Interactive multi-objective particle swarm optimisation using decision space interaction

The most common approach to decision making in multi-objective optimisation with metaheuristics is a posteriori preference articulation. Increased model complexity and a gradual increase of optimisation problems with three or more objectives have revived an interest in progressively interactive decision making, where a human decision maker interacts with the algorithm at regular intervals. This paper presents an interactive approach to multi-objective particle swarm optimisation (MOPSO) using a novel technique to preference articulation based on decision space interaction and visual preference articulation. The approach is tested on a 2D aerofoil design case study and comparisons are drawn to non-interactive MOPSO. © 2013 IEEE.

Canonical normal shock wave/boundary-layer interaction flows relevant to external compression inlets

The normal shock wave/boundary-layer interaction is important to the operation and performance of a supersonic inlet, and the normal shock wave/boundary-layer interaction is particularly prominent in external compression inlets. To improve understanding of such interactions, it is helpful to make use of fundamental flows that capture the main elements of inlets, without resorting to the level of complexity and system integration associated with full-geometry inlets. In this paper, several fundamental flowfield configurations have been considered as possible test cases to represent the normal shock wave/boundary-layer interaction aspects found in typical external compression inlets, and it was found that the spillage diffuser more closely retains the basic flow features of an external compression inlet than the other configurations. In particular, this flowfield allows the normal shock Mach number as well as the amount and rate of subsonic diffusion to all be held approximately constant and independent of the application of flow control. In addition, a survey of several external compression inlets was conducted to quantify the flow and geometric parameters of the spillage diffuser relevant to actual inlets. The results indicated that such a flow may be especially relevant if the terminal Mach number is about 1.3 to 1.4, the confinement parameter is around 10%, and the width is around twice or three times the height. In addition, the area expansion downstream of the shock should be limited to the conservative side of incipient stall based on incompressible diffusers. Copyright © 2013 by the authors.

A computational fluid-structure interaction study of inflation cycles of a tension cone decelerator

Inflatable aerodynamic decelerators present potential advantages for planetary entry in missions of robotic and human exploration. The design of these structures face many engineering challenges, including complex deformable geometries, anisotropic material response, and coupled shockturbulence interactions. In this paper, we describe a comprehensive computational fluid-structure interaction study of an inflation cycle of a tension cone decelerator in supersonic flow and compare the simulations with earlier published experimental results. The aeroshell design and flow conditions closely match recent experiments conducted at Mach 2.5. The structural model is a 16-sided polygonal tension cone with seams between each segment. The computational model utilizes adaptive mesh refinement, large-eddy simulation, and shell mechanics with self-contact modeling to represent the flow and structure interaction. This study focuses on the dynamics of the structure as the inflation pressure varies gradually, and the behavior of forces experienced by the flexible and rigid (the payload capsule) structures. © 2011 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

On-line policy optimisation of Bayesian spoken dialogue systems via human interaction

A partially observable Markov decision process has been proposed as a dialogue model that enables robustness to speech recognition errors and automatic policy optimisation using reinforcement learning (RL). However, conventional RL algorithms require a very large number of dialogues, necessitating a user simulator. Recently, Gaussian processes have been shown to substantially speed up the optimisation, making it possible to learn directly from interaction with human users. However, early studies have been limited to very low dimensional spaces and the learning has exhibited convergence problems. Here we investigate learning from human interaction using the Bayesian Update of Dialogue State system. This dynamic Bayesian network based system has an optimisation space covering more than one hundred features, allowing a wide range of behaviours to be learned. Using an improved policy model and a more robust reward function, we show that stable learning can be achieved that significantly outperforms a simulator trained policy. © 2013 IEEE.

Sorptive interaction between goethite and strongly reducing organic substances from anaerobic decomposition of green manures

Strongly reducing organic substances (SROS) and iron oxides exist widely in soils and sediments and have been implicated in many soil and sediment processes. In the present work, the sorptive interaction between goethite and SROS derived from anaerobic decomposition of green manures was investigated by differential pulse voltammetry (DPV). Both green manures, Astragaltus sinicus (Astragalus) and Vicia varia (Vicia) were chosen to be anaerobically decomposed by the mixed microorganisms isolated from paddy soils for 30 d to prepare different SROS. Goethite used in experiments was synthesized in laboratory. The anaerobic incubation solutions from green manures at different incubation time were arranged to react with goethite, in which SROS concentration and Fe(II) species were analyzed. The anaerobic decomposition of Astragalus generally produced SROS more in amount but weaker in reducibility than that of Vicia in the same incubation time. The available SROS from Astragalus that could interact with goethite was 0.69 +/- 0.04, 0.84 +/- 0.04 and 1.09 +/- 0.03 cmol kg(-1) as incubated for 10, 15 and 30 d, respectively, for Vicia, it was 0.12 +/- 0.03, 0.46 +/- 0.02 and 0.70 +/- 0.02 cmol kg(-1). One of the fates of SROS as they interacted with goethite was oxidation. The amounts of oxidizable SROS from Astragalus decreased over increasing incubation time from 0.51 +/- 0.05 cmol kg(-1) at day 10 to 0.39 +/- 0.04 cmol kg(-1) at day 30, but for Vicia, it increased with the highest reaching to 0.58 +/- 0.04 cmol kg(-1) at day 30. Another fate of these substances was sorption by goethite. The SROS from Astragalus were sorbed more readily than those from Vicia, and closely depended upon the incubation time, whereas for those from Vicia, the corresponding values were remarkably less and apparently unchangeable with incubation time. The extent of goethite dissolution induced by the anaerobic solution from Vicia was greater than that from Astragalus, showing its higher reactivity. (c) 2008 Published by Elsevier Ltd.