Structural monitoring-the collection and analysis of structural response to ambient or forced excitation-is an important application of networked embedded sensing with significant commercial potential. The first generation of sensor networks for structural monitoring are likely to be data acquisition systems that collect data at a single node for centralized processing. In this paper, we discuss the design and evaluation of a wireless sensor network system (called Wisden) for structural data acquisition. Wisden incorporates two novel mechanisms, reliable data transport using a hybrid of end-to-end and hop-by-hop recovery, and low-overhead data time-stamping that does not require global clock synchronization. We also study the applicability of wavelet-based compression techniques to overcome the bandwidth limitations imposed by lowpower wireless radios. We describe our implementation of these mechanisms on the Mica-2 motes and evaluate the performance of our implementation. We also report experiences from deploying Wisden on a large structure.

Particle size distributions of light-duty vehicle brake wear debris are reported with careful attention paid to avoid sampling biases. Electrical low-pressure impactor and micro-orifice uniform deposit impactor measurements yield consistent size distributions, and the net particulate matter mass from each method is in good agreement with gravimetric filter measurements. The mass mean diameter of wear debris from braking events representative of urban driving is 6 microm, and the number-weighted mean is 1-2 microm for three currently used classes of lining materials: low metallic, semimetallic, and non-asbestos organic (NAO). In contrast, the wear rates are very material dependent, both in number and mass of particles, with 3-4 times higher emissions observed from the low metallic linings as compared to the semimetallic and NAO linings. Wind tunnel and test track measurements demonstrate the appearance of micron size particles that correlate with braking events, with approximately 50% of the wear debris being airborne for the test vehicle in this study. Elemental analysis of the wear debris reveals a consistent presence of the elements Fe, Cu, and Ba in both dynamometer and test track samples.

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Wind tunnel measurements and direct tailpipe particulate matter (PM) sampling are utilized to examine how the combination of oxidation catalyst and fuel sulfur content affects the nature and quantity of PM emissions from the exhaust of a light duty diesel truck. When low sulfur fuel (4 ppm) is used, or when high sulfur (350 ppm)fuel is employed without an active catalyst present, a single log-normal distribution of exhaust particles is observed with a number mean diameter in the range of 70-83 nm. In the absence of the oxidation catalyst, the high sulfur level has at most a modest effect on particle emissions (<50%) and a minor effect on particle size (<5%). In combination with the active oxidation catalyst tested, high sulfur fuel can lead to a second, nanoparticle, mode, which appears at approximately 20 nm during high speed operation (70 mph), but is not present at low speed (40 mph). A thermodenuder significantly reduces the nanoparticle mode when set to temperatures above approximately 200 degrees C, suggesting that these particles are semivolatile in nature. Because they are observed only when the catalyst is present and the sulfur level is high, this mode likely originates from the nucleation of sulfates formed over the catalyst, although the composition may also include hydrocarbons.