Improving the operational skills of the health personnel working in the emergency departments. A useful tool to give concrete answers to EU policies on patients' safety and to create new working opportunities” (VS/2013/0430) finanziato dalla Commissione Europea nell'ambito del programma PROGRESS.

A useful tool to give concrete answers to EU policies on patients' safety and to create new working opportunities (VS / 2013/0430

Use of satellite observations for operational oceanography: recent achievements and future prospects

The paper gives an overview of the development of satellite oceanography over the past five years focusing on the most relevant issues for operational oceanography. Satellites provide key essential variables to constrain ocean models and/or serve downstream applications. New and improved satellite data sets have been developed and have directly improved the quality of operational products. The status of the satellite constellation for the last five years was, however, not optimal. Review of future missions shows clear progress and new research and development missions with a potentially large impact for operational oceanography should be demonstrated. Improvement of data assimilation techniques and developing synergetic use of high resolution satellite observations are important future priorities.

'Artificial Immune Systems: A new Decision Making Paradigm for Operational Research'

Over the last few years, more and more heuristic decision making techniques have been inspired by nature, e.g. evolutionary algorithms, ant colony optimisation and simulated annealing. More recently, a novel computational intelligence technique inspired by immunology has emerged, called Artificial Immune Systems (AIS). This immune system inspired technique has already been useful in solving some computational problems. In this keynote, we will very briefly describe the immune system metaphors that are relevant to AIS. We will then give some illustrative real-world problems suitable for AIS use and show a step-by-step algorithm walkthrough. A comparison of AIS to other well-known algorithms and areas for future work will round this keynote off. It should be noted that as AIS is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from the examples given here

Geothermal district heating networks: modelling novel operational strategies incorporating heat storage

The value of integrating a heat storage into a geothermal district heating system has been investigated. The behaviour of the system under a novel operational strategy has been simulated focusing on the energetic, economic and environmental effects of the new strategy of incorporation of the heat storage within the system. A typical geothermal district heating system consists of several production wells, a system of pipelines for the transportation of the hot water to end-users, one or more re-injection wells and peak-up devices (usually fossil-fuel boilers). Traditionally in these systems, the production wells change their production rate throughout the day according to heat demand, and if their maximum capacity is exceeded the peak-up devices are used to meet the balance of the heat demand. In this study, it is proposed to maintain a constant geothermal production and add heat storage into the network. Subsequently, hot water will be stored when heat demand is lower than the production and the stored hot water will be released into the system to cover the peak demands (or part of these). It is not intended to totally phase-out the peak-up devices, but to decrease their use, as these will often be installed anyway for back-up purposes. Both the integration of a heat storage in such a system as well as the novel operational strategy are the main novelties of this thesis. A robust algorithm for the sizing of these systems has been developed. The main inputs are the geothermal production data, the heat demand data throughout one year or more and the topology of the installation. The outputs are the sizing of the whole system, including the necessary number of production wells, the size of the heat storage and the dimensions of the pipelines amongst others. The results provide several useful insights into the initial design considerations for these systems, emphasizing particularly the importance of heat losses. Simulations are carried out for three different cases of sizing of the installation (small, medium and large) to examine the influence of system scale. In the second phase of work, two algorithms are developed which study in detail the operation of the installation throughout a random day and a whole year, respectively. The first algorithm can be a potentially powerful tool for the operators of the installation, who can know a priori how to operate the installation on a random day given the heat demand. The second algorithm is used to obtain the amount of electricity used by the pumps as well as the amount of fuel used by the peak-up boilers over a whole year. These comprise the main operational costs of the installation and are among the main inputs of the third part of the study. In the third part of the study, an integrated energetic, economic and environmental analysis of the studied installation is carried out together with a comparison with the traditional case. The results show that by implementing heat storage under the novel operational strategy, heat is generated more cheaply as all the financial indices improve, more geothermal energy is utilised and less fuel is used in the peak-up boilers, with subsequent environmental benefits, when compared to the traditional case. Furthermore, it is shown that the most attractive case of sizing is the large one, although the addition of the heat storage most greatly impacts the medium case of sizing. In other words, the geothermal component of the installation should be sized as large as possible. This analysis indicates that the proposed solution is beneficial from energetic, economic, and environmental perspectives. Therefore, it can be stated that the aim of this study is achieved in its full potential. Furthermore, the new models for the sizing, operation and economic/energetic/environmental analyses of these kind of systems can be used with few adaptations for real cases, making the practical applicability of this study evident. Having this study as a starting point, further work could include the integration of these systems with end-user demands, further analysis of component parts of the installation (such as the heat exchangers) and the integration of a heat pump to maximise utilisation of geothermal energy.

Wind turbine indirect ice detection and operational analysis

Wind energy is one of the most promising and fast growing sector of energy production. Wind is ecologically friendly and relatively cheap energy resource available for development in practically all corners of the world (where only the wind blows). Today wind power gained broad development in the Scandinavian countries. Three important challenges concerning sustainable development, i.e. energy security, climate change and energy access make a compelling case for large-scale utilization of wind energy. In Finland, according to the climate and energy strategy, accepted in 2008, the total consumption of electricity generated by means of wind farms by 2020, should reach 6 - 7% of total consumption in the country [1]. The main challenges associated with wind energy production are harsh operational conditions that often accompany the turbine operation in the climatic conditions of the north and poor accessibility for maintenance and service. One of the major problems that require a solution is the icing of turbine structures. Icing reduces the performance of wind turbines, which in the conditions of a long cold period, can significantly affect the reliability of power supply. In order to predict and control power performance, the process of ice accretion has to be carefully tracked. There are two ways to detect icing – directly or indirectly. The first way applies to the special ice detection instruments. The second one is using indirect characteristics of turbine performance. One of such indirect methods for ice detection and power loss estimation has been proposed and used in this paper. The results were compared to the results directly gained from the ice sensors. The data used was measured in Muukko wind farm, southeast Finland during a project 'Wind power in cold climate and complex terrain'. The project was carried out in 9/2013 - 8/2015 with the partners Lappeenranta university of technology, Alstom renovables España S.L., TuuliMuukko, and TuuliSaimaa.

How to optimize operational shipping processes of non-production materials? The Volkswagen Autoeuropa case study

Field lab: Entrepreneurial and innovative ventures

Forming the link between strategic performance and operational success: The development of a balanced scorecard at Lisbon Consulting Group

Directed internship

MEDAR/MEDATLAS 2002: A Mediterranean and Black Sea database for operational oceanography Elsevier Oceanography Series

A comprehensive database of temperature, salinity and bio-chemical parameters in the Mediterranean and Black Sea has been constructed through comprehensive co-operation between the bordering countries. Statistical climatologies have been computed with all assembled and quality controlled data. The database, designed to initiate and validate prediction models, also represents a system to quality-check new incoming data produced by ocean observing systems.

IQuOD 4th workshop in Tokyo: Copernicus Marine in situ TAC, a service for operational oceanography

Copernicus is a European system for monitoring the Earth. COPERNICUS-CMEMS products and services are meant to serve all marine applications: Marine resources, Maritime safety, Coastal and Marine Environment, Seasonal Forecast & Climate. The service is ambitious as the ocean is complex and many processes are involved, from physical oceanography, biology, geology, ocean-atmosphere fluxes, solar radiations, moon induced tides, anthropic activity. A multi-platform approach is essential, taking into account sea-level stations, coastal buoys, HF radars, river flows, drifting buoys, sea-mammal or fishes fitted with sensors, vessels, gliders, floats.

Developing European operational oceanography for Blue Growth, climate change adaptation and mitigation, and ecosystem-based management

Operational approaches have been more and more widely developed and used for providing marine data and information services for different socio-economic sectors of the Blue Growth and to advance knowledge about the marine environment. The objective of operational oceanographic research is to develop and improve the efficiency, timeliness, robustness and product quality of this approach. This white paper aims to address key scientific challenges and research priorities for the development of operational oceanography in Europe for the next 5-10 years. Knowledge gaps and deficiencies are identified in relation to common scientific challenges in four EuroGOOS knowledge areas: European Ocean Observations, Modelling and Forecasting Technology, Coastal Operational Oceanography and Operational Ecology. The areas "European Ocean Observations" and "Modelling and Forecasting Technology" focus on the further advancement of the basic instruments and capacities for European operational oceanography, while "Coastal Operational Oceanography" and "Operational Ecology" aim at developing new operational approaches for the corresponding knowledge areas.

Exploration of the dendritic cell algorithm with the duration calculus

As one of the newest members in Articial Immune Systems (AIS), the Dendritic Cell Algorithm (DCA) has been applied to a range of problems. These applications mainly belong to the eld of anomaly detection. However, real-time detection, a new challenge to anomaly detection, requires improvement on the real-time capability of the DCA. To assess such capability, formal methods in the research of real-time systems can be employed. The ndings of the assessment can provide guideline for the future development of the algorithm. Therefore, in this paper we use an interval logic based method, named the Duration Calcu- lus (DC), to specify a simplied single-cell model of the DCA. Based on the DC specications with further induction, we nd that each individual cell in the DCA can perform its function as a detector in real-time. Since the DCA can be seen as many such cells operating in parallel, it is potentially capable of performing real-time detection. However, the analysis process of the standard DCA constricts its real-time capability. As a result, we conclude that the analysis process of the standard DCA should be replaced by a real-time analysis component, which can perform periodic analysis for the purpose of real-time detection.

Enabling effective operational decision making on a Combined Heat and Power System using the 5C architecture

The use of Cyber Physical Systems (CPS) to optimise industrial energy systems is an approach which has the potential to positively impact on manufacturing sector energy efficiency. The need to obtain data to facilitate the implementation of a CPS in an industrial energy system is however a complex task which is often implemented in a non-standardised way. The use of the 5C CPS architecture has the potential to standardise this approach. This paper describes a case study where data from a Combined Heat and Power (CHP) system located in a large manufacturing company was fused with grid electricity and gas models as well as a maintenance cost model using the 5C architecture with a view to making effective decisions on its cost efficient operation. A control change implemented based on the cognitive analysis enabled via the 5C architecture implementation has resulted in energy cost savings of over €7400 over a four-month period, with energy cost savings of over €150,000 projected once the 5C architecture is extended into the production environment.