Optimization of wireless power transfer via magnetic resonance in different media

A wide range of non-destructive testing (NDT) methods for the monitoring the health of concrete structure has been studied for several years. The recent rapid evolution of wireless sensor network (WSN) technologies has resulted in the development of sensing elements that can be embedded in concrete, to monitor the health of infrastructure, collect and report valuable related data. The monitoring system can potentially decrease the high installation time and reduce maintenance cost associated with wired monitoring systems. The monitoring sensors need to operate for a long period of time, but sensors batteries have a finite life span. Hence, novel wireless powering methods must be devised. The optimization of wireless power transfer via Strongly Coupled Magnetic Resonance (SCMR) to sensors embedded in concrete is studied here. First, we analytically derive the optimal geometric parameters for transmission of power in the air. This specifically leads to the identification of the local and global optimization parameters and conditions, it was validated through electromagnetic simulations. Second, the optimum conditions were employed in the model for propagation of energy through plain and reinforced concrete at different humidity conditions, and frequencies with extended Debye's model. This analysis leads to the conclusion that SCMR can be used to efficiently power sensors in plain and reinforced concrete at different humidity levels and depth, also validated through electromagnetic simulations. The optimization of wireless power transmission via SMCR to Wearable and Implantable Medical Device (WIMD) are also explored. The optimum conditions from the analytics were used in the model for propagation of energy through different human tissues. This analysis shows that SCMR can be used to efficiently transfer power to sensors in human tissue without overheating through electromagnetic simulations, as excessive power might result in overheating of the tissue. Standard SCMR is sensitive to misalignment; both 2-loops and 3-loops SCMR with misalignment-insensitive performances are presented. The power transfer efficiencies above 50% was achieved over the complete misalignment range of 0°-90° and dramatically better than typical SCMR with efficiencies less than 10% in extreme misalignment topologies.

A model for continuous measurement of drilled shaft diameter during construction

Non-Destructive Testing (NDT) of deep foundations has become an integral part of the industry's standard manufacturing processes. It is not unusual for the evaluation of the integrity of the concrete to include the measurement of ultrasonic wave speeds. Numerous methods have been proposed that use the propagation speed of ultrasonic waves to check the integrity of concrete for drilled shaft foundations. All such methods evaluate the integrity of the concrete inside the cage and between the access tubes. The integrity of the concrete outside the cage remains to be considered to determine the location of the border between the concrete and the soil in order to obtain the diameter of the drilled shaft. It is also economic to devise a methodology to obtain the diameter of the drilled shaft using the Cross-Hole Sonic Logging system (CSL). Performing such a methodology using the CSL and following the CSL tests is performed and used to check the integrity of the inside concrete, thus allowing the determination of the drilled shaft diameter without having to set up another NDT device.^ This proposed new method is based on the installation of galvanized tubes outside the shaft across from each inside tube, and performing the CSL test between the inside and outside tubes. From the performed experimental work a model is developed to evaluate the relationship between the thickness of concrete and the ultrasonic wave properties using signal processing. The experimental results show that there is a direct correlation between concrete thicknesses outside the cage and maximum amplitude of the received signal obtained from frequency domain data. This study demonstrates how this new method to measuring the diameter of drilled shafts during construction using a NDT method overcomes the limitations of currently-used methods. ^ In the other part of study, a new method is proposed to visualize and quantify the extent and location of the defects. It is based on a color change in the frequency amplitude of the signal recorded by the receiver probe in the location of defects and it is called Frequency Tomography Analysis (FTA). Time-domain data is transferred to frequency-domain data of the signals propagated between tubes using Fast Fourier Transform (FFT). Then, distribution of the FTA will be evaluated. This method is employed after CSL has determined the high probability of an anomaly in a given area and is applied to improve location accuracy and to further characterize the feature. The technique has a very good resolution and clarifies the exact depth location of any void or defect through the length of the drilled shaft for the voids inside the cage. ^ The last part of study also evaluates the effect of voids inside and outside the reinforcement cage and corrosion in the longitudinal bars on the strength and axial load capacity of drilled shafts. The objective is to quantify the extent of loss in axial strength and stiffness of drilled shafts due to presence of different types of symmetric voids and corrosion throughout their lengths.^

Optimization of Wireless Power Transfer via Magnetic Resonance in Different Media

A wide range of non-destructive testing (NDT) methods for the monitoring the health of concrete structure has been studied for several years. The recent rapid evolution of wireless sensor network (WSN) technologies has resulted in the development of sensing elements that can be embedded in concrete, to monitor the health of infrastructure, collect and report valuable related data. The monitoring system can potentially decrease the high installation time and reduce maintenance cost associated with wired monitoring systems. The monitoring sensors need to operate for a long period of time, but sensors batteries have a finite life span. Hence, novel wireless powering methods must be devised. The optimization of wireless power transfer via Strongly Coupled Magnetic Resonance (SCMR) to sensors embedded in concrete is studied here. First, we analytically derive the optimal geometric parameters for transmission of power in the air. This specifically leads to the identification of the local and global optimization parameters and conditions, it was validated through electromagnetic simulations. Second, the optimum conditions were employed in the model for propagation of energy through plain and reinforced concrete at different humidity conditions, and frequencies with extended Debye's model. This analysis leads to the conclusion that SCMR can be used to efficiently power sensors in plain and reinforced concrete at different humidity levels and depth, also validated through electromagnetic simulations. The optimization of wireless power transmission via SMCR to Wearable and Implantable Medical Device (WIMD) are also explored. The optimum conditions from the analytics were used in the model for propagation of energy through different human tissues. This analysis shows that SCMR can be used to efficiently transfer power to sensors in human tissue without overheating through electromagnetic simulations, as excessive power might result in overheating of the tissue. Standard SCMR is sensitive to misalignment; both 2-loops and 3-loops SCMR with misalignment-insensitive performances are presented. The power transfer efficiencies above 50% was achieved over the complete misalignment range of 0°-90° and dramatically better than typical SCMR with efficiencies less than 10% in extreme misalignment topologies.

A Model for Continuous Measurement of Drilled Shaft Diameter During Construction

Non-Destructive Testing (NDT) of deep foundations has become an integral part of the industry’s standard manufacturing processes. It is not unusual for the evaluation of the integrity of the concrete to include the measurement of ultrasonic wave speeds. Numerous methods have been proposed that use the propagation speed of ultrasonic waves to check the integrity of concrete for drilled shaft foundations. All such methods evaluate the integrity of the concrete inside the cage and between the access tubes. The integrity of the concrete outside the cage remains to be considered to determine the location of the border between the concrete and the soil in order to obtain the diameter of the drilled shaft. It is also economic to devise a methodology to obtain the diameter of the drilled shaft using the Cross-Hole Sonic Logging system (CSL). Performing such a methodology using the CSL and following the CSL tests is performed and used to check the integrity of the inside concrete, thus allowing the determination of the drilled shaft diameter without having to set up another NDT device. This proposed new method is based on the installation of galvanized tubes outside the shaft across from each inside tube, and performing the CSL test between the inside and outside tubes. From the performed experimental work a model is developed to evaluate the relationship between the thickness of concrete and the ultrasonic wave properties using signal processing. The experimental results show that there is a direct correlation between concrete thicknesses outside the cage and maximum amplitude of the received signal obtained from frequency domain data. This study demonstrates how this new method to measuring the diameter of drilled shafts during construction using a NDT method overcomes the limitations of currently-used methods. In the other part of study, a new method is proposed to visualize and quantify the extent and location of the defects. It is based on a color change in the frequency amplitude of the signal recorded by the receiver probe in the location of defects and it is called Frequency Tomography Analysis (FTA). Time-domain data is transferred to frequency-domain data of the signals propagated between tubes using Fast Fourier Transform (FFT). Then, distribution of the FTA will be evaluated. This method is employed after CSL has determined the high probability of an anomaly in a given area and is applied to improve location accuracy and to further characterize the feature. The technique has a very good resolution and clarifies the exact depth location of any void or defect through the length of the drilled shaft for the voids inside the cage. The last part of study also evaluates the effect of voids inside and outside the reinforcement cage and corrosion in the longitudinal bars on the strength and axial load capacity of drilled shafts. The objective is to quantify the extent of loss in axial strength and stiffness of drilled shafts due to presence of different types of symmetric voids and corrosion throughout their lengths.

Stereotype threat and the standardized testing experiences of African American children at an urban elementary school

Stereotype threat (Steele & Aronson, 1995) refers to the risk of confirming a negative stereotype about one’s group in a particular performance domain. The theory assumes that performance in the stereotyped domain is most negatively affected when individuals are more highly identified with the domain in question. As federal law has increased the importance of standardized testing at the elementary level, it can be reasonably hypothesized that the standardized test performance of African American children will be depressed when they are aware of negative societal stereotypes about the academic competence of African Americans. This sequential mixed-methods study investigated whether the standardized testing experiences of African American children in an urban elementary school are related to their level of stereotype awareness. The quantitative phase utilized data from 198 African American children at an urban elementary school. Both ex-post facto and experimental designs were employed. Experimental conditions were diagnostic and non-diagnostic testing experiences. The qualitative phase utilized data from a series of six focus group interviews conducted with a purposefully selected group of 4 African American children. The interview data were supplemented with data from 30 hours of classroom observations. Quantitative findings indicated that the stereotype threat condition evoked by diagnostic testing depresses the reading test performance of stereotype-aware African American children (F[1, 194] = 2.21, p < .01). This was particularly true of students who are most highly domain-identified with reading (F[1, 91] = 19.18, p < .01). Moreover, findings indicated that only stereotype-aware African American children who were highly domain-identified were more likely to experience anxiety in the diagnostic condition (F[1, 91] = 5.97, p < .025). Qualitative findings revealed 4 themes regarding how African American children perceive and experience the factors related to stereotype threat: (1) a narrow perception of education as strictly test preparation, (2) feelings of stress and anxiety related to the state test, (3) concern with what “others” think (racial salience), and (4) stereotypes. A new conceptual model for stereotype threat is presented, and future directions including implications for practice and policy are discussed.

Stereotype Threat and the Standardized Testing Experiences of African American Children at an Urban Elementary School

Stereotype threat (Steele & Aronson, 1995) refers to the risk of confirming a negative stereotype about one’s group in a particular performance domain. The theory assumes that performance in the stereotyped domain is most negatively affected when individuals are more highly identified with the domain in question. As federal law has increased the importance of standardized testing at the elementary level, it can be reasonably hypothesized that the standardized test performance of African American children will be depressed when they are aware of negative societal stereotypes about the academic competence of African Americans. This sequential mixed-methods study investigated whether the standardized testing experiences of African American children in an urban elementary school are related to their level of stereotype awareness. The quantitative phase utilized data from 198 African American children at an urban elementary school. Both ex-post facto and experimental designs were employed. Experimental conditions were diagnostic and non-diagnostic testing experiences. The qualitative phase utilized data from a series of six focus group interviews conducted with a purposefully selected group of 4 African American children. The interview data were supplemented with data from 30 hours of classroom observations. Quantitative findings indicated that the stereotype threat condition evoked by diagnostic testing depresses the reading test performance of stereotype-aware African American children (F[1, 194] = 2.21, p < .01). This was particularly true of students who are most highly domain-identified with reading (F[1, 91] = 19.18, p < .01). Moreover, findings indicated that only stereotype-aware African American children who were highly domain-identified were more likely to experience anxiety in the diagnostic condition (F[1, 91] = 5.97, p < .025). Qualitative findings revealed 4 themes regarding how African American children perceive and experience the factors related to stereotype threat: (1) a narrow perception of education as strictly test preparation, (2) feelings of stress and anxiety related to the state test, (3) concern with what “others” think (racial salience), and (4) stereotypes. A new conceptual model for stereotype threat is presented, and future directions including implications for practice and policy are discussed.

Responses of sawgrass and spikerush to variation in hydrologic drivers and salinity in Southern Everglades marshes

Aboveground net primary production (ANPP) by the dominant macrophyte and plant community composition are related to the changing hydrologic environment and to salinity in the southern Everglades, FL, USA. We present a new non-destructive ANPP technique that is applicable to any continuously growing herbaceous system. Data from 16 sites, collected from 1998 to 2004, were used to investigate how hydrology and salinity controlled sawgrass (Cladium jamaicense Crantz.) ANPP. Sawgrass live biomass showed little seasonal variation and annual means ranged from 89 to 639 gdw m)2. Mortality rates were 20–35% of live biomass per 2 month sampling interval, for biomass turnover rates of 1.3–2.5 per year. Production by C. jamaicense was manifest primarily as biomass turnover, not as biomass accumulation. Rates typically ranged from 300 to 750 gdw m)2 year)1, but exceeded 1000 gdw m)2 year)1 at one site and were as high as 750 gdw m)2 year)1 at estuarine ecotone sites. Production was negatively related to mean annual water depth, hydroperiod, and to a variable combining the two (depth-days). As water depths and hydroperiods increased in our southern Everglades study area, sawgrass ANPP declined. Because a primary restoration goal is to increase water depths and hydroperiods for some regions of the Everglades, we investigated how the plant community responded to this decline in sawgrass ANPP. Spikerush (Eleocharis sp.) was the next most prominent component of this community at our sites, and 39% of the variability in sawgrass ANPP was explained by a negative relationship with mean annual water depth, hydroperiod, and Eleocharis sp. density the following year. Sawgrass ANPP at estuarine ecotone sites responded negatively to salinity, and rates of production were slow to recover after high salinity years. Our results suggest that ecologists, managers, and the public should not necessarily interpret a decline in sawgrass that may result from hydrologic restoration as a negative phenomenon.

Flexible pavement layer moduli determination : an adaptive artificial neural network approach

The estimation of pavement layer moduli through the use of an artificial neural network is a new concept which provides a less strenuous strategy for backcalculation procedures. Artificial Neural Networks are biologically inspired models of the human nervous system. They are specifically designed to carry out a mapping characteristic. This study demonstrates how an artificial neural network uses non-destructive pavement test data in determining flexible pavement layer moduli. The input parameters include plate loadings, corresponding sensor deflections, temperature of pavement surface, pavement layer thicknesses and independently deduced pavement layer moduli.