Efficient algorithms for dynamic probabilistic safety assessment. An application to convex damage domain.

The design of nuclear power plant has to follow a number of regulations aimed at limiting the risks inherent in this type of installation. The goal is to prevent and to limit the consequences of any possible incident that might threaten the public or the environment. To verify that the safety requirements are met a safety assessment process is followed. Safety analysis is as key component of a safety assessment, which incorporates both probabilistic and deterministic approaches. The deterministic approach attempts to ensure that the various situations, and in particular accidents, that are considered to be plausible, have been taken into account, and that the monitoring systems and engineered safety and safeguard systems will be capable of ensuring the safety goals. On the other hand, probabilistic safety analysis tries to demonstrate that the safety requirements are met for potential accidents both within and beyond the design basis, thus identifying vulnerabilities not necessarily accessible through deterministic safety analysis alone. Probabilistic safety assessment (PSA) methodology is widely used in the nuclear industry and is especially effective in comprehensive assessment of the measures needed to prevent accidents with small probability but severe consequences. Still, the trend towards a risk informed regulation (RIR) demanded a more extended use of risk assessment techniques with a significant need to further extend PSA’s scope and quality. Here is where the theory of stimulated dynamics (TSD) intervenes, as it is the mathematical foundation of the integrated safety assessment (ISA) methodology developed by the CSN(Consejo de Seguridad Nuclear) branch of Modelling and Simulation (MOSI). Such methodology attempts to extend classical PSA including accident dynamic analysis, an assessment of the damage associated to the transients and a computation of the damage frequency. The application of this ISA methodology requires a computational framework called SCAIS (Simulation Code System for Integrated Safety Assessment). SCAIS provides accident dynamic analysis support through simulation of nuclear accident sequences and operating procedures. Furthermore, it includes probabilistic quantification of fault trees and sequences; and integration and statistic treatment of risk metrics. SCAIS comprehensively implies an intensive use of code coupling techniques to join typical thermal hydraulic analysis, severe accident and probability calculation codes. The integration of accident simulation in the risk assessment process and thus requiring the use of complex nuclear plant models is what makes it so powerful, yet at the cost of an enormous increase in complexity. As the complexity of the process is primarily focused on such accident simulation codes, the question of whether it is possible to reduce the number of required simulation arises, which will be the focus of the present work. This document presents the work done on the investigation of more efficient techniques applied to the process of risk assessment inside the mentioned ISA methodology. Therefore such techniques will have the primary goal of decreasing the number of simulation needed for an adequate estimation of the damage probability. As the methodology and tools are relatively recent, there is not much work done inside this line of investigation, making it a quite difficult but necessary task, and because of time limitations the scope of the work had to be reduced. Therefore, some assumptions were made to work in simplified scenarios best suited for an initial approximation to the problem. The following section tries to explain in detail the process followed to design and test the developed techniques. Then, the next section introduces the general concepts and formulae of the TSD theory which are at the core of the risk assessment process. Afterwards a description of the simulation framework requirements and design is given. Followed by an introduction to the developed techniques, giving full detail of its mathematical background and its procedures. Later, the test case used is described and result from the application of the techniques is shown. Finally the conclusions are presented and future lines of work are exposed.

The HOSHIN KANRI TREE. Cross-Plant Lean Shopfloor Management

Shopfloor Management (SM) empowerment methodologies have traditionally focused on two aspects: goal achievement following rigid structures, such as SQDCME, or evolutional aspects of empowerment factors away from strategic goal achievement. Furthermore, SM Methodologies have been organized almost solely around the hierarchical structure of the organization, failing systematically to cope with the challenges that Industry 4.0 is facing. The latter include the growing complexity of value-stream networks, sustainable empowerment of the workforce (Learning Factory), an autonomous and intelligent process management (Smart Factory), the need to cope with the increasing complexity of value-stream networks (VSN) and the leadership paradigm shift to strategic alignment. This paper presents a novel Lean SM Method (LSM) called ?HOSHIN KANRI Tree? (HKT), which is based on standardization of the communication patterns among process owners (POs) by PDCA. The standardization of communication patterns by HKT technology should bring enormous benefits in value stream (VS) performance, speed of standardization and learning rates to the Industry 4.0 generation of organizations. These potential advantages of HKT are being tested at present in worldwide research.

Enhancing Guideline-based decision support with distributed computation through local mobile application

We introduce the need for a distributed guideline-based decision sup-port (DSS) process, describe its characteristics, and explain how we implement-ed this process within the European Union?s MobiGuide project. In particular, we have developed a mechanism of sequential, piecemeal projection, i.e., 'downloading' small portions of the guideline from the central DSS server, to the local DSS in the patient's mobile device, which then applies that portion, us-ing the mobile device's local resources. The mobile device sends a callback to the central DSS when it encounters a triggering pattern predefined in the pro-jected module, which leads to an appropriate predefined action by the central DSS, including sending a new projected module, or directly controlling the rest of the workflow. We suggest that such a distributed architecture that explicitly defines a dialog between a central DSS server and a local DSS module, better balances the computational load and exploits the relative advantages of the cen-tral server and of the local mobile device.

Modelado experimental de un sistema de e-Salud aplicado en cooperación al desarrollo

Los Objetivos de Desarrollo del Milenio comprometieron a los países con una nueva alianza mundial de alcanzar gradualmente una cobertura universal de los niveles mínimos de bienestar en los países en desarrollo (reducir la pobreza y el hambre y dar respuesta a problemas como la mala salud, las desigualdades de género, la falta de educación, el acceso a agua salubre y la degradación ambiental). Para dar continuidad a esta iniciativa, recientemente en septiembre de 2015, la ONU promulgó la declaración de los Objetivos de Desarrollo Sostenible. Los ODM sitúan la salud en el corazón del desarrollo y establecen un novedoso pacto mundial que vincula a los países desarrollados y los países en desarrollo por medio de obligaciones claras y recíprocas. En este sentido, diversos organismos de cooperación a través de sus programas de cooperación internacional, tratan de mejorar el acceso a la asistencia sanitaria, especialmente a la población vulnerable que vive en zonas rurales de países en desarrollo. Con el fin de ayudar a cumplir los ODM que apoyan los temas de salud en dicha población, estos organismos desarrollan proyectos que despliegan sistemas de e-salud. Las intervenciones se enfrentan a múltiples retos: condicionantes de los países en desarrollo, las necesidades y demandas de los sistemas sanitarios y la complejidad de implantar las TIC en entornos complejos y altamente dinámicos como son los países en desarrollo. Estos condicionantes ocasionan la mayoría de proyectos fallidos que terminan convirtiéndose en soluciones aisladas, que anteponen la tecnología a las necesidades de la población y no generan el impacto esperado en su desarrollo. En este contexto tuvo origen esta tesis doctoral, que persigue como objetivo analizar, planificar, diseñar, verificar y validar un marco arquitectónico de implantación de sistemas de e-salud en áreas rurales de países en desarrollo, que promueva el mejoramiento de la calidad de vida de la población vulnerable de estas regiones y la efectividad de las intervenciones de e-salud en el marco de proyectos de cooperación al desarrollo. Para lograrlo, tomé como punto de partida, diversas estrategias, modelos, metodologías de implantación de e-salud, modelos de gestión de proyectos propuestos por distintos organismos internacionales y propuse una instanciación de estos modelos a proyectos de implantación de sistemas de e-salud en países en desarrollo. Apliqué la metodología action research y los enfoques twin track, middle out y design thinking que me permitieron el refinamiento iterativo del modelo propuesto en la tesis doctoral mediante el trabajo de campo realizado en dos zonas rurales de países de Centroamérica: Jocotán (Guatemala) y San José de Cusmapa (Nicaragua). Como resultado obtuve un modelo experimental basado en cuatro componentes: un modelo de referencia tipo, un modelo conceptual de e-salud, los procesos de gestión y de implantación de sistemas de e-salud en países en desarrollo y una arquitectura de referencia. El modelo experimental resultante aporta herramientas importantes para el despliegue de sistemas de e-salud en países en desarrollo. Se ha propuesto un modelo de referencia que proporciona una visión holística del contexto del país en desarrollo donde se desarrollarán las intervenciones. Un modelo conceptual de e-salud que representa los principales conceptos involucrados en un sistema de e-salud. Los procesos ii- de gestión del proyecto y de implantación del sistema que proporcionan a los grupos de cooperación, herramientas para el análisis, diseño, desarrollo y despliegue de los sistemas de e-salud en áreas rurales de países en desarrollo. Y finalmente la arquitectura de referencia que sienta las bases para la aplicación de estos procesos a un contexto en particular. Las líneas futuras de trabajo sugieren extender el modelo a más casos de estudio que permitan su refinamiento y evaluar los futuros usos que pueden surgir de los sistemas de e-salud resultantes. ABSTRACT Millennium Development Goals (MDGs) committing the countries with a new global partnership to achieve universal coverage of minimum levels of well-being in Developing Countries (for addressing extreme poverty in its many dimensions-income poverty, hunger, disease, lack of adequate housing, and exclusion-while promoting gender equality, education, and environmental sustainability). From September 2015, these goals are replaces with Sustainable Development Goals (SDGs). The MDG place health at the heart of development and establish a novel global compact, linking developed and developing countries through clear, reciprocal obligations. Many public and private institutions promote international cooperation programs to support in achieving the MDGs. Some of these cooperation programs deal improving access to healthcare to poor people living in isolated areas from developing countries. In order to accomplish this goal organizations perform projects (interventions or cooperation projects) that deploy e-health systems in these zones. Nevertheless, this kind of projects face multiple challenges that dismiss the effectiveness of the projects results. In particular, cooperation teams face issues such as constraints in developing countries, lack of electrical and ICT infrastructure, scarce transport, extreme climate conditions, lack ICT capacity, lack of access to healthcare and inefficient delivery methods, etc. Hence, these issues increase the complexity of implementing e-health in developing countries and then causes the most projects fail. In other words, the solutions do not meet population needs and do not generate the expected impact on development. This context is the starting point of this doctoral thesis, which deals with analysing, planning, designing, testing and validating an architectural framework in order to implement e-health systems in rural areas from developing countries, promote development of the population in these regions, and thus improve the impact of interventions of development cooperation projects. To achieve this goal, I took as a starting point the strategies, models, e-health implementation methodologies and projects management models proposed by various international agencies. Then I proposed an instantiation of these models to manage the intervention and implement e-health systems in developing countries. I applied the action research methodology and the approaches twin track, middle out and design thinking which allowed me the iterative refinement of the model proposed in this doctoral thesis. The proposed framework was validated by running two cases studies in rural areas of Central America: Jocotán (Guatemala) and San José de Cusmapa (Nicaragua). As a result, I obtained an experimental model based on four components: a Type reference model, an e-health conceptual model, both process management and implementation e-health systems in developing countries and a reference architecture. The resulting experimental model provides important tools for the deployment of e-health systems in developing countries. The model become as reference model that provides a holistic view of the developing countries context where the interventions will be running. The conceptual model of e-health represents the main concepts involved into an e-health system. The project management and implementation processes of the iv- system provide to the cooperation teams with tools for analysing, designing, developing and deploying e-health systems in rural areas from developing countries. Finally, the reference architecture provides the basis for the implementation of these processes into a particular context. The future research suggest the extension the model to other cases studies in order to refine and evaluate the viability the model.

A Methodological model to assist the optimization and risk management of mining investment decisions

Identifying, quantifying, and minimizing technical risks associated with investment decisions is a key challenge for mineral industry decision makers and investors. However, risk analysis in most bankable mine feasibility studies are based on the stochastic modelling of project “Net Present Value” (NPV)which, in most cases, fails to provide decision makers with a truly comprehensive analysis of risks associated with technical and management uncertainty and, as a result, are of little use for risk management and project optimization. This paper presents a value-chain risk management approach where project risk is evaluated for each step of the project lifecycle, from exploration to mine closure, and risk management is performed as a part of a stepwise value-added optimization process.

Participatory modelling to support decision making in water management. A case study in the middle Guadiana basin, Spain.

The objective of this research was the implementation of a participatory process for the development of a tool to support decision making in water management. The process carried out aims at attaining an improved understanding of the water system and an encouragement of the exchange of knowledge and views between stakeholders to build a shared vision of the system. In addition, the process intends to identify impacts of possible solutions to given problems, which will help to take decisions.

Modelling Pinus pinea forest management to attain natural regeneration under present and future climatic scenarios

Natural regeneration-based silviculture has been increasingly regarded as a reliable option in sustainable forest management. However, successful natural regeneration is not always easy to achieve. Recently, new concerns have arisen because of changing future climate. To date, regeneration models have proved helpful in decision-making concerning natural regeneration. The implementation of such models into optimization routines is a promising approach in providing forest managers with accurate tools for forest planning. In the present study, we present a stochastic multistage regeneration model for Pinus pinea L. managed woodlands in Central Spain, where regeneration has been historically unsuccessful. The model is able to quantify recruitment under different silviculture alternatives and varying climatic scenarios, with further application to optimize management scheduling. The regeneration process in the species showed high between-year variation, with all subprocesses (seed production, dispersal, germination, predation, and seedling survival) having the potential to become bottlenecks. However, model simulations demonstrate that current intensive management is responsible for regeneration failure in the long term. Specifically, stand densities at rotation age are too low to guarantee adequate dispersal, the optimal density of seed-producing trees being around 150 stems·ha−1. In addition, rotation length needs to be extended up to 120 years to benefit from the higher seed production of older trees. Stochastic optimization confirms these results. Regeneration does not appear to worsen under climate change conditions; the species exhibiting resilience worthy of broader consideration in Mediterranean silviculture.

Participatory modelling to support decision making in water management under uncertainty: Two comparative case studies in the Guadiana river basin, Spain.

A participatory modelling process has been conducted in two areas of the Guadiana river (the upper and the middle sub-basins), in Spain, with the aim of providing support for decision making in the water management field. The area has a semi-arid climate where irrigated agriculture plays a key role in the economic development of the region and accounts for around 90% of water use. Following the guidelines of the European Water Framework Directive, we promote stakeholder involvement in water management with the aim to achieve an improved understanding of the water system and to encourage the exchange of knowledge and views between stakeholders in order to help building a shared vision of the system. At the same time, the resulting models, which integrate the different sectors and views, provide some insight of the impacts that different management options and possible future scenarios could have. The methodology is based on a Bayesian network combined with an economic model and, in the middle Guadiana sub-basin, with a crop model. The resulting integrated modelling framework is used to simulate possible water policy, market and climate scenarios to find out the impacts of those scenarios on farm income and on the environment. At the end of the modelling process, an evaluation questionnaire was filled by participants in both sub-basins. Results show that this type of processes are found very helpful by stakeholders to improve the system understanding, to understand each others views and to reduce conflict when it exists. In addition, they found the model an extremely useful tool to support management. The graphical interface, the quantitative output and the explicit representation of uncertainty helped stakeholders to better understand the implications of the scenario tested. Finally, the combination of different types of models was also found very useful, as it allowed exploring in detail specific aspects of the water management problems.

Integration of research advances in modelling and monitoring in support of WFD river basin management planning in the context of climate change

The integration of scientific knowledge about possible climate change impacts on water resources has a direct implication on the way water policies are being implemented and evolving. This is particularly true regarding various technical steps embedded into the EU Water Framework Directive river basin management planning, such as risk characterisation, monitoring, design and implementation of action programmes and evaluation of the "good status" objective achievements (in 2015). The need to incorporate climate change considerations into the implementation of EU water policy is currently discussed with a wide range of experts and stakeholders at EU level. Research trends are also on-going, striving to support policy developments and examining how scientific findings and recommendations could be best taken on board by policy-makers and water managers within the forthcoming years. This paper provides a snapshot of policy discussions about climate change in the context of the WFD river basin management planning and specific advancements of related EU-funded research projects. Perspectives for strengthening links among the scientific and policy-making communities in this area are also highlighted.

Novel Negotiation protocol to support CDM process in a layered ATM System

In the SESAR Step 2 concept of operations a RBT is available and seen by all making it possible to conceive a different operating method than the current ATM system based on Collaborative Decisions Making processes. Currently there is a need to describe in more detail the mechanisms by which actors (ATC, Network Management, Flight Crew, airports and Airline Operation Centre) will negotiate revisions to the RBT. This paper introduces a negotiation model, which uses constraint based programing applied to a mediator to facilitate negotiation process in a SWIM enabled environment. Three processes for modelling the negotiation process are explained as well a preliminary reasoning agent algorithm modelled with constraint satisfaction problem is presented. Computational capability of the model is evaluated in the conclusion.

Modelling the relationship between urban environment and travel behaviour: policy and indicators

Due to the necessity to undertake activities, every year people increase their standards of travelling (distance and time). Urban sprawl development plays an important role in these "enlargements". Thus, governments invest money in an exhaustiva search for solutions to high levels of congestion and car-trips. The complex relationship between urban environment and travel behaviour has been studied in a number of cases. Thus, the objective of this paper is to answer the important question of which land-use attributes influence which dimensions of travel behaviour, and to verify to what extent specific urban planning measures affect the individual decision process, by exhaustiva statistical and systematic tests. This paper found that a crucial issue in the analysis of the relationship between the built environment and travel behaviour is the definition of indicators. As such, we recommend a feasible list of indicators to analyze this relationship.

Modelling uncertainty of flood quantile estimation at ungauged sites by Bayesian networks

Prediction at ungauged sites is essential for water resources planning and management. Ungauged sites have no observations about the magnitude of floods, but some site and basin characteristics are known. Regression models relate physiographic and climatic basin characteristics to flood quantiles, which can be estimated from observed data at gauged sites. However, these models assume linear relationships between variables Prediction intervals are estimated by the variance of the residuals in the estimated model. Furthermore, the effect of the uncertainties in the explanatory variables on the dependent variable cannot be assessed. This paper presents a methodology to propagate the uncertainties that arise in the process of predicting flood quantiles at ungauged basins by a regression model. In addition, Bayesian networks were explored as a feasible tool for predicting flood quantiles at ungauged sites. Bayesian networks benefit from taking into account uncertainties thanks to their probabilistic nature. They are able to capture non-linear relationships between variables and they give a probability distribution of discharges as result. The methodology was applied to a case study in the Tagus basin in Spain.