Mechanical MNIST: A benchmark dataset for mechanical metamodels

Metamodels, or models of models, map defined model inputs to defined model outputs. Typically, metamodels are constructed by generating a dataset through sampling a direct model and training a machine learning algorithm to predict a limited number of model outputs from varying model inputs. When metamodels are constructed to be computationally cheap, they are an invaluable tool for applications ranging from topology optimization, to uncertainty quantification, to multi-scale simulation. By nature, a given metamodel will be tailored to a specific dataset. However, the most pragmatic metamodel type and structure will often be general to larger classes of problems. At present, the most pragmatic metamodel selection for dealing with mechanical data has not been thoroughly explored. Drawing inspiration from the benchmark datasets available to the computer vision research community, we introduce a benchmark data set (Mechanical MNIST) for constructing metamodels of heterogeneous material undergoing large deformation. We then show examples of how our benchmark dataset can be used, and establish baseline metamodel performance. Because our dataset is readily available, it will enable the direct quantitative comparison between different metamodeling approaches in a pragmatic manner. We anticipate that it will enable the broader community of researchers to develop improved metamodeling techniques for mechanical data that will surpass the baseline performance that we show here.Accepted manuscrip

Aspecten van filosofische verklaring

Opzet van dit artikel is een antwoord te geven op de vraag wat de minimale vereisten zijn waaraan een verklaring moet voldoen om een filosofische verklaring te zijn. Achtereenvolgens gaan wij na hoe de filosofische verklaring zich verhoudt tot de andere activiteiten in het domein van de filosofie, en hoe zij zich verhoudt tot de verklaring in het domein van de wetenschap. Om de eigenheid van de filosofische verklaring duidelijk in het licht te stellen, nemen wij de ‘klassieke’ analyse van wetenschappelijke verklaringen als referentiepunt. Uit die ‘vergelijking’ blijkt dat de filosofische verklaring zich van de wetenschappelijke verklaring onderscheidt, niet door het soort vragen dat zij behandelt, maar door haar zuiver theoretische aard en door haar logica. Waar de wetenschappelijke verklaring ‘wat verklaring verlangt’ afleidt uit de uitleg, brengt de filosofie haar uitleg binnen in ‘wat zij wil verklaren’. Volledigheidshalve behandelen wij ook nog de vraag naar criteria waarmee wij de kwaliteit van een filosofische verklaring kunnen toetsen, en sluiten deze uiteenzetting af met een korte reflectie over het nut van de filosofie in het algemeen en van filosofische verklaringen in het bijzonder

Information technology as boundary object for transformational learning

Collaborative work is considered as a way to improve productivity and value generation in construction. However, recent research demonstrates that socio-cognitive factors related to fragmentation of specialized knowledge may hinder team performance. New methods based on theories of practice are emerging in Computer Supported Collaborative Work and organisational learning to break these knowledge boundaries, facilitating knowledge sharing and the generation of new knowledge through transformational learning. According to these theories, objects used in professional practice play a key role in mediating interactions. Rules and methods related to these practices are also embedded in these objects. Therefore changing collaborative patterns demand reconfiguring objects that are at the boundary between specialized practices, namely boundary objects. This research is unique in presenting an IT strategy in which technology is used as a boundary object to facilitate transformational learning in collaborative design work

A revised HRD for individual components of binary systems from BaSeL BVRI synthetic photometry. Influence of interstellar extinction and stellar rotation

Johnson BVRI photometric data for individual components of binary systems have been provided by ten Brummelaar et al. (2000). This is essential because such binaries could play a critical role in calibrating the single-star stellar evolution theory. While they derived the effective temperature from their estimated spectral type, we infer metallicity-dependent Teffs from a minimizing method fitting the B-V, V-R and V-I colours. For this purpose, a grid of 621,600 flux distributions were computed from the Basel Stellar Library (BaSeL 2.2) of model-atmosphere spectra, and their theoretical colours compared with the observed photometry. As a matter of fact, the BaSeL colours show a very good agreement with the BVRI metallicity-dependent empirical calibrations of Alonso et al. (1996), temperatures being different by 3+-3 % in the range 4000-8000 K for dwarf stars. Before deriving the metallicity-dependent Teff from the BaSeL models, we paid particular attention to the influence of reddening and stellar rotation. A comparison between the MExcess code and neutral hydrogen column density data shows a good agreement for the sample but we point out a few directions where the MExcess model overestimates the E(B-V) colour excess. Influence of stellar rotation on the BVRI colours can be neglected except for 5 stars with large vsini, the maximum effect on temperature being less than 5%. Our final results are in good agreement with previous spectroscopic determinations available for a few primary components, and with ten Brummelaar et al. below ~10,000 K. Nevertheless, we obtain an increasing disagreement with their Teffs beyond 10,000 K. Finally, we provide a revised Hertzsprung-Russell diagram for the systems with the more accurately determined temperatures. (Abridged)Comment: 11 pages, accepted for publication in A&