This paper describes a radiation source that can be used to actively interrogate containers, trucks, trains, cars, etc to determine the presence and location of chemical explosives and special nuclear materials such as uranium and plutonium. Active interrogation methods using high energy photon or neutron sources to induce fission are the only feasible option for detection of highly enriched uranium (HEU) because passive detection methods are easily compromised by even moderate amounts of shielding. For detection of chemical explosives, the same active interrogation device can be used to produce resonant photons that can detect nitrogen that is used in most chemical explosives. The accelerator based system described here produces a penetrating beam of high energy photons or neutrons that can "see" inside a sealed container. If chemical explosives or special nuclear materials are present, they will emit a characteristic signal that is detected and interpreted by electronic sensors. Shielded “dirty bombs” can be detected by the attenuation of high energy photons caused by the density of the shield material. The interrogating source of radiation is based upon a new high current negative ion source and high current tandem accelerator. The accelerator accelerates ions and projects them onto an appropriately designed target. The target converts the energy of the ion beam into a high energy highly penetrating photon or neutron beam. The beam is made to pass through the container. If explosives, special nuclear materials or shielded dirty bombs are present, the beam together with a suitable detection system uniquely identifies the location, amount and density of material.
This paper describes the basic configuration for a visual identification system (VIS) for Homeland Security and law enforcement support. Security and law enforcement systems with an integrated VIS will accurately and rapidly provide identification of vehicles or containers that have entered, exited or passed through a specific monitoring location. The VIS system stores all images and makes them available for recall for approximately one week. Images of alarming vehicles will be archived indefinitely as part of the alarming vehicle’s or cargo container’s record. Depending on user needs, the digital imaging information will be provided electronically to the individual inspectors, supervisors, and/or control center at the customer’s office. The key components of the VIS are the high-resolution cameras that capture images of vehicles, lights, presence sensors, image cataloging software, and image recognition software. In addition to the cameras, the physical integration and network communications of the VIS components with the balance of the security system and client must be ensured.
Little is known about the neurological underpinnings of deliberate deception. Recent advances in the detection of deception have examined brain responses during experimental deception protocols. A consensus has begun to emerge across the handful of functional magnetic resonance imaging (fMRI) studies that have examined deception implicating areas of the dorsolateral and inferior prefrontal cortex as active during deliberate deception. The purpose of the current study was to determine the utility of functional near-infrared spectroscopy (fNIR), a neuroimaging technique that allows reasonable ecological utility, for the detection of deception. Using a modified version of the Guilty Knowledge Task, participants attempted to conceal the identity of a playing card they were holding while dorsolateral and inferior frontal cortices were monitored with fNIR. The results revealed increased activation in bilateral inferior frontal gyri (BA 47/45) and middle frontal gyri (BA 46/10) when participants were lying. The results provide evidence that inferior and middle prefrontal cortical areas are associated at least some forms of deliberate deception. fNIR has the potential to provide a field-deployable brain-based method for the detection of deception.
U.S. Customs and Border Protection (CBP) is the primary enforcement agency protecting the nation’s ports of entry. CBP is enhancing its capability to interdict the illicit import of nuclear and radiological materials and devices that may be used by terrorists. Pacific Northwest National Laboratory (PNNL) is providing scientific and technical support to CBP in their goal to enable rapid deployment of nuclear and radiation detection systems at U. S. ports of entry to monitor 100% of the incoming international traffic and cargo while not adversely impacting the operations or throughput of the ports. The U.S. ports of entry include the following vectors: land border crossings, seaports, airports, rail crossings, and mail and express consignment courier facilities.
U.S. Customs and Border Protection (CBP) determined that a screening solution was needed for Seaport cargo containers being transported by Straddle Carriers (straddle carriers). A stationary Radiation Portal Monitor (RPM) for Straddle Carriers (SCRPM) is needed so that cargo containers can be scanned while in transit under a Straddle Carrier. The Straddle Carrier Portal operational impacts were minimized by conducting a time-motion study at the Port, and adaptation of a Remotely Operated RPM (RO-RPM) booth concept that uses logical lighting schemes for traffic control, cameras, Optical Character Recognition, and wireless technology.
U.S. Customs and Border Protection (CBP) is the primary enforcement agency protecting the nation’s ports of entry. CBP is enhancing its capability to interdict the illicit import of nuclear and radiological materials and devices that may be used by terrorists. Pacific Northwest National Laboratory (PNNL) is providing scientific and technical support to CBP in their goal to enable rapid deployment of nuclear and radiation detection systems at U. S. ports of entry to monitor 100% of the incoming international traffic and cargo while not adversely impacting the operations or throughput of the ports.
As the deployment of radiation detection systems proceeds, there is a need to adapt the baseline radiation portal monitor (RPM) system technology to operations at these diverse ports of entry. When screening produces an alarm in the primary inspection RPM, the alarming vehicle is removed from the flow of commerce and the alarm is typically confirmed in a secondary inspection RPM. The portable source identification device (PSID) is a radiation sensor panel (RSP), based on thallium-doped sodium iodide (NaI(Tl)) scintillation detector and gamma spectroscopic analysis hardware and software, mounted on a scissor lift on a small truck. The lift supports a box containing a commercial off-the-shelf (COTS) sodium iodide detector that provides real-time isotopic identification, including neutron detectors to interdict Weapons of Mass Destruction (WMD) and radiation dispersion devices (RDD). The scissor lift will lower the detectors to within a foot off the ground and raise them to approximately 24 feet (7.3 m) in the air, allowing a wide vertical scanning range.
This paper presents an integrated sensor network and distributed event processing architecture for managed in-building traffic evacuation during natural and human-caused disasters, including earthquakes, fire and biological/chemical terrorist attacks. The proposed wireless sensor network protocols and distributed event processing mechanisms offer a new distributed paradigm for improving reliability in building evacuation and disaster management. The networking component of the system is constructed using distributed wireless sensors for measuring environmental parameters such as temperature, humidity, and detecting unusual events such as smoke, structural failures, vibration, biological/chemical or nuclear agents. Distributed event processing algorithms will be executed by these sensor nodes to detect the propagation pattern of the disaster and to measure the concentration and activity of human traffic in different parts of the building. Based on this information, dynamic evacuation decisions are taken for maximizing the evacuation speed and minimizing unwanted incidents such as human exposure to harmful agents and stampedes near exits. A set of audio-visual indicators and actuators are used for aiding the automated evacuation process. In this paper we develop integrated protocols, algorithms and their simulation models for the proposed sensor networking and the distributed event processing framework. Also, efficient harnessing of the individually low, but collectively massive, processing abilities of the sensor nodes is a powerful concept behind our proposed distributed event processing algorithms. Results obtained through simulation in this paper are used for a detailed characterization of the proposed evacuation management system and its associated algorithmic components.
Recent security lapses within the Department of Energy laboratories prompted the establishment and implementation of additional procedures and training for operations involving classified removable electronic media (CREM) storage. In addition, the definition of CREM has been expanded and the number of CREM has increased significantly. Procedures now require that all CREM be inventoried and accounted for on a weekly basis. Weekly inventories consist of a physical comparison of each item against the reportable inventory listing. Securing and accounting for CREM is a continuous challenge for existing security systems. To address this challenge, an innovative framework, encompassing a suite of technologies, has been developed by Pacific Northwest National Laboratory (PNNL) to monitor, track, and locate CREM in safes, vaults, and storage areas. This Automated Removable Media Observation and Reporting (ARMOR)framework, described in this paper, is an extension of an existing PNNL program, SecureSafe. The key attributes of systems built around the ARMOR framework include improved accountability, reduced risk of human error, improved accuracy and timeliness of inventory data, and reduced costs. ARMOR solutions require each CREM to be tagged with a unique electronically readable ID code. Inventory data is collected from tagged CREM at regular intervals and upon detection of an access event. Automated inventory collection and report generation eliminates the need for hand-written inventory sheets and allows electronic transfer of the collected inventory data to a modern electronic reporting system. An electronic log of CREM access events is maintained, providing enhanced accountability for daily/weekly checks, routine audits, and follow-up investigations.
DuraNode is a sensing system designed for structural monitoring. It can detect the damage of structural members, provide crucial intelligence information of structural integrity and activate emergency response mechanism in the initial stages of a disaster. The sensor encompasses three MEMS-type accelerometers (SD-1221) and Wi-Fi (802.11b) communication adapter. It operates on solar power and rechargeable battery making it last for long term service without battery replacement. DuraNodes can be deployed in the form of a dense wireless network to enable seamless acquisition of structural intelligence in a complex structural system. A preliminary data acquisition and signal display module with graphic user interface (GUI) has been developed for connection of access points in ad-hoc networking. To validate the performance of DuraNode in structural monitoring applications, experiments were conducted on measuring vibration of a Pedestrian bridge in UC, Irvine, and a two-column bridge bent specimen with a Shake-table test in University of Neveda, Reno. Results were compared with that from conventional wired sensors and showed that DuraNode is cost-effective for carrying out robust sensing functions in the structural safety monitoring missions.
Condition evaluation of large constructed structures has been widely researched over the last decade. In numerous studies dynamic testing has been used as the primary experimentation tool for measuring the dynamic characteristics and extracting various proposed indicators of structural condition. Despite these efforts, dynamic testing of constructed systems has not yet evolved to a point that it can be standardized as a tool for condition evaluation. Writers believe that two major sources of uncertainty in dynamic test based condition evaluation are the reasons for the gap between concepts and meaningful real-life applications. Most dynamic test methods are built on principles of observability, linearity and stationarity. The first major source of uncertainty is due to constructed systems and their loading environments’ inherent complexity leading to limitations in the application of the above tenets. The second category of uncertainty is related to the experiment, i.e. sensing, data acquisition, processing and analysis for different dynamic test methods. Ambient vibration (i.e. operational modal analysis) and impact testing are two different tools aiming to identify same parameters. Comparative evaluation of different test methods at the presence of different levels of uncertainty will enable us to assess the reliability of dynamic testing tools for condition evaluation. Writers designed a set of experiments on a laboratory physical model to investigate the effects of these two groups of uncertainties on modal parameter identification. Results will be discussed along with mitigation measures of uncertainties in dynamic testing of constructed systems.
Fatigue crack propagation tests of magnesium alloy were conducted under conditions of biaxial and uniaxial loading by using a cruciform specimen in a biaxial fatigue machine, in order to investigate the effect of non-singular stress cycling on the fatigue crack growth properties ΔKI -da/dN. The Magnesium alloys (AZ31B-O) used for this research are 2.5mm thickness plates. There are four different kinds of plates due to their heat treatment conditions. These conditions are (a) with no heat treatments (AZ31B-O), (b) 200-degree 2 hours (AZ31B-200), (c) 350-degree 2 hours (AZ31B-350), and (d) 430-degree 2 hours (AZ31B-430). From these comprehensive experiments, the remarkable effect was found in the specific biaxial load stress ratio σx0/σy0 on ΔKI -da/dN relation. When biaxial load stress ratio was 0.5, it turned out that the fatigue crack propagation rate of a magnesium alloy becomes very slow. Of course, in other biaxial load stress ratios, fatigue crack propagation velocity was influenced to some extent. It turned out that fatigue crack propagation rate becomes fast when a biaxial load stress ratio is minus, and it becomes slow when a biaxial load stress ratio is plus. Some discussion is made on the effect of microstructure on fatigue crack propagation of magnesium alloy in a biaxial stress field.
The purpose of this paper is to present an overview of experimental structural dynamics as a unique technology for global health monitoring of large structures. Assessment of damage and objective condition evaluation of existing civil infrastructure systems (CIS) are important needs for making decisions during regular operation as well as before and after disasters. Objective condition assessment is also a fundamental knowledge need for successful health monitoring of
CIS. In this paper, the writers discuss promises as well as the challenges for dynamic measurements, and the use of modal flexibility matrices for condition assessment when dynamic methods are applied on large structures. They present snapshots from their past and current studies where dynamic tests were implemented on medium and long span bridges
Structural condition assessment of highway bridges has long been relying on visual inspection, which, however, involves subjective judgment of the inspector and detects only local flaws. Local flaws might not affect the global performance of the bridge. By instrumenting bridges with accelerometers and other sensors, one is able to monitor ambient or forced vibration of the bridge and assess its global structural condition. Ambient vibration measurement outwits forced vibration measurement in that it requires no special test arrangement, such as traffic control or a heavy shaker. As a result, it can be continuously executed while the bridge is under its normal serving condition. For short-to mid-span highway bridges, ambient vibration is predominantly due to traffic excitation, inducing the bridge to vibrate mainly in vertical direction. Based on its physical nature, traffic excitation is modeled as moving loads from the passing vehicles whose arrivals and speeds are extracted from digital video. Traffic-induced vibration provides valuable information for assessing the health of super-structure, but is less sensitive to possible seismic damage in the sub-structure. During earthquakes, bridges are excited in all directions by short-duration un-stationary ground motion, and are expected to better reveal their sub-structure integrity. Therefore, traffic-induced and ground-motion-induced ambient vibration data are treated separately in this paper for different assessment objectives, because of the different characteristics and measurability of the excitation. By continuously monitoring the ambient vibration of the instrumented bridge, its global structural conditions of both super- and sub-structures can be evaluated with possible damage locations identified, which will aid local non-destructive evaluation or visual inspection to further localize and access the damage.
Damage location and damage state identification of a hybrid Carbon-glass FRP rod was performed by means of a serially multiplexed fiber optic acoustic emission sensor. The detection and identification of acoustic emission signals along a single data stream reduces the data acquisition rigor and provides for rapid real time damage location detection in materials. Linear source location method and signature frequency spectra energy of acoustic emission signals were employed for locating the fiber breakage and distinguishing the damage state in the hybrid FRP rod, respectively.
Bad things often happen fast. This means that we need to react fast. In this work, we develop the technology that allows one to identify and characterize fast events. In real time, we dynamically process hyperspectral information of a scene, specifically analyzing its temporal behavior. The goal is to detect fast and super-fast events like explosions, fast-moving objects and instant changes in the chemical composition of air and other materials. Until recently, the enormous quantity of hyperspectral information confined us to static hyperspectral data processing. Hyperspectral techniques were used for finding certain objects, chemicals, or anomalies in a picture, frame by frame, statically. Dynamic (temporal) analysis was developed primarily for astrophysical applications performed a long time after the frames had been captured. In this work, we study ways of taking advantage of emerging hardware technologies that allow one to look at hyperspectral information dynamically: by characterizing temporal changes as they occur. We apply methods from astrophysics (supernova observations) and present our unique algorithms for contemporaneous dynamical analysis of hyperspectral data. The application addresses the question: have there been any sudden changes in the hyperspectral pattern of a scene? If there were sudden changes, were those changes related to a substantial energy release? These questions do not depend on assumptions about specific spectral patterns, chemical composition, or shapes: we look for any changes in a scene. Such dynamical analysis can therefore allow one to react promptly to fast events without prior knowledge about what occurred. This paper addresses issues specific to dynamic (as opposed to static) hyperspectral imaging, algorithmic approaches to dynamic hyperspectral data processing, and associated hardware-implementation issues.
Nano-coatings with adjustable optical features is one of the revolutionary technologies of today. In this work, we investigate how hyperspectral imaging can detect adjustable nano-surfaces used, for example, for active camouflage. The distinct attributes of the nano-coating spectra are discussed. Fast algorithms of utilizing hyperspectral information for recognizing these attributes are suggested. The research applies to both recognizing the camouflaged objects and to building unrecognizable camouflage technology. In the context of tracking active camouflage, the identification of
characteristic spectral attributes is especially important. Active spectra can constantly change, therefore confusing traditional hyperspectral classification. In contrast, the identified general spectral attributes stay the same allowing for robust identification and reliable tracking of the camouflaged objects.
Leaking valves, connections and distribution pipelines are significant sources of fugitive gas and volatile chemical
emissions in chemical manufacturing, gas production, transmission, and oil refineries. A gas leak detection method has been developed based on continuous monitoring of the oxygen concentration surrounding a natural gas pipeline. The method utilizes optical fibers coated with an oxygen permeable polymeric film containing a luminescent sensor molecule. When the specialty fiber is illuminated by a light source that excites the luminophor, the functional
cladding compound has the ability to detect and quantify leaks by measuring small changes in oxygen concentrations in the surrounding environment. Key features of the technology include long-term performance based on well understood platinum porphyrin chemistry, in addition to the capability of distributed sensing using fiber optic
evanescent field spectroscopy. Results of leak detection in various environments namely atmospheric conditions, dry sand as well as saturated sand is reported, along with test results on long term system performance.
This paper discusses the conceptual development of a continuously monitored intelligent system for underground infrastructure. The proposed sensors are based on advanced coupling and refinement of several technologies: electrically conducting composite pipe (ECCP), electrochemical impedance spectroscopy (EIS) and time domain reflectometry (TDR). A significant benefit gleaned from the combination of these technologies is that the resulting system may be used on non-metallic, as well as, metallic pipes. In addition, the synergism of the technologies obtains the maximum information regarding defect location and characterization. The monitoring signal, waveguides, and damage sensor are also discussed, as well as, the data fusion, dynamic modeling and simulation requirements for the intelligent monitoring system.