Multi-objective optimization for multiphase orbital rendezvous missions

A multi-objective optimization approach was proposed for multiphase orbital rendezvous missions and validated by application to a representative numerical problem. By comparing the Pareto fronts obtained using the proposed method, the relationships between the three objectives considered are revealed, and the influences of other mission parameters, such as the sensors' field of view, can also be analyzed effectively. For multiphase orbital rendezvous missions, the tradeoff relationships between the total velocity increment and the trajectory robustness index as well as between the total velocity increment and the time of flight are obvious and clear. However, the tradeoff relationship between the time of flight and the trajectory robustness index is weak, especially for the four- and five-phase missions examined. The proposed approach could be used to reorganize a stable rendezvous profile for an engineering rendezvous mission, when there is a failure that prevents the completion of the nominal mission.

An example of the use of neural computing techniques in materials science - The modelling of fatigue thresholds in Ni-base superalloys

Two adaptive numerical modelling techniques have been applied to prediction of fatigue thresholds in Ni-base superalloys. A Bayesian neural network and a neurofuzzy network have been compared, both of which have the ability to automatically adjust the network's complexity to the current dataset. In both cases, despite inevitable data restrictions, threshold values have been modelled with some degree of success. However, it is argued in this paper that the neurofuzzy modelling approach offers real benefits over the use of a classical neural network as the mathematical complexity of the relationships can be restricted to allow for the paucity of data, and the linguistic fuzzy rules produced allow assessment of the model without extensive interrogation and examination using a hypothetical dataset. The additive neurofuzzy network structure means that redundant inputs can be excluded from the model and simple sub-networks produced which represent global output trends. Both of these aspects are important for final verification and validation of the information extracted from the numerical data. In some situations neurofuzzy networks may require less data to produce a stable solution, and may be easier to verify in the light of existing physical understanding because of the production of transparent linguistic rules. © 1999 Elsevier Science S.A.

A global assessment of manufacturing: Economic development, energy use, carbon emissions, and the potential for energy efficiency and materials recycling

We present in two parts an assessment of global manufacturing. In the first part, we review economic development, pollution, and carbon emissions from a country perspective, tracking the rise of China and other developing countries. The results show not only a rise in the economic fortunes of the newly industrializing nations, but also a significant rise in global pollution, particularly air pollution and CO2 emissions largely from coal use, which alter and even reverse previous global trends. In the second part, we change perspective and quantitatively evaluate two important technical strategies to reduce pollution and carbon emissions: energy efficiency and materials recycling. We subdivide the manufacturing sector on the basis of the five major subsectors that dominate energy use and carbon emissions: (a) iron and steel, (b) cement, (c) plastics, (d) paper, and (e) aluminum. The analysis identifies technical constraints on these strategies, but by combined and aggressive action, industry should be able to balance increases in demand with these technical improvements. The result would be high but relatively flat energy use and carbon emissions. The review closes by demonstrating the consequences of extrapolating trends in production and carbon emissions and suggesting two options for further environmental improvements, materials efficiency, and demand reduction. © 2013 by Annual Reviews. All rights reserved.

Fracture of brittle lattice materials: A review

The mechanics of failure for elastic-brittle lattice materials is reviewed. Closed-form expressions are summarized for fracture toughness as a function of relative density for a wide range of periodic lattices. A variety of theoretical and numerical approaches has been developed in the literature and in the main the predictions coincide for any given topology. However, there are discrepancies and the underlying reasons for these are highlighted. The role of imperfections at the cell wall level can be accounted for by Weibull analysis. Nevertheless, defects can also arise on the meso-scale in the form of misplaced joints, wavy cell walls and randomly distributed missing cell walls. These degrade the macroscopic fracture toughness of the lattice. © 2010 Springer Science+Business Media B.V.

Mechanical and fracture properties of cement-based bi-materials after thermal cycling

This study investigates the effect of thermal cycles on the fracture properties of the cement-based bi-materials. Sixty eight cubes were exposed to a varied number of 24-hour thermal cycles ranging from 0 to 90 and subsequently were tested in a wedge splitting configuration. The mechanical and fracture properties of normal strength and high strength concretes are substantially improved after 30 thermal cycles, but less so after 90 thermal cycles both in isolation and when bonded to an ultra high-performance fibre-reinforced cement-based composite. © 2009 Elsevier Ltd. All rights reserved.

Mechanical characterisation of hydrogel materials

Interest in hydrogel materials is growing rapidly, due to the potential for hydrogel use in tissue engineering and drug delivery applications, and as coatings on medical devices. However, a key limitation with the use of hydrogel materials in many applications is their relatively poor mechanical properties compared with those of (less biocompatible) solid polymers. In this review, basic chemistry, microstructure and processing routes for common natural and synthetic hydrogel materials are explored first. Underlying structure-properties relationships for hydrogels are considered. A series of mechanical testing modalities suitable for hydrogel characterisation are next considered, including emerging test modalities, such as nanoindentation and atomic force microscopy (AFM) indentation. As the data analysis depends in part on the material's constitutive behaviour, a series of increasingly complex constitutive models will be examined, including elastic, viscoelastic and theories that explicitly treat the multiphasic poroelastic nature of hydrogel materials. Results from the existing literature on agar and polyacrylamide mechanical properties are compiled and compared, highlighting the challenges and uncertainties inherent in the process of gel mechanical characterisation. © 2014 Institute of Materials, Minerals and Mining and ASM International.