Real-time Burst Detection in Water Distribution Systems Using a Bayesian Demand Forecasting Methodology

AbstractThe negative consequences of non-revenue water losses from Water Distribution Systems (WDS) can be reduced through the successful and prompt identification of bursts and abnormal conditions. Here we present a preliminary investigation into the application of a probabilistic demand forecasting approach to identify pipe bursts. The method produces a probabilistic forecast of future demand under normal conditions. This, in turn, quantifies the probability that a future observation is abnormal. The method, when tested using synthetic bursts applied to a demand time-series for a UK WDS, performed well in detecting bursts, particularly those >5% of mean daily flow at night time

Breaking barriers, building community: improving student engagement with preparation for studying online multidisciplinary science by distance learning - a case study

Developing an online learning community can help to improve student success. This presents a challenge as the student cohort is often time-limited and shifting in composition before a module starts. The continued evaluation and development of an online preparatory website for the new, year one module S112 - Science: concepts and practice is reported. Evaluation of the site in 2017-18 showed high levels of student satisfaction with the resources, though very little engagement with the asynchronous forum. Therefore, improvements before the October 2018 module start centred on increasing student engagement on the forum: Firstly, tutors moderating the forums were tasked with developing several optional scientific tasks for staged release to generate student discussion. Secondly, volunteer peer mentors from the 2017-18 presentation were recruited and trained as “student buddies” to provide non-academic advice and support.Student engagement increased markedly prior to the October 2018 module. The clearest emergent theme from tutors who moderated the forums was that students were seeking to establish a study community, rather than obtain subject-specific advice. Student response to the buddies was positive, with students more willing to ask questions of the buddies than of the tutor moderators. Data for S112 show that registrations at module start increased by 23.5% from 2017 to 2018, and early withdrawals (14 days after module start) dropped by 2%.Our results provide ideas for building online student engagement, particularly in scenarios where students may come and go, and have little available time: for example, bridging gaps in time or academic readiness, whether by blended or distance learning

Assessing the value of seasonal hydrological forecasts for improving water resource management:insights from a pilot application in the UK

Improved skill of long-range weather forecasts have motivated an increasing effort towards developing seasonal hydrological forecasting systems across Europe. Among other purposes, such forecasting systems are expected to support better water management decisions. In this paper we evaluate the potential use of a real-time optimisation system (RTOS) informed by seasonal forecasts in a water supply system in the UK. For this purpose, we simulate the performances of the RTOS fed by ECMWF seasonal forecasting systems (SEAS5) over the past ten years, and we compare them to a benchmark operation that mimics the common practices for reservoir operation in the UK. We also attempt to link the improvement of system performances, i.e. the forecast value, to the forecast skill (measured by the mean error and the Continuous Ranked Probability Skill Score) as well as other factors such as bias correction, the decision maker priorities, hydrological conditions and level of uncertainty consideration. We find that some of these factors control the forecast value much more strongly than the forecast skill. For the (realistic) scenario where the decision-maker prioritises water resource availability over energy cost reductions, we identify clear operational benefits from using seasonal forecasts, provided that forecast uncertainty is explicitly considered. However, when comparing the use of ECMWF-SEAS5 products to ensemble streamflow predictions (ESP), which are more easily derived from historical weather data, we find that ESP remains a hard-to-beat reference not only in terms of skill but also in terms of value

Characterization of Prepreg Tack for Composite Manufacturing by Automated Fiber Placement

Automated fiber placement (AFP) has become the industry standard for large-scale production of carbon fiber reinforced plastics (CFRP) to improve rate and reduce defects associated with manual layup. Still, defects generated during AFP processes require manual, painstaking inspection by technicians and rework of the part when substantial defects are found. Prepreg (carbon fiber infused with uncured epoxy resin) tack is one of the primary factors that influences the generation of defects that arise during auto-mated fiber placement (AFP). Tack, as it relates to AFP processes and defect formation, can be understood as a combination of two stages, cohesion and decohesion. During the cohesion phase, two pieces of prepreg are brought into contact under elevated temperature and pressure. Compaction of the resin within the contact area will result in a degree of intimate contact, I, between the mating prepreg surfaces. Defect formation, as a result of decohesion between prepreg surfaces, occurs after the cohesion phase and arises due to stress from events such as fiber placement over an existing defect, on a contoured path, etc. (Figure 1). Tack strength resists the displacement of prepreg on a surface due to stresses developed during deposition

Evaluating the effectiveness of printed materials as an alternative to online resources

The Open University has a strategic priority to maximise accessibility of its module materials. The majority of the Environmental Science curriculum is delivered online, and this presents accessibility challenges for students with certain additional learning requirements and those in secure institutions. Printed packs of online materials are provided to these students. We will present our initial evaluation of this adjustment and discuss our results and next steps for improving its efficacy. This session will be of interest to colleagues from across higher education who need to provide alternative resources to students who can’t access online resources

Towards Best Practice In Designing Sustainable Online Peer Mentoring At Scale - What’s In It For The Mentors?

The benefits of peer mentoring for students studying in Higher Education are well established and have been demonstrated in online, blended and hybrid settings. Best practice in establishing financially sustainable schemes in online settings at a large scale is under researched. Motivations and barriers for peer mentors working effectively as volunteers are poorly established. Findings of a longitudinal study on undergraduate Earth and Environmental Science modules at The Open University, UK are presented. Peer mentors (who had already passed the module) were surveyed before and after completing a 9-month period supporting students asynchronously with non-academic support via a forum. Questionnaires established the challenges and benefits for the mentors, and were followed up by focus groups. Most mentors remained active and committed throughout, identifying few barriers; their expectations before starting were similar to their actual experience. More students volunteer for mentoring than are needed, with many completing more than one round of duty. It is therefore concluded that the mentoring scheme is financially sustainable and transferable to different modules and disciplines. While mentors valued their skills development, further work is required to help them appreciate their employability skills development and potential impact