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At San Francisco State University, a Hispanic Serving Institute and a Primarily Undergraduate Institution, 67% of engineering students are from ethnic minority groups, with only 27% of Hispanic students retained and graduated in their senior year. Additionally, only 14% of students reported full-time employment secured at the time of graduation. Of these secured jobs, only 54% were full-time positions (40+ hours a week). To improve the situation, San Francisco State University, in collaboration with two local community colleges, Skyline and Cañada Colleges, was recently funded by the National Science Foundation through a Hispanic Serving Institute Improving Undergraduate STEM Education Strengthening Student Motivation and Resilience through Research and Advising program to enhance undergraduate engineering education and build capacity for student success. This project will use a data-driven and evidence-based approach to identify the barriers to the success of underrepresented minority students and to generate new knowledge on the best practices for increasing students’ retention and graduation rates, self- efficacy, professional development, and workforce preparedness. Three objectives underpin this overall goal. The first is to develop and implement a Summer Research Internship Program together with community college partners. The second is to establish an HSI Engineering Success Center to provide students with academic resources, networking opportunities with industry, and career development tools. The third is to develop resources for the professional development of faculty members, including Summer Faculty Teaching Workshops, an Inclusive Teaching and Mentoring Seminar Series, and an Engineering Faculty Learning Community. Qualitative and quantitative approaches are used to assess the project outcomes using a survey instrument and interview protocols developed by an external evaluator. This paper discusses an overview of the project and its first-year implementation. The focus is placed on the introduction and implementation of the several main project components, namely the Engineering Success Center, Summer Research Internship Program, and Faculty Summer Teaching Workshop. The preliminary evaluation results, demonstrating the great success of these strategies, are also discussed. 

Smart Structures Technologies (SST) is receiving considerable attention as the demands for high performance in structural systems increase. Although both the academic and professional engineering worlds are seeking ways to utilize SST, there is a significant gap between engineering science and engineering practice. To bridge the gap and facilitate the research infusion, San Francisco State University (SFSU) and the University of South Carolina (UofSC) collaborated with industry partners to establish a Research Experiences for Undergraduates (REU) Site program, which provides undergraduate students a unique opportunity to experience research in both academic and professional settings through cooperative research projects. The objectives of the program were to: 1) provide participants a unique and exciting summer research experience in both academic and industrial environments; 2) prepare students to become the catalysts to help close the gap between engineering science (academia) and engineering practice (industry); and 3) motivate the participants, especially those from underrepresented minority groups (URMs), not only to complete their undergraduate degrees but also to pursue advanced degrees and/or careers in engineering. 

As one of the serviceability limit states of structural design, excessive vibration has attracted more attention in recent years, with the design trend moving toward lighter and more slender structures. Footfall vibration contains high uncertainties in nature, with significant variations in walker weight, walking speeds, and dynamic load factor. Since conservative designs can often lead to significant cost premiums, this study focuses on the stochastic assessment of footfall vibration of on a composite steel floor to better understand the variation in performance of various design factors and better inform the ultimate decision-makers. To close the knowledge gap between academia and industry in this area, San Francisco State University and the University of South Carolina partnered with Arup through an NSF-funded Research Experience for Undergraduates (REU) program. A composite steel structure was modeled to resemble a typical office bay. The model was developed and analyzed in Oasys GSA. Monte Carlo simulation was used to quantify the probability of exceeding certain common vibration criteria. The results of this study would provide actionable guidance to stakeholders to weigh the benefits and costs between performance targets. 

Greenhouse gases trap heat within our atmosphere, leading to an unnatural increase in temperature. Carbon dioxide and its equivalent emissions have been a large focus when considering sustainability in the civil engineering field, with a reduction of global warming potential being a top priority. According to a 2017 report by the World Green Building Council, the construction and usage of buildings account for 39 percent of human carbon emissions in the United States, almost one third of which are from the extraction, manufacturing, and transportation of materials. Substituting wood for high emission materials could greatly reduce carbon if harvested and disposed of in a controlled way. To investigate this important issue, San Francisco State University and University of South Carolina partnered with Skidmore, Owings & Merrill LLP, a world leader in designing high-rise buildings, through a National Science Foundation (NSF) Research Experience for Undergraduates (REU) Site program, to investigate and quantify the embodied carbons of various slab system designs using a high-rise residential complex in San Francisco as a case study. Three concept designs were considered: a concrete building with cementitious replacement, a concrete building without cementitious replacement, and a concrete building with cementitious replacement and nail-laminated timber wood inlays inserted into various areas of the superstructure slabs. The composite structural slab system has the potential to surpass the limitations of wood-framed structures yet incorporate the carbon sequestration that makes wood a more sustainable material. The results show that wood substitution could decrease overall emissions from the aforementioned designs and reduce the environmental footprint of the construction industry. 

The gap between research in academia and industry is narrowing as collaboration between the two becomes critical. Topology optimization has the potential to reduce the carbon footprint by minimizing material usage within the design space based on given loading conditions. While being a useful tool in the design phase of the engineering process, its complexity has hindered its progression and integration in actual design. As a result, the advantages of topology optimization have yet to be implemented into common engineering practice. To facilitate the implementation and promote the usage of topology optimization, San Francisco State University and the University of South Carolina collaborated with ARUP, a world leader in structural designs, to develop an Automated Topology Optimization Platform (ATOP) to synchronize commonly used industry software programs and provide a user-friendly and automated solution to perform topology optimization. ATOP allows for users to form a conceptual understanding of a structure’s ideal shape and design in terms of ideal material placement by iterating various parameters such as volume fraction, and minimum and maximum member size at the start of a project. With developed platform, a high-rise building design from the literature was first adopted to validate the results from ATOP, after which an actual design project from ARUP was utilized to fully explore its functionality and versatility. Results show that ATOP has the potential to create aesthetic and structurally sound designs through an automated and intelligent process.