Structural Health Monitoring Inside Concrete and Grout Using the Wireless Identification and Sensing Platform (WISP)

This research investigates the implementation of battery-less RFID sensing platforms inside lossy media, such as, concrete and grout. Both concrete and novel grouts can be used for nuclear plant decommissioning as part of the U.S. Department of Energy’s (DOE’s) cleanup projects. Our research examines the following: (1) material characterization, (2) analytical modeling of transmission and propagation losses inside lossy media, (3) maximum operational range of RFID wireless sensors embedded inside concrete and grout, and (4) best positioning of antennas for achieving longer communication range between RFID antennas and wireless sensors. Our research uses the battery-less Wireless Identification and Sensing Platform (WISP) which can be used to monitor temperature, and humidity inside complex materials. By using a commercial Agilent open-ended coaxial probe (HP8570B), the measurements of the dielectric permittivity of concrete and grout are performed. Subsequently, the measured complex permittivity is used to formulate analytical Debye models. Also, the transmission and propagation losses of a uniform plane wave inside grout are calculated. Our results show that wireless sensors will perform better in concrete than grout. In addition, the maximum axial and radial ranges for WISP are experimentally determined. Our work illustrates the feasibility of battery-less wireless sensors that are embedded inside concrete and grout. Also, our work provides information that can be used to optimize the power management, sampling rate, and antenna design of such sensors.

Using structural equation modeling to assess two theoretical models that explain dropout

This study evaluated the relative fit of both Finn's (1989) Participation-Identification and Wehlage, Rutter, Smith, Lesko and Fernandez's (1989) School Membership models of high school completion to a sample of 4,597 eighth graders taken from the National Educational Longitudinal Study of 1988, (NELS:88), utilizing structural equation modeling techniques. This study found support for the importance of educational engagement as a factor in understanding academic achievement. The Participation-Identification model was particularly well fitting when applied to the sample of high school completers, dropouts (both overall and White dropouts) and African-American students. This study also confirmed the contribution of school environmental factors (i.e., size, diversity of economic and ethnic status among students) and family resources (i.e., availability of learning resources in the home and parent educational level) to students' educational engagement. Based on these findings, school social workers will need to be more attentive to utilizing macro-level interventions (i.e., community organization, interagency coordination) to achieve the organizational restructuring needed to address future challenges. The support found for the Participation-Identification model supports a shift in school social workers' attention from reactive attempts to improve the affective-interpersonal lives of students to proactive attention to their academic lives. The model concentrates school social work practices on the central mission of schools, which is educational engagement. School social workers guided by this model would be encouraged to seek changes in school policies and organization that would facilitate educational engagement. ^

Chilling damage in a changing climate in coastal landscapes of the subtropical zone: a case study from south Florida

Freeze events significantly influence landscape structure and community composition along subtropical coastlines. This is particularly true in south Florida, where such disturbances have historically contributed to patch diversity within the mangrove forest, and have played a part in limiting its inland transgression. With projected increases in mean global temperatures, such instances are likely to become much less frequent in the region, contributing to a reduction in heterogeneity within the mangrove forest itself. To understand the process more clearly, we explored the dynamics of a Dwarf mangrove forest following two chilling events that produced freeze-like symptoms, i.e., leaf browning, desiccation, and mortality, and interpreted the resulting changes within the context of current winter temperatures and projected future scenarios. Structural effects from a 1996 chilling event were dramatic, with mortality and tissue damage concentrated among individuals comprising the Dwarf forest's low canopy. This disturbance promoted understory plant development and provided an opportunity for Laguncularia racemosa to share dominance with Rhizophora mangle. Mortality due to the less severe 2001 event was greatest in the understory, probably because recovery of the protective canopy following the earlier freeze was still incomplete. Stand dynamics were static over the same period in nearby unimpacted sites. The probability of reaching temperatures as low as those recorded at a nearby meteorological station (≤3 °C) under several warming scenarios was simulated by applying 1° incremental temperature increases to a model developed from a 42-year temperature record. According to the model, the frequency of similar chilling events decreased from once every 1.9 years at present to once every 3.4 and 32.5 years with 1 and 4 °C warming, respectively. The large decrease in the frequency of these events would eliminate an important mechanism that maintains Dwarf forest structure, and promotes compositional diversity.

Structural Data Acquisition Using Sensor Network

The development cost of any civil infrastructure is very high; during its life span, the civil structure undergoes a lot of physical loads and environmental effects which damage the structure. Failing to identify this damage at an early stage may result in severe property loss and may become a potential threat to people and the environment. Thus, there is a need to develop effective damage detection techniques to ensure the safety and integrity of the structure. One of the Structural Health Monitoring methods to evaluate a structure is by using statistical analysis. In this study, a civil structure measuring 8 feet in length, 3 feet in diameter, embedded with thermocouple sensors at 4 different levels is analyzed under controlled and variable conditions. With the help of statistical analysis, possible damage to the structure was analyzed. The analysis could detect the structural defects at various levels of the structure.