Parallel coordinates in computational engineering design

Modern Engineering Design involves the deployment of many computational tools. Re- search on challenging real-world design problems is focused on developing improvements for the engineering design process through the integration and application of advanced com- putational search/optimization and analysis tools. Successful application of these methods generates vast quantities of data on potential optimum designs. To gain maximum value from the optimization process, designers need to visualise and interpret this information leading to better understanding of the complex and multimodal relations between param- eters, objectives and decision-making of multiple and strongly conflicting criteria. Initial work by the authors has identified that the Parallel Coordinates interactive visualisation method has considerable potential in this regard. This methodology involves significant levels of user-interaction, making the engineering designer central to the process, rather than the passive recipient of a deluge of pre-formatted information. In the present work we have applied and demonstrated this methodology in two differ- ent aerodynamic turbomachinery design cases; a detailed 3D shape design for compressor blades, and a preliminary mean-line design for the whole compressor core. The first case comprises 26 design parameters for the parameterisation of the blade geometry, and we analysed the data produced from a three-objective optimization study, thus describing a design space with 29 dimensions. The latter case comprises 45 design parameters and two objective functions, hence developing a design space with 47 dimensions. In both cases the dimensionality can be managed quite easily in Parallel Coordinates space, and most importantly, we are able to identify interesting and crucial aspects of the relationships between the design parameters and optimum level of the objective functions under con- sideration. These findings guide the human designer to find answers to questions that could not even be addressed before. In this way, understanding the design leads to more intelligent decision-making and design space exploration. © 2012 AIAA.

Risk-based approaches to sustainability in civil engineering

Infrastructure project sustainability assessment typically entails the use of specialised assessment tools to measure and rate project performance against a set of criteria. This paper looks beyond the prevailing approaches to sustainability assessments and explores sustainability principles in terms of project risks and opportunities. Taking a risk management approach to applying sustainability concepts to projects has the potential to reconceptualise decision structures for sustainability from bespoke assessments to becoming a standard part of the project decisionmaking process. By integrating issues of sustainability into project risk management for project planning, design and construction, sustainability is considered within a more traditional business and engineering language. Currently, there is no widely practised approach for objectively considering the environmental and social context of projects alongside the more traditional project risk assessments of time, cost and quality. A risk-based approach would not solve all the issues associated with existing sustainability assessments but it would place sustainability concerns alongside other key risks and opportunities, integrating sustainability with other project decisions.

Donor-donor binding in In2O3: Engineering shallow donor levels

Using first-principles band structure methods, we investigate the interactions between different donors in In2O3. Through the formation energy and transition energy level calculations, we find that an oxygen-vacancy creates a deep donor level, while an indium-interstitial or a tin-dopant induces a shallow donor level. The coupling between these donor levels gives rise to even shallower donor levels and leads to a significant reduction in their formation energies. Based on the analysis of the PBE0-corrected band structure and the molecular-orbital bonding diagram, we demonstrate these effects of donor-donor binding. In addition, total energy calculations show that these defect pairs tend to be more stable with respect to the isolated defects due to their negative binding energies. Thus, we may design shallow donor levels to enhance the electrical conductivity via the donor donor binding.

Mechanism for Giycinebetaine to Improve Plant Salt Resistance and Its Research Advances in Genetic Engineering

The paper systematically discusses the mechanism for glycinebetaine to improve plant salt resistance and its research advances in genetic engineering at home and abroad as well as summarizing the research progresses about the key enzymes and their genetic engineering in glycinebetaine biosynthesis. It suggests that on the basis of further understanding the mechanism for glycinebetaine to improve plant salt resistance,the transformation of the genes relating to glycinebetaine biosynthesis should be carried out in major crops so that new plant varieties resistant to salt can be obtained.

A novel neural/symbolic hybrid approach to heuristically optimized fuel allocation and automated revision of heuristics in nuclear engineering

FUELCON is an expert system for optimized refueling design in nuclear engineering. This task is crucial for keeping down operating costs at a plant without compromising safety. FUELCON proposes sets of alternative configurations of allocation of fuel assemblies that are each positioned in the planar grid of a horizontal section of a reactor core. Results are simulated, and an expert user can also use FUELCON to revise rulesets and improve on his or her heuristics. The successful completion of FUELCON led this research team into undertaking a panoply of sequel projects, of which we provide a meta-architectural comparative formal discussion. In this paper, we demonstrate a novel adaptive technique that learns the optimal allocation heuristic for the various cores. The algorithm is a hybrid of a fine-grained neural network and symbolic computation components. This hybrid architecture is sensitive enough to learn the particular characteristics of the ‘in-core fuel management problem’ at hand, and is powerful enough to use this information fully to automatically revise heuristics, thus improving upon those provided by a human expert.

Refueling in nuclear engineering: the FUELCON project

Over a time span of almost a decade, the FUELCON project in nuclear engineering has led to a fully functional expert system and spawned sequel projects. Its task is in-core fuel management, also called `refueling', i.e., good fuel-allocation for reloading the core of a given nuclear reactor, for a given operation cycle. The task is crucial for keeping down operation costs at nuclear power plants. Fuel comes in different types and is positioned in a grid representing the core of a reactor. The tool is useful for practitioners but also helps the expert in the domain to test his or her rules of thumb and to discover new ones.

Scale of production and choice of technique in the engineering industries in developing countries

This article examines the relationship between scale of production, optimal choice of technique and costs for three engineering industries: nuts and bolts, iron founding and machine tools. In all three industries costs of production fell as the scale of output increased. This was associated with switches of technique and the spread of fixed costs over a larger number of units. The capital-output ratio fell and labour productivity increased with increases in scale while, in most cases, the capital-labour ratio increased. The implications of these findings are briefly discussed.