An improved procedure for obtaining and maintaining well characterized partial water saturation states on concrete samples to be used for mass transport tests

A conditioning procedure is proposed allowing to install into the concrete specimens any selected value of water saturation degree with homogeneous moisture distribution. This is achieved within the least time and the minimum alteration of the concrete specimens. The protocol has the following steps: obtaining basic drying data at 50 °C (water absorption capacity and drying curves); unidirectional drying of the specimens at 50 °C until reaching the target saturation degree values; redistribution phase in closed containers at 50 °C (with measurement of the quasi-equilibrium relative humidities); storage into controlled environment chambers until and during mass transport tests, if necessary. A water transport model is used to derive transport parameters of the tested materials from the drying data, i.e., relative permeabilities and apparent water diffusion coefficients. The model also allows calculating moisture profiles during isothermal drying and redistribution phases, thus allowing optimization of the redistribution times for obtaining homogeneous moisture distributions.

Constraint qualifications in linear vector semi-infinite optimization

Linear vector semi-infinite optimization deals with the simultaneous minimization of finitely many linear scalar functions subject to infinitely many linear constraints. This paper provides characterizations of the weakly efficient, efficient, properly efficient and strongly efficient points in terms of cones involving the data and Karush–Kuhn–Tucker conditions. The latter characterizations rely on different local and global constraint qualifications. The global constraint qualifications are illustrated on a collection of selected applications.

Constraint qualifications in convex vector semi-infinite optimization

Convex vector (or multi-objective) semi-infinite optimization deals with the simultaneous minimization of finitely many convex scalar functions subject to infinitely many convex constraints. This paper provides characterizations of the weakly efficient, efficient and properly efficient points in terms of cones involving the data and Karush–Kuhn–Tucker conditions. The latter characterizations rely on different local and global constraint qualifications. The results in this paper generalize those obtained by the same authors on linear vector semi-infinite optimization problems.