Juan M. Caicedo - US grants

Civil Engineering (54)

Most undergraduate engineering curricula provide the core knowledge and technical skills necessary to practice engineering. However, students rarely comprehend the underlying theory and fundamental concepts because the common assessment instruments can be satisfied through memorization and equation application. Students may not question the validity or potential repercussions of their solution or design, an essential step in any engineering design. Faculty from the University of South Carolina and Midlands Technical College are developing an Engineering Environment for Fostering Effective Critical Thinking (EFFECT) through measurements which relies on a conceptual model of how engineering judgment is formulated. In each EFFECT, students are solving real-world problems in Civil Engineering, while gaining hands-on experience with a directly related engineering measurement. Engineering judgment has three major components: 1) authentic experience, 2) core content knowledge, and 3) fundamental data-based technical skills. These components are synthesized when students think critically to solve the realistic engineering problems that are addressed in each EFFECT using an open-ended, inquiry-based approach. Various assessment methods are being used to evaluate the effectiveness, longitudinal impact, and institutional transferability of
each EFFECT.

The research objective of this project is to formulate a systematic and efficient computational approach for computer simulations to estimate the vibrations on the train, track, free-field and nearby surface or embedded structures generated by the high speed trains. The passage of high speed trains over soft soil sites can create vibrations similar to a sonic boom with the potential to affect the train and track, and cause damage to nonstructural components in adjacent structures and annoyance to the occupants. This work couples the well established Boundary Element Method and Finite Element Method in the time domain. The approach developed here can accommodate arbitrary soil profile, track and train configurations. All system components are equally represented in sufficient detail in a fully integrated dynamic interaction model for desired levels of computational accuracy. The approach will be tested and verified on the field data.

The successful completion of this project will provide a computational tool to analyze the complex behavior of train-track-soil system and play an important role in future development of the high speed trains in the United States. The outcomes of this project could be used in future developments of design charts for rapid vibration assessment of adjacent structures caused by high speed trains, in studies evaluating effectiveness of vibration mitigation measures, in integrated cost-benefit analysis and decision making processes related to train induced vibration reduction, and to study train stability affected by the interaction between the train, track and soil. This methodology can be expanded to problems involving vibration studies on bridges due to passage of high speed trains. The findings of this project will be disseminated to practicing engineers and designers, and integrated in the existing graduate and undergraduate engineering courses to provide the students the most recent information on the state of the art of the high speed train induced vibrations and their mitigation.

This award is funded under the American recovery and Reinvestment Act of 2009 (Public Law 111-5)

The research objective of this early career development (CAREER) project is to develop a framework for cooperative human-computer Model Updating Cognitive systems (MUCogS). Commonly used numerical modeling techniques, such as finite or boundary elements, provide accurate representations of simple structures, but until data and additional observations are incorporated into these models they often fail to represent the physical parameters of complex existing structures with desirable levels of accuracy. Model updating techniques are used to enhance these numerical models based on experimental data. Current model updating techniques obtain one model that best matches the existing structure by minimizing the error between experimental measurements and data produced by the numerical model. The analyst is limited to the selection of an initial model, adjusting few algorithm parameters or ?knobs? and has little control on the process performed by the algorithm itself. This research changes this paradigm by designing advances algorithms to detect several plausible solutions to the model updating problem. A trained engineer can use his/her engineering judgment to select one or several appropriated models for subsequent analysis. Through this framework MUCogS formally include the analyst on the model updating technique creating a cooperative human-computer system.

This research has direct application in any field of structural engineering that incorporates numerical modeling of existing structures (e.g., earthquake engineering, wind engineering and structural health monitoring). The successful completion of this research will significantly enhance an engineer?s ability to validate innovative designs, evaluate the performance and detect damage of existing structures. This advancement directly impacts state, federal and private budgets dedicated to infrastructure maintenance and replacement. The educational component of this research includes the development of engineering judgment among undergraduate students by nurturing critical thinking through the implementation of inquiry-based teaching in structural engineering classes. The outreach activities focus on exposing urban schools, with a significant population of minority students, to structural engineering. In addition, undergraduate research assistants are included on the research activities during the duration of the project.

This ten-week collaborative international REU site program will establish a Smart Structures Undergraduate Research Collaboratory where students at the Universities of Akron, South Carolina, and Connecticut will partner with the Korean Advance Institute for Science and Technology (KAIST) to gain access to world class facilities in Smart Structures and by doing so this will enhance the scope of the undergraduate research. A challenge faced by the Smart Structures community is the fact that structures vary in different geographical regions due to local building practices, availability of materials and dynamic loads likely to be experienced in the region. Ideal Smart Structure solutions should be universal in order to achieve the desired performance for various structures in the environment.

Reducing structural damage due to natural and made-made hazards in is vital to the safety and economic viability of society. Smart Structures which are those structures that can sense their environment and react accordingly, can provide more resilient designs, more effective construction, and extend overall the safe life of our built infrastructure. This collaborative project will further advance research on universal solutions in Smart Structures.

This program will engage six undergraduate students over ten weeks in these research activities: 1) formal training in structural dynamics, health monitoring and control; 2) experience conducting laboratory experiments in Smart Structures; 3) travel to KAIST in South Korea to experience international collaboration and gain access to world class facilities in Smart Structures; and 4) participate in site visits and cultural events.

The PIs will focus recruitment efforts on students from underrepresented groups at minority institutions. Undergraduate students will work directly with U.S. and Korean graduate students gaining valuable insight about research and graduate school.

The project is a collaboration between the University of South Carolina and Marshall University. It is establishing strategies to aid faculty in the design and implementation of special instructional modules (EFFECTs) designed to foster critical thinking. This proposal leverages the success of a Phase I CCLI project that defined the pedagogical structure for the EFFECTS, generated six EFFECTs, and developed an assessment methodology. Each module contains three elements: 1) a decision worksheet that guides an initial design for the first class period, 2) active learning modules and journal questions during the next n class periods, and 3) material to guides a group discussion to produce a final design during the last class period. Using these modules in several classes under the earlier grant led to gains in the students' core knowledge and critical thinking skills. Developing a systematic approach that enables other faculty to use EFFECTs is a key aspect for disseminating the approach widely through the engineering education community. To achieve this, the investigators are working to develop instructional material to teach the EFFECTs to faculty, to expand current assessment tools, to develop a community of practice to support the design and implementation of EFFECTs, and to assess the strategies developed to design and implement EFFECTs. Dissemination is being accomplished through web postings, including links with the NSDL, through conference presentation and journal publications, and through faculty workshops. A comprehensive evaluation effort, under the direction of an independent expert, includes the monitoring of student learning outcomes using instruments for measuring scientific reasoning skills, critical thinking skills, and content knowledge. Broader impacts include the dissemination of the material and the evaluation results, faculty workshops, and outreach through existing K-12 programs.

This Nanotechnology Undergraduate Education (NUE) in Engineering program at the University of South Carolina, entitled "NUE: Nano in a Global Context for Engineering Students", under the direction of Dr. Navid Saleh, will offer the opportunity to teach the principles and application of nanotechnology through a real-world program of global significance: water decontamination. The proposed new Introduction to Nanotechnology course will address five focus areas under the common water contamination theme, namely, (i) arsenic, (ii) pathogens, and (iii) organics/metal contamination and remediation, (iv) contaminant sensors, and (v) alternative power supply for treatment systems. The course has three principal goals: (1) introduce nanotechnology to engineering students who otherwise have no formal exposure to this important emerging technology; (2) integrate the approaches pertaining to nanotechnology offered by different engineering disciplines; and (3) fully incorporate discussions about the practical ethical implications of implementing nano in a real, developing world context. The course will include students from Claflin University an historically black college that will broaden the impact of the course to a larger, more diverse audience. In addition, students who complete the course will have the opportunity to travel to Bangladesh, meet researchers and students at the Bangladesh University of Engineering and Technology, and visit actual water decontamination sites in that region.

The overall outcomes of this project include (a) development of an introductory nanotechnology class, (b) making the individual modules of the class available to other classes within USC and beyond, (c) incorporation of technical articles as the driver of the technical modules for student exposure to scientific research, (d) inclusion of minority students from Claflin University, and (e) international collaboration through the study-abroad program in Bangladesh.

This grant provides funding for research on the standardization of system integration protocols for the purpose of simulating and managing civil infrastructure systems. This research studies the applicability of model integration standards that are based on the concept of component software architectures for modeling the integration of civil infrastructure systems. The project tasks focus on the design of a component-based modeling environment that is appropriate for modeling the integration of coupled urban infrastructure systems, and the application of the developed framework to evaluate a real-time flooding event using a case study system in Columbia, SC. The scientific questions addressed by this research include: (1) Are the component-based system integration concepts developed for integrating water resource models applicable for the representation of the integration of civil infrastructure systems? (2) What are the appropriate component interface and data exchange standards for integrating various modeling components representing civil infrastructure system? (3) Do simulations of integrated civil infrastructure lead to effective decisions for the management and operation of urban infrastructure systems?

If successful, the results of this research will lead to improvements in our ability to manage large, complex urban infrastructure systems as an integrated system that improves their reliability, resiliency, and sustainability. This research work could have implications for both day to day operations of civil infrastructure systems, as well as their management during extreme events. In addition to the aforementioned research objectives, this grant will also provide funding to advance civil engineering education by incorporating ideas and concepts from systems analysis into the civil the engineering curriculum using an Environment For Fostering Effective Critical Thinking (EFFECTs) pedagogical structures.

This NUE in Engineering program entitled, "NUE: Nanotechnology LINK: An integrated approach for nanotechnology education: End of life management of nanomaterial-containing wastes", at the University of South Carolina (USC), under the direction of Dr. Nicole Berge, has as its goal to develop an integrated undergraduate nanotechnology theme within the currently existing Civil and Environmental Engineering (CEE) curriculum at USC that focuses on the environmental implications associated with the end-of-life management of nanomaterial-containing products, materials, and nanomaterial manufacturing waste streams to produce a more informed and competitive CEE workforce.

To accomplish this goal, the project team plans to develop nanotechnology problem-based hands-on modules following a pedagogical approach referred to as Environments for Fostering Effective Critical Thinking (EFFECTs). EFFECTs use student-centered learning strategies to promote deep learning, enhance conceptual understanding, and stimulate growth in critical thinking skills. The EFFECTs approach has become institutionalized within the USC CEE curriculum. However, even though EFFECTs have been developed and implemented in a significant number of courses, these EFFECTs are independent and unrelated. Dr. Berge and her team propose to create an EFFECT LINK (Learning Integration of New Knowledge) for teaching and learning of nanotechnology content across the curriculum, which is referred to as the Nanotechnology LINK. As part of this integrated approach, students will assemble nanotechnology-themed electronic portfolios, building content knowledge as they advance through a sequence of courses. In addition, students will have the option of participating in an undergraduate nanotechnology-based research experience and graduate with a Leadership Distinction in Research.

The development and implementation of the proposed Nanotechnology LINK framework will result in the generation and refinement of a transformative educational approach of linking student learning across a curriculum to enhance student learning of other techniques/concepts. In addition, knowledge associated with the environmental implications associated with the end-of-life management of nanomaterial-containing wastes will be advanced. To date, there has been little research in this area. This work will also result in better-prepared civil and environmental engineers.

This proposal is addressing the fundamental challenge of assessing individual student's knowledge in cornerstone engineering classes with high student-to-faculty ratios. The goal is to: develop a computational assessment framework that easily integrates into an instructor's routine efforts to track student knowledge, suggest remedial interventions, and guide future examinations. The rationale is that individual student knowledge is a hypothesis/model that needs to be tested using the scientific method. Similarly, assessment instruments are just experiments to discover how well a student masters specific concepts. This fits naturally with probabilistic methodologies such as the Bayesian inference that formalize the scientific method.

The main approach taken is to track the progress of individual students by developing student knowledge models based on Bayesian networks. This proposal addresses an open fundamental problem in constructing and using knowledge models to assess learning, namely how to relate curricular structure to knowledge models and how to inform the models using assessment data. The proposed methodology emphasizes the role of concept inventories to inform the construction of Bayesian networks models and to extract information from these models to suggest informative questions for future examinations. To facilitate ease of use and broader adoption by faculty, the software artifacts will be made available under open source licenses and the functionality of the framework will be integrated within a widely used learning management system through the development of a prototype plugin. The education and outreach aspects of this proposal include training participants in effective educational strategies and mentoring of future faculty.

The San Francisco State University (SFSU) and the University of South Carolina (USC) will collaborate with industrial partners to provide a Research Experiences for Undergraduates (REU) Site program entitled, Collaborative Research: Integrated Academia-Industry Research Experience for Undergraduate in Smart Structure Technology (IAIRESST),focusing on academia-industry collaborations in Smart Structures Technologies (SST). These technologies include innovative devices and techniques that make structures safer, less expensive to maintain, and able to provide additional services. This REU program will provide engineering undergraduate students a unique research experience in both academic and industrial settings through cooperative research projects. Experiencing research in both worlds is expected to help students transition from a relatively dependent status to an independent a status as their competence level increases. The model developed through this REU program may help to exemplify the establishment of a sustainable collaboration model between academia and industry that helps address the nation's need for mature, independent, informed, and globally competitive science, technology, engineering, and mathematics (STEM) professionals and is adapted to other disciplines.

With increasing demands for high performance in structural systems, SST including advanced sensing, modern control, smart materials, optimization and novel testing, is receiving considerable attention as it has the potential to transform many fields in engineering, including civil, mechanical, aerospace, and geotechnical engineering. Currently, there is a significant gap between the engineering science with fundamental research in academia and engineering practice with potential implementation in the industry. This REU program will train undergraduate students to serve as the catalysts to facilitate the research infusion between academic and industrial partners. This student-driven joint venture between academia and industry will establish a virtuous circle for knowledge exchange and contribute to advancing both fundamental research and implementation of SST. To achieve these, the program will feature: formal training, workshops, and supplemental activities in the conduct of research in academia and industry; innovative research experience through engagement in projects with scientific and practical merits in both academic and industrial environments; experience in conducting laboratory experiments; and opportunities to present the research outcomes to the broader community at professional settings. The joint efforts among two institutions and industry partners provide the project team with extensive access to valuable resources, such as expertise to offer a wider-range of informative training workshops, advanced equipment, valuable data sets, experienced undergraduate mentors, and professional connections, that will facilitate a meaningful REU experience. Recruitment of REU participants will target 20 collaborating minority and primarily undergraduate institutions (15 of them are Hispanic-Serving Institutions) with limited STEM research capabilities.

The United States population is growing older. There is an urgent need for tools to better connect health professionals with their patients and perform at-home assessments in an automated fashion. The long-term goal of this proposal is to discover the knowledge necessary to enable an always-on, non-intrusive, non-wearable smart system for automated at-home gait parameter estimation using floor vibrations. To achieve this vision, the proposal has the objective of connecting health professionals with older adults living independently through a smart system that estimates gait parameters using floor vibration. The aims to achieve this goal are to 1) determine at-home gait parameters as a function of time and space; 2) establish a digital identifier of the older adult based on gait parameters; and 3) correlate changes in at-home gait parameters, after considering spatial-temporal correlations, with changes in the well-being of the resident. The proposed research will advance the state-of-the-art in engineering, physical therapy and public health by testing the following hypotheses: 1) Floor vibration is a viable means to automatically and continuously determine gait parameters; 2) For healthy individuals living in an independent at-home setting, gait parameters will be consistent based on location in the home, time of the day and day of the week; and 3) For patients recently discharged from the hospital, recovery will correlate with improvements in their gait parameters. The testing of the hypotheses will be performed through five tasks: 1) Develop an automated system to capture floor vibration and extract gait parameters; 2) Validate the system in laboratory setting; 3) Collect data at participant?s homes; 4) Test the hypothesis that at-home gait parameters are consistent with time and space; 5) Test the hypothesis that improvement in gait parameters correlates improvement in health status of recently discharged patients. This research will be pursued by a group of interdisciplinary researchers in engineering and physical therapy with the support of an experienced geriatric physician and will advance the knowledge in signal processing techniques, estimation and validation of at-home gait parameters and their uncertainty, and relationship between changes at-home gait parameters and changes in health status. The proposed activities will have a significant impact on older adult care, the research community and the next generation of researchers and engineers stemming from: 1) improved health of older adults and reduced health care cost by early intervening and thus decreasing the readmission rate; 2) increased scientific literacy and public engagement through benchmark problems, interdisciplinary seminars, new courses and outreach activities; 3) the training of diverse convergence researchers competent in solving interdisciplinary problems, including underrepresented groups in STEM fields.