Traditional factorial designs for evaluating interactions among chemicals in a mixture may be prohibitive when the number of chemicals is large. Using a mixture of chemicals with a fixed ratio (mixture ray) results in an economical design that allows estimation of additivity or nonadditive interaction for a mixture of interest. This methodology is extended easily to a mixture with a large numbe...

The problem with computer model calibration by tuning the parameters associated models is significant in many engineering and scientific applications. Although several methods have been established to estimate parameters, research focusing on design of remains limited. Therefore, this paper proposes a sequential experiment based D-optimal criterion, which can efficiently tune while improving pr...

this study concerns the scope to improve water flooding in heterogeneous reservoirs. we used an existing, in-house developed, optimization program consisting of a reservoir simulator in combination with an adjoint-based optimal control algorithm. in particular we aimed to examine the scope for optimization in a two-dimensional horizontal reservoir containing a single high permeable streak, as a...

We review recent results obtained by the authors on the approximability of a family of combinatorial problems arising in optimal experimental design. We first recall a result based on submodularity, which states that the greedy approach always gives a design within 1 − 1/e of the optimal solution. Then, we present a new result on the design found by rounding the solution of the continuous relax...

Finding optimal designs for experiments for non-linear models and dependent data is a challenging task. We show how the problem simplifies when the search is restricted to designs that are minimally supported; that is, the number of distinct runs (treatments) is equal to the number of unknown parameters, p, in the model. Under this restriction, the problem of finding a locally or pseudo-Bayesia...

Accurate battery health modeling allows one to make better design decisions, enables health conscious control, and allows for feed-forward State of Health estimation. However, experiments are necessary in order to obtain and validate these models. Unfortunately, battery health experiments are costly in terms of time, person-hours, and equipment. This makes it extremely important to minimize the...

We discuss two experimental designs and show how to use them to evaluate difficult empirical combinatorial problems. We restrict our analysis here to the knapsack problem but comment more generally on the use of computational testing to analyze the performances of algorithms.