications

NASA Astrophysics Data System (ADS)

Saleem, Hussam; Laflamme, Simon; Zhang, Huanhuan; Geiger, Randall; Kessler, Michael; Rajan, Krishna

2014-02-01

A large and flexible strain transducer consisting of a soft elastomeric capacitor (SEC) has been proposed by the authors. Arranged in a network setup, the sensing strategy offers tremendous potential at conducting non-destructive evaluation of large-scale surfaces. In prior work, the authors have demonstrated the performance of the sensor at tracking strain history, localizing cracks, and detecting vibration signatures. In this paper, we characterize the static performance of the proposed SEC. The characterization includes sensitivity of the signal, and temperature and humidity dependences. Tests are conducted on a simply supported aluminum beam subjected to bending as well as on a free standing sensor. The performance of the SEC is compared against off-the-shelf resistance-based strain gauges with resolution of 1 μɛ. A sensitivity of 1190 pF/ɛ is obtained experimentally, in agreement with theory. Results also show the sensor linearity over the given level of strain, showing the promise of the SEC at monitoring of surface strain.

Integrated Joule switches for the control of current dynamics in parallel superconducting strips

NASA Astrophysics Data System (ADS)

Casaburi, A.; Heath, R. M.; Cristiano, R.; Ejrnaes, M.; Zen, N.; Ohkubo, M.; Hadfield, R. H.

2018-06-01

Understanding and harnessing the physics of the dynamic current distribution in parallel superconducting strips holds the key to creating next generation sensors for single molecule and single photon detection. Non-uniformity in the current distribution in parallel superconducting strips leads to low detection efficiency and unstable operation, preventing the scale up to large area sensors. Recent studies indicate that non-uniform current distributions occurring in parallel strips can be understood and modeled in the framework of the generalized London model. Here we build on this important physical insight, investigating an innovative design with integrated superconducting-to-resistive Joule switches to break the superconducting loops between the strips and thus control the current dynamics. Employing precision low temperature nano-optical techniques, we map the uniformity of the current distribution before- and after the resistive strip switching event, confirming the effectiveness of our design. These results provide important insights for the development of next generation large area superconducting strip-based sensors.

The Cramér-Rao Bounds and Sensor Selection for Nonlinear Systems with Uncertain Observations.

PubMed

Wang, Zhiguo; Shen, Xiaojing; Wang, Ping; Zhu, Yunmin

2018-04-05

This paper considers the problems of the posterior Cramér-Rao bound and sensor selection for multi-sensor nonlinear systems with uncertain observations. In order to effectively overcome the difficulties caused by uncertainty, we investigate two methods to derive the posterior Cramér-Rao bound. The first method is based on the recursive formula of the Cramér-Rao bound and the Gaussian mixture model. Nevertheless, it needs to compute a complex integral based on the joint probability density function of the sensor measurements and the target state. The computation burden of this method is relatively high, especially in large sensor networks. Inspired by the idea of the expectation maximization algorithm, the second method is to introduce some 0-1 latent variables to deal with the Gaussian mixture model. Since the regular condition of the posterior Cramér-Rao bound is unsatisfied for the discrete uncertain system, we use some continuous variables to approximate the discrete latent variables. Then, a new Cramér-Rao bound can be achieved by a limiting process of the Cramér-Rao bound of the continuous system. It avoids the complex integral, which can reduce the computation burden. Based on the new posterior Cramér-Rao bound, the optimal solution of the sensor selection problem can be derived analytically. Thus, it can be used to deal with the sensor selection of a large-scale sensor networks. Two typical numerical examples verify the effectiveness of the proposed methods.

Magnetically-coupled microcalorimeter arrays for x-ray astrophysics

NASA Astrophysics Data System (ADS)

Bandler, Simon

The "X-ray Surveyor" has been listed by NASA as one of the four major large mission concepts to be studied in the next Astrophysics Decadal Review in its preliminary list of large concepts. One of the key instruments on such a mission would be a very large format X-ray microcalorimeter array, with an array size of greater than 100 thousand pixels. Magnetically-coupled microcalorimeters (MCC) are one of the technologies with the greatest potential to meet the requirements of this mission, and this proposal is one to carry out research specifically to reach the goals of this vision. The "X-ray Surveyor" is a concept for a future mission that will make X-ray observations that are instrumental to understanding the quickly emerging population of galaxies and supermassive black holes at z ~10. The observations will trace the formation of galaxies and their assembly into large-scale structures starting from the earliest possible epochs. This mission would be observing baryons and large-scale physical processes outside of the very densest regions in the local Universe. This can be achieved with an X-ray observatory with similar angular resolution as Chandra but with significantly improved optic area and detector sensitivity. Chandra-scale angular resolution (1" or better) is essential in building more powerful, higher throughput observatories to avoid source confusion and remain photon-limited rather than background-limited. A prime consideration for the microcalorimeter camera on this type of mission is maintaining ~ 1 arcsec spatial resolution over the largest possible field of view, even if this means a slight trade-off against the spectral resolution. A uniform array of 1" pixels covering at least 5'x5' field of view is desired. To reduce the number of sensors read out, in geometries where extremely fine pitch (~50 microns) is desired, the most promising technologies are those in which a thermal sensor such an MCC can read out a sub-array of 20-25 individual 1'• pixels. Projections based on the current state of this technology indicate that less than 5 eV energy resolution can be achieved with this sort of geometry. Theoretically, magnetically-coupled microcalorimeters are well-equipped to achieve the very highest energy resolutions, especially when several absorbers are attached to each sensor, increasing the heat capacity. This program will build upon the work carried out by our group on metallic magnetic calorimeters (MMC) and Magnetic penetration thermometers (MPT) in the antecedent program. In this program we will carry out development in three main areas. First, we will develop sensor geometries that are optimized for reading out sub-arrays of pixels with a single sensor of the type that is likely desired by the "X-ray Surveyor". Second, we will further develop large-format arraying prototypes with the engineering of wiring-pixel approaches that are scalable to the large-format arrays that are needed. Third, we will develop the read-out technology that will be necessary, which utilizes the next generation of X-ray microcalorimeter read-out approach, a microwave multiplexing readout.

GPU-based Space Situational Awareness Simulation utilising Parallelism for Enhanced Multi-sensor Management

NASA Astrophysics Data System (ADS)

Hobson, T.; Clarkson, V.

2012-09-01

As a result of continual space activity since the 1950s, there are now a large number of man-made Resident Space Objects (RSOs) orbiting the Earth. Because of the large number of items and their relative speeds, the possibility of destructive collisions involving important space assets is now of significant concern to users and operators of space-borne technologies. As a result, a growing number of international agencies are researching methods for improving techniques to maintain Space Situational Awareness (SSA). Computer simulation is a method commonly used by many countries to validate competing methodologies prior to full scale adoption. The use of supercomputing and/or reduced scale testing is often necessary to effectively simulate such a complex problem on todays computers. Recently the authors presented a simulation aimed at reducing the computational burden by selecting the minimum level of fidelity necessary for contrasting methodologies and by utilising multi-core CPU parallelism for increased computational efficiency. The resulting simulation runs on a single PC while maintaining the ability to effectively evaluate competing methodologies. Nonetheless, the ability to control the scale and expand upon the computational demands of the sensor management system is limited. In this paper, we examine the advantages of increasing the parallelism of the simulation by means of General Purpose computing on Graphics Processing Units (GPGPU). As many sub-processes pertaining to SSA management are independent, we demonstrate how parallelisation via GPGPU has the potential to significantly enhance not only research into techniques for maintaining SSA, but also to enhance the level of sophistication of existing space surveillance sensors and sensor management systems. Nonetheless, the use of GPGPU imposes certain limitations and adds to the implementation complexity, both of which require consideration to achieve an effective system. We discuss these challenges and how they can be overcome. We further describe an application of the parallelised system where visibility prediction is used to enhance sensor management. This facilitates significant improvement in maximum catalogue error when RSOs become temporarily unobservable. The objective is to demonstrate the enhanced scalability and increased computational capability of the system.

Chemiresistive Graphene Sensors for Ammonia Detection.

PubMed

Mackin, Charles; Schroeder, Vera; Zurutuza, Amaia; Su, Cong; Kong, Jing; Swager, Timothy M; Palacios, Tomás

2018-05-09

The primary objective of this work is to demonstrate a novel sensor system as a convenient vehicle for scaled-up repeatability and the kinetic analysis of a pixelated testbed. This work presents a sensor system capable of measuring hundreds of functionalized graphene sensors in a rapid and convenient fashion. The sensor system makes use of a novel array architecture requiring only one sensor per pixel and no selector transistor. The sensor system is employed specifically for the evaluation of Co(tpfpp)ClO 4 functionalization of graphene sensors for the detection of ammonia as an extension of previous work. Co(tpfpp)ClO 4 treated graphene sensors were found to provide 4-fold increased ammonia sensitivity over pristine graphene sensors. Sensors were also found to exhibit excellent selectivity over interfering compounds such as water and common organic solvents. The ability to monitor a large sensor array with 160 pixels provides insights into performance variations and reproducibility-critical factors in the development of practical sensor systems. All sensors exhibit the same linearly related responses with variations in response exhibiting Gaussian distributions, a key finding for variation modeling and quality engineering purposes. The mean correlation coefficient between sensor responses was found to be 0.999 indicating highly consistent sensor responses and excellent reproducibility of Co(tpfpp)ClO 4 functionalization. A detailed kinetic model is developed to describe sensor response profiles. The model consists of two adsorption mechanisms-one reversible and one irreversible-and is shown capable of fitting experimental data with a mean percent error of 0.01%.

The detection of improvised nonmilitary peroxide based explosives using a titania nanotube array sensor.

PubMed

Banerjee, Subarna; Mohapatra, Susanta K; Misra, Mano; Mishra, Indu B

2009-02-18

There is a critical need to develop an efficient, reliable and highly selective sensor for the detection of improvised nonmilitary explosives. This paper describes the utilization of functionalized titania nanotube arrays for sensing improvised organic peroxide explosives such as triacetone triperoxide (TATP). TATP forms complexes with titania nanotube arrays (prepared by anodization and sensitized with zinc ions) and thus affects the electron state of the nanosensing device, which is signaled as a change in current of the overall nanotube material. The response is rapid and a signal of five to eight orders of magnitude is observed. These nanotube array sensors can be used as hand-held miniaturized devices as well as large scale portable units for military and homeland security applications.

Localization of CO2 Leakage from a Circular Hole on a Flat-Surface Structure Using a Circular Acoustic Emission Sensor Array

PubMed Central

Cui, Xiwang; Yan, Yong; Guo, Miao; Han, Xiaojuan; Hu, Yonghui

2016-01-01

Leak localization is essential for the safety and maintenance of storage vessels. This study proposes a novel circular acoustic emission sensor array to realize the continuous CO2 leak localization from a circular hole on the surface of a large storage vessel in a carbon capture and storage system. Advantages of the proposed array are analyzed and compared with the common sparse arrays. Experiments were carried out on a laboratory-scale stainless steel plate and leak signals were obtained from a circular hole in the center of this flat-surface structure. In order to reduce the influence of the ambient noise and dispersion of the acoustic wave on the localization accuracy, ensemble empirical mode decomposition is deployed to extract the useful leak signal. The time differences between the signals from the adjacent sensors in the array are calculated through correlation signal processing before estimating the corresponding distance differences between the sensors. A hyperbolic positioning algorithm is used to identify the location of the circular leak hole. Results show that the circular sensor array has very good directivity toward the circular leak hole. Furthermore, an optimized method is proposed by changing the position of the circular sensor array on the flat-surface structure or adding another circular sensor array to identify the direction of the circular leak hole. Experiential results obtained on a 100 cm × 100 cm stainless steel plate demonstrate that the full-scale error in the leak localization is within 0.6%. PMID:27869765

Comparing catchment hydrologic response to a regional storm using specific conductivity sensors

USGS Publications Warehouse

Inserillo, Ashley; Green, Mark B.; Shanley, James B.; Boyer, Joseph

2017-01-01

A better understanding of stormwater generation and solute sources is needed to improve the protection of aquatic ecosystems, infrastructure, and human health from large runoff events. Much of our understanding of water and solutes produced during stormflow comes from studies of individual, small headwater catchments. This study compared many different types of catchments during a single large event to help isolate landscape controls on streamwater and solute generation, including human-impacted land cover. We used a distributed network of specific electrical conductivity sensors to trace storm response during the post-tropical cyclone Sandy event of October 2012 at 29 catchments across the state of New Hampshire. A citizen science sensor network, Lotic Volunteer for Temperature, Electrical Conductivity, and Stage, provided a unique opportunity to investigate high-temporal resolution stream behavior at a broad spatial scale. Three storm response metrics were analyzed in this study: (a) fraction of new water contributing to the hydrograph; (b) presence of first flush (mobilization of solutes during the beginning of the rain event); and (c) magnitude of first flush. We compared new water and first flush to 64 predictor attributes related to land cover, soil, topography, and precipitation. The new water fraction was positively correlated with low and medium intensity development in the catchment and riparian buffers and with the precipitation from a rain event 9 days prior to Sandy. The presence of first flush was most closely related (positively) to soil organic matter. Magnitude of first flush was not strongly related to any of the catchment variables. Our results highlight the potentially important role of human landscape modification in runoff generation at multiple spatial scales and the lack of a clear role in solute flushing. Further development of regional-scale in situ sensor networks will provide better understanding of stormflow and solute generation across a wide range of landscape conditions.

A comparison of long-term parallel measurements of sunshine duration obtained with a Campbell-Stokes sunshine recorder and two automated sunshine sensors

NASA Astrophysics Data System (ADS)

Baumgartner, D. J.; Pötzi, W.; Freislich, H.; Strutzmann, H.; Veronig, A. M.; Foelsche, U.; Rieder, H. E.

2017-06-01

In recent decades, automated sensors for sunshine duration (SD) measurements have been introduced in meteorological networks, thereby replacing traditional instruments, most prominently the Campbell-Stokes (CS) sunshine recorder. Parallel records of automated and traditional SD recording systems are rare. Nevertheless, such records are important to understand the differences/similarities in SD totals obtained with different instruments and how changes in monitoring device type affect the homogeneity of SD records. This study investigates the differences/similarities in parallel SD records obtained with a CS and two automated SD sensors between 2007 and 2016 at the Kanzelhöhe Observatory, Austria. Comparing individual records of daily SD totals, we find differences of both positive and negative sign, with smallest differences between the automated sensors. The larger differences between CS-derived SD totals and those from automated sensors can be attributed (largely) to the higher sensitivity threshold of the CS instrument. Correspondingly, the closest agreement among all sensors is found during summer, the time of year when sensitivity thresholds are least critical. Furthermore, we investigate the performance of various models to create the so-called sensor-type-equivalent (STE) SD records. Our analysis shows that regression models including all available data on daily (or monthly) time scale perform better than simple three- (or four-) point regression models. Despite general good performance, none of the considered regression models (of linear or quadratic form) emerges as the "optimal" model. Although STEs prove useful for relating SD records of individual sensors on daily/monthly time scales, this does not ensure that STE (or joint) records can be used for trend analysis.

Methodology for the design, production, and test of plastic optical displacement sensors

NASA Astrophysics Data System (ADS)

Rahlves, Maik; Kelb, Christian; Reithmeier, Eduard; Roth, Bernhard

2016-08-01

Optical displacement sensors made entirely from plastic materials offer various advantages such as biocompatibility and high flexibility compared to their commonly used electrical and glass-based counterparts. In addition, various low-cost and large-scale fabrication techniques can potentially be utilized for their fabrication. In this work we present a toolkit for the design, production, and test of such sensors. Using the introduced methods, we demonstrate the development of a simple all-optical displacement sensor based on multimode plastic waveguides. The system consists of polymethylmethacrylate and cyclic olefin polymer which serve as cladding and core materials, respectively. We discuss several numerical models which are useful for the design and simulation of the displacement sensors as well as two manufacturing methods capable of mass-producing such devices. Prior to fabrication, the sensor layout and performance are evaluated by means of a self-implemented ray-optical simulation which can be extended to various other types of sensor concepts. Furthermore, we discuss optical and mechanical test procedures as well as a high-precision tensile testing machine especially suited for the characterization of the opto-mechanical performance of such plastic optical displacement sensors.

Data Intensive Systems (DIS) Benchmark Performance Summary

DTIC Science & Technology

2003-08-01

models assumed by today’s conventional architectures. Such applications include model- based Automatic Target Recognition (ATR), synthetic aperture...radar (SAR) codes, large scale dynamic databases/battlefield integration, dynamic sensor- based processing, high-speed cryptanalysis, high speed...distributed interactive and data intensive simulations, data-oriented problems characterized by pointer- based and other highly irregular data structures

TDM interrogation of intensity-modulated USFBGs network based on multichannel lasers.

PubMed

Rohollahnejad, Jalal; Xia, Li; Cheng, Rui; Ran, Yanli; Rahubadde, Udaya; Zhou, Jiaao; Zhu, Lin

2017-01-23

We report a large-scale multi-channel fiber sensing network, where ultra-short FBGs (USFBGs) instead of conventional narrow-band ultra-weak FBGs are used as the sensors. In the time division multiplexing scheme of the network, each grating response is resolved as three adjacent discrete peaks. The central wavelengths of USFBGs are tracked with the differential detection, which is achieved by calculating the peak-to-peak ratio of two maximum peaks. Compared with previous large-scale hybrid multiplexing sensing networks (e.g., WDM/TDM) which typically have relatively low interrogation speed and very high complexity, the proposed system can achieve interrogation of all channel sensors through very fast and simple intensity measurements with a broad dynamic range. A proof-of-concept experiment with twenty USFBGs, at two wavelength channels, was performed and a fast static strain measurements were demonstrated, with a high average sensitivity of ~0.54dB/µƐ and wide dynamic range of over ~3000µƐ. The channel to channel switching time was 10ms and total network interrogation time was 50ms.

Urban structure analysis of mega city Mexico City using multisensoral remote sensing data

NASA Astrophysics Data System (ADS)

Taubenböck, H.; Esch, T.; Wurm, M.; Thiel, M.; Ullmann, T.; Roth, A.; Schmidt, M.; Mehl, H.; Dech, S.

2008-10-01

Mega city Mexico City is ranked the third largest urban agglomeration to date around the globe. The large extension as well as dynamic urban transformation and sprawl processes lead to a lack of up-to-date and area-wide data and information to measure, monitor, and understand the urban situation. This paper focuses on the capabilities of multisensoral remotely sensed data to provide a broad range of products derived from one scientific field - remote sensing - to support urban managing and planning. Therefore optical data sets from the Landsat and Quickbird sensors as well as radar data from the Shuttle Radar Topography Mission (SRTM) and the TerraSAR-X sensor are utilised. Using the multi-sensoral data sets the analysis are scale-dependent. On the one hand change detection on city level utilising the derived urban footprints enables to monitor and to assess spatiotemporal urban transformation, areal dimension of urban sprawl, its direction, and the built-up density distribution over time. On the other hand, structural characteristics of an urban landscape - the alignment and types of buildings, streets and open spaces - provide insight in the very detailed physical pattern of urban morphology on higher scale. The results show high accuracies of the derived multi-scale products. The multi-scale analysis allows quantifying urban processes and thus leading to an assessment and interpretation of urban trends.

Learning Activity Predictors from Sensor Data: Algorithms, Evaluation, and Applications.

PubMed

Minor, Bryan; Doppa, Janardhan Rao; Cook, Diane J

2017-12-01

Recent progress in Internet of Things (IoT) platforms has allowed us to collect large amounts of sensing data. However, there are significant challenges in converting this large-scale sensing data into decisions for real-world applications. Motivated by applications like health monitoring and intervention and home automation we consider a novel problem called Activity Prediction , where the goal is to predict future activity occurrence times from sensor data. In this paper, we make three main contributions. First, we formulate and solve the activity prediction problem in the framework of imitation learning and reduce it to a simple regression learning problem. This approach allows us to leverage powerful regression learners that can reason about the relational structure of the problem with negligible computational overhead. Second, we present several metrics to evaluate activity predictors in the context of real-world applications. Third, we evaluate our approach using real sensor data collected from 24 smart home testbeds. We also embed the learned predictor into a mobile-device-based activity prompter and evaluate the app for 9 participants living in smart homes. Our results indicate that our activity predictor performs better than the baseline methods, and offers a simple approach for predicting activities from sensor data.

Convection of wall shear stress events in a turbulent boundary layer

NASA Astrophysics Data System (ADS)

Pabon, Rommel; Mills, David; Ukeiley, Lawrence; Sheplak, Mark

2017-11-01

The fluctuating wall shear stress is measured in a zero pressure gradient turbulent boundary layer of Reτ 1700 simultaneously with velocity measurements using either hot-wire anemometry or particle image velocimetry. These experiments elucidate the patterns of large scale structures in a single point measurement of the wall shear stress, as well as their convection velocity at the wall. The wall shear stress sensor is a CS-A05 one-dimensional capacitice floating element from Interdisciplinary Consulting Corp. It has a nominal bandwidth from DC to 5 kHz and a floating element size of 1 mm in the principal sensing direction (streamwise) and 0.2 mm in the cross direction (spanwise), allowing the large scales to be well resolved in the current experimental conditions. In addition, a two sensor array of CS-A05 aligned in the spanwise direction with streamwise separations O (δ) is utilized to capture the convection velocity of specific scales of the shear stress through a bandpass filter and peaks in the correlation. Thus, an average wall normal position for the corresponding convecting event can be inferred at least as high as the equivalent local streamwise velocity. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1315138.

Nonlinear Dynamic Model-Based Multiobjective Sensor Network Design Algorithm for a Plant with an Estimator-Based Control System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paul, Prokash; Bhattacharyya, Debangsu; Turton, Richard

Here, a novel sensor network design (SND) algorithm is developed for maximizing process efficiency while minimizing sensor network cost for a nonlinear dynamic process with an estimator-based control system. The multiobjective optimization problem is solved following a lexicographic approach where the process efficiency is maximized first followed by minimization of the sensor network cost. The partial net present value, which combines the capital cost due to the sensor network and the operating cost due to deviation from the optimal efficiency, is proposed as an alternative objective. The unscented Kalman filter is considered as the nonlinear estimator. The large-scale combinatorial optimizationmore » problem is solved using a genetic algorithm. The developed SND algorithm is applied to an acid gas removal (AGR) unit as part of an integrated gasification combined cycle (IGCC) power plant with CO 2 capture. Due to the computational expense, a reduced order nonlinear model of the AGR process is identified and parallel computation is performed during implementation.« less

Distributed Fiber-Optic Sensors for Vibration Detection

PubMed Central

Liu, Xin; Jin, Baoquan; Bai, Qing; Wang, Yu; Wang, Dong; Wang, Yuncai

2016-01-01

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. Optical parameters such as light intensity, phase, polarization state, or light frequency will change when external vibration is applied on the sensing fiber. In this paper, various technologies of distributed fiber-optic vibration sensing are reviewed, from interferometric sensing technology, such as Sagnac, Mach–Zehnder, and Michelson, to backscattering-based sensing technology, such as phase-sensitive optical time domain reflectometer, polarization-optical time domain reflectometer, optical frequency domain reflectometer, as well as some combinations of interferometric and backscattering-based techniques. Their operation principles are presented and recent research efforts are also included. Finally, the applications of distributed fiber-optic vibration sensors are summarized, which mainly include structural health monitoring and perimeter security, etc. Overall, distributed fiber-optic vibration sensors possess the advantages of large-scale monitoring, good concealment, excellent flexibility, and immunity to electromagnetic interference, and thus show considerable potential for a variety of practical applications. PMID:27472334

Scalable Low-Cost Fabrication of Disposable Paper Sensors for DNA Detection

PubMed Central

2015-01-01

Controlled integration of features that enhance the analytical performance of a sensor chip is a challenging task in the development of paper sensors. A critical issue in the fabrication of low-cost biosensor chips is the activation of the device surface in a reliable and controllable manner compatible with large-scale production. Here, we report stable, well-adherent, and repeatable site-selective deposition of bioreactive amine functionalities and biorepellant polyethylene glycol-like (PEG) functionalities on paper sensors by aerosol-assisted, atmospheric-pressure, plasma-enhanced chemical vapor deposition. This approach requires only 20 s of deposition time, compared to previous reports on cellulose functionalization, which takes hours. A detailed analysis of the near-edge X-ray absorption fine structure (NEXAFS) and its sensitivity to the local electronic structure of the carbon and nitrogen functionalities. σ*, π*, and Rydberg transitions in C and N K-edges are presented. Application of the plasma-processed paper sensors in DNA detection is also demonstrated. PMID:25423585

Scalable Low-Cost Fabrication of Disposable Paper Sensors for DNA Detection

DOE PAGES

Gandhiraman, Ram P.; Nordlund, Dennis; Jayan, Vivek; ...

2014-11-25

Controlled integration of features that enhance the analytical performance of a sensor chip is a challenging task in the development of paper sensors. A critical issue in the fabrication of low-cost biosensor chips is the activation of the device surface in a reliable and controllable manner compatible with large-scale production. Here, we report stable, well-adherent, and repeatable site-selective deposition of bioreactive amine functionalities and biorepellant polyethylene glycol-like (PEG) functionalities on paper sensors by aerosol-assisted, atmospheric-pressure, plasma-enhanced chemical vapor deposition. This approach requires only 20 s of deposition time, compared to previous reports on cellulose functionalization, which takes hours. We presentmore » a detailed analysis of the near-edge X-ray absorption fine structure (NEXAFS) and its sensitivity to the local electronic structure of the carbon and nitrogen functionalities. σ*, π*, and Rydberg transitions in C and N K-edges. Lastly, application of the plasma-processed paper sensors in DNA detection is also demonstrated.« less

Distributed Fiber-Optic Sensors for Vibration Detection.

PubMed

Liu, Xin; Jin, Baoquan; Bai, Qing; Wang, Yu; Wang, Dong; Wang, Yuncai

2016-07-26

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. Optical parameters such as light intensity, phase, polarization state, or light frequency will change when external vibration is applied on the sensing fiber. In this paper, various technologies of distributed fiber-optic vibration sensing are reviewed, from interferometric sensing technology, such as Sagnac, Mach-Zehnder, and Michelson, to backscattering-based sensing technology, such as phase-sensitive optical time domain reflectometer, polarization-optical time domain reflectometer, optical frequency domain reflectometer, as well as some combinations of interferometric and backscattering-based techniques. Their operation principles are presented and recent research efforts are also included. Finally, the applications of distributed fiber-optic vibration sensors are summarized, which mainly include structural health monitoring and perimeter security, etc. Overall, distributed fiber-optic vibration sensors possess the advantages of large-scale monitoring, good concealment, excellent flexibility, and immunity to electromagnetic interference, and thus show considerable potential for a variety of practical applications.

Nonlinear Dynamic Model-Based Multiobjective Sensor Network Design Algorithm for a Plant with an Estimator-Based Control System

DOE PAGES

Paul, Prokash; Bhattacharyya, Debangsu; Turton, Richard; ...

2017-06-06

Here, a novel sensor network design (SND) algorithm is developed for maximizing process efficiency while minimizing sensor network cost for a nonlinear dynamic process with an estimator-based control system. The multiobjective optimization problem is solved following a lexicographic approach where the process efficiency is maximized first followed by minimization of the sensor network cost. The partial net present value, which combines the capital cost due to the sensor network and the operating cost due to deviation from the optimal efficiency, is proposed as an alternative objective. The unscented Kalman filter is considered as the nonlinear estimator. The large-scale combinatorial optimizationmore » problem is solved using a genetic algorithm. The developed SND algorithm is applied to an acid gas removal (AGR) unit as part of an integrated gasification combined cycle (IGCC) power plant with CO 2 capture. Due to the computational expense, a reduced order nonlinear model of the AGR process is identified and parallel computation is performed during implementation.« less

Intercomparison of Evapotranspiration Over the Savannah Volta Basin in West Africa Using Remote Sensing Data

PubMed Central

Opoku-Duah, S.; Donoghue, D.N.M.; Burt, T. P.

2008-01-01

This paper compares evapotranspiration estimates from two complementary satellite sensors – NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and ESA's ENVISAT Advanced Along-Track Scanning Radiometer (AATSR) over the savannah area of the Volta basin in West Africa. This was achieved through solving for evapotranspiration on the basis of the regional energy balance equation, which was computationally-driven by the Surface Energy Balance Algorithm for Land algorithm (SEBAL). The results showed that both sensors are potentially good sources of evapotranspiration estimates over large heterogeneous landscapes. The MODIS sensor measured daily evapotranspiration reasonably well with a strong spatial correlation (R2=0.71) with Landsat ETM+ but underperformed with deviations up to ∼2.0 mm day-1, when compared with local eddy correlation observations and the Penman-Monteith method mainly because of scale mismatch. The AATSR sensor produced much poorer correlations (R2=0.13) with Landsat ETM+ and conventional ET methods also because of differences in atmospheric correction and sensor calibration over land. PMID:27879847

Sensitive detection of capsaicinoids using a surface plasmon resonance sensor with anti-homovanillic Acid polyclonal antibodies.

PubMed

Nakamura, Shingo; Yatabe, Rui; Onodera, Takeshi; Toko, Kiyoshi

2013-11-13

Recently, highly functional biosensors have been developed in preparation for possible large-scale terrorist attacks using chemical warfare agents. Practically applicable sensors are required to have various abilities, such as high portability and operability, the capability of performing rapid and continuous measurement, as well as high sensitivity and selectivity. We developed the detection method of capsaicinoids, the main component of some lachrymators, using a surface plasmon resonance (SPR) immunosensor as an on-site detection sensor. Homovanillic acid, which has a vanillyl group similar to capsaicinoids such as capsaicin and dihydrocapsaicin, was bound to Concholepas concholepas hemocyanin (CCH) for use as an immunogen to generate polyclonal antibodies. An indirect competitive assay was carried out to detect capsaicinoids using SPR sensor chips on which different capsaicin analogues were immobilized. For the sensor chip on which 4-hydroxy-3-methoxybenzylamine hydrochloride was immobilized, a detection limit of 150 ppb was achieved. We found that the incubation time was not required and the detection can be completed in five minutes.

Roll-to-Roll Gravure Printed Electrochemical Sensors for Wearable and Medical Devices.

PubMed

Bariya, Mallika; Shahpar, Ziba; Park, Hyejin; Sun, Junfeng; Jung, Younsu; Gao, Wei; Nyein, Hnin Yin Yin; Liaw, Tiffany Sun; Tai, Li-Chia; Ngo, Quynh P; Chao, Minghan; Zhao, Yingbo; Hettick, Mark; Cho, Gyoujin; Javey, Ali

2018-06-25

As recent developments in noninvasive biosensors spearhead the thrust toward personalized health and fitness monitoring, there is a need for high throughput, cost-effective fabrication of flexible sensing components. Toward this goal, we present roll-to-roll (R2R) gravure printed electrodes that are robust under a range of electrochemical sensing applications. We use inks and electrode morphologies designed for electrochemical and mechanical stability, achieving devices with uniform redox kinetics printed on 150 m flexible substrate rolls. We show that these electrodes can be functionalized into consistently high performing sensors for detecting ions, metabolites, heavy metals, and other small molecules in noninvasively accessed biofluids, including sensors for real-time, in situ perspiration monitoring during exercise. This development of robust and versatile R2R gravure printed electrodes represents a key translational step in enabling large-scale, low-cost fabrication of disposable wearable sensors for personalized health monitoring applications.

FPGA-Based Multimodal Embedded Sensor System Integrating Low- and Mid-Level Vision

PubMed Central

Botella, Guillermo; Martín H., José Antonio; Santos, Matilde; Meyer-Baese, Uwe

2011-01-01

Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms. PMID:22164069

All-IP-Ethernet architecture for real-time sensor-fusion processing

NASA Astrophysics Data System (ADS)

Hiraki, Kei; Inaba, Mary; Tezuka, Hiroshi; Tomari, Hisanobu; Koizumi, Kenichi; Kondo, Shuya

2016-03-01

Serendipter is a device that distinguishes and selects very rare particles and cells from huge amount of population. We are currently designing and constructing information processing system for a Serendipter. The information processing system for Serendipter is a kind of sensor-fusion system but with much more difficulties: To fulfill these requirements, we adopt All IP based architecture: All IP-Ethernet based data processing system consists of (1) sensor/detector directly output data as IP-Ethernet packet stream, (2) single Ethernet/TCP/IP streams by a L2 100Gbps Ethernet switch, (3) An FPGA board with 100Gbps Ethernet I/F connected to the switch and a Xeon based server. Circuits in the FPGA include 100Gbps Ethernet MAC, buffers and preprocessing, and real-time Deep learning circuits using multi-layer neural networks. Proposed All-IP architecture solves existing problem to construct large-scale sensor-fusion systems.

FPGA-based multimodal embedded sensor system integrating low- and mid-level vision.

PubMed

Botella, Guillermo; Martín H, José Antonio; Santos, Matilde; Meyer-Baese, Uwe

2011-01-01

Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms.

Multi-source Geospatial Data Analysis with Google Earth Engine

NASA Astrophysics Data System (ADS)

Erickson, T.

2014-12-01

The Google Earth Engine platform is a cloud computing environment for data analysis that combines a public data catalog with a large-scale computational facility optimized for parallel processing of geospatial data. The data catalog is a multi-petabyte archive of georeferenced datasets that include images from Earth observing satellite and airborne sensors (examples: USGS Landsat, NASA MODIS, USDA NAIP), weather and climate datasets, and digital elevation models. Earth Engine supports both a just-in-time computation model that enables real-time preview and debugging during algorithm development for open-ended data exploration, and a batch computation mode for applying algorithms over large spatial and temporal extents. The platform automatically handles many traditionally-onerous data management tasks, such as data format conversion, reprojection, and resampling, which facilitates writing algorithms that combine data from multiple sensors and/or models. Although the primary use of Earth Engine, to date, has been the analysis of large Earth observing satellite datasets, the computational platform is generally applicable to a wide variety of use cases that require large-scale geospatial data analyses. This presentation will focus on how Earth Engine facilitates the analysis of geospatial data streams that originate from multiple separate sources (and often communities) and how it enables collaboration during algorithm development and data exploration. The talk will highlight current projects/analyses that are enabled by this functionality.https://earthengine.google.org

IRIS Arrays: Observing Wavefields at Multiple Scales and Frequencies

NASA Astrophysics Data System (ADS)

Sumy, D. F.; Woodward, R.; Frassetto, A.

2014-12-01

The Incorporated Research Institutions for Seismology (IRIS) provides instruments for creating and operating seismic arrays at a wide range of scales. As an example, for over thirty years the IRIS PASSCAL program has provided instruments to individual Principal Investigators to deploy arrays of all shapes and sizes on every continent. These arrays have ranged from just a few sensors to hundreds or even thousands of sensors, covering areas with dimensions of meters to thousands of kilometers. IRIS also operates arrays directly, such as the USArray Transportable Array (TA) as part of the EarthScope program. Since 2004, the TA has rolled across North America, at any given time spanning a swath of approximately 800 km by 2,500 km, and thus far sampling 2% of the Earth's surface. This achievement includes all of the lower-48 U.S., southernmost Canada, and now parts of Alaska. IRIS has also facilitated specialized arrays in polar environments and on the seafloor. In all cases, the data from these arrays are freely available to the scientific community. As the community of scientists who use IRIS facilities and data look to the future they have identified a clear need for new array capabilities. In particular, as part of its Wavefields Initiative, IRIS is exploring new technologies that can enable large, dense array deployments to record unaliased wavefields at a wide range of frequencies. Large-scale arrays might utilize multiple sensor technologies to best achieve observing objectives and optimize equipment and logistical costs. Improvements in packaging and power systems can provide equipment with reduced size, weight, and power that will reduce logistical constraints for large experiments, and can make a critical difference for deployments in harsh environments or other situations where rapid deployment is required. We will review the range of existing IRIS array capabilities with an overview of previous and current deployments and examples of data and results. We will review existing IRIS projects that explore new array capabilities and highlight future directions for IRIS instrumentation facilities.

Convergence Rate Analysis of Distributed Gossip (Linear Parameter) Estimation: Fundamental Limits and Tradeoffs

NASA Astrophysics Data System (ADS)

Kar, Soummya; Moura, José M. F.

2011-08-01

The paper considers gossip distributed estimation of a (static) distributed random field (a.k.a., large scale unknown parameter vector) observed by sparsely interconnected sensors, each of which only observes a small fraction of the field. We consider linear distributed estimators whose structure combines the information \\emph{flow} among sensors (the \\emph{consensus} term resulting from the local gossiping exchange among sensors when they are able to communicate) and the information \\emph{gathering} measured by the sensors (the \\emph{sensing} or \\emph{innovations} term.) This leads to mixed time scale algorithms--one time scale associated with the consensus and the other with the innovations. The paper establishes a distributed observability condition (global observability plus mean connectedness) under which the distributed estimates are consistent and asymptotically normal. We introduce the distributed notion equivalent to the (centralized) Fisher information rate, which is a bound on the mean square error reduction rate of any distributed estimator; we show that under the appropriate modeling and structural network communication conditions (gossip protocol) the distributed gossip estimator attains this distributed Fisher information rate, asymptotically achieving the performance of the optimal centralized estimator. Finally, we study the behavior of the distributed gossip estimator when the measurements fade (noise variance grows) with time; in particular, we consider the maximum rate at which the noise variance can grow and still the distributed estimator being consistent, by showing that, as long as the centralized estimator is consistent, the distributed estimator remains consistent.

Assessment and Computerized Modeling of the Environmental Deposition of Military Smokes. Characterization of the Atmospheric Boundary Layer in Complex Terrain and Results from the Amadeus Smoke Dispersion Experiments

DTIC Science & Technology

1991-12-01

profiles may De seriously distorted in the presence 3 of large roughness elements or hills. Regardless of surface characteristics, similarity theory may...scaling parameters described in Section 2.2.1 These profiles may be written in the following form 24 du u. ( - 4m() (2.15) de e. 4 (2.16) where $m and 4h...temperature sensor on Station A103 "exhibited a very slow response time as compared with the other sur- face-station sensors . These stations ran continuously

Measuring short-term post-fire forest recovery across a burn severity gradient in a mixed pine-oak forest using multi-sensor remote sensing techniques

DOE PAGES

Meng, Ran; Wu, Jin; Zhao, Feng; ...

2018-06-01

Understanding post-fire forest recovery is pivotal to the study of forest dynamics and global carbon cycle. Field-based studies indicated a convex response of forest recovery rate to burn severity at the individual tree level, related with fire-induced tree mortality; however, these findings were constrained in spatial/temporal extents, while not detectable by traditional optical remote sensing studies, largely attributing to the contaminated effect from understory recovery. For this work, we examined whether the combined use of multi-sensor remote sensing techniques (i.e., 1m simultaneous airborne imaging spectroscopy and LiDAR and 2m satellite multi-spectral imagery) to separate canopy recovery from understory recovery wouldmore » enable to quantify post-fire forest recovery rate spanning a large gradient in burn severity over large-scales. Our study was conducted in a mixed pine-oak forest in Long Island, NY, three years after a top-killing fire. Our studies remotely detected an initial increase and then decline of forest recovery rate to burn severity across the burned area, with a maximum canopy area-based recovery rate of 10% per year at moderate forest burn severity class. More intriguingly, such remotely detected convex relationships also held at species level, with pine trees being more resilient to high burn severity and having a higher maximum recovery rate (12% per year) than oak trees (4% per year). These results are one of the first quantitative evidences showing the effects of fire adaptive strategies on post-fire forest recovery, derived from relatively large spatial-temporal domains. Our study thus provides the methodological advance to link multi-sensor remote sensing techniques to monitor forest dynamics in a spatially explicit manner over large-scales, with important implications for fire-related forest management, and for constraining/benchmarking fire effect schemes in ecological process models.« less

Measuring short-term post-fire forest recovery across a burn severity gradient in a mixed pine-oak forest using multi-sensor remote sensing techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meng, Ran; Wu, Jin; Zhao, Feng

Understanding post-fire forest recovery is pivotal to the study of forest dynamics and global carbon cycle. Field-based studies indicated a convex response of forest recovery rate to burn severity at the individual tree level, related with fire-induced tree mortality; however, these findings were constrained in spatial/temporal extents, while not detectable by traditional optical remote sensing studies, largely attributing to the contaminated effect from understory recovery. For this work, we examined whether the combined use of multi-sensor remote sensing techniques (i.e., 1m simultaneous airborne imaging spectroscopy and LiDAR and 2m satellite multi-spectral imagery) to separate canopy recovery from understory recovery wouldmore » enable to quantify post-fire forest recovery rate spanning a large gradient in burn severity over large-scales. Our study was conducted in a mixed pine-oak forest in Long Island, NY, three years after a top-killing fire. Our studies remotely detected an initial increase and then decline of forest recovery rate to burn severity across the burned area, with a maximum canopy area-based recovery rate of 10% per year at moderate forest burn severity class. More intriguingly, such remotely detected convex relationships also held at species level, with pine trees being more resilient to high burn severity and having a higher maximum recovery rate (12% per year) than oak trees (4% per year). These results are one of the first quantitative evidences showing the effects of fire adaptive strategies on post-fire forest recovery, derived from relatively large spatial-temporal domains. Our study thus provides the methodological advance to link multi-sensor remote sensing techniques to monitor forest dynamics in a spatially explicit manner over large-scales, with important implications for fire-related forest management, and for constraining/benchmarking fire effect schemes in ecological process models.« less

Evaluation of a Microbial Sensor as a Tool for Antimicrobial Activity Test of Cosmetic Preservatives.

PubMed

Gomyo, Hideyuki; Ookawa, Masaki; Oshibuchi, Kota; Sugamura, Yuriko; Hosokawa, Masahito; Shionoiri, Nozomi; Maeda, Yoshiaki; Matsunaga, Tadashi; Tanaka, Tsuyoshi

2015-01-01

For high-throughput screening of novel cosmetic preservatives, a rapid and simple assay to evaluate the antimicrobial activities should be developed because the conventional agar dilution method is time-consuming and labor-intensive. To address this issue, we evaluated a microbial sensor as a tool for rapid antimicrobial activity testing. The sensor consists of an oxygen electrode and a filter membrane that holds the test microorganisms, Staphylococcus aureus and Candida albicans. The antimicrobial activity of the tested cosmetic preservative was evaluated by measuring the current increases corresponding to the decreases in oxygen consumption in the microbial respiration. The current increases detected by the sensor showed positive correlation to the concentrations of two commercially used preservatives, chlorphenesin and 2-phenoxyethanol. The same tendency was also observed when a model cosmetic product was used as a preservative solvent, indicating the feasibility in practical use. Furthermore, the microbial sensor and microfluidic flow-cell was assembled to achieve sequential measurements. The sensor system presented in this study could be useful in large-scale screening experiments.

Sensor Selection and Optimization for Health Assessment of Aerospace Systems

NASA Technical Reports Server (NTRS)

Maul, William A.; Kopasakis, George; Santi, Louis M.; Sowers, Thomas S.; Chicatelli, Amy

2007-01-01

Aerospace systems are developed similarly to other large-scale systems through a series of reviews, where designs are modified as system requirements are refined. For space-based systems few are built and placed into service. These research vehicles have limited historical experience to draw from and formidable reliability and safety requirements, due to the remote and severe environment of space. Aeronautical systems have similar reliability and safety requirements, and while these systems may have historical information to access, commercial and military systems require longevity under a range of operational conditions and applied loads. Historically, the design of aerospace systems, particularly the selection of sensors, is based on the requirements for control and performance rather than on health assessment needs. Furthermore, the safety and reliability requirements are met through sensor suite augmentation in an ad hoc, heuristic manner, rather than any systematic approach. A review of the current sensor selection practice within and outside of the aerospace community was conducted and a sensor selection architecture is proposed that will provide a justifiable, dependable sensor suite to address system health assessment requirements.

Sensor Selection and Optimization for Health Assessment of Aerospace Systems

NASA Technical Reports Server (NTRS)

Maul, William A.; Kopasakis, George; Santi, Louis M.; Sowers, Thomas S.; Chicatelli, Amy

2008-01-01

Aerospace systems are developed similarly to other large-scale systems through a series of reviews, where designs are modified as system requirements are refined. For space-based systems few are built and placed into service these research vehicles have limited historical experience to draw from and formidable reliability and safety requirements, due to the remote and severe environment of space. Aeronautical systems have similar reliability and safety requirements, and while these systems may have historical information to access, commercial and military systems require longevity under a range of operational conditions and applied loads. Historically, the design of aerospace systems, particularly the selection of sensors, is based on the requirements for control and performance rather than on health assessment needs. Furthermore, the safety and reliability requirements are met through sensor suite augmentation in an ad hoc, heuristic manner, rather than any systematic approach. A review of the current sensor selection practice within and outside of the aerospace community was conducted and a sensor selection architecture is proposed that will provide a justifiable, defendable sensor suite to address system health assessment requirements.

Flexible and transparent strain sensors based on super-aligned carbon nanotube films.

PubMed

Yu, Yang; Luo, Yufeng; Guo, Alexander; Yan, Lingjia; Wu, Yang; Jiang, Kaili; Li, Qunqing; Fan, Shoushan; Wang, Jiaping

2017-05-25

Highly flexible and transparent strain sensors are fabricated by directly coating super-aligned carbon nanotube (SACNT) films on polydimethylsiloxane (PDMS) substrates. The fabrication process is simple, low cost, and favorable for industrial scalability. The SACNT/PDMS strain sensors present a high sensing range of 400%, a fast response of less than 98 ms, and a low creep of 4% at 400% strain. The SACNT/PDMS strain sensors can withstand 5000 stretching-releasing cycles at 400% strain. Moreover, the SACNT/PDMS strain sensors are transparent with 80% transmittance at 550 nm. In situ microscopic observation clarifies that the surface morphology of the SACNT film exhibits a reversible change during the stretching and releasing processes and thus its electrical conductance is able to fully recover to the original value after the loading-unloading cycles. The SACNT/PDMS strain sensors have the advantages of a wide sensing range, fast response, low creep, transparency, and excellent durability, and thus show great potential in wearable devices to monitor fast and large-scale movements without affecting the appearance of the devices.

SoilNet - A Zigbee based soil moisture sensor network

NASA Astrophysics Data System (ADS)

Bogena, H. R.; Weuthen, A.; Rosenbaum, U.; Huisman, J. A.; Vereecken, H.

2007-12-01

Soil moisture plays a key role in partitioning water and energy fluxes, in providing moisture to the atmosphere for precipitation, and controlling the pattern of groundwater recharge. Large-scale soil moisture variability is driven by variation of precipitation and radiation in space and time. At local scales, land cover, soil conditions, and topography act to redistribute soil moisture. Despite the importance of soil moisture, it is not yet measured in an operational way, e.g. for a better prediction of hydrological and surface energy fluxes (e.g. runoff, latent heat) at larger scales and in the framework of the development of early warning systems (e.g. flood forecasting) and the management of irrigation systems. The SoilNet project aims to develop a sensor network for the near real-time monitoring of soil moisture changes at high spatial and temporal resolution on the basis of the new low-cost ZigBee radio network that operates on top of the IEEE 802.15.4 standard. The sensor network consists of soil moisture sensors attached to end devices by cables, router devices and a coordinator device. The end devices are buried in the soil and linked wirelessly with nearby aboveground router devices. This ZigBee wireless sensor network design considers channel errors, delays, packet losses, and power and topology constraints. In order to conserve battery power, a reactive routing protocol is used that determines a new route only when it is required. The sensor network is also able to react to external influences, e.g. such as rainfall occurrences. The SoilNet communicator, routing and end devices have been developed by the Forschungszentrum Juelich and will be marketed through external companies. We will present first results of experiments to verify network stability and the accuracy of the soil moisture sensors. Simultaneously, we have developed a data management and visualisation system. We tested the wireless network on a 100 by 100 meter forest plot equipped with 25 end devices each consisting of 6 vertically arranged soil moisture sensors. The next step will be the instrumentation of two small catchments (~30 ha) with a 30 m spacing of the end devices. juelich.de/icg/icg-4/index.php?index=739

Sensor Networks, Dataloggers, and Other Handy Gadgets Using Open-Source Electronics for the Christina River Basin CZO

NASA Astrophysics Data System (ADS)

Hicks, S. D.; Aufdenkampe, A. K.; Montgomery, D. S.

2011-12-01

The search for biogeochemical "hot spots" and "hot moments" that control ecosystem-level processes requires a rethinking of how we observe the environment. Extensive multi-sensor/measurement arrays are required to realize 2D, 3D, or 4D maps of environmental properties with sufficient spatial and temporal resolution to find and understand hot spots and hot moments. To date, the cost of the data logging and communication infrastructure has been a major limitation to large-scale sensor deployment, especially for near-real-time (NRT) wireless networks. A low-cost, user-friendly alternative is needed so that resources can be prioritized toward sensor hardware rather than data acquisition and communication hardware. A flexible development platform would also allow for easy creation of other useful devices in addition to the already apparent need for economical dataloggers. The recent proliferation of open-source electronics platforms offers an opportunity for environmental observatories to deploy sensors at large scales by reducing data logging and communications costs by more than an order of magnitude. Leading the open-source electronics revolution is the Arduino project, designed to make the process of using electronics in multidisciplinary projects more accessible to hobbyists and professionals alike. A large user community has developed and shared hundreds of practical applications for projects that interface with a variety of sensors and use embedded logic to control external hardware. Likewise, dozens of companies and individuals sell low-cost Arduino-compatible boards that can connect together in a modular framework, allowing the user to quickly create devices for a wide range of applications. Based on these open-source technologies and products, we are designing and building a variety of circuit devices for use in our research watersheds. One Arduino-based device is a multi-channel datalogger that can be used with a variety of analog and digital sensors, such as pressure transducers, conductivity sensors, soil moisture and temperature probes, and redox probes. Radio modules can be added to the loggers to create a self-meshing wireless network for streaming live sensor data. A variation of the logger circuit is a smaller handheld unit with a text display that can be used when testing sensors in the field. Another useful custom device is a remote streamwater sampling system, made up of an Arduino circuit and a prepaid cell phone, allowing a user to remotely control multiple pumps by following interactive voice menus and hearing live sensor value readouts. In the lab, an Arduino circuit is used in a multi-chamber CO2 respiration experiment where it is controlling dozens of solenoid valves and logging the data from the analytical instruments. One of the biggest benefits of open source hardware is the low cost of the components. Each of the devices we have built costs less than $100 and can be assembled in a few hours. These circuits could easily be adapted to other applications or interfaced with other sensors in a variety of configurations, making the Arduino platform an incredibly useful tool for researchers.

1 million-Q optomechanical microdisk resonators for sensing with very large scale integration

NASA Astrophysics Data System (ADS)

Hermouet, M.; Sansa, M.; Banniard, L.; Fafin, A.; Gely, M.; Allain, P. E.; Santos, E. Gil; Favero, I.; Alava, T.; Jourdan, G.; Hentz, S.

2018-02-01

Cavity optomechanics have become a promising route towards the development of ultrasensitive sensors for a wide range of applications including mass, chemical and biological sensing. In this study, we demonstrate the potential of Very Large Scale Integration (VLSI) with state-of-the-art low-loss performance silicon optomechanical microdisks for sensing applications. We report microdisks exhibiting optical Whispering Gallery Modes (WGM) with 1 million quality factors, yielding high displacement sensitivity and strong coupling between optical WGMs and in-plane mechanical Radial Breathing Modes (RBM). Such high-Q microdisks with mechanical resonance frequencies in the 102 MHz range were fabricated on 200 mm wafers with Variable Shape Electron Beam lithography. Benefiting from ultrasensitive readout, their Brownian motion could be resolved with good Signal-to-Noise ratio at ambient pressure, as well as in liquid, despite high frequency operation and large fluidic damping: the mechanical quality factor reduced from few 103 in air to 10's in liquid, and the mechanical resonance frequency shifted down by a few percent. Proceeding one step further, we performed an all-optical operation of the resonators in air using a pump-probe scheme. Our results show our VLSI process is a viable approach for the next generation of sensors operating in vacuum, gas or liquid phase.

Beam test results of a monolithic pixel sensor in the 0.18 μm tower-jazz technology with high resistivity epitaxial layer

NASA Astrophysics Data System (ADS)

Mattiazzo, S.; Aimo, I.; Baudot, J.; Bedda, C.; La Rocca, P.; Perez, A.; Riggi, F.; Spiriti, E.

2015-10-01

The ALICE experiment at CERN will undergo a major upgrade in the second Long LHC Shutdown in the years 2018-2019; this upgrade includes the full replacement of the Inner Tracking System (ITS), deploying seven layers of Monolithic Active Pixel Sensors (MAPS). For the development of the new ALICE ITS, the Tower-Jazz 0.18 μm CMOS imaging sensor process has been chosen as it is possible to use full CMOS in the pixel and different silicon wafers (including high resistivity epitaxial layers). A large test campaign has been carried out on several small prototype chips, designed to optimize the pixel sensor layout and the front-end electronics. Results match the target requirements both in terms of performance and of radiation hardness. Following this development, the first full scale chips have been designed, submitted and are currently under test, with promising results. A telescope composed of 4 planes of Mimosa-28 and 2 planes of Mimosa-18 chips is under development at the DAFNE Beam Test Facility (BTF) at the INFN Laboratori Nazionali di Frascati (LNF) in Italy with the final goal to perform a comparative test of the full scale prototypes. The telescope has been recently used to test a Mimosa-22THRb chip (a monolithic pixel sensor built in the 0.18 μm Tower-Jazz process) and we foresee to perform tests on the full scale chips for the ALICE ITS upgrade at the beginning of 2015. In this contribution we will describe some first measurements of spatial resolution, fake hit rate and detection efficiency of the Mimosa-22THRb chip obtained at the BTF facility in June 2014 with an electron beam of 500 MeV.

Design and evaluation of a wireless sensor network based aircraft strength testing system.

PubMed

Wu, Jian; Yuan, Shenfang; Zhou, Genyuan; Ji, Sai; Wang, Zilong; Wang, Yang

2009-01-01

The verification of aerospace structures, including full-scale fatigue and static test programs, is essential for structure strength design and evaluation. However, the current overall ground strength testing systems employ a large number of wires for communication among sensors and data acquisition facilities. The centralized data processing makes test programs lack efficiency and intelligence. Wireless sensor network (WSN) technology might be expected to address the limitations of cable-based aeronautical ground testing systems. This paper presents a wireless sensor network based aircraft strength testing (AST) system design and its evaluation on a real aircraft specimen. In this paper, a miniature, high-precision, and shock-proof wireless sensor node is designed for multi-channel strain gauge signal conditioning and monitoring. A cluster-star network topology protocol and application layer interface are designed in detail. To verify the functionality of the designed wireless sensor network for strength testing capability, a multi-point WSN based AST system is developed for static testing of a real aircraft undercarriage. Based on the designed wireless sensor nodes, the wireless sensor network is deployed to gather, process, and transmit strain gauge signals and monitor results under different static test loads. This paper shows the efficiency of the wireless sensor network based AST system, compared to a conventional AST system.

Design and Evaluation of a Wireless Sensor Network Based Aircraft Strength Testing System

PubMed Central

Wu, Jian; Yuan, Shenfang; Zhou, Genyuan; Ji, Sai; Wang, Zilong; Wang, Yang

2009-01-01

The verification of aerospace structures, including full-scale fatigue and static test programs, is essential for structure strength design and evaluation. However, the current overall ground strength testing systems employ a large number of wires for communication among sensors and data acquisition facilities. The centralized data processing makes test programs lack efficiency and intelligence. Wireless sensor network (WSN) technology might be expected to address the limitations of cable-based aeronautical ground testing systems. This paper presents a wireless sensor network based aircraft strength testing (AST) system design and its evaluation on a real aircraft specimen. In this paper, a miniature, high-precision, and shock-proof wireless sensor node is designed for multi-channel strain gauge signal conditioning and monitoring. A cluster-star network topology protocol and application layer interface are designed in detail. To verify the functionality of the designed wireless sensor network for strength testing capability, a multi-point WSN based AST system is developed for static testing of a real aircraft undercarriage. Based on the designed wireless sensor nodes, the wireless sensor network is deployed to gather, process, and transmit strain gauge signals and monitor results under different static test loads. This paper shows the efficiency of the wireless sensor network based AST system, compared to a conventional AST system. PMID:22408521

Higher resolution satellite remote sensing and the impact on image mapping

USGS Publications Warehouse

Watkins, Allen H.; Thormodsgard, June M.

1987-01-01

Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges.The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

Large Scale Bacterial Colony Screening of Diversified FRET Biosensors

PubMed Central

Litzlbauer, Julia; Schifferer, Martina; Ng, David; Fabritius, Arne; Thestrup, Thomas; Griesbeck, Oliver

2015-01-01

Biosensors based on Förster Resonance Energy Transfer (FRET) between fluorescent protein mutants have started to revolutionize physiology and biochemistry. However, many types of FRET biosensors show relatively small FRET changes, making measurements with these probes challenging when used under sub-optimal experimental conditions. Thus, a major effort in the field currently lies in designing new optimization strategies for these types of sensors. Here we describe procedures for optimizing FRET changes by large scale screening of mutant biosensor libraries in bacterial colonies. We describe optimization of biosensor expression, permeabilization of bacteria, software tools for analysis, and screening conditions. The procedures reported here may help in improving FRET changes in multiple suitable classes of biosensors. PMID:26061878

Tuneable diode laser gas analyser for methane measurements on a large scale solid oxide fuel cell

NASA Astrophysics Data System (ADS)

Lengden, Michael; Cunningham, Robert; Johnstone, Walter

2011-10-01

A new in-line, real time gas analyser is described that uses tuneable diode laser spectroscopy (TDLS) for the measurement of methane in solid oxide fuel cells. The sensor has been tested on an operating solid oxide fuel cell (SOFC) in order to prove the fast response and accuracy of the technology as compared to a gas chromatograph. The advantages of using a TDLS system for process control in a large-scale, distributed power SOFC unit are described. In future work, the addition of new laser sources and wavelength modulation will allow the simultaneous measurement of methane, water vapour, carbon-dioxide and carbon-monoxide concentrations.

Fabrication of a Miniature Multi-Parameter Sensor Chip for Water Quality Assessment.

PubMed

Zhou, Bo; Bian, Chao; Tong, Jianhua; Xia, Shanhong

2017-01-14

Water contamination is a main inducement of human diseases. It is an important step to monitor the water quality in the water distribution system. Due to the features of large size, high cost, and complicated structure of traditional water determination sensors and devices, it is difficult to realize real-time water monitoring on a large scale. In this paper, we present a multi-parameter sensor chip, which is miniature, low-cost, and robust, to detect the pH, conductivity, and temperature of water simultaneously. The sensor chip was fabricated using micro-electro-mechanical system (MEMS) techniques. Iridium oxide film was electrodeposited as the pH-sensing material. The atomic ratio of Ir(III) to Ir(IV) is about 1.38 according to the X-ray photoelectron spectroscopy (XPS) analysis. The pH sensing electrode showed super-Nernstian response (-67.60 mV/pH) and good linearity (R² = 0.9997), in the range of pH 2.22 to pH 11.81. KCl-agar and epoxy were used as the electrolyte layer and liquid junction for the solid-state reference electrode, respectively, and its potential stability in deionized water was 56 h. The conductivity cell exhibited a linear determination range from 21.43 μ S / cm to 1.99 mS / cm , and the electrode constant was 1.566 cm -1 . Sensitivity of the temperature sensor was 5.46 Ω / ° C . The results indicate that the developed sensor chip has potential application in water quality measurements.

Fiber Optic Sensor for Real-Time Sensing of Silica Scale Formation in Geothermal Water.

PubMed

Okazaki, Takuya; Orii, Tatsuya; Ueda, Akira; Ozawa, Akiko; Kuramitz, Hideki

2017-06-13

We present a novel fiber optic sensor for real-time sensing of silica scale formation in geothermal water. The sensor is fabricated by removing the cladding of a multimode fiber to expose the core to detect the scale-formation-induced refractive index change. A simple experimental setup was constructed to measure the transmittance response using white light as a source and a spectroscopy detector. A field test was performed on geothermal water containing 980 mg/L dissolved silica at 93 °C in Sumikawa Geothermal Power Plant, Japan. The transmittance response of the fiber sensor decreased due to the formation of silica scale on the fiber core from geothermal water. An application of this sensor in the evaluation of scale inhibitors was demonstrated. In geothermal water containing a pH modifier, the change of transmittance response decreased with pH decrease. The effectiveness of a polyelectrolyte inhibitor in prevention of silica scale formation was easily detectable using the fiber sensor in geothermal water.

Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

NASA Astrophysics Data System (ADS)

Wilson, Brian; Manipon, Gerald; Hua, Hook; Fetzer, Eric

2014-05-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map-reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in a hybrid Cloud (private eucalyptus & public Amazon). Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Multi-year datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will present the architecture of SciReduce, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. We will also present a concept and prototype for staging NASA's A-Train Atmospheric datasets (Levels 2 & 3) in the Amazon Cloud so that any number of compute jobs can be executed "near" the multi-sensor data. Given such a system, multi-sensor climate studies over 10-20 years of data could be perform

Using Custom Fiber Bragg Grating-Based Sensors to Monitor Artificial Landslides.

PubMed

Zhang, Qinghua; Wang, Yuan; Sun, Yangyang; Gao, Lei; Zhang, Zhenglin; Zhang, Wenyuan; Zhao, Pengchong; Yue, Yin

2016-09-02

Four custom fiber Bragg grating (FBG)-based sensors are developed to monitor an artificial landslide located in Nanjing, China. The sensors are composed of a rod and two FBGs. Based on the strength of the rods, two sensors are referred to as "hard sensors" (Sensor 1 and Sensor 2), the other two are referred to as "soft sensors" (Sensor 3 and Sensor 4). The two FBGs are fixed on each sensor rod at distances of 50 cm and 100 cm from the top of the rod (an upper FBG and a lower FBG). In the experiment presented in this paper, the sensors are installed on a slope on which an artificial landslide is generated through both machine-based and manual excavation. The fiber sensing system consists of the four custom FBG-based sensors, optical fiber, a static fiber grating demodulation instrument (SM125), and a PC with the necessary software. Experimental data was collected in the presence of an artificial landslide, and the results show that the lower FBGs are more sensitive than the upper FBGs for all four of the custom sensors. It was also found that Sensor 2 and Sensor 4 are more capable of monitoring small-scale landslides than Sensor 1 and Sensor 3, and this is mainly due to their placement location with respect to the landslide. The stronger rods used in the hard sensors make them more adaptable to the harsh environments of large landslides. Thus, hard sensors should be fixed near the landslide, while soft sensors should be placed farther away from the landslide. In addition, a clear tendency of strain variation can be detected by the soft sensors, which can be used to predict landslides and raise a hazard alarm.

Energy Efficient Cluster Based Scheduling Scheme for Wireless Sensor Networks

PubMed Central

Srie Vidhya Janani, E.; Ganesh Kumar, P.

2015-01-01

The energy utilization of sensor nodes in large scale wireless sensor network points out the crucial need for scalable and energy efficient clustering protocols. Since sensor nodes usually operate on batteries, the maximum utility of network is greatly dependent on ideal usage of energy leftover in these sensor nodes. In this paper, we propose an Energy Efficient Cluster Based Scheduling Scheme for wireless sensor networks that balances the sensor network lifetime and energy efficiency. In the first phase of our proposed scheme, cluster topology is discovered and cluster head is chosen based on remaining energy level. The cluster head monitors the network energy threshold value to identify the energy drain rate of all its cluster members. In the second phase, scheduling algorithm is presented to allocate time slots to cluster member data packets. Here congestion occurrence is totally avoided. In the third phase, energy consumption model is proposed to maintain maximum residual energy level across the network. Moreover, we also propose a new packet format which is given to all cluster member nodes. The simulation results prove that the proposed scheme greatly contributes to maximum network lifetime, high energy, reduced overhead, and maximum delivery ratio. PMID:26495417

Chemistry integrated circuit: chemical system on a complementary metal oxide semiconductor integrated circuit.

PubMed

Nakazato, Kazuo

2014-03-28

By integrating chemical reactions on a large-scale integration (LSI) chip, new types of device can be created. For biomedical applications, monolithically integrated sensor arrays for potentiometric, amperometric and impedimetric sensing of biomolecules have been developed. The potentiometric sensor array detects pH and redox reaction as a statistical distribution of fluctuations in time and space. For the amperometric sensor array, a microelectrode structure for measuring multiple currents at high speed has been proposed. The impedimetric sensor array is designed to measure impedance up to 10 MHz. The multimodal sensor array will enable synthetic analysis and make it possible to standardize biosensor chips. Another approach is to create new functional devices by integrating molecular systems with LSI chips, for example image sensors that incorporate biological materials with a sensor array. The quantum yield of the photoelectric conversion of photosynthesis is 100%, which is extremely difficult to achieve by artificial means. In a recently developed process, a molecular wire is plugged directly into a biological photosynthetic system to efficiently conduct electrons to a gold electrode. A single photon can be detected at room temperature using such a system combined with a molecular single-electron transistor.

A High-Speed Vision-Based Sensor for Dynamic Vibration Analysis Using Fast Motion Extraction Algorithms.

PubMed

Zhang, Dashan; Guo, Jie; Lei, Xiujun; Zhu, Changan

2016-04-22

The development of image sensor and optics enables the application of vision-based techniques to the non-contact dynamic vibration analysis of large-scale structures. As an emerging technology, a vision-based approach allows for remote measuring and does not bring any additional mass to the measuring object compared with traditional contact measurements. In this study, a high-speed vision-based sensor system is developed to extract structure vibration signals in real time. A fast motion extraction algorithm is required for this system because the maximum sampling frequency of the charge-coupled device (CCD) sensor can reach up to 1000 Hz. Two efficient subpixel level motion extraction algorithms, namely the modified Taylor approximation refinement algorithm and the localization refinement algorithm, are integrated into the proposed vision sensor. Quantitative analysis shows that both of the two modified algorithms are at least five times faster than conventional upsampled cross-correlation approaches and achieve satisfactory error performance. The practicability of the developed sensor is evaluated by an experiment in a laboratory environment and a field test. Experimental results indicate that the developed high-speed vision-based sensor system can extract accurate dynamic structure vibration signals by tracking either artificial targets or natural features.

A Wirelessly Powered Smart Contact Lens with Reconfigurable Wide Range and Tunable Sensitivity Sensor Readout Circuitry

PubMed Central

Chiou, Jin-Chern; Hsu, Shun-Hsi; Huang, Yu-Chieh; Yeh, Guan-Ting; Liou, Wei-Ting; Kuei, Cheng-Kai

2017-01-01

This study presented a wireless smart contact lens system that was composed of a reconfigurable capacitive sensor interface circuitry and wirelessly powered radio-frequency identification (RFID) addressable system for sensor control and data communication. In order to improve compliance and reduce user discomfort, a capacitive sensor was embedded on a soft contact lens of 200 μm thickness using commercially available bio-compatible lens material and a standard manufacturing process. The results indicated that the reconfigurable sensor interface achieved sensitivity and baseline tuning up to 120 pF while consuming only 110 μW power. The range and sensitivity tuning of the readout circuitry ensured a reliable operation with respect to sensor fabrication variations and independent calibration of the sensor baseline for individuals. The on-chip voltage scaling allowed the further extension of the detection range and prevented the implementation of large on-chip elements. The on-lens system enabled the detection of capacitive variation caused by pressure changes in the range of 2.25 to 30 mmHg and hydration level variation from a distance of 1 cm using incident power from an RFID reader at 26.5 dBm. PMID:28067859

Smart Sensors: Why and when the origin was and why and where the future will be

NASA Astrophysics Data System (ADS)

Corsi, C.

2013-12-01

Smart Sensors is a technique developed in the 70's when the processing capabilities, based on readout integrated with signal processing, was still far from the complexity needed in advanced IR surveillance and warning systems, because of the enormous amount of noise/unwanted signals emitted by operating scenario especially in military applications. The Smart Sensors technology was kept restricted within a close military environment exploding in applications and performances in the 90's years thanks to the impressive improvements in the integrated signal read-out and processing achieved by CCD-CMOS technologies in FPA. In fact the rapid advances of "very large scale integration" (VLSI) processor technology and mosaic EO detector array technology allowed to develop new generations of Smart Sensors with much improved signal processing by integrating microcomputers and other VLSI signal processors. inside the sensor structure achieving some basic functions of living eyes (dynamic stare, non-uniformity compensation, spatial and temporal filtering). New and future technologies (Nanotechnology, Bio-Organic Electronics, Bio-Computing) are lightning a new generation of Smart Sensors extending the Smartness from the Space-Time Domain to Spectroscopic Functional Multi-Domain Signal Processing. History and future forecasting of Smart Sensors will be reported.

Electrical Design and Evaluation of Asynchronous Serial Bus Communication Network of 48 Sensor Platform LSIs with Single-Ended I/O for Integrated MEMS-LSI Sensors

PubMed Central

Shao, Chenzhong; Tanaka, Shuji; Nakayama, Takahiro; Hata, Yoshiyuki

2018-01-01

For installing many sensors in a limited space with a limited computing resource, the digitization of the sensor output at the site of sensation has advantages such as a small amount of wiring, low signal interference and high scalability. For this purpose, we have developed a dedicated Complementary Metal-Oxide-Semiconductor (CMOS) Large-Scale Integration (LSI) (referred to as “sensor platform LSI”) for bus-networked Micro-Electro-Mechanical-Systems (MEMS)-LSI integrated sensors. In this LSI, collision avoidance, adaptation and event-driven functions are simply implemented to relieve data collision and congestion in asynchronous serial bus communication. In this study, we developed a network system with 48 sensor platform LSIs based on Printed Circuit Board (PCB) in a backbone bus topology with the bus length being 2.4 m. We evaluated the serial communication performance when 48 LSIs operated simultaneously with the adaptation function. The number of data packets received from each LSI was almost identical, and the average sampling frequency of 384 capacitance channels (eight for each LSI) was 73.66 Hz. PMID:29342923

Design and Analysis of a Data Fusion Scheme in Mobile Wireless Sensor Networks Based on Multi-Protocol Mobile Agents

PubMed Central

Wu, Chunxue; Wu, Wenliang; Wan, Caihua

2017-01-01

Sensors are increasingly used in mobile environments with wireless network connections. Multiple sensor types measure distinct aspects of the same event. Their measurements are then combined to produce integrated, reliable results. As the number of sensors in networks increases, low energy requirements and changing network connections complicate event detection and measurement. We present a data fusion scheme for use in mobile wireless sensor networks with high energy efficiency and low network delays, that still produces reliable results. In the first phase, we used a network simulation where mobile agents dynamically select the next hop migration node based on the stability parameter of the link, and perform the data fusion at the migration node. Agents use the fusion results to decide if it should return the fusion results to the processing center or continue to collect more data. In the second phase. The feasibility of data fusion at the node level is confirmed by an experimental design where fused data from color sensors show near-identical results to actual physical temperatures. These results are potentially important for new large-scale sensor network applications. PMID:29099793

Processing of Fine-Scale Piezoelectric Ceramic/Polymer Composites for Sensors and Actuators

NASA Technical Reports Server (NTRS)

Janas, V. F.; Safari, A.

1996-01-01

The objective of the research effort at Rutgers is the development of lead zirconate titanate (PZT) ceramic/polymer composites with different designs for transducer applications including hydrophones, biomedical imaging, non-destructive testing, and air imaging. In this review, methods for processing both large area and multifunctional ceramic/polymer composites for acoustic transducers were discussed.

Sensor Spatial Distortion, Visual Latency, and Update Rate Effects on 3D Tracking in Virtual Environments

NASA Technical Reports Server (NTRS)

Ellis, S. R.; Adelstein, B. D.; Baumeler, S.; Jense, G. J.; Jacoby, R. H.; Trejo, Leonard (Technical Monitor)

1998-01-01

Several common defects that we have sought to minimize in immersing virtual environments are: static sensor spatial distortion, visual latency, and low update rates. Human performance within our environments during large amplitude 3D tracking was assessed by objective and subjective methods in the presence and absence of these defects. Results show that 1) removal of our relatively small spatial sensor distortion had minor effects on the tracking activity, 2) an Adapted Cooper-Harper controllability scale proved the most sensitive subjective indicator of the degradation of dynamic fidelity caused by increasing latency and decreasing frame rates, and 3) performance, as measured by normalized RMS tracking error or subjective impressions, was more markedly influenced by changing visual latency than by update rate.

Location estimation in wireless sensor networks using spring-relaxation technique.

PubMed

Zhang, Qing; Foh, Chuan Heng; Seet, Boon-Chong; Fong, A C M

2010-01-01

Accurate and low-cost autonomous self-localization is a critical requirement of various applications of a large-scale distributed wireless sensor network (WSN). Due to its massive deployment of sensors, explicit measurements based on specialized localization hardware such as the Global Positioning System (GPS) is not practical. In this paper, we propose a low-cost WSN localization solution. Our design uses received signal strength indicators for ranging, light weight distributed algorithms based on the spring-relaxation technique for location computation, and the cooperative approach to achieve certain location estimation accuracy with a low number of nodes with known locations. We provide analysis to show the suitability of the spring-relaxation technique for WSN localization with cooperative approach, and perform simulation experiments to illustrate its accuracy in localization.

Two-Scale Simulation of Drop-Induced Failure of Polysilicon MEMS Sensors

PubMed Central

Mariani, Stefano; Ghisi, Aldo; Corigliano, Alberto; Martini, Roberto; Simoni, Barbara

2011-01-01

In this paper, an industrially-oriented two-scale approach is provided to model the drop-induced brittle failure of polysilicon MEMS sensors. The two length-scales here investigated are the package (macroscopic) and the sensor (mesoscopic) ones. Issues related to the polysilicon morphology at the micro-scale are disregarded; an upscaled homogenized constitutive law, able to describe the brittle cracking of silicon, is instead adopted at the meso-scale. The two-scale approach is validated against full three-scale Monte-Carlo simulations, which allow for stochastic effects linked to the microstructural properties of polysilicon. Focusing on inertial MEMS sensors exposed to drops, it is shown that the offered approach matches well the experimentally observed failure mechanisms. PMID:22163885

Citizen Sensors for SHM: Use of Accelerometer Data from Smartphones

PubMed Central

Feng, Maria; Fukuda, Yoshio; Mizuta, Masato; Ozer, Ekin

2015-01-01

Ubiquitous smartphones have created a significant opportunity to form a low-cost wireless Citizen Sensor network and produce big data for monitoring structural integrity and safety under operational and extreme loads. Such data are particularly useful for rapid assessment of structural damage in a large urban setting after a major event such as an earthquake. This study explores the utilization of smartphone accelerometers for measuring structural vibration, from which structural health and post-event damage can be diagnosed. Widely available smartphones are tested under sinusoidal wave excitations with frequencies in the range relevant to civil engineering structures. Large-scale seismic shaking table tests, observing input ground motion and response of a structural model, are carried out to evaluate the accuracy of smartphone accelerometers under operational, white-noise and earthquake excitations of different intensity. Finally, the smartphone accelerometers are tested on a dynamically loaded bridge. The extensive experiments show satisfactory agreements between the reference and smartphone sensor measurements in both time and frequency domains, demonstrating the capability of the smartphone sensors to measure structural responses ranging from low-amplitude ambient vibration to high-amplitude seismic response. Encouraged by the results of this study, the authors are developing a citizen-engaging and data-analytics crowdsourcing platform towards a smartphone-based Citizen Sensor network for structural health monitoring and post-event damage assessment applications. PMID:25643056

Ultra-low power high precision magnetotelluric receiver array based customized computer and wireless sensor network

NASA Astrophysics Data System (ADS)

Chen, R.; Xi, X.; Zhao, X.; He, L.; Yao, H.; Shen, R.

2016-12-01

Dense 3D magnetotelluric (MT) data acquisition owns the benefit of suppressing the static shift and topography effect, can achieve high precision and high resolution inversion for underground structure. This method may play an important role in mineral exploration, geothermal resources exploration, and hydrocarbon exploration. It's necessary to reduce the power consumption greatly of a MT signal receiver for large-scale 3D MT data acquisition while using sensor network to monitor data quality of deployed MT receivers. We adopted a series of technologies to realized above goal. At first, we designed an low-power embedded computer which can couple with other parts of MT receiver tightly and support wireless sensor network. The power consumption of our embedded computer is less than 1 watt. Then we designed 4-channel data acquisition subsystem which supports 24-bit analog-digital conversion, GPS synchronization, and real-time digital signal processing. Furthermore, we developed the power supply and power management subsystem for MT receiver. At last, a series of software, which support data acquisition, calibration, wireless sensor network, and testing, were developed. The software which runs on personal computer can monitor and control over 100 MT receivers on the field for data acquisition and quality control. The total power consumption of the receiver is about 2 watts at full operation. The standby power consumption is less than 0.1 watt. Our testing showed that the MT receiver can acquire good quality data at ground with electrical dipole length as 3 m. Over 100 MT receivers were made and used for large-scale geothermal exploration in China with great success.

New early warning system for gravity-driven ruptures based on codetection of acoustic signal

NASA Astrophysics Data System (ADS)

Faillettaz, J.

2016-12-01

Gravity-driven rupture phenomena in natural media - e.g. landslide, rockfalls, snow or ice avalanches - represent an important class of natural hazards in mountainous regions. To protect the population against such events, a timely evacuation often constitutes the only effective way to secure the potentially endangered area. However, reliable prediction of imminence of such failure events remains challenging due to the nonlinear and complex nature of geological material failure hampered by inherent heterogeneity, unknown initial mechanical state, and complex load application (rainfall, temperature, etc.). Here, a simple method for real-time early warning that considers both the heterogeneity of natural media and characteristics of acoustic emissions attenuation is proposed. This new method capitalizes on codetection of elastic waves emanating from microcracks by multiple and spatially separated sensors. Event-codetection is considered as surrogate for large event size with more frequent codetected events (i.e., detected concurrently on more than one sensor) marking imminence of catastrophic failure. Simple numerical model based on a Fiber Bundle Model considering signal attenuation and hypothetical arrays of sensors confirms the early warning potential of codetection principles. Results suggest that although statistical properties of attenuated signal amplitude could lead to misleading results, monitoring the emergence of large events announcing impeding failure is possible even with attenuated signals depending on sensor network geometry and detection threshold. Preliminary application of the proposed method to acoustic emissions during failure of snow samples has confirmed the potential use of codetection as indicator for imminent failure at lab scale. The applicability of such simple and cheap early warning system is now investigated at a larger scale (hillslope). First results of such a pilot field experiment are presented and analysed.

Properties of piezoresistive silicon nano-scale cantilevers with applications to BioNEMS

NASA Astrophysics Data System (ADS)

Arlett, Jessica Lynn

Over the last decade a great deal of interest has been raised in applications of Microelectromechanical Sensors [MEMS] for the detection of biological molecules and to the study of their forces of interaction. Experiments in these areas have included Force Spectroscopy (Chemical Force Microscopy), MEMS patch clamp technology, and surface stress sensors. All of these technologies suffer from limitations on temporal response and involve devices with active surface areas that are large compared to molecular dimensions. Biofunctionalized nanoelectromechanical systems (BioNEMS) have the potential to overcome both of these hurdles, offering important new prospects for single-molecule force assays that are amenable to large scale integration. Results are presented here on the characterization of piezoresistive silicon cantilevers with applications to BioNEMS devices. The cantilevers were characterized by studying their response in gaseous ambients under a number of drive conditions including magnetic, piezoelectric, and thermal actuation, in addition to passive detection of the thermomechanical response. The measurements were performed at liquid helium temperature, at room temperature, and over a range of pressures (atmospheric pressure to 30mT). Theoretical studies have been performed on the response of these devices to Brownian fluctuations in fluid, on the feasibility of these devices as surface stress sensors, and on improvements in device design as compared to piezoresistive surface stress sensors currently discussed in the literature. The devices were encapsulated in microfluidics and measurements were performed to show the noise floor in fluid. The piezoresistive response of the device in fluid was shown through the use of pulsatory fluidic drive. As a proof of concept, biodetection experiments are presented for biotin labeled beads. The biofunctionalization for the latter experiment was performed entirely within the microfluidics. A discussion of how these experiments can be extended to other cells, spores, and molecules is presented.

Autonomous UAV-based mapping of large-scale urban firefights

NASA Astrophysics Data System (ADS)

Snarski, Stephen; Scheibner, Karl; Shaw, Scott; Roberts, Randy; LaRow, Andy; Breitfeller, Eric; Lupo, Jasper; Nielson, Darron; Judge, Bill; Forren, Jim

2006-05-01

This paper describes experimental results from a live-fire data collect designed to demonstrate the ability of IR and acoustic sensing systems to detect and map high-volume gunfire events from tactical UAVs. The data collect supports an exploratory study of the FightSight concept in which an autonomous UAV-based sensor exploitation and decision support capability is being proposed to provide dynamic situational awareness for large-scale battalion-level firefights in cluttered urban environments. FightSight integrates IR imagery, acoustic data, and 3D scene context data with prior time information in a multi-level, multi-step probabilistic-based fusion process to reliably locate and map the array of urban firing events and firepower movements and trends associated with the evolving urban battlefield situation. Described here are sensor results from live-fire experiments involving simultaneous firing of multiple sub/super-sonic weapons (2-AK47, 2-M16, 1 Beretta, 1 Mortar, 1 rocket) with high optical and acoustic clutter at ranges up to 400m. Sensor-shooter-target configurations and clutter were designed to simulate UAV sensing conditions for a high-intensity firefight in an urban environment. Sensor systems evaluated were an IR bullet tracking system by Lawrence Livermore National Laboratory (LLNL) and an acoustic gunshot detection system by Planning Systems, Inc. (PSI). The results demonstrate convincingly the ability for the LLNL and PSI sensor systems to accurately detect, separate, and localize multiple shooters and the associated shot directions during a high-intensity firefight (77 rounds in 5 sec) in a high acoustic and optical clutter environment with very low false alarms. Preliminary fusion processing was also examined that demonstrated an ability to distinguish co-located shooters (shooter density), range to <0.5 m accuracy at 400m, and weapon type. The combined results of the high-intensity firefight data collect and a detailed systems study demonstrate the readiness of the FightSight concept for full system development and integration.

Scales of variability of bio-optical properties as observed from near-surface drifters

NASA Technical Reports Server (NTRS)

Abbott, Mark R.; Brink, Kenneth H.; Booth, C. R.; Blasco, Dolors; Swenson, Mark S.; Davis, Curtiss O.; Codispoti, L. A.

1995-01-01

A drifter equipped with bio-optical sensors and an automated water sampler was deployed in the California Current as part of the coastal transition zone program to study the biological, chemical, and physical dynamics of the meandering filaments. During deployments in 1987 and 1988, measurements were made of fluorescence, downwelling irradiance, upwelling radiance, and beam attenuation using several bio-optical sensors. Samples were collected by an automated sampler for later analysis of nutrients and phytoplankton species compositon. Large-scale spatial and temporal changes in the bio-optical and biological properties of the region were driven by changes in phytoplankton species composition which, in turn, were associated with the meandering circulation. Variance spectra of the bio-optical paramenters revealed fluctuations on both diel and semidiurnal scales, perhaps associated with solar variations and internal tides, respectively. Offshore, inertial-scale fluctuations were apparent in the variance spectra of temperature, fluorescence, and beam attenuation. Although calibration samples can help remove some of these variations, these results suggest that the use of bio-optical data from unattended platforms such as moorings and drifters must be analyzed carefully. Characterization of the scaled of phytoplankton variability must account for the scales of variability in the algorithms used to convert bio-optical measurments into biological quantities.

Coarse Scale In Situ Albedo Observations over Heterogeneous Land Surfaces and Validation Strategy

NASA Astrophysics Data System (ADS)

Xiao, Q.; Wu, X.; Wen, J.; BAI, J., Sr.

2017-12-01

To evaluate and improve the quality of coarse-pixel land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. The performance of albedo validation depends on the quality of ground-based albedo measurements at a corresponding coarse-pixel scale, which can be conceptualized as the "truth" value of albedo at coarse-pixel scale. The wireless sensor network (WSN) technology provides access to continuously observe on the large pixel scale. Taking the albedo products as an example, this paper was dedicated to the validation of coarse-scale albedo products over heterogeneous surfaces based on the WSN observed data, which is aiming at narrowing down the uncertainty of results caused by the spatial scaling mismatch between satellite and ground measurements over heterogeneous surfaces. The reference value of albedo at coarse-pixel scale can be obtained through an upscaling transform function based on all of the observations for that pixel. We will devote to further improve and develop new method that that are better able to account for the spatio-temporal characteristic of surface albedo in the future. Additionally, how to use the widely distributed single site measurements over the heterogeneous surfaces is also a question to be answered. Keywords: Remote sensing; Albedo; Validation; Wireless sensor network (WSN); Upscaling; Heterogeneous land surface; Albedo truth at coarse-pixel scale

Research on precision grinding technology of large scale and ultra thin optics

NASA Astrophysics Data System (ADS)

Zhou, Lian; Wei, Qiancai; Li, Jie; Chen, Xianhua; Zhang, Qinghua

2018-03-01

The flatness and parallelism error of large scale and ultra thin optics have an important influence on the subsequent polishing efficiency and accuracy. In order to realize the high precision grinding of those ductile elements, the low deformation vacuum chuck was designed first, which was used for clamping the optics with high supporting rigidity in the full aperture. Then the optics was planar grinded under vacuum adsorption. After machining, the vacuum system was turned off. The form error of optics was on-machine measured using displacement sensor after elastic restitution. The flatness would be convergenced with high accuracy by compensation machining, whose trajectories were integrated with the measurement result. For purpose of getting high parallelism, the optics was turned over and compensation grinded using the form error of vacuum chuck. Finally, the grinding experiment of large scale and ultra thin fused silica optics with aperture of 430mm×430mm×10mm was performed. The best P-V flatness of optics was below 3 μm, and parallelism was below 3 ″. This machining technique has applied in batch grinding of large scale and ultra thin optics.

Investigation of Hydrological Response of Three Identical Artificial Hillslopes at the Landscape Evolution Observatory

NASA Astrophysics Data System (ADS)

Matos, K.; Alves Meira Neto, A.; Troch, P. A. A.; Volkmann, T.

2017-12-01

Hydrological processes at the hillslope scale are complex and heterogeneous, but monitoring hillslopes with a large number of sensors or replicate experimental designs is rarely feasible. The Landscape Evolution Observatory (LEO) at Biosphere 2 consists of three replicated, large (330 m2) artificial hillslopes (East, Center and West) packed with 1-m depth of initially homogeneous, basaltic soil. Each landscape contains a spatially dense network of sensors capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture content and water potential, as well as the hillslope-integrated water balance components. A sophisticated irrigation system allows performing controlled forcing experiments. The three hillslopes are thought to be nearly identical, however recent data showed significant differences in discharge and storage behavior. A 45-day periodic-steady-state tracer experiment was conducted in November and December of 2016, where a 3.5-day long, identical irrigation sequence was repeated 15 times. Each sequence's rainfall, runoff, and storage dynamics were recorded, and distributed moisture characteristics were derived using paired moisture content and matric potential data from 496 positions in each hillslope. In order to understand why the three hillslopes behave hydrologically different, we analyzed soil water retention characteristics at various scales ranging from individually paired moisture and matric potential to whole-hillslope soil water retention characteristics. The results confirm the distinct hydrological behavior between the three hillslopes. The East and West hillslopes behave more similar with respect to the release of water. In contrast, the East and Center hillslopes are more similar with respect to their storage behavior. The differences in hillslope behavior arising from three identically built hillslopes are a surprising and beneficial opportunity to explore how differences in small-scale heterogeneity can impact hydrological dynamics at the hillslope scale.

Using Custom Fiber Bragg Grating-Based Sensors to Monitor Artificial Landslides

PubMed Central

Zhang, Qinghua; Wang, Yuan; Sun, Yangyang; Gao, Lei; Zhang, Zhenglin; Zhang, Wenyuan; Zhao, Pengchong; Yue, Yin

2016-01-01

Four custom fiber Bragg grating (FBG)-based sensors are developed to monitor an artificial landslide located in Nanjing, China. The sensors are composed of a rod and two FBGs. Based on the strength of the rods, two sensors are referred to as “hard sensors” (Sensor 1 and Sensor 2), the other two are referred to as “soft sensors” (Sensor 3 and Sensor 4). The two FBGs are fixed on each sensor rod at distances of 50 cm and 100 cm from the top of the rod (an upper FBG and a lower FBG). In the experiment presented in this paper, the sensors are installed on a slope on which an artificial landslide is generated through both machine-based and manual excavation. The fiber sensing system consists of the four custom FBG-based sensors, optical fiber, a static fiber grating demodulation instrument (SM125), and a PC with the necessary software. Experimental data was collected in the presence of an artificial landslide, and the results show that the lower FBGs are more sensitive than the upper FBGs for all four of the custom sensors. It was also found that Sensor 2 and Sensor 4 are more capable of monitoring small-scale landslides than Sensor 1 and Sensor 3, and this is mainly due to their placement location with respect to the landslide. The stronger rods used in the hard sensors make them more adaptable to the harsh environments of large landslides. Thus, hard sensors should be fixed near the landslide, while soft sensors should be placed farther away from the landslide. In addition, a clear tendency of strain variation can be detected by the soft sensors, which can be used to predict landslides and raise a hazard alarm. PMID:27598163

Implications of sensor design for coral reef detection: Upscaling ground hyperspectral imagery in spatial and spectral scales

NASA Astrophysics Data System (ADS)

Caras, Tamir; Hedley, John; Karnieli, Arnon

2017-12-01

Remote sensing offers a potential tool for large scale environmental surveying and monitoring. However, remote observations of coral reefs are difficult especially due to the spatial and spectral complexity of the target compared to sensor specifications as well as the environmental implications of the water medium above. The development of sensors is driven by technological advances and the desired products. Currently, spaceborne systems are technologically limited to a choice between high spectral resolution and high spatial resolution, but not both. The current study explores the dilemma of whether future sensor design for marine monitoring should prioritise on improving their spatial or spectral resolution. To address this question, a spatially and spectrally resampled ground-level hyperspectral image was used to test two classification elements: (1) how the tradeoff between spatial and spectral resolutions affects classification; and (2) how a noise reduction by majority filter might improve classification accuracy. The studied reef, in the Gulf of Aqaba (Eilat), Israel, is heterogeneous and complex so the local substrate patches are generally finer than currently available imagery. Therefore, the tested spatial resolution was broadly divided into four scale categories from five millimeters to one meter. Spectral resolution resampling aimed to mimic currently available and forthcoming spaceborne sensors such as (1) Environmental Mapping and Analysis Program (EnMAP) that is characterized by 25 bands of 6.5 nm width; (2) VENμS with 12 narrow bands; and (3) the WorldView series with broadband multispectral resolution. Results suggest that spatial resolution should generally be prioritized for coral reef classification because the finer spatial scale tested (pixel size < 0.1 m) may compensate for some low spectral resolution drawbacks. In this regard, it is shown that the post-classification majority filtering substantially improves the accuracy of all pixel sizes up to the point where the kernel size reaches the average unit size (pixel < 0.25 m). However, careful investigation as to the effect of band distribution and choice could improve the sensor suitability for the marine environment task. This in mind, while the focus in this study was on the technologically limited spaceborne design, aerial sensors may presently provide an opportunity to implement the suggested setup.

Simulating the directional, spectral and textural properties of a large-scale scene at high resolution using a MODIS BRDF product

NASA Astrophysics Data System (ADS)

Rengarajan, Rajagopalan; Goodenough, Adam A.; Schott, John R.

2016-10-01

Many remote sensing applications rely on simulated scenes to perform complex interaction and sensitivity studies that are not possible with real-world scenes. These applications include the development and validation of new and existing algorithms, understanding of the sensor's performance prior to launch, and trade studies to determine ideal sensor configurations. The accuracy of these applications is dependent on the realism of the modeled scenes and sensors. The Digital Image and Remote Sensing Image Generation (DIRSIG) tool has been used extensively to model the complex spectral and spatial texture variation expected in large city-scale scenes and natural biomes. In the past, material properties that were used to represent targets in the simulated scenes were often assumed to be Lambertian in the absence of hand-measured directional data. However, this assumption presents a limitation for new algorithms that need to recognize the anisotropic behavior of targets. We have developed a new method to model and simulate large-scale high-resolution terrestrial scenes by combining bi-directional reflectance distribution function (BRDF) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data, high spatial resolution data, and hyperspectral data. The high spatial resolution data is used to separate materials and add textural variations to the scene, and the directional hemispherical reflectance from the hyperspectral data is used to adjust the magnitude of the MODIS BRDF. In this method, the shape of the BRDF is preserved since it changes very slowly, but its magnitude is varied based on the high resolution texture and hyperspectral data. In addition to the MODIS derived BRDF, target/class specific BRDF values or functions can also be applied to features of specific interest. The purpose of this paper is to discuss the techniques and the methodology used to model a forest region at a high resolution. The simulated scenes using this method for varying view angles show the expected variations in the reflectance due to the BRDF effects of the Harvard forest. The effectiveness of this technique to simulate real sensor data is evaluated by comparing the simulated data with the Landsat 8 Operational Land Image (OLI) data over the Harvard forest. Regions of interest were selected from the simulated and the real data for different targets and their Top-of-Atmospheric (TOA) radiance were compared. After adjusting for scaling correction due to the difference in atmospheric conditions between the simulated and the real data, the TOA radiance is found to agree within 5 % in the NIR band and 10 % in the visible bands for forest targets under similar illumination conditions. The technique presented in this paper can be extended for other biomes (e.g. desert regions and agricultural regions) by using the appropriate geographic regions. Since the entire scene is constructed in a simulated environment, parameters such as BRDF or its effects can be analyzed for general or target specific algorithm improvements. Also, the modeling and simulation techniques can be used as a baseline for the development and comparison of new sensor designs and to investigate the operational and environmental factors that affects the sensor constellations such as Sentinel and Landsat missions.

Confronting weather and climate models with observational data from soil moisture networks over the United States

PubMed Central

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal D.; Balsamo, Gianpaolo; Lawrence, David M.

2018-01-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison. PMID:29645013

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

NASA Technical Reports Server (NTRS)

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;

Confronting weather and climate models with observational data from soil moisture networks over the United States.

PubMed

Dirmeyer, Paul A; Wu, Jiexia; Norton, Holly E; Dorigo, Wouter A; Quiring, Steven M; Ford, Trenton W; Santanello, Joseph A; Bosilovich, Michael G; Ek, Michael B; Koster, Randal D; Balsamo, Gianpaolo; Lawrence, David M

2016-04-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

Comparison of Tissue Heat Balance- and Thermal Dissipation-Derived Sap Flow Measurements in Ring-Porous Oaks and a Pine

PubMed Central

Renninger, Heidi J.; Schäfer, Karina V. R.

2012-01-01

Sap flow measurements have become integral in many physiological and ecological investigations. A number of methods are used to estimate sap flow rates in trees, but probably the most popular is the thermal dissipation (TD) method because of its affordability, relatively low power consumption, and ease of use. However, there have been questions about the use of this method in ring-porous species and whether individual species and site calibrations are needed. We made concurrent measurements of sap flow rates using TD sensors and the tissue heat balance (THB) method in two oak species (Quercus prinus Willd. and Quercus velutina Lam.) and one pine (Pinus echinata Mill.). We also made concurrent measurements of sap flow rates using both 1 and 2-cm long TD sensors in both oak species. We found that both the TD and THB systems tended to match well in the pine individual, but sap flow rates were underestimated by 2-cm long TD sensors in five individuals of the two ring-porous oak species. Underestimations of 20–35% occurred in Q. prinus even when a “Clearwater” correction was applied to account for the shallowness of the sapwood depth relative to the sensor length and flow rates were underestimated by up to 50% in Q. velutina. Two centimeter long TD sensors also underestimated flow rates compared with 1-cm long sensors in Q. prinus, but only at large flow rates. When 2-cm long sensor data in Q. prinus were scaled using the regression with 1-cm long data, daily flow rates matched well with the rates measured by the THB system. Daily plot level transpiration estimated using TD sap flow rates and scaled 1 cm sensor data averaged about 15% lower than those estimated by the THB method. Therefore, these results suggest that 1-cm long sensors are appropriate in species with shallow sapwood, however more corrections may be necessary in ring-porous species. PMID:22661978

Scale up of large ALON® and spinel windows

NASA Astrophysics Data System (ADS)

Goldman, Lee M.; Kashalikar, Uday; Ramisetty, Mohan; Jha, Santosh; Sastri, Suri

2017-05-01

Aluminum Oxynitride (ALON® Transparent Ceramic) and Magnesia Aluminate Spinel (Spinel) combine broadband transparency with excellent mechanical properties. Their cubic structure means that they are transparent in their polycrystalline form, allowing them to be manufactured by conventional powder processing techniques. Surmet has scaled up its ALON® production capability to produce and deliver windows as large as 4.4 sq ft. We have also produced our first 6 sq ft window. We are in the process of producing 7 sq ft ALON® window blanks for armor applications; and scale up to even larger, high optical quality blanks for Recce window applications is underway. Surmet also produces spinel for customers that require superior transmission at the longer wavelengths in the mid wave infra-red (MWIR). Spinel windows have been limited to smaller sizes than have been achieved with ALON. To date the largest spinel window produced is 11x18-in, and windows 14x20-in size are currently in process. Surmet is now scaling up its spinel processing capability to produce high quality window blanks as large as 19x27-in for sensor applications.

Faulty node detection in wireless sensor networks using a recurrent neural network

NASA Astrophysics Data System (ADS)

Atiga, Jamila; Mbarki, Nour Elhouda; Ejbali, Ridha; Zaied, Mourad

2018-04-01

The wireless sensor networks (WSN) consist of a set of sensors that are more and more used in surveillance applications on a large scale in different areas: military, Environment, Health ... etc. Despite the minimization and the reduction of the manufacturing costs of the sensors, they can operate in places difficult to access without the possibility of reloading of battery, they generally have limited resources in terms of power of emission, of processing capacity, data storage and energy. These sensors can be used in a hostile environment, such as, for example, on a field of battle, in the presence of fires, floods, earthquakes. In these environments the sensors can fail, even in a normal operation. It is therefore necessary to develop algorithms tolerant and detection of defects of the nodes for the network of sensor without wires, therefore, the faults of the sensor can reduce the quality of the surveillance if they are not detected. The values that are measured by the sensors are used to estimate the state of the monitored area. We used the Non-linear Auto- Regressive with eXogeneous (NARX), the recursive architecture of the neural network, to predict the state of a node of a sensor from the previous values described by the functions of time series. The experimental results have verified that the prediction of the State is enhanced by our proposed model.

Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

2015-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, MODIS, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. HySDS is a Hybrid-Cloud Science Data System that has been developed and applied under NASA AIST, MEaSUREs, and ACCESS grants. HySDS uses the SciFlow workflow engine to partition analysis workflows into parallel tasks (e.g. segmenting by time or space) that are pushed into a durable job queue. The tasks are "pulled" from the queue by worker Virtual Machines (VM's) and executed in an on-premise Cloud (Eucalyptus or OpenStack) or at Amazon in the public Cloud or govCloud. In this way, years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the transferred data. We are using HySDS to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a MEASURES grant. We will present the architecture of HySDS, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. Our system demonstrates how one can pull A-Train variables (Levels 2 & 3) on-demand into the Amazon Cloud, and cache only those variables that are heavily used, so that any number of compute jobs can be executed "near" the multi-sensor data. Decade-long, multi-sensor studies can be performed without pre-staging data, with the researcher paying only his own Cloud compute bill.

(Un)Natural Disasters: The Electoral Cycle Outweighs the Hydrologic Cycle in Drought Declaration in Northeast Brazil

NASA Astrophysics Data System (ADS)

Camps-Valls, G.; Gomez-Chova, L.; Mateo, G.; Laparra, V.; Perez-Suay, A.; Munoz-Mari, J.

2016-12-01

Current Earth-observation (EO) applications for image classification have to deal with an unprecedented big amount of heterogeneous and complex data sources. Spatio-temporally explicit classification methods are a requirement in a variety of Earth system data processing applications. Upcoming missions such as the super-spectral Copernicus Sentinels EnMAP and FLEX will soon provide unprecedented data streams. Very high resolution (VHR) sensors like Worldview-3 also pose big challenges to data processing. The challenge is not only attached to optical sensors but also to infrared sounders and radar images which increased in spectral, spatial and temporal resolution. Besides, we should not forget the availability of the extremely large remote sensing data archives already collected by several past missions, such ENVISAT, Cosmo-SkyMED, Landsat, SPOT, or Seviri/MSG. These large-scale data problems require enhanced processing techniques that should be accurate, robust and fast. Standard parameter retrieval and classification algorithms cannot cope with this new scenario efficiently. In this work, we review the field of large scale kernel methods for both atmospheric parameter retrieval and cloud detection using infrared sounding IASI data and optical Seviri/MSG imagery. We propose novel Gaussian Processes (GPs) to train problems with millions of instances and high number of input features. Algorithms can cope with non-linearities efficiently, accommodate multi-output problems, and provide confidence intervals for the predictions. Several strategies to speed up algorithms are devised: random Fourier features and variational approaches for cloud classification using IASI data and Seviri/MSG, and engineered randomized kernel functions and emulation in temperature, moisture and ozone atmospheric profile retrieval from IASI as a proxy to the upcoming MTG-IRS sensor. Excellent compromise between accuracy and scalability are obtained in all applications.

The evolution and exploitation of the fiber-optic hydrophone

NASA Astrophysics Data System (ADS)

Hill, David J.

2007-07-01

In the late 1970s one of the first applications identified for fibre-optic sensing was the fibre-optic hydrophone. It was recognised that the technology had the potential to provide a cost effective solution for large-scale arrays of highly sensitive hydrophones which could be interrogated over large distances. Consequently both the United Kingdom and United States navies funded the development of this sonar technology to the point that it is now deployed on submarines and as seabed arrays. The basic design of a fibre-optic hydrophone has changed little; comprising a coil of optical fibre wound on a compliant mandrel, interrogated using interferometric techniques. Although other approaches are being investigated, including the development of fibre-laser hydrophones, the interferometric approach remains the most efficient way to create highly multiplexed arrays of acoustic sensors. So much so, that the underlying technology is now being exploited in civil applications. Recently the exploration and production sector of the oil and gas industry has begun funding the development of fibre-optic seismic sensing using seabed mounted, very large-scale arrays of four component (three accelerometers and a hydrophone) packages based upon the original technology developed for sonar systems. This has given new impetus to the development of the sensors and the associated interrogation systems which has led to the technology being adopted for other commercial uses. These include the development of networked in-road fibre-optic Weigh-in-Motion sensors and of intruder detection systems which are able to acoustically monitor long lengths of border, on both land and at sea. After two decades, the fibre-optic hydrophone and associated technology has matured and evolved into a number of highly capable sensing solutions used by a range of industries.

A wireless laser displacement sensor node for structural health monitoring.

PubMed

Park, Hyo Seon; Kim, Jong Moon; Choi, Se Woon; Kim, Yousok

2013-09-30

This study describes a wireless laser displacement sensor node that measures displacement as a representative damage index for structural health monitoring (SHM). The proposed measurement system consists of a laser displacement sensor (LDS) and a customized wireless sensor node. Wireless communication is enabled by a sensor node that consists of a sensor module, a code division multiple access (CDMA) communication module, a processor, and a power module. An LDS with a long measurement distance is chosen to increase field applicability. For a wireless sensor node driven by a battery, we use a power control module with a low-power processor, which facilitates switching between the sleep and active modes, thus maximizing the power consumption efficiency during non-measurement and non-transfer periods. The CDMA mode is also used to overcome the limitation of communication distance, which is a challenge for wireless sensor networks and wireless communication. To evaluate the reliability and field applicability of the proposed wireless displacement measurement system, the system is tested onsite to obtain the required vertical displacement measurements during the construction of mega-trusses and an edge truss, which are the primary structural members in a large-scale irregular building currently under construction. The measurement values confirm the validity of the proposed wireless displacement measurement system and its potential for use in safety evaluations of structural elements.

Limitations and tradeoffs in synchronization of large-scale networks with uncertain links

PubMed Central

Diwadkar, Amit; Vaidya, Umesh

2016-01-01

The synchronization of nonlinear systems connected over large-scale networks has gained popularity in a variety of applications, such as power grids, sensor networks, and biology. Stochastic uncertainty in the interconnections is a ubiquitous phenomenon observed in these physical and biological networks. We provide a size-independent network sufficient condition for the synchronization of scalar nonlinear systems with stochastic linear interactions over large-scale networks. This sufficient condition, expressed in terms of nonlinear dynamics, the Laplacian eigenvalues of the nominal interconnections, and the variance and location of the stochastic uncertainty, allows us to define a synchronization margin. We provide an analytical characterization of important trade-offs between the internal nonlinear dynamics, network topology, and uncertainty in synchronization. For nearest neighbour networks, the existence of an optimal number of neighbours with a maximum synchronization margin is demonstrated. An analytical formula for the optimal gain that produces the maximum synchronization margin allows us to compare the synchronization properties of various complex network topologies. PMID:27067994

Development of X-Ray Microcalorimeter Imaging Spectrometers for the X-Ray Surveyor Mission Concept

NASA Technical Reports Server (NTRS)

Bandler, Simon R.; Adams, Joseph S.; Chervenak, James A.; Datesman, Aaron M.; Eckart, Megan E.; Finkbeiner, Fred M.; Kelley, Richard L.; Kilbourne, Caroline A.; Betncourt-Martinez, Gabriele; Miniussi, Antoine R.;

An Event-based Assessment of Uncertainty in Measurements Between Multiple Precipitation Sensors During the North American Monsoon

NASA Astrophysics Data System (ADS)

Kautz, M. A.; Keefer, T.; Demaria, E. M.; Goodrich, D. C.; Hazenberg, P.; Petersen, W. A.; Wingo, M. T.; Smith, J.

2017-12-01

The USDA - Agricultural Research Service (USDA-ARS) Long-Term Agroecosystem Research network (LTAR) is a partnership between 18 long-term research sites across the United States. As part of the program, LTAR aims to assemble a network of common sensors and measurements of hydrological, meteorological, and biophysical variables to accompany the legacy datasets of individual LTAR sites. Uncertainty remains as to how the common sensor-based measurements will compare to those measured with existing sensors at each site. The USDA-ARS Southwest Watershed Research Center (SWRC) operated Walnut Gulch Experimental Watershed (WGEW) represents the semiarid grazing lands located in southeastern Arizona in the LTAR network. The bimodal precipitation regime of this region is characterized by large-scale frontal precipitation in the winter and isolated, high-intensity, convective thunderstorms in the summer during the North American Monsoon (NAM). SWRC maintains a network of 90 rain gauges across the 150 km2 WGEW and surrounding area, with measurements dating back to the 1950's. The high intensity and isolated nature of the summer storms has historically made it difficult to quantify compared to other regimes in the US. This study assesses the uncertainty of measurement between the common LTAR Belfort All Weather Precipitation Gauge (AEPG 600) and the legacy WGEW weighing-type raingage. Additionally, in a collaboration with NASA Global Precipitation Measurement mission (GPM) and the University of Arizona a dense array of precipitation measuring sensors was installed at WGEW within a 10 meter radius for observation during the NAM, July through October 2017. In addition to two WGEW weighing-type gauges, the array includes: an AEPG 600, a tipping bucket, a weighing-bucket installed with orifice at ground level, an OTT Pluvio2 rain gauge, a Two-Dimensional Video Disdrometer (2DVD), and three OTT Parsivel2 disdrometers. An event-based comparison was made between precipitation sensors using metrics including total depth, peak intensity (1, 15, 30, and 60 minute), event duration, time to peak intensity, and start time of event. These results provide further insight into the uncertainties of measuring point-based precipitation in this unique precipitation regime and representation in large-scale observation networks.

Social Media in Crisis Management and Forensic Disaster Analysis

NASA Astrophysics Data System (ADS)

Dittrich, André; Lucas, Christian

2014-05-01

Today, modern sensors or sensor networks provide good quality measurements for the observation of large-scale emergencies as a result of natural disasters. Mostly however, only at certain points in their respective locations and for a very limited number of measurement parameters (e.g. seismograph) and not over the entire course of a disaster event. The proliferation of different social media application (e.g. Twitter, Facebook, Google+, etc.), yields the possibility to use the resulting data as a free and fast supplement or complement to traditional monitoring techniques. In particular, these new channels can serve for rapid detection, for information gathering for emergency protection and for information dissemination. Thus, each user of these networks represents a so-called virtual sensor ('social sensor'), whose eyewitness account can be important for understanding the situation on the ground. The advantages of these social sensors are the high mobility, the versatility of the parameters that can be captured (text, images, videos, etc.) as well as the rapid spread of information. Due to the subjective characteristics however, the data often show different quality and quantity. Against this background, it is essential for an application in crisis management to reasonably (pre-)process the data from social media. Hence, fully-automated processes are used which adequately filter and structure the enormous amount of information and associate it with an event, respectively, a geographic location. This is done through statistical monitoring of the volume of messages (Twitter) in different geographic regions of the world. In combination with a frequency analysis with respect to disaster-relevant terms (in 43 languages), thematic as well as spatio-temporal clustering, an initial assessment regarding the severity and extent of the detected event, its classification and (spatio-temporal) localization can be achieved. This detection in real time (2-5 minutes) thus allows gathering first responder reports or eyewitness reports, which can provide important information for a first situation analysis for the various officials and volunteers, especially in case of large-scale emergencies. Eventually, this can be used in combination with conventional sensors and information sources to conduct a detailed forensic disaster analysis of an event.

Non-contact XUV metrology of Ru/B4C multilayer optics by means of Hartmann wavefront analysis.

PubMed

Ruiz-Lopez, Mabel; Dacasa, Hugo; Mahieu, Benoit; Lozano, Magali; Li, Lu; Zeitoun, Philippe; Bleiner, Davide

2018-02-20

Short-wavelength imaging, spectroscopy, and lithography scale down the characteristic length-scale to nanometers. This poses tight constraints on the optics finishing tolerances, which is often difficult to characterize. Indeed, even a tiny surface defect degrades the reflectivity and spatial projection of such optics. In this study, we demonstrate experimentally that a Hartmann wavefront sensor for extreme ultraviolet (XUV) wavelengths is an effective non-contact analytical method for inspecting the surface of multilayer optics. The experiment was carried out in a tabletop laboratory using a high-order harmonic generation as an XUV source. The wavefront sensor was used to measure the wavefront errors after the reflection of the XUV beam on a spherical Ru/B 4 C multilayer mirror, scanning a large surface of approximately 40 mm in diameter. The results showed that the technique detects the aberrations in the nanometer range.

Synthesis of large scale graphene oxide using plasma enhanced chemical vapor deposition method and its application in humidity sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yang; Chen, Yuming, E-mail: yumingchen@fudan.edu.cn; Engineering Research Center of Advanced Lighting Technology, Ministry of Education, 220 Handan Road, Shanghai 00433

2016-03-14

Large scale graphene oxide (GO) is directly synthesized on copper (Cu) foil by plasma enhanced chemical vapor deposition method under 500 °C and even lower temperature. Compared to the modified Hummer's method, the obtained GO sheet in this article is large, and it is scalable according to the Cu foil size. The oxygen-contained groups in the GO are introduced through the residual gas of methane (99.9% purity). To prevent the Cu surface from the bombardment of the ions in the plasma, we use low intensity discharge. Our experiment reveals that growth temperature has important influence on the carbon to oxygen ratiomore » (C/O ratio) in the GO; and it also affects the amount of π-π* bonds between carbon atoms. Preliminary experiments on a 6 mm × 12 mm GO based humidity sensor prove that the synthesized GO reacts well to the humidity change. Our GO synthesis method may provide another channel for obtaining large scale GO in gas sensing or other applications.« less

Ultra-high gain diffusion-driven organic transistor

PubMed Central

Torricelli, Fabrizio; Colalongo, Luigi; Raiteri, Daniele; Kovács-Vajna, Zsolt Miklós; Cantatore, Eugenio

2016-01-01

Emerging large-area technologies based on organic transistors are enabling the fabrication of low-cost flexible circuits, smart sensors and biomedical devices. High-gain transistors are essential for the development of large-scale circuit integration, high-sensitivity sensors and signal amplification in sensing systems. Unfortunately, organic field-effect transistors show limited gain, usually of the order of tens, because of the large contact resistance and channel-length modulation. Here we show a new organic field-effect transistor architecture with a gain larger than 700. This is the highest gain ever reported for organic field-effect transistors. In the proposed organic field-effect transistor, the charge injection and extraction at the metal–semiconductor contacts are driven by the charge diffusion. The ideal conditions of ohmic contacts with negligible contact resistance and flat current saturation are demonstrated. The approach is general and can be extended to any thin-film technology opening unprecedented opportunities for the development of high-performance flexible electronics. PMID:26829567

Non-negative Tensor Factorization for Robust Exploratory Big-Data Analytics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alexandrov, Boian; Vesselinov, Velimir Valentinov; Djidjev, Hristo Nikolov

Currently, large multidimensional datasets are being accumulated in almost every field. Data are: (1) collected by distributed sensor networks in real-time all over the globe, (2) produced by large-scale experimental measurements or engineering activities, (3) generated by high-performance simulations, and (4) gathered by electronic communications and socialnetwork activities, etc. Simultaneous analysis of these ultra-large heterogeneous multidimensional datasets is often critical for scientific discoveries, decision-making, emergency response, and national and global security. The importance of such analyses mandates the development of the next-generation of robust machine learning (ML) methods and tools for bigdata exploratory analysis.

Knowledge Discovery from Climate Data using Graph-Based Methods

NASA Astrophysics Data System (ADS)

Steinhaeuser, K.

2012-04-01

Climate and Earth sciences have recently experienced a rapid transformation from a historically data-poor to a data-rich environment, thus bringing them into the realm of the Fourth Paradigm of scientific discovery - a term coined by the late Jim Gray (Hey et al. 2009), the other three being theory, experimentation and computer simulation. In particular, climate-related observations from remote sensors on satellites and weather radars, in situ sensors and sensor networks, as well as outputs of climate or Earth system models from large-scale simulations, provide terabytes of spatio-temporal data. These massive and information-rich datasets offer a significant opportunity for advancing climate science and our understanding of the global climate system, yet current analysis techniques are not able to fully realize their potential benefits. We describe a class of computational approaches, specifically from the data mining and machine learning domains, which may be novel to the climate science domain and can assist in the analysis process. Computer scientists have developed spatial and spatio-temporal analysis techniques for a number of years now, and many of them may be applicable and/or adaptable to problems in climate science. We describe a large-scale, NSF-funded project aimed at addressing climate science question using computational analysis methods; team members include computer scientists, statisticians, and climate scientists from various backgrounds. One of the major thrusts is in the development of graph-based methods, and several illustrative examples of recent work in this area will be presented.

Distributed Coding/Decoding Complexity in Video Sensor Networks

PubMed Central

Cordeiro, Paulo J.; Assunção, Pedro

2012-01-01

Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality. PMID:22736972

Distributed coding/decoding complexity in video sensor networks.

PubMed

Cordeiro, Paulo J; Assunção, Pedro

2012-01-01

Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality.

Imaging Science Panel. Multispectral Imaging Science Working Group joint meeting with Information Science Panel: Introduction

NASA Technical Reports Server (NTRS)

1982-01-01

The state-of-the-art of multispectral sensing is reviewed and recommendations for future research and development are proposed. specifically, two generic sensor concepts were discussed. One is the multispectral pushbroom sensor utilizing linear array technology which operates in six spectral bands including two in the SWIR region and incorporates capabilities for stereo and crosstrack pointing. The second concept is the imaging spectrometer (IS) which incorporates a dispersive element and area arrays to provide both spectral and spatial information simultaneously. Other key technology areas included very large scale integration and the computer aided design of these devices.

The Influence of Radiosonde 'Age' on TRMM Field Campaign Soundings Humidity Correction

NASA Technical Reports Server (NTRS)

Roy, Biswadev; Halverson, Jeffrey B.; Wang, Jun-Hong

2002-01-01

Hundreds of Vaisala sondes with a RS80-H Humicap thin-film capacitor humidity sensor were launched during the Tropical Rainfall Measuring Mission (TRMM) field campaigns in Large Scale Biosphere-Atmosphere held in Brazil (LBA) and in Kwajalein experiment (KWAJEX) held in the Republic of Marshall Islands. Using Six humidity error correction algorithms by Wang et al., these sondes were corrected for significant dry bias in the RS80-H data. It is further shown that sonde surface temperature error must be corrected for a better representation of the relative humidity. This error becomes prominent due to sensor arm-heating in the first 50-s data.

Global Distribution of Aerosols Over the Open Ocean as Derived from the Coastal Zone Color Scanner

NASA Technical Reports Server (NTRS)

Stegmann, P. M.; Tindale, N. W.

1999-01-01

Climatological maps of monthly mean aerosol radiance levels derived from the coastal zone color scanner (CZCS) were constructed for the world's ocean basins. This is the first study to use the 7.5.-year CZCS data set to examine the distribution and seasonality of aerosols over the open ocean on a global scale. Examination of our satellite images found the most prominent large-scale patch of elevated aerosol radiances in each month off the coast of northwest Africa. The well-known, large-scale plumes of elevated aerosol levels in the Arabian Sea, the northwest Pacific, and off the east coast of North America were also successfully captured. Radiance data were extracted from 13 major open-ocean zones, ranging from the subpolar to equatorial regions. Results from these extractions revealed the aerosol load in both subpolar and subtropical zones to be higher in the Northern Hemisphere than in the Southern Hemisphere. Aerosol radiances in the subtropics of both hemispheres were about 2 times higher in summer than in winter. In subpolar regions, aerosol radiances in late spring/early summer were almost 3 times that observed in winter. In general, the aerosol signal was higher during the warmer months and lower during the cooler months, irrespective of location. A comparison between our mean monthly aerosol radiance maps with mean monthly chlorophyll maps (also from CZCS) showed similar seasonality between aerosol and chlorophyll levels in the subpolar zones of both hemispheres, i.e., high levels in summer, low levels in winter. In the subtropics of both hemispheres, however, chlorophyll levels were higher in winter months which coincided with a depressed aerosol signal. Our results indicate that the near-IR channel on ocean color sensors can be used to successfully capture well-known, large-scale aerosol plumes on a global scale and that future ocean color sensors may provide a platform for long-term synoptic studies of combined aerosol-phytoplankton productivity interactions.

An investigation of small scales of turbulence in a boundary layer at high Reynolds numbers

NASA Technical Reports Server (NTRS)

Wallace, James M.; Ong, L.; Balint, J.-L.

1993-01-01

The assumption that turbulence at large wave-numbers is isotropic and has universal spectral characteristics which are independent of the flow geometry, at least for high Reynolds numbers, has been a cornerstone of closure theories as well as of the most promising recent development in the effort to predict turbulent flows, viz. large eddy simulations. This hypothesis was first advanced by Kolmogorov based on the supposition that turbulent kinetic energy cascades down the scales (up the wave-numbers) of turbulence and that, if the number of these cascade steps is sufficiently large (i.e. the wave-number range is large), then the effects of anisotropies at the large scales are lost in the energy transfer process. Experimental attempts were repeatedly made to verify this fundamental assumption. However, Van Atta has recently suggested that an examination of the scalar and velocity gradient fields is necessary to definitively verify this hypothesis or prove it to be unfounded. Of course, this must be carried out in a flow with a sufficiently high Reynolds number to provide the necessary separation of scales in order unambiguously to provide the possibility of local isotropy at large wave-numbers. An opportunity to use our 12-sensor hot-wire probe to address this issue directly was made available at the 80'x120' wind tunnel at the NASA Ames Research Center, which is normally used for full-scale aircraft tests. An initial report on this high Reynolds number experiment and progress toward its evaluation is presented.

New methods for state estimation and adaptive observation of environmental flow systems leveraging coordinated swarms of sensor vehicles

NASA Astrophysics Data System (ADS)

Bewley, Thomas

2015-11-01

Accurate long-term forecasts of the path and intensity of hurricanes are imperative to protect property and save lives. Accurate estimations and forecasts of the spread of large-scale contaminant plumes, such as those from Deepwater Horizon, Fukushima, and recent volcanic eruptions in Iceland, are essential for assessing environment impact, coordinating remediation efforts, and in certain cases moving folks out of harm's way. The challenges in estimating and forecasting such systems include: (a) environmental flow modeling, (b) high-performance real-time computing, (c) assimilating measured data into numerical simulations, and (d) acquiring in-situ data, beyond what can be measured from satellites, that is maximally relevant for reducing forecast uncertainty. This talk will focus on new techniques for addressing (c) and (d), namely, data assimilation and adaptive observation, in both hurricanes and large-scale environmental plumes. In particular, we will present a new technique for the energy-efficient coordination of swarms of sensor-laden balloons for persistent, in-situ, distributed, real-time measurement of developing hurricanes, leveraging buoyancy control only (coupled with the predictable and strongly stratified flowfield within the hurricane). Animations of these results are available at http://flowcontrol.ucsd.edu/3dhurricane.mp4 and http://flowcontrol.ucsd.edu/katrina.mp4. We also will survey our unique hybridization of the venerable Ensemble Kalman and Variational approaches to large-scale data assimilation in environmental flow systems, and how essentially the dual of this hybrid approach may be used to solve the adaptive observation problem in a uniquely effective and rigorous fashion.

Massive Cloud-Based Big Data Processing for Ocean Sensor Networks and Remote Sensing

NASA Astrophysics Data System (ADS)

Schwehr, K. D.

2017-12-01

Until recently, the work required to integrate and analyze data for global-scale environmental issues was prohibitive both in cost and availability. Traditional desktop processing systems are not able to effectively store and process all the data, and super computer solutions are financially out of the reach of most people. The availability of large-scale cloud computing has created tools that are usable by small groups and individuals regardless of financial resources or locally available computational resources. These systems give scientists and policymakers the ability to see how critical resources are being used across the globe with little or no barrier to entry. Google Earth Engine has the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra, MODIS Aqua, and Global Land Data Assimilation Systems (GLDAS) data catalogs available live online. Here we demonstrate these data to calculate the correlation between lagged chlorophyll and rainfall to identify areas of eutrophication, matching these events to ocean currents from datasets like HYbrid Coordinate Ocean Model (HYCOM) to check if there are constraints from oceanographic configurations. The system can provide addition ground truth with observations from sensor networks like the International Comprehensive Ocean-Atmosphere Data Set / Voluntary Observing Ship (ICOADS/VOS) and Argo floats. This presentation is intended to introduce users to the datasets, programming idioms, and functionality of Earth Engine for large-scale, data-driven oceanography.

2001 Industry Studies: Electronics

DTIC Science & Technology

2001-01-01

Center, Dallas, TX Northrop Grumman Corp, Electronic Sensors & Systems, Baltimore, MD International Acer Incorporated, Hsin Chu, Taiwan Aerospace...manufacturing. Many of the large-scale fabrication foundries are offshore in such countries as Taiwan, Singapore and Malaysia .5 - 5 - The largest market for...done in the US. However, more of the actual mass manufacturing of the chips are done in Taiwan, Singapore, and Malaysia . A new semiconductor facility

Regional applicability of forest height and aboveground biomass models for the Geoscience Laser Altimeter System

Treesearch

Dirk Pflugmacher; Warren B. Cohen; Robert E. Kennedy; Michael. Lefsky

2008-01-01

Accurate estimates of forest aboveground biomass are needed to reduce uncertainties in global and regional terrestrial carbon fluxes. In this study we investigated the utility of the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land Elevation Satellite for large-scale biomass inventories. GLAS is the first spaceborne lidar sensor that will...

Distributed intelligent urban environment monitoring system

NASA Astrophysics Data System (ADS)

Du, Jinsong; Wang, Wei; Gao, Jie; Cong, Rigang

2018-02-01

The current environmental pollution and destruction have developed into a world-wide major social problem that threatens human survival and development. Environmental monitoring is the prerequisite and basis of environmental governance, but overall, the current environmental monitoring system is facing a series of problems. Based on the electrochemical sensor, this paper designs a small, low-cost, easy to layout urban environmental quality monitoring terminal, and multi-terminal constitutes a distributed network. The system has been small-scale demonstration applications and has confirmed that the system is suitable for large-scale promotion

Application of remote sensor data to geologic analysis of the Bonanza Test Site Colorado

NASA Technical Reports Server (NTRS)

Lee, K. (Compiler)

1973-01-01

A geologic map of the Bonanza Test Site is nearing completion. Using published large scale geologic maps from various sources, the geology of the area is being compiled on a base scaled at 1:250,000. Sources of previously published geologic mapping include: (1) USGS Bulletins; (2) professional papers and geologic quadrangle maps; (3) Bureau of Mines reports; (4) Colorado School of Mines quarterlies; and (5) Rocky Mountain Association of Geologist Guidebooks. This compilation will be used to evaluate ERTS, Skylab, and remote sensing underflight data.

Data-Gathering Scheme Using AUVs in Large-Scale Underwater Sensor Networks: A Multihop Approach

PubMed Central

Khan, Jawaad Ullah; Cho, Ho-Shin

2016-01-01

In this paper, we propose a data-gathering scheme for hierarchical underwater sensor networks, where multiple Autonomous Underwater Vehicles (AUVs) are deployed over large-scale coverage areas. The deployed AUVs constitute an intermittently connected multihop network through inter-AUV synchronization (in this paper, synchronization means an interconnection between nodes for communication) for forwarding data to the designated sink. In such a scenario, the performance of the multihop communication depends upon the synchronization among the vehicles. The mobility parameters of the vehicles vary continuously because of the constantly changing underwater currents. The variations in the AUV mobility parameters reduce the inter-AUV synchronization frequency contributing to delays in the multihop communication. The proposed scheme improves the AUV synchronization frequency by permitting neighboring AUVs to share their status information via a pre-selected node called an agent-node at the static layer of the network. We evaluate the proposed scheme in terms of the AUV synchronization frequency, vertical delay (node→AUV), horizontal delay (AUV→AUV), end-to-end delay, and the packet loss ratio. Simulation results show that the proposed scheme significantly reduces the aforementioned delays without the synchronization time-out process employed in conventional works. PMID:27706042

Data-Gathering Scheme Using AUVs in Large-Scale Underwater Sensor Networks: A Multihop Approach.

PubMed

Khan, Jawaad Ullah; Cho, Ho-Shin

2016-09-30

In this paper, we propose a data-gathering scheme for hierarchical underwater sensor networks, where multiple Autonomous Underwater Vehicles (AUVs) are deployed over large-scale coverage areas. The deployed AUVs constitute an intermittently connected multihop network through inter-AUV synchronization (in this paper, synchronization means an interconnection between nodes for communication) for forwarding data to the designated sink. In such a scenario, the performance of the multihop communication depends upon the synchronization among the vehicles. The mobility parameters of the vehicles vary continuously because of the constantly changing underwater currents. The variations in the AUV mobility parameters reduce the inter-AUV synchronization frequency contributing to delays in the multihop communication. The proposed scheme improves the AUV synchronization frequency by permitting neighboring AUVs to share their status information via a pre-selected node called an agent-node at the static layer of the network. We evaluate the proposed scheme in terms of the AUV synchronization frequency, vertical delay (node→AUV), horizontal delay (AUV→AUV), end-to-end delay, and the packet loss ratio. Simulation results show that the proposed scheme significantly reduces the aforementioned delays without the synchronization time-out process employed in conventional works.

Recent advances in large-scale assembly of semiconducting inorganic nanowires and nanofibers for electronics, sensors and photovoltaics.

PubMed

Long, Yun-Ze; Yu, Miao; Sun, Bin; Gu, Chang-Zhi; Fan, Zhiyong

2012-06-21

Semiconducting inorganic nanowires (NWs), nanotubes and nanofibers have been extensively explored in recent years as potential building blocks for nanoscale electronics, optoelectronics, chemical/biological/optical sensing, and energy harvesting, storage and conversion, etc. Besides the top-down approaches such as conventional lithography technologies, nanowires are commonly grown by the bottom-up approaches such as solution growth, template-guided synthesis, and vapor-liquid-solid process at a relatively low cost. Superior performance has been demonstrated using nanowires devices. However, most of the nanowire devices are limited to the demonstration of single devices, an initial step toward nanoelectronic circuits, not adequate for production on a large scale at low cost. Controlled and uniform assembly of nanowires with high scalability is still one of the major bottleneck challenges towards the materials and device integration for electronics. In this review, we aim to present recent progress toward nanowire device assembly technologies, including flow-assisted alignment, Langmuir-Blodgett assembly, bubble-blown technique, electric/magnetic- field-directed assembly, contact/roll printing, planar growth, bridging method, and electrospinning, etc. And their applications in high-performance, flexible electronics, sensors, photovoltaics, bioelectronic interfaces and nano-resonators are also presented.

Air-Induced Drag Reduction at High Reynolds Numbers: Velocity and Void Fraction Profiles

NASA Astrophysics Data System (ADS)

Elbing, Brian; Mäkiharju, Simo; Wiggins, Andrew; Dowling, David; Perlin, Marc; Ceccio, Steven

2010-11-01

The injection of air into a turbulent boundary layer forming over a flat plate can reduce the skin friction. With sufficient volumetric fluxes an air layer can separate the solid surface from the flowing liquid, which can produce drag reduction in excess of 80%. Several large scale experiments have been conducted at the US Navy's Large Cavitation Channel on a 12.9 m long flat plate model investigating bubble drag reduction (BDR), air layer drag reduction (ALDR) and the transition between BDR and ALDR. The most recent experiment acquired phase velocities and void fraction profiles at three downstream locations (3.6, 5.9 and 10.6 m downstream from the model leading edge) for a single flow speed (˜6.4 m/s). The profiles were acquired with a combination of electrode point probes, time-of-flight sensors, Pitot tubes and an LDV system. Additional diagnostics included skin-friction sensors and flow-field image visualization. During this experiment the inlet flow was perturbed with vortex generators immediately upstream of the injection location to assess the robustness of the air layer. From these, and prior measurements, computational models can be refined to help assess the viability of ALDR for full-scale ship applications.

Performance evaluation of the Fiber Bragg Grating (FBG) sensing device and comparison with piezoelectric sensors for AE detection

NASA Astrophysics Data System (ADS)

Zhang, Chuang; Bond, Leonard J.

2017-02-01

Structural health monitoring (SHM) of engineering structures in service has assumed a significant role in assessing their safety and integrity. Several sensing modalities have been developed to monitor cracking, using acoustic emission (AE). Piezoelectric sensors are commonly used in AE systems, however, for some applications there are limitations and challenges. One alternative approach that is being investigated is using Fiber Bragg Grating (FBG) sensors which have emerged as a reliable, in situ and nondestructive tool in some applications for monitoring and diagnostics in large-scale structure. The main objective of this work is to evaluate and compare the AE sensing characteristics for FBG and piezoelectric sensors. A ball drop impact is used as the source for generating waves in an Aluminum plate. The source repeatability was verified and a 4-channel FBG AE detection device was used to compare with the response of PZT sensors, investigating amplitude and frequency response which can indicate sensitivity. The low sensitivity and slow sampling rate are identified, for the unit investigated, as the main factors limiting FBG engineering AE applications.

High temperature, harsh environment sensors for advanced power generation systems

NASA Astrophysics Data System (ADS)

Ohodnicki, P. R.; Credle, S.; Buric, M.; Lewis, R.; Seachman, S.

2015-05-01

One mission of the Crosscutting Technology Research program at the National Energy Technology Laboratory is to develop a suite of sensors and controls technologies that will ultimately increase efficiencies of existing fossil-fuel fired power plants and enable a new generation of more efficient and lower emission power generation technologies. The program seeks to accomplish this mission through soliciting, managing, and monitoring a broad range of projects both internal and external to the laboratory which span sensor material and device development, energy harvesting and wireless telemetry methodologies, and advanced controls algorithms and approaches. A particular emphasis is placed upon harsh environment sensing for compatibility with high temperature, erosive, corrosive, and highly reducing or oxidizing environments associated with large-scale centralized power generation. An overview of the full sensors and controls portfolio is presented and a selected set of current and recent research successes and on-going projects are highlighted. A more detailed emphasis will be placed on an overview of the current research thrusts and successes of the in-house sensor material and device research efforts that have been established to support the program.

Sensitive Detection of Capsaicinoids Using a Surface Plasmon Resonance Sensor with Anti-Homovanillic Acid Polyclonal Antibodies

PubMed Central

Nakamura, Shingo; Yatabe, Rui; Onodera, Takeshi; Toko, Kiyoshi

2013-01-01

Recently, highly functional biosensors have been developed in preparation for possible large-scale terrorist attacks using chemical warfare agents. Practically applicable sensors are required to have various abilities, such as high portability and operability, the capability of performing rapid and continuous measurement, as well as high sensitivity and selectivity. We developed the detection method of capsaicinoids, the main component of some lachrymators, using a surface plasmon resonance (SPR) immunosensor as an on-site detection sensor. Homovanillic acid, which has a vanillyl group similar to capsaicinoids such as capsaicin and dihydrocapsaicin, was bound to Concholepas concholepas hemocyanin (CCH) for use as an immunogen to generate polyclonal antibodies. An indirect competitive assay was carried out to detect capsaicinoids using SPR sensor chips on which different capsaicin analogues were immobilized. For the sensor chip on which 4-hydroxy-3-methoxybenzylamine hydrochloride was immobilized, a detection limit of 150 ppb was achieved. We found that the incubation time was not required and the detection can be completed in five minutes. PMID:25586413

Fabrication of a Miniature Multi-Parameter Sensor Chip for Water Quality Assessment

PubMed Central

Zhou, Bo; Bian, Chao; Tong, Jianhua; Xia, Shanhong

2017-01-01

Water contamination is a main inducement of human diseases. It is an important step to monitor the water quality in the water distribution system. Due to the features of large size, high cost, and complicated structure of traditional water determination sensors and devices, it is difficult to realize real-time water monitoring on a large scale. In this paper, we present a multi-parameter sensor chip, which is miniature, low-cost, and robust, to detect the pH, conductivity, and temperature of water simultaneously. The sensor chip was fabricated using micro-electro-mechanical system (MEMS) techniques. Iridium oxide film was electrodeposited as the pH-sensing material. The atomic ratio of Ir(III) to Ir(IV) is about 1.38 according to the X-ray photoelectron spectroscopy (XPS) analysis. The pH sensing electrode showed super-Nernstian response (−67.60 mV/pH) and good linearity (R2 = 0.9997), in the range of pH 2.22 to pH 11.81. KCl-agar and epoxy were used as the electrolyte layer and liquid junction for the solid-state reference electrode, respectively, and its potential stability in deionized water was 56 h. The conductivity cell exhibited a linear determination range from 21.43 μS/cm to 1.99 mS/cm, and the electrode constant was 1.566 cm−1. Sensitivity of the temperature sensor was 5.46 Ω/°C. The results indicate that the developed sensor chip has potential application in water quality measurements. PMID:28098824

Microsensor research

NASA Astrophysics Data System (ADS)

Hughes, R. C.; Drebing, C. G.

1990-04-01

The technology that led to very large scale integrated circuits on silicon chips also provides a basis for new microsensors that are small, inexpensive, low power, rugged, and reliable. Two examples of microsensors Sandia is developing that take advantage of this technology are the microelectronic chemical sensor array and the radiation sensing field effect transistor (RADFET). Increasingly, the technology of chemical sensing needs new microsensor concepts. Applications in this area include environmental monitoring, criminal investigations, and state-of-health monitoring, both for equipment and living things. Chemical microsensors can satisfy sensing needs in the industrial, consumer, aerospace, and defense sectors. The microelectronic chemical-sensor array may address some of these applications. We have fabricated six separate chemical gas sensing areas on the microelectronic chemical sensor array. By using different catalytic metals on the gate areas of the diodes, we can selectively sense several gases.

Testing the pyramid truth wavefront sensor for NFIRAOS in the lab

NASA Astrophysics Data System (ADS)

Mieda, Etsuko; Rosensteiner, Matthias; van Kooten, Maaike; Veran, Jean-Pierre; Lardiere, Olivier; Herriot, Glen

2016-07-01

For today and future adaptive optics observations, sodium laser guide stars (LGSs) are crucial; however, the LGS elongation problem due to the sodium layer has to be compensated, in particular for extremely large telescopes. In this paper, we describe the concept of truth wavefront sensing as a solution and present its design using a pyramid wavefront sensor (PWFS) to improve NFIRAOS (Narrow Field InfraRed Adaptive Optics System), the first light adaptive optics system for Thirty Meter Telescope. We simulate and test the truth wavefront sensor function under a controlled environment using the HeNOS (Herzberg NFIRAOS Optical Simulator) bench, a scaled-down NFIRAOS bench at NRC-Herzberg. We also touch on alternative pyramid component options because despite recent high demands for PWFSs, we suffer from the lack of pyramid supplies due to engineering difficulties.

Geometric scaling of artificial hair sensors for flow measurement under different conditions

NASA Astrophysics Data System (ADS)

Su, Weihua; Reich, Gregory W.

2017-03-01

Artificial hair sensors (AHSs) have been developed for prediction of the local flow speed and aerodynamic force around an airfoil and subsequent application in vibration control of the airfoil. Usually, a specific sensor design is only sensitive to the flow speeds within its operating flow measurement region. This paper aims at expanding this flow measurement concept of using AHSs to different flow speed conditions by properly sizing the parameters of the sensors, including the dimensions of the artificial hair, capillary, and carbon nanotubes (CNTs) that make up the sensor design, based on a baseline sensor design and its working flow condition. In doing so, the glass fiber hair is modeled as a cantilever beam with an elastic foundation, subject to the distributed aerodynamic drag over the length of the hair. Hair length and diameter, capillary depth, and CNT height are scaled by keeping the maximum compressive strain of the CNTs constant for different sensors under different speed conditions. Numerical studies will demonstrate the feasibility of the geometric scaling methodology by designing AHSs for aircraft with different dimensions and flight conditions, starting from the same baseline sensor. Finally, the operating bandwidth of the scaled sensors are explored.

Sensor fusion approaches for EMI and GPR-based subsurface threat identification

NASA Astrophysics Data System (ADS)

Torrione, Peter; Morton, Kenneth, Jr.; Besaw, Lance E.

2011-06-01

Despite advances in both electromagnetic induction (EMI) and ground penetrating radar (GPR) sensing and related signal processing, neither sensor alone provides a perfect tool for detecting the myriad of possible buried objects that threaten the lives of Soldiers and civilians. However, while neither GPR nor EMI sensing alone can provide optimal detection across all target types, the two approaches are highly complementary. As a result, many landmine systems seek to make use of both sensing modalities simultaneously and fuse the results from both sensors to improve detection performance for targets with widely varying metal content and GPR responses. Despite this, little work has focused on large-scale comparisons of different approaches to sensor fusion and machine learning for combining data from these highly orthogonal phenomenologies. In this work we explore a wide array of pattern recognition techniques for algorithm development and sensor fusion. Results with the ARA Nemesis landmine detection system suggest that nonlinear and non-parametric classification algorithms provide significant performance benefits for single-sensor algorithm development, and that fusion of multiple algorithms can be performed satisfactorily using basic parametric approaches, such as logistic discriminant classification, for the targets under consideration in our data sets.

Biology Inspired Approach for Communal Behavior in Sensor Networks

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

2006-01-01

Research in wireless sensor network technology has exploded in the last decade. Promises of complex and ubiquitous control of the physical environment by these networks open avenues for new kinds of science and business. Due to the small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors working in concert. Although the reduction in size has been phenomenal it results in severe limitations on the computing, communicating, and power capabilities of these devices. Under these constraints, research efforts have concentrated on developing techniques for performing relatively simple tasks with minimal energy expense assuming some form of centralized control. Unfortunately, centralized control does not scale to massive size networks and execution of simple tasks in sparsely populated networks will not lead to the sophisticated applications predicted. These must be enabled by new techniques dependent on local and autonomous cooperation between sensors to effect global functions. As a step in that direction, in this work we detail a technique whereby a large population of sensors can attain a global goal using only local information and by making only local decisions without any form of centralized control.

Effect of structure variation of the aptamer-DNA duplex probe on the performance of displacement-based electrochemical aptamer sensors.

PubMed

Pang, Jie; Zhang, Ziping; Jin, Haizhu

2016-03-15

Electrochemical aptamer-based (E-AB) sensors employing electrode-immobilized, redox-tagged aptamer probes have emerged as a promising platform for the sensitive and quick detection of target analytes ranging from small molecules to proteins. Signal generation in this class of sensor is linked to change in electron transfer efficiency upon binding-induced change in flexibility/conformation of the aptamer probe. Because of this signaling mechanism, signal gains of these sensors can be improved by employing a displacement-based recognition system, which links target binding with a large-scale flexibility/conformation shift from the aptamer-DNA duplex to the single-stranded DNA or the native aptamer. Despite the relatively large number of displacement-based E-AB sensor samples, little attention has been paid to the structure variation of the aptamer-DNA duplex probe. Here we detail the effects of complementary length and position of the aptamer-DNA duplex probe on the performance of a model displacement-based E-AB sensor for ATP. We find that, greater background suppression and signal gain are observed with longer complementary length of the aptamer-DNA duplex probe. However, sensor equilibration time slows monotonically with increasing complementary length; and with too many target binding sites in aptamer sequence being occupied by the complementary DNA, the aptamer-target binding does not occur and no signal gain observed. We also demonstrate that signal gain of the displacement-based E-AB sensor is strongly dependent on the complementary position of the aptamer-DNA duplex probe, with complementary position located at the electrode-attached or redox-tagged end of the duplex probe, larger background suppression and signal increase than that of the middle position are observed. These results highlight the importance of rational structure design of the aptamer-DNA duplex probe and provide new insights into the optimization of displacement-based E-AB sensors. Copyright © 2015 Elsevier B.V. All rights reserved.

Circuits and Systems for Low-Power Miniaturized Wireless Sensors

NASA Astrophysics Data System (ADS)

Nagaraju, Manohar

The field of electronic sensors has witnessed a tremendous growth over the last decade particularly with the proliferation of mobile devices. New applications in Internet of Things (IoT), wearable technology, are further expected to fuel the demand for sensors from current numbers in the range of billions to trillions in the next decade. The main challenges for a trillion sensors are continued miniaturization, low-cost and large-scale manufacturing process, and low power consumption. Traditional integration and circuit design techniques in sensor systems are not suitable for applications in smart dust, IoT etc. The first part of this thesis demonstrates an example sensor system for biosignal recording and illustrates the tradeoffs in the design of low-power miniaturized sensors. The different components of the sensor system are integrated at the board level. The second part of the thesis demonstrates fully integrated sensors that enable extreme miniaturization of a sensing system with the sensor element, processing circuitry, a frequency reference for communication and the communication circuitry in a single hermetically sealed die. Design techniques to reduce the power consumption of the sensor interface circuitry at the architecture and circuit level are demonstrated. The principles are used to design sensors for two of the most common physical variables, mass and pressure. A low-power wireless mass and pressure sensor suitable for a wide variety of biological/chemical sensing applications and Tire Pressure Monitoring Systems (TPMS) respectively are demonstrated. Further, the idea of using high-Q resonators for a Voltage Controlled Oscillator (VCO) is proposed and a low-noise, wide bandwidth FBAR-based VCO is presented.

INNOVATIVE EASY-TO-USE PASSIVE TECHNIQUE FOR 222RN AND 220RN DECAY PRODUCT DETECTION.

PubMed

Mishra, Rosaline; Rout, R; Prajith, R; Jalalluddin, S; Sapra, B K; Mayya, Y S

2016-10-01

The decay products of radon and thoron are essentially the radioisotopes of polonium, bismuth and lead, and are solid particulates, which deposit in different parts of the respiratory tract upon inhalation, subsequently emitting high-energy alpha particles upon their radioactive decay. Development of passive deposition-based direct progeny sensors known as direct radon and thoron progeny sensors have provided an easy-to-use technique for time-integrated measurements of the decay products only. These dosemeters are apt for large-scale population dosimetry to assign inhalation doses to the public. The paper gives an insight into the technique, the calibration, comparison with the prevalently used active grab filter paper sampling technique, alpha track diameter analysis in these progeny sensors, progeny deposition velocity measurements carried out using these detector systems in the indoor as well as outdoor environment, and applications of these sensors for time-integrated unattached fraction estimation. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Microelectromechanical Systems for Aerodynamics Applications

NASA Technical Reports Server (NTRS)

Mehregany, Mehran; DeAnna, Russell G.; Reshotko, Eli

1996-01-01

Microelectromechanical systems (MEMS) embody the integration of sensors, actuators, and electronics on a single substrate using integrated circuit fabrication techniques and compatible micromachining processes. Silicon and its derivatives form the material base for the MEMS technology. MEMS devices, including micro-sensors and micro-actuators, are attractive because they can be made small (characteristic dimension about microns), be produced in large numbers with uniform performance, include electronics for high performance and sophisticated functionality, and be inexpensive. MEMS pressure sensors, wall-shear-stress sensors, and micromachined hot-wires are nearing application in aeronautics. MEMS actuators face a tougher challenge since they have to be scaled (up) to the physical phenomena that are being controlled. MEMS actuators are proposed, for example, for controlling the small structures in a turbulent boundary layer, for aircraft control, for cooling, and for mixing enhancement. Data acquisition or control logistics require integration of electronics along with the transducer elements with appropriate consideration of analog-to-digital conversion, multiplexing, and telemetry. Altogether, MEMS technology offers exciting opportunities for aerodynamics applications both in wind tunnels and in flight

Finite element analysis-based study of fiber Bragg grating sensor for cracks detection in reinforced concrete

NASA Astrophysics Data System (ADS)

Wang, Lili; Xin, Xiangjun; Song, Jun; Wang, Honggang; Sai, Yaozhang

2018-02-01

Fiber Bragg sensor is applied for detecting and monitoring the cracks that occur in the reinforced concrete. We use the three-dimensional finite element model to provide the three-axial stresses along the fiber Bragg sensor and then converted the stresses as a wavelength deformation of fiber Bragg grating (FBG) reflected spectrum. For the crack detection, an FBG sensor with 10-mm length is embedded in the reinforced concrete, and its reflection spectrum is measured after loading is applied to the concrete slab. As a result, the main peak wavelength and the ratio of the peak reflectivity to the maximal side-mode reflectivity of the optic-fiber grating represent the fracture severity. The fact that the sharp decreasing of the ratio of the peak reflectivity to the maximal side-mode reflectivity represents the early crack is confirmed by the theoretical calculation. The method can be used to detect the cracks in the reinforced concrete and give safety evaluation of large-scale infrastructure.

Spatial Copula Model for Imputing Traffic Flow Data from Remote Microwave Sensors.

PubMed

Ma, Xiaolei; Luan, Sen; Du, Bowen; Yu, Bin

2017-09-21

Issues of missing data have become increasingly serious with the rapid increase in usage of traffic sensors. Analyses of the Beijing ring expressway have showed that up to 50% of microwave sensors pose missing values. The imputation of missing traffic data must be urgently solved although a precise solution that cannot be easily achieved due to the significant number of missing portions. In this study, copula-based models are proposed for the spatial interpolation of traffic flow from remote traffic microwave sensors. Most existing interpolation methods only rely on covariance functions to depict spatial correlation and are unsuitable for coping with anomalies due to Gaussian consumption. Copula theory overcomes this issue and provides a connection between the correlation function and the marginal distribution function of traffic flow. To validate copula-based models, a comparison with three kriging methods is conducted. Results indicate that copula-based models outperform kriging methods, especially on roads with irregular traffic patterns. Copula-based models demonstrate significant potential to impute missing data in large-scale transportation networks.

Wearable and flexible electronics for continuous molecular monitoring.

PubMed

Yang, Yiran; Gao, Wei

2018-04-03

Wearable biosensors have received tremendous attention over the past decade owing to their great potential in predictive analytics and treatment toward personalized medicine. Flexible electronics could serve as an ideal platform for personalized wearable devices because of their unique properties such as light weight, low cost, high flexibility and great conformability. Unlike most reported flexible sensors that mainly track physical activities and vital signs, the new generation of wearable and flexible chemical sensors enables real-time, continuous and fast detection of accessible biomarkers from the human body, and allows for the collection of large-scale information about the individual's dynamic health status at the molecular level. In this article, we review and highlight recent advances in wearable and flexible sensors toward continuous and non-invasive molecular analysis in sweat, tears, saliva, interstitial fluid, blood, wound exudate as well as exhaled breath. The flexible platforms, sensing mechanisms, and device and system configurations employed for continuous monitoring are summarized. We also discuss the key challenges and opportunities of the wearable and flexible chemical sensors that lie ahead.

Miniaturized integration of a fluorescence microscope

PubMed Central

Ghosh, Kunal K.; Burns, Laurie D.; Cocker, Eric D.; Nimmerjahn, Axel; Ziv, Yaniv; Gamal, Abbas El; Schnitzer, Mark J.

2013-01-01

The light microscope is traditionally an instrument of substantial size and expense. Its miniaturized integration would enable many new applications based on mass-producible, tiny microscopes. Key prospective usages include brain imaging in behaving animals towards relating cellular dynamics to animal behavior. Here we introduce a miniature (1.9 g) integrated fluorescence microscope made from mass-producible parts, including semiconductor light source and sensor. This device enables high-speed cellular-level imaging across ∼0.5 mm2 areas in active mice. This capability allowed concurrent tracking of Ca2+ spiking in >200 Purkinje neurons across nine cerebellar microzones. During mouse locomotion, individual microzones exhibited large-scale, synchronized Ca2+ spiking. This is a mesoscopic neural dynamic missed by prior techniques for studying the brain at other length scales. Overall, the integrated microscope is a potentially transformative technology that permits distribution to many animals and enables diverse usages, such as portable diagnostics or microscope arrays for large-scale screens. PMID:21909102

Carbon nanotube circuit integration up to sub-20 nm channel lengths.

PubMed

Shulaker, Max Marcel; Van Rethy, Jelle; Wu, Tony F; Liyanage, Luckshitha Suriyasena; Wei, Hai; Li, Zuanyi; Pop, Eric; Gielen, Georges; Wong, H-S Philip; Mitra, Subhasish

2014-04-22

Carbon nanotube (CNT) field-effect transistors (CNFETs) are a promising emerging technology projected to achieve over an order of magnitude improvement in energy-delay product, a metric of performance and energy efficiency, compared to silicon-based circuits. However, due to substantial imperfections inherent with CNTs, the promise of CNFETs has yet to be fully realized. Techniques to overcome these imperfections have yielded promising results, but thus far only at large technology nodes (1 μm device size). Here we demonstrate the first very large scale integration (VLSI)-compatible approach to realizing CNFET digital circuits at highly scaled technology nodes, with devices ranging from 90 nm to sub-20 nm channel lengths. We demonstrate inverters functioning at 1 MHz and a fully integrated CNFET infrared light sensor and interface circuit at 32 nm channel length. This demonstrates the feasibility of realizing more complex CNFET circuits at highly scaled technology nodes.

Miniaturized integration of a fluorescence microscope.

PubMed

Ghosh, Kunal K; Burns, Laurie D; Cocker, Eric D; Nimmerjahn, Axel; Ziv, Yaniv; Gamal, Abbas El; Schnitzer, Mark J

2011-09-11

The light microscope is traditionally an instrument of substantial size and expense. Its miniaturized integration would enable many new applications based on mass-producible, tiny microscopes. Key prospective usages include brain imaging in behaving animals for relating cellular dynamics to animal behavior. Here we introduce a miniature (1.9 g) integrated fluorescence microscope made from mass-producible parts, including a semiconductor light source and sensor. This device enables high-speed cellular imaging across ∼0.5 mm2 areas in active mice. This capability allowed concurrent tracking of Ca2+ spiking in >200 Purkinje neurons across nine cerebellar microzones. During mouse locomotion, individual microzones exhibited large-scale, synchronized Ca2+ spiking. This is a mesoscopic neural dynamic missed by prior techniques for studying the brain at other length scales. Overall, the integrated microscope is a potentially transformative technology that permits distribution to many animals and enables diverse usages, such as portable diagnostics or microscope arrays for large-scale screens.

Real-time monitoring of CO2 storage sites: Application to Illinois Basin-Decatur Project

USGS Publications Warehouse

Picard, G.; Berard, T.; Chabora, E.; Marsteller, S.; Greenberg, S.; Finley, R.J.; Rinck, U.; Greenaway, R.; Champagnon, C.; Davard, J.

2011-01-01

Optimization of carbon dioxide (CO2) storage operations for efficiency and safety requires use of monitoring techniques and implementation of control protocols. The monitoring techniques consist of permanent sensors and tools deployed for measurement campaigns. Large amounts of data are thus generated. These data must be managed and integrated for interpretation at different time scales. A fast interpretation loop involves combining continuous measurements from permanent sensors as they are collected to enable a rapid response to detected events; a slower loop requires combining large datasets gathered over longer operational periods from all techniques. The purpose of this paper is twofold. First, it presents an analysis of the monitoring objectives to be performed in the slow and fast interpretation loops. Second, it describes the implementation of the fast interpretation loop with a real-time monitoring system at the Illinois Basin-Decatur Project (IBDP) in Illinois, USA. ?? 2011 Published by Elsevier Ltd.

Reduced-Scale Transition-Edge Sensor Detectors for Solar and X-Ray Astrophysics

NASA Technical Reports Server (NTRS)

Datesman, Aaron M.; Adams, Joseph S.; Bandler, Simon R.; Betancourt-Martinez, Gabriele L.; Chang, Meng-Ping; Chervenak, James A.; Eckart, Megan E.; Ewin, Audrey E.; Finkbeiner, Fred M.; Ha, Jong Yoon;

Modelling disease outbreaks in realistic urban social networks

NASA Astrophysics Data System (ADS)

Eubank, Stephen; Guclu, Hasan; Anil Kumar, V. S.; Marathe, Madhav V.; Srinivasan, Aravind; Toroczkai, Zoltán; Wang, Nan

2004-05-01

Most mathematical models for the spread of disease use differential equations based on uniform mixing assumptions or ad hoc models for the contact process. Here we explore the use of dynamic bipartite graphs to model the physical contact patterns that result from movements of individuals between specific locations. The graphs are generated by large-scale individual-based urban traffic simulations built on actual census, land-use and population-mobility data. We find that the contact network among people is a strongly connected small-world-like graph with a well-defined scale for the degree distribution. However, the locations graph is scale-free, which allows highly efficient outbreak detection by placing sensors in the hubs of the locations network. Within this large-scale simulation framework, we then analyse the relative merits of several proposed mitigation strategies for smallpox spread. Our results suggest that outbreaks can be contained by a strategy of targeted vaccination combined with early detection without resorting to mass vaccination of a population.

A Review of Passive RFID Tag Antenna-Based Sensors and Systems for Structural Health Monitoring Applications.

PubMed

Zhang, Jun; Tian, Gui Yun; Marindra, Adi M J; Sunny, Ali Imam; Zhao, Ao Bo

2017-01-29

In recent few years, the antenna and sensor communities have witnessed a considerable integration of radio frequency identification (RFID) tag antennas and sensors because of the impetus provided by internet of things (IoT) and cyber-physical systems (CPS). Such types of sensor can find potential applications in structural health monitoring (SHM) because of their passive, wireless, simple, compact size, and multimodal nature, particular in large scale infrastructures during their lifecycle. The big data from these ubiquitous sensors are expected to generate a big impact for intelligent monitoring. A remarkable number of scientific papers demonstrate the possibility that objects can be remotely tracked and intelligently monitored for their physical/chemical/mechanical properties and environment conditions. Most of the work focuses on antenna design, and significant information has been generated to demonstrate feasibilities. Further information is needed to gain deep understanding of the passive RFID antenna sensor systems in order to make them reliable and practical. Nevertheless, this information is scattered over much literature. This paper is to comprehensively summarize and clearly highlight the challenges and state-of-the-art methods of passive RFID antenna sensors and systems in terms of sensing and communication from system point of view. Future trends are also discussed. The future research and development in UK are suggested as well.

Automatic Multi-sensor Data Quality Checking and Event Detection for Environmental Sensing

NASA Astrophysics Data System (ADS)

LIU, Q.; Zhang, Y.; Zhao, Y.; Gao, D.; Gallaher, D. W.; Lv, Q.; Shang, L.

2017-12-01

With the advances in sensing technologies, large-scale environmental sensing infrastructures are pervasively deployed to continuously collect data for various research and application fields, such as air quality study and weather condition monitoring. In such infrastructures, many sensor nodes are distributed in a specific area and each individual sensor node is capable of measuring several parameters (e.g., humidity, temperature, and pressure), providing massive data for natural event detection and analysis. However, due to the dynamics of the ambient environment, sensor data can be contaminated by errors or noise. Thus, data quality is still a primary concern for scientists before drawing any reliable scientific conclusions. To help researchers identify potential data quality issues and detect meaningful natural events, this work proposes a novel algorithm to automatically identify and rank anomalous time windows from multiple sensor data streams. More specifically, (1) the algorithm adaptively learns the characteristics of normal evolving time series and (2) models the spatial-temporal relationship among multiple sensor nodes to infer the anomaly likelihood of a time series window for a particular parameter in a sensor node. Case studies using different data sets are presented and the experimental results demonstrate that the proposed algorithm can effectively identify anomalous time windows, which may resulted from data quality issues and natural events.

Fatigue crack monitoring with coupled piezoelectric film acoustic emission sensors

NASA Astrophysics Data System (ADS)

Zhou, Changjiang

Fatigue-induced cracking is a commonly seen problem in civil infrastructures reaching their original design life. A number of high-profile accidents have been reported in the past that involved fatigue damage in structures. Such incidences often happen without prior warnings due to lack of proper crack monitoring technique. In order to detect and monitor the fatigue crack, acoustic emission (AE) technique, has been receiving growing interests recently. AE can provide continuous and real-time monitoring data on damage progression in structures. Piezoelectric film AE sensor measures stress-wave induced strain in ultrasonic frequency range and its feasibility for AE signal monitoring has been demonstrated recently. However, extensive work in AE monitoring system development based on piezoelectric film AE sensor and sensor characterization on full-scale structures with fatigue cracks, have not been done. A lack of theoretical formulations for understanding the AE signals also hinders the use of piezoelectric film AE sensors. Additionally, crack detection and source localization with AE signals is a very important area yet to be explored for this new type of AE sensor. This dissertation presents the results of both analytical and experimental study on the signal characteristics of surface stress-wave induced AE strain signals measured by piezoelectric film AE sensors in near-field and an AE source localization method based on sensor couple theory. Based on moment tensor theory, generalized expression for AE strain signal is formulated. A special case involving the response of piezoelectric film AE sensor to surface load is also studied, which could potentially be used for sensor calibration of this type of sensor. A new concept of sensor couple theory based AE source localization technique is proposed and validated with both simulated and experimental data from fatigue test and field monitoring. Two series of fatigue tests were conducted to perform fatigue crack monitoring on large-scale steel test specimens using piezoelectric film AE sensors. Continuous monitoring of fatigue crack growth in steel structures is demonstrated in these fatigue test specimens. The use of piezoelectric film AE sensor for field monitoring of existing fatigue crack is also demonstrated in a real steel I-girder bridge located in Maryland. The sensor couple theory based AE source localization is validated using a limited number of piezoelectric film AE sensor data from both fatigue test specimens and field monitoring bridge. Through both laboratory fatigue test and field monitoring of steel structures with active fatigue cracks, the signal characteristics of piezoelectric film AE sensor have been studied in real-world environment.

Wearable Wireless Sensor for Multi-Scale Physiological Monitoring

DTIC Science & Technology

2013-10-01

AD_________________ Award Number: W81XWH-12-1-0541 TITLE: Wearable Wireless Sensor for Multi-Scale...TYPE Annual 3. DATES COVERED 25 12- 13 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Wearable Wireless Sensor for Multi-Scale Physiological...peripheral management • Procedures for low power mode activation and wake - up • Routines for start- up state detection • Flash memory management

Evaluating the Performance of the Goddard Multi-Scale Modeling Framework against GPM, TRMM and CloudSat/CALIPSO Products

NASA Astrophysics Data System (ADS)

Chern, J. D.; Tao, W. K.; Lang, S. E.; Matsui, T.; Mohr, K. I.

2014-12-01

Four six-month (March-August 2014) experiments with the Goddard Multi-scale Modeling Framework (MMF) were performed to study the impacts of different Goddard one-moment bulk microphysical schemes and large-scale forcings on the performance of the MMF. Recently a new Goddard one-moment bulk microphysics with four-ice classes (cloud ice, snow, graupel, and frozen drops/hail) has been developed based on cloud-resolving model simulations with large-scale forcings from field campaign observations. The new scheme has been successfully implemented to the MMF and two MMF experiments were carried out with this new scheme and the old three-ice classes (cloud ice, snow graupel) scheme. The MMF has global coverage and can rigorously evaluate microphysics performance for different cloud regimes. The results show MMF with the new scheme outperformed the old one. The MMF simulations are also strongly affected by the interaction between large-scale and cloud-scale processes. Two MMF sensitivity experiments with and without nudging large-scale forcings to those of ERA-Interim reanalysis were carried out to study the impacts of large-scale forcings. The model simulated mean and variability of surface precipitation, cloud types, cloud properties such as cloud amount, hydrometeors vertical profiles, and cloud water contents, etc. in different geographic locations and climate regimes are evaluated against GPM, TRMM, CloudSat/CALIPSO satellite observations. The Goddard MMF has also been coupled with the Goddard Satellite Data Simulation Unit (G-SDSU), a system with multi-satellite, multi-sensor, and multi-spectrum satellite simulators. The statistics of MMF simulated radiances and backscattering can be directly compared with satellite observations to assess the strengths and/or deficiencies of MMF simulations and provide guidance on how to improve the MMF and microphysics.

Full-Scale Prestress Loss Monitoring of Damaged RC Structures Using Distributed Optical Fiber Sensing Technology

PubMed Central

Lan, Chunguang; Zhou, Zhi; Ou, Jinping

2012-01-01

For the safety of prestressed structures, prestress loss is a critical issue that will increase with structural damage, so it is necessary to investigate prestress loss of prestressed structures under different damage scenarios. Unfortunately, to date, no qualified techniques are available due to difficulty for sensors to survive in harsh construction environments of long service life and large span. In this paper, a novel smart steel strand based on the Brillouin optical time domain analysis (BOTDA) sensing technique was designed and manufactured, and then series of tests were used to characterize properties of the smart steel strands. Based on prestress loss principle analysis of damaged structures, laboratory tests of two similar beams with different damages were used to verify the concept of full-scale prestress loss monitoring of damaged reinforced concrete (RC) beams by using the smart steel strands. The prestress losses obtained from the Brillouin sensors are compared with that from conventional sensors, which provided the evolution law of prestress losses of damaged RC beams. The monitoring results from the proposed smart strand can reveal both spatial distribution and time history of prestress losses of damaged RC beams. PMID:22778590

A Web service-based architecture for real-time hydrologic sensor networks

NASA Astrophysics Data System (ADS)

Wong, B. P.; Zhao, Y.; Kerkez, B.

2014-12-01

Recent advances in web services and cloud computing provide new means by which to process and respond to real-time data. This is particularly true of platforms built for the Internet of Things (IoT). These enterprise-scale platforms have been designed to exploit the IP-connectivity of sensors and actuators, providing a robust means by which to route real-time data feeds and respond to events of interest. While powerful and scalable, these platforms have yet to be adopted by the hydrologic community, where the value of real-time data impacts both scientists and decision makers. We discuss the use of one such IoT platform for the purpose of large-scale hydrologic measurements, showing how rapid deployment and ease-of-use allows scientists to focus on their experiment rather than software development. The platform is hardware agnostic, requiring only IP-connectivity of field devices to capture, store, process, and visualize data in real-time. We demonstrate the benefits of real-time data through a real-world use case by showing how our architecture enables the remote control of sensor nodes, thereby permitting the nodes to adaptively change sampling strategies to capture major hydrologic events of interest.

Full-scale prestress loss monitoring of damaged RC structures using distributed optical fiber sensing technology.

PubMed

Lan, Chunguang; Zhou, Zhi; Ou, Jinping

2012-01-01

For the safety of prestressed structures, prestress loss is a critical issue that will increase with structural damage, so it is necessary to investigate prestress loss of prestressed structures under different damage scenarios. Unfortunately, to date, no qualified techniques are available due to difficulty for sensors to survive in harsh construction environments of long service life and large span. In this paper, a novel smart steel strand based on the Brillouin optical time domain analysis (BOTDA) sensing technique was designed and manufactured, and then series of tests were used to characterize properties of the smart steel strands. Based on prestress loss principle analysis of damaged structures, laboratory tests of two similar beams with different damages were used to verify the concept of full-scale prestress loss monitoring of damaged reinforced concrete (RC) beams by using the smart steel strands. The prestress losses obtained from the Brillouin sensors are compared with that from conventional sensors, which provided the evolution law of prestress losses of damaged RC beams. The monitoring results from the proposed smart strand can reveal both spatial distribution and time history of prestress losses of damaged RC beams.

Urban-scale mapping of PM2.5 distribution via data fusion between high-density sensor network and MODIS Aerosol Optical Depth

NASA Astrophysics Data System (ADS)

Ba, Yu Tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Tang, Yu jia; Zhang, Da wei

2017-04-01

High-resolution mapping of PM2.5 is the prerequisite for precise analytics and subsequent anti-pollution interventions. Considering the large variances of particulate distribution, urban-scale mapping is challenging either with ground-based fixed stations, with satellites or via models. In this study, a dynamic fusion method between high-density sensor network and MODIS Aerosol Optical Depth (AOD) was introduced. The sensor network was deployed in Beijing ( > 1000 fixed monitors across 16000 km2 area) to provide raw observations with high temporal resolution (sampling interval < 1 hour), high spatial resolution in flat areas ( < 1 km), and low spatial resolution in mountainous areas ( > 5 km). The MODIS AOD was calibrated to provide distribution map with low temporal resolution (daily) and moderate spatial resolution ( = 3 km). By encoding the data quality and defects (e.g. could, reflectance, abnormal), a hybrid interpolation procedure with cross-validation generated PM2.5 distribution with both high temporal and spatial resolution. Several no-pollutant and high-pollution periods were tested to validate the proposed fusion method for capturing the instantaneous patterns of PM2.5 emission.

Landcover Based Optimal Deconvolution of PALS L-band Microwave Brightness Temperature

NASA Technical Reports Server (NTRS)

Limaye, Ashutosh S.; Crosson, William L.; Laymon, Charles A.; Njoku, Eni G.

2004-01-01

An optimal de-convolution (ODC) technique has been developed to estimate microwave brightness temperatures of agricultural fields using microwave radiometer observations. The technique is applied to airborne measurements taken by the Passive and Active L and S band (PALS) sensor in Iowa during Soil Moisture Experiments in 2002 (SMEX02). Agricultural fields in the study area were predominantly soybeans and corn. The brightness temperatures of corn and soybeans were observed to be significantly different because of large differences in vegetation biomass. PALS observations have significant over-sampling; observations were made about 100 m apart and the sensor footprint extends to about 400 m. Conventionally, observations of this type are averaged to produce smooth spatial data fields of brightness temperatures. However, the conventional approach is in contrast to reality in which the brightness temperatures are in fact strongly dependent on landcover, which is characterized by sharp boundaries. In this study, we mathematically de-convolve the observations into brightness temperature at the field scale (500-800m) using the sensor antenna response function. The result is more accurate spatial representation of field-scale brightness temperatures, which may in turn lead to more accurate soil moisture retrieval.

A Combined Approach of Sensor Data Fusion and Multivariate Geostatistics for Delineation of Homogeneous Zones in an Agricultural Field

PubMed Central

Castrignanò, Annamaria; Quarto, Ruggiero; Vitti, Carolina; Langella, Giuliano; Terribile, Fabio

2017-01-01

To assess spatial variability at the very fine scale required by Precision Agriculture, different proximal and remote sensors have been used. They provide large amounts and different types of data which need to be combined. An integrated approach, using multivariate geostatistical data-fusion techniques and multi-source geophysical sensor data to determine simple summary scale-dependent indices, is described here. These indices can be used to delineate management zones to be submitted to differential management. Such a data fusion approach with geophysical sensors was applied in a soil of an agronomic field cropped with tomato. The synthetic regionalized factors determined, contributed to split the 3D edaphic environment into two main horizontal structures with different hydraulic properties and to disclose two main horizons in the 0–1.0-m depth with a discontinuity probably occurring between 0.40 m and 0.70 m. Comparing this partition with the soil properties measured with a shallow sampling, it was possible to verify the coherence in the topsoil between the dielectric properties and other properties more directly related to agronomic management. These results confirm the advantages of using proximal sensing as a preliminary step in the application of site-specific management. Combining disparate spatial data (data fusion) is not at all a naive problem and novel and powerful methods need to be developed. PMID:29207510

A Combined Approach of Sensor Data Fusion and Multivariate Geostatistics for Delineation of Homogeneous Zones in an Agricultural Field.

PubMed

Castrignanò, Annamaria; Buttafuoco, Gabriele; Quarto, Ruggiero; Vitti, Carolina; Langella, Giuliano; Terribile, Fabio; Venezia, Accursio

2017-12-03

To assess spatial variability at the very fine scale required by Precision Agriculture, different proximal and remote sensors have been used. They provide large amounts and different types of data which need to be combined. An integrated approach, using multivariate geostatistical data-fusion techniques and multi-source geophysical sensor data to determine simple summary scale-dependent indices, is described here. These indices can be used to delineate management zones to be submitted to differential management. Such a data fusion approach with geophysical sensors was applied in a soil of an agronomic field cropped with tomato. The synthetic regionalized factors determined, contributed to split the 3D edaphic environment into two main horizontal structures with different hydraulic properties and to disclose two main horizons in the 0-1.0-m depth with a discontinuity probably occurring between 0.40 m and 0.70 m. Comparing this partition with the soil properties measured with a shallow sampling, it was possible to verify the coherence in the topsoil between the dielectric properties and other properties more directly related to agronomic management. These results confirm the advantages of using proximal sensing as a preliminary step in the application of site-specific management. Combining disparate spatial data (data fusion) is not at all a naive problem and novel and powerful methods need to be developed.

Comparing SMAP to Macro-scale and Hyper-resolution Land Surface Models over Continental U. S.

NASA Astrophysics Data System (ADS)

Pan, Ming; Cai, Xitian; Chaney, Nathaniel; Wood, Eric

2016-04-01

SMAP sensors collect moisture information in top soil at the spatial resolution of ~40 km (radiometer) and ~1 to 3 km (radar, before its failure in July 2015). Such information is extremely valuable for understanding various terrestrial hydrologic processes and their implications on human life. At the same time, soil moisture is a joint consequence of numerous physical processes (precipitation, temperature, radiation, topography, crop/vegetation dynamics, soil properties, etc.) that happen at a wide range of scales from tens of kilometers down to tens of meters. Therefore, a full and thorough analysis/exploration of SMAP data products calls for investigations at multiple spatial scales - from regional, to catchment, and to field scales. Here we first compare the SMAP retrievals to the Variable Infiltration Capacity (VIC) macro-scale land surface model simulations over the continental U. S. region at 3 km resolution. The forcing inputs to the model are merged/downscaled from a suite of best available data products including the NLDAS-2 forcing, Stage IV and Stage II precipitation, GOES Surface and Insolation Products, and fine elevation data. The near real time VIC simulation is intended to provide a source of large scale comparisons at the active sensor resolution. Beyond the VIC model scale, we perform comparisons at 30 m resolution against the recently developed HydroBloks hyper-resolution land surface model over several densely gauged USDA experimental watersheds. Comparisons are also made against in-situ point-scale observations from various SMAP Cal/Val and field campaign sites.

Large scale in-situ BOrehole and Geofluid Simulator (i.BOGS) for the development and testing of borehole technologies at reservoir conditions

NASA Astrophysics Data System (ADS)

Duda, Mandy; Bracke, Rolf; Stöckhert, Ferdinand; Wittig, Volker

2017-04-01

A fundamental problem of technological applications related to the exploration and provision of geothermal energy is the inaccessibility of subsurface processes. As a result, actual reservoir properties can only be determined using (a) indirect measurement techniques such as seismic surveys, machine feedback and geophysical borehole logging, (b) laboratory experiments capable of simulating in-situ properties, but failing to preserve temporal and spatial scales, or vice versa, and (c) numerical simulations. Moreover, technological applications related to the drilling process, the completion and cementation of a wellbore or the stimulation and exploitation of the reservoir are exposed to high pressure and temperature conditions as well as corrosive environments resulting from both, rock formation and geofluid characteristics. To address fundamental and applied questions in the context of geothermal energy provision and subsurface exploration in general one of Europe's largest geoscientific laboratory infrastructures is introduced. The in-situ Borehole and Geofluid Simulator (i.BOGS) allows to simulate quasi scale-preserving processes at reservoir conditions up to depths of 5000 m and represents a large scale pressure vessel for iso-/hydrostatic and pore pressures up to 125 MPa and temperatures from -10°C to 180°C. The autoclave can either be filled with large rock core samples (25 cm in diameter, up to 3 m length) or with fluids and technical borehole devices (e.g. pumps, sensors). The pressure vessel is equipped with an ultrasound system for active transmission and passive recording of acoustic emissions, and can be complemented by additional sensors. The i.BOGS forms the basic module for the Match.BOGS finally consisting of three modules, i.e. (A) the i.BOGS, (B) the Drill.BOGS, a drilling module to be attached to the i.BOGS capable of applying realistic torques and contact forces to a drilling device that enters the i.BOGS, and (C) the Fluid.BOGS, a geofluid reactor for the composition of highly corrosive geofluids serving as synthetic groundwater / pore fluid in the i.BOGS. The i.BOGS will support scientists and engineers in developing instruments and applications such as drilling tooling and drillstrings, borehole cements and cementation procedures, geophysical tooling and sensors, or logging/measuring while drilling equipment, but will also contribute to optimized reservoir exploitation methods, for example related to stimulation techniques, pumping equipment and long-term reservoir accessibility.

Self-localization of wireless sensor networks using self-organizing maps

NASA Astrophysics Data System (ADS)

Ertin, Emre; Priddy, Kevin L.

2005-03-01

Recently there has been a renewed interest in the notion of deploying large numbers of networked sensors for applications ranging from environmental monitoring to surveillance. In a typical scenario a number of sensors are distributed in a region of interest. Each sensor is equipped with sensing, processing and communication capabilities. The information gathered from the sensors can be used to detect, track and classify objects of interest. For a number of locations the sensors location is crucial in interpreting the data collected from those sensors. Scalability requirements dictate sensor nodes that are inexpensive devices without a dedicated localization hardware such as GPS. Therefore the network has to rely on information collected within the network to self-localize. In the literature a number of algorithms has been proposed for network localization which uses measurements informative of range, angle, proximity between nodes. Recent work by Patwari and Hero relies on sensor data without explicit range estimates. The assumption is that the correlation structure in the data is a monotone function of the intersensor distances. In this paper we propose a new method based on unsupervised learning techniques to extract location information from the sensor data itself. We consider a grid consisting of virtual nodes and try to fit grid in the actual sensor network data using the method of self organizing maps. Then known sensor network geometry can be used to rotate and scale the grid to a global coordinate system. Finally, we illustrate how the virtual nodes location information can be used to track a target.

Parameter identification of civil engineering structures

NASA Technical Reports Server (NTRS)

Juang, J. N.; Sun, C. T.

1980-01-01

This paper concerns the development of an identification method required in determining structural parameter variations for systems subjected to an extended exposure to the environment. The concept of structural identifiability of a large scale structural system in the absence of damping is presented. Three criteria are established indicating that a large number of system parameters (the coefficient parameters of the differential equations) can be identified by a few actuators and sensors. An eight-bay-fifteen-story frame structure is used as example. A simple model is employed for analyzing the dynamic response of the frame structure.

Novel Battery Management System with Distributed Wireless and Fiber Optic Sensors for Early Detection and Suppression of Thermal Runaway in Large Battery Packs, FY13 Q4 Report, ARPA-E Program: Advanced Management Protection of Energy Storage Devices (AMPE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farmer, J.; Chang, J.; Zumstein, J.

Technology has been developed that enables monitoring of individual cells in highcapacity lithium-ion battery packs, with a distributed array of wireless Bluetooth 4.0 tags and sensors, and without proliferation of extensive wiring harnesses. Given the safety challenges facing lithium-ion batteries in electric vehicle, civilian aviation and defense applications, these wireless sensors may be particularly important to these emerging markets. These wireless sensors will enhance the performance, reliability and safety of such energy storage systems. Specific accomplishments to date include, but are not limited to: (1) the development of wireless tags using Bluetooth 4.0 standard to monitor a large array ofmore » sensors in battery pack; (2) sensor suites enabling the simultaneous monitoring of cell voltage, cell current, cell temperature, and package strain, indicative of swelling and increased internal pressure, (3) small receivers compatible with USB ports on portable computers; (4) software drivers and logging software; (5) a 7S2P battery simulator, enabling the safe development of wireless BMS hardware in the laboratory; (6) demonstrated data transmission out of metal enclosures, including battery box, with small variable aperture opening; (7) test data demonstrating the accurate and reliable operation of sensors, with transmission of terminal voltage, cell temperature and package strain at distances up to 110 feet; (8) quantification of the data transmission error as a function of distance, in both indoor and outdoor operation; (9) electromagnetic interference testing during operation with live, high-capacity battery management system at Yardney Technical Products; (10) demonstrated operation with live high-capacity lithium-ion battery pack during charge-discharge cycling; (11) development of special polymer-gel lithium-ion batteries with embedded temperature sensors, capable of measuring the core temperature of individual of the cells during charge-discharge cycling at various temperatures, thereby enabling earlier warning of thermal runaway than possible with external sensors. Ultimately, the team plans to extend this work to include: (12) flexible wireless controllers, also using Bluetooth 4.0 standard, essential for balancing large-scale battery packs. LLNL received $925K for this project, and has $191K remaining after accomplishing these objectives.« less

Fabrication of a 3D micro/nano dual-scale carbon array and its demonstration as the microelectrodes for supercapacitors

NASA Astrophysics Data System (ADS)

Jiang, Shulan; Shi, Tielin; Gao, Yang; Long, Hu; Xi, Shuang; Tang, Zirong

2014-04-01

An easily accessible method is proposed for the fabrication of a 3D micro/nano dual-scale carbon array with a large surface area. The process mainly consists of three critical steps. Firstly, a hemispherical photoresist micro-array was obtained by the cost-effective nanoimprint lithography process. Then the micro-array was transformed into hierarchical structures with longitudinal nanowires on the microstructure surface by oxygen plasma etching. Finally, the micro/nano dual-scale carbon array was fabricated by carbonizing these hierarchical photoresist structures. It has also been demonstrated that the micro/nano dual-scale carbon array can be used as the microelectrodes for supercapacitors by the electrodeposition of a manganese dioxide (MnO2) film onto the hierarchical carbon structures with greatly enhanced electrochemical performance. The specific gravimetric capacitance of the deposited micro/nano dual-scale microelectrodes is estimated to be 337 F g-1 at the scan rate of 5 mV s-1. This proposed approach of fabricating a micro/nano dual-scale carbon array provides a facile way in large-scale microstructures’ manufacturing for a wide variety of applications, including sensors and on-chip energy storage devices.

Design of an omnidirectional single-point photodetector for large-scale spatial coordinate measurement

NASA Astrophysics Data System (ADS)

Xie, Hongbo; Mao, Chensheng; Ren, Yongjie; Zhu, Jigui; Wang, Chao; Yang, Lei

2017-10-01

In high precision and large-scale coordinate measurement, one commonly used approach to determine the coordinate of a target point is utilizing the spatial trigonometric relationships between multiple laser transmitter stations and the target point. A light receiving device at the target point is the key element in large-scale coordinate measurement systems. To ensure high-resolution and highly sensitive spatial coordinate measurement, a high-performance and miniaturized omnidirectional single-point photodetector (OSPD) is greatly desired. We report one design of OSPD using an aspheric lens, which achieves an enhanced reception angle of -5 deg to 45 deg in vertical and 360 deg in horizontal. As the heart of our OSPD, the aspheric lens is designed in a geometric model and optimized by LightTools Software, which enables the reflection of a wide-angle incident light beam into the single-point photodiode. The performance of home-made OSPD is characterized with working distances from 1 to 13 m and further analyzed utilizing developed a geometric model. The experimental and analytic results verify that our device is highly suitable for large-scale coordinate metrology. The developed device also holds great potential in various applications such as omnidirectional vision sensor, indoor global positioning system, and optical wireless communication systems.

Wireless sensor placement for structural monitoring using information-fusing firefly algorithm

NASA Astrophysics Data System (ADS)

Zhou, Guang-Dong; Yi, Ting-Hua; Xie, Mei-Xi; Li, Hong-Nan

2017-10-01

Wireless sensor networks (WSNs) are promising technology in structural health monitoring (SHM) applications for their low cost and high efficiency. The limited wireless sensors and restricted power resources in WSNs highlight the significance of optimal wireless sensor placement (OWSP) during designing SHM systems to enable the most useful information to be captured and to achieve the longest network lifetime. This paper presents a holistic approach, including an optimization criterion and a solution algorithm, for optimally deploying self-organizing multi-hop WSNs on large-scale structures. The combination of information effectiveness represented by the modal independence and the network performance specified by the network connectivity and network lifetime is first formulated to evaluate the performance of wireless sensor configurations. Then, an information-fusing firefly algorithm (IFFA) is developed to solve the OWSP problem. The step sizes drawn from a Lévy distribution are adopted to drive fireflies toward brighter individuals. Following the movement with Lévy flights, information about the contributions of wireless sensors to the objective function as carried by the fireflies is fused and applied to move inferior wireless sensors to better locations. The reliability of the proposed approach is verified via a numerical example on a long-span suspension bridge. The results demonstrate that the evaluation criterion provides a good performance metric of wireless sensor configurations, and the IFFA outperforms the simple discrete firefly algorithm.

Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E.

2013-05-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will present the architecture of SciReduce, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. We will also present a concept/prototype for staging NASA's A-Train Atmospheric datasets (Levels 2 & 3) in the Amazon Cloud so that any number of compute jobs can be executed "near" the multi-sensor data. Given such a system, multi-sensor climate studies over 10-20 years of data could be performed in an efficient way, with the researcher paying only his own Cloud compute bill.; Figure 1 -- Architecture.

Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

2013-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the 'A-Train' platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (MERRA), stratify the comparisons using a classification of the 'cloud scenes' from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically 'sharded' by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will present the architecture of SciReduce, describe the achieved 'clock time' speedups in fusing datasets on our own compute nodes and in the public Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. We will also present a concept/prototype for staging NASA's A-Train Atmospheric datasets (Levels 2 & 3) in the Amazon Cloud so that any number of compute jobs can be executed 'near' the multi-sensor data. Given such a system, multi-sensor climate studies over 10-20 years of data could be performed in an efficient way, with the researcher paying only his own Cloud compute bill. SciReduce Architecture

Autonomous vision networking: miniature wireless sensor networks with imaging technology

NASA Astrophysics Data System (ADS)

Messinger, Gioia; Goldberg, Giora

2006-09-01

The recent emergence of integrated PicoRadio technology, the rise of low power, low cost, System-On-Chip (SOC) CMOS imagers, coupled with the fast evolution of networking protocols and digital signal processing (DSP), created a unique opportunity to achieve the goal of deploying large-scale, low cost, intelligent, ultra-low power distributed wireless sensor networks for the visualization of the environment. Of all sensors, vision is the most desired, but its applications in distributed sensor networks have been elusive so far. Not any more. The practicality and viability of ultra-low power vision networking has been proven and its applications are countless, from security, and chemical analysis to industrial monitoring, asset tracking and visual recognition, vision networking represents a truly disruptive technology applicable to many industries. The presentation discusses some of the critical components and technologies necessary to make these networks and products affordable and ubiquitous - specifically PicoRadios, CMOS imagers, imaging DSP, networking and overall wireless sensor network (WSN) system concepts. The paradigm shift, from large, centralized and expensive sensor platforms, to small, low cost, distributed, sensor networks, is possible due to the emergence and convergence of a few innovative technologies. Avaak has developed a vision network that is aided by other sensors such as motion, acoustic and magnetic, and plans to deploy it for use in military and commercial applications. In comparison to other sensors, imagers produce large data files that require pre-processing and a certain level of compression before these are transmitted to a network server, in order to minimize the load on the network. Some of the most innovative chemical detectors currently in development are based on sensors that change color or pattern in the presence of the desired analytes. These changes are easily recorded and analyzed by a CMOS imager and an on-board DSP processor. Image processing at the sensor node level may also be required for applications in security, asset management and process control. Due to the data bandwidth requirements posed on the network by video sensors, new networking protocols or video extensions to existing standards (e.g. Zigbee) are required. To this end, Avaak has designed and implemented an ultra-low power networking protocol designed to carry large volumes of data through the network. The low power wireless sensor nodes that will be discussed include a chemical sensor integrated with a CMOS digital camera, a controller, a DSP processor and a radio communication transceiver, which enables relaying of an alarm or image message, to a central station. In addition to the communications, identification is very desirable; hence location awareness will be later incorporated to the system in the form of Time-Of-Arrival triangulation, via wide band signaling. While the wireless imaging kernel already exists specific applications for surveillance and chemical detection are under development by Avaak, as part of a co-founded program from ONR and DARPA. Avaak is also designing vision networks for commercial applications - some of which are undergoing initial field tests.

Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments.

PubMed

Roy, Nirmalya; Misra, Archan; Cook, Diane

2016-02-01

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users' spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user or a home environment. In this paper, we propose a hybrid approach for recognizing complex activities of daily living (ADL), that lie in between the two extremes of intensive use of body-worn sensors and the use of ambient sensors. Our approach harnesses the power of simple ambient sensors (e.g., motion sensors) to provide additional 'hidden' context (e.g., room-level location) of an individual, and then combines this context with smartphone-based sensing of micro-level postural/locomotive states. The major novelty is our focus on multi-inhabitant environments, where we show how the use of spatiotemporal constraints along with multitude of data sources can be used to significantly improve the accuracy and computational overhead of traditional activity recognition based approaches such as coupled-hidden Markov models. Experimental results on two separate smart home datasets demonstrate that this approach improves the accuracy of complex ADL classification by over 30 %, compared to pure smartphone-based solutions.

Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments

PubMed Central

Misra, Archan; Cook, Diane

2016-01-01

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users' spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user or a home environment. In this paper, we propose a hybrid approach for recognizing complex activities of daily living (ADL), that lie in between the two extremes of intensive use of body-worn sensors and the use of ambient sensors. Our approach harnesses the power of simple ambient sensors (e.g., motion sensors) to provide additional ‘hidden’ context (e.g., room-level location) of an individual, and then combines this context with smartphone-based sensing of micro-level postural/locomotive states. The major novelty is our focus on multi-inhabitant environments, where we show how the use of spatiotemporal constraints along with multitude of data sources can be used to significantly improve the accuracy and computational overhead of traditional activity recognition based approaches such as coupled-hidden Markov models. Experimental results on two separate smart home datasets demonstrate that this approach improves the accuracy of complex ADL classification by over 30 %, compared to pure smartphone-based solutions. PMID:27042240

Visualizing the history of living spaces.

PubMed

Ivanov, Yuri; Wren, Christopher; Sorokin, Alexander; Kaur, Ishwinder

2007-01-01

The technology available to building designers now makes it possible to monitor buildings on a very large scale. Video cameras and motion sensors are commonplace in practically every office space, and are slowly making their way into living spaces. The application of such technologies, in particular video cameras, while improving security, also violates privacy. On the other hand, motion sensors, while being privacy-conscious, typically do not provide enough information for a human operator to maintain the same degree of awareness about the space that can be achieved by using video cameras. We propose a novel approach in which we use a large number of simple motion sensors and a small set of video cameras to monitor a large office space. In our system we deployed 215 motion sensors and six video cameras to monitor the 3,000-square-meter office space occupied by 80 people for a period of about one year. The main problem in operating such systems is finding a way to present this highly multidimensional data, which includes both spatial and temporal components, to a human operator to allow browsing and searching recorded data in an efficient and intuitive way. In this paper we present our experiences and the solutions that we have developed in the course of our work on the system. We consider this work to be the first step in helping designers and managers of building systems gain access to information about occupants' behavior in the context of an entire building in a way that is only minimally intrusive to the occupants' privacy.

Large-Scale Covariability Between Aerosol and Precipitation Over the 7-SEAS Region: Observations and Simulations

NASA Technical Reports Server (NTRS)

Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Zhang, Chidong; Jeong, Myeong Jae; Gautam, Ritesh; Bettenhausen, Corey; Sayer, Andrew M.; Hansell, Richard A.; Liu, Xiaohong;

A Low Cost Matching Motion Estimation Sensor Based on the NIOS II Microprocessor

PubMed Central

González, Diego; Botella, Guillermo; Meyer-Baese, Uwe; García, Carlos; Sanz, Concepción; Prieto-Matías, Manuel; Tirado, Francisco

2012-01-01

This work presents the implementation of a matching-based motion estimation sensor on a Field Programmable Gate Array (FPGA) and NIOS II microprocessor applying a C to Hardware (C2H) acceleration paradigm. The design, which involves several matching algorithms, is mapped using Very Large Scale Integration (VLSI) technology. These algorithms, as well as the hardware implementation, are presented here together with an extensive analysis of the resources needed and the throughput obtained. The developed low-cost system is practical for real-time throughput and reduced power consumption and is useful in robotic applications, such as tracking, navigation using an unmanned vehicle, or as part of a more complex system. PMID:23201989

CMOS Imaging Sensor Technology for Aerial Mapping Cameras

NASA Astrophysics Data System (ADS)

Neumann, Klaus; Welzenbach, Martin; Timm, Martin

2016-06-01

In June 2015 Leica Geosystems launched the first large format aerial mapping camera using CMOS sensor technology, the Leica DMC III. This paper describes the motivation to change from CCD sensor technology to CMOS for the development of this new aerial mapping camera. In 2002 the DMC first generation was developed by Z/I Imaging. It was the first large format digital frame sensor designed for mapping applications. In 2009 Z/I Imaging designed the DMC II which was the first digital aerial mapping camera using a single ultra large CCD sensor to avoid stitching of smaller CCDs. The DMC III is now the third generation of large format frame sensor developed by Z/I Imaging and Leica Geosystems for the DMC camera family. It is an evolution of the DMC II using the same system design with one large monolithic PAN sensor and four multi spectral camera heads for R,G, B and NIR. For the first time a 391 Megapixel large CMOS sensor had been used as PAN chromatic sensor, which is an industry record. Along with CMOS technology goes a range of technical benefits. The dynamic range of the CMOS sensor is approx. twice the range of a comparable CCD sensor and the signal to noise ratio is significantly better than with CCDs. Finally results from the first DMC III customer installations and test flights will be presented and compared with other CCD based aerial sensors.

High performance computing applications in neurobiological research

NASA Technical Reports Server (NTRS)

Ross, Muriel D.; Cheng, Rei; Doshay, David G.; Linton, Samuel W.; Montgomery, Kevin; Parnas, Bruce R.

1994-01-01

The human nervous system is a massively parallel processor of information. The vast numbers of neurons, synapses and circuits is daunting to those seeking to understand the neural basis of consciousness and intellect. Pervading obstacles are lack of knowledge of the detailed, three-dimensional (3-D) organization of even a simple neural system and the paucity of large scale, biologically relevant computer simulations. We use high performance graphics workstations and supercomputers to study the 3-D organization of gravity sensors as a prototype architecture foreshadowing more complex systems. Scaled-down simulations run on a Silicon Graphics workstation and scale-up, three-dimensional versions run on the Cray Y-MP and CM5 supercomputers.

Biomagnetic Monitoring of Atmospheric Pollution: A Review of Magnetic Signatures from Biological Sensors.

PubMed

Hofman, Jelle; Maher, Barbara A; Muxworthy, Adrian R; Wuyts, Karen; Castanheiro, Ana; Samson, Roeland

2017-06-20

Biomagnetic monitoring of atmospheric pollution is a growing application in the field of environmental magnetism. Particulate matter (PM) in atmospheric pollution contains readily measurable concentrations of magnetic minerals. Biological surfaces, exposed to atmospheric pollution, accumulate magnetic particles over time, providing a record of location-specific, time-integrated air quality information. This review summarizes current knowledge of biological material ("sensors") used for biomagnetic monitoring purposes. Our work addresses the following: the range of magnetic properties reported for lichens, mosses, leaves, bark, trunk wood, insects, crustaceans, mammal and human tissues; their associations with atmospheric pollutant species (PM, NO x , trace elements, PAHs); the pros and cons of biomagnetic monitoring of atmospheric pollution; current challenges for large-scale implementation of biomagnetic monitoring; and future perspectives. A summary table is presented, with the aim of aiding researchers and policy makers in selecting the most suitable biological sensor for their intended biomagnetic monitoring purpose.

A signal processing framework for simultaneous detection of multiple environmental contaminants

NASA Astrophysics Data System (ADS)

Chakraborty, Subhadeep; Manahan, Michael P.; Mench, Matthew M.

2013-11-01

The possibility of large-scale attacks using chemical warfare agents (CWAs) has exposed the critical need for fundamental research enabling the reliable, unambiguous and early detection of trace CWAs and toxic industrial chemicals. This paper presents a unique approach for the identification and classification of simultaneously present multiple environmental contaminants by perturbing an electrochemical (EC) sensor with an oscillating potential for the extraction of statistically rich information from the current response. The dynamic response, being a function of the degree and mechanism of contamination, is then processed with a symbolic dynamic filter for the extraction of representative patterns, which are then classified using a trained neural network. The approach presented in this paper promises to extend the sensing power and sensitivity of these EC sensors by augmenting and complementing sensor technology with state-of-the-art embedded real-time signal processing capabilities.

Smart-Pixel Array Processors Based on Optimal Cellular Neural Networks for Space Sensor Applications

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi; Sheu, Bing J.; Venus, Holger; Sandau, Rainer

1997-01-01

A smart-pixel cellular neural network (CNN) with hardware annealing capability, digitally programmable synaptic weights, and multisensor parallel interface has been under development for advanced space sensor applications. The smart-pixel CNN architecture is a programmable multi-dimensional array of optoelectronic neurons which are locally connected with their local neurons and associated active-pixel sensors. Integration of the neuroprocessor in each processor node of a scalable multiprocessor system offers orders-of-magnitude computing performance enhancements for on-board real-time intelligent multisensor processing and control tasks of advanced small satellites. The smart-pixel CNN operation theory, architecture, design and implementation, and system applications are investigated in detail. The VLSI (Very Large Scale Integration) implementation feasibility was illustrated by a prototype smart-pixel 5x5 neuroprocessor array chip of active dimensions 1380 micron x 746 micron in a 2-micron CMOS technology.

Implementation of Wireless and Intelligent Sensor Technologies in the Propulsion Test Environment

NASA Technical Reports Server (NTRS)

Solano, Wanda M.; Junell, Justin C.; Shumard, Kenneth

2003-01-01

From the first Saturn V rocket booster (S-II-T) testing in 1966 and the routine Space Shuttle Main Engine (SSME) testing beginning in 1975, to more recent test programs such as the X-33 Aerospike Engine, the Integrated Powerhead Development (IPD) program, and the Hybrid Sounding Rocket (HYSR), Stennis Space Center (SSC) continues to be a premier location for conducting large-scale propulsion testing. Central to each test program is the capability for sensor systems to deliver reliable measurements and high quality data, while also providing a means to monitor the test stand area to the highest degree of safety and sustainability. As part of an on-going effort to enhance the testing capabilities of Stennis Space Center, the Test Technology and Development group is developing and applying a number of wireless and intelligent sensor technologies in ways that are new to the test existing test environment.

Management of Large-Scale Wireless Sensor Networks Utilizing Multi-Parent Recursive Area Hierarchies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cree, Johnathan V.; Delgado-Frias, Jose

2013-04-19

Autonomously configuring and self-healing a largescale wireless sensor network requires a light-weight maintenance protocol that is scalable. Further, in a battery powered wireless sensor network duty-cycling a node’s radio can reduce the power consumption of a device and extend the lifetime of a network. With duty-cycled nodes the power consumption of a node’s radio depends on the amount of communication is must perform and by reducing the communication the power consumption can also be reduced. Multi-parent hierarchies can be used to reduce the communication cost when constructing a recursive area clustering hierarchy when compared to singleparent solutions that utilize inefficientmore » communication methods such as flooding and information propagation via single-hop broadcasts. The multi-parent hierarchies remain scalable and provides a level of redundancy for the hierarchy.« less

Toward RADSCAT measurements over the sea and their interpretation

NASA Technical Reports Server (NTRS)

Claassen, J. P.; Fung, A. K.; Wu, S. T.; Chan, H. L.

1973-01-01

Investigations into several areas which are essential to the execution and interpretation of suborbital observations by composite radiometer - scatterometer sensor (RADSCAT) are reported. Experiments and theory were developed to demonstrate the remote anemometric capability of the sensor over the sea through various weather conditions. It is shown that weather situations found in extra tropical cyclones are useful for demonstrating the all weather capability of the composite sensor. The large scale fluctuations of the wind over the sea dictate the observational coverage required to correlate measurements with the mean surface wind speed. Various theoretical investigations were performed to establish a premise for the joint interpretation of the experiment data. The effects of clouds and rains on downward radiometric observations over the sea were computed. A method of predicting atmospheric attenuation from joint observations is developed. In other theoretical efforts, the emission and scattering characteristics of the sea were derived. Composite surface theories with coherent and noncoherent assumptions were employed.

The need for harmonization of methods for finding locations and magnitudes of air pollution sources using observations of concentrations and wind fields

NASA Astrophysics Data System (ADS)

Hanna, Steven R.; Young, George S.

2017-01-01

What do the terms "top-down", "inverse", "backwards", "adjoint", "sensor data fusion", "receptor", "source term estimation (STE)", to name several appearing in the current literature, have in common? These varied terms are used by different disciplines to describe the same general methodology - the use of observations of air pollutant concentrations and knowledge of wind fields to identify air pollutant source locations and/or magnitudes. Academic journals are publishing increasing numbers of papers on this topic. Examples of scenarios related to this growing interest, ordered from small scale to large scale, are: use of real-time samplers to quickly estimate the location of a toxic gas release by a terrorist at a large public gathering (e.g., Haupt et al., 2009);

Cosmology Large Angular Scale Surveyor (CLASS) Focal Plane Development

NASA Technical Reports Server (NTRS)

Chuss, D. T.; Ali, A.; Amiri, M.; Appel, J.; Bennett, C. L.; Colazo, F.; Denis, K. L.; Dunner, R.; Essinger-Hileman, T.; Eimer, J.;

Cosmology Large Angular Scale Surveyor (CLASS) Focal Plane Development

NASA Astrophysics Data System (ADS)

Chuss, D. T.; Ali, A.; Amiri, M.; Appel, J.; Bennett, C. L.; Colazo, F.; Denis, K. L.; Dünner, R.; Essinger-Hileman, T.; Eimer, J.; Fluxa, P.; Gothe, D.; Halpern, M.; Harrington, K.; Hilton, G.; Hinshaw, G.; Hubmayr, J.; Iuliano, J.; Marriage, T. A.; Miller, N.; Moseley, S. H.; Mumby, G.; Petroff, M.; Reintsema, C.; Rostem, K.; U-Yen, K.; Watts, D.; Wagner, E.; Wollack, E. J.; Xu, Z.; Zeng, L.

2016-08-01

The Cosmology Large Angular Scale Surveyor (CLASS) will measure the polarization of the Cosmic Microwave Background to search for and characterize the polarized signature of inflation. CLASS will operate from the Atacama Desert and observe ˜ 70 % of the sky. A variable-delay polarization modulator provides modulation of the polarization at ˜ 10 Hz to suppress the 1/ f noise of the atmosphere and enable the measurement of the large angular scale polarization modes. The measurement of the inflationary signal across angular scales that spans both the recombination and reionization features allows a test of the predicted shape of the polarized angular power spectra in addition to a measurement of the energy scale of inflation. CLASS is an array of telescopes covering frequencies of 38, 93, 148, and 217 GHz. These frequencies straddle the foreground minimum and thus allow the extraction of foregrounds from the primordial signal. Each focal plane contains feedhorn-coupled transition-edge sensors that simultaneously detect two orthogonal linear polarizations. The use of single-crystal silicon as the dielectric for the on-chip transmission lines enables both high efficiency and uniformity in fabrication. Integrated band definition has been implemented that both controls the bandpass of the single-mode transmission on the chip and prevents stray light from coupling to the detectors.

MicroSensors Systems: detection of a dismounted threat

NASA Astrophysics Data System (ADS)

Davis, Bill; Berglund, Victor; Falkofske, Dwight; Krantz, Brian

2005-05-01

The Micro Sensor System (MSS) is a layered sensor network with the goal of detecting dismounted threats approaching high value assets. A low power unattended ground sensor network is dependant on a network protocol for efficiency in order to minimize data transmissions after network establishment. The reduction of network 'chattiness' is a primary driver for minimizing power consumption and is a factor in establishing a low probability of detection and interception. The MSS has developed a unique protocol to meet these challenges. Unattended ground sensor systems are most likely dependant on batteries for power which due to size determines the ability of the sensor to be concealed after placement. To minimize power requirements, overcome size limitations, and maintain a low system cost the MSS utilizes advanced manufacturing processes know as Fluidic Self-Assembly and Chip Scale Packaging. The type of sensing element and the ability to sense various phenomenologies (particularly magnetic) at ranges greater than a few meters limits the effectiveness of a system. The MicroSensor System will overcome these limitations by deploying large numbers of low cost sensors, which is made possible by the advanced manufacturing process used in production of the sensors. The MSS program will provide unprecedented levels of real-time battlefield information which greatly enhances combat situational awareness when integrated with the existing Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance (C4ISR) infrastructure. This system will provide an important boost to realizing the information dominant, network-centric objective of Joint Vision 2020.

Is flat fielding safe for precision CCD astronomy?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baumer, Michael; Davis, Christopher P.; Roodman, Aaron

The ambitious goals of precision cosmology with wide-field optical surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST) demand precision CCD astronomy as their foundation. This in turn requires an understanding of previously uncharacterized sources of systematic error in CCD sensors, many of which manifest themselves as static effective variations in pixel area. Such variation renders a critical assumption behind the traditional procedure of flat fielding—that a sensor's pixels comprise a uniform grid—invalid. In this work, we present a method to infer a curl-free model of a sensor's underlying pixel grid from flat-field images,more » incorporating the superposition of all electrostatic sensor effects—both known and unknown—present in flat-field data. We use these pixel grid models to estimate the overall impact of sensor systematics on photometry, astrometry, and PSF shape measurements in a representative sensor from the Dark Energy Camera (DECam) and a prototype LSST sensor. Applying the method to DECam data recovers known significant sensor effects for which corrections are currently being developed within DES. For an LSST prototype CCD with pixel-response non-uniformity (PRNU) of 0.4%, we find the impact of "improper" flat fielding on these observables is negligible in nominal .7'' seeing conditions. Furthermore, these errors scale linearly with the PRNU, so for future LSST production sensors, which may have larger PRNU, our method provides a way to assess whether pixel-level calibration beyond flat fielding will be required.« less

Is flat fielding safe for precision CCD astronomy?

DOE PAGES

Baumer, Michael; Davis, Christopher P.; Roodman, Aaron

2017-07-06

The ambitious goals of precision cosmology with wide-field optical surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST) demand precision CCD astronomy as their foundation. This in turn requires an understanding of previously uncharacterized sources of systematic error in CCD sensors, many of which manifest themselves as static effective variations in pixel area. Such variation renders a critical assumption behind the traditional procedure of flat fielding—that a sensor's pixels comprise a uniform grid—invalid. In this work, we present a method to infer a curl-free model of a sensor's underlying pixel grid from flat-field images,more » incorporating the superposition of all electrostatic sensor effects—both known and unknown—present in flat-field data. We use these pixel grid models to estimate the overall impact of sensor systematics on photometry, astrometry, and PSF shape measurements in a representative sensor from the Dark Energy Camera (DECam) and a prototype LSST sensor. Applying the method to DECam data recovers known significant sensor effects for which corrections are currently being developed within DES. For an LSST prototype CCD with pixel-response non-uniformity (PRNU) of 0.4%, we find the impact of "improper" flat fielding on these observables is negligible in nominal .7'' seeing conditions. Furthermore, these errors scale linearly with the PRNU, so for future LSST production sensors, which may have larger PRNU, our method provides a way to assess whether pixel-level calibration beyond flat fielding will be required.« less

Improved Testing Capability and Adaptability Through the Use of Wireless Sensors

NASA Technical Reports Server (NTRS)

Solano, Wanda M.

2003-01-01

From the first Saturn V rocket booster (S-II-T) testing in 1966 and the routine Space Shuttle Main Engine (SSME) testing beginning in 1975, to more recent test programs such as the X-33 Aerospike Engine, the Integrated Powerhead Development (IPD) program, and the Hybrid Sounding Rocket (HYSR), Stennis Space Center (SSC) continues to be a premier location for conducting large-scale testing. Central to each test program is the capability for sensor systems to deliver reliable measurements and high quality data, while also providing a means to monitor the test stand area to the highest degree of safety and sustainability. Sensor wiring is routed along piping and through cable trenches, making its way from the engine test area, through the test stand area and to the signal conditioning building before final transfer to the test control center. When sensor requirements lie outside the reach of the routine sensor cable routing, the use of wireless sensor networks becomes particularly attractive due to their versatility and ease of installation. As part of an on-going effort to enhance the testing capabilities of Stennis Space Center, the Test Technology and Development group has found numerous applications for its sensor-adaptable wireless sensor suite. While not intended for critical engine measurements or control loops, in-house hardware and software development of the sensor suite can provide improved testing capability for a range of applications including the safety monitoring of propellant storage barrels and as an experimental test-bed for embedded health monitoring paradigms.

Chip-scale sensor system integration for portable health monitoring.

PubMed

Jokerst, Nan M; Brooke, Martin A; Cho, Sang-Yeon; Shang, Allan B

2007-12-01

The revolution in integrated circuits over the past 50 yr has produced inexpensive computing and communications systems that are powerful and portable. The technologies for these integrated chip-scale sensing systems, which will be miniature, lightweight, and portable, are emerging with the integration of sensors with electronics, optical systems, micromachines, microfluidics, and the integration of chemical and biological materials (soft/wet material integration with traditional dry/hard semiconductor materials). Hence, we stand at a threshold for health monitoring technology that promises to provide wearable biochemical sensing systems that are comfortable, inauspicious, wireless, and battery-operated, yet that continuously monitor health status, and can transmit compressed data signals at regular intervals, or alarm conditions immediately. In this paper, we explore recent results in chip-scale sensor integration technology for health monitoring. The development of inexpensive chip-scale biochemical optical sensors, such as microresonators, that are customizable for high sensitivity coupled with rapid prototyping will be discussed. Ground-breaking work in the integration of chip-scale optical systems to support these optical sensors will be highlighted, and the development of inexpensive Si complementary metal-oxide semiconductor circuitry (which makes up the vast majority of computational systems today) for signal processing and wireless communication with local receivers that lie directly on the chip-scale sensor head itself will be examined.

Cloud-Based Automated Design and Additive Manufacturing: A Usage Data-Enabled Paradigm Shift

PubMed Central

Lehmhus, Dirk; Wuest, Thorsten; Wellsandt, Stefan; Bosse, Stefan; Kaihara, Toshiya; Thoben, Klaus-Dieter; Busse, Matthias

2015-01-01

Integration of sensors into various kinds of products and machines provides access to in-depth usage information as basis for product optimization. Presently, this large potential for more user-friendly and efficient products is not being realized because (a) sensor integration and thus usage information is not available on a large scale and (b) product optimization requires considerable efforts in terms of manpower and adaptation of production equipment. However, with the advent of cloud-based services and highly flexible additive manufacturing techniques, these obstacles are currently crumbling away at rapid pace. The present study explores the state of the art in gathering and evaluating product usage and life cycle data, additive manufacturing and sensor integration, automated design and cloud-based services in manufacturing. By joining and extrapolating development trends in these areas, it delimits the foundations of a manufacturing concept that will allow continuous and economically viable product optimization on a general, user group or individual user level. This projection is checked against three different application scenarios, each of which stresses different aspects of the underlying holistic concept. The following discussion identifies critical issues and research needs by adopting the relevant stakeholder perspectives. PMID:26703606

Cloud-Based Automated Design and Additive Manufacturing: A Usage Data-Enabled Paradigm Shift.

PubMed

Lehmhus, Dirk; Wuest, Thorsten; Wellsandt, Stefan; Bosse, Stefan; Kaihara, Toshiya; Thoben, Klaus-Dieter; Busse, Matthias

2015-12-19

Integration of sensors into various kinds of products and machines provides access to in-depth usage information as basis for product optimization. Presently, this large potential for more user-friendly and efficient products is not being realized because (a) sensor integration and thus usage information is not available on a large scale and (b) product optimization requires considerable efforts in terms of manpower and adaptation of production equipment. However, with the advent of cloud-based services and highly flexible additive manufacturing techniques, these obstacles are currently crumbling away at rapid pace. The present study explores the state of the art in gathering and evaluating product usage and life cycle data, additive manufacturing and sensor integration, automated design and cloud-based services in manufacturing. By joining and extrapolating development trends in these areas, it delimits the foundations of a manufacturing concept that will allow continuous and economically viable product optimization on a general, user group or individual user level. This projection is checked against three different application scenarios, each of which stresses different aspects of the underlying holistic concept. The following discussion identifies critical issues and research needs by adopting the relevant stakeholder perspectives.

Enhancement of Tropical Land Cover Mapping with Wavelet-Based Fusion and Unsupervised Clustering of SAR and Landsat Image Data

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Laporte, Nadine; Netanyahuy, Nathan S.; Zukor, Dorothy (Technical Monitor)

2001-01-01

The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument, In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.

Maestro: an orchestration framework for large-scale WSN simulations.

PubMed

Riliskis, Laurynas; Osipov, Evgeny

2014-03-18

Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol stacks for communications. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. It is therefore challenging to develop, test and validate even small WSN applications, and this process can easily consume significant resources. Simulations are inexpensive tools for testing, verifying and generally experimenting with new technologies in a repeatable fashion. Consequently, as the size of the systems to be tested increases, so does the need for large-scale simulations. This article describes a tool called Maestro for the automation of large-scale simulation and investigates the feasibility of using cloud computing facilities for such task. Using tools that are built into Maestro, we demonstrate a feasible approach for benchmarking cloud infrastructure in order to identify cloud Virtual Machine (VM)instances that provide an optimal balance of performance and cost for a given simulation.

Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing

DOE PAGES

Steed, Chad A.; Halsey, William; Dehoff, Ryan; ...

2017-02-16

Flexible visual analysis of long, high-resolution, and irregularly sampled time series data from multiple sensor streams is a challenge in several domains. In the field of additive manufacturing, this capability is critical for realizing the full potential of large-scale 3D printers. Here, we propose a visual analytics approach that helps additive manufacturing researchers acquire a deep understanding of patterns in log and imagery data collected by 3D printers. Our specific goals include discovering patterns related to defects and system performance issues, optimizing build configurations to avoid defects, and increasing production efficiency. We introduce Falcon, a new visual analytics system thatmore » allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations, all with adjustable scale options. To illustrate the effectiveness of Falcon at providing thorough and efficient knowledge discovery, we present a practical case study involving experts in additive manufacturing and data from a large-scale 3D printer. The techniques described are applicable to the analysis of any quantitative time series, though the focus of this paper is on additive manufacturing.« less

Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steed, Chad A.; Halsey, William; Dehoff, Ryan

Flexible visual analysis of long, high-resolution, and irregularly sampled time series data from multiple sensor streams is a challenge in several domains. In the field of additive manufacturing, this capability is critical for realizing the full potential of large-scale 3D printers. Here, we propose a visual analytics approach that helps additive manufacturing researchers acquire a deep understanding of patterns in log and imagery data collected by 3D printers. Our specific goals include discovering patterns related to defects and system performance issues, optimizing build configurations to avoid defects, and increasing production efficiency. We introduce Falcon, a new visual analytics system thatmore » allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations, all with adjustable scale options. To illustrate the effectiveness of Falcon at providing thorough and efficient knowledge discovery, we present a practical case study involving experts in additive manufacturing and data from a large-scale 3D printer. The techniques described are applicable to the analysis of any quantitative time series, though the focus of this paper is on additive manufacturing.« less

Maestro: An Orchestration Framework for Large-Scale WSN Simulations

PubMed Central

Riliskis, Laurynas; Osipov, Evgeny

2014-01-01

Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol stacks for communications. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. It is therefore challenging to develop, test and validate even small WSN applications, and this process can easily consume significant resources. Simulations are inexpensive tools for testing, verifying and generally experimenting with new technologies in a repeatable fashion. Consequently, as the size of the systems to be tested increases, so does the need for large-scale simulations. This article describes a tool called Maestro for the automation of large-scale simulation and investigates the feasibility of using cloud computing facilities for such task. Using tools that are built into Maestro, we demonstrate a feasible approach for benchmarking cloud infrastructure in order to identify cloud Virtual Machine (VM)instances that provide an optimal balance of performance and cost for a given simulation. PMID:24647123

Experiences with a Decade of Wireless Sensor Networks in Mountain Cryosphere Research

NASA Astrophysics Data System (ADS)

Beutel, Jan

2017-04-01

Research in geoscience depends on high-quality measurements over long periods of time in order to understand processes and to create and validate models. The promise of wireless sensor networks to monitor autonomously at unprecedented spatial and temporal scale motivated the use of this novel technology for studying mountain permafrost in the mid 2000s. Starting from a first experimental deployment to investigate the thermal properties of steep bedrock permafrost in 2006 on the Jungfraujoch, Switzerland at 3500 m asl using prototype wireless sensors the PermaSense project has evolved into a multi-site and multi-discipline initiative. We develop, deploy and operate wireless sensing systems customized for long-term autonomous operation in high-mountain environments. Around this central element, we develop concepts, methods and tools to investigate and to quantify the connection between climate, cryosphere (permafrost, glaciers, snow) and geomorphodynamics. In this presentation, we describe the concepts and system architecture used both for the wireless sensor network as well as for data management and processing. Furthermore, we will discuss the experience gained in over a decade of planning, installing and operating large deployments on field sites spread across a large part of the Swiss and French Alps and applications ranging from academic, experimental research campaigns, long-term monitoring and natural hazard warning in collaboration with government authorities and local industry partners. Reference http://www.permasense.ch Online Open Data Access http://data.permasense.ch

Bidirectional QoS support for novelty detection applications based on hierarchical wireless sensor network model

NASA Astrophysics Data System (ADS)

Edwards, Mark; Hu, Fei; Kumar, Sunil

2004-10-01

The research on the Novelty Detection System (NDS) (called as VENUS) at the authors' universities has generated exciting results. For example, we can detect an abnormal behavior (such as cars thefts from the parking lot) from a series of video frames based on the cognitively motivated theory of habituation. In this paper, we would like to describe the implementation strategies of lower layer protocols for using large-scale Wireless Sensor Networks (WSN) to NDS with Quality-of-Service (QoS) support. Wireless data collection framework, consisting of small and low-power sensor nodes, provides an alternative mechanism to observe the physical world, by using various types of sensing capabilities that include images (and even videos using Panoptos), sound and basic physical measurements such as temperature. We do not want to lose any 'data query command' packets (in the downstream direction: sink-to-sensors) or have any bit-errors in them since they are so important to the whole sensor network. In the upstream direction (sensors-to-sink), we may tolerate the loss of some sensing data packets. But the 'interested' sensing flow should be assigned a higher priority in terms of multi-hop path choice, network bandwidth allocation, and sensing data packet generation frequency (we hope to generate more sensing data packet for that novel event in the specified network area). The focus of this paper is to investigate MAC-level Quality of Service (QoS) issue in Wireless Sensor Networks (WSN) for Novelty Detection applications. Although QoS has been widely studied in other types of networks including wired Internet, general ad hoc networks and mobile cellular networks, we argue that QoS in WSN has its own characteristics. In wired Internet, the main QoS parameters include delay, jitter and bandwidth. In mobile cellular networks, two most common QoS metrics are: handoff call dropping probability and new call blocking probability. Since the main task of WSN is to detect and report events, the most important QoS parameters should include sensing data packet transmission reliability, lifetime extension degree from sensor sleeping control, event detection latency, congestion reduction level through removal of redundant sensing data. In this paper, we will focus on the following bi-directional QoS topics: (1) Downstream (sink-to-sensor) QoS: Reliable data query command forwarding to particular sensor(s). In other words, we do not want to lose the query command packets; (2) Upstream (sensor-to-sink) QoS: transmission of sensed data with priority control. The more interested data that can help in novelty detection should be transmitted on an optimal path with higher reliability. We propose the use of Differentiated Data Collection. Due to the large-scale nature and resource constraints of typical wireless sensor networks, such as limited energy, small memory (typically RAM < 4K bytes) and short communication range, the above problems become even more challenging. Besides QoS support issue, we will also describe our low-energy Sensing Data Transmission network Architecture. Our research results show the scalability and energy-efficiency of our proposed WSN QoS schemes.

Fire Detection Organizing Questions

NASA Technical Reports Server (NTRS)

2004-01-01

Verified models of fire precursor transport in low and partial gravity: a. Development of models for large-scale transport in reduced gravity. b. Validated CFD simulations of transport of fire precursors. c. Evaluation of the effect of scale on transport and reduced gravity fires. Advanced fire detection system for gaseous and particulate pre-fire and fire signaturesa: a. Quantification of pre-fire pyrolysis products in microgravity. b. Suite of gas and particulate sensors. c. Reduced gravity evaluation of candidate detector technologies. d. Reduced gravity verification of advanced fire detection system. e. Validated database of fire and pre-fire signatures in low and partial gravity.

Exploration of geomagnetic field anomaly with balloon for geophysical research

NASA Astrophysics Data System (ADS)

Jia, Wen-Kui

The use of a balloon to explore the geomagnetic field anomaly in the area east of Beijing is demonstrated. The present results are compared with those of aerial surveys. Descriptions are given of the fluxgate magnetometer, the sensor's attitude control and measurement, and data transmission and processing. At an altitude of about 30 km, a positive anomaly of the vertical component of about 100 nanoteslas was measured. The results suggest that, for this particular area, the shallow layer of a small-scale geological structure differs from the deep layer of a large-scale geological structure.

Intercomparison of cosmic-ray neutron sensors and water balance monitoring in an urban environment

NASA Astrophysics Data System (ADS)

Schrön, Martin; Zacharias, Steffen; Womack, Gary; Köhli, Markus; Desilets, Darin; Oswald, Sascha E.; Bumberger, Jan; Mollenhauer, Hannes; Kögler, Simon; Remmler, Paul; Kasner, Mandy; Denk, Astrid; Dietrich, Peter

2018-03-01

Sensor-to-sensor variability is a source of error common to all geoscientific instruments that needs to be assessed before comparative and applied research can be performed with multiple sensors. Consistency among sensor systems is especially critical when subtle features of the surrounding terrain are to be identified. Cosmic-ray neutron sensors (CRNSs) are a recent technology used to monitor hectometre-scale environmental water storages, for which a rigorous comparison study of numerous co-located sensors has not yet been performed. In this work, nine stationary CRNS probes of type CRS1000 were installed in relative proximity on a grass patch surrounded by trees, buildings, and sealed areas. While the dynamics of the neutron count rates were found to be similar, offsets of a few percent from the absolute average neutron count rates were found. Technical adjustments of the individual detection parameters brought all instruments into good agreement. Furthermore, we found a critical integration time of 6 h above which all sensors showed consistent dynamics in the data and their RMSE fell below 1 % of gravimetric water content. The residual differences between the nine signals indicated local effects of the complex urban terrain on the scale of several metres. Mobile CRNS measurements and spatial simulations with the URANOS neutron transport code in the surrounding area (25 ha) have revealed substantial sub-footprint heterogeneity to which CRNS detectors are sensitive despite their large averaging volume. The sealed and constantly dry structures in the footprint furthermore damped the dynamics of the CRNS-derived soil moisture. We developed strategies to correct for the sealed-area effect based on theoretical insights about the spatial sensitivity of the sensor. This procedure not only led to reliable soil moisture estimation during dry-out periods, it further revealed a strong signal of intercepted water that emerged over the sealed surfaces during rain events. The presented arrangement offered a unique opportunity to demonstrate the CRNS performance in complex terrain, and the results indicated great potential for further applications in urban climate research.

Large HAWT wake measurement and analysis

NASA Technical Reports Server (NTRS)

Miller, A. H.; Wegley, H. L.; Buck, J. W.

1995-01-01

From the theoretical fluid dynamics point of view, the wake region of a large horizontal-axis wind turbine has been defined and described, and numerical models of wake behavior have been developed. Wind tunnel studies of single turbine wakes and turbine array wakes have been used to verify the theory and further refine the numerical models. However, the effects of scaling, rotor solidity, and topography on wake behavior are questions that remain unanswered. In the wind tunnel studies, turbines were represented by anything from scaled models to tea strainers or wire mesh disks whose solidity was equivalent to that of a typical wind turbine. The scale factor compensation for the difference in Reynolds number between the scale model and an actual turbine is complex, and not typically accounted for. Though it is wise to study the simpler case of wakes in flat topography, which can be easily duplicated in the wind tunnel, current indications are that wind turbine farm development is actually occurring in somewhat more complex terrain. Empirical wake studies using large horizontal-axis wind turbines have not been thoroughly composited, and, therefore, the results have not been applied to the well-developed theory of wake structure. The measurement programs have made use of both in situ sensor systems, such as instrumented towers, and remote sensors, such as kites and tethered, balloonborne anemometers. We present a concise overview of the work that has been performed, including our own, which is based on the philosophy that the MOD-2 turbines are probably their own best detector of both the momentum deficit and the induced turbulence effect downwind. Only the momentum deficit aspects of the wake/machine interactions have been addressed. Both turbine power output deficits and wind energy deficits as measured by the onsite meteorological towers have been analyzed from a composite data set. The analysis has also evidenced certain topographic influences on the operation of spatially diverse wind turbines.

Large HAWT wake measurement and analysis

NASA Astrophysics Data System (ADS)

Miller, A. H.; Wegley, H. L.; Buck, J. W.

1995-05-01

From the theoretical fluid dynamics point of view, the wake region of a large horizontal-axis wind turbine has been defined and described, and numerical models of wake behavior have been developed. Wind tunnel studies of single turbine wakes and turbine array wakes have been used to verify the theory and further refine the numerical models. However, the effects of scaling, rotor solidity, and topography on wake behavior are questions that remain unanswered. In the wind tunnel studies, turbines were represented by anything from scaled models to tea strainers or wire mesh disks whose solidity was equivalent to that of a typical wind turbine. The scale factor compensation for the difference in Reynolds number between the scale model and an actual turbine is complex, and not typically accounted for. Though it is wise to study the simpler case of wakes in flat topography, which can be easily duplicated in the wind tunnel, current indications are that wind turbine farm development is actually occurring in somewhat more complex terrain. Empirical wake studies using large horizontal-axis wind turbines have not been thoroughly composited, and, therefore, the results have not been applied to the well-developed theory of wake structure. The measurement programs have made use of both in situ sensor systems, such as instrumented towers, and remote sensors, such as kites and tethered, balloonborne anemometers. We present a concise overview of the work that has been performed, including our own, which is based on the philosophy that the MOD-2 turbines are probably their own best detector of both the momentum deficit and the induced turbulence effect downwind. Only the momentum deficit aspects of the wake/machine interactions have been addressed. Both turbine power output deficits and wind energy deficits as measured by the onsite meteorological towers have been analyzed from a composite data set. The analysis has also evidenced certain topographic influences on the operation of spatially diverse wind turbines.

Investigation of the feasibility of non-invasive optical sensors for the quantitative assessment of dehydration.

PubMed

Visser, Cobus; Kieser, Eduard; Dellimore, Kiran; van den Heever, Dawie; Smith, Johan

2017-10-01

This study explores the feasibility of prospectively assessing infant dehydration using four non-invasive, optical sensors based on the quantitative and objective measurement of various clinical markers of dehydration. The sensors were investigated to objectively and unobtrusively assess the hydration state of an infant based on the quantification of capillary refill time (CRT), skin recoil time (SRT), skin temperature profile (STP) and skin tissue hydration by means of infrared spectrometry (ISP). To evaluate the performance of the sensors a clinical study was conducted on a cohort of 10 infants (aged 6-36 months) with acute gastroenteritis. High sensitivity and specificity were exhibited by the sensors, in particular the STP and SRT sensors, when combined into a fusion regression model (sensitivity: 0.90, specificity: 0.78). The SRT and STP sensors and the fusion model all outperformed the commonly used "gold standard" clinical dehydration scales including the Gorelick scale (sensitivity: 0.56, specificity: 0.56), CDS scale (sensitivity: 1.0, specificity: 0.2) and WHO scale (sensitivity: 0.13, specificity: 0.79). These results suggest that objective and quantitative assessment of infant dehydration may be possible using the sensors investigated. However, further evaluation of the sensors on a larger sample population is needed before deploying them in a clinical setting. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Silicon oxynitride-on-glass waveguide array refractometer with wide sensing range and integrated read-out (Conference Presentation)

NASA Astrophysics Data System (ADS)

Viegas, Jaime; Mayeh, Mona; Srinivasan, Pradeep; Johnson, Eric G.; Marques, Paulo V. S.; Farahi, Faramarz

2017-02-01

In this work, a silicon oxynitride-on-silica refractometer is presented, based on sub-wavelength coupled arrayed waveguide interference, and capable of low-cost, high resolution, large scale deployment. The sensor has an experimental spectral sensitivity as high as 3200 nm/RIU, covering refractive indices ranging from 1 (air) up to 1.43 (oils). The sensor readout can be performed by standard spectrometers techniques of by pattern projection onto a camera, followed by optical pattern recognition. Positive identification of the refractive index of an unknown species is obtained by pattern cross-correlation with a look-up calibration table based algorithm. Given the lower contrast between core and cladding in such devices, higher mode overlap with single mode fiber is achieved, leading to a larger coupling efficiency and more relaxed alignment requirements as compared to silicon photonics platform. Also, the optical transparency of the sensor in the visible range allows the operation with light sources and camera detectors in the visible range, of much lower capital costs for a complete sensor system. Furthermore, the choice of refractive indices of core and cladding in the sensor head with integrated readout, allows the fabrication of the same device in polymers, for mass-production replication of disposable sensors.

Temperature insensitive curvature sensor based on cascading photonic crystal fiber

NASA Astrophysics Data System (ADS)

Fu, Guangwei; Li, Yunpu; Fu, Xinghu; Jin, Wa; Bi, Weihong

2018-03-01

A temperature insensitive curvature sensor is proposed based on cascading photonic crystal fiber. Using the arc fusion splicing method, this sensor is fabricated by cascading together a single-mode fiber (SMF), a three layers air holes structure of photonic crystal fiber (3PCF), a five layers air holes structure of photonic crystal fiber (5PCF) and a SMF in turn. So the structure SMF-3PCF-5PCF-SMF can be obtained with a total length of 20 mm. During the process of fabrication, the splicing machine parameters and the length of each optical fiber are adjusted to obtain a high sensitivity curvature sensor. The experimental results show that the curvature sensitivity is -8.40 nm/m-1 in the curvature variation range of 0-1.09 m-1, which also show good linearity. In the range of 30-90 °C, the temperature sensitivity is only about 3.24 pm/°C, indicating that the sensor is not sensitive to temperature. The sensor not only has the advantages of easy fabricating, simple structure, high sensitivity but also can solve the problem of temperature measurement cross sensitivity, so it can be used for different areas including aerospace, large-scale bridge, architectural structure health monitoring and so on.

Parallel multi-join query optimization algorithm for distributed sensor network in the internet of things

NASA Astrophysics Data System (ADS)

Zheng, Yan

2015-03-01

Internet of things (IoT), focusing on providing users with information exchange and intelligent control, attracts a lot of attention of researchers from all over the world since the beginning of this century. IoT is consisted of large scale of sensor nodes and data processing units, and the most important features of IoT can be illustrated as energy confinement, efficient communication and high redundancy. With the sensor nodes increment, the communication efficiency and the available communication band width become bottle necks. Many research work is based on the instance which the number of joins is less. However, it is not proper to the increasing multi-join query in whole internet of things. To improve the communication efficiency between parallel units in the distributed sensor network, this paper proposed parallel query optimization algorithm based on distribution attributes cost graph. The storage information relations and the network communication cost are considered in this algorithm, and an optimized information changing rule is established. The experimental result shows that the algorithm has good performance, and it would effectively use the resource of each node in the distributed sensor network. Therefore, executive efficiency of multi-join query between different nodes could be improved.

Nanostructure Engineered Chemical Sensors for Hazardous Gas and Vapor Detection

NASA Technical Reports Server (NTRS)

Li, Jing; Lu, Yijiang

2005-01-01

A nanosensor technology has been developed using nanostructures, such as single walled carbon nanotubes (SWNTs) and metal oxides nanowires or nanobelts, on a pair of interdigitated electrodes (IDE) processed with a silicon based microfabrication and micromachining technique. The IDE fingers were fabricated using 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 hazardous gases and vapors, such as acetone, benzene, chlorine, and ammonia in the concentration range of ppm to ppb at room temperature. The electronic molecular sensing in our sensor platform can be understood by electron modulation between the nanostructure engineered device and gas molecules. As a result of the electron modulation, the conductance of nanodevice 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.

Efficient detection of contagious outbreaks in massive metropolitan encounter networks

PubMed Central

Sun, Lijun; Axhausen, Kay W.; Lee, Der-Horng; Cebrian, Manuel

2014-01-01

Physical contact remains difficult to trace in large metropolitan networks, though it is a key vehicle for the transmission of contagious outbreaks. Co-presence encounters during daily transit use provide us with a city-scale time-resolved physical contact network, consisting of 1 billion contacts among 3 million transit users. Here, we study the advantage that knowledge of such co-presence structures may provide for early detection of contagious outbreaks. We first examine the “friend sensor” scheme - a simple, but universal strategy requiring only local information - and demonstrate that it provides significant early detection of simulated outbreaks. Taking advantage of the full network structure, we then identify advanced “global sensor sets”, obtaining substantial early warning times savings over the friends sensor scheme. Individuals with highest number of encounters are the most efficient sensors, with performance comparable to individuals with the highest travel frequency, exploratory behavior and structural centrality. An efficiency balance emerges when testing the dependency on sensor size and evaluating sensor reliability; we find that substantial and reliable lead-time could be attained by monitoring only 0.01% of the population with the highest degree. PMID:24903017

Self-assembled diatom substrates with plasmonic functionality

NASA Astrophysics Data System (ADS)

Kwon, Sun Yong; Park, Sehyun; Nichols, William T.

2014-04-01

Marine diatoms have an exquisitely complex exoskeleton that is promising for engineered surfaces such as sensors and catalysts. For such applications, creating uniform arrays of diatom frustules across centimeter scales will be necessary. Here, we present a simple, low-cost floating interface technique to self-assemble the diatom frustules. We show that well-prepared diatoms form floating hexagonal close-packed arrays at the air-water interface that can be transferred directly to a substrate. We functionalize the assembled diatom surfaces with gold and characterize the plasmonic functionality by using surface enhanced Raman scattering (SERS). Thin gold films conform to the complex, hierarchical diatom structure and produce a SERS enhancement factor of 2 × 104. Small gold nanoparticles attached to the diatom's surface produce a higher enhancement of 7 × 104 due to stronger localization of the surface plasmons. Taken together, the large-scale assembly and plasmonic functionalization represent a promising platform to control the energy and the material flows at a complex surface for applications such as sensors and plasmonic enhanced catalysts.

Parameterization and scaling of Arctic ice conditions in the context of ice-atmosphere processes

NASA Technical Reports Server (NTRS)

Barry, R. G.; Heinrichs, J.; Steffen, K.; Maslanik, J. A.; Key, J.; Serreze, M. C.; Weaver, R. W.

1994-01-01

This report summarizes achievements during year three of our project to investigate the use of ERS-1 SAR data to study Arctic ice and ice/atmosphere processes. The project was granted a one year extension, and goals for the final year are outlined. The specific objects of the project are to determine how the development and evolution of open water/thin ice areas within the interior ice pack vary under different atmospheric synoptic regimes; compare how open water/thin ice fractions estimated from large-area divergence measurements differ from fractions determined by summing localized openings in the pack; relate these questions of scale and process to methods of observation, modeling, and averaging over time and space; determine whether SAR data might be used to calibrate ice concentration estimates from medium and low-rate bit sensors (AVHRR and DMSP-OLS) and the special sensor microwave imager (SSM/I); and investigate methods to integrate SAR data for turbulent heat flux parametrization at the atmosphere interface with other satellite data.

Topics in programmable automation. [for materials handling, inspection, and assembly

NASA Technical Reports Server (NTRS)

Rosen, C. A.

1975-01-01

Topics explored in the development of integrated programmable automation systems include: numerically controlled and computer controlled machining; machine intelligence and the emulation of human-like capabilities; large scale semiconductor integration technology applications; and sensor technology for asynchronous local computation without burdening the executive minicomputer which controls the whole system. The role and development of training aids, and the potential application of these aids to augmented teleoperator systems are discussed.

Characterizing Multiple Wireless Sensor Networks for Large-Scale Radio Tomography

DTIC Science & Technology

2015-03-01

with other transceivers over a wireless frequency. A base station transceiver collects the information and processes the information into something...or most other obstructions in between the two links [4]. A base station transceiver is connected to a processing computer to collect the RSS of each... transceivers at four different heights to create a Three-Dimensional (3-D) RTI network. Using shadowing- based RTI, this research demonstrated that RTI

Real-time terrain storage generation from multiple sensors towards mobile robot operation interface.

PubMed

Song, Wei; Cho, Seoungjae; Xi, Yulong; Cho, Kyungeun; Um, Kyhyun

2014-01-01

A mobile robot mounted with multiple sensors is used to rapidly collect 3D point clouds and video images so as to allow accurate terrain modeling. In this study, we develop a real-time terrain storage generation and representation system including a nonground point database (PDB), ground mesh database (MDB), and texture database (TDB). A voxel-based flag map is proposed for incrementally registering large-scale point clouds in a terrain model in real time. We quantize the 3D point clouds into 3D grids of the flag map as a comparative table in order to remove the redundant points. We integrate the large-scale 3D point clouds into a nonground PDB and a node-based terrain mesh using the CPU. Subsequently, we program a graphics processing unit (GPU) to generate the TDB by mapping the triangles in the terrain mesh onto the captured video images. Finally, we produce a nonground voxel map and a ground textured mesh as a terrain reconstruction result. Our proposed methods were tested in an outdoor environment. Our results show that the proposed system was able to rapidly generate terrain storage and provide high resolution terrain representation for mobile mapping services and a graphical user interface between remote operators and mobile robots.

Application of portable XRF and VNIR sensors for rapid assessment of soil heavy metal pollution.

PubMed

Hu, Bifeng; Chen, Songchao; Hu, Jie; Xia, Fang; Xu, Junfeng; Li, Yan; Shi, Zhou

2017-01-01

Rapid heavy metal soil surveys at large scale with high sampling density could not be conducted with traditional laboratory physical and chemical analyses because of the high cost, low efficiency and heavy workload involved. This study explored a rapid approach to assess heavy metals contamination in 301 farmland soils from Fuyang in Zhejiang Province, in the southern Yangtze River Delta, China, using portable proximal soil sensors. Portable X-ray fluorescence spectroscopy (PXRF) was used to determine soil heavy metals total concentrations while soil pH was predicted by portable visible-near infrared spectroscopy (PVNIR). Zn, Cu and Pb were successfully predicted by PXRF (R2 >0.90 and RPD >2.50) while As and Ni were predicted with less accuracy (R2 <0.75 and RPD <1.40). The pH values were well predicted by PVNIR. Classification of heavy metals contamination grades in farmland soils was conducted based on previous results; the Kappa coefficient was 0.87, which showed that the combination of PXRF and PVNIR was an effective and rapid method to determine the degree of pollution with soil heavy metals. This study provides a new approach to assess soil heavy metals pollution; this method will facilitate large-scale surveys of soil heavy metal pollution.

Real-Time Terrain Storage Generation from Multiple Sensors towards Mobile Robot Operation Interface

PubMed Central

Cho, Seoungjae; Xi, Yulong; Cho, Kyungeun

2014-01-01

A mobile robot mounted with multiple sensors is used to rapidly collect 3D point clouds and video images so as to allow accurate terrain modeling. In this study, we develop a real-time terrain storage generation and representation system including a nonground point database (PDB), ground mesh database (MDB), and texture database (TDB). A voxel-based flag map is proposed for incrementally registering large-scale point clouds in a terrain model in real time. We quantize the 3D point clouds into 3D grids of the flag map as a comparative table in order to remove the redundant points. We integrate the large-scale 3D point clouds into a nonground PDB and a node-based terrain mesh using the CPU. Subsequently, we program a graphics processing unit (GPU) to generate the TDB by mapping the triangles in the terrain mesh onto the captured video images. Finally, we produce a nonground voxel map and a ground textured mesh as a terrain reconstruction result. Our proposed methods were tested in an outdoor environment. Our results show that the proposed system was able to rapidly generate terrain storage and provide high resolution terrain representation for mobile mapping services and a graphical user interface between remote operators and mobile robots. PMID:25101321

Application of portable XRF and VNIR sensors for rapid assessment of soil heavy metal pollution

PubMed Central

Hu, Bifeng; Chen, Songchao; Hu, Jie; Xia, Fang; Xu, Junfeng; Li, Yan; Shi, Zhou

2017-01-01

Rapid heavy metal soil surveys at large scale with high sampling density could not be conducted with traditional laboratory physical and chemical analyses because of the high cost, low efficiency and heavy workload involved. This study explored a rapid approach to assess heavy metals contamination in 301 farmland soils from Fuyang in Zhejiang Province, in the southern Yangtze River Delta, China, using portable proximal soil sensors. Portable X-ray fluorescence spectroscopy (PXRF) was used to determine soil heavy metals total concentrations while soil pH was predicted by portable visible-near infrared spectroscopy (PVNIR). Zn, Cu and Pb were successfully predicted by PXRF (R2 >0.90 and RPD >2.50) while As and Ni were predicted with less accuracy (R2 <0.75 and RPD <1.40). The pH values were well predicted by PVNIR. Classification of heavy metals contamination grades in farmland soils was conducted based on previous results; the Kappa coefficient was 0.87, which showed that the combination of PXRF and PVNIR was an effective and rapid method to determine the degree of pollution with soil heavy metals. This study provides a new approach to assess soil heavy metals pollution; this method will facilitate large-scale surveys of soil heavy metal pollution. PMID:28234944

Simultaneous wall-shear-stress and wide-field PIV measurements in a turbulent boundary layer

NASA Astrophysics Data System (ADS)

Gomit, Guillaume; Fourrie, Gregoire; de Kat, Roeland; Ganapathisubramani, Bharathram

2015-11-01

Simultaneous particle image velocimetry (PIV) and hot-film shear stress sensor measurements were performed to study the large-scale structures associated with shear stress events in a flat plate turbulent boundary layer at a high Reynolds number (Reτ ~ 4000). The PIV measurement was performed in a streamwise-wall normal plane using an array of six high resolution cameras (4 ×16MP and 2 ×29MP). The resulting field of view covers 8 δ (where δ is the boundary layer thickness) in the streamwise direction and captures the entire boundary layer in the wall-normal direction. The spatial resolution of the measurement is approximately is approximately 70 wall units (1.8 mm) and sampled each 35 wall units (0.9 mm). In association with the PIV setup, a spanwise array of 10 skin-friction sensors (spanning one δ) was used to capture the footprint of the large-scale structures. This combination of measurements allowed the analysis of the three-dimensional conditional structures in the boundary layer. Particularly, from conditional averages, the 3D organisation of the wall normal and streamwise velocity components (u and v) and the Reynolds shear stress (-u'v') related to a low and high shear stress events can be extracted. European Research Council Grant No-277472-WBT.

Instrumentation Performance During the TMI-2 Accident

NASA Astrophysics Data System (ADS)

Rempe, Joy L.; Knudson, Darrell L.

2014-08-01

The accident at the Three Mile Island Unit 2 (TMI-2) reactor provided a unique opportunity to evaluate sensors exposed to severe accident conditions. The loss of coolant and the hydrogen combustion that occurred during this accident exposed instrumentation to harsh conditions, including direct radiation, radioactive contamination, and high humidity with elevated temperatures and pressures. As part of a program initiated by the Department of Energy Office of Nuclear Energy (DOE-NE), a review was completed to gain insights from prior TMI-2 sensor survivability and data qualification efforts. This new effort focused upon a set of sensors that provided critical data to TMI-2 operators for assessing the condition of the plant and the effects of mitigating actions taken by these operators. In addition, the effort considered sensors providing data required for subsequent accident simulations. Over 100 references related to instrumentation performance and post-accident evaluations of TMI-2 sensors and measurements were reviewed. Insights gained from this review are summarized within this paper. As noted within this paper, several techniques were invoked in the TMI-2 post-accident program to evaluate sensor survivability status and data qualification, including comparisons with data from other sensors, analytical calculations, laboratory testing, and comparisons with sensors subjected to similar conditions in large-scale integral tests and with sensors that were similar in design but more easily removed from the TMI-2 plant for evaluations. Conclusions from this review provide important insights related to sensor survivability and enhancement options for improving sensor performance. In addition, this paper provides recommendations related to sensor survivability and the data evaluation process that could be implemented in upcoming Fukushima Daiichi recovery efforts.

An Energy Scaled and Expanded Vector-Based Forwarding Scheme for Industrial Underwater Acoustic Sensor Networks with Sink Mobility.

PubMed

Wadud, Zahid; Hussain, Sajjad; Javaid, Nadeem; Bouk, Safdar Hussain; Alrajeh, Nabil; Alabed, Mohamad Souheil; Guizani, Nadra

2017-09-30

Industrial Underwater Acoustic Sensor Networks (IUASNs) come with intrinsic challenges like long propagation delay, small bandwidth, large energy consumption, three-dimensional deployment, and high deployment and battery replacement cost. Any routing strategy proposed for IUASN must take into account these constraints. The vector based forwarding schemes in literature forward data packets to sink using holding time and location information of the sender, forwarder, and sink nodes. Holding time suppresses data broadcasts; however, it fails to keep energy and delay fairness in the network. To achieve this, we propose an Energy Scaled and Expanded Vector-Based Forwarding (ESEVBF) scheme. ESEVBF uses the residual energy of the node to scale and vector pipeline distance ratio to expand the holding time. Resulting scaled and expanded holding time of all forwarding nodes has a significant difference to avoid multiple forwarding, which reduces energy consumption and energy balancing in the network. If a node has a minimum holding time among its neighbors, it shrinks the holding time and quickly forwards the data packets upstream. The performance of ESEVBF is analyzed through in network scenario with and without node mobility to ensure its effectiveness. Simulation results show that ESEVBF has low energy consumption, reduces forwarded data copies, and less end-to-end delay.

Workflow-Oriented Cyberinfrastructure for Sensor Data Analytics

NASA Astrophysics Data System (ADS)

Orcutt, J. A.; Rajasekar, A.; Moore, R. W.; Vernon, F.

2015-12-01

Sensor streams comprise an increasingly large part of Earth Science data. Analytics based on sensor data require an easy way to perform operations such as acquisition, conversion to physical units, metadata linking, sensor fusion, analysis and visualization on distributed sensor streams. Furthermore, embedding real-time sensor data into scientific workflows is of growing interest. We have implemented a scalable networked architecture that can be used to dynamically access packets of data in a stream from multiple sensors, and perform synthesis and analysis across a distributed network. Our system is based on the integrated Rule Oriented Data System (irods.org), which accesses sensor data from the Antelope Real Time Data System (brtt.com), and provides virtualized access to collections of data streams. We integrate real-time data streaming from different sources, collected for different purposes, on different time and spatial scales, and sensed by different methods. iRODS, noted for its policy-oriented data management, brings to sensor processing features and facilities such as single sign-on, third party access control lists ( ACLs), location transparency, logical resource naming, and server-side modeling capabilities while reducing the burden on sensor network operators. Rich integrated metadata support also makes it straightforward to discover data streams of interest and maintain data provenance. The workflow support in iRODS readily integrates sensor processing into any analytical pipeline. The system is developed as part of the NSF-funded Datanet Federation Consortium (datafed.org). APIs for selecting, opening, reaping and closing sensor streams are provided, along with other helper functions to associate metadata and convert sensor packets into NetCDF and JSON formats. Near real-time sensor data including seismic sensors, environmental sensors, LIDAR and video streams are available through this interface. A system for archiving sensor data and metadata in NetCDF format has been implemented and will be demonstrated at AGU.

Structural Stability Monitoring of a Physical Model Test on an Underground Cavern Group during Deep Excavations Using FBG Sensors.

PubMed

Li, Yong; Wang, Hanpeng; Zhu, Weishen; Li, Shucai; Liu, Jian

2015-08-31

Fiber Bragg Grating (FBG) sensors are comprehensively recognized as a structural stability monitoring device for all kinds of geo-materials by either embedding into or bonding onto the structural entities. The physical model in geotechnical engineering, which could accurately simulate the construction processes and the effects on the stability of underground caverns on the basis of satisfying the similarity principles, is an actual physical entity. Using a physical model test of underground caverns in Shuangjiangkou Hydropower Station, FBG sensors were used to determine how to model the small displacements of some key monitoring points in the large-scale physical model during excavation. In the process of building the test specimen, it is most successful to embed FBG sensors in the physical model through making an opening and adding some quick-set silicon. The experimental results show that the FBG sensor has higher measuring accuracy than other conventional sensors like electrical resistance strain gages and extensometers. The experimental results are also in good agreement with the numerical simulation results. In conclusion, FBG sensors could effectively measure small displacements of monitoring points in the whole process of the physical model test. The experimental results reveal the deformation and failure characteristics of the surrounding rock mass and make some guidance for the in situ engineering construction.

Structural Stability Monitoring of a Physical Model Test on an Underground Cavern Group during Deep Excavations Using FBG Sensors

PubMed Central

Li, Yong; Wang, Hanpeng; Zhu, Weishen; Li, Shucai; Liu, Jian

2015-01-01

Fiber Bragg Grating (FBG) sensors are comprehensively recognized as a structural stability monitoring device for all kinds of geo-materials by either embedding into or bonding onto the structural entities. The physical model in geotechnical engineering, which could accurately simulate the construction processes and the effects on the stability of underground caverns on the basis of satisfying the similarity principles, is an actual physical entity. Using a physical model test of underground caverns in Shuangjiangkou Hydropower Station, FBG sensors were used to determine how to model the small displacements of some key monitoring points in the large-scale physical model during excavation. In the process of building the test specimen, it is most successful to embed FBG sensors in the physical model through making an opening and adding some quick-set silicon. The experimental results show that the FBG sensor has higher measuring accuracy than other conventional sensors like electrical resistance strain gages and extensometers. The experimental results are also in good agreement with the numerical simulation results. In conclusion, FBG sensors could effectively measure small displacements of monitoring points in the whole process of the physical model test. The experimental results reveal the deformation and failure characteristics of the surrounding rock mass and make some guidance for the in situ engineering construction. PMID:26404287