Properties of bio-based polymer nylon 11 reinforced with short carbon fiber composites

In this work, micro-composite materials were produced by incorporating 3-mm long reclaimed short carbon fibers into bio-based nylon 11 via melt compounding. A systematic fiber length distribution analysis was performed after the masterbatching, compounding and an injection moulding processes using optical microscopy images. It was found that the large majority of the fibers were within the 200-300 μm in length range after the injection moulding process. The mechanical (flexural and tensile), thermo-mechanical, and creep properties of the injection moulded materials are reported. We found that an enhancement in flexural and Young's modulus of 25% and 14%, respectively, could be attained with 2 wt% carbon fiber loading whilst no significant drawback on the ductility and toughness of the matrix was observed. The creep resistance and recovery of the nylon 11, tested using dynamic mechanical thermal analysis at room temperature and 65°C, was significantly improved by up to 30% and 14%, respectively, after loading with carbon fiber. This work provides an insight into the property improvement of the bio-based polymer nylon 11 using a small amount of a reclaimed engineered material. © 2014 Society of Plastics Engineers.

A universal optimization strategy for ant colony optimization algorithms based on the Physarum-inspired mathematical model

Ant colony optimization (ACO) algorithms often fall into the local optimal solution and have lower search efficiency for solving the travelling salesman problem (TSP). According to these shortcomings, this paper proposes a universal optimization strategy for updating the pheromone matrix in the ACO algorithms. The new optimization strategy takes advantages of the unique feature of critical paths reserved in the process of evolving adaptive networks of the Physarum-inspired mathematical model (PMM). The optimized algorithms, denoted as PMACO algorithms, can enhance the amount of pheromone in the critical paths and promote the exploitation of the optimal solution. Experimental results in synthetic and real networks show that the PMACO algorithms are more efficient and robust than the traditional ACO algorithms, which are adaptable to solve the TSP with single or multiple objectives. Meanwhile, we further analyse the influence of parameters on the performance of the PMACO algorithms. Based on these analyses, the best values of these parameters are worked out for the TSP.

A Physarum-inspired multi-agent system to solve maze

Physarum Polycephalum is a primitive unicellular organism. Its foraging behavior demonstrates a unique feature to form a shortest path among food sources, which can be used to solve a maze. This paper proposes a Physarum-inspired multi-agent system to reveal the evolution of Physarum transportation networks. Two types of agents – one type for search and the other for convergence – are used in the proposed model, and three transition rules are identified to simulate the foraging behavior of Physarum. Based on the experiments conducted, the proposed multiagent system can solve the two possible routes of maze, and exhibits the reconfiguration ability when cutting down one route. This indicates that the proposed system is a new way to reveal the intelligence of Physarum during the evolution process of its transportation networks.

Digital material representation and testing of metal foams

In recent years, metal foams are becoming more and more popular due to their high energy absorption ability and low density, which are being widely used in automotive engineering and aerospace engineering. As a design guide, foams can be characterised by several main geometric parameters, such as pore size, pore shape, spatial distribution and arrangement and so on. Considering most foam materials have random distributions of cell size and cell shape, the digital material representation and modelling of such materials become more complex. Cell size and shape effects on mechanical behaviours of metal foams have been found and investigated numerically and experimentally in authors' previous studies in which the authors have developed a digital framework for the representation, modelling and evaluation of multi-phase materials including metal foams. In this study, 2-/3-D finite element models are both developed to represent metal foams with random cell distributions and then a series of digital testing are simulated to investigate the mechanical behaviours of such foams. For validation and verification purpose, the results obtained from 2-/3-D models have been compared and good agreement has been found which demonstrated the effectiveness of the digital framework developed for metal forms. © (2014) Trans Tech Publications, Switzerland.

Surface functionalisation of magnesium alloys for use as bio-implants

 Magnesium-based alloys containing appropriate quantities of Strontium can induce optimal bone formation. Surface modification of these alloys with Collagen-I increased mineral deposition on the peri-implant surface over shorter periods of time as compared to the unmodified alloys, indicating the role of Collagen-I and Strontium concentration in bone resorption and remodelling.

A multi-objective ant colony optimization algorithm based on the physarum-inspired mathematical model

Multi-objective traveling salesman problem (MOTSP) is an important field in operations research, which has wide applications in the real world. Multi-objective ant colony optimization (MOACO) as one of the most effective algorithms has gained popularity for solving a MOTSP. However, there exists the problem of premature convergence in most of MOACO algorithms. With this observation in mind, an improved multiobjective network ant colony optimization, denoted as PMMONACO, is proposed, which employs the unique feature of critical tubes reserved in the network evolution process of the Physarum-inspired mathematical model (PMM). By considering both pheromones deposited by ants and flowing in the Physarum network, PM-MONACO uses an optimized pheromone matrix updating strategy. Experimental results in benchmark networks show that PM-MONACO can achieve a better compromise solution than the original MOACO algorithm for solving MOTSPs.