The retrieval of structured design rationale for the re-use of design knowledge with an integrated representation

Design knowledge can be acquired from various sources and generally requires an integrated representation for its effective and efficient re-use. Though knowledge about products and processes can illustrate the solutions created (know-what) and the courses of actions (know-how) involved in their creation, the reasoning process (know-why) underlying the solutions and actions is still needed for an integrated representation of design knowledge. Design rationale is an effective way of capturing that missing part, since it records the issues addressed, the options considered, and the arguments used when specific design solutions are created and evaluated. Apart from the need for an integrated representation, effective retrieval methods are also of great importance for the re-use of design knowledge, as the knowledge involved in designing complex products can be huge. Developing methods for the retrieval of design rationale is very useful as part of the effective management of design knowledge, for the following reasons. Firstly, design engineers tend to want to consider issues and solutions before looking at solid models or process specifications in detail. Secondly, design rationale is mainly described using text, which often embodies much relevant design knowledge. Last but not least, design rationale is generally captured by identifying elements and their dependencies, i.e. in a structured way which opens the opportunity for going beyond simple keyword-based searching. In this paper, the management of design rationale for the re-use of design knowledge is presented. The retrieval of design rationale records in particular is discussed in detail. As evidenced in the development and evaluation, the methods proposed are useful for the re-use of design knowledge and can be generalised to be used for the retrieval of other kinds of structured design knowledge. © 2012 Elsevier Ltd. All rights reserved.

Superconducting fault current limiter design using parallel-connected YBCO thin films

Superconducting Fault Current Limiters (SFCLs) are able to reduce fault currents to an acceptable value, reducing potential mechanical and thermal damage to power system apparatus and allowing more flexibility in power system design and operation. The device can also help avoid replacing circuit breakers whose capacity has been exceeded. Due to limitations in current YBCO thin film manufacturing processes, it is not easy to obtain one large thin film that satisfies the specifications for high voltage and large current applications. The combination of standardized thin films has merit to reduce costs and maintain device quality, and it is necessary to connect these thin films in different series and parallel configurations in order to meet these specifications. In this paper, the design of a resistive type SFCL using parallel-connected YBCO thin films is discussed, including the role of a parallel resistor and the influence of individual thin film characteristics, based on both theory and experimental results. © 2009 IEEE.

A high performance oxygen storage material for chemical looping processes with CO2 capture

Chemical looping combustion (CLC) is a novel combustion technology that involves cyclic reduction and oxidation of oxygen storage materials to provide oxygen for the combustion of fuels to CO2 and H2O, whilst giving a pure stream of CO2 suitable for sequestration or utilisation. Here, we report a method for preparing of oxygen storage materials from layered double hydroxides (LDHs) precursors and demonstrate their applications in the CLC process. The LDHs precursor enables homogeneous mixing of elements at the molecular level, giving a high degree of dispersion and high-loading of active metal oxide in the support after calcination. Using a Cu-Al LDH precursor as a prototype, we demonstrate that rational design of oxygen storage materials by material chemistry significantly improved the reactivity and stability in the high temperature redox cycles. We discovered that the presence of sodium-containing species were effective in inhibiting the formation of copper aluminates (CuAl2O4 or CuAlO 2) and stabilising the copper phase in an amorphous support over multiple redox cycles. A representative nanostructured Cu-based oxygen storage material derived from the LDH precursor showed stable gaseous O2 release capacity (∼5 wt%), stable oxygen storage capacity (∼12 wt%), and stable reaction rates during reversible phase changes between CuO-Cu 2O-Cu at high temperatures (800-1000 °C). We anticipate that the strategy can be extended to manufacture a variety of metal oxide composites for applications in novel high temperature looping cycles for clean energy production and CO2 capture. © The Royal Society of Chemistry 2013.

Design and characteristion of a hydraulic microactuator fabricated by lithography

To improve the force output of microactuators, this work focuses on actuators driven by pressurized gasses or liquids. Despite their well known ability to generate high actuation forces, hydraulic actuators remain uncommon in microsystems. This is both due to the difficulty of fabricating these microactuators with the existing micromachining processes and to the lack of adequate microseals. This paper describes how to overcome these limitations with a combination of anisotropic micromachining, UV definable polymers and low temperature bonding. The functionality of these actuators is proven by extensive measurements which showed that actuation forces of 0.1 N can be achieved for actuators with an active cross-section of 0.15 mm2. This is an order of magnitude higher than what is reported for classic MEMS actuators of similar size.

Bayesian Structured Prediction Using Gaussian Processes

We introduce a conceptually novel structured prediction model, GPstruct, which is kernelized, non-parametric and Bayesian, by design. We motivate the model with respect to existing approaches, among others, conditional random fields (CRFs), maximum margin Markov networks (M3N), and structured support vector machines (SVMstruct), which embody only a subset of its properties. We present an inference procedure based on Markov Chain Monte Carlo. The framework can be instantiated for a wide range of structured objects such as linear chains, trees, grids, and other general graphs. As a proof of concept, the model is benchmarked on several natural language processing tasks and a video gesture segmentation task involving a linear chain structure. We show prediction accuracies for GPstruct which are comparable to or exceeding those of CRFs and SVMstruct.