Search results for: Francico Salguero Caparros

Authors: Juan Carlos Rubio Romero, Francico Salguero Caparros, Virginia Herrera-Pérez

Abstract:

No one is in the slightest doubt about the high levels of risk involved in work in the construction industry. They are even higher in structural construction work. The Critical Decision Method (CDM) is a semi-structured interview technique that uses cognitive tests to identify the different disturbances that workers have to deal with in their work activity. At present, the vision of safety focused on daily performance and things that go well for safety and health management is facing the new paradigm known as Resilience Engineering. The aim of this study has been to describe the variability in formwork labour on concrete structures in the construction industry and, from there, to find out the resilient attitude of workers to unexpected events that they have experienced during their working lives. For this purpose, a series of semi-structured interviews were carried out with construction employees with extensive experience in formwork labour in Spain by applying the Critical Decision Method. This work has been the first application of the Critical Decision Method in the field of construction and, more specifically, in the execution of structures. The results obtained show that situations categorised as unthought-of are identified to a greater extent than potentially unexpected situations. The identification during these interviews of both expected and unexpected events provides insight into the critical decisions made and actions taken to improve resilience in daily practice in this construction work. From this study, it is clear that it is essential to gain more knowledge about the nature of the human cognitive process in work situations within complex socio-technical systems such as construction sites. This could lead to a more effective design of workplaces in the search for improved human performance.

Keywords: resilience engineering, construction industry, unthought-of situations, critical decision method

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Authors: C. Fúnez Guerra, B. Nieto Calderón, M. Jaén Caparrós, L. Reyes-Bozo, A. Godoy-Faúndez, E. Vyhmeister

Abstract:

The global energy system is experiencing a change of scenery. Unstable energy markets, an increasing focus on climate change and its sustainable development is forcing businesses to pursue new solutions in order to ensure future economic growth. This has led to the interest in using hydrogen as an energy carrier in transportation and industrial applications. As an energy carrier, hydrogen is accessible and holds a high gravimetric energy density. Abundant in hydrocarbons, hydrogen can play an important role in the shift towards low-emission fossil value chains. By combining hydrogen production by natural gas reforming with carbon capture and storage, the overall CO2 emissions are significantly reduced. In addition, the flexibility of hydrogen as an energy storage makes it applicable as a stabilizer in the renewable energy mix. The recent development in hydrogen fuel cells is also raising the expectations for a hydrogen powered transportation sector. Hydrogen value chains exist to a large extent in the industry today. The global hydrogen consumption was approximately 50 million tonnes (7.2 EJ) in 2013, where refineries, ammonia, methanol production and metal processing were main consumers. Natural gas reforming produced 48% of this hydrogen, but without carbon capture and storage (CCS). The total emissions from the production reached 500 million tonnes of CO2, hence alternative production methods with lower emissions will be necessary in future value chains. Hydrogen from electrolysis is used for a wide range of industrial chemical reactions for many years. Possibly, the earliest use was for the production of ammonia-based fertilisers by Norsk Hydro, with a test reactor set up in Notodden, Norway, in 1927. This application also claims one of the world’s largest electrolyser installations, at Sable Chemicals in Zimbabwe. Its array of 28 electrolysers consumes 80 MW per hour, producing around 21,000 Nm3/h of hydrogen. These electrolysers can compete if cheap sources of electricity are available and natural gas for steam reforming is relatively expensive. Because electrolysis of water produces oxygen as a by-product, a system of Autothermal Reforming (ATR) utilizing this oxygen has been analyzed. Replacing the air separation unit with electrolysers produces the required amount of oxygen to the ATR as well as additional hydrogen. The aim of this paper is to evaluate the technical and economic potential of large-scale production of hydrogen for oil refining industry. Sensitivity analysis of parameters such as investment costs, plant operating hours, electricity price and sale price of hydrogen and oxygen are performed.

Keywords: autothermal reforming, electrolyser, hydrogen, natural gas, steam methane reforming

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Authors: Manuel I. Capel, Antonio Tomeu, Alberto Salguero

Abstract:

Tumor growth from a transformed cancer-cell up to a clinically apparent mass spans through a range of spatial and temporal magnitudes. Through computer simulations, Cellular Automata (CA) can accurately describe the complexity of the development of tumors. Tumor development prognosis can now be made -without making patients undergo through annoying medical examinations or painful invasive procedures- if we develop appropriate CA-based software tools. In silico testing mainly refers to Computational Biology research studies of application to clinical actions in Medicine. To establish sound computer-based models of cellular behavior, certainly reduces costs and saves precious time with respect to carrying out experiments in vitro at labs or in vivo with living cells and organisms. These aim to produce scientifically relevant results compared to traditional in vitro testing, which is slow, expensive, and does not generally have acceptable reproducibility under the same conditions. For speeding up computer simulations of cellular models, specific literature shows recent proposals based on the CA approach that include advanced techniques, such the clever use of supporting efficient data structures when modeling with deterministic stochastic cellular automata. Multiparadigm and multiscale simulation of tumor dynamics is just beginning to be developed by the concerned research community. The use of stochastic cellular automata (SCA), whose parallel programming implementations are open to yield a high computational performance, are of much interest to be explored up to their computational limits. There have been some approaches based on optimizations to advance in multiparadigm models of tumor growth, which mainly pursuit to improve performance of these models through efficient memory accesses guarantee, or considering the dynamic evolution of the memory space (grids, trees,…) that holds crucial data in simulations. In our opinion, the different optimizations mentioned above are not decisive enough to achieve the high performance computing power that cell-behavior simulation programs actually need. The possibility of using multicore and GPU parallelism as a promising multiplatform and framework to develop new programming techniques to speed-up the computation time of simulations is just starting to be explored in the few last years. This paper presents a model that incorporates parallel processing, identifying the synchronization necessary for speeding up tumor growth simulations implemented in Java and C++ programming environments. The speed up improvement that specific parallel syntactic constructs, such as executors (thread pools) in Java, are studied. The new tumor growth parallel model is proved using implementations with Java and C++ languages on two different platforms: chipset Intel core i-X and a HPC cluster of processors at our university. The parallelization of Polesczuk and Enderling model (normally used by researchers in mathematical oncology) proposed here is analyzed with respect to performance gain. We intend to apply the model and overall parallelization technique presented here to solid tumors of specific affiliation such as prostate, breast, or colon. Our final objective is to set up a multiparadigm model capable of modelling angiogenesis, or the growth inhibition induced by chemotaxis, as well as the effect of therapies based on the presence of cytotoxic/cytostatic drugs.

Keywords: cellular automaton, tumor growth model, simulation, multicore and manycore programming, parallel programming, high performance computing, speed up

Procedia PDF Downloads 209