Dataset Information

Application of 3-D Drucker-Prager Material Model to Determine Optimal Operating Parameters of Centrifugal Regeneration Device.

ABSTRACT: The process of metal casting indisposable sand molds is associated with the generation of large amounts of waste, mainly used molding and core sands, from which the molds and cores reproducing the external and internal shapes of the castings were made. It is estimated that about 600 kg of waste can come from the production of 1 ton of casting. The main component of the waste is quartz matrix, which after undergoing appropriate reclamation treatments can be recovered and reused in the production process. This article presents the theoretical foundations regarding the existing methods of quartz matrix recovery and an experimentally justified model of the regeneration process occurring in one of the varieties used in the practice of mechanical regenerators. The goal is to improve the quality of regenerated molding sand by means of liberating the sand grain's surface from the layer of the used binding component. The elastic-plastic material model characterized by the Drucker-Prager yield criterion was used to describe the deformation of the sand layer during treatment performed in a centrifugal regenerator. Conclusions based on the results of numerical calculations, obtained with the use of the software adopting the material point method, enable us to find out how to control the device in a way that ensures a permanent reclamation effect which is independent of the working components that wear out over time.

SUBMITTER: Latas W

PROVIDER: S-EPMC7254343 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Application of 3-D Drucker-Prager Material Model to Determine Optimal Operating Parameters of Centrifugal Regeneration Device.

Łatas Waldemar W Dańko Rafał R Czapla Przemysław P

Materials (Basel, Switzerland) 20200505 9

The process of metal casting indisposable sand molds is associated with the generation of large amounts of waste, mainly used molding and core sands, from which the molds and cores reproducing the external and internal shapes of the castings were made. It is estimated that about 600 kg of waste can come from the production of 1 ton of casting. The main component of the waste is quartz matrix, which after undergoing appropriate reclamation treatments can be recovered and reused in the production ...[more]

PMID: 32380677

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Project description:An epistatic genetic architecture can have a significant impact on prediction accuracies of genomic prediction (GP) methods. Machine learning methods predict traits comprised of epistatic genetic architectures more accurately than statistical methods based on additive mixed linear models. The differences between these types of GP methods suggest a diagnostic for revealing genetic architectures underlying traits of interest. In addition to genetic architecture, the performance of GP methods may be influenced by the sample size of the training population, the number of QTL, and the proportion of phenotypic variability due to genotypic variability (heritability). Possible values for these factors and the number of combinations of the factor levels that influence the performance of GP methods can be large. Thus, efficient methods for identifying combinations of factor levels that produce most accurate GPs is needed. Herein, we employ response surface methods (RSMs) to find the experimental conditions that produce the most accurate GPs. We illustrate RSM with an example of simulated doubled haploid populations and identify the combination of factors that maximize the difference between prediction accuracies of best linear unbiased prediction (BLUP) and support vector machine (SVM) GP methods. The greatest impact on the response is due to the genetic architecture of the population, heritability of the trait, and the sample size. When epistasis is responsible for all of the genotypic variance and heritability is equal to one and the sample size of the training population is large, the advantage of using the SVM method vs. the BLUP method is greatest. However, except for values close to the maximum, most of the response surface shows little difference between the methods. We also determined that the conditions resulting in the greatest prediction accuracy for BLUP occurred when genetic architecture consists solely of additive effects, and heritability is equal to one.

Dataset Information

Application of 3-D Drucker-Prager Material Model to Determine Optimal Operating Parameters of Centrifugal Regeneration Device.

Publications

Application of 3-D Drucker-Prager Material Model to Determine Optimal Operating Parameters of Centrifugal Regeneration Device.

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