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In the paper some methods are presented, with the corresponding practical examples, related to MonteCarlo (MC) techniques for thermal model/test correlation purposes. The MonteCarlo techniques applied to model correlation are intended to be used as an alternative to empirical ‘manual’ correlation techniques, gradients methods, matrix methods based on least square fit minimization. First of all, Design Of Experiments (DoE) tools are used to determine the model response to uncertain parameters and the confidence level of such a response. A sensitivity map is built, allowing the design of the test to maximize the response of the system to the uncertain parameters. Techniques derived from the extreme statistics are used to extrapolate data beyond test limits, with a sufficient confidence in the queue behaviour.

An experimental campaign is presented aiming at the characterization of thermal dissipation of batteries to be used on board of small satellites. A suitably designed device allows to manage automatically the orbital cycling simulation between battery cell charge and discharge. The cell thermal performance is characterized in various combinations of temperature, discharge current and Depth of Discharge. The gathered data are used for providing guidelines in the design of a family of Italian Small Satellites.

In the paper several application techniques of MonteCarlo (MC) method applied to thermal analysis of space vehicles are presented. Although these methods are widely used in other engineering domains, their introduction to the thermal one is quite recent and not fully developed in the industrial practice. This paper aims at showing that, even without demanding computation resources (all what presented has been obtained with a single processor PC) MonteCarlo analysis techniques, in a preliminary design phase, can support and integrate engineering judgment of the thermal designer. In particular, it is exploited the applicability of the method to reduced thermal models, with a clear advantage in terms of computation time. An original approach is proposed, and results are shown. The papers shows the applicability of the MC method to the case when experimental data of the uncertain parameters are available, using the bootstrap re-sampling techniques.

This paper presents a novel fully-automatic remeshing procedure, based on the level-set method and Delaunay triangulation, to model three-dimensional boundary problems and generate a new conformal body-fitted mesh. The proposed methodology is applied to long-term in-flight ice accretion, which is characterized by the formation of extremely irregular ice shapes. Since ice accretion is coupled with the aerodynamic flow field, a multi-step procedure is implemented. The total icing exposure time is subdivided into smaller time steps, and at each time step a three-dimensional body-fitted mesh, suitable for the computation of the aerodynamic flow field around the updated geometry, is generated automatically. The methodology proposed can effectively deal with front intersections, as shown with a manufactured example.

1Restraints constitute the unique and necessary aids for living and working in microgravity conditions in which crewmembers need facilities as support to move around and as restraints while they work. In environments with microgravity, disturbance to the vestibular sense, when it occurs together with conflicting visual and perceptive stimuli, can cause disorientation, vertigo and illusions regarding posture and movement. Therefore, the design of restraints is a critical ingredient of success for crewmembers performance in space during both IVA and EVA activities. Standard restraints and mobility aids are provided on ISS such that all installation, operation, and maintenance can be performed: Foot Restraint, Adjustable Length Tether, Handrails, Adjustable Length Tether and Torso Restraint Assembly. Crewmembers use Standard Foot Restraints and Handrails to improve the movement capacities and the postural stability.

We present a framework for the robust optimization of the heat flux distribution for an anti-ice electro-thermal ice protection system (AI-ETIPS) and iced airfoil performance analysis under uncertain conditions. The considered uncertainty regards a lack of knowledge concerning the characteristics of the cloud i.e. the liquid water content and the median volume diameter of water droplets, and the accuracy of measuring devices i.e., the static temperature probe, uncertain parameters are modeled as uniform random variables. A forward uncertainty propagation analysis is carried out using a Monte Carlo approach. The optimization framework relies on a gradient-free algorithm (Mesh Adaptive Direct Search) and three different problem formulations are considered in this work. Two bi-objective deterministic optimizations aim to minimize power consumption and either minimize ice formations or the iced airfoil drag coefficient.

Very little is currently known of the aerodynamic interaction between neighboring cycloidal rotors. Such knowledge is, however, of crucial importance to tune the controller and rotor disposition of a cyclogiro aircraft. Thus, a three-dimensional computational fluid dynamics (CFD) model is developed, validated, and used to analyze the D-Dalus L1 four-rotor unmanned aircraft operating under several configurations. The model solves the Euler equations using the OpenFOAM toolbox in order to provide fast results on a desktop computer. Validation is performed against thrust forces and flow streamlines obtained during wind tunnel experiments at various flight velocities. Numerical results from CFD match the trends of the experimental data. Flow behavior matches the video footage of the wind tunnel tests. Although boundary layer effects are neglected, satisfactory results are obtained both qualitatively and quantitatively.