Comparison of formulations for the two-level uncapacitated facility location problem with single assignment constraints

We consider the two-level uncapacitated facility location problem with single assignment constraints (TUFLP-S), an extension of the uncapacitated facility location problem. We present six mixed-integer programming models for the TUFLP-S based on reformulation techniques and on the relaxation of the integrality of some of the variables associated with location decisions. We compare the models by carrying out extensive computational experiments on large, hard, artificial instances, as well as on instances derived from an industrial application in freight transportation.     

The relative importance of moisture transfer,soil freezing and snow cover on ground temperature predictions

Predicting ground temperature is an important part of the analysis of geothermal resources assessment and use. Thus, we develop and validate one-dimensional numerical model for heat and mass transfer in partially frozen soils. The model is implemented in HVACSIM Plus and used to simulate the thermal regime of soil profile. In addition to modeling heat conduction, model variations also includes moisture transfer, snow accumulation and melting, and soil freezing and thawing. The results are compared against experimental measurements of ground temperature for three locations in Montana, USA. The differences between simulated depth temperature with and without snow cover and freezing and thawing of soil reveal that ground temperatures are predominantly influenced by these two factors. Considering moisture transfer slightly improves temperature predictions, although it increases computational time by one order of magnitude. To balance computational efficiency with prediction accuracy, we propose an equivalent moisture content of 40–60% saturation in predicting ground temperature.     

Effect of silicon nitride coating thickness on fatigue of silicon microbeams

In this paper, two silicon nitride layers with thickness, 0.2 and 0.4 μm, are coated onto single crystal silicon (SCS) in order to achieve Si₃N₄/Si cantilever microbeams. The effect of LPCVD silicon nitride surface coatings on fatigue properties of SCS cantilever microbeams is investigated. Fatigue testing is conducted at both 40 Hz and 100 Hz. Typical S–N (strain amplitude–fatigue cycle) curves of the beams are achieved and correlated fatigue failure modes are investigated. It is found that thinner Si₃N₄ coating of 0.2 μm results in better fatigue lives of Si₃N₄/Si beams than thicker Si₃N₄ coating of 0.4 μm. Both thinner and thicker coated beams have major fatigue crack planes along {1 1 1} planes; however, thicker coated beams possess specific failure mode of delamination, which is not found in thinner coated beams. Delamination reduces the reinforcing effect of thicker Si₃N₄ coating and leads to its shorter fatigue life. For thicker coated beams, fatigue life at 100 Hz is longer than that at 40 Hz. The mechanism for delamination and the effect of cyclic frequency is investigated, and factors for better fatigue life are proposed.     

Uniaxial and biaxial failure behaviors of aluminum alloy foams

Combined shear–tensile test have been performed on a closed-cell aluminum alloy foams with three relative densities over a wide range of loading rates in order to probe their failure behaviors under biaxial loading conditions. Quasi-static uniaxial compressive and tensile tests have also been conducted to investigate uniaxial failure behaviors of the aluminum alloy foams. The materials exhibit uniaxial failure stress asymmetry due to different failure mechanism in the uniaxial tensile and compression. Comparison is made between three phenomenological failure criteria and the measured failure stresses under different loading conditions to verify these criteria. The experimental failure surfaces of the aluminum alloy foams provide support for the three phenomenological failure criteria when suitable Poisson’s ratio is employed. The shape of the experimental failure surface in principal stress plane was not significantly influenced by variation in the relative density. The slight expansion of the failure surfaces with loading rate happened to be isotropic for this investigated closed-cell aluminum alloy foams in combined shear–tensile testes.     

Use of 2D Graphene Nanoplatelets (GNP) in cement composites for structural health evaluation

This study investigates the use of Graphene Nanoplatelets (GNP) in cement composite to quantify the material damage extent. The damage sensing capability of this new cement composite is demonstrated by experimentally measuring the electric potential across prisms with a known notch depth and comparing it with the finite element simulations. Meanwhile, the damage extent is directly related to the change in electric potential based on a mathematical analogy between the electrostatic field and the elastostatic field under anti-plane shear loading. It is shown that the fractional change in electric potential arising from damage is equivalent to the fractional change in elastic compliance, which can be exploited for structural health evaluation.     

Going from green to white color electroluminescence through a nanoscale complex of Zinc (II)

In this paper, we report application of four novel Nano Zinc (II) complexes as the emitter dyes in organic light emitting diodes (OLEDs). The Nano Zinc (II) complexes emission, particularly its absorption, fluorescence spectra and quantum yield, tuned by varying sizes which affects environments of the Zinc (II) ion. OLED Devices with Nano Zinc (II) complexes were fabricated, giving rise to devices with peak emission ranging from 498 to 541 nm. Here, we have successfully employed sonoelectrochemical method for fabricating white OLEDs. The white emission ascribed to the exciton emission in Nano Zinc (II) complex emitter and from exciplex formation at the interface of PVK/Nano Zinc (II) complex. The experimental results demonstrate that this approach is ideal for color tuning of single and multilayer conducting semiconducting thin films used in the fabrication of organic electronic devices such as OLEDs.     

Perceived similarity in face measurement

Automatic face recognition is a widely used biometric identification method, since it is based on standard video surveillance systems and does not require the collaboration of the person to be recognised. The recognition process involves decisions based on the face measurement results. The reliability and robustness of the recognition procedure are critical factors, strongly affected by influence quantities, such as face-camera relative orientation and position, illumination and expression. To improve performance it makes sense to imitate the recognition process in humans, who succeed in recognising faces even from poor quality images. It is therefore interesting to investigate the perception of similarity between faces, with the aim of gaining insight into the process of human face recognition. We report on an investigation that has been carried out by original methods developed in our laboratory for the direct measurement of perceptual quantities. Such methods have been implemented for two complementary recognition procedures, based either on the global appearance of a face or on the detection of specific repere points.     

The analysis of damage degree of oil and gas pipeline with type II plain dent

Dent is a common type of defect in oil and gas pipelines and the assessment on dented pipelines is carried out with major international standards and specifications based on dent depth as the evaluation criteria. However, such evaluation criteria based on depth does not account for the impact of various parameters (e.g. parameters of dent, parameters of pipeline and the internal pressure of pipeline) on the evaluation result, as a result, many dented pipelines lose their efficacy, even though they meet the depth-based standards. The influence of parameters changes on the damage degree of II-type dented pipelines is investigated on the basis of Oyane's ductile fracture criterion and by the method adopting finite element numerical calculations. Finally, the non-linear regression analysis is conducted and based on the outputs, a specific expression of dent depth and pipeline damage degree is also acquired within a certain scope of application.     

Topology optimization of stiffened plate/shell structures based on adaptive morphogenesis algorithm

This article proposes an adaptive morphogenesis algorithm to design stiffened plate/shell structures in a growth manner. The idea of this work is inspired by researches in leaf venation which indicates that the adaptive growth of leaf vein provides the relatively large structure with an effective reinforcement. This excellent performance is regarded as the contribution of two primary morphological features: branching and hierarchy. To apply the growth mechanism of leaf venation into stiffened plate/shell structures, a mathematical model describing the growth process is established. Based on this, the adaptive morphogenesis algorithm is developed to make stiffeners “grow” step by step. Besides, the “stiffness transforming operation”, a numerical treatment, is introduced to enable stiffeners to grow along arbitrary directions in the FEM model, which guarantees the design more optimized than previous methods. To obtain a further verification of the proposed method, a comparison between the proposed method and three typical methods is implemented. This comparison shows that the proposed method endows the designed object with a more excellent performance than others. Therefore, the proposed method is competent in the stiffened plate/shell structure design.     

Approximating class-departure variability in tandem queues with downtime events: Regression-based variability function

Predicting queue performance by approximating class-departure variability in tandem queues with downtime events via existing decomposition methods is neither accurate enough nor efficient enough. Analytic approximations, if conducted alone, lack accuracy but attempting to increase accuracy by incorporating simulation to analytic approximation has proved to require significant computation efforts. The aim of this paper is to reduce the latter inefficiency by modeling the Regression-Based Variability Function (RBVF) designed to approximate the between-class effect by exploiting the departure process from a single queue. The new approach predicts performance of n-tandem queues by reducing the focus to two-tandem queues for each traffic intensity level, as well as by modeling different policies of downtimes (e.g. first-come-first-served or priority). Numerical experiments demonstrate that the proposed RBVF delivers both accuracy and efficiency improvements: the relative errors associated with RBVF are about three times smaller than the best existing analytic procedures and the computation efforts associated with RBVF are about five times smaller than existing analytic procedure combined with simulation.