6 resultados para BODY VOLUME CHANGES
em Digital Commons - Michigan Tech
Resumo:
High resolution digital elevation models (DEMs) of Santiaguito and Pacaya volcanoes, Guatemala, were used to estimate volume changes and eruption rates between 1954 and 2001. The DEMs were generated from contour maps and aerial photography, which were analyzed in ArcGIS 9.0®. Because both volcanoes were growing substantially over the five decade period, they provide a good data set for exploring effective methodology for estimating volume changes. The analysis shows that the Santiaguito dome complex grew by 0.78 ± 0.07 km3 (0.52 ± 0.05 m3 s-1) over the 1954-2001 period with nearly all the growth occurring on the El Brujo (1958-75) and Caliente domes (1971-2001). Adding information from field data prior to 1954, the total volume extruded from Santiaguito since 1922 is estimated at 1.48 ± 0.19 km3. Santiaguito’s growth rate is lower than most other volcanic domes, but it has been sustained over a much longer period and has undergone a change toward more exogenous and progressively slower extrusion with time. At Santiaguito some of the material being added at the dome is subsequently transported downstream by block and ash flows, mudflows and floods, creating channel shifting and areas of aggradation and erosion. At Pacaya volcano a total volume of 0.21 ± 0.05 km3 was erupted between 1961 and 2001 for an average extrusion rate of 0.17 ± 0.04 m3 s-1. Both the Santiaguito and Pacaya eruption rate estimates reported here are minima, because they do not include estimates of materials which are transported downslope after eruption and data on ashfall which may result in significant volumes of material spread over broad areas. Regular analysis of high resolution DEMs using the methods outlined here, would help quantify the effects of fluvial changes to downstream populated areas, as well as assist in tracking hazards related to dome collapse and eruption.
Resumo:
When a concrete slab experiences differential volume change due to temperature, moisture, and shrinkage gradients, it deforms. The stresses induced by these differential volume changes can reduce the pavement’s fatigue life. Differential volume change is quantified by the equivalent temperature difference required to deform a comparable flat slab to the same shape as the actual slab. This thesis presents models to predict the equivalent temperature difference due to moisture warping and differential drying shrinkage. Moisture warping occurs because a portion of drying shrinkage is reversible, while differential drying shrinkage is due to the irreversible portion of drying shrinkage. The amount of reversible shrinkage was investigated for concretes made with different types of aggregate, including lightweight and recycled. Another source of differential volume change is built-in curl, which is caused by temperature gradients at the time of paving. This thesis also presents a comparison of methods used to quantify built-in curl.
Resumo:
Virtually every sector of business and industry that uses computing, including financial analysis, search engines, and electronic commerce, incorporate Big Data analysis into their business model. Sophisticated clustering algorithms are popular for deducing the nature of data by assigning labels to unlabeled data. We address two main challenges in Big Data. First, by definition, the volume of Big Data is too large to be loaded into a computer’s memory (this volume changes based on the computer used or available, but there is always a data set that is too large for any computer). Second, in real-time applications, the velocity of new incoming data prevents historical data from being stored and future data from being accessed. Therefore, we propose our Streaming Kernel Fuzzy c-Means (stKFCM) algorithm, which reduces both computational complexity and space complexity significantly. The proposed stKFCM only requires O(n2) memory where n is the (predetermined) size of a data subset (or data chunk) at each time step, which makes this algorithm truly scalable (as n can be chosen based on the available memory). Furthermore, only 2n2 elements of the full N × N (where N >> n) kernel matrix need to be calculated at each time-step, thus reducing both the computation time in producing the kernel elements and also the complexity of the FCM algorithm. Empirical results show that stKFCM, even with relatively very small n, can provide clustering performance as accurately as kernel fuzzy c-means run on the entire data set while achieving a significant speedup.
Resumo:
The study of volcano deformation data can provide information on magma processes and help assess the potential for future eruptions. In employing inverse deformation modeling on these data, we attempt to characterize the geometry, location and volume/pressure change of a deformation source. Techniques currently used to model sheet intrusions (e.g., dikes and sills) often require significant a priori assumptions about source geometry and can require testing a large number of parameters. Moreover, surface deformations are a non-linear function of the source geometry and location. This requires the use of Monte Carlo inversion techniques which leads to long computation times. Recently, ‘displacement tomography’ models have been used to characterize magma reservoirs by inverting source deformation data for volume changes using a grid of point sources in the subsurface. The computations involved in these models are less intensive as no assumptions are made on the source geometry and location, and the relationship between the point sources and the surface deformation is linear. In this project, seeking a less computationally intensive technique for fracture sources, we tested if this displacement tomography method for reservoirs could be used for sheet intrusions. We began by simulating the opening of three synthetic dikes of known geometry and location using an established deformation model for fracture sources. We then sought to reproduce the displacements and volume changes undergone by the fractures using the sources employed in the tomography methodology. Results of this validation indicate the volumetric point sources are not appropriate for locating fracture sources, however they may provide useful qualitative information on volume changes occurring in the surrounding rock, and therefore indirectly indicate the source location.
Resumo:
Autonomous system applications are typically limited by the power supply operational lifetime when battery replacement is difficult or costly. A trade-off between battery size and battery life is usually calculated to determine the device capability and lifespan. As a result, energy harvesting research has gained importance as society searches for alternative energy sources for power generation. For instance, energy harvesting has been a proven alternative for powering solar-based calculators and self-winding wristwatches. Thus, the use of energy harvesting technology can make it possible to assist or replace batteries for portable, wearable, or surgically-implantable autonomous systems. Applications such as cardiac pacemakers or electrical stimulation applications can benefit from this approach since the number of surgeries for battery replacement can be reduced or eliminated. Research on energy scavenging from body motion has been investigated to evaluate the feasibility of powering wearable or implantable systems. Energy from walking has been previously extracted using generators placed on shoes, backpacks, and knee braces while producing power levels ranging from milliwatts to watts. The research presented in this paper examines the available power from walking and running at several body locations. The ankle, knee, hip, chest, wrist, elbow, upper arm, side of the head, and back of the head were the chosen target localizations. Joints were preferred since they experience the most drastic acceleration changes. For this, a motor-driven treadmill test was performed on 11 healthy individuals at several walking (1-4 mph) and running (2-5 mph) speeds. The treadmill test provided the acceleration magnitudes from the listed body locations. Power can be estimated from the treadmill evaluation since it is proportional to the acceleration and frequency of occurrence. Available power output from walking was determined to be greater than 1mW/cm³ for most body locations while being over 10mW/cm³ at the foot and ankle locations. Available power from running was found to be almost 10 times higher than that from walking. Most energy harvester topologies use linear generator approaches that are well suited to fixed-frequency vibrations with sub-millimeter amplitude oscillations. In contrast, body motion is characterized with a wide frequency spectrum and larger amplitudes. A generator prototype based on self-winding wristwatches is deemed to be appropriate for harvesting body motion since it is not limited to operate at fixed-frequencies or restricted displacements. Electromagnetic generation is typically favored because of its slightly higher power output per unit volume. Then, a nonharmonic oscillating rotational energy scavenger prototype is proposed to harness body motion. The electromagnetic generator follows the approach from small wind turbine designs that overcome the lack of a gearbox by using a larger number of coil and magnets arrangements. The device presented here is composed of a rotor with multiple-pole permanent magnets having an eccentric weight and a stator composed of stacked planar coils. The rotor oscillations induce a voltage on the planar coil due to the eccentric mass unbalance produced by body motion. A meso-scale prototype device was then built and evaluated for energy generation. The meso-scale casing and rotor were constructed on PMMA with the help of a CNC mill machine. Commercially available discrete magnets were encased in a 25mm rotor. Commercial copper-coated polyimide film was employed to manufacture the planar coils using MEMS fabrication processes. Jewel bearings were used to finalize the arrangement. The prototypes were also tested at the listed body locations. A meso-scale generator with a 2-layer coil was capable to extract up to 234 µW of power at the ankle while walking at 3mph with a 2cm³ prototype for a power density of 117 µW/cm³. This dissertation presents the analysis of available power from walking and running at different speeds and the development of an unobtrusive miniature energy harvesting generator for body motion. Power generation indicates the possibility of powering devices by extracting energy from body motion.
ALTERNATING CURRENT DIELECTROPHORETIC MANIPULATION OF ERYTHROCYTES IN MEDICAL MICRODEVICE TECHNOLOGY
Resumo:
Medical microdevices have gained popularity in the past few decades because they allow the medical laboratory to be taken out into the field and for disease diagnostics to happen with a smaller sample volume, at a lower cost and much faster. Blood is the human body's most readily available and informative diagnostic fluid because of the wealth of information it provides about the body's general health including enzymatic, proteomic and immunological states. The purpose of this project is to optimize operating conditions and study ABO-Rh erythrocytes dielectrophoretic responses to alternating current electric signals. The end goal of this project is the creation of a relatively inexpensive microfluidic device, which can be used for the ABO-Rh typing of a blood sample. This dissertation presents results showing how blood samples of a known ABO- Rh blood type exhibit differing behavior to the same electrical stimulus based on their blood type. The first panel of donors and experiments, presented in Chapter 4 occurred when a sample of known blood type was injected into a microdevice with a T-shaped electrode configuration and the erythorcytes were found to rupture at a rate specific to their ABO-Rh blood type. The second set of experiments, presented in Chapter 5, were originally published in Electrophoresis in 20111. Novel in this work was the discovery that treatment of human erythrocytes with β-galactosidase successfully removed ABO surface antigens such that native A and B blood no longer agglutinated with the proper antibodies. This work was performed in a medium of conductivity 0.9S/m which is close to the measured conductivity of pooled plasma (~1.1S/m). The ability to perform dielectrophoresis experiments at physiological conductivities conditions is advantageous for future portable devices because the device/instrument would not need to store dilution buffers. The final results of this project, presented in Chapter 6, explore the entire dielectrophoretic spectra of the ABO-Rh erythrocytes including the cross-over frequency and the magnitudes of the positive or negative dielectrophoretic response. These were completed at lower medium conductivities of 0.1S/m and 0.01-0.04S/m. These results show that by using the sweep function built into the Agilent alternating current generator it is possible to explore how a single group of blood cells will react to rapid changes in frequency and will provide the user with curve that can be matched the theoretical dielectrophoretic response curves. As a whole this project shows that it is possible to distinguish human erythrocytes by their ABO-Rh blood type via three different dielectrophoretic methods. This work builds on the foundation of that it is possible to distinguish healthy from infected cells2-7, similar cell types1,7-14 and other work regarding the dielectrophoresis of human erythrocytes1,10,11. This work has implications in both medical diagnostics and future dielectrophoretic work because it has shown that ABO-Rh blood type is now a factor, which must be identified when working with a human blood sample. It also shows that the creation of a microfluidic device that subjects human erythrocytes to a dielectrophoretic impulse and then exports an ABO-Rh blood type is a near future possibility.