In this study, two different calibration approaches, the multi-criteria and the generalized likelihood uncertainty estimation (GLUE) method, were used to quantify uncertainties originated from the use of multi-site discharge observations and the presence of equifinal solutions.
In the core of our approach, the multi-resolution volumetric model is used.
In the proposed approach, the multi-resolution volumetric model is based on designing a customized model, composed of the following stages (a) Reconstructing a multi-resolution volumetric model of a porous structure; (b) Defining ROIs and their resolution properties; and (c) Constructing an adaptive model.
With respect to the pairwise approach, the multi-view approach solved the alignment failures of the Cherub and the Hurricane datasets by exploiting the cumulative information available.
In the present approach, the multi-objective nature of problem is converted into single objective (normalized objective function) and Pareto front is developed by changing the weights for both cost and resilience measure.
The techniques that approach the multi-mobile-DOA estimation problem by applying advanced statistics mostly rely on some variation of the popular technique known as Multiple Signal Classification (MUSIC) algorithm [1].
Acceptance of this process or thinking, or not thinking for that matter, is the best way to approach the multi-disciplinary art of Tremel.
This model is solved in three stages: (1) a Jackson network determines the queuing parameters, (2) an Lp-metric approach makes the multi-objectives into a single objective, and (3) an efficient Lagrangian relaxation based on a sub-gradient approach solves the presented model.
In the Monte Carlo depletion approach, the McCARD multi-cycle core depletion calculation was performed up to an equilibrium cycle, involving a great details of core geometry and material inventory.
The methodology is partially based in the methodological approach of the Multi-hazard Loss Estimation Methodology (Hazus) developed by the Federal Emergency Management Agency (FEMA).
The details on the implementation of this modeling approach in the multi-sites framework will be discussed in a future work.
