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The steady flow method (SFM), most commonly used for permeability measurement in the laboratory, is not applicable for tight rocks, higher rank coals and coals under highly stressed condition because of the difficulty in measuring steady-state gas flowrates resulting from the tight rock structure of. However, accurate estimation of permeability of highly stressed coals is pivotal in coalbed methane (CBM) operations in order to precisely and effectively model and project long-term gas production. A fast and accurate permeability measurement technique is, therefore, required to investigate gas flow behavior of CBM reservoirs. The pulse-decay method (PDM) of permeability measurement is believed to be better suited for low-permeability rocks. In this study, application of the currently used pulse-decay laboratory permeability measurement techniques for highly stressed coals were evaluated. Considering the limitations of these techniques in permeability measurement of unconventional gas reservoirs, such as coal and gas shales, the conventional PDM was optimized by adjusting the experimental apparatus and procedures. Furthermore, the applicability of an optimized PDM was verified numerically and experimentally. This dissertation is composed of five chapters. To complete the research objectives as discussed above, it is necessary to have a profound understanding of the basic theories, such as, gas storage mechanism, gas migration, and permeability evolution during gas depletion in coalbed reservoirs. In Chapter 1, a brief discussion regarding the basic knowledge of reservoir properties and transport mechanisms is presented. The chapter also provides the appropriate background and rationale for the theoretical and experimental work conducted in this study. Chapter 2 presents the transient pressure-decay technique in permeability measurement of highly stressed coals and verifies the validity of Brace et al.’s solution (1968) by comparing it with Dicker and Smits’s solution (1988) and Cui et al.’s solution. The differences between these three solutions are discussed in detail. Based on the established permeability trends from these different solutions, a persuasive suggestion is presented for selection of the best alternative when testing coal permeability. Furthermore, permeability is regarded as a coupled parameter, resulting from the combined effects of mechanical compression and “matrix shrinkage” caused by desorption of gas. To isolate the role of gas desorption from the coupled result, a series of experiments were carried out under constant effective stress condition and a stress-dependent permeability trend was established. Chapter 3 proposes an optimized experimental design in order to improve the accuracy of the calculated permeability for sorptive rocks. In order to verify the optimized design theoretically, a modified mathematical model is presented and describes the one-dimensional fluid flow in porous media by a partial differential equation. The numerical solutions of the model are presented graphically to evaluate the fluid flow behavior in porous media. Finally, the validity of Brace et al.’s solution when testing sorptive rocks, without the need of consideration on the compressive storage and sorption effect, is elucidated. Chapter 4 demonstrates the efficiency and applicability of the optimized PDM through its direct application to experimental work designed to establish the permeability trend under best replicated in situ conditions. In this chapter, CO2 was used as the test fluid to profile and characterize the pulse decay plots due to its higher affinity towards coal than methane, and then establish the stress-dependent-permeability trend for highly-stressed CBM reservoirs. In this chapter, Brace et al.’s solution was also verified by comparing the laboratory data and computer simulated results obtained from the optimized mathematical model proposed in Chapter 3. The experimental work demonstrates that the optimized technique can be used for permeability tests of sorptive rocks without the need to carry out additional experimental work required to measure rock porosities and sorption isotherms. Finally, a summary and future research perspectives are presented in Chapter 5.

In recent years, sparsity and compressive sensing have attracted significant attention in parameter estimation tasks, including frequency estimation, delay estimation, and localization. Parametric dictionaries collect signals for a sampling of the parameter space and can yield sparse representations for the signals of interest when the sampling is sufficiently dense. While this dense sampling can lead to high coherence in the dictionary, it is possible to leverage structured sparsity models to prevent highly coherent dictionary elements from appearing simultaneously in a signal representation, alleviating these coherence issues. However, the resulting approaches depend heavily on a careful setting of the maximum allowable coherence; furthermore, their guarantees apply to the coefficient vector recovery and do not translate in general to the parameter estimation task. We propose a new algorithm based on optimal sparse approximation measured by earth mover's distance (EMD). Theoretically, we show that EMD provides a better metric for the performance of parametric dictionary-based parameter estimation and $K$-median clustering algorithms has the potential to solve the EMD-optimal sparse approximation problems. Simulations show that the resulting compressive parameter estimation algorithm is better at addressing the coherence issuers without a careful setting of additional parameters.

Typically, inverse imaging problems deal with the reconstruction of images from the sensor measurements where sensors can take form of any imaging modality like camera, radar, hyperspectral or medical imaging systems. In an ideal scenario, we can reconstruct the images via applying an inversion procedure from these sensors’ measurements, but practical applications have several challenges: the measurement acquisition process is heavily corrupted by the noise, the forward model is not exactly known, and non-linearities or unknown physics of the data acquisition play roles. Hence, perfect inverse function is not exactly known for immaculate image reconstruction. To this end, in this dissertation, I propose an automatic sensing and reconstruction scheme based on deep learning within the compressive sensing (CS) framework to solve the computational imaging problems. Here, I develop a data-driven approach to learn both the measurement matrix and the inverse reconstruction scheme for a given class of signals, such as images. This approach paves the way for end-to-end learning and reconstruction of signals with the aid of cascaded fully connected and multistage convolutional layers with a weighted loss function in an adversarial learning framework. I also propose to extend our analysis to introduce data driven models to directly classify from compressed measurements through joint reconstruction and classification. I develop constrained measurement learning framework and demonstrate higher performance of the proposed approach in the field of typical image reconstruction and hyperspectral image classification tasks. Finally, I also propose a single data driven network that can take and reconstruct images at multiple rates of signal acquisition. In summary, this dissertation proposes novel methods on the data driven measurement acquisition for sparse signal reconstruction and classification, learning measurements for given constraints underlying the requirement of the hardware for different applications, and producing a common data driven platform for learning measurements to reconstruct signals at multiple rates. This dissertation opens the path to the learned sensing systems. The future research can use these proposed data driven approaches as the pivotal factors to accomplish task-specific smart sensors in several real-world applications.

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The Concrete Masonry Association of California and Nevada in conjunction with Brigham Young University devised a masonry prism testing scheme to aid in the determination of whether prisms constructed with grouts possessing high levels of supplemental cementitious materials could meet minimum masonry compressive strength requirements. ASTM standards, identical to that of concrete, place restrictions on quantities, by weight, of supplemental materials that can replace ordinary Portland cement. For an all fly ash replacement, up to 40% of Portland cement can be replaced while up to 70% can be replaced by a fly ash-slag combination. Research is focused on class F fly ash and ground granulated blast furnace slag replacing Portland cement in larger quantities. Manufacturing grouts with increasing incremental amounts help to establish higher use limitations associated specifically with masonry grout. Masonry prisms, concrete masonry units, type M mortar, and variations of grout were tested for their respective compressive strengths at age intervals of 14, 28, 42, 56, and 90 days. Grouts were designed to support the discussion of whether non-traditional grouts can achieve acceptable masonry compressive strength in prisms while not possessing adequate grout compressive strength. The control grout consisted of one mix design containing a cementitious materials content of 100% Portland cement. Three grouts replaced Portland cement with fly ash and three grouts replaced Portland cement with a fly ash-slag combination without modifying the cementitious material weight contribution. Class F fly ash replaced Portland cement at rates of 45%, 55%, and 65%. Class F fly ash-ground granulated blast furnace slag combinations replaced Portland cement at rates of 65%, 75%, and 85% where the combinations consisted of 25% fly ash and 40%, 50%, and 60% slag. Results indicate that all prisms exceeded the 10.3 MPa (1500 psi) minimum compressive strength requirements before the mandated 28-day age period. Neither 55% and 65% fly ash replacements nor the 85% fly ash-slag combination achieved grout strength minimums at the typical specified age. The grout mixtures manufactured with exceeding addition rates which attained greater than the minimum strength at the 28-day age were the 45% fly ash and 65% and 75% fly ash-slag combination. All grouts did, eventually, extend their strength gain beyond 13.8 MPa (2000 psi) through the course of testing and all but 65% fly ash achieved this strength within 42 days.

Light-weight aggregate has been used successfully for structural and non-structural applications, and its most common use has been in light-weight concrete. Limited research has been done on light-weight grout though and there are no standards in place. The research performed in this study is intended to increase the knowledge of light-weight grout specifically made with expanded shale aggregate. The research presented herein is a pilot study and consists of preliminary aggregate and grout testing that resulted in the mix design of six grout types: three fine grout designs and three coarse grout designs. Conventional normal-weight aggregate was employed in the first grout mix. A light-weight aggregate batch was made with the same material proportions, as well as the same target water-cement (w/c) ratio and cement content. The weight of the cement was increased by 30 percent in the third grout type of each set to determine the effect on strength. The slump, component temperature, unit weight, air content, segregation, cement content, w/c ratio, and compressive strength for each grout type was gathered throughout testing. Correlations between grout testing results are examined and discussed. In addition, the effectiveness of expanded shale grout, other light-weight grouts, and normal-weight grout with respect to compressive strength to cement content ratio are determined. Results of the testing show that all six grout types studied in this research reached the minimum 28-day strength of 13.8 MPa (2000 psi) ASTM standard. In addition, the results indicate that the cement content in expanded shale light-weight grout would need to be increased to reach comparable compressive strengths to that of the normal-weight grout. The comparison between the compressive strength to cement content ratio of the different grouts indicate that normal-weight grout is more efficient. In addition, light-weight grout made with blast furnace slag grout is slightly more efficient than that made with expanded shale; however, this observation was only possible after several crucial assumptions were made about an existing blast furnace slag study. These strength-cement ratios do not account, however, for the benefits of reduced dead loads, improved thermal insulation, and improved sound insulation that could potentially influence the choice of the material used in and the life-cycle cost of the construction. Additional research should be done to verify the results of the ratios and the assumptions made herein. Furthermore, a life-cycle analysis needs to be conducted before a definite conclusion is made about which type grout is more efficient.

The objective of this research was to measure and analyze the long-term modulus values of cement-treated base (CTB) layers constructed in Utah using microcracking. Because modulus values of pavement layers are among the most influential inputs affecting mechanistic-empirical pavement design, obtaining reasonable estimates of modulus values is critical. Testing was performed with a portable falling-weight deflectometer, also called a lightweight deflectometer, and modulus values were backcalculated with the computer program BAKFAA. Testing occurred at five asphalt pavement sites in northern Utah, where reconstruction with full-depth reclamation and cement stabilization, in the form of cement slurry, was performed approximately 2 to 14 years previously. Unconfined compressive strength (UCS) data collected for the CTB materials during earlier projects were compiled for all five sites. The correlation between backcalculated CTB modulus values, which ranged from 42 to 433 ksi, and 7-day UCS values, which ranged from 366 to 559 psi, was analyzed, and uniformity and sensitivity analyses were performed. Based on the results of this research, a new correlation is proposed for estimating the long-term modulus values of microcracked CTB layers constructed in a seasonally cold climate, such as northern Utah. For an average 7-day UCS of 450 psi, a CTB modulus value of 114 ksi would be estimated using this correlation, whereas a much higher modulus value of 630 ksi would be estimated from an existing correlation chart that was published in 1972 before microcracking was developed as a CTB construction practice. The results of the uniformity analyses indicate that statistically significant spatial variability in the CTB modulus values exists at each site. In comparison to a proposed maximum threshold coefficient of variation of 40 percent presented in the literature for aspects of CTB construction, the CTB modulus at all of the sites would be characterized as having low uniformity, with values ranging from 42.9 to 90.3 percent. The results of the sensitivity analyses indicate that backcalculated CTB modulus values are sensitive to typical deviations from design values that may occur in pavement layer thicknesses and suggest that CTB modulus estimation errors may range from -22,561 to 62,097 psi, or -3.73 to 10.81 percent, for pavements similar to those studied in this research when the actual asphalt and CTB layer thicknesses are different than the assumed values by up to 0.25 or 0.50 in., respectively.

Objectives: To determine if temporomandibular joint (TMJ) compressive stresses during incisor biting (1) differed between growing children over time, and (2) were correlated with Frankfort Horizontal-mandibular plane angle (FHMPA, 8) and ramus length (Condylion-Gonion (Co-Go), mm). Materials and Methods: Three-dimensional anatomical geometries, FHMPA and Co-Go, were measured longitudinally from lateral and posteroanterior cephalographs1 of children aged 6 (T1), 12 (T2), and 18 (T3) years. Geometries were used in numerical models to estimate subject-specific TMJ eminence shape and forces for incisor bite-forces of 3, 5, and 8 Newtons at T1, T2, and T3, respectively. TMJ compressive stresses were estimated via two steps: First, TMJ force divided by age-dependent mandibular condylar dimensions, and second, modified by loading surfaces' congruency. Analysis of variance and Tukey honest significant difference post-hoc tests, plus repeated measures and mixed effects model analyses were used to evaluate differences in variables between facial groups. Regression analyses tested for correlation between agedependent compressive stresses, FHMPA, and Co-Go. Results: Sixty-five of 842 potential subjects had T1-T3 cephalographs and were grouped by FHMPA at T3. Dolichofacial (FHMPA ≥ 27°, n=36) compared to meso-brachyfacial (FHMPA, 27°, n=29) subjects had significantly larger FHMPA at T1-T3, shorter Co-Go at T2 and T3 (all P < .01), and larger increases in TMJ compressive stresses with age (P < .0001). Higher compressive stresses were correlated with larger FHMPA (all R2 ≥ 0.41) and shorter Co-Go (all R2 ≥ 0.49). Conclusions: Estimated TMJ compressive stress increases from ages 6 to 18 years were significantly larger in dolichofacial compared to meso-brachyfacial subjects and correlated to FHMPA and Co-Go.