Maintenance strategy optimization using a continuous-state partially observable semi-Markov decision process

Due to the limitation of current condition monitoring technologies, the estimates of asset health states may contain some uncertainties. A maintenance strategy ignoring this uncertainty of asset health state can cause additional costs or downtime. The partially observable Markov decision process (POMDP) is a commonly used approach to derive optimal maintenance strategies when asset health inspections are imperfect. However, existing applications of the POMDP to maintenance decision-making largely adopt the discrete time and state assumptions. The discrete-time assumption requires the health state transitions and maintenance activities only happen at discrete epochs, which cannot model the failure time accurately and is not cost-effective. The discrete health state assumption, on the other hand, may not be elaborate enough to improve the effectiveness of maintenance. To address these limitations, this paper proposes a continuous state partially observable semi-Markov decision process (POSMDP). An algorithm that combines the Monte Carlo-based density projection method and the policy iteration is developed to solve the POSMDP. Different types of maintenance activities (i.e., inspections, replacement, and imperfect maintenance) are considered in this paper. The next maintenance action and the corresponding waiting durations are optimized jointly to minimize the long-run expected cost per unit time and availability. The result of simulation studies shows that the proposed maintenance optimization approach is more cost-effective than maintenance strategies derived by another two approximate methods, when regular inspection intervals are adopted. The simulation study also shows that the maintenance cost can be further reduced by developing maintenance strategies with state-dependent maintenance intervals using the POSMDP. In addition, during the simulation studies the proposed POSMDP shows the ability to adopt a cost-effective strategy structure when multiple types of maintenance activities are involved.

Numerical methods for second-order stochastic differential equations

We seek numerical methods for second‐order stochastic differential equations that reproduce the stationary density accurately for all values of damping. A complete analysis is possible for scalar linear second‐order equations (damped harmonic oscillators with additive noise), where the statistics are Gaussian and can be calculated exactly in the continuous‐time and discrete‐time cases. A matrix equation is given for the stationary variances and correlation for methods using one Gaussian random variable per timestep. The only Runge–Kutta method with a nonsingular tableau matrix that gives the exact steady state density for all values of damping is the implicit midpoint rule. Numerical experiments, comparing the implicit midpoint rule with Heun and leapfrog methods on nonlinear equations with additive or multiplicative noise, produce behavior similar to the linear case.

The effect of oral metformin on insulin sensitivity in insulin-resistant ponies

Metformin may be an effective therapeutic option for insulin-resistant (I-R) horses/ponies because, in humans, it reportedly enhances insulin sensitivity (SI) of peripheral tissues without stimulating insulin secretion. To determine the effect of metformin on insulin and glucose dynamics in I-R ponies, six ponies were studied in a cross-over design by Minimal Model analysis of a frequently-sampled intravenous glucose tolerance test (FSIGT). Metformin was administered at 15. mg/kg bodyweight (BW), orally, twice-daily, for 21. days to the metformin-treated group. The control group received a placebo. A FSIGT was conducted before and after treatment. The Minimal Model of glucose and insulin dynamics rendered indices describing SI, glucose effectiveness (Sg), acute insulin response to glucose (AIRg) and the disposition index (DI). The body condition score (BCS), BW and cresty neck score (CNS) were also assessed. There was no significant change in SI, Sg, AIRg, DI, BW, BCS or CNS in response to metformin, or over time in the control group. There were no measurable benefits of metformin on SI, consistent with recent work showing that the bioavailability of metformin in horses is poor, and chronic dosing may not achieve therapeutic blood concentrations. Alternatively, metformin may only be effective in obese ponies losing weight or with hyperglycaemia.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

Nonlinear interactions of azimuthal surface waves in magnetoactive plasma filled waveguides

This paper deals with the theoretical studies of nonlinear interactions of azimuthal surface waves (ASW) in cylindrical metal waveguides fully filled by a uniform magnetoactive plasma. These surface-type wave perturbations propagate in azimuthal direction across an external magnetic field, which is directed along the waveguide axis. The ASW is a relatively new kind of surface waves and so far the nonlinear effects associated with their propagation are outside the scope of scientific issues. They are characterized by a discrete set of mode numbers values which define the ASW eigenfrequencies. This fact leads to several peculiarities of ASW compared with ordinary surface-type waves.

Interacting motile agents : taking a mean-field approach beyond monomers and nearest-neighbor steps

We consider a discrete agent-based model on a one-dimensional lattice, where each agent occupies L sites and attempts movements over a distance of d lattice sites. Agents obey a strict simple exclusion rule. A discrete-time master equation is derived using a mean-field approximation and careful probability arguments. In the continuum limit, nonlinear diffusion equations that describe the average agent occupancy are obtained. Averaged discrete simulation data are generated and shown to compare very well with the solution to the derived nonlinear diffusion equations. This framework allows us to approach a lattice-free result using all the advantages of lattice methods. Since different cell types have different shapes and speeds of movement, this work offers insight into population-level behavior of collective cellular motion.

Collective motion of dimers

We consider a discrete agent-based model on a one-dimensional lattice and a two-dimensional square lattice, where each agent is a dimer occupying two sites. Agents move by vacating one occupied site in favor of a nearest-neighbor site and obey either a strict simple exclusion rule or a weaker constraint that permits partial overlaps between dimers. Using indicator variables and careful probability arguments, a discrete-time master equation for these processes is derived systematically within a mean-field approximation. In the continuum limit, nonlinear diffusion equations that describe the average agent occupancy of the dimer population are obtained. In addition, we show that multiple species of interacting subpopulations give rise to advection-diffusion equations. Averaged discrete simulation data compares very well with the solution to the continuum partial differential equation models. Since many cell types are elongated rather than circular, this work offers insight into population-level behavior of collective cellular motion.

Comparing multilevel and Bayesian spatial random effects survival models to assess geographical inequalities in colorectal cancer survival: a case study

Background Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. Methods Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20–84 years diagnosed during 1997–2007 from Queensland, Australia. Results Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients. Conclusions With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings

MRI-based measurement of carotid mechanical properties in asymptomatic patients

Arterial mechanical property may be a potential variable for risk stratification. Large artery and central arterial compliance have been shown not only to correlate well with overall cardiovascular outcome in large epidemiological studies [1, 2] but also to correlate with coronary atherosclerotic burden as measured by conventional angiography [3]. Until recently, real-time B-mode ultrasound combined with simultaneous blood pressure measurements have been used to assess large artery compliance [4]. These techniques have an excellent temporal resolution but are unable to provide adequate spatial resolution to determine changes in vessel area as opposed to diameter and make the assumption that the vessel is perfectly round. Attempts to use MR imaging to measure large artery compliance have been published previously [5]. However, they have not utilised simultaneous blood pressure measurements during sequence acquisition. We report a technique using regular and simultaneous blood pressure measurement during 2 dimensional phase contrast magnetic resonance imaging 2DPC-MRI to determine local carotid compliance.

Insights into students' conceptual understanding using textual analysis: A case study in signal processing

Concept inventory tests are one method to evaluate conceptual understanding and identify possible misconceptions. The multiple-choice question format, offering a choice between a correct selection and common misconceptions, can provide an assessment of students' conceptual understanding in various dimensions. Misconceptions of some engineering concepts exist due to a lack of mental frameworks, or schemas, for these types of concepts or conceptual areas. This study incorporated an open textual response component in a multiple-choice concept inventory test to capture written explanations of students' selections. The study's goal was to identify, through text analysis of student responses, the types and categorizations of concepts in these explanations that had not been uncovered by the distractor selections. The analysis of the textual explanations of a subset of the discrete-time signals and systems concept inventory questions revealed that students have difficulty conceptually explaining several dimensions of signal processing. This contributed to their inability to provide a clear explanation of the underlying concepts, such as mathematical concepts. The methods used in this study evaluate students' understanding of signals and systems concepts through their ability to express understanding in written text. This may present a bias for students with strong written communication skills. This study presents a framework for extracting and identifying the types of concepts students use to express their reasoning when answering conceptual questions.

The Art of Studio Teaching

This project began in 2013, with the award of an internal QUT Teaching and Learning grant. The task we wished to undertake was to document and better understand the role of studio teaching practice in the Creative Industries Faculty. While it was well understood that the Faculty had long used studio pedagogies as a key part of its teaching approach, organizational and other changes made it productive and timely to consider how the various study areas within the Faculty were approaching studio teaching. Chief among these changes were innovations in the use of technology in teaching, and at an organizational level the merging of what were once two schools within different faculties into a newly-structured Creative Industries Faculty. The new faculty consists of two schools, Media, Entertainment and Creative Art (MECA) and Design. We hoped to discover more about how studio techniques were developing alongside an ever-increasing number of options for content delivery, assessment, and interaction with students. And naturally we wanted to understand such developments across the broad range of nineteen study areas now part of the Creative Industries Faculty. This e-book represents the first part of our project, which in the main consisted in observing the teaching practices used in eight units across the Faculty, and then interviews with the unit coordinators involved. In choosing units, we opted for a broad opening definition of ‘studio’ to include not only traditional studios but also workshops and tutorials in which we could identify a component of studio teaching as enumerated by the Australian Learning and Teaching Council’s Studio Teaching Project: • A culture, a creative community created by a group of students and studio teachers working together for periods of time • A mode of teaching and learning where students and studio teachers interact in a creative and reflective process • A program of projects and activities where content is structured to enable ‘learning in action’ • A physical space or constructed environment in which the teaching and learning can take place (Source: http://www.studioteaching.org/?page=what_is_studio) The units we chose to observe, and which we hoped would represent something of the diversity of our study areas, were: • Dance Project 1 • Furniture Studies • Wearable Architecture • Fashion Design 4 • Industrial Design 6 • Advanced Writing Practice 3 • Introduction to Creative Writing • Studio Art Practice 2 Over the course of two semesters in 2013, we attended classes, presentations, and studio time in these units, and then conducted interviews that we felt would give further insight into both individual and discipline-specific approaches to studio pedagogies. We asked the same questions in each of the interviews: • Could you describe the main focus and aims of your unit? • How do you use studio time to achieve those aims? • Can you give us an example of the kind of activities you use in your studio teaching? • What does/do these example(s) achieve in terms of learning outcomes? • What, if any, is the role of technology in your studio teaching practice? • What do you consider distinctive about your approach to studio teaching, or the approach taken in your discipline area? The unit coordinators’ responses to these questions form some of the most interesting and valuable material in this book, and point to both consistencies in approach and teaching philosophies, as well as areas of difference. We believe that both can help to raise our critical awareness of studio teaching, and provide points of comparison for the future development of studio pedagogy in the Creative Industries. In each of the following pages, the interviews are placed alongside written descriptions of the units, their aims and outcomes, assessment models, and where possible photographs and video footage, as well as additional resources that may be useful to others engaged in studio teaching.

Real-time decision making by driverless city vehicles : a discrete event driven approach

This thesis addresses the topic of real-time decision making by driverless (autonomous) city vehicles, i.e. their ability to make appropriate driving decisions in non-simplified urban traffic conditions. After addressing the state of research, and explaining the research question, the thesis presents solutions for the subcomponents which are relevant for decision making with respect to information input (World Model), information output (Driving Maneuvers), and the real-time decision making process. TheWorld Model is a software component developed to fulfill the purpose of collecting information from perception and communication subsystems, maintaining an up-to-date view of the vehicle’s environment, and providing the required input information to the Real-Time Decision Making subsystem in a well-defined, and structured way. The real-time decision making process consists of two consecutive stages. While the first decision making stage uses a Petri net to model the safetycritical selection of feasible driving maneuvers, the second stage uses Multiple Criteria Decision Making (MCDM) methods to select the most appropriate driving maneuver, focusing on fulfilling objectives related to efficiency and comfort. The complex task of autonomous driving is subdivided into subtasks, called driving maneuvers, which represent the output (i.e. decision alternatives) of the real-time decision making process. Driving maneuvers are considered as implementations of closed-loop control algorithms, each capable of maneuvering the autonomous vehicle in a specific traffic situation. Experimental tests in both a 3D simulation and real-world experiments attest that the developed approach is suitable to deal with the complexity of real-world urban traffic situations.

Communication Architecture Design for Real-Time Networked Control Systems

Networked control over data networks has received increasing attention in recent years. Among many problems in networked control systems (NCSs) is the need to reduce control latency and jitter and to deal with packet dropouts. This paper introduces our recent progress on a queuing communication architecture for real-time NCS applications, and simple strategies for dealing with packet dropouts. Case studies for a middle-scale process or multiple small-scale processes are presented for TCP/IP based real-time NCSs. Variations of network architecture design are modelled, simulated, and analysed for evaluation of control latency and jitter performance. It is shown that a simple bandwidth upgrade or adding hierarchy does not necessarily bring benefits for performance improvement of control latency and jitter. A co-design of network and control is necessary to maximise the real-time control performance of NCSs