(For a list of publications by Dr. Caicedo, click here)
Model Updating Cognitive Systems (MUCogS) provide a new paradigm on model updating of structural systems. Commonly used numerical modeling techniques, such as finite or boundary elements, provide accurate representations of simple structures but often fail to represent complex structural systems. Model updating techniques are used to enhance these numerical models based on experimental data. Current model updating techniques obtain a single 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. MUCogS can be further enhanced by including software agents to aid the analyst in the decision making process.
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.
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.
Falls and fall injuries continue to be major safety challenges for older adults with dementia. In the long term care setting, falls and near falls often go unreported, leading to missed opportunities for interventions that might prevent future, more serious, and disabling falls. While the literature is replete with reports of fall detection systems that have been developed and tested in laboratory settings (using weight proportionate manikins or adults who have been trained to perform simulated falls), there are few studies that have been conducted in real-world settings. This project builds on our existing research, in which we have developed a falls detection system that is based on structural accelerations. The proposed monitoring system is fully passive, i.e., it is embedded entirely within the environment, and does not require the monitored person to wear any device. Moving beyond existing environmental systems that consist of sound, motion, direct video, the proposed system uses structural vibrations.
The project is a collaboration between the University of South Carolina and Marshall University. The project stablsihes 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 strategy for EFFECTs. 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. Developing a systematic approach that enables other faculty to use EFFECTs is a key aspect for widely disseminating the approach through the engineering education community. To achieve this, the research group is 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.
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 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.
This project is collaboration between scientists and engineers at Clemson University, University of South Carolina, and South Carolina State University. The experimental and modeling efforts of this project are guided by the overarching scientific question: What are the major molecular level chemical, biological, and microbial interactions that control the mobility of radionuclides in natural and engineered systems and how can these molecular and pore scale processes be properly defined and quantified for incorporation into larger scale, coupled experimental systems and reactive transport modeling efforts? The project investigators at the University of South Carolina are Drs. Matta, Flora, Knight, Ziehl and Caicedo. The overall project PI is Dr. Powell at Clemson University. The SDII team is providing expertise in model updating and in the development of cyber-infrastructure for data management, curation and archival.
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.
This project focuses on 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 project 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 methodology utilized 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.
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.