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A multi-disciplinary optimization analysis is a highly iterative process that requires a large number of function evaluations for computing the objective functions and the constraints. Metamodels (i.e. response surface methodologies) can be constructed before starting the optimization for each one of the objective functions and the constraint functions. The metamodels can be employed in the multi-discipline optimization instead of high fidelity simulations resulting in significant computational savings. A multi-discipline design optimization of an aircraft wing under aerodynamic and structural analysis considerations is performed in this manner. Design variables associated with the shape of the wing are considered in the CFD simulations, while sizing structural design variables are considered in the structural discipline. At the top system level, a cost type metric is defined for driving the overall design optimization process.

One of the main threats to military vehicles originates from landmine blasts. In order to improve the survivability of the occupants it is important to design a military vehicle for increased occupant safety. Simulation technology that combines modeling of the blast loads from the landmine explosion, the response of the vehicle to the blast load, and the loads developed on the members of an occupant are important factors in this effort. Uncertainties from the soil properties can influence the blast loads and thus the occupants' safety. In this paper, principal component analysis along with metamodel theory are employed for developing fast running models for the response functions of interest. The response functions of interest are the time domain loads which are developed on an occupant's members due to the blast. The fast running models allow assessing the probability level associated with injury for an occupant.

One of the main threats to military vehicles originates from landmine blasts. In order to improve the survivability of the occupants it is important to design a military vehicle for increased occupant safety. Simulation technology that combines modeling of the blast loads from the landmine explosion, the response of the vehicle to the blast load, and the loads developed on the members of an occupant are important factors in this effort. The ability to simulate the landmine explosion is validated first by comparing simulation results to test data collected by gages placed in the ground and above the ground. Combined simulations predicting the damage to a target structure due to a landmine explosion are also compared to test data for further validation. Principal component analysis and metamodel theory is employed for generating fast running models in order to adjust the soil parameters in the simulation models during the correlation effort.

The advancement of numerical methods for acoustics has enhanced the ability to make meaningful predictions of acoustic responses in vehicle passenger compartments, such as those found in automobiles, trucks, and construction equipment. A design objective of growing importance is to isolate the occupants from both structural and air-borne noise. This paper presents how an indirect boundary element formulation can be used to study the effect of holes on the transmission of air-borne sound, and how design changes effect the transmission of sound through heater and air conditioning ducts. The theoretical background of the indirect formulation is also presented. The significance of this method is that it can include openings in the model while considering the acoustic medium on both sides of the mesh. It is also computationally superior to the direct method because the assembled matrices are symmetric.

Numerical models are used for computing the shock response in many areas of engineering applications. Current analysis methods do not account for uncertainties in the model parameters. In addition, when numerical models are calibrated based on test data neither the uncertainty which is present in the test data nor the uncertainty in the model are taken into account. In this paper an approach for model update under uncertainty and error estimation for shock applications is presented. Fast running models are developed for the model update based on principal component analysis and surrogate models. Once the numerical model has been updated the fast running models are employed for performing probabilistic analyses and estimate the error in the numerical solution. The new developments are applied for computing the shock response of large scale structures, updating the numerical model based on test data, and estimating the error in the predictions.