Key principles for developing industrially relevant strategic technology management toolkits

When considering the potential uptake and utilization of technology management tools by industry, it must be recognized that companies face the difficult challenges of selecting, adopting and integrating individual tools into a toolkit that must be implemented within their current organizational processes and systems. This situation is compounded by the lack of sound advice on integrating well-founded individual tools into a robust toolkit that has the necessary degree of flexibility such that they can be tailored for application to specific problems faced by individual organizations. As an initial stepping stone to offering a toolkit with empirically proven utility, this paper provides a conceptual foundation to the development of toolkits by outlining an underlying philosophical position based on observations from multiple research and commercial collaborations with industry. This stance is underpinned by a set of operationalized principles that can offer guidance to organizations when deciding upon the appropriate form, functions and features that should be embodied by any potential tool/toolkit. For example, a key objective of any tool is to aid decision-making and a core set of powerful, flexible, scaleable and modular tools should be sufficient to allow users to generate, explore, shape and implement possible solutions across a wide array of strategic issues. From our philosophical stance, the preferred mode of engagement is facilitated workshops with a participatory process that enables multiple perspectives and structures the conversation through visual representations in order to manage the cognitive load in the collaborative environment. The generic form of the tools should be configurable for the given context and utilized in a lightweight manner based on the premise of 'start small and iterate fast'. © 2012 Elsevier Inc.

Resource Management for Responsive Web Computing

The exploding demand for services like the World Wide Web reflects the potential that is presented by globally distributed information systems. The number of WWW servers world-wide has doubled every 3 to 5 months since 1993, outstripping even the growth of the Internet. At each of these self-managed sites, the Common Gateway Interface (CGI) and Hypertext Transfer Protocol (HTTP) already constitute a rudimentary basis for contributing local resources to remote collaborations. However, the Web has serious deficiencies that make it unsuited for use as a true medium for metacomputing --- the process of bringing hardware, software, and expertise from many geographically dispersed sources to bear on large scale problems. These deficiencies are, paradoxically, the direct result of the very simple design principles that enabled its exponential growth. There are many symptoms of the problems exhibited by the Web: disk and network resources are consumed extravagantly; information search and discovery are difficult; protocols are aimed at data movement rather than task migration, and ignore the potential for distributing computation. However, all of these can be seen as aspects of a single problem: as a distributed system for metacomputing, the Web offers unpredictable performance and unreliable results. The goal of our project is to use the Web as a medium (within either the global Internet or an enterprise intranet) for metacomputing in a reliable way with performance guarantees. We attack this problem one four levels: (1) Resource Management Services: Globally distributed computing allows novel approaches to the old problems of performance guarantees and reliability. Our first set of ideas involve setting up a family of real-time resource management models organized by the Web Computing Framework with a standard Resource Management Interface (RMI), a Resource Registry, a Task Registry, and resource management protocols to allow resource needs and availability information be collected and disseminated so that a family of algorithms with varying computational precision and accuracy of representations can be chosen to meet realtime and reliability constraints. (2) Middleware Services: Complementary to techniques for allocating and scheduling available resources to serve application needs under realtime and reliability constraints, the second set of ideas aim at reduce communication latency, traffic congestion, server work load, etc. We develop customizable middleware services to exploit application characteristics in traffic analysis to drive new server/browser design strategies (e.g., exploit self-similarity of Web traffic), derive document access patterns via multiserver cooperation, and use them in speculative prefetching, document caching, and aggressive replication to reduce server load and bandwidth requirements. (3) Communication Infrastructure: Finally, to achieve any guarantee of quality of service or performance, one must get at the network layer that can provide the basic guarantees of bandwidth, latency, and reliability. Therefore, the third area is a set of new techniques in network service and protocol designs. (4) Object-Oriented Web Computing Framework A useful resource management system must deal with job priority, fault-tolerance, quality of service, complex resources such as ATM channels, probabilistic models, etc., and models must be tailored to represent the best tradeoff for a particular setting. This requires a family of models, organized within an object-oriented framework, because no one-size-fits-all approach is appropriate. This presents a software engineering challenge requiring integration of solutions at all levels: algorithms, models, protocols, and profiling and monitoring tools. The framework captures the abstract class interfaces of the collection of cooperating components, but allows the concretization of each component to be driven by the requirements of a specific approach and environment.

An Adaptive Policy Management Approach to BGP Convergence

The Border Gateway Protocol (BGP) is the current inter-domain routing protocol used to exchange reachability information between Autonomous Systems (ASes) in the Internet. BGP supports policy-based routing which allows each AS to independently adopt a set of local policies that specify which routes it accepts and advertises from/to other networks, as well as which route it prefers when more than one route becomes available. However, independently chosen local policies may cause global conflicts, which result in protocol divergence. In this paper, we propose a new algorithm, called Adaptive Policy Management Scheme (APMS), to resolve policy conflicts in a distributed manner. Akin to distributed feedback control systems, each AS independently classifies the state of the network as either conflict-free or potentially-conflicting by observing its local history only (namely, route flaps). Based on the degree of measured conflicts (policy conflict-avoidance vs. -control mode), each AS dynamically adjusts its own path preferences—increasing its preference for observably stable paths over flapping paths. APMS also includes a mechanism to distinguish route flaps due to topology changes, so as not to confuse them with those due to policy conflicts. A correctness and convergence analysis of APMS based on the substability property of chosen paths is presented. Implementation in the SSF network simulator is performed, and simulation results for different performance metrics are presented. The metrics capture the dynamic performance (in terms of instantaneous throughput, delay, routing load, etc.) of APMS and other competing solutions, thus exposing the often neglected aspects of performance.

Load Testing of Floor Slabs in a Full-Scale Reinforced Concrete Building

A series of short and long term service load tests were undertaken on the sixth floor of the full-scale, seven storey, reinforced concrete building at the Large Building Test Facility of the Building Research Establishment at Cardington. By using internally strain gauged reinforcing bars cast into an internal and external floor bay during the construction process it was possible to gain a detailed record of slab strains resulting from the application of several arrangements of test loads. Short term tests were conducted in December 1998 and long term monitoring then ensued until April 2001. This paper describes the test programmes and presents results to indicate slab behaviour for the various loading regimes.

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

HTS Machines as Enabling Technology for All-Electric Airborne Vehicles

Environmental protection has now become paramount as evidence mounts to support the thesis of human activity-driven global warming. A global reduction of the emissions of pollutants into the atmosphere is therefore needed and new technologies have to be considered. A large part of the emissions come from transportation vehicles, including cars, trucks and airplanes, due to the nature of their combustion-based propulsion systems. Our team has been working for several years on the development of high power density superconducting motors for aircraft propulsion and fuel cell based power systems for aircraft. This paper investigates the feasibility of all-electric aircraft based on currently available technology. Electric propulsion would require the development of high power density electric propulsion motors, generators, power management and distribution systems. The requirements in terms of weight and volume of these components cannot be achieved with conventional technologies; however, the use of superconductors associated with hydrogen-based power plants makes possible the design of a reasonably light power system and would therefore enable the development of all-electric aero-vehicles. A system sizing has been performed both for actuators and for primary propulsion. Many advantages would come from electrical propulsion such as better controllability of the propulsion, higher efficiency, higher availability and less maintenance needs. Superconducting machines may very well be the enabling technology for all-electric aircraft development.

Electric vehicles and displaced gaseous emission

Electric vehicles (EV) do not emit tailpipe exhaust fumes in the same manner as internal combustion engine vehicles. Optimal benefits can only be achieved, if EVS are deployed effectively, so that the tailpipe emissions are not substituted by additional emissions in the electricity sector. This paper examines the potential contributions that Plug in Hybrid Electric Vehicles can make in reducing carbon dioxide. The paper presents the results of the generation expansion model for Northern Ireland and the Republic of Ireland built using the dynamic programming based long term generation expansion planning tool called the Wien Automatic System Planning IV tool. The model optimizes power dispatch using hourly electricity demand curves for each year up to 2020, while incorporating generator characteristics and certain operational requirements such as energy not served and loss of load probability while satisfying constraints on environmental emissions, fuel availability and generator operational and maintenance costs. In order to simulate the effect of PHEV, two distinct charging scenarios are applied based on a peak tariff and an off peak tariff. The importance and influence of the charging regime on the amount of energy used and gaseous emissions displaced is determined and discussed.

Functional management of ankle sprains: what volume and intensity of walking is undertaken in the first week postinjury:what volume and intensity of walking is undertaken in the first week postinjury

BACKGROUND: Acute ankle sprains are usually managed functionally, with advice to undertake progressive weight-bearing and walking. Mechanical loading is an important modular of tissue repair; therefore, the clinical effectiveness of walking after ankle sprain may be dose dependent. The intensity, magnitude and duration of load associated with current functional treatments for ankle sprain are unclear.

AIM: To describe physical activity (PA) in the first week after ankle sprain and to compare results with a healthy control group.

METHODS: Participants (16-65 years) with an acute ankle sprain were randomised into two groups (standard or exercise). Both groups were advised to apply ice and compression, and walk within the limits of pain. The exercise group undertook additional therapeutic exercises. PA was measured using an activPAL accelerometer, worn for 7 days after injury. Comparisons were made with a non-injured control group.

RESULTS: The standard group were significantly less active (1.2 ± 0.4 h activity/day; 5621 ± 2294 steps/day) than the exercise (1.7 ± 0 .7 h/day, p=0.04; 7886 ± 3075 steps/day, p=0.03) and non-injured control groups (1.7 ± 0.4 h/day, p=0.02; 8844 ± 2185 steps/day, p=0.002). Also, compared with the non-injured control group, the standard and exercise groups spent less time in moderate (38.3 ± 12.7 min/day vs 14.5 ± 11.4 min/day, p=0.001 and 22.5 ± 15.9 min/day, p=0.003) and high-intensity activity (4.1 ± 6.9 min/day vs 0.1 ± 0.1 min/day, p=0.001 and 0.62 ± 1.0 min/day p=0.005).

CONCLUSION: PA patterns are reduced in the first week after ankle sprain, which is partly ameliorated with addition of therapeutic exercises. This study represents the first step towards developing evidence-based walking prescription after acute ankle sprain.

Algorithmic method for scraper load-time optimization

Scrapers have established an important position in the earthmoving field as they are independently capable of accomplishing an earthmoving operation. Given that loading a scraper to its capacity does not entail its maximum production, optimizing the scraper’s loading time is an essential prerequisite for successful operations management. The relevant literature addresses the loading time optimization through a graphical method that is founded on the invalid assumption that the hauling time is independent of the load time. To correct this, a new algorithmic optimization method that incorporates the golden section search and the bisection algorithm is proposed. Comparison of the results derived from the proposed and the existing method demonstrates that the latter entails the systematic needless prolongation of the loading stage thus resulting in reduced hourly production and increased cost. Therefore, the proposed method achieves an improved modeling of scraper earthmoving operations and contributes toward a more efficient cost management.

Day-Ahead Optimal Charging/Discharging Scheduling for Electric Vehicles in Micro-Grids

A micro-grid is an autonomous system which can be operated and connected to an external system or isolated with the help of energy storage systems (ESSs). While the daily output of distributed generators (DGs) strongly depends on the temporal distribution of natural resources such as wind and solar, unregulated electric vehicle (EV) charging demand will deteriorate the imbalance between the daily load and generation curves. In this paper, a statistical model is presented to describe daily EV charging/discharging behaviour. An optimisation problem is proposed to obtain economic operation for the micro-grid based on this model. In day-ahead scheduling, with estimated information of power generation and load demand, optimal charging/discharging of EVs during 24 hours is obtained. A series of numerical optimization solutions in different scenarios is achieved by serial quadratic programming. The results show that optimal charging/discharging of EVs, a daily load curve can better track the generation curve and the network loss and required ESS capacity are both decreased. The paper also demonstrates cost benefits for EVs and operators.

Development of a Bridge Weigh-in-Motion Sensor: Performance comparison using fibre optic and electric resistance strain sensor systems

This paper addresses the problems of effective in situ measurement of the real-time strain for bridge weigh in motion in reinforced concrete bridge structures through the use of optical fiber sensor systems. By undertaking a series of tests, coupled with dynamic loading, the performance of fiber Bragg grating-based sensor systems with various amplification techniques were investigated. In recent years, structural health monitoring (SHM) systems have been developed to monitor bridge deterioration, to assess load levels and hence extend bridge life and safety. Conventional SHM systems, based on measuring strain, can be used to improve knowledge of the bridge's capacity to resist loads but generally give no information on the causes of any increase in stresses. Therefore, it is necessary to find accurate sensors capable of capturing peak strains under dynamic load and suitable methods for attaching these strain sensors to existing and new bridge structures. Additionally, it is important to ensure accurate strain transfer between concrete and steel, adhesives layer, and strain sensor. The results show the benefits in the use of optical fiber networks under these circumstances and their ability to deliver data when conventional sensors cannot capture accurate strains and/or peak strains.

In situ diagnostics and prognostics of solder fatigue in IGBT modules for electric vehicle drives

This paper proposes an in situ diagnostic and prognostic (D&P) technology to monitor the health condition of insulated gate bipolar transistors (IGBTs) used in EVs with a focus on the IGBTs' solder layer fatigue. IGBTs' thermal impedance and the junction temperature can be used as health indicators for through-life condition monitoring (CM) where the terminal characteristics are measured and the devices' internal temperature-sensitive parameters are employed as temperature sensors to estimate the junction temperature. An auxiliary power supply unit, which can be converted from the battery's 12-V dc supply, provides power to the in situ test circuits and CM data can be stored in the on-board data-logger for further offline analysis. The proposed method is experimentally validated on the developed test circuitry and also compared with finite-element thermoelectrical simulation. The test results from thermal cycling are also compared with acoustic microscope and thermal images. The developed circuitry is proved to be effective to detect solder fatigue while each IGBT in the converter can be examined sequentially during red-light stopping or services. The D&P circuitry can utilize existing on-board hardware and be embedded in the IGBT's gate drive unit.

Non-convex dynamic economic/environmental dispatch with plug-in electric vehicle loads

Electric vehicles are a key prospect for future transportation. A large penetration of electric vehicles has the potential to reduce the global fossil fuel consumption and hence the greenhouse gas emissions and air pollution. However, the additional stochastic loads imposed by plug-in electric vehicles will possibly introduce significant changes to existing load profiles. In his paper, electric vehicles loads are integrated into an 5-unit system using a non-convex dynamic dispatch model. The actual infrastructure characteristics including valve-point effects, load balance constrains and transmission loss have been included in the model. Multiple load profiles are comparatively studied and compared in terms of economic and environmental impacts in order o identify patterns to charge properly. The study as expected shows ha off-peak charging is the best scenario with respect to using less fuels and producing less emissions.