This paper deals with developing an efficient Robust Design Optimization (RDO) framework. The goal is to obtain an aerodynamic shape that is less sensitive to small random geometry perturbations and to uncertain operational conditions. The initial shape is the RAE2822 airfoil which is parameterized with 10 design variables. The robust design formulation used is based on an expectation measure. ...

Using surrogate models in place of high fidelity engineering simulations can help reduce design cycle times and cost by enabling rapid analysis of alternative designs. Surrogate models can also be used in a deliverable product as an efficient replacement for large lookup tables or as a soft sensor to predict quantities than cannot be directly measured. Many different surrogate modeling techniqu...

We investigate surrogate-assisted strategies for derivative-free optimization using the mesh adaptive direct search (MADS) blackbox optimization algorithm. In particular, we build an ensemble of surrogate models to be used within the search step of MADS, and examine different methods for selecting the best model for a given problem at hand. To do so, we introduce an order-based error tailored t...

nowadays, due to increasing the complexity of ic engines, calibration task becomes more severe and the need to use surrogate models for investigating of the engine behavior arises. accordingly, many black box modeling approaches have been used in this context among which network based models are of the most powerful approaches thanks to their flexible structures. in this paper four network base...

A typical approach in surrogate-based modeling is to assess the performance of alternative surrogate models and select the model that performs the best. In this paper, we extend the utility of an ensemble of surrogates to: i) identify regions of high uncertainties at locations where predictions of surrogates widely differ, and ii) provide a more robust approximation approach. We explore the pos...

Chemical processes with complex reaction mechanisms generally lead to dynamic models which, while beneficial for predicting and capturing the detailed process behavior, are not readily amenable for direct use in online applications related to process operation, optimisation, control, and troubleshooting. Surrogate models can help overcome this problem. In this research article, the first part f...

As we strive to solve more complex and integrated optimization problems, there is an increasing demand for process models that are sufficiently accurate as well as computationally efficient. In this work, we develop an algorithm for the data-driven construction of a type of surrogate models that can be formulated as mixed-integer linear programs yet still provide good approximations of nonlinea...

Fracture probabilities derived from the surrogate FRAX model for Armenia were compared to those from the model based on regional estimates of the incidence of hip fracture. Disparities between the surrogate and authentic FRAX models indicate the importance of developing country-specific FRAX models. Despite large differences between models, differences in the rank order of fracture probabilitie...

This paper describes an optimization procedure to design thermoplastic composite panels under axial compressive load conditions. Minimum weight is the goal. The panel design is subject to buckling constraints. The presence of the bending-twisting coupling and of particular boundary conditions does not allow an analytical solution for the critical buckling load. Surrogate models are used to appr...

OBJECTIVES To explore the use of surrogate outcomes in Health Technology Assessment (HTA) and provide a basis for guidance for their future use, validation and reporting. This report focuses on the role of surrogate outcomes in cost-effectiveness models (CEMs) within UK HTA Programme reports. DATA SOURCES Reports published in the UK HTA Programme monograph series in 2005 and 2006 formed the s...