Automating construction manufacturing procedures using BIM digital objects (BDOs): Case study of knowledge transfer partnership project in UK

Purpose This paper aims to present a novel proof-of-concept framework for implementing building information modeling (BIM) Digital Objects (BDO) to automate construction product manufacturers’ processes and augment lean manufacturing. Design/methodology/approach A mixed interpretivist and post-positivist epistemological lens is adopted to pursue the proof-of-concept’s development. From an operational perspective, a synthesis of literature using interpretivism provides the foundation for deductive research inquiry implemented within a case study approach. Within the case study, participatory action research (PAR) is implemented to test the proof of concept via three “waterfall” research phases, namely, literature diagnosis and BIM package selection, BDO development and validation and evaluation. Findings The findings illustrate that a BDO (which represents the digital twin of manufacturing products) can augment and drive automation processes and workflows for construction product manufacturers within a contractor’s supply chain. The developed framework illustrates the benefits of a BDO, by reducing the number of manufacturing processes to effectively eliminate early errors in the model, generates financial savings and reduces material wastage. Originality/value This research provides a seminal case study that implements BDO to automate construction product manufacturing processes and demonstrates the utilisation of BDO at an operational (vis-à-vis theoretical) level. Future research is proposed to implement a longitudinal approach to measure and report upon the success (or otherwise) of the proof of concept when implemented on fabrications and shop floor procedures

Contribution of soil bacteria to the atmosphere across biomes

Artículo escrito por un elevado número de autores, solo se referencian el que aparece en primer lugar, los autores pertenecientes a la UAM y el nombre del grupo de colaboración, si lo hubiereThe dispersion of microorganisms through the atmosphere is a continual and essential process that underpins biogeography and ecosystem development and function. Despite the ubiquity of atmospheric microorganisms globally, specific knowledge of the determinants of atmospheric microbial diversity at any given location remains unresolved. Here we describe bacterial diversity in the atmospheric boundary layer and underlying soil at twelve globally distributed locations encompassing all major biomes, and characterise the contribution of local and distant soils to the observed atmospheric community. Across biomes the diversity of bacteria in the atmosphere was negatively correlated with mean annual precipitation but positively correlated to mean annual temperature. We identified distinct non-randomly assembled atmosphere and soil communities from each location, and some broad trends persisted across biomes including the enrichment of desiccation and UV tolerant taxa in the atmospheric community. Source tracking revealed that local soils were more influential than distant soil sources in determining observed diversity in the atmosphere, with more emissive semi-arid and arid biomes contributing most to signatures from distant soil. Our findings highlight complexities in the atmospheric microbiota that are relevant to understanding regional and global ecosystem connectivityThis work was supported by the Singapore Ministry of Education and Yale-NUS College, grant number R-607-265-331-12

The value of 'community' in supporting transitions outside university

Statistics from the Destinations of Leavers in Higher Education (DLHE) survey has shown that graduate level employment or study 6 months after graduation is relatively low for psychology graduates compared to graduates from other disciplines. Due to highly competitive conditions for postgraduate places on professional psychology training courses, new graduates often spend time developing their portfolio of relevant skills and experience in order to compete for postgraduate places one or more years after graduating. In addition, QAA (2010) noted that only 15-20% of psychology graduates develop careers as professional psychologists. Many initiatives have been introduced across the UK (see Reddy, Lantz, & Hulme, 2013) to support students' transitions out of university and into employment or further study, however these initiatives vary in the extent to which they are embedded and capture student engagement. At the University of Strathclyde, we are taking a multi-pronged approach to enhancing students’ employability that is underpinned by an ethos of ‘community’. First, the creation of the Strathclyde Psychology Alumni Network (SPAN), developed in collaboration with students, provides a platform through which current students, alumni, and staff, interact as members of the Strathclyde Psychology Community, virtually via LinkedIn and face-to-face at networking events. Second, a new work placement class in the final year will provide students the opportunity to enhance their experience and apply their psychological knowledge and skills in a work-based context. Third, a novel curriculum review process involving staff, alumni, and employers (representing private, public, and third sectors) has sought to identify the opportunities and challenges that graduates face, and the characteristics of the ‘Ideal Strathclyde Psychology Graduate’. A core competency framework will be output from this process and will drive the curriculum enhancement process so that students have the opportunity to develop the characteristics of the ‘Ideal Strathclyde Psychology Graduate’

A generalized model for fuel channel bore estimation in AGR cores

One of the major life-limiting factors of an Advanced Gas-cooled Reactor (AGR) nuclear power station is the graphite core as it cannot be repaired or replaced and therefore detailed information about the health of the core is vital for continued safe operation. The graphite bricks that comprise the core experience gradual degradation during operation as a result of irradiation. Routine physical inspection of the graphite core fuel channels is performed by specialist inspection equipment during outages every 12 months to 3 years. It has also been shown to be advantageous to supplement this periodic inspection information with analysis of operational data which can provide additional insights into the core health. One such approach is through the use of online monitoring data called the Fuel Grab Load Trace (FGLT). An FGLT is a measure of the perceived load of the fuel assembly with contributions from aerodynamic forces and frictional forces, which is related to bore diameter. This paper describes enhancements to existing analysis of FGLT data which, to date, has focussed solely on using data from a single reactor at a time to build bore estimation models, by considering data from multiple reactors to produce a generalised model of bore estimation. This paper initially describes the process of producing a bore estimation from an FGLT by isolating the contribution that relates to the fuel channel bore and then discusses the limitations with the existing bore estimation model. Improvements are then proposed for the bore estimation model and a detailed assessment is undertaken to understand the effect of each of these proposed improvements. In addition, the effect of introducing non-linear regression models to further enhance the bore estimation is explored. The existing model is trained on data from one reactor in the UK and therefore the results produced from it are only applicable to this reactor. However, out of the remaining 13 nuclear reactors currently in operation, 3 also have a similar construction to the reactor the model is trained on, and these should all produce similar FGLT data. Therefore, a generalised model is proposed that produces bore estimations for four AGRs station’s reactors, compared with one previously. It is shown that this approach offers an improved overall bore estimation model

Electrodynamics of quasi-two-dimensional BEDT-TTF charge transfer salts

We consider the millimeter-wave electrodynamics specific to quasi-two-dimensional conductors and superconductors based on the organic donor molecule BEDT-TTF. Using realistic physical parameters, we examine the current polarizations that result for different oscillating (GHz) electric and magnetic field polarizations. We show that, in general, it is possible to discriminate between effects (dissipation and dispersion) due to in-plane and interlayer ac currents. However, we also show that it is not possible to selectively probe any single component of the in-plane conductivity tensor, and that excitation of interlayer currents is strongly influenced by the sample geometry and the electromagnetic field polarization.Comment: 5 pages including 3 figures Minor correction to figure

A data analytic approach to automatic fault diagnosis and prognosis for distribution automation

Distribution Automation (DA) is deployed to reduce outages and to rapidly reconnect customers following network faults. Recent developments in DA equipment have enabled the logging of load and fault event data, referred to as ‘pick-up activity’. This pick-up activity provides a picture of the underlying circuit activity occurring between successive DA operations over a period of time and has the potential to be accessed remotely for off-line or on-line analysis. The application of data analytics and automated analysis of this data supports reactive fault management and post fault investigation into anomalous network behavior. It also supports predictive capabilities that identify when potential network faults are evolving and offers the opportunity to take action in advance in order to mitigate any outages. This paper details the design of a novel decision support system to achieve fault diagnosis and prognosis for DA schemes. It combines detailed data from a specific DA device with rule-based, data mining and clustering techniques to deliver the diagnostic and prognostic functions. These are applied to 11kV distribution network data captured from Pole Mounted Auto-Reclosers (PMARs) as provided by a leading UK network operator. This novel automated analysis system diagnoses the nature of a circuit’s previous fault activity, identifies underlying anomalous circuit activity, and highlights indications of problematic events gradually evolving into a full scale circuit fault. The novel contributions include the tackling of ‘semi-permanent faults’ and the re-usable methodology and approach for applying data analytics to any DA device data sets in order to provide diagnostic decisions and mitigate potential fault scenarios

The effect of different combinations of vascular, dependency and cognitive endpoints on the sample size required to detect a treatment effect in trials of treatments to improve outcome after lacunar and non-lacunar ischaemic stroke

Background Endpoints that are commonly used in trials of moderate/severe stroke may be less frequent in patients with minor, non-disabling stroke thus inflating sample sizes. We tested whether trial efficiency might be improved with composite endpoints. Methods We prospectively recruited patients with lacunar and minor non-lacunar ischaemic stroke (NIHSS ≤ 7) and assessed recurrent vascular events (stroke, transient ischaemic attack (TIA), ischemic heart disease (IHD)), modified Rankin Score (mRS) and cognitive testing with the Addenbrooke’s Cognitive Examination (ACE-R) one year post-stroke. For a potential secondary prevention randomised controlled trial (RCT), we estimated sample sizes using individual or combined outcomes, at power 80% (and 90%), alpha 5%, required to detect a relative 10% risk reduction. Results Amongst 264 patients (118 lacunar, 146 non-lacunar), at one year, 30/264 (11%) patients had a recurrent vascular event, 5 (2%) had died, 3 (1%) had clinically-diagnosed dementia, 53/264 (20%) had mRS ≥ 3 and 29/158 (19%) had ACE-R ≤ 82 (57 could not attend for cognitive testing). For a potential trial, at 80% power, using mRS ≥ 3 alone would require n > 5000 participants, recurrent vascular events alone n = 9908 participants, and a composite of any recurrent vascular event, ACE-R ≤ 82, dementia or mRS ≥ 2 (present in 56% of patients) n = 2224 patients. However, including cognition increased missing data. Results were similar for lacunar and non-lacunar minor ischaemic stroke. Conclusions Composite outcomes including vascular events, dependency, and cognition reduce sample size and increase efficiency, feasibility, and relevance to patients of RCTs in minor ischaemic stroke. Efficiency might be improved further with more practical cognitive test strategies

A Gaussian process based fleet lifetime predictor model for unmonitored power network assets

This paper proposes the use of Gaussian Process Regression to automatically identify relevant predictor variables in a formulation of a remaining useful life model for unmonitored, low value power network assets. Reclosers are used as a proxy for evaluating the efficacy of this method. Distribution network reclosers are typically high-volume assets without on-line monitoring, leading to an insufficient understanding of which factors drive their failures. The ubiquity of reclosers, and their lack of monitoring, prevents the tracking of their individual remaining life, and, confirms their use in validating the proposed process. As an alternative to monitoring, periodic inspection data is used to evaluate asset risk level, which is then used in a predictive model of remaining useful life. Inspection data is often variable in quality with a number of features missing from records. Accordingly, missing inputs are imputed by the proposed process using samples drawn from an advanced form of joint distribution learned from test records and reduced to its conditional form. This work is validated on operational data provided by a regional distribution network operator, but conceptually is applicable to unmonitored fleets of assets of any power network