Perspectives on research in project management : the nine schools

This paper demonstrates that project management is a developing field of academic study in management, of considerable diversity and richness, which can make a valuable contribution to the development of management knowledge, as well as being of considerable economic importance. The paper reviews the substantial progress and trends of research in the subject, which has been grouped into nine major schools of thought: optimization, modelling, governance, behaviour, success, decision, process, contingency, and marketing. The paper addresses interactions between the different schools and with other related management fields, and provides insights into current and potential research in each and across these schools.

Strain engineering of selective chemical adsorption on monolayer MoS2

Nanomaterials are prone to influence by chemical adsorption because of their large surface to volume ratios. This enables sensitive detection of adsorbed chemical species which, in turn, can tune the property of the host material. Recent studies discovered that single and multi-layer molybdenum disulfide (MoS2) films are ultra-sensitive to several important environmental molecules. Here we report new findings from ab inito calculations that reveal substantially enhanced adsorption of NO and NH3 on strained monolayer MoS2 with significant impact on the properties of the adsorbates and the MoS2 layer. The magnetic moment of adsorbed NO can be tuned between 0 and 1 μB; strain also induces an electronic phase transition between half-metal and metal. Adsorption of NH3 weakens the MoS2 layer considerably, which explains the large discrepancy between the experimentally measured strength and breaking strain of MoS2 films and previous theoretical predictions. On the other hand, adsorption of NO2, CO, and CO2 is insensitive to the strain condition in the MoS2 layer. This contrasting behavior allows sensitive strain engineering of selective chemical adsorption on MoS2 with effective tuning of mechanical, electronic, and magnetic properties. These results suggest new design strategies for constructing MoS2-based ultrahigh-sensitivity nanoscale sensors and electromechanical devices.

Critical success factors for the implementation of a knowledge management system in a knowledge-based engineering firm

This research identifies factors that are crucial to the success of a knowledge management system (KMS) implementation in a prominent Australian engineering consultancy firm. The study employs the Delphi method to solicit the opinions of experienced market leaders in the Australian construction industry, and then benchmarks the organisational profile of the consultancy firm against the Delphi findings. From this comparative case study, recommendations are made pertaining to the organisational and cultural changes required within the consultancy firm in order to improve its readiness to successfully implement a KMS.

Starting out in STEM : a study of young men and women in first year science, technology, engineering and mathematics courses

In late 2011, first year university students in science, technology, engineering and mathematics (STEM) courses across Australia were invited to participate in the international Interests and Recruitment in Science (IRIS) study. IRIS investigates the influences on young people's decisions to choose university STEM courses and their subsequent experiences of these courses. The study also has a particular focus on the motivations and experiences of young women in courses such as physics, IT and engineering given the low rates of female participation in these fields. Around 3500 students from 30 Australian universities contributed their views on the relative importance of various school and non-school influences on their decisions, as well as insights into their experiences of university STEM courses so far. It is hoped that their contributions will help improve recruitment, retention and gender equity in STEM higher education and careers.

Digital tablets as a tool for blended learning in power engineering education

Digital tablets have been identified as a tool for enabling blended learning and supporting online teaching and learning. A small scale trial was undertaken to assess the effectiveness of this technology when applied to power engineering education. Critical findings and experiences gained from this trial, including potential benefits, presentation techniques and the resulting student feedback are presented in this paper.

Maximum loadability achievement in SWER networks using optimal sizing and locating of batteries

This paper presents an optimisation algorithm to maximize the loadability of single wire earth return (SWER) by minimizing the cost of batteries and regulators considering the voltage constraints and thermal limits. This algorithm, that finds the optimum location of batteries and regulators, uses hybrid discrete particle swarm optimization and mutation (DPSO + Mutation). The simulation results on realistic highly loaded SWER network show the effectiveness of using battery to improve the loadability of SWER network in a cost-effective way. In this case, while only 61% of peak load can be supplied without violating the constraints by existing network, the loadability of the network is increased to peak load by utilizing two battery sites which are located optimally. That is, in a SWER system like the studied one, each installed kVA of batteries, optimally located, supports a loadability increase as 2 kVA.

Distribution harmonic state estimation based on a modified PSO considering parameters uncertainty

This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).

Load profile based determination of distribution feeder configuration by dynamic programming

This paper presents a new method to determine feeder reconfiguration scheme considering variable load profile. The objective function consists of system losses, reliability costs and also switching costs. In order to achieve an optimal solution the proposed method compares these costs dynamically and determines when and how it is reasonable to have a switching operation. The proposed method divides a year into several equal time periods, then using particle swarm optimization (PSO), optimal candidate configurations for each period are obtained. System losses and customer interruption cost of each configuration during each period is also calculated. Then, considering switching cost from a configuration to another one, dynamic programming algorithm (DPA) is used to determine the annual reconfiguration scheme. Several test systems were used to validate the proposed method. The obtained results denote that to have an optimum solution it is necessary to compare operation costs dynamically.

A novel hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration with regard to DGs

This paper presents an efficient hybrid evolutionary optimization algorithm based on combining Ant Colony Optimization (ACO) and Simulated Annealing (SA), called ACO-SA, for distribution feeder reconfiguration (DFR) considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. The approach is tested on a real distribution feeder. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving DFR problem.

A hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration

This paper deals with an efficient hybrid evolutionary optimization algorithm in accordance with combining the ant colony optimization (ACO) and the simulated annealing (SA), so called ACO-SA. The distribution feeder reconfiguration (DFR) is known as one of the most important control schemes in the distribution networks, which can be affected by distributed generations (DGs) for the multi-objective DFR. In such a case, DGs is used to minimize the real power loss, the deviation of nodes voltage and the number of switching operations. The approach is carried out on a real distribution feeder, where the simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving the DFR problem.

Mechanism based emulation of dynamic simulation models : concept and application in hydrology

Many model-based investigation techniques, such as sensitivity analysis, optimization, and statistical inference, require a large number of model evaluations to be performed at different input and/or parameter values. This limits the application of these techniques to models that can be implemented in computationally efficient computer codes. Emulators, by providing efficient interpolation between outputs of deterministic simulation models, can considerably extend the field of applicability of such computationally demanding techniques. So far, the dominant techniques for developing emulators have been priors in the form of Gaussian stochastic processes (GASP) that were conditioned with a design data set of inputs and corresponding model outputs. In the context of dynamic models, this approach has two essential disadvantages: (i) these emulators do not consider our knowledge of the structure of the model, and (ii) they run into numerical difficulties if there are a large number of closely spaced input points as is often the case in the time dimension of dynamic models. To address both of these problems, a new concept of developing emulators for dynamic models is proposed. This concept is based on a prior that combines a simplified linear state space model of the temporal evolution of the dynamic model with Gaussian stochastic processes for the innovation terms as functions of model parameters and/or inputs. These innovation terms are intended to correct the error of the linear model at each output step. Conditioning this prior to the design data set is done by Kalman smoothing. This leads to an efficient emulator that, due to the consideration of our knowledge about dominant mechanisms built into the simulation model, can be expected to outperform purely statistical emulators at least in cases in which the design data set is small. The feasibility and potential difficulties of the proposed approach are demonstrated by the application to a simple hydrological model.

An exploration of the professional competencies required in engineering asset management

Engineering asset management (EAM) is a rapidly growing and developing field. However, efforts to select and develop engineers in this area are complicated by our lack of understanding of the full range of competencies required to perform. This exploratory study sought to clarify and categorise the professional competencies required of individuals at different hierarchical levels within EAM. Data from 14 field interviews, 61 online surveys, and 10 expert panel interviews were used to develop an initial professional competency framework. Overall, nine competency clusters were identified. These clusters indicate that engineers working in this field need to be able to collaborate and influence others, complete objectives within organisational guidelines, and be able to manage themselves effectively. Limitations and potential uses of this framework in engineering education and research are discussed.

Distribution harmonic state estimation based on a hybrid PSO and SA algorithm considering parameters uncertainty

This paper presents a new algorithm based on a Hybrid Particle Swarm Optimization (PSO) and Simulated Annealing (SA) called PSO-SA to estimate harmonic state variables in distribution networks. The proposed algorithm performs estimation for both amplitude and phase of each harmonic currents injection by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WT). The main feature of proposed PSO-SA algorithm is to reach quickly around the global optimum by PSO with enabling a mutation function and then to find that optimum by SA searching algorithm. Simulation results on IEEE 34 bus radial and a realistic 70-bus radial test networks are presented to demonstrate the speed and accuracy of proposed Distribution Harmonic State Estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO and Honey Bees Mating Optimization (HBMO) algorithm.

Ethnographic notes on visualization practices in tissue engineering

Visual information is central to several of the scientific disciplines. This paper studies how scientists working in a multidisciplinary field produce scientific evidence through building and manipulating scientific visualizations. Using ethnographic methods, we studied visualization practices of eight scientists working in the domain of tissue engineering research. Tissue engineering is an upcoming field of research that deals with replacing or regenerating human cells, tissues, or organs to restore or establish normal function. We spent 3 months in the field, where we recorded laboratory sessions of these scientists and used semi-structured interviews to get an insight into their visualization practices. From our results, we elicit two themes characterizing their visualization practices: multiplicity and physicality. In this article, we provide several examples of scientists’ visualization practices to describe these two themes and show that multimodality of such practices plays an important role in scientific visualization.

Analysis of distance learner value assessment of distance education in engineering

Numerous research studies have evaluated whether distance learning is a viable alternative to traditional learning methods. These studies have generally made use of cross-sectional surveys for collecting data, comparing distance to traditional learners with intent to validate the former as a viable educational tool. Inherent fundamental differences between traditional and distance learning pedagogies, however, reduce the reliability of these comparative studies and constrain the validity of analyses resulting from this analytical approach. This article presents the results of a research project undertaken to analyze expectations and experiences of distance learners with their degree programs. Students were given surveys designed to examine factors expected to affect their overall value assessment of their distance learning program. Multivariate statistical analyses were used to analyze the correlations among variables of interest to support hypothesized relationships among them. Focusing on distance learners overcomes some of the limitations with assessments that compare off- and on-campus student experiences. Evaluation and modeling of distance learner responses on perceived value for money of the distance education they received indicate that the two most important influences are course communication requirements, which had a negative effect, and course logistical simplicity, which revealed a positive effect. Combined, these two factors accounted for approximately 47% of the variability in perceived value for money of the educational program of sampled students. A detailed focus on comparing expectations with outcomes of distance learners complements the existing literature dominated by comparative studies of distance and nondistance learners.