When a vehicle moves over a flexible pavement structure,it generates loading and unloading cycles that produce recoverable(resilient)and permanent(plastic)deformations in the granular base and subbase layers,which are...When a vehicle moves over a flexible pavement structure,it generates loading and unloading cycles that produce recoverable(resilient)and permanent(plastic)deformations in the granular base and subbase layers,which are made of unbound granular materials(UGMs).The primary parameter used to evaluate the resilient response of UGMs in pavements is the resilient modulus(MR).The MR is widely used in calculating stress-strain states for flexible pavement design and as a control parameter during the construction process.It is also employed to understand the progression of distresses,such as fatigue cracking and rutting.The main objective of this study was to conduct a literature review on the resilient behavior of UGMs.This manuscript presents and describes the MR and the factors that influence it.It also outlines the evolution of the mathematical equations most commonly used to estimate and predict this physical parameter.Conclusions and recommendations for future research are provided at the end of the article.Despite the large amount of research done on the subject,the resilient behavior of UGM has not yet been fully understood.This is since these materials are highly heterogeneous and show nonlinear-anisotropic behavior under different cyclic loading paths and water contents.Likewise,these materials undergo different behaviors depending on their macro and microscopic properties(gradation,density,porosity,texture,mineralogy,particle geometry and orientation,temperature,among others).On the other hand,the main limitation of the mathematical equations is that their parameters are difficult to determine experimentally and are not constants of the material(they are state variables that can change with multiple factors).Additionally,these equations do not consider the boundary conditions to which UGM in pavements are exposed.Moreover,they are obtained from repeated load triaxial(RLT)tests,which cannot simulate the three cyclic stress components(vertical,horizontal,and shear)to which UGMs are subjected in a pavement.In recent years,there has been an increase in studies evaluating the use of recycled aggregates and the effect of temperature(particularly at subzero temperatures),but more research is still needed to reach definitive conclusions.展开更多
Microalgae possess significant advantages in nitrogen and phosphorus removal from nutrient-richwastewater that are highly efficient and independent of the C/N ratio.However,challenges such as low biomass productivity,...Microalgae possess significant advantages in nitrogen and phosphorus removal from nutrient-richwastewater that are highly efficient and independent of the C/N ratio.However,challenges such as low biomass productivity,high variability in nutrient removal under different trophic types,and difficulty in harvesting biomass limits the large-scale application of microalgae wastewater treatment.This study attempted to employmixotrophic microalgae biofilm to address these issues.The biomass production,microalgal activity,and nutrient removal of Chlorella pyrenoidosa biofilms with different trophic types were compared for nutrient-rich wastewater treatment.The results showed that the biomass productivity of the mixotrophic microalgal biofilm(0.215 g/(L·d))was 2.3,8.6,and 6.0 times higher than that of photoautotrophic microalgal biofilm,heterotrophic microalgal biofilm,and photoautotrophic suspended microalga,respectively.Additionally,the dehydrogenase activity(DHA),indicating microalgal activity,of the mixotrophic biofilm was 2.3 and 16.5 times higher than that of photoautotrophic and heterotrophic biofilms,respectively.Meanwhile,the mixotrophic biofilm removed 96.0%of NH_(4)^(+)-N and 99.2%of PO_(4)^(3-)-P,more efficient than that with other types of biofilms and suspended microalgae.In an open-ended air-lift photobioreactor,the mixotrophic microalgal biofilm produced biomass at 0.12 g/(L·d)and removed 90.0%of NH_(4)^(+)-N and 97.6%of PO_(4)^(3-)-P.This study suggests that the mixotrophic microalgal biofilm shows promise in treating nutrient-rich wastewater and producing microalgal biomass for value-added products.展开更多
The rapid growth of impervious areas in urban basins worldwide has increased the number of impermeable surfaces in cities,leading to severe flooding and significant economic losses for civilians.This trend highlights ...The rapid growth of impervious areas in urban basins worldwide has increased the number of impermeable surfaces in cities,leading to severe flooding and significant economic losses for civilians.This trend highlights the urgent need for methodologies that assess flood hazards and specifically address the direct impact on pedestrians,which is often overlooked in traditional flood hazard analyses.This study aims to evaluate a methodology for assessing the risk to pedestrians from hydrodynamic forces during urban floods,with a specific focus on Cúcuta,Colombia.The methodology couples research outcomes from other studies on the impact of floodwaters on individuals of different ages and sizes with 1D/2D hydrological modeling.Advanced computational algorithms for image recognition were used to measure water levels at 5-s intervals on November 6,2020,using drones for digital elevation model data collection.In Cúcuta,where flood risk is high and drainage infrastructure is limited,the PCSWMM(Computer-based Urban Stormwater Management Model)was calibrated and validated to simulate extreme flood events.The model incorporated urban infrastructure details and geomorphological parameters of Cúcuta's urban basin.Four return periods(5,10,50,100),with extreme rainfall of 3 h,were used to estimate the variability of the risk map.The output of the model was analyzed,and an integrated and time-varying comparison of the results was done.Results show that the regions of high-water depth and high velocity could vary significantly along the duration of the different extreme events.Also,from 5 to 100 years return period,the percentage of area at risk increased from 9.6%to 16.6%.The pedestrian sensitivity appears much higher than the increase in velocities or water depth individually.This study identified medium to high-risk locations,which are dynamic in time.We can conclude dynamics are spatiotemporal,and the added information layer of pedestrians brings vulnerability information that is also dynamic.Areas of immediate concern in Cúcuta can enhance pedestrian safety during flash flood events.The spatiotemporal variation of patterns requires further studies to map trajectories and sequences that machine learning models could capture.展开更多
The Atlantic Meridional Overturning Circulation(AMOC)is a crucial component of the Earth’s climate system due to its fundamental role in heat distribution,carbon and oxygen transport,and the weather.Other climate com...The Atlantic Meridional Overturning Circulation(AMOC)is a crucial component of the Earth’s climate system due to its fundamental role in heat distribution,carbon and oxygen transport,and the weather.Other climate components,such as the atmosphere and sea ice,influence the AMOC.Evaluating the physical mechanisms of those interactions is paramount to increasing knowledge about AMOC’s functioning.In this study,the authors used outputs from the Community Earth System Model version 2 and observational data to investigate changes in theAMOC and the associated physical processes.Two DECK experiments were evaluated:piControl and 1pctCO_(2),with an annual increase of 1%of atmospheric CO_(2).The analysis revealed a significant decrease in the AMOC,associated with changes in mixed layer depth and buoyancy in high latitudes of the North Atlantic,resulting in the shutdown of deep convection and potentially affecting the formation of North Atlantic Deep Water and Antarctic Bottom Water.A vital aspect observed in this study is the association between increased runoff and reduced water evaporation,giving rise to a positive feedback process.Consequently,the rates of freshwater spreading have intensified during this period,which could lead to an accelerated disruption of the AMOC beyond the projections of existing models.展开更多
The viability of a complete structural characterization of civil structures is explored and discussed. In particular, the identification of modal （i.e. natural frequencies, damping ratios and modal shapes） and physi...The viability of a complete structural characterization of civil structures is explored and discussed. In particular, the identification of modal （i.e. natural frequencies, damping ratios and modal shapes） and physical properties （i.e. mass and stiffness） using only the structure＇s free decay response is studied. To accomplish this, modal analysis from flee vibration response only （MAFVRO） and mass modification （MM） methodologies are engaged along with Wavelet based techniques for optimal signal processing and modal reconstruction. The methodologies are evaluated using simulated and experimental data. The simulated data are extracted from a simple elastic model of a 5 story shear building and from a more realistic nonlinear model of a RC frame structure. The experimental data are gathered from shake table test of a 2-story scaled shear building. Guidelines for the reconstruction procedure from the data are proposed as the quality of the identified properties is shown to be governed by adequate selection of the frequency bands and optimal modal shape reconstruction. Moreover, in cases where the structure has undergone damage, the proposed identification scheme can also be applied for preliminary assessment of structural health.展开更多
In supervised learning, the imbalanced number of instances among the classes in a dataset can make the algorithms to classify one instance from the minority class as one from the majority class. With the aim to solve ...In supervised learning, the imbalanced number of instances among the classes in a dataset can make the algorithms to classify one instance from the minority class as one from the majority class. With the aim to solve this problem, the KNN algorithm provides a basis to other balancing methods. These balancing methods are revisited in this work, and a new and simple approach of KNN undersampling is proposed. The experiments demonstrated that the KNN undersampling method outperformed other sampling methods. The proposed method also outperformed the results of other studies, and indicates that the simplicity of KNN can be used as a base for efficient algorithms in machine learning and knowledge discovery.展开更多
The outlook concerning the occurrence of industrial accidents has led to the implementation of response systems based on geoprocessing tools, which are widely adopted in emergency for such ventures, since they have he...The outlook concerning the occurrence of industrial accidents has led to the implementation of response systems based on geoprocessing tools, which are widely adopted in emergency for such ventures, since they have helped and served as a support for decision making, as well as for the preparation of guidelines aimed at managing emergencies. Nuclear power plants, because they constitute types of industrial activities that present dangerous conditions and attention regarding security are characterized as hazardous, especially due to consequences that occurred from large accidents— such as Chernobyl (1986) and Fukushima (2011)—highlighting the importance to its negative impacts, since the occurrence of accidents at nuclear power plants may affect surrounding areas, thus exposing a set of elements that are part of the environmental dynamics that integrates the catchment area where this type of plant is situated. In this way, through an integrated view of the region where the nuclear complex is located in Angra dos Reis City (Rio de Janeiro State) and, also, by aggregating information that portray the geobiophysical reality of its surroundings, several elements were incorporated into a database developed in a virtual environment, in which was produced a geographic information system (GIS) that presents a complex of variables that, once considered, can enhance various analysis in order to support emergency situations and planning, as well as guidelines that help define actions from the occurrence of accidental events at the nuclear plant.展开更多
The instability of the tensile armor wire of flexible pipes is a failure mode associated with deep and ultra-deep water applications. Real compressive forces acting on the pipe are necessary to trigger this process. T...The instability of the tensile armor wire of flexible pipes is a failure mode associated with deep and ultra-deep water applications. Real compressive forces acting on the pipe are necessary to trigger this process. The loss of stability may be divided into two distinct processes, according to the main direction of the wire＇s displacement： radial or lateral instability. This study aims at proposing a numerical tool for predicting lateral and radial critical buckling loads for the tensile armor wires of flexible pipes. A simple finite element model, based on springs and beams elements, was developed in ABAQUS~ to deal with this problem in an efficient and reliable manner. A parametric study was conducted concerning the behavior of the critical load when the laying angle, the initial curvature and the total pipe length are varied. The results were consistent with previously published literature data and analytical expressions, proving its applicability to pipe engineering projects. It also has the advantage of approaching the problem three-dimensionally, which allows further modelling modifications, such as including friction effects.展开更多
Since viruses are able to influence the trophic status and community structure they should be accessed and accounted in ecosystem functioning and management models. So, this work met a set of biological, chemical and ...Since viruses are able to influence the trophic status and community structure they should be accessed and accounted in ecosystem functioning and management models. So, this work met a set of biological, chemical and physical time series in order to explore the correlations with marine virioplankton community across different trophic gradients. The case studied is the Arraial do Cabo upwelling system, northeast of Rio de Janeiro State in Southeast coast of Brazil. The main goal is to evolve three type of artificial neural network (ANN) by genetic algorithm (GA) optimization to predict virioplankton abundance and dynamic. The input variables range from the abundance of phytoplankton, bacterioplankton and its ratios acquired by one in situ and another ex situ flow cytometers. These data were collected with weekly frequency from August 2006 to June 2007. Our results show viruses being highly correlated to their host, and that GA provided an efficient method of optimizing ANN architectures to predict the virioplankton abundance. The RBF-NN model presented the best performance to an accuracy of 97% for any period in the year. A discussion and ecological interpretations about the system behavior is also provided.展开更多
Oscillations in sea level due to meteorological forces related to wind and pressure affect the regular tides and modify the sea level conditions, mainly in restricted waters such as bays. Investigations surrounding th...Oscillations in sea level due to meteorological forces related to wind and pressure affect the regular tides and modify the sea level conditions, mainly in restricted waters such as bays. Investigations surrounding these variations and the biological and chemical response are important for monitoring coastal regions mainly where upwelling shelf systems occur. A spatial and temporal database from Quick Scatterometer satellite vector wind, surface stations from the Southeast coast of Brazil and surface seawater data collected in Anjos Bay, Arraial do Cabo city, northeast of Rio de Janeiro State were used to investigate the meteorological influences in the variability of the dissolved oxygen, nutrients, meroplankton larvae and chlorophyll-a concentrations. Multivariate statistical approaches such as Principal Component Analysis (PCA) and Clustering Analysis (CA) were applied to verify spatial and temporal variances. A correlation matrix was also verified for different water masses in order to identify the relationship between the above parameters. A seasonal variability of the meteorological residual presents a well-defined pattern with maximum peaks in autumn/winter and minimum during spring/summer with negative values, period of occurrence of upwelling in this region. This lowering of the sea level is in accordance with the increasing of nutrients and meroplankton larvae for the same period. CA showed six groups and an importance of the zonal and meridional wind variability, including these variables in a single cluster. PCA retained eight components, explaining 64.10% of the total variance of data set. Some clusters and loadings have the same variables, showing the importance of the sea-air interaction.展开更多
Photodegradation or photocatalysis is a chemical degradation process that occurs when an inorganic semiconductor is exposed to ultraviolet (UV) light. UV light (wavelength 320 - 400 nm) has enough energy to detach an ...Photodegradation or photocatalysis is a chemical degradation process that occurs when an inorganic semiconductor is exposed to ultraviolet (UV) light. UV light (wavelength 320 - 400 nm) has enough energy to detach an electron from the last layer of the semiconductor, leading to the conduction band, leaving a hole in the valence band. In these bands, chemical reduction and oxidation reactions occur, respectively. These reactions degrade diverse surface dirt, dissociating them into simpler and less offensive substances such as CO2 and H2O. In this work, we studied the potential of photocatalysis of a composite based on a semiconductor encapsulated in epoxy resin, in the degradation of Staphylococcus aureus, pathogen with a high degree of hospital contamination, in order to apply it to the construction in hospital facilities. The experiments were carried out with a fabrication of only epoxy resin tablets and tablets with the composite, at various concentrations of the semiconductor and glass powder. Through contamination of these tablets and their exposure to sunlight and the ambient light, contamination on their surfaces was verified. The results indicated potential photodegradation capacity of the composite.展开更多
Wrong-way driving(WWD)has been a long-lasting issue for transportation agencies and law enforcement,since it causes pivotal threats to road users.Notwithstanding being rare,crashes occurring due to WWD are more severe...Wrong-way driving(WWD)has been a long-lasting issue for transportation agencies and law enforcement,since it causes pivotal threats to road users.Notwithstanding being rare,crashes occurring due to WWD are more severe than other types of crashes.In order to analyze WWD crashes,there is a need to obtain WWD incidents or crash data.However,it is time-consuming to identify actual WWD crashes from potential WWD crashes in large crash databases.It often involves large man-hours to review hardcopy of crash narratives in the police reports.Otherwise,it may cause an overestimation or underestimation of WWD crash frequencies.To fill this gap,the present study,as the first-of-its-kind,aims at identifying actual WWD crashes from potential WWD crashes in police reports by using machine learning methods.Recently,Bidirectional Encoder Representations from Transformers(BERT)models have shown promising results in natural language processing.In this study,we implemented the BERT model as well as five conventional classification algorithms,including Naïve Bayes(NB),Support Vector Machine(SVM),Decision Tree(DT),Random Forest(RF),and Single Layer Perceptron(SLP)to classify crash report narratives as actual WWD and non-WWD crashes.Cross-validation and different performance metrics were used to evaluate the performance of each classification algorithm.Results indicated that the BERT model outperformed in identifying actual WWD crashes in comparison with other algorithms with an accuracy of 81.59%.The BERT classification algorithm can be implemented to reduce the time needed to identify actual WWD crashes from crash report narratives.展开更多
文摘When a vehicle moves over a flexible pavement structure,it generates loading and unloading cycles that produce recoverable(resilient)and permanent(plastic)deformations in the granular base and subbase layers,which are made of unbound granular materials(UGMs).The primary parameter used to evaluate the resilient response of UGMs in pavements is the resilient modulus(MR).The MR is widely used in calculating stress-strain states for flexible pavement design and as a control parameter during the construction process.It is also employed to understand the progression of distresses,such as fatigue cracking and rutting.The main objective of this study was to conduct a literature review on the resilient behavior of UGMs.This manuscript presents and describes the MR and the factors that influence it.It also outlines the evolution of the mathematical equations most commonly used to estimate and predict this physical parameter.Conclusions and recommendations for future research are provided at the end of the article.Despite the large amount of research done on the subject,the resilient behavior of UGM has not yet been fully understood.This is since these materials are highly heterogeneous and show nonlinear-anisotropic behavior under different cyclic loading paths and water contents.Likewise,these materials undergo different behaviors depending on their macro and microscopic properties(gradation,density,porosity,texture,mineralogy,particle geometry and orientation,temperature,among others).On the other hand,the main limitation of the mathematical equations is that their parameters are difficult to determine experimentally and are not constants of the material(they are state variables that can change with multiple factors).Additionally,these equations do not consider the boundary conditions to which UGM in pavements are exposed.Moreover,they are obtained from repeated load triaxial(RLT)tests,which cannot simulate the three cyclic stress components(vertical,horizontal,and shear)to which UGMs are subjected in a pavement.In recent years,there has been an increase in studies evaluating the use of recycled aggregates and the effect of temperature(particularly at subzero temperatures),but more research is still needed to reach definitive conclusions.
基金supported by the Natural Science Foundation of Guangdong Province(No.2020A1515011113)the Applied Basic Research Project of Guangzhou(No.202002030455)Zhongshan Science and Technology Plan Project(No.2020AG021).
文摘Microalgae possess significant advantages in nitrogen and phosphorus removal from nutrient-richwastewater that are highly efficient and independent of the C/N ratio.However,challenges such as low biomass productivity,high variability in nutrient removal under different trophic types,and difficulty in harvesting biomass limits the large-scale application of microalgae wastewater treatment.This study attempted to employmixotrophic microalgae biofilm to address these issues.The biomass production,microalgal activity,and nutrient removal of Chlorella pyrenoidosa biofilms with different trophic types were compared for nutrient-rich wastewater treatment.The results showed that the biomass productivity of the mixotrophic microalgal biofilm(0.215 g/(L·d))was 2.3,8.6,and 6.0 times higher than that of photoautotrophic microalgal biofilm,heterotrophic microalgal biofilm,and photoautotrophic suspended microalga,respectively.Additionally,the dehydrogenase activity(DHA),indicating microalgal activity,of the mixotrophic biofilm was 2.3 and 16.5 times higher than that of photoautotrophic and heterotrophic biofilms,respectively.Meanwhile,the mixotrophic biofilm removed 96.0%of NH_(4)^(+)-N and 99.2%of PO_(4)^(3-)-P,more efficient than that with other types of biofilms and suspended microalgae.In an open-ended air-lift photobioreactor,the mixotrophic microalgal biofilm produced biomass at 0.12 g/(L·d)and removed 90.0%of NH_(4)^(+)-N and 97.6%of PO_(4)^(3-)-P.This study suggests that the mixotrophic microalgal biofilm shows promise in treating nutrient-rich wastewater and producing microalgal biomass for value-added products.
基金University of PamplonaColombian School of Engineering Julio Garavito。
文摘The rapid growth of impervious areas in urban basins worldwide has increased the number of impermeable surfaces in cities,leading to severe flooding and significant economic losses for civilians.This trend highlights the urgent need for methodologies that assess flood hazards and specifically address the direct impact on pedestrians,which is often overlooked in traditional flood hazard analyses.This study aims to evaluate a methodology for assessing the risk to pedestrians from hydrodynamic forces during urban floods,with a specific focus on Cúcuta,Colombia.The methodology couples research outcomes from other studies on the impact of floodwaters on individuals of different ages and sizes with 1D/2D hydrological modeling.Advanced computational algorithms for image recognition were used to measure water levels at 5-s intervals on November 6,2020,using drones for digital elevation model data collection.In Cúcuta,where flood risk is high and drainage infrastructure is limited,the PCSWMM(Computer-based Urban Stormwater Management Model)was calibrated and validated to simulate extreme flood events.The model incorporated urban infrastructure details and geomorphological parameters of Cúcuta's urban basin.Four return periods(5,10,50,100),with extreme rainfall of 3 h,were used to estimate the variability of the risk map.The output of the model was analyzed,and an integrated and time-varying comparison of the results was done.Results show that the regions of high-water depth and high velocity could vary significantly along the duration of the different extreme events.Also,from 5 to 100 years return period,the percentage of area at risk increased from 9.6%to 16.6%.The pedestrian sensitivity appears much higher than the increase in velocities or water depth individually.This study identified medium to high-risk locations,which are dynamic in time.We can conclude dynamics are spatiotemporal,and the added information layer of pedestrians brings vulnerability information that is also dynamic.Areas of immediate concern in Cúcuta can enhance pedestrian safety during flash flood events.The spatiotemporal variation of patterns requires further studies to map trajectories and sequences that machine learning models could capture.
基金This work was possible through the financing of PEC-20480 Project between Royal Dutch Shell(Shell)and the Laboratório de Métodos Computacionais em Engenharia(LAMCE)and through the doctoral fellowship funding by CNPq for Elisa Passos Case number 141819/2016-2the postdoctoral fellowship funding by FAPERJ E 10/2020-Edital Inteligência Artificial Case Number E-26/203.327/2022-Enrollment No.Scholarship 2015.08297.7 for Lívia Sancho.
文摘The Atlantic Meridional Overturning Circulation(AMOC)is a crucial component of the Earth’s climate system due to its fundamental role in heat distribution,carbon and oxygen transport,and the weather.Other climate components,such as the atmosphere and sea ice,influence the AMOC.Evaluating the physical mechanisms of those interactions is paramount to increasing knowledge about AMOC’s functioning.In this study,the authors used outputs from the Community Earth System Model version 2 and observational data to investigate changes in theAMOC and the associated physical processes.Two DECK experiments were evaluated:piControl and 1pctCO_(2),with an annual increase of 1%of atmospheric CO_(2).The analysis revealed a significant decrease in the AMOC,associated with changes in mixed layer depth and buoyancy in high latitudes of the North Atlantic,resulting in the shutdown of deep convection and potentially affecting the formation of North Atlantic Deep Water and Antarctic Bottom Water.A vital aspect observed in this study is the association between increased runoff and reduced water evaporation,giving rise to a positive feedback process.Consequently,the rates of freshwater spreading have intensified during this period,which could lead to an accelerated disruption of the AMOC beyond the projections of existing models.
基金supported by the National Science Foundation Grant No.CMMI-1121146
文摘The viability of a complete structural characterization of civil structures is explored and discussed. In particular, the identification of modal （i.e. natural frequencies, damping ratios and modal shapes） and physical properties （i.e. mass and stiffness） using only the structure＇s free decay response is studied. To accomplish this, modal analysis from flee vibration response only （MAFVRO） and mass modification （MM） methodologies are engaged along with Wavelet based techniques for optimal signal processing and modal reconstruction. The methodologies are evaluated using simulated and experimental data. The simulated data are extracted from a simple elastic model of a 5 story shear building and from a more realistic nonlinear model of a RC frame structure. The experimental data are gathered from shake table test of a 2-story scaled shear building. Guidelines for the reconstruction procedure from the data are proposed as the quality of the identified properties is shown to be governed by adequate selection of the frequency bands and optimal modal shape reconstruction. Moreover, in cases where the structure has undergone damage, the proposed identification scheme can also be applied for preliminary assessment of structural health.
文摘In supervised learning, the imbalanced number of instances among the classes in a dataset can make the algorithms to classify one instance from the minority class as one from the majority class. With the aim to solve this problem, the KNN algorithm provides a basis to other balancing methods. These balancing methods are revisited in this work, and a new and simple approach of KNN undersampling is proposed. The experiments demonstrated that the KNN undersampling method outperformed other sampling methods. The proposed method also outperformed the results of other studies, and indicates that the simplicity of KNN can be used as a base for efficient algorithms in machine learning and knowledge discovery.
文摘The outlook concerning the occurrence of industrial accidents has led to the implementation of response systems based on geoprocessing tools, which are widely adopted in emergency for such ventures, since they have helped and served as a support for decision making, as well as for the preparation of guidelines aimed at managing emergencies. Nuclear power plants, because they constitute types of industrial activities that present dangerous conditions and attention regarding security are characterized as hazardous, especially due to consequences that occurred from large accidents— such as Chernobyl (1986) and Fukushima (2011)—highlighting the importance to its negative impacts, since the occurrence of accidents at nuclear power plants may affect surrounding areas, thus exposing a set of elements that are part of the environmental dynamics that integrates the catchment area where this type of plant is situated. In this way, through an integrated view of the region where the nuclear complex is located in Angra dos Reis City (Rio de Janeiro State) and, also, by aggregating information that portray the geobiophysical reality of its surroundings, several elements were incorporated into a database developed in a virtual environment, in which was produced a geographic information system (GIS) that presents a complex of variables that, once considered, can enhance various analysis in order to support emergency situations and planning, as well as guidelines that help define actions from the occurrence of accidental events at the nuclear plant.
文摘The instability of the tensile armor wire of flexible pipes is a failure mode associated with deep and ultra-deep water applications. Real compressive forces acting on the pipe are necessary to trigger this process. The loss of stability may be divided into two distinct processes, according to the main direction of the wire＇s displacement： radial or lateral instability. This study aims at proposing a numerical tool for predicting lateral and radial critical buckling loads for the tensile armor wires of flexible pipes. A simple finite element model, based on springs and beams elements, was developed in ABAQUS~ to deal with this problem in an efficient and reliable manner. A parametric study was conducted concerning the behavior of the critical load when the laying angle, the initial curvature and the total pipe length are varied. The results were consistent with previously published literature data and analytical expressions, proving its applicability to pipe engineering projects. It also has the advantage of approaching the problem three-dimensionally, which allows further modelling modifications, such as including friction effects.
文摘Since viruses are able to influence the trophic status and community structure they should be accessed and accounted in ecosystem functioning and management models. So, this work met a set of biological, chemical and physical time series in order to explore the correlations with marine virioplankton community across different trophic gradients. The case studied is the Arraial do Cabo upwelling system, northeast of Rio de Janeiro State in Southeast coast of Brazil. The main goal is to evolve three type of artificial neural network (ANN) by genetic algorithm (GA) optimization to predict virioplankton abundance and dynamic. The input variables range from the abundance of phytoplankton, bacterioplankton and its ratios acquired by one in situ and another ex situ flow cytometers. These data were collected with weekly frequency from August 2006 to June 2007. Our results show viruses being highly correlated to their host, and that GA provided an efficient method of optimizing ANN architectures to predict the virioplankton abundance. The RBF-NN model presented the best performance to an accuracy of 97% for any period in the year. A discussion and ecological interpretations about the system behavior is also provided.
基金financial support of the Coordination for the Improvement of Higher Level Personnel-Brazilian Research Agency(Capes).
文摘Oscillations in sea level due to meteorological forces related to wind and pressure affect the regular tides and modify the sea level conditions, mainly in restricted waters such as bays. Investigations surrounding these variations and the biological and chemical response are important for monitoring coastal regions mainly where upwelling shelf systems occur. A spatial and temporal database from Quick Scatterometer satellite vector wind, surface stations from the Southeast coast of Brazil and surface seawater data collected in Anjos Bay, Arraial do Cabo city, northeast of Rio de Janeiro State were used to investigate the meteorological influences in the variability of the dissolved oxygen, nutrients, meroplankton larvae and chlorophyll-a concentrations. Multivariate statistical approaches such as Principal Component Analysis (PCA) and Clustering Analysis (CA) were applied to verify spatial and temporal variances. A correlation matrix was also verified for different water masses in order to identify the relationship between the above parameters. A seasonal variability of the meteorological residual presents a well-defined pattern with maximum peaks in autumn/winter and minimum during spring/summer with negative values, period of occurrence of upwelling in this region. This lowering of the sea level is in accordance with the increasing of nutrients and meroplankton larvae for the same period. CA showed six groups and an importance of the zonal and meridional wind variability, including these variables in a single cluster. PCA retained eight components, explaining 64.10% of the total variance of data set. Some clusters and loadings have the same variables, showing the importance of the sea-air interaction.
文摘Photodegradation or photocatalysis is a chemical degradation process that occurs when an inorganic semiconductor is exposed to ultraviolet (UV) light. UV light (wavelength 320 - 400 nm) has enough energy to detach an electron from the last layer of the semiconductor, leading to the conduction band, leaving a hole in the valence band. In these bands, chemical reduction and oxidation reactions occur, respectively. These reactions degrade diverse surface dirt, dissociating them into simpler and less offensive substances such as CO2 and H2O. In this work, we studied the potential of photocatalysis of a composite based on a semiconductor encapsulated in epoxy resin, in the degradation of Staphylococcus aureus, pathogen with a high degree of hospital contamination, in order to apply it to the construction in hospital facilities. The experiments were carried out with a fabrication of only epoxy resin tablets and tablets with the composite, at various concentrations of the semiconductor and glass powder. Through contamination of these tablets and their exposure to sunlight and the ambient light, contamination on their surfaces was verified. The results indicated potential photodegradation capacity of the composite.
文摘Wrong-way driving(WWD)has been a long-lasting issue for transportation agencies and law enforcement,since it causes pivotal threats to road users.Notwithstanding being rare,crashes occurring due to WWD are more severe than other types of crashes.In order to analyze WWD crashes,there is a need to obtain WWD incidents or crash data.However,it is time-consuming to identify actual WWD crashes from potential WWD crashes in large crash databases.It often involves large man-hours to review hardcopy of crash narratives in the police reports.Otherwise,it may cause an overestimation or underestimation of WWD crash frequencies.To fill this gap,the present study,as the first-of-its-kind,aims at identifying actual WWD crashes from potential WWD crashes in police reports by using machine learning methods.Recently,Bidirectional Encoder Representations from Transformers(BERT)models have shown promising results in natural language processing.In this study,we implemented the BERT model as well as five conventional classification algorithms,including Naïve Bayes(NB),Support Vector Machine(SVM),Decision Tree(DT),Random Forest(RF),and Single Layer Perceptron(SLP)to classify crash report narratives as actual WWD and non-WWD crashes.Cross-validation and different performance metrics were used to evaluate the performance of each classification algorithm.Results indicated that the BERT model outperformed in identifying actual WWD crashes in comparison with other algorithms with an accuracy of 81.59%.The BERT classification algorithm can be implemented to reduce the time needed to identify actual WWD crashes from crash report narratives.
