A constrained‐optimization methodology for the detection phase in contact mechanics simulations

The detection phase in computational contact mechanics can be subdivided into a global search and a local detection. When potential contact is detected by the former, a rigorous local detection determines which surface elements come or may come in contact in the current increment. We first introduce a rigorous definition of the closest point for non‐differentiable lower‐dimensional manifolds. We then simplify the detection by formulating an optimization problem subject to inequality constraints. The formulation is then solved using different techniques from the field of mathematical optimization, for both linear and quadratic finite element meshes. The resulting general and robust detection scheme is tested on a set of problems and compared with other techniques commonly used in computational geometry. Copyright © 2013 John Wiley & Sons, Ltd.     

The role of K2O on sintering and crystallization of glass powder compacts in the Li2O–K2O–Al2O3–SiO2 system

The effects of K₂O content on sintering and crystallization of glass powder compacts in the Li₂O–K₂O–Al₂O₃–SiO₂ system were investigated. Glasses featuring SiO₂/Li₂O molar ratios of 2.69–3.13, far beyond the lithium disilicate (LD-Li₂Si₂O₅) stoichiometry, were produced by conventional melt-quenching technique. The sintering and crystallization behaviour of glass powders was explored using hot stage microscopy (HSM), scanning electron microscopy (SEM), differential thermal (DTA) and X-ray diffraction (XRD) analyses. Increasing K₂O content at the expense of SiO₂ was shown to lower the temperature of maximum shrinkage, eventually resulting in early densification of the glass-powder compacts. Lithium metasilicate was the main crystalline phase formed upon heat treating the glass powders with higher amounts of K₂O. In contrast, lithium disilicate predominantly crystallized from the compositions with lower K₂O contents resulting in strong glass–ceramics with high chemical and electrical resistance. The total content of K₂O should be kept below 4.63 mol% for obtaining LD-based glass–ceramics.     

Robust method to provide exponential convergence of model parameters solving linear time-invariant plant identification problem

The scope of this research is a problem of parameters identification of a linear time-invariant plant, which (1) input signal is not frequency-rich, (2) is subjected to initial conditions and external disturbances. The memory regressor extension (MRE) scheme, in which a specially derived differential equation is used as a filter, is applied to solve the above-stated problem. Such a filter allows us to obtain a bounded regressor value, for which a condition of the initial excitation (IE) is met. Using the MRE scheme, the recursive least-squares method with the forgetting factor is used to derive an adaptation law. The following properties have been proved for the proposed approach. If the IE condition is met, then: (1) the parameter error of identification is bounded and converges to zero exponentially (if there are no external disturbances) or to a set (in the case of them) with an adjustable rate, (2) the parameters adaptation rate is a finite value. The above-mentioned properties are mathematically proved and demonstrated via simulation experiments.     

Metastable Sigma-phase Formation by Crystallization of Amorphous Fe-Si-B and Fe-Cr-V-B Alloys

Initial stages of crystallization of amorphous iron base alloys were investigated by means of transmission electrone microscopy, X-ray diffraction, differential thermal analysis. Metastable phase with structure type of sigma phase (e.g., in Fe-Cr alloys) was observed in melt spun ribbons by rapid heating or annealing at temperatures below the first exothermic peak of DTA curve. The composition of 6-phase is close to that of amorphous matrix—it contains a considerable amount of metalloid atoms. Sigma-phase is formed in Fe-Si-B alloys which do not contain metal atoms other than Fe. Sigma phase appears also as an intermediate stage before formation of nanocrystalline finemet-type structure on the base of -Fe in Fe-V-B alloy.     

Robust topology optimization using a posteriori error estimator for the finite element method

In our work, we consider the classical density-based approach to the topology optimization. We propose to modify the discretized cost functional using a posteriori error estimator for the finite element method. It can be regarded as a new technique to prevent checkerboards. It also provides higher regularity of solutions and robustness of results.     

A Sol–Gel Derived CuOx/Al2O3–ZrO2 Catalyst for the Selective Reduction of NO by Propane in the Presence of Excess Oxygen

Copper catalysts supported on alumina-doped zirconia were prepared by sol–gel processing followed by supercritical drying or aging in the mother solution at 100°C. After drying and calcination, the catalyst supports were impregnated with a copper(II) nitrate aqueous solution by the incipient wetness method to achieve a Cu loading of about 2%. The samples showed 90% NO conversion at 350–400°C. The catalytic performance of these systems appears to be determined by the degree of clustering of copper cations as probed by FTIR spectroscopy of adsorbed CO.     

Synaptic scaling stabilizes persistent activity driven by asynchronous neurotransmitter release

Small networks of cultured hippocampal neurons respond to transient stimulation with rhythmic network activity (reverberation) that persists for several seconds, constituting an in vitro model of synchrony, working memory, and seizure. This mode of activity has been shown theoretically and experimentally to depend on asynchronous neurotransmitter release (an essential feature of the developing hippocampus) and is supported by a variety of developing neuronal networks despite variability in the size of populations (10-200 neurons) and in patterns of synaptic connectivity. It has previously been reported in computational models that "small-world" connection topology is ideal for the propagation of similar modes of network activity, although this has been shown only for neurons utilizing synchronous (phasic) synaptic transmission. We investigated how topological constraints on synaptic connectivity could shape the stability of reverberations in small networks that also use asynchronous synaptic transmission. We found that reverberation duration in such networks was resistant to changes in topology and scaled poorly with network size. However, normalization of synaptic drive, by reducing the variance of synaptic input across neurons, stabilized reverberation in such networks. Our results thus suggest that the stability of both normal and pathological states in developing networks might be shaped by variance-normalizing constraints on synaptic drive. We offer an experimental prediction for the consequences of such regulation on the behavior of small networks.     

Particle size and support effects on the complete benzene oxidation by Co and Co–Pt catalysts

Monometallic cobalt and bimetallic Co–Pt samples of various particle sizes have been prepared using SiO₂ and synthetic kenyaite (layered silicate) as a support. They are characterized by elemental analysis, XRD, TPR, and XPS. Cobalt is introduced by two methods—classical impregnation and ammonia method. The ammonia method of preparation leads to the formation of finely dispersed Co₃O₄ on both supports. Besides, hardly reducible cobalt silicate phases appear predominantly on the SiO₂ support. The Co₃O₄ particle size varies between 5 and 20 nm, depending on the support. The monometallic Co samples prepared by ammonia method on both supports are more active in benzene combustion than the impregnated ones due to the finer dispersion of the easily reducible Co₃O₄. Addition of Pt improves the activity and the promoting effect is more evident for the impregnated sample. This is explained with the synergy effect of cobalt oxide species and Pt. The less promoting effect of Pt on the catalytic activity of the bimetallic kenyaite-supported samples is attributed to the stronger interaction between the Co oxide phase and Pt during the preparation process.     

Interactive mobile equipment safety task-training in surface mining

Improving the quality of equipment training for the Heavy Equipment Operators (HEO) is a critical task in improving safety and eliminating equipment-related injuries in mining. One of major responsibilities for the HEOs is proper machine inspection. Traditional miner safety training includes the use of hardcopy documents and video instructions. However, modern mobile and computer technology offers tremendous potential to improve the training process. In this study, we apply a 360-degree camera, open-source platform WordPress™, and the software Unity3D in order to create materials and tools for the HEOs safety training to help trainees better understand the pre-shift safety machine inspection. The computer-based safety task training developed in this research is tested and implemented at a surface mine in the southern United States.