%0 Generic %D 2019 %T Parametric shape optimization for combined additive- subtractive manufacturing %A C. Altenhofen %A M. Attene %A O. Barrowclough %A M. Chiumenti %A M. Livesu %A F. Marini %A M. Martinelli %A V. Skytt %A L. Tamellini %K Additive manufacturing %K parametric shape optimization %X In the industrial practice, additive manufacturing processes are often followed by post-processing operations such as subtractive machining, milling, etc. to achieve the desired surface quality and dimensional accuracy. Hence, a given part must be 3D printed with extra material to enable such finishing phase. This combined additive/subtractive technique can be optimized to reduce manufacturing costs by saving printing time and reducing material and energy usage. In this work, a numerical methodology based on parametric shape optimization is proposed for optimizing the thickness of the extra material, allowing for minimal machining operations while ensuring the finishing requirements. Moreover, the proposed approach is complemented by a novel algorithm for generating inner structures leading to reduced distortion and improved weight reduction. The computational effort induced by classical constrained optimization methods is alleviated by replacing both the objective and constraint functions by their sparse-grid surrogates. Numerical results showcase the effectiveness of the proposed approach. %B IMATI Report Series %I CNR-IMATI %C Pavia %P 27 %8 06/2019 %G eng %9 Preprint %0 Generic %D 2016 %T Comparing methods for the approximation of rainfall fields in environmental applications %A G. Patané %A A. Cerri %A V. Skytt %A S. Pittaluga %A S. Biasotti %A D. Sobrero %A T. Dokken %A M. Spagnuolo %K Precipitation analysis %K Storm tracking %K Surface approximation %X Digital environmental data are becoming commonplace and the amount of information they provide is huge, yet complex to process, due to the size, variety, and dynamic nature of the data captured by sensing devices. The paper discusses an evaluation framework for comparing methods to approximate observed rain data, in real conditions of sparsity of the observations. The novelty brought by this experimental study stands in the geographical area and heterogeneity of the data used for evaluation, aspects which challenge all approximation methods. The Liguria region, located in the north-west of Italy, is a complex area for the orography and the closeness to the sea, which cause complex hydro-meteorological events. The observed rain data are highly heterogeneous: two data sets come from measured rain gathered from two different rain gauge networks, with different characteristics and spatial distribution over the Liguria region; the third data set come from weather radar, with a more regular coverage of the same region but a different veracity. Finally, another novelty of the paper is brought by the proposal of an application-oriented perspective on the comparison. The approximation models the rain field, whose maxima and their evolution is essential for an effective monitoring of meteorological events. Therefore, we adapt a storm tracking technique to the analysis of the displacement of maxima computed by the different methods. %B IMATI Report Series %I CNR-IMATI %C Genova %P 26 p. %8 February %G eng %U http://irs.imati.cnr.it/reports/irs16-10 %9 Technical Report