Numerical simulation and experimental validation of a multi-step deep drawing process

This paper presents the numerical simulation of an industrial multi-step deep drawing process. A large strain finite element formulation including a hyperelastic elastoplastic constitutive model and a contact-friction law is used to this end where the steel sheet material parameters considered in the analysis are previously derived through a characterization procedure of its mechanical response. The numerical predictions of the final shape and thickness distribution of the blank are compared and discussed with available experimental values measured at the end of three successive drawing steps. In addition, a plastic work-based damage index is used to assess failure occurrence during the process. The damage values computed at the end of the drawing process are found to be lower than that corresponding to rupture in the tensile test, considered here as the threshold of failure, confirming, as observed experimentally, that neither fracture nor necking is developed in the blank during the whole drawing process. Finally, the possibility to carry out a reduced two-step drawing process, obtained by merging the second and third steps of the three-step process, is precluded since the damage criterion predicts in this case excessively large values that indicate that failure may occur in specific zones of the sheet.     

Optimizing location and size of rural schools in Chile

The Chilean Ministry of Education oversees preschool, primary, and secondary education in both urban and rural areas. Many parts of Chile are sparsely populated and there are currently over 4,000 rural schools (almost 38% of all schools in Chile) educating 9.5% of the students in the country. Many of the rural schools are small with only one teacher responsible for instruction of all local students (multigrade schools). The geographical distribution of the rural schools has not been coordinated and this has resulted in unequal utilization of existing schools and some unreasonably long travel distances by students. Good management of the rural schools is fundamental to meeting Chile's goal of providing quality education to its citizens. Seeking to improve the situation, the Ministry of Education ordered a study of the optimal location and size of rural schools with the general goals of reducing the number of lesser quality multigrade schools and reducing student travel distances while maintaining reasonable costs. This paper presents results of this study obtained using an integer linear program that has been embedded in a geographical information system. We present computational results for the entire country. Recommendations include where to open new rural schools as well as where to expand, reduce, close, or leave unchanged existing schools. We show how recommendations are sensitive to key parameters such as the cost of transportation.     

Cyclic staff scheduling: optimization models for some real-life problems

In this work, we propose a general integer programming model to address the staff scheduling problem, flexible enough to be easily adapted to a wide-range of real-world problems. The model is applied with slight changes to two case studies: a glass plant and a continuous care unit, and also to a collection of benchmark instances available in the literature. The emphasis of our approach is on a novel formulation of sequence constraints and also on workload balance, which is tackled through cyclic scheduling. Models are solved using the CPLEX solver. Computational results indicate that optimal solutions can be achieved within a reasonable amount of time.     

Comparison between discrete and continuous analysis of facial expressions,elicited by bitter-tasting beverages in overweight and healthy-weight individuals

The aim of the present study was to compare the information provided by a discrete and continuous data analysis of two emotions (disgust and joy), elicited by bitter-tasting beverages (coffee, yerba mate infusion and grapefruit juice) in two groups with different body mass index (BMI): overweight group (25 < BMI < 30), and healthy-weight control group (18.5 < BMI ≤ 25). Participants (n = 66; 34 females, 32 males) evaluated a total of three consecutive sips of the same beverage (taking one sip every 20 s and registering a continuous video for 60 s). The Wilcoxon test (continuous analysis) showed some changes generated as the drinks were being consumed. The biggest difference was the expression of disgust for coffee in the high BMI group, at the first sip (0–10 s). It represented 27% compared to 2% in normal BMI. The continuous analysis allowed to observe the periods where the differences were greater (0–10 and 40–50 s).     

Microstructural development during crystallization firing of a dental-grade nanostructured lithia-zirconia glass-ceramic

The microstructural development during crystallization firing of a commercially-available dental-grade nanostructured lithia-zirconia glass-ceramic (Vita Suprinity® PC) was unraveled using a wide battery of ex-situ and in-situ characterization techniques. It was found that the milling blocks are slightly crystallized glass-ceramics, with a complex chemical composition and consisting of partially de-polymerized glass plus lithium silicate (Li₂SiO₃) nanocrystals. It was also found that during crystallization firing the glassy matrix first reacts with part of the Li₂SiO₃ to form lithium disilicate (Li₂Si₂O₅) at ～810?820 °C, and then lithium orthophosphate (Li₃PO₄) precipitates from the glass. This results in glass-ceramics with abundant nanocrystals embedded in a sparse zirconosilicate glass matrix (containing many other cations subsumed) that, due to its high viscosity, inhibited crystal growth. Therefore, these dental glass-ceramics are not reinforced with zirconia (ZrO₂) crystals unless over-fired above ～890 °C and at the expense of its singular nanostructure. Finally, this study opens doors for optimizing the clinical performance of these dental glass-ceramics via microstructural tailoring.     

A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding

The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.