Robust design and optimization of stochastic wind-excited systems: an adaptive kriging-based approach

This research proposes a robust design framework for wind-excited systems in which performance is estimated at a system level in terms of state-of-the-art performance-based design metrics. In particular, the robust design problem is formulated as a stochastic optimization with objective the minimization of the variance of the performance metric. Constraints are also imposed on the initial cost of the system and expected value of the performance metric. To effectively treat the performance metrics within the optimization problem, adaptive kriging models of the deagreggated loss metrics are defined in terms of the second order statistics of the demands. By then relating the demand statistics to the design variables through the concept of the Auxiliary Variable Vector, a deterministic optimization sub-problem is defined that can handle high-dimensional design variable vectors and general stochastic excitation. By solving a sequence of sub-problems, each formulated in the solution of the previous, solutions to the original robust design problem are found. A case study consisting in a large-scale system subject to stochastic wind excitation is used to illustrate the applicability of the proposed framework.This research effort was supported in part by the National Science Foundation (NSF) through grants CMMI-1462084 and CMMI-1562388. This support is gratefully acknowledged

Performance optimization of uncertain and dynamic high-dimensional wind-excited systems

This paper focuses on the development of an efficient design optimization framework for wind-excited systems that is capable of handling not only high-dimensional and complex probability spaces, but also high-dimensional spaces of design parameters. Data-driven simulation models are utilized in assessing the system-level probabilistic measures. To efficiently solve the performance-based design optimization problem, a framework is proposed that is based on approximately decoupling the stochastic simulation from the optimization process. Local approximation models, constructed from results of a single stochastic simulation, are used to define a deterministic composite function that relates the design parameters to the system-level performance metrics. The explicit nature of this relationship is then exploited to define a sequence of deterministic optimization sub-problems that yield solutions to the original stochastic optimization problem. To illustrate the applicability of the proposed approach, a large-scale building system is optimized under stochastic wind tunnel-informed excitations and subject to system-level loss constraints.This research effort was supported in part by the National Science Foundation (NSF) through grants CMMI-1462084 and CMMI-1562388. This support is gratefully acknowledged

Efficient Uncertainty Propagation through Inelastic Wind-Excited Structures Subject to Stochastic Excitation

The growing interest in applying probabilistic performance-based design to wind excited structural systems has increased the need for models capable of efficiently estimating the inelastic responses of these systems. This paper outlines the development of such a model that combines the theory of dynamic shakedown with distributed plasticity and simulation methods, providing a framework for estimating any system-level probabilistic performance metric of interest. The potential of the proposed framework is illustrated on a full scale three dimensional building.This research effort was supported in part by the National Science Foundation (NSF) under Grant No. CMMI-1462084 and the Magnusson Klemencic Associates (MKA) Foundation under Research Grant Agreement #A101. This support is gratefully acknowledged

Probabilistic Quantification of Hurricane Resilience of Communities through a Distributed Simulation Platform

Resilience is an essential requirement in mitigating the effects of natural hazards such as hurricanes. This paper presents a framework to probabilistically quantify the damage of residential communities subject to hurricane hazards which is an essential step in quantifying community resilience. An engineering-based vulnerability model is developed for typical residential buildings. In particular, damage due to the two mechanisms of net pressure and wind-borne debris impact on the envelope components is considered. By integrating full hurricane wind field models into the framework, damage can be estimated for any given hurricane category and storm track. A distributed simulation platform, using Lightweight Communications and Marshalling (LCM) libraries, is proposed for modeling the debris-induced interdependencies between the damages sustained by the buildings defining the community.This work was supported by the National Science Foundation (NSF) through grants ACI-1638186 and CMMI-1562388. Any opinions, findings, conclusions, and recommendations expressed in this work are those of the authors and do not necessarily reflect the views of the sponsors

The Cholecystectomy As A Day Case (CAAD) Score: A Validated Score of Preoperative Predictors of Successful Day-Case Cholecystectomy Using the CholeS Data Set

Background Day-case surgery is associated with significant patient and cost benefits. However, only 43% of cholecystectomy patients are discharged home the same day. One hypothesis is day-case cholecystectomy rates, defined as patients discharged the same day as their operation, may be improved by better assessment of patients using standard preoperative variables. Methods Data were extracted from a prospectively collected data set of cholecystectomy patients from 166 UK and Irish hospitals (CholeS). Cholecystectomies performed as elective procedures were divided into main (75%) and validation (25%) data sets. Preoperative predictors were identified, and a risk score of failed day case was devised using multivariate logistic regression. Receiver operating curve analysis was used to validate the score in the validation data set. Results Of the 7426 elective cholecystectomies performed, 49% of these were discharged home the same day. Same-day discharge following cholecystectomy was less likely with older patients (OR 0.18, 95% CI 0.15–0.23), higher ASA scores (OR 0.19, 95% CI 0.15–0.23), complicated cholelithiasis (OR 0.38, 95% CI 0.31 to 0.48), male gender (OR 0.66, 95% CI 0.58–0.74), previous acute gallstone-related admissions (OR 0.54, 95% CI 0.48–0.60) and preoperative endoscopic intervention (OR 0.40, 95% CI 0.34–0.47). The CAAD score was developed using these variables. When applied to the validation subgroup, a CAAD score of ≤5 was associated with 80.8% successful day-case cholecystectomy compared with 19.2% associated with a CAAD score >5 (p < 0.001). Conclusions The CAAD score which utilises data readily available from clinic letters and electronic sources can predict same-day discharges following cholecystectomy

An integrated topology optimization framework for three‐dimensional domains using shell elements

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163928/1/tal1817_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163928/2/tal1817.pd