Silylation of layered double hydroxides via a calcination−rehydration route

Silylated layered double hydroxides (LDHs) were synthesized through a surfactant-free method involving an in situ condensation of silane with the surface hydroxyl group of LDHs during its reconstruction in carbonate solution. X-ray diffraction (XRD) patterns showed the silylation reaction occurred on the external surfaces of LDHs layers. The successful silylation was evidenced by 29Si cross-polarization magic-angle spinning nuclear magnetic resonance (29Si CP/MAS NMR) spectroscopy, attenuated total reflection Fourier transform infrared (ATR FTIR) spectroscopy, and infrared emission spectroscopy (IES). The ribbon shaped crystallites with a “rodlike” aggregation were observed through transmission electron microscopy (TEM) images. The aggregation was explained by the T2 and T3 types of linkage between adjacent silane molecules as indicated in the 29Si NMR spectrum. In addition, the silylated products show high thermal stability by maintained Si related bands even when the temperature was increased to 1000 °C as observed in IES spectra.

Robot path planning in dynamic environments using a simulated annealing based approach

Mobile robots are widely used in many industrial fields. Research on path planning for mobile robots is one of the most important aspects in mobile robots research. Path planning for a mobile robot is to find a collision-free route, through the robot’s environment with obstacles, from a specified start location to a desired goal destination while satisfying certain optimization criteria. Most of the existing path planning methods, such as the visibility graph, the cell decomposition, and the potential field are designed with the focus on static environments, in which there are only stationary obstacles. However, in practical systems such as Marine Science Research, Robots in Mining Industry, and RoboCup games, robots usually face dynamic environments, in which both moving and stationary obstacles exist. Because of the complexity of the dynamic environments, research on path planning in the environments with dynamic obstacles is limited. Limited numbers of papers have been published in this area in comparison with hundreds of reports on path planning in stationary environments in the open literature. Recently, a genetic algorithm based approach has been introduced to plan the optimal path for a mobile robot in a dynamic environment with moving obstacles. However, with the increase of the number of the obstacles in the environment, and the changes of the moving speed and direction of the robot and obstacles, the size of the problem to be solved increases sharply. Consequently, the performance of the genetic algorithm based approach deteriorates significantly. This motivates the research of this work. This research develops and implements a simulated annealing algorithm based approach to find the optimal path for a mobile robot in a dynamic environment with moving obstacles. The simulated annealing algorithm is an optimization algorithm similar to the genetic algorithm in principle. However, our investigation and simulations have indicated that the simulated annealing algorithm based approach is simpler and easier to implement. Its performance is also shown to be superior to that of the genetic algorithm based approach in both online and offline processing times as well as in obtaining the optimal solution for path planning of the robot in the dynamic environment. The first step of many path planning methods is to search an initial feasible path for the robot. A commonly used method for searching the initial path is to randomly pick up some vertices of the obstacles in the search space. This is time consuming in both static and dynamic path planning, and has an important impact on the efficiency of the dynamic path planning. This research proposes a heuristic method to search the feasible initial path efficiently. Then, the heuristic method is incorporated into the proposed simulated annealing algorithm based approach for dynamic robot path planning. Simulation experiments have shown that with the incorporation of the heuristic method, the developed simulated annealing algorithm based approach requires much shorter processing time to get the optimal solutions in the dynamic path planning problem. Furthermore, the quality of the solution, as characterized by the length of the planned path, is also improved with the incorporated heuristic method in the simulated annealing based approach for both online and offline path planning.

A cost-based optimization of a fiberboard pressing plant using Monte-Carlo simulation (a reliability program)

In this research the reliability and availability of fiberboard pressing plant is assessed and a cost-based optimization of the system using the Monte- Carlo simulation method is performed. The woodchip and pulp or engineered wood industry in Australia and around the world is a lucrative industry. One such industry is hardboard. The pressing system is the main system, as it converts the wet pulp to fiberboard. The assessment identified the pressing system has the highest downtime throughout the plant plus it represents the bottleneck in the process. A survey in the late nineties revealed there are over one thousand plants around the world, with the pressing system being a common system among these plants. No work has been done to assess or estimate the reliability of such a pressing system; therefore this assessment can be used for assessing any plant of this type.

Selection and optimization of piezoelectric polyvinylidene fluoride polymers for adaptive optics in space environments

Various piezoelectric polymers based on polyvinylidene fluoride (PVDF) are of interest for large aperture space-based telescopes. Dimensional adjustments of adaptive polymer films depend on charge deposition and require a detailed understanding of the piezoelectric material responses which are expected to deteriorate owing to strong vacuum UV, � -, X-ray, energetic particles and atomic oxygen exposure. We have investigated the degradation of PVDF and its copolymers under various stress environments detrimental to reliable operation in space. Initial radiation aging studies have shown complex material changes with lowered Curie temperatures, complex material changes with lowered melting points, morphological transformations and significant crosslinking, but little influence on piezoelectric d33 constants. Complex aging processes have also been observed in accelerated temperature environments inducing annealing phenomena and cyclic stresses. The results suggest that poling and chain orientation are negatively affected by radiation and temperature exposure. A framework for dealing with these complex material qualification issues and overall system survivability predictions in low earth orbit conditions has been established. It allows for improved material selection, feedback for manufacturing and processing, material optimization/stabilization strategies and provides guidance on any alternative materials.

Modelling urban public transit users’ route choice behaviour : a review and outlook

Public transport is one of the key promoters of sustainable urban transport. To encourage and increase public transport patronage it is important to investigate the route choice behaviours of urban public transit users. This chapter reviews the main developments of modelling urban public transit users’ route choice behaviours in a historical perspective, from the 1960s to the present time. The approaches re- viewed for this study include the early heuristic studies on finding the least-cost transit route and all-or- nothing transit assignment, the bus common lines problem, the disaggregate discrete choice models, the deterministic and stochastic user equilibrium transit assignment models, and the recent dynamic transit assignment models. This chapter also provides an outlook for the future directions of modelling transit users’ route choice behaviours. Through the comparison with the development of models for motorists’ route choice and traffic assignment problems, this chapter advocates that transit route choice research should draw inspiration from the research outcomes from the road area, and that the modelling practice of transit users’ route choice should further explore the behavioural complexities.

An optimization-based algorithm for shunt active filter under distorted supply voltages

When the supply voltages are balanced and sinusoidal, load compensation can give both unity power factor (UPF) and perfect harmonic cancellation (PHC) source currents. But under distorted supply voltages, achieving both UPF and PHC currents are not possible and contradictory to each other. Hence there should be an optimal performance between these two important compensation goals. This paper presents an optimal control algorithm for load compensation under unbalanced and distorted supply voltages. In this algorithm source currents are compensated for reactive, imbalance components and harmonic distortions set by the limits. By satisfying the harmonic distortion limits and power balance, this algorithm gives the source currents which will provide the maximum achievable power factor. The detailed simulation results using MATLAB are presented to support the performance of the proposed optimal control algorithm.

Urban dynamic origin-destination matrices estimation

The aim of this paper is to explore a new approach to obtain better traffic demand (Origin-Destination, OD matrices) for dense urban networks. From reviewing existing methods, from static to dynamic OD matrix evaluation, possible deficiencies in the approach could be identified: traffic assignment details for complex urban network and lacks in dynamic approach. To improve the global process of traffic demand estimation, this paper is focussing on a new methodology to determine dynamic OD matrices for urban areas characterized by complex route choice situation and high level of traffic controls. An iterative bi-level approach will be used, the Lower level (traffic assignment) problem will determine, dynamically, the utilisation of the network by vehicles using heuristic data from mesoscopic traffic simulator and the Upper level (matrix adjustment) problem will proceed to an OD estimation using optimization Kalman filtering technique. In this way, a full dynamic and continuous estimation of the final OD matrix could be obtained. First results of the proposed approach and remarks are presented.

Implementing value management as a decision-making tool in the design stages of design and build construction projects : a methodology for improved cost optimization

Value Management (VM) has been proven to provide a structured framework, together with other supporting tools and techniques, that facilitate effective decision-making in many types of projects, thus achieving ‘best value’ for clients. One of the major success factors of VM in achieving better project objectives for clients is through the provision of beneficial input by multi-disciplinary team members being involved in critical decision-making discussions during the early stage of construction projects. This paper describes a doctoral research proposal based on the application of VM in design and build construction projects, especially focusing on the design stage. The research aims to study the effects of implementing VM in design and build construction projects, in particular how well the methodology addresses issues related to cost overruns resulting from poor coordination and overlooking of critical constructability issues amongst team members in construction projects in Malaysia. It is proposed that through contractors’ early involvement during the design stage, combined with the use of the VM methodology, particularly as a decision-making tool, better optimization of construction cost can be achieved, thus promoting more efficient and effective constructability. The main methods used in this research involve a thorough literature study, semi-structured interviews, and a survey of major stakeholders, a detailed case study and a VM workshop and focus group discussions involving construction professionals in order to explore and possibly develop a framework and a specific methodology for the facilitating successful application of VM within design and build construction projects.

Optimization of long rural feeders using a genetic algorithm

This paper describes the optimization of conductor size and the voltage regulator location & magnitude of long rural distribution lines. The optimization minimizes the lifetime cost of the lines, including capital costs and losses while observing voltage drop and operational constraints using a Genetic Algorithm (GA). The GA optimization is applied to a real Single Wire Earth Return (SWER) network in regional Queensland and results are presented.

Transit users' route-choice modelling in transit assignment : a review

This paper reviews the main studies on transit users’ route choice in thecontext of transit assignment. The studies are categorized into three groups: static transit assignment, within-day dynamic transit assignment, and emerging approaches. The motivations and behavioural assumptions of these approaches are re-examined. The first group includes shortest-path heuristics in all-or-nothing assignment, random utility maximization route-choice models in stochastic assignment, and user equilibrium based assignment. The second group covers within-day dynamics in transit users’ route choice, transit network formulations, and dynamic transit assignment. The third group introduces the emerging studies on behavioural complexities, day-to-day dynamics, and real-time dynamics in transit users’ route choice. Future research directions are also discussed.

Bayesian multinomial logit: Theory and route choice example

Statisticians along with other scientists have made significant computational advances that enable the estimation of formerly complex statistical models. The Bayesian inference framework combined with Markov chain Monte Carlo estimation methods such as the Gibbs sampler enable the estimation of discrete choice models such as the multinomial logit (MNL) model. MNL models are frequently applied in transportation research to model choice outcomes such as mode, destination, or route choices or to model categorical outcomes such as crash outcomes. Recent developments allow for the modification of the potentially limiting assumptions of MNL such as the independence from irrelevant alternatives (IIA) property. However, relatively little transportation-related research has focused on Bayesian MNL models, the tractability of which is of great value to researchers and practitioners alike. This paper addresses MNL model specification issues in the Bayesian framework, such as the value of including prior information on parameters, allowing for nonlinear covariate effects, and extensions to random parameter models, so changing the usual limiting IIA assumption. This paper also provides an example that demonstrates, using route-choice data, the considerable potential of the Bayesian MNL approach with many transportation applications. This paper then concludes with a discussion of the pros and cons of this Bayesian approach and identifies when its application is worthwhile

Quantitative evaluation of route allocation solutions at large-scale passenger stations

Routing trains within passenger stations in major cities is a common scheduling problem for railway operation. Various studies have been undertaken to derive and formulate solutions to this route allocation problem (RAP) which is particularly evident in mainland China nowadays because of the growing traffic demand and limited station capacity. A reasonable solution must be selected from a set of available RAP solutions attained in the planning stage to facilitate station operation. The selection is however based on the experience of the operators only and objective evaluation of the solutions is rarely addressed. In order to maximise the utilisation of station capacity while maintaining service quality and allowing for service disturbance, quantitative evaluation of RAP solutions is highly desirable. In this study, quantitative evaluation of RAP solutions is proposed and it is enabled by a set of indices covering infrastructure utilisation, buffer times and delay propagation. The proposed evaluation is carried out on a number of RAP solutions at a real-life busy railway station in mainland China and the results highlight the effectiveness of the indices in pinpointing the strengths and weaknesses of the solutions. This study provides the necessary platform to improve the RAP solution in planning and to allow train re-routing upon service disturbances.