Sealing behaviour of glass-based composites for oxygen transport membranes

In this study, seven different filler materials in different proportions were added to a Ba-Ca-Si glass matrix “H” to investigate new sealant with higher thermal expansion coefficient (CTE) value and good sealing performance for application in oxygen transport membrane (OTM). SrTi_0.75Fe_0.25O_3-δ (STF25) was used as an OTM, and the sealing partners were ferritic steel Aluchrom and pre-oxidized Aluchrom. Compatibility tests were carried out to investigate the feasibility of the composites. Higher CTE values were found in dilatometer tests on composite samples by adding 40 wt% Ag (HAg40) and 30 wt% Ni-Cr (HNC30). Gas-tightness measurements of sandwiched samples produced appropriate helium leakage rates in the range of 10^?6 mbar·l·s^?1. Sealing behaviour of sealants HAg40 and HNC30 were investigated by joining STF25 and as-delivered/pre-oxidized Aluchrom together. Scanning electron microscopy (SEM) on cross-sections of the joints revealed a homogeneous microstructure and good adherence of the glass sealants to support metals and STF25.     

Earliness–tardiness minimization on scheduling a batch processing machine with non-identical job sizes

This paper considers the scheduling problem of minimizing earliness–tardiness (E/T) on a single batch processing machine with a common due date. The problem is extended to the environment of non-identical job sizes. First, a mathematical model is formulated, which is tested effectively under IBM ILOG CPLEX using the constraint programming solver. Then several optimal properties are given to schedule batches effectively, and by introducing the concept of ARB (Attribute Ratio of Batch), it is proven that the ARB of each batch should be made as small as possible in order to minimize the objective, designed as the heuristic information for assigning jobs into batches. Based on these properties, a heuristic algorithm MARB (Minimum Attribute Ratio of Batch) for batch forming is proposed, and a hybrid genetic algorithm is developed for the problem under study by combining GA (genetic algorithm) with MARB. Experimental results demonstrate that the proposed algorithm outperforms other algorithms in the literature, both for small and large problem instances.     

A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

A steelmaking-continuous casting (SCC) scheduling problem is an example of complex hybrid flow shop scheduling problem (HFSSP) with a strong industrial background. This paper investigates the SCC scheduling problem that involves controllable processing times (CPT) with multiple objectives concerning the total waiting time, earliness/tardiness and adjusting cost. The SCC scheduling problem with CPT is seldom discussed in the existing literature. This study is motivated by the practical situation of a large integrated steel company in which the just-in-time (JIT) and cost-cutting production strategy have become a significant concern. To address this complex HFSSP, the scheduling problem is decomposed into two subproblems: a parallel machine scheduling problem (PMSP) in the last stage and an HFSSP in the upstream stages. First, a hybrid differential evolution (HDE) algorithm combined with a variable neighborhood decomposition search (VNDS) is proposed for the former subproblem. Second, an iterative backward list scheduling (IBLS) algorithm is presented to solve the latter subproblem. The effectiveness of this bi-layer optimization approach is verified by computational experiments on well-designed and real-world scheduling instances. This study provides a new perspective on modeling and solving practical SCC scheduling problems.     

Effect of Temperature and Strain Rate on the Hot Deformation Behaviour of Ferritic Stainless Steel

Metals and Materials International - The flow behaviour and microstructure characteristics of a ferritic stainless steel were investigated using plain strain compression test on a Gleeble 3500...     

Effects of sintering in a high magnetic field on properties of vitrified bond and vitrified CBN composites

Vitrified bond CBN grinding wheels are being widely used due to their superior performance. Also, advantages of vitrified grinding wheels are high elastic modulus, stable chemical property, and low thermal expansion coefficient. Brittleness and low strength are key factors restricting the development of vitrified bond CBN grinding wheels. In this paper, the sintering in a high magnetic field was innovatively introduced into the manufacturing of vitrified bond CBN grinding wheels, and the effects of sintering in a high magnetic field on properties on vitrified bond and vitrified CBN composites were systematically investigated. Vitrified bond was characterized using three-point bending, scanning electron microscopy, X-ray diffraction. It was observed that microstructure of vitrified bond could be changed, grain orientation could be controlled and average grain size could be decreased in a high magnetic field, while vitrified bond strength could be simultaneously improved. High quality vitrified bond could be obtained by appropriately adjusting the strength and direction of high magnetic field. Results demonstrated that vitrified bond properties were improved when the magnetic field strength was 6?T. In order to highlight the high magnetic field effect on the vitrified CBN composites, the ordinary CBN abrasives and nickel plated CBN abrasives were used respectively. Microstructures, bending strengths of vitrified CBN composites were compared in different high magnetic fields. When the magnetic field strength was appropriate (less than 6?T), the binding characteristic of vitrified bond CBN composites with nickel plated CBN abrasives was greatly improved. The highest bending strength value of vitrified CBN composites was 79.5?MPa in 6?T high magnetic field.     

Fatigue performance of Friction Stir Welded titanium structural joints

The Friction Stir Welding process for producing corner and T-joints out of 6 mm Ti–6Al–4V was developed in this effort using previous work on butt weld joints as a starting point. A limited number of corner joints were also subjected to a bending fatigue test to preliminarily assess the applicability of the process in producing fatigue critical structures. These results were also compared to predictions made by applying stress concentration factors to previously generated uniaxial butt joint test data. While additional testing is still required to obtain a higher degree of confidence in the conclusions of this study, it was found that the performance of these corner joints in fatigue could be compared to butt joint data when a geometrically based stress concentration factor is applied. Furthermore, these welded joints possessed equivalent fatigue performance relative to identical test specimens machined from wrought product forms, both bar and extrusion. Thus, from the perspective of fatigue design, this study has shown that Friction Stir Welding is able to produce structures with the same performance as currently made from wrought materials.     

Using direct competition to select for competent controllers in evolutionary robotics

Evolutionary robotics (ER) is a field of research that applies artificial evolution toward the automatic design and synthesis of intelligent robot controllers. The preceding decade saw numerous advances in evolutionary robotics hardware and software systems. However, the sophistication of resulting robot controllers has remained nearly static over this period of time. Here, we make the case that current methods of controller fitness evaluation are primary factors limiting the further development of ER. To address this, we define a form of fitness evaluation that relies on intra-population competition. In this research, complex neural networks were trained to control robots playing a competitive team game. To limit the amount of human bias or know-how injected into the evolving controllers, selection was based on whether controllers won or lost games. The robots relied on video sensing of their environment, and the neural networks required on the order of 150 inputs. This represents an order of magnitude increase in sensor complexity compared to other research in this field. Evolved controllers were tested extensively in real fully-autonomous robots and in simulation. Results and experiments are presented to characterize the training process and the acquisition of controller competency under different evolutionary conditions.     

Effect of residual surface stress on the fatigue behavior of a low-alloy powder metallurgy steel

In this study we have characterized the fatigue behavior of a low-alloy powder metallurgy (P/M) sintered steel, composed mainly of martensite and bainite with 10.4% porosity. After each processing step, the residual axial surface stress was measured by X-ray diffraction. Significant compressive surface stresses were generated during the machining of the fatigue specimens. A heat-treatment at 175 °C after machining had no effect on these residual stresses, but polishing the surface resulted in a 20% reduction in compressive stresses. The residual surface stresses had no apparent effect on the fatigue behavior of the sintered steel. Rather, the fatigue behavior was controlled by sub-surface defects consisting of weakly bonded particles located in regions of high porosity.     

Formation of γ-LiAlO2 nano-network in an Al-based metal matrix composite

We report the synthesis of a nanostructured γ-LiAlO₂ network in an Al-based metal matrix composite (MMC) by arc-melting a powder compact of Al–15 wt.%Li₂O. During synthesis, chemical reactions between Al and Li₂O occurred, and a two-phase Al-γ-LiAlO₂ MMC was produced. The γ-LiAlO₂ was in the form of nano-network extended evenly in the Al matrix. The apparent density and Vickers' hardness number of the MMC were determined to be 2.31 gcm^− 3 and 143, respectively, and having a relative density of 0.87. The MMC was made nano-porous by etching away Al with a 2 M NaOH solution. The sizes of pores were about 150 nm and the width of the branches in the γ-LiAlO₂ network was about 90 nm. Atomic force microscopy revealed that the branches were composed of fine grains of 50 nm in diameter. Microstructure of the network was not altered even after prolonged etching, and this suggested that γ-LiAlO₂ was chemically inert to NaOH corrosion. Specific surface area of the γ-LiAlO₂ nano-network was measured to be 79 m²/g, and its porosity was determined to be 43.7%.     

Correlating microstructural features with wear resistance of dual phase steel

In order to explore the tribological potential of the dual phase (DP) steel as a wear resistant material, the wear characteristics of the dual phase (DP) steel have been investigated with varying amounts of martensite from 43 to 81 vol pct, developed by varying holding time at the intercritical annealing temperature of 780 °C. Dry sliding wear tests have been conducted on DP steels using a pin-on-disk machine under different normal loads of 61.3, 68.5, 75.7 and 82.6 N and at a constant sliding speed of 1.20 m/s. At these loads, the mechanism of wear is mainly delamination, which has been confirmed by SEM micrographs of the subsurface and wear debris of the samples. Wear and friction properties have been found to be improved with increasing martensite volume fraction in dual phase steels.