Optimal control of nonlinear differential algebraic equation systems

A novel iterative procedure is described for solving nonlinear optimal control problems subject to differential algebraic equations. The procedure iterates on an integrated modified linear quadratic model based problem with parameter updating in such a manner that the correct solution of the original non-linear problem is achieved. The resulting algorithm has a particular advantage in that the solution is achieved without the need to solve the differential algebraic equations . Convergence aspects are discussed and a simulation example is described which illustrates the performance of the technique. 1. Introduction When modelling industrial processes often the resulting equations consist of coupled differential and algebraic equations (DAEs). In many situations these equations are nonlinear and cannot readily be directly reduced to ordinary differential equations.

A technique for delivering individualised formative problems and examples

Active learning plays a strong role in mathematics and statistics, and formative problems are vital for developing key problem-solving skills. To keep students engaged and help them master the fundamentals before challenging themselves further, we have developed a system for delivering problems tailored to a student‟s current level of understanding. Specifically, by adapting simple methodology from clinical trials, a framework for delivering existing problems and other illustrative material has been developed, making use of macros in Excel. The problems are assigned a level of difficulty (a „dose‟), and problems are presented to the student in an order depending on their ability, i.e. based on their performance so far on other problems. We demonstrate and discuss the application of the approach with formative examples developed for a first year course on plane coordinate geometry, and also for problems centred on the topic of chi-square tests.

A nonparametric ensemble transform method for Bayesian inference

Many applications, such as intermittent data assimilation, lead to a recursive application of Bayesian inference within a Monte Carlo context. Popular data assimilation algorithms include sequential Monte Carlo methods and ensemble Kalman filters (EnKFs). These methods differ in the way Bayesian inference is implemented. Sequential Monte Carlo methods rely on importance sampling combined with a resampling step, while EnKFs utilize a linear transformation of Monte Carlo samples based on the classic Kalman filter. While EnKFs have proven to be quite robust even for small ensemble sizes, they are not consistent since their derivation relies on a linear regression ansatz. In this paper, we propose another transform method, which does not rely on any a priori assumptions on the underlying prior and posterior distributions. The new method is based on solving an optimal transportation problem for discrete random variables. © 2013, Society for Industrial and Applied Mathematics

Measuring the value of “all play and no work”: can rigorous assessment of simulation games drive innovative teaching in construction?

The construction field is dynamic and dominated by complex, ill-defined problems for which myriad possible solutions exist. Teaching students to solve construction-related problems requires an understanding of the nature of these complex problems as well as the implementation of effective instructional strategies to address them. Traditional approaches to teaching construction planning and management have long been criticized for presenting students primarily with well-defined problems - an approach inconsistent with the challenges encountered in the industry. However, growing evidence suggests that employing innovative teaching approaches, such as interactive simulation games, offers more active, hands-on and problem-based learning opportunities for students to synthesize and test acquired knowledge more closely aligned with real-life construction scenarios. Simulation games have demonstrated educational value in increasing student problem solving skills and motivation through critical attributes such as interaction and feedback-supported active learning. Nevertheless, broad acceptance of simulation games in construction engineering education remains limited. While recognizing benefits, research focused on the role of simulation games in educational settings lacks a unified approach to developing, implementing and evaluating these games. To address this gap, this paper provides an overview of the challenges associated with evaluating the effectiveness of simulation games in construction education that still impede their wide adoption. An overview of the current status, as well as the results from recently implemented Virtual Construction Simulator (VCS) game at Penn State provide lessons learned, and are intended to guide future efforts in developing interactive simulation games to reach their full potential.

Forensic students are getting their hands dirty

Final year research projects are an important part of undergraduate chemistry courses, allowing students to enhance transferable skills in teamworking, problem solving and presentations, at the same time as learning valuable practical skills. Several recent reports have highlighted the importance of research based studies as part of undergraduate courses. ‘We need to encourage universities to explore new models of curriculum. They should all incorporate research based study for undergraduates to cultivate awareness of research careers, to train students in research skills for employment, and to sustain the advantages of a research teaching connection,’ wrote Paul Ramsden from James Cook University, Australia, in a 2008 report for the UK’s Higher Education Academy.1 A 2010 report published by the Biopharma Skills Consortium – that promotes collaboration across the higher education sector in the area of biopharma – also stated that: ‘Companies seek recruits well placed to acclimatise quickly to the work environment. They are looking for recruits who can deploy a range of generic skills in the application of their knowledge.’2

The CURE scale: a multidimensional measure of service recovery strategy

Purpose – This paper aims to address the gaps in service recovery strategy assessment. An effective service recovery strategy that prevents customer defection after a service failure is a powerful managerial instrument. The literature to date does not present a comprehensive assessment of service recovery strategy. It also lacks a clear picture of the service recovery actions at managers’ disposal in case of failure and the effectiveness of individual strategies on customer outcomes. Design/methodology/approach – Based on service recovery theory, this paper proposes a formative index of service recovery strategy and empirically validates this measure using partial least-squares path modelling with survey data from 437 complainants in the telecommunications industry in Egypt. Findings – The CURE scale (CUstomer REcovery scale) presents evidence of reliability as well as convergent, discriminant and nomological validity. Findings also reveal that problem-solving, speed of response, effort, facilitation and apology are the actions that have an impact on the customer’s satisfaction with service recovery. Practical implications – This new formative index is of potential value in investigating links between strategy and customer evaluations of service by helping managers identify which actions contribute most to changes in the overall service recovery strategy as well as satisfaction with service recovery. Ultimately, the CURE scale facilitates the long-term planning of effective complaint management. Originality/value – This is the first study in the service marketing literature to propose a comprehensive assessment of service recovery strategy and clearly identify the service recovery actions that contribute most to changes in the overall service recovery strategy.

Towards a nutrient export risk matrix approach to managing agricultural pollution at source

A generic Nutrient Export Risk Matrix (NERM) approach is presented. This provides advice to farmers and policy makers on good practice for reducing nutrient loss and is intended to persuade them to implement such measures. Combined with a range of nutrient transport modelling tools and field experiments, NERMs can play an important role in reducing nutrient export from agricultural land. The Phosphorus Export Risk Matrix (PERM) is presented as an example NERM. The PERM integrates hydrological understanding of runoff with a number of agronomic and policy factors into a clear problem-solving framework. This allows farmers and policy makers to visualise strategies for reducing phosphorus loss through proactive land management. The risk Of Pollution is assessed by a series of informed questions relating to farming intensity and practice. This information is combined with the concept of runoff management to point towards simple, practical remedial strategies which do not compromise farmers' ability to obtain sound economic returns from their crop and livestock.

Metacognitive experience and transfer of logical reasoning

The experiments examine the influence of metacognitive experience on the transfer of logical processes in a problem solving setting. Subjects were presented with two versions of Wason's (1966) selection task. Although they were able to perform successfully on the concrete tasks (following a minimal explanation of the correct solution on an initial trial), the majority were not able to transfer a successful method to the abstract tasks. Verbalization during, or following, the concrete tasks produced substantial transfer effects however. It is suggested that verbalization may lead to an increased awareness of past behaviour, particularly of those aspects necessary for successful solution.

Working memory and working attention: What could possibly evolve?

The concept of “working” memory is traceable back to nineteenth century theorists (Baldwin, 1894; James 1890) but the term itself was not used until the mid-twentieth century (Miller, Galanter & Pribram, 1960). A variety of different explanatory constructs have since evolved which all make use of the working memory label (Miyake & Shah, 1999). This history is briefly reviewed and alternative formulations of working memory (as language-processor, executive attention, and global workspace) are considered as potential mechanisms for cognitive change within and between individuals and between species. A means, derived from the literature on human problem-solving (Newell & Simon, 1972), of tracing memory and computational demands across a single task is described and applied to two specific examples of tool-use by chimpanzees and early hominids. The examples show how specific proposals for necessary and/or sufficient computational and memory requirements can be more rigorously assessed on a task by task basis. General difficulties in connecting cognitive theories (arising from the observed capabilities of individuals deprived of material support) with archaeological data (primarily remnants of material culture) are discussed.

Age and flexible thinking: an experimental demonstration of the beneficial effects of increased cognitively stimulating activity on fluid intelligence in healthy older adults

The disuse hypothesis of cognitive aging attributes decrements in fluid intelligence in older adults to reduced cognitively stimulating activity. This study experimentally tested the hypothesis that a period of increased mentally stimulating activities thus would enhance older adults' fluid intelligence performance. Participants (N = 44, mean age 67.82) were administered pre- and post-test measures, including the fluid intelligence measure, Cattell's Culture Fair (CCF) test. Experimental participants engaged in diverse, novel, mentally stimulating activities for 10-12 weeks and were compared to a control condition. Results supported the hypothesis; the experimental group showed greater pre- to post-CCF gain than did controls (effect size d = 0.56), with a similar gain on a spatial-perceptual task (WAIS-R Blocks). Even brief periods of increased cognitive stimulation can improve older adults' problem solving and flexible thinking.

Conversational success in Williams syndrome: communication in the face of cognitive and linguistic limitations

Williams syndrome (WS) is characterized by apparent relative strengths in language, facial processing and social cognition but by profound impairment in spatial cognition, planning and problem solving. Following recent research which suggests that individuals with WS may be less linguistically able than was once thought, in this paper we begin to investigate why and how they may give the impression of linguistic proficiency despite poor standardized test results. This case study of Brendan, a 12-year-old boy with WS, who presents with a considerable lack of linguistic ability, suggests that impressions of linguistic competence may to some extent be the result of conversational strategies which enable him to compensate for various cognitive and linguistic deficits with a considerable degree of success. These conversational strengths are not predicted by his standardized language test results, and provide compelling support for the use of approaches such as Conversation Analysis in the assessment of individuals with communication impairments.

An algorithm for the shallow water equations with body fitted meshes

An efficient algorithm based on flux difference splitting is presented for the solution of the two-dimensional shallow water equations in a generalised coordinate system. The scheme is based on solving linearised Riemann problems approximately and in more than one dimension incorporates operator splitting. The scheme has good jump capturing properties and the advantage of using body-fitted meshes. Numerical results are shown for flow past a circular obstruction.

An isentropic flow algorithm with body fitted meshes

An efficient algorithm based on flux difference splitting is presented for the solution of the three-dimensional equations of isentropic flow in a generalised coordinate system, and with a general convex gas law. The scheme is based on solving linearised Riemann problems approximately and in more than one dimension incorporates operator splitting. The algorithm requires only one function evaluation of the gas law in each computational cell. The scheme has good shock capturing properties and the advantage of using body-fitted meshes. Numerical results are shown for Mach 3 flow of air past a circular cylinder. Furthermore, the algorithm also applies to shallow water flows by employing the familiar gas dynamics analogy.