The investigation of a natural phenomenon explores its occurrence in some space-time reference frame. Typically, scientists select a set of observables that represent the phenomenon and record the latter through a spatio-time series defined by the former. Numerical Simulation reproduces a natural phenomenon by representing the space using a geometry mesh and computing the values of observables through time steps. In this work, we present SimDB, which is a system designed to manage numerical simulation data with observable values varying in space-time. We adopt a multidimensional array data model in which dimensions correspond to space, time and numerical simulation trials. The mapping of numerical simulation data to a multi-dimensional array is, however, not trivial. Particularly, for non-uniform dimensions, as is the case of irregular meshes, a naive mapping produces an extremely sparse array, jeopardising query response time. SimDB proposes technique that transforms nun-uniform dimensions in uniform one, producing compact dense regions, which are efficiently accessed by the multi-dimensional system. SimDB is built on top of SciDB to take advantage of its parallel capacity.