Uncertainty based MDO of UAS using HAPMOEA

CFD has been successfully used in the optimisation of aerodynamic surfaces using a given set of parameters such as Mach numbers and angle of attack. While carrying out a multidisciplinary design optimisation one deals with situations where the parameters have some uncertain attached. Any optimisation carried out for fixed values of input parameters gives a design which may be totally unacceptable under off-design conditions. The challenge is to develop a robust design procedure which takes into account the fluctuations in the input parameters. In this work, we attempt this using a modified Taguchi approach. This is incorporated into an evolutionary algorithm with many features developed in house. The method is tested for an UCAV design which simultaneously handles aerodynamics, electromagnetics and maneuverability. Results demonstrate that the method has considerable potential.

A distributed control based coordination scheme of household PV systems for overvoltage prevention

This paper presents a distributed communication based active power curtailment (APC) control scheme for grid connected photovoltaic (PV) systems to address voltage rise. A simple distribution feeder model is presented and simulated using MATLAB. The resource sharing based control scheme proposed is shown to be effective at reducing voltage rise during times of peak generation and low load. Simulations also show the even distribution of APC using simple communications. Simulations demonstrate the versatility of the proposed control method under major communication failure conditions. Further research may lead to possible applications in coordinated electric vehicle (EV) charging.

Uncertainty based online planning for UAV target finding in cluttered and GPS-denied environments

There are some scenarios in which Unmmaned Aerial Vehicle (UAV) navigation becomes a challenge due to the occlusion of GPS systems signal, the presence of obstacles and constraints in the space in which a UAV operates. An additional challenge is presented when a target whose location is unknown must be found within a confined space. In this paper we present a UAV navigation and target finding mission, modelled as a Partially Observable Markov Decision Process (POMDP) using a state-of-the-art online solver in a real scenario using a low cost commercial multi rotor UAV and a modular system architecture running under the Robotic Operative System (ROS). Using POMDP has several advantages to conventional approaches as they take into account uncertainties in sensor information. We present a framework for testing the mission with simulation tests and real flight tests in which we model the system dynamics and motion and perception uncertainties. The system uses a quad-copter aircraft with an board downwards looking camera without the need of GPS systems while avoiding obstacles within a confined area. Results indicate that the system has 100% success rate in simulation and 80% rate during flight test for finding targets located at different locations.

Data and process requirements for product recall coordination

When an organisation becomes aware that one of its products may pose a safety risk to customers, it must take appropriate action as soon as possible or it can be held liable. The ability to automatically trace potentially dangerous goods through the supply chain would thus help organisations fulfill their legal obligations in a timely and effective manner. Furthermore, product recall legislation requires manufacturers to separately notify various government agencies, the health department and the public about recall incidents. This duplication of effort and paperwork can introduce errors and data inconsistencies. In this paper, we examine traceability and notification requirements in the product recall domain from two perspectives: the activities carried out during the manufacturing and recall processes and the data collected during the enactment of these processes. We then propose a workflow-based coordination framework to support these data and process requirements.

Smarten up! applying market design theory to greyfields housing supply : a background paper

This paper examines whether recent innovation in market design can address persistent problems of housing choice and affordability in the inner and middle suburbs of Australian cities. Australia's ageing middle suburbs are the result of a low density and highly car-dependent garden city greenfield approach to planning that failed to consider possible future resource or environmental constraints on urban development (Newton et al., 2011). Described as 'greyfield' sites in contrast to greenfield (signalling the change from rural to urban land use) and 'brownfield' (being the transformation of former industrial use to mixed use, including housing), intensification of development in such areas is expected to deliver positive social, economic and environmental outcomes (Trubka et al., 2008; Gurran et al., 2006; Newton et al., 2011; Goodman et al., 2010). Yet despite broad policy consensus progress remains elusive (Major Cities Unit, 2010). In this paper we argue that the application of market design theory, specifically through the internet-based coordination of market information, offers a new policy approach and practical measures to address these problems.

Worldwide outdoor round robin study of organic photovoltaic devices and modules

Accurate characterization and reporting of organic photovoltaic (OPV) device performance remains one of the important challenges in the field. The large spread among the efficiencies of devices with the same structure reported by different groups is significantly caused by different procedures and equipment used during testing. The presented article addresses this issue by offering a new method of device testing using “suitcase sample” approach combined with outdoor testing that limits the diversity of the equipment, and a strict measurement protocol. A round robin outdoor characterization of roll-to-roll coated OPV cells and modules conducted among 46 laboratories worldwide is presented, where the samples and the testing equipment were integrated in a compact suitcase that served both as a sample transportation tool and as a holder and test equipment during testing. In addition, an internet based coordination was used via plasticphotovoltaics.org that allowed fast and efficient communication among participants and provided a controlled reporting format for the results that eased the analysis of the data. The reported deviations among the laboratories were limited to 5% when compared to the Si reference device integrated in the suitcase and were up to 8% when calculated using the local irradiance data. Therefore, this method offers a fast, cheap and efficient tool for sample sharing and testing that allows conducting outdoor measurements of OPV devices in a reproducible manner.

Managing a portfolio of corporate venture units : challenges in achieving within-unit focus and between-unit coordination

Principal Topic: There is increasing recognition that the organizational configurations of corporate venture units should depend on the types of ventures the unit seeks to develop (Burgelman, 1984; Hill and Birkinshaw, 2008). Distinction have been made between internal and external as well as exploitative versus explorative ventures (Hill and Birkinshaw, 2008; Narayan et al., 2009; Schildt et al., 2005). Assuming that firms do not want to limit themselves to a single type of venture, but rather employ a portfolio of ventures, the logical consequence is that firms should employ multiple corporate venture units. Each venture unit tailor-made for the type of venture it seeks to develop. Surprisingly, there is limited attention in the literature for the challenges of managing multiple corporate venture units in a single firm. Maintaining multiple venture units within one firm provides easier access to funding for new ideas (Hamel, 1999). It allows for freedom and flexibility to tie the organizational systems (Rice et al., 2000), autonomy (Hill and Rothaermel, 2003), and involvement of management (Day, 1994; Wadwha and Kotha, 2006) to the requirements of the individual ventures. Yet, the strategic objectives of a venture may change when uncertainty around the venture is resolved (Burgelman, 1984). For example, firms may decide to spin-in external ventures (Chesbrough, 2002) or spun-out ventures that prove strategically unimportant (Burgelman, 1984). This suggests that ventures might need to be transferred between venture units, e.g. from a more internally-driven corporate venture division to a corporate venture capital unit. Several studies suggested that ventures require different managerial skills across their phase of development (Desouza et al., 2007; O'Connor and Ayers, 2005; Kazanjian and Drazin, 1990; Westerman et al., 2006). To facilitate effective transfer between venture units and manage the overall venturing process, it is important that firms set up and manage integrative linkages. Integrative linkages provide synergies and coordination between differentiated units (Lawrence and Lorsch, 1967). Prior findings pointed to the important role of senior management (Westerman et al., 2006; Gilbert, 2006) and a shared organizational vision (Burgers et al., 2009) to coordinate venture units with mainstream businesses. We will draw on these literatures to investigate the key question of how to integratively manage multiple venture units. ---------- Methodology/Key Propositions: In order to seek an answer to the research question, we employ a case study approach that provides unique insights into how firms can break up their venturing process. We selected three Fortune 500 companies that employ multiple venturing units, IBM, Royal Dutch/ Shell and Nokia, and investigated and compared their approaches. It was important that the case companies somewhat differed in the type of venture units they employed as well as the way they integrate and coordinate their venture units. The data are based on extensive interviews and a variety of internal and external company documents to triangulate our findings (Eisenhardt, 1989). The key proposition of the article is that firms can best manage their multiple venture units through an ambidextrous design of loosely coupled units. This provides venture units with sufficient flexibility to employ organizational configurations that best support the type of venture they seek to develop, as well as provides sufficient integration to facilitate smooth transfer of ventures between venture units. Based on the case findings, we develop a generic framework for a new way of managing the venturing process through multiple corporate venture units. ---------- Results and Implications: One of our main findings is that these firms tend to organize their venture units according to phases in the venture development process. That is, they tend to have venture units aimed at incubation of venture ideas as well as units aimed more at the commercialization of ventures into a new business unit for the firm or a start-up. The companies in our case studies tended to coordinate venture units through integrative management skills or a coordinative venture unit that spanned multiple phases. We believe this paper makes two significant contributions. First, we extend prior venturing literature by addressing how firms manage a portfolio of venture units, each achieving different strategic objectives. Second, our framework provides recommendations on how firms should manage such an approach towards venturing. This helps to increase the likelihood of success of their venturing programs.

Optimal coordination of overcurrent relays in distribution systems with distributed generators based on differential evolution algorithm

Distributed generators (DGs) are defined as generators that are connected to a distribution network. The direction of the power flow and short-circuit current in a network could be changed compared with one without DGs. The conventional protective relay scheme does not meet the requirement in this emerging situation. As the number and capacity of DGs in the distribution network increase, the problem of coordinating protective relays becomes more challenging. Given this background, the protective relay coordination problem in distribution systems is investigated, with directional overcurrent relays taken as an example, and formulated as a mixed integer nonlinear programming problem. A mathematical model describing this problem is first developed, and the well-developed differential evolution algorithm is then used to solve it. Finally, a sample system is used to demonstrate the feasiblity and efficiency of the developed method.

A New DER coordination in LV network based on the concept of distributed control

Given the paradigm of smart grid as the promising backbone for future network, this paper uses this paradigm to propose a new coordination approach for LV network based on distributed control algorithm. This approach divides the LV network into hierarchical communities where each community is controlled by a control agent. Different level of communication has been proposed for this structure to control the network in different operation modes.

Uncertainty analysis of pollutant build-up modelling based on a Bayesian Weighted Least Squares approach

Reliable pollutant build-up prediction plays a critical role in the accuracy of urban stormwater quality modelling outcomes. However, water quality data collection is resource demanding compared to streamflow data monitoring, where a greater quantity of data is generally available. Consequently, available water quality data sets span only relatively short time scales unlike water quantity data. Therefore, the ability to take due consideration of the variability associated with pollutant processes and natural phenomena is constrained. This in turn gives rise to uncertainty in the modelling outcomes as research has shown that pollutant loadings on catchment surfaces and rainfall within an area can vary considerably over space and time scales. Therefore, the assessment of model uncertainty is an essential element of informed decision making in urban stormwater management. This paper presents the application of a range of regression approaches such as ordinary least squares regression, weighted least squares Regression and Bayesian Weighted Least Squares Regression for the estimation of uncertainty associated with pollutant build-up prediction using limited data sets. The study outcomes confirmed that the use of ordinary least squares regression with fixed model inputs and limited observational data may not provide realistic estimates. The stochastic nature of the dependent and independent variables need to be taken into consideration in pollutant build-up prediction. It was found that the use of the Bayesian approach along with the Monte Carlo simulation technique provides a powerful tool, which attempts to make the best use of the available knowledge in the prediction and thereby presents a practical solution to counteract the limitations which are otherwise imposed on water quality modelling.

Perceptions of land-use uncertainty in Queensland's resource-based regions

Some of Queensland's regions are experiencing rapid changes related to the recent and growing capacity to more effectively exploit significant energy sources. These changes have triggered land-use conflicts between the mining sector and other economic sectors, mainly agriculture. These conflicts fuel existing uncertainty surrounding the current and future economic, social and environmental impacts of extractive industries. This paper explores the concept of uncertainty as it applies to planning for resource-based regions through a scoping analysis of regional stakeholders' perceptions of land-use uncertainty. It then investigates solutions to alleviate such an issue.

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).

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.

Score-level multibiometric fusion based on Dempster-Shafer theory incorporating uncertainty factors

While existing multi-biometic Dempster-Shafer the- ory fusion approaches have demonstrated promising perfor- mance, they do not model the uncertainty appropriately, sug- gesting that further improvement can be achieved. This research seeks to develop a unified framework for multimodal biometric fusion to take advantage of the uncertainty concept of Dempster- Shafer theory, improving the performance of multi-biometric authentication systems. Modeling uncertainty as a function of uncertainty factors affecting the recognition performance of the biometric systems helps to address the uncertainty of the data and the confidence of the fusion outcome. A weighted combination of quality measures and classifiers performance (Equal Error Rate) are proposed to encode the uncertainty concept to improve the fusion. We also found that quality measures contribute unequally to the recognition performance, thus selecting only significant factors and fusing them with a Dempster-Shafer approach to generate an overall quality score play an important role in the success of uncertainty modeling. The proposed approach achieved a competitive performance (approximate 1% EER) in comparison with other Dempster-Shafer based approaches and other conventional fusion approaches.