OPTIMAL RAILWAY INFRASTRUCTURE MAINTENANCE AND REPAIR POLICIES TO MANAGE RISK UNDER UNCERTAINTY WITH ADAPTIVE CONTROL

The aim of this paper is to apply two adaptive control formulations under uncertainty, say open-loop and closed-loop, to the process of developing maintenance and repair policies for railway infrastructures. To establish the optimal maintenance and repair policies for railway lines, we use a previous design of risk model based on two factors: the criticality and the deterioration ratios of the facilities. Thus, our theory benefits from the Reliability Centered Management methodology application, but it also explicitly models uncertainty in characterizing a facility deterioration rate to decide the optimal policy to maintain the railway infrastructures. This may be the major contribution of this work. To verify the models presented, a computation study has been developed and tested for a real scenario: the railway line Villalba-Cercedilla in Madrid (Spain). Our results demonstrate again that applying any adaptive formulation, the cost of the railway lines maintenance shown is decreased. Moreover applying a Closed Loop Formulation the cost associated to the risk takes smaller values (40% less cost for the same risk than the deterministic approach), but with an Open Loop formulation the generated risk in the railway line is also smaller.

Characterisation of hourly temperature of a thin-film module from weather conditions by artificial intelligence techniques

The aim of this paper is the use and validation of artificial intelligence techniques to predict the temperature of a thin-film module based on tandem CdS/CdTe technology. The cell temperature of a module is usually tens of degrees above the air temperature, so that the greater the intensity of the received radiation, the greater the difference between these two temperature values. In practice, directly measuring the cell temperature is very complicated, since cells are encapsulated between insulation materials that do not allow direct access. In the literature there are several equations to obtain the cell temperature from the external conditions. However, these models use some coefficients which do not appear in the specification sheets and must be estimated experimentally. In this work, a support vector machine and a multilayer perceptron are proposed as alternative models to predict the cell temperature of a module. These methods allow us to achieve an automatic way to learn only from the underlying information extracted from the measured data, without proposing any previous equation. These proposed methods were validated through an experimental campaign of measurements. From the obtained results, it can be concluded that the proposed models can predict the cell temperature of a module with an error less than 1.5 °C.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Mission performance analysis of a conceptual coaxial rotorcraft for air taxi applications

The rotorcraft industry has recently shown a new interest in compound rotorcraft as a feasible alternative to tackle the rapid growth of civil aviation activities and associated environmental impact. Indeed, aircraft contribution to the global emissions of CO2CO2, NOxNOx, and noise are driving the development of innovative technologies and vehicles. At present, compound rotorcraft architectures are regarded by the industry as promising platforms that can potentially increase productivity at a reduced environmental cost. In order to quantify the benefits of compound rotorcraft, this paper details the performance analysis of a coaxial counter-rotating rotor configuration with a pusher propeller. A comprehensive approach targeting the assessment of the aforementioned rotorcraft design for civil applications is presented herein. The methodology developed encompasses a rotorcraft flight dynamics simulation module and an engine performance module, coupled with a gaseous emissions prediction tool for environmental impact studies. They have been integrated together to constitute a standalone performance simulation framework and verified with the performance calculations of Harrington's “rotor 1” and the Sikorsky X2TD. The method is then applied to evaluate the performance of a conceptual coaxial rotorcraft, during a notional inter-city air taxi mission, in terms of cruise altitude, speed, and range, overall mission time and environmental impact. The several trade-offs between these parameters highlight the need for an integrated optimisation process. Besides, the concept demonstrates the benefits of the compound rotorcraft architecture with a best range speed reaching 90 m/s leading to reduced response times and increase of round trips in a given time. As a consequence, operators will need fewer vehicles and heliports to cover the same areas. This outcome is highly attractive in the current growing market

New software tool to characterize photovoltaic modules from commercial equipment

A software platform has been developed in order to unify the different measurements obtained from different manufacturers in the photovoltaic system laboratory of the University of Malaga, Spain. These measurements include the current-voltage curve of PV modules and several meteorological parameters such as global and direct irradiance, temperature and spectral distribution of solar irradiance. The measurements are performed in an automated way by a stand-alone application that is able to communicate with a pair of multimeters and a bipolar power supply that are controlled in order to obtain the current–voltage pairs. In addition, several magnitudes, that can be configured by the user, such as irradiance, module temperature or wind speed, are incorporated to register the conditions of each measurement. Moreover, it is possible to attach to each curve the spectral distribution of the solar radiation at each moment. Independently of the source of the information, all these measurements are stored in a uniform relational database. These data can be accessed through a public web site that can generate several graphics from the data.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Junta de Andalucía. Proyecto de Excelencia P11-RNM-711

Novel turboshaft engines design and optimisation for rotorcraft applications.

Since the inception of the first gas turbine engines, scientists and aircraft propulsion designers have attempted to improve engine efficiency, size, weight, fuel consumption and power output. In the current scenario, where the conventional gas turbine technology has almost reached its maturity, companies and researchers are starting to seek new engine architectures and novel cycles to comply with the next future aviation challenges. One of the proposed solutions is the implementation of an auxiliary combustion process into the turbines, known as reheated cycle. In the reheated cycle, the gas from an expansion process (through a turbine stage or a whole turbine) is burned before the next expansion. This concept has the potential to increase the specific work, at the same time the thermal efficiency is improved. Numerous investigations have been performed on the application of the reheated cycle to turbojet and civil turbofan engines. However, no studies are published about the potential application of this technology in rotorcraft powerplants. Therefore, the aim of this research project is to accomplish an exhaustive analysis and optimisation of a reheated turboshaft engine in terms of thermal efficiency and engine weight. The optimal engines identified at this stage are to be evaluated at mission level in order to assess the final impact on mission fuel abatement. For this matter, models for the performance simulation of a representative helicopter and for the thermodynamic analysis of the engine architectures have been developed and validated against experimental data. An additional module estimating the cooling flows fluctuation with the engine cycle parameters has been coupled with the engine performance model. Finally, a procedure for the sizing of reheated turboshaft engines have been developed and validated by the author. The different models have been built after a reference Twin-Engine Medium (T EM) helicopter, the Sikorsky UH-60A Black Hawk helicopter powered by two General Electric T700-GE-700 turboshaft engines. The aforementioned models have been integrated in a common simulation framework for the completion of a preliminary parametric analysis showing the sensitivity of the reheated configurations to changes in the engine design variables. In particular, three distinct reheated architectures have been investigated together with a conventional engine for comparison purposes. The individual response of each engine architecture has been discussed. The deployed framework has been then coupled with a Genetic Algorithm optimiser to efficiently seek for the best candidate engines in terms of total weight and Specific Fuel Consumption at cruise (SFCcr). At this step, Response Surface Models (RSMs) have been developed for the fast estimation of engine weight and coupled with the optimiser routine. It has been proven that the reheated engines have the potential to reduce engine mass and increase thermal efficiency in comparison with the baseline engine, although the optimal conventional engine still shows superior performance under the conditions simulated. This conclusion has been also confirmed by the results obtained at mission level. A final mission level multi-objective optimisation has been conducted for the conventional engine targeting the minimisation of the overall mission fuel burn and NOᵪ emissions. A representative model for the prediction of the combustor emissions production has been developed and validated for this purpose. The trade-off existing between fuel efficiency and pollutant depletion has been highlighted along with the potential benefits in block fuel and NOᵪ inventory.PhD in Aerospac

Conclusion

International audienceAs we have seen in the former chapters, facilitating the adoption and usage of sustainable ultrascale computing systems, will need providing innovative solutions to advance the knowledge of designing sustainable ultrascale software and systems, which will be the basic facilities for new discoveries in science and technology and will have a direct impact on economic growth, society, and environmental aspects.

Impact of adverse environmental conditions on rotorcraft operational performance and pollutant emissions

It is anticipated that the contribution of rotorcraft activities to the environmental impact of civil aviation will increase in the future. Due to their versatility and robustness, helicopters are often operated in harsh environments with extreme ambient conditions. These severe conditions not only affect the performance of the engine but also affect the aerodynamics of the rotorcraft. This impact is reflected in the fuel burn and pollutants emitted by the rotorcraft during a mission. The aim of this paper is to introduce an exhaustive methodology to quantify the influence adverse environment conditions have in the mission fuel consumption and the associated emissions of nitrogen oxides (NOx). An emergency medical service (EMS) and a search and rescue (SAR) mission are used as case studies to simulate the effects of extreme temperatures, high altitude, and compressor degradation on a representative twin-engine medium (TEM) weight helicopter, the Sikorsky UH-60A Black Hawk. A simulation tool for helicopter mission performance analysis developed and validated at Cranfield University was employed. This software comprises different modules that enable the analysis of helicopter flight dynamics, powerplant performance, and exhaust emissions over a user-defined flight path profile. For the validation of the models implemented, extensive comparisons with experimental data are presented throughout for rotorcraft and engine performance as well as NOx emissions. Reductions as high as 12% and 40% in mission fuel and NOx emissions, respectively, were observed for the “high and cold” scenario simulated at the SAR role relative to the same mission trajectory under standard conditions

Ultrascale Computing Systems

International audienceThe needs of future digital data and computer systems are expected to be two to three orders of magnitude larger than for today's systems, to take account of unprecedented amounts of heterogeneous hardware, lines of source code, numbers of users, and volumes of data. Ultrascale computing systems (UCS) are a solution. Envisioned as large-scale complex systems joining parallel and distributed computing systems, which can be located at multiple sites and cooperate to provide the required resources and performance to the users, these technologies will extend individual systems to provide the resources that are very much needed. Based on the research work in the COST Action IC 1305 Network for Sustainable Ultrascale Computing (NESUS) this book presents important results and methods towards achieving sustainable UCS. The authors present a wide range of emerging programming models that facilitate the task of scaling and extracting performance on continuously evolving platforms, while providing resilience and fault-tolerant mechanisms to tackle the increasing probability of failures throughout the entire software stack. These methods are needed to achieve scale handling, better programmability and adaptation to rapidly changing underlying computing architecture, data centric programming models, resilience, and energy-efficiency

Monitoring the Bioactive Compounds Status in Olea europaea According to Collecting Period and Drying Conditions

Polyphenols and triterpenoids in olive have relevant importance both in the physiology of the plant and the nutritional and biological value of its products. Olive leaf extracts are of special interest for their numerous health-promoting properties. The present research is investigating the occurrence of phytochemicals in supercritical fluid extracts from leaves with regard to collection time and drying temperature. The phytochemical profiles of the olive leaf extracts were determined by reversed-phase high-performance liquid chromatography (HPLC) coupled to electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS) detection. The main extracted phytochemicals were phenols and terpenoids. A significant variation in the amounts of the different components was observed as a function of the different drying temperature and collecting time (p < 0.05). Among samples, the maximal contents of polyphenols and secoiridoid derivatives were found in the extracts from olive leaves collected in November and dried at 120 ºC, whereas triterpenoids showed the highest content in fresh leaves collected in August.This work was supported by the Tunisian Ministry of Higher Education under the Tunisian-Korean project “Development of Anti-arthritic remedy with Olive by-products”

Epidemiology, mortality, and health service use of local-level multimorbidity patterns in South Spain

Multimorbidity –understood as the occurrence of chronic diseases together–represents a major challenge for healthcare systems due to its impact on disability, quality of life, increased use of services and mortality. However, despite the global need to address this health problem, evidence is still needed to advance our understanding of its clinical and social implications. Our study aims to characterisemultimorbidity patterns in a dataset of 1,375,068 patients residing in southern Spain. Combining LCA techniques and geographic information, together with service use, mortality, and socioeconomic data, 25 chronicity profiles were identified and subsequently characterised by sex and age. The present study has led us to several findings that take a step forward in this field of knowledge. Specifically, we contribute to the identification of an extensive range of at-risk groups. Moreover, our study reveals that the complexity of multimorbidity patterns escalates at a faster rate and is associated with a poorer prognosis in local areas characterised by lower socioeconomic status. These results emphasize the persistence of social inequalities in multimorbidity, highlighting the need for targeted interventions to mitigate the impact on patients’ quality of life, healthcare utilisation, and mortality rates.University Research Institute for Sustainable Social DevelopmentBiomedical Research and Innovation Institute of Cadiz (INiBICA)University of CadizRamon y Cajal programme run by the Spanish Ministry of Science and InnovationPublic funds by the ITI call (Integrated Territorial Investment), developed by the Health Department of the Andalusian Government (ITI-0028-2019)DEMMOCAD project has been 80% co-financed by funds from the European Regional Development Fund (ERDF) operational programme of Andalusia 2014–2020INDESS (Instituto Universitario de Investigación para el Desarrollo Social Sostenible)University of Cadiz, Jerez de la Frontera, Spai