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In this paper, a multi-frequency MEMS acoustic emission (AE) sensor is designed, characterized, and tested. The sensor includes sixteen individual resonators tuned in the range of 100 kHz to 700 kHz. The resonator frequencies are selected to form constructive interference when they are connected in parallel to increase the signal-to-noise ratio. Each resonator is comprised of a membrane that forms the mass and four beams that provide stiffness. The membrane size is kept the same for each resonator to have approximately the same sensitivity per frequency. The influence of spring elements on the resonant frequency and the sensitivity is numerically demonstrated. The sensor is manufactured using MEMSCAP PiezoMUMPs. The characterization experiments show a slight shift in the resonant frequency of individual resonators compared to the design values. The MEMS sensor is packaged using a custom-designed printed circuit board to improve the signal-to-noise ratio. The sensor performance is compared with a conventional AE sensor. The sensitivity and frequency bandwidth of the MEMS AE device is brought to a comparable level to bulky AE sensors. 

This paper presents a review of state-of-the-art micro-electro-mechanical-systems (MEMS) acoustic emission (AE) sensors. MEMS AE sensors are designed to detect active defects in materials with the transduction mechanisms of piezoresistivity, capacitance or piezoelectricity. The majority of MEMS AE sensors are designed as resonators to improve the signal-to-noise ratio. The fundamental design variables of MEMS AE sensors include resonant frequency, bandwidth/quality factor and sensitivity. Micromachining methods have the flexibility to tune the sensor frequency to a particular range, which is important, as the frequency of AE signal depends on defect modes, constitutive properties and structural composition. This paper summarizes the properties of MEMS AE sensors, their design specifications and applications for detecting the simulated and real AE sources and discusses the future outlook. 

Phononic crystals have the ability to manipulate the propagation of elastic waves in solids by generating unique dispersion characteristics. They can modify the conventional behavior of wave spreading in isotropic materials, known as attenuation, which negatively influences the ability of acoustic emission method to detect active defects in long-range, pipe-like structures. In this study, pipe geometry is reconfigured by adding gradient-index (GRIN) phononic crystal lens to improve the propagation distance of waves released by active defects such as crack growth and leak. The sensing element is designed to form a ring around the pipe circumference to capture the plane wave with the improved amplitude. The GRIN lens is designed by a special gradient-index profile with varying height stubs adhesively bonded to the pipe surface. The performance of GRIN lens for improving the amplitude of localized sources is demonstrated with finite element numerical model using multiphysics software. Experiments are conducted using pencil lead break simulating crack growth, as well as an orifice with pressured pipe simulating leak. The amplitude of the burst-type signal approximately doubles on average, validating the numerical findings. Hence, the axial distance between sensors can be increased proportionally in the passive sensing of defects in pipe-like geometries. 

This Complete Research paper will describe the implementation of an introductory course (ENGR194) for first semester engineering students. The course is meant to improve retention and academic success of engineering first-year students in the College of Engineering at the University of Illinois at Chicago. The implementation of this course is part of an ongoing National Science Foundation (NSF) Scholarships in Science, Technology, Engineering, and Math (S-STEM) project. This paper reports on the impact of combinatorial enrollment in ENGR194 and a previously described two-week Summer Bridge Program (SBP) offered only for entering S-STEM scholars before their first semester. To measure the impact of this course on student retention and academic success, various evaluation metrics are compared for three separate Comparison Groups (C-Groups) of students. The results show that the ENGR194 course had a significant positive impact on the first-year retention rate. The results also revealed that students who participated in both ENGR194 and SBP (C-Group 1) made changes to their declared majors earlier than students who had only taken ENGR 123 or neither of the courses (C-Groups 2 and 3 respectively). Furthermore, students in C-Group 1 received better grades in math and science than their peers, and students in C-Groups 1 and 2 had significantly higher GPAs than their peers in C-Group 3. 

This paper provides detailed information for a poster that will be presented in the National Science Foundation (NSF) Grantees Poster Session during the 2020 ASEE Annual Conference & Exposition. The poster describes the progress and the state of an NSF Scholarships in Science, Technology, Engineering, and Math (S-STEM) project. The objectives of this project are to 1) enhance student learning by providing access to extra- and co-curricular experiences, 2) create a positive student experience through mentorship, and 3) ensure successful student placement in the STEM workforce or graduate school. S-STEM Scholars supported by this program receive financial, academic, professional, and social development via various evidence-based activities integrated throughout their four-year undergraduate degrees beginning during the summer prior to starting at the University. The paper describes the characteristics (demographics, high school GPA, ACT/SAT scores, etc.) of the Scholars supported by the S-STEM grant. The paper also provides information about the completed tasks of the project to date. The completed tasks include a system for recruiting academically talented and economically disadvantaged students, a Summer Bridge Program (SBP), a first semester introductory engineering course, and a system to recruit and maintain faculty mentors. The ongoing tasks include the execution of a service learning project course and a system for recruiting industry mentors. This paper reports detailed assessment and evaluation data about different project tasks and the academic success metrics of the Scholars. It also lists a set of recommendations based on the lessons learned in this S-STEM project.