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3. Hawk Falls Bridge, Beaver County, Pennsylvania (for monitoring stresses in truss members). 4. George Washington Bridge, NJ, managed by Port Authority of New York and New Jersey (use of magnetostrictive sensor technology). The integration of an RHM system with a nite element model de nes it as a smart bridge and empowers the client to make objective asset management decisions based on actual bridge performance. The case study of a smart bridge is presented: 1. Case Study of Hawk Falls Bridge located in Beaver County, PA: This is a continuous, 680foot-long, riveted steel deck truss structure built in the 1950s is owned by the Pennsylvania Turnpike Commission. To compliment this data, a 3-D nite element model (FEM) of the structure using MIDAS/Civil (Modeling, Integrated Design and Analysis Software for Civil Structures), a general purpose nite element software developed by MIDAS Information Technology Co., was used. Validation of the FEM model using the data from these sensors ensures accuracy in the analytical assessment of other bridge members. The performance of any component of the bridge can be modeled in detail and evaluated objectively. Coupling of the RHM system data stream with the FEM model resulted in Pennsylvania s rst smart bridge. Smart bridge technology can improve the way bridges are designed, evaluated, and maintained. Stress wave timer: This NDT method offers the ability to determine the presence of internal decay in bridge members. It is especially useful for glulam or thick timbers where hammer sounding is not effective. Timber testing resistograph: This instrument drills a small 1-mm diameter hole in wood and it measures resistance output on wax paper. Decayed wood offers less resistance. A more expensive model offers PDF le output. Sound wave re ector: Impact generated sound waves are applicable to concrete and masonry. Impact waves that propagate through the structure are re ected by internal aws and external surfaces. A piezoelectric crystal in a transducer produces a voltage proportional to displacement. This method can be used to determine the location and extent of cracks, delaminations, voids, honey combing, and debonding in reinforced and prestressed concrete. 2. Case study of smart bridge technology on I-35W replacement bridge, Minneapolis: The failure of the bridge (presumably due to failure of gusset plates and from additional dead load of storage material for resurfacing) cost almost $250 million. But the silver lining is the use of redundant steel girders and smart bridge technology to detect small problems before they turn into big problems in the future. A system of over 300 sensors and cameras providing traf c data including speeds, accidents, stalls, and traf c jams are embedded in concrete to generate an extensive record of heavy moving traf c and extreme Minnesota climatic conditions. In addition, some sensors will be used to prevent icing of the bridge deck. Additional sensors act as security sensors. During construction, sensors were placed in fresh concrete to monitor the curing process. Additional technology used on the new bridge includes: Strain gauges to detect stress changes Accelerometers for vibration study Linear potentiometers at expansion joints and bearings to measure how the bridge expands and contracts Chloride penetration sensors in the bridge deck for corrosion study from deicing salts. Sacri cial steel bars are placed at different depths to see the degree of corrosion and the need for deck replacement. The data will feed into a bank of computers in a control room near the bridge and will be recorded and downloaded for analysis.
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Hand geometry systems provide improved security, accuracy, and convenience for many applications such as access control, time and attendance, metering the use of a resource, and facilitating border control. Some typical applications are discussed next, while s 16 and 18 also provide examples of hand geometry use.
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n extremely important event occurred in the lifecycle of C# when version 2.0 was released. This was the addition of generics. Not only did generics add a new syntactic element to C#, it also resulted in many changes and upgrades to the .NET library. Although it has been a few years since generics were added, its effects still reverberate throughout C# 3.0. Generics have become an indispensable part of C# programming. The generics feature makes it possible to create classes, interfaces, methods, and delegates that work in a type-safe manner with various kinds of data. As you may know, many algorithms are logically the same, no matter what type of data they are being applied to. For example, the mechanism that supports a queue is the same whether the queue is storing items of type int, string, object, or a user-defined class. Prior to generics, you might have created several different versions of the same algorithm to handle different types of data. Through the use of generics, you can define a solution once, independently of any specific type of data, and then apply that solution to a wide variety of data types without any additional effort. Before beginning, it is necessary to state that the generics feature is one of C# s most sophisticated and, at times, most complicated. Furthermore, the topic of generics is quite large. It is not possible in this beginner s guide to detail all aspects of this powerful subsystem. Instead, this chapter introduces the theory behind generics, describes its syntax, and then shows several examples that put it into action. After completing this chapter, you will be able to begin writing your own generic code and make use of the generic features in the .NET library. You will also have the knowledge needed to move on to its more advanced features.
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