Conferences, Lectures, & Seminars
Events for September
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CEE Seminar
Fri, Sep 06, 2013 @ 04:00 PM - 05:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Drs. Amy Childress and George Ban-Weiss, VSoE- Civil and Environmental Engineering
Talk Title: TBA
Abstract:
TBA
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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CEE Ph.D. Seminar
Fri, Sep 13, 2013 @ 04:00 PM - 05:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Shentong Lu , CE Ph.D. Candidates
Talk Title: Investigation of Harbor Oscillation Induced by Long Wave with Numerical Model
Abstract:
In this study, we would introduce and validate one Boussinesq model (Mike 21), which was developed by Danish Hydraulic Institute based on the earlier work of Madsen and Sorensen. Six cases of experiment would be used to investigate the reliability and accuracy of the present model. After the verification, we would apply this model into four real harbors and inspect the response caused by an idealized incident wave train (white noise analysis). By comparing the first resonance mode with earlier work and observation, we noticed that the effect of nonlinearity and dispersion did not appear to be significant in harbor oscillation. In addition, the impact of various tidal levels was also studied to determine the reason that caused the increased number of resonance mode in some tsunami scenarios.
This presentation is back-to-back with Ali Bolourchi
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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CEE Ph.D. Seminar
Fri, Sep 13, 2013 @ 04:00 PM - 05:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Ali Bolourchi, Ph.D. Candidate, Astani Civil and Environmental Engnieering
Talk Title: Studies into computational intelligence approaches for the identification of complex nonlinear systems
Abstract:
This paper builds on advancements in the field of Computational Intelligence to develop a robust approach that combines stochastic optimization methods utilizing Genetic Programming, together with nonlinear evolutionary optimization methods for optimizing the parameters, and Computer Algebra techniques that involve symbolic manipulation of expressions during the course of evolution, to “discover” a parsimonious differential operator that represents an optimum match to the governing differential equation of the target complex nonlinear system, and subsequently discloses the correct nature of the investigated system. The proposed scheme requires input and output data only, without postulating any model-class in advance. This technique can also discover an accurate single-expression, with direct
physical interpretation, that represents the governing multiregion (response domain) equations of systems that incorporate certain classes of nonlinear phenomena (such as yielding). Yet, unlike many conventional non-parametric techniques whose approximations result in undesirable oscillations around unsmooth points, automatic incorporation of discontinuous basis functions in this approach eliminates the need of such approximations and their concomitant errors. A variety of highly nonlinear and hysteretic phenomena are considered to assess the capabilities and the generalization extent of the suggested approach. It is shown that the method of this paper provides a robust methodology for developing reduced-order, reduced-complexity, computational models (in the form of governing differential equations) that can be used for obtaining high-fidelity models that reflect the correct
“physics” of the underlying phenomena.
Presentation is back-to-back with Shentong Lu
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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CEE Ph. D. Seminar
Fri, Sep 20, 2013 @ 04:00 PM - 05:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ram Rajagopal, Stanford University
Talk Title: Demand Management in Smart Grids: Architecture, Data Analytics and Control.
Abstract: Increased penetration of renewable generation in the grid has required the development of novel power management approaches capable of handling the significant increase in uncertainty. A major focus has been demand-side management and control, including investigations of demand response and load scheduling mechanisms. Yet, the performance and scalability of existing methodologies is limited, and little is known about the broader potential of these mechanisms in realistic scenarios. Moreover, in many instances demand side management practice has failed to account appropriately for the additional uncertainty generated by consumer behavior. This talk presents a architecture for demand management that organizes consumers around communities (or clusters). Power management is implemented as a multi-scale hierarchical risk limiting control solution in such communities. Scalable demand-side behavioral analytics for segmenting, targeting, ranking and community design are presented, relying on new observations of consumer behavior from the large amounts of data collected in smart grids. Novel performance metrics for the architecture are estimated from the data to illustrate the potential of the proposed approach. If time permits, some applications to parking management are also presented.
Bio: Ram Rajagopal is an Assistant Professor of Civil and Environmental Engineering at Stanford University, where he directs the Stanford Sustainable Systems Lab (S3L), focused on large scale monitoring, data analytics and stochastic control for infrastructure networks, in particular energy and transportation. His current research interests in power systems are in integration of renewables, smart distribution systems and demand-side data analytics. Prior to his current position he was a DSP Research Engineer at National Instruments and a Visiting Research Scientist at IBM Research. He holds a Ph.D. in Electrical Engineering and Computer Sciences and an M.A. in Statistics, both from the University of California Berkeley, Masters in Electrical and Computer Engineering from University of Texas, Austin and Bachelors in Electrical Engineering from the Federal University of Rio de Janeiro. He is a recipient of the Powell Foundation Fellowship, Berkeley Regents Fellowship and the Makhoul Conjecture Challenge award. He holds more than 30 patents from his work, and has advised or founded various companies in the fields of sensor networks, power systems and data analytics.
Pizza is served following the presentation in KAP 147.
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes