The Experts below are selected from a list of 775485 Experts worldwide ranked by ideXlab platform
Caprace Jean-david - One of the best experts on this subject based on the ideXlab platform.
-
A discrete-event Simulation Approach to evaluate the effect of stochastic parameters on offshore wind farms assembly strategies
2018Co-Authors: Tekle Muhabie Y., Rigo Philippe, Cepeda M., De Almeida D'agosto M., Caprace Jean-davidAbstract:The wind industry is facing new challenges due to the planned construction of thousands of offshore wind turbines all around the world. However, with their increasing distance from the shore, greater water depths, and increasing sizes of the plants, the industry has to face the challenge to develop sustainable installation procedures. Important limiting factors for offshore wind farm installation are the weather conditions and installation strategies. In this context, the focus of this research is the investigation of the most effective Approach to installing offshore wind farms at sea, including the effects of weather conditions. This target is achieved through the implementation of a discrete-event Simulation Approach which includes the analysis of the environmental conditions, distance matrix, vessel characteristics, and assembly scenarios. The model maps the logistics chain in the offshore wind industry. A deterministic and a probabilistic metocean data method have been compared and cross validated. The results point to a good agreement between the two considered models, while highlighting the huge risks to the time and cost of the installation due to the stochastic nature of the weather. We suggest that Simulations may improve and reduce these risks in the planning process of offshore wind farms. © 2017 Elsevier LtdPeer reviewe
-
A discrete-event Simulation Approach to evaluate the effect of stochastic parameters on offshore wind farms assembly strategies
'Elsevier BV', 2018Co-Authors: Tekle Muhabie Y., Rigo Philippe, Cepeda M., De Almeida D'agosto M., Caprace Jean-davidAbstract:peer reviewedaudience: researcher, professionalThe wind industry is facing new challenges due to the planned construction of thousands of offshore wind turbines all around the world. However, with their increasing distance from the shore, greater water depths, and increasing sizes of the plants, the industry has to face the challenge to develop sustainable installation procedures. Important limiting factors for offshore wind farm installation are the weather conditions and installation strategies. In this context, the focus of this research is the investigation of the most effective Approach to installing offshore wind farms at sea, including the effects of weather conditions. This target is achieved through the implementation of a discrete-event Simulation Approach which includes the analysis of the environmental conditions, distance matrix, vessel characteristics, and assembly scenarios. The model maps the logistics chain in the offshore wind industry. A deterministic and a probabilistic metocean data method have been compared and cross validated. The results point to a good agreement between the two considered models, while highlighting the huge risks to the time and cost of the installation due to the stochastic nature of the weather. We suggest that Simulations may improve and reduce these risks in the planning process of offshore wind farms. © 2017 Elsevier Lt
Liang Chen - One of the best experts on this subject based on the ideXlab platform.
-
sky view factor analysis of street canyons and its implications for daytime intra urban air temperature differentials in high rise high density urban areas of hong kong a gis based Simulation Approach
International Journal of Climatology, 2012Co-Authors: Liang Chen, Chao Ren, Max Lee, Una WangAbstract:Hong Kong is a high-density sub-tropical city with 7 million people living in an urban area of just over 260 km2. Tall and closely packed buildings are the common urban morphology. How the urban geometry influences the microclimate in summer daytime is a primary planning concern. The sky view factor (SVF) has been commonly used to indicate the impact of urban geometry on air temperature differences in cities. However, only limited discussions in this aspect have been addressed for daytime course in high-rise and high-density urban environment such as Hong Kong. This paper firstly provides a comprehensive review of SVF analysis in urban climatology studies and then presents a Simulation Approach to investigate the role of SVF in determining summer daytime intra-urban air temperature differences in urban Hong Kong. An ArcGIS-embedded computer program is developed for calculating continuous SVF values for an entire urban environment and an SVF map is generated. The result is evaluated against meteorological data observed in field measurements. The regression analysis shows that the spatial average of SVF values has a close negative relationship with daytime intra-urban temperature differences. The study indicates that SVF is a significant factor for understanding the microthermal climate in Hong Kong's street canyons. The paper further raises discussions on the application of SVF analysis to urban planning. The study demonstrates that the SVF analysis is a useful and effective tool for planners and urban climatologists conducting studies on high-rise and high-density sub-tropical cities. The understanding can provide support for the development of planning standards and good practice. Copyright © 2010 Royal Meteorological Society
-
quantitative urban climate mapping based on a geographical database a Simulation Approach using hong kong as a case study
International Journal of Applied Earth Observation and Geoinformation, 2011Co-Authors: Liang ChenAbstract:The urban environment has been dramatically changed by artificial constructions. How the modified urban geometry affects the urban climate and therefore human thermal comfort has become a primary concern for urban planners. The present study takes a Simulation Approach to analyze the influence of urban geometry on the urban climate and maps this climatic understanding from a quantitative perspective. A geographical building database is used to characterize two widely discussed aspects: urban heat island effect (UHI) and wind dynamics. The parameters of the sky view factor (SVF) and the frontal area density (FAD) are simulated using ArcGIS-embedded computer programs to link urban geometry with the UHI and wind dynamic conditions. The simulated results are synergized and classified to evaluate different urban climatic conditions based on thermal comfort consideration. A climatic map is then generated implementing the classification. The climatic map shows reasonable agreement with thermal comfort understanding, as indicated by the biometeorological index of the physiological equivalent temperature (PET) obtained in an earlier study. The proposed climate mapping Approach can provide both quantitative and visual evaluation of the urban environment for urban planners with climatic concerns. The map could be used as a decision support tool in planning and policy-making processes. An urban area in Hong Kong is used as a case study.
Tekle Muhabie Y. - One of the best experts on this subject based on the ideXlab platform.
-
A discrete-event Simulation Approach to evaluate the effect of stochastic parameters on offshore wind farms assembly strategies
2018Co-Authors: Tekle Muhabie Y., Rigo Philippe, Cepeda M., De Almeida D'agosto M., Caprace Jean-davidAbstract:The wind industry is facing new challenges due to the planned construction of thousands of offshore wind turbines all around the world. However, with their increasing distance from the shore, greater water depths, and increasing sizes of the plants, the industry has to face the challenge to develop sustainable installation procedures. Important limiting factors for offshore wind farm installation are the weather conditions and installation strategies. In this context, the focus of this research is the investigation of the most effective Approach to installing offshore wind farms at sea, including the effects of weather conditions. This target is achieved through the implementation of a discrete-event Simulation Approach which includes the analysis of the environmental conditions, distance matrix, vessel characteristics, and assembly scenarios. The model maps the logistics chain in the offshore wind industry. A deterministic and a probabilistic metocean data method have been compared and cross validated. The results point to a good agreement between the two considered models, while highlighting the huge risks to the time and cost of the installation due to the stochastic nature of the weather. We suggest that Simulations may improve and reduce these risks in the planning process of offshore wind farms. © 2017 Elsevier LtdPeer reviewe
-
A discrete-event Simulation Approach to evaluate the effect of stochastic parameters on offshore wind farms assembly strategies
'Elsevier BV', 2018Co-Authors: Tekle Muhabie Y., Rigo Philippe, Cepeda M., De Almeida D'agosto M., Caprace Jean-davidAbstract:peer reviewedaudience: researcher, professionalThe wind industry is facing new challenges due to the planned construction of thousands of offshore wind turbines all around the world. However, with their increasing distance from the shore, greater water depths, and increasing sizes of the plants, the industry has to face the challenge to develop sustainable installation procedures. Important limiting factors for offshore wind farm installation are the weather conditions and installation strategies. In this context, the focus of this research is the investigation of the most effective Approach to installing offshore wind farms at sea, including the effects of weather conditions. This target is achieved through the implementation of a discrete-event Simulation Approach which includes the analysis of the environmental conditions, distance matrix, vessel characteristics, and assembly scenarios. The model maps the logistics chain in the offshore wind industry. A deterministic and a probabilistic metocean data method have been compared and cross validated. The results point to a good agreement between the two considered models, while highlighting the huge risks to the time and cost of the installation due to the stochastic nature of the weather. We suggest that Simulations may improve and reduce these risks in the planning process of offshore wind farms. © 2017 Elsevier Lt
Riva Gabriele - One of the best experts on this subject based on the ideXlab platform.
-
A Multi-Scale Simulation Approach to InvestigateLocal Contact Temperatures for Commercial Cu-Fulland Cu-Free Brake Pads
Brembo S.p.A., 2019Co-Authors: Riva GabrieleAbstract:Copper from vehicles disc brakes is one main contributor of the total copper found inthe environment. Therefore, the U.S. Environmental Protection Agency (EPA) and the automotiveindustries started the Copper-Free Brake Initiative. The pad friction material is essentially composedof a binder, fillers, reinforcing fibres and frictional additives. Copper and brass fibres are the mostcommonly used fibres in brake pads. There is a need to understand how the contact temperaturedistribution will change if copper-based fibres are changed to steel fibres. The aim of this work is,therefore, to investigate how this change could influence the local contact temperatures. This is doneby developing a multi-scale Simulation Approach which combines cellular automaton, finite elementanalysis (FEA) and computational fluid dynamics (CFD) Approaches with outputs from inertia brakedyno bench tests of Cu-full and Cu-free pads. FEA and thermal-CFD are used to set the pressureand the temperature boundary conditions of the cellular automaton. The outputs of dyno tests areused to calibrate FEA and CFD Simulations. The results of the study show lower peaks in contacttemperature and a more uniform temperature distribution for the Cu-free pad friction material.QC 20200922
-
A Multi-Scale Simulation Approach to Investigate Local Contact Temperatures for Commercial Cu-Full and Cu-Free Brake Pads
Basel, 2019Co-Authors: Riva Gabriele, Perricone Guido, Wahlström JensAbstract:Copper from vehicles disc brakes is one main contributor of the total copper found in the environment. Therefore, the U.S. Environmental Protection Agency (EPA) and the automotive industries started the Copper-Free Brake Initiative. The pad friction material is essentially composed of a binder, fillers, reinforcing fibres and frictional additives. Copper and brass fibres are the most commonly used fibres in brake pads. There is a need to understand how the contact temperature distribution will change if copper-based fibres are changed to steel fibres. The aim of this work is, therefore, to investigate how this change could influence the local contact temperatures. This is done by developing a multi-scale Simulation Approach which combines cellular automaton, finite element analysis (FEA) and computational fluid dynamics (CFD) Approaches with outputs from inertia brake dyno bench tests of Cu-full and Cu-free pads. FEA and thermal-CFD are used to set the pressure and the temperature boundary conditions of the cellular automaton. The outputs of dyno tests are used to calibrate FEA and CFD Simulations. The results of the study show lower peaks in contact temperature and a more uniform temperature distribution for the Cu-free pad friction material.QC 20190918EIT Raw Materials project ECOPAD
De Almeida D'agosto M. - One of the best experts on this subject based on the ideXlab platform.
-
A discrete-event Simulation Approach to evaluate the effect of stochastic parameters on offshore wind farms assembly strategies
2018Co-Authors: Tekle Muhabie Y., Rigo Philippe, Cepeda M., De Almeida D'agosto M., Caprace Jean-davidAbstract:The wind industry is facing new challenges due to the planned construction of thousands of offshore wind turbines all around the world. However, with their increasing distance from the shore, greater water depths, and increasing sizes of the plants, the industry has to face the challenge to develop sustainable installation procedures. Important limiting factors for offshore wind farm installation are the weather conditions and installation strategies. In this context, the focus of this research is the investigation of the most effective Approach to installing offshore wind farms at sea, including the effects of weather conditions. This target is achieved through the implementation of a discrete-event Simulation Approach which includes the analysis of the environmental conditions, distance matrix, vessel characteristics, and assembly scenarios. The model maps the logistics chain in the offshore wind industry. A deterministic and a probabilistic metocean data method have been compared and cross validated. The results point to a good agreement between the two considered models, while highlighting the huge risks to the time and cost of the installation due to the stochastic nature of the weather. We suggest that Simulations may improve and reduce these risks in the planning process of offshore wind farms. © 2017 Elsevier LtdPeer reviewe
-
A discrete-event Simulation Approach to evaluate the effect of stochastic parameters on offshore wind farms assembly strategies
'Elsevier BV', 2018Co-Authors: Tekle Muhabie Y., Rigo Philippe, Cepeda M., De Almeida D'agosto M., Caprace Jean-davidAbstract:peer reviewedaudience: researcher, professionalThe wind industry is facing new challenges due to the planned construction of thousands of offshore wind turbines all around the world. However, with their increasing distance from the shore, greater water depths, and increasing sizes of the plants, the industry has to face the challenge to develop sustainable installation procedures. Important limiting factors for offshore wind farm installation are the weather conditions and installation strategies. In this context, the focus of this research is the investigation of the most effective Approach to installing offshore wind farms at sea, including the effects of weather conditions. This target is achieved through the implementation of a discrete-event Simulation Approach which includes the analysis of the environmental conditions, distance matrix, vessel characteristics, and assembly scenarios. The model maps the logistics chain in the offshore wind industry. A deterministic and a probabilistic metocean data method have been compared and cross validated. The results point to a good agreement between the two considered models, while highlighting the huge risks to the time and cost of the installation due to the stochastic nature of the weather. We suggest that Simulations may improve and reduce these risks in the planning process of offshore wind farms. © 2017 Elsevier Lt
