Effects of interstitial oxygen on microstructure and mechanical properties of Ti-48Al-2Cr-2Nb with fully lamellar and duplex microstructures

The effect of added oxygen in the range of 1000 to 4000 wt ppm on the microstructures of a Ti-48Al-2Cr-2Nb alloy has been investigated and compared to the microstructures for a high-purity alloy. For specimens cooled from theα phase, interstitial oxygen stabilizes the lamellar microstructure with respect toγ grains, with higher than equilibrium values for theα ₂ volume fraction. For specimens cooled from theα +γ phase field, the lamellar microstructure still tends to be favored by oxygen, but it is found that the phase volume fractions are not significantly different from equilibrium values. This suggests that interstitial O essentially reduces the kinetics of theα toα +γ transformation. Thus, interstitial oxygen will have a strong effect on microstructures obtained by continuous cooling fromα, but significantly less on those, such as the duplex microstructure, obtained by long treatment in theα +γ phase field. In general, increased O content is well correlated with reduced ductility. Finally, the role of interstitial oxygen on this phase transformation is discussed.     

Experimental Investigation of the Recovery of Soaked Paper Using Evaporative Freeze Drying

The aim of this article is to develop an experiment and a procedure to investigate the restoration of water-damaged paper and archival materials using freeze drying in order to allow a reproducible test and comparison of the influence of different operating conditions on drying time and restored paper quality. Firstly, a reproducible method for the preparation of soaked samples simulating water-damaged paper has been developed. Then, the samples have been freeze-dried in a laboratory-scale apparatus that allowed monitoring the temperature as well as the weight of the samples. The technique of evaporative freezing, which reduces the drying time required, has been used in this case. An innovative procedure for the visualization of the progress of the drying process has been validated, thus allowing the validation of a simple phenomenological model of the time evolution of the ice core volume; in addition, data on the residual moisture of the dried paper sheets in different zones have been given. Finally, optimization of this particular drying process by using simple or more sophisticated approaches has been discussed.     

Statics Aware Grid Shells

We introduce a framework for the generation of polygonal gridshell architectural structures, whose topology is designed in order to excel in static performances. We start from the analysis of stress on the input surface and we use the resulting tensor field to induce an anisotropic nonEuclidean metric over it. This metric is derived by studying the relation between the stress tensor over a continuous shell and the optimal shape of polygons in a corresponding gridshell. Polygonal meshes with uniform density and isotropic cells under this metric exhibit variable density and anisotropy in Euclidean space, thus achieving a better distribution of the strain energy over their elements. Meshes are further optimized taking into account symmetry and regularity of cells to improve aesthetics. We experiment with quad meshes and hexdominant meshes, demonstrating that our gridshells achieve better static performances than stateoftheart gridshells.     

When simulated environments make the difference: the effectiveness of different types of training of car service procedures

An empirical analysis was performed to compare the effectiveness of different approaches to training a set of procedural skills to a sample of novice trainees. Sixty-five participants were randomly assigned to one of the following three training groups: (1) learning-by-doing in a 3D desktop virtual environment, (2) learning-by-observing a video (show-and-tell) explanation of the procedures, and (3) trial-and-error. In each group, participants were trained on two car service procedures. Participants were recalled to perform a procedure either 2 or 4 weeks after the training. The results showed that: (1) participants trained through the virtual approach of learning-by-doing performed both procedures significantly better (i.e. p < .05 in terms of errors and time) than people of non-virtual groups, (2) the virtual training group, after a period of non-use, were more effective than non-virtual training (i.e. p < .05) in their ability to recover their skills, (3) after a (simulated) long period from the training—i.e. up to 12 weeks—people who experienced 3D environments consistently performed better than people who received other kinds of training. The results also suggested that independently from the training group, trainees’ visuospatial abilities were a predictor of performance, at least for the complex service procedure, adj R ² = .460, and that post-training performances of people trained through virtual learning-by-doing are not affected by learning styles. Finally, a strong relationship (p < .001, R ² = .441) was identified between usability and trust in the use of the virtual training tool—i.e. the more the system was perceived as usable, the more it was perceived as trustable to acquire the competences.     

Binarised regression tasks: methods and evaluation metrics

Some supervised tasks are presented with a numerical output but decisions have to be made in a discrete, binarised, way, according to a particular cutoff. This binarised regression task is a very common situation that requires its own analysis, different from regression and classification—and ordinal regression. We first investigate the application cases in terms of the information about the distribution and range of the cutoffs and distinguish six possible scenarios, some of which are more common than others. Next, we study two basic approaches: the retraining approach, which discretises the training set whenever the cutoff is available and learns a new classifier from it, and the reframing approach, which learns a regression model and sets the cutoff when this is available during deployment. In order to assess the binarised regression task, we introduce context plots featuring error against cutoff. Two special cases are of interest, the \( UCE \) and \( OCE \) curves, showing that the area under the former is the mean absolute error and the latter is a new metric that is in between a ranking measure and a residual-based measure. A comprehensive evaluation of the retraining and reframing approaches is performed using a repository of binarised regression problems created on purpose, concluding that no method is clearly better than the other, except when the size of the training data is small.     

Modelling of interfacial mass transfer in microfluidic solvent extraction: part II. Heterogeneous transport with chemical reaction

The use of a microfluidic device in determining the extraction kinetics of Co^II ions by di-(2-ethylhexyl) phosphoric acid (DEHPA) was demonstrated. Experimental data obtained using a Y-Y-shaped microchannel were modelled using a finite volume method. The contributions of diffusion and reaction transport resistances to the overall rate of mass transfer were obtained. A diffusion-controlled transfer assumption could not account for the experimental data, confirming that transport occurs under a mixed reaction–diffusion resistance regime. The reaction rate constant was determined to be $(2.4 \pm 0.6) \times 10^{-10}$  m/s, in good agreement with corresponding Lewis cell measurements from the literature.     

Laser pyrolysis in papers and patents

Journal of Intelligent Manufacturing - This paper presents a critical review of laser pyrolysis. Although this technology is almost 60&nbsp;years old, in literature many researchers, both from...     

AlphaPilot: autonomous drone racing

Autonomous Robots - This paper presents a novel system for autonomous, vision-based drone racing combining learned data abstraction, nonlinear filtering, and time-optimal trajectory planning. The...     

Herding stochastic autonomous agents via local control rules and online target selection strategies

Autonomous Robots - We propose a simple yet effective set of local control rules to make a small group of “herder agents” collect and contain in a desired region a large ensemble of...