Numerical simulation of mud-flows impacting structures

The study of the interaction of mud-flows with obstacles is important to define inundation zones in urban areas and to design the possible structural countermeasures. The paper numerically investigates the impact of a mud-flow on rigid obstacles to evaluate the force acting on them using two different depth-integrated theoretical models, Single-Phase Model(SPM) and Two-Phase Model(TPM), to compare their performance and limits. In the first one the water-sediment mixture is represented as a homogeneous continuum described by a shearthinning power-law rheology. Alternatively, the twophase model proposed by Di Cristo et al in 2016 is used, which separately accounts for the liquid and solid phases. The considered test cases are represented by a 1D landslide flowing on a steep slope impacting on a rigid wall and a 2D mud dam-break flowing on a horizontal bottom in presence of single and multiple rigid obstacles. In the 1D test case, characterized by a very steep slope, the Two-Phase Model predicts the separation between the two phases with a significant longitudinal variation of the solid concentration. In this case the results indicate appreciable differences between the two models in the estimation of both the wave celerity and the magnitude of the impact, with an overestimation of the peak force when using the Single-Phase Model. In the 2D test-cases, where the liquid and solid phases remain mixed, even if the flow fields predicted by the two models present some differences, the essential features of the interaction with the obstacles, along with the maximum impact force, are comparable.

Assessment of possible impacts of climate change on the hydrological regimes of different regions in China

The aim of this work is to investigate the soil water budget across China by means of hydrological modeling under current and future climate conditions and to evaluate the sensitivity to soil parameters. For this purpose, observed precipitation and temperature data(1981-2010) and climate simulations(2021-2050, 2071-2100) at high resolution(about 14 km) on a large part of China are used as weather forcing. The simulated weather forcing has been bias corrected by means of the distribution derived quantile mapping method to eliminate the effects of systematic biases in current climate modeling on water cycle components. As hydrological models, two 1D models are tested: TERRA-ML and HELP. Concerning soil properties, two datasets, provided respectively by Food and Agriculture Organization and U.S. Department of Agriculture, are separately tested. The combination of two hydrological models, two soil parameter datasets and three weather forcing inputs(observations, raw and bias corrected climate simulations) results in ?ve different simulation chains.The study highlights how the choice of some approaches or soil parameterizations can affect the results both in absolute and in relative terms and how these differences could be highly related to weather forcing in inputs or investigated soil. The analyses point out a decrease in average water content in the shallower part of the soil with different extents according to climate zone, concentration scenario and soil/cover features.Moreover, the projected increase in temperature and then in evapotranspirative demand do not ever result in higher actual evapotranspiration values, due to the concurrent variations in precipitation patterns.

An <i>in Vitro</i>Evaluation of Pressure Generated by Programmed Intermittent Epidural Bolus (PIEB) or Continuous Epidural Infusion (CEI)

PIEB has been reported as being superior to CEI for labor analgesia. The aim of this study was to measure the pressures generated by two commercially available pumps (CADD PIB, Smiths and Gemstar, Hospira) when delivering PIEB or CEI at 2 commonly used rates of infusion (10 or 5 mL). The two pumps were set to deliver fluid at four rates (CEI: 5 or 10 mL/h;PIEB: 5 or 10 mL every h) and connected to a pressure transducer (PCB Piezotronics 1500 connected to a NI USB-6251 Screw Terminal) to determine the pressures applied during each infusion. The peak pressure generated during the PIEB mode was consistently higher when compared to the CEI mode in both pumps. When comparing the two pumps in the PIEB 10 mL every hour mode, the peak pressures were approximately the same, while the pressure pattern differed. For each cycle the pressure generated by Gemstar oscillated from 25 mmHg to 0 mmHg;whereas with the CADD pump the baseline pressure was above 0. The Gemstar pump piston frequency (1.2 Hz) was twice as high as the CADD (0.5 Hz), so the volume delivered per cycle was lower. In the PIEB 5 mL every hour mode the peak pressures followed the same wave patterns. However, unlike the 10 mL mode, the pump piston frequency was approximately the same in both pumps. In both the CEI 5 or 10 mL/h modes, the CADD peak pressure was four times greater than the Gemstar. Both cycled between their respective peak pressures and 0 mmHg. Since the peak pressure of the CADD was approximately the same with PIEB and CEI, we speculated that the most important factor affecting the distribution of the solution in the epidural space was not the peak pressure per se, but the mode of delivery of the bolus.

Seawater Intrusion and Salinization Processes Assessment in a Multistrata Coastal Aquifer in Italy

This paper presents the results of the investigations, driven by different techniques, including environmental tracers and geophysical methods, in the aim of better understand the causes of the current salt-water intrusion in the Pontina Plain, in the south of the Lazio Region (Italy). In the last 50 years many investigation campaigns have been carried out to evaluate the evolution of salt-water intrusion. This is an area with a strong man-made residential and tourist impact and, in the some cases, it is characterized by intensive agricultural practices. Therefore, it can be affected not only by salt-water intrusion, but by the salinization of its groundwater also due to other factors. All these factors have led the Pontina Plain to a groundwater situation which makes the groundwater resource management and the planning of their future exploitation very difficult.

Experiments on two-phase flow in hydraulic jump on pebbled rough bed:Part 1–Turbulence properties and particle chord time and length

This study reported and discussed turbulence characteristics,such as turbulence intensity,correlation time scales,and advective length scales.The characteristic air–water time scale,including the particle chord time and length and their probability density functions(PDFs),was investigated.The results demonstrated that turbulence intensity was relatively greater on a rough bed in the roller length,whereas further downstream,the decay rate was higher.In addition,the relationship between turbulence intensity and dimensionless bubble count rate reflected an increase in turbulence intensity associated with the number of entrained particles.Triple decomposition analysis(TDA)was performed to determine the contributions of slow and fast turbulent components.The TDA results indicated that,regardless of bed type and inflow conditions,the sum of the band-pass(T'_(u))and high-pass(T″_(u))filtered turbulence intensities was equal to the turbulence intensity of the raw signal data(T_(u)).T″_(u) highlighted a higher turbulence intensity and larger vorticities on the rough bed for an identical inflow Froude number.Additional TDA results were presented in terms of the interfacial velocity,auto-and cross-correlation time scales,and longitudinal advection length scale,with the effects of low-and high-frequency signal components on each highlighted parameter.The analysis of the air chord time indicated an increase in the proportion of small bubbles moving downstream.The second part of this research focused on the basic properties of particle grouping and clustering.

Experiments on two-phase flow in hydraulic jump on pebbled rough bed:Part 2–Bubble clustering

A survey on bubble clustering in air–water flow processes may provide significant insights into turbulent two-phaseflow.These processes have been studied in plunging jets,dropshafts,and hydraulic jumps on a smooth bed.As a first attempt,this study examined the bubble clustering process in hydraulic jumps on a pebbled rough bed using experimental data for 1.70<Fr_(1)<2.84(with Fr_(1) denoting the inflow Froude number).The basic properties of particle grouping and clustering,including the number of clusters,the dimensionless number of clusters per second,the percentage of clustered bubbles,and the number of bubbles per cluster,were analyzed based on two criteria.For both criteria,the maximum cluster count rate was greater on the rough bed than on the smooth bed,suggesting greater interactions between turbulence and bubbly flow on the rough bed.The results were consistent with the longitudinal distribution of the interfacial velocity using one of the criteria.In addition,the clustering process was analyzed using a different approach:the interparticle arrival time of bubbles.The comparison showed that the bubbly flow structure had a greater density of bubbles per unitflux on the rough bed than on the smooth bed.Bed roughness was the dominant parameter close to the jump toe.Further downstream,Fr_(1) predominated.Thus,the rate of bubble density decreased more rapidly for the hydraulic jump with the lowest Fr_(1).

Development of an Expert Model to Assess Falls from Height Hazards in Construction Sites

This paper reports on the current state of an ongoing research project which is aimed at implementing intelligent models for hardly predictable hazard scenarios identification in construction sites. As any programmatic actions cannot deal with the unpredictable nature of many risk dynamics, an attempt to improve the current approach for safety management in the construction industry will be presented in this paper. To this aim, the features offered by Bayesian networks have been exploited. The present research has led to the definition of a probabilistic model using elicitation techniques from subjective knowledge. This model, which might be meant as a reliable knowledge map about accident dynamics, showed that a relevant part of occurrences fall in the ＂hardly predictable hazards＂ category, which cannot be warded off by programmatic safety measures. Hence, more effort turned out to be needed in order to manage those hardly predictable hazardous scenarios. Consequently, further developments of this research project will focus on a real time monitoring system for the identification of unpredictable hazardous events in construction.

An efficient improved Gradient Boosting for strain prediction in Near-Surface Mounted fiber-reinforced polymer strengthened reinforced concrete beam

The Near-Surface Mounted(NSM)strengthening technique has emerged as a promising alternative to traditional strengthening methods in recent years.Over the past two decades,researchers have extensively studied its potential,advantages,and applications,as well as related parameters,aiming at optimization of construction systems.However,there is still a need to explore further,both from a static perspective,which involves accounting for the nonconservation of the contact section resulting from the bond-slip effect between fiber-reinforced polymer(FRP)rods and resin and is typically neglected by existing analytical models,as well as from a dynamic standpoint,which involves studying the trends of vibration frequencies to understand the effects of various forms of damage and the efficiency of reinforcement.To address this gap in knowledge,this research involves static and dynamic tests on simply supported reinforced concrete(RC)beams using rods of NSM carbon fiber reinforced polymer(CFRP)and glass fiber reinforced polymer(GFRP).The main objective is to examine the effects of various strengthening methods.This research conducts bending tests with loading cycles until failure,and it helps to define the behavior of beam specimens under various damage degrees,including concrete cracking.Dynamic analysis by free vibration testing enables tracking of the effectiveness of the reinforcement at various damage levels at each stage of the loading process.In addition,application of Particle Swarm Optimization(PSO)and Genetic Algorithm(GA)is proposed to optimize Gradient Boosting(GB)training performance for concrete strain prediction in NSM-FRP RC.The GB using Particle Swarm Optimization(GBPSO)and GB using Genetic Algorithm(GBGA)systems were trained using an experimental data set,where the input data was a static applied load and the output data was the consequent strain.Hybrid models of GBPSO and GBGA have been shown to provide highly accurate results for predicting strain.These models combine the strengths of both optimization techniques to create a powerful and efficient predictive tool.

A review of top-down cracking in asphalt pavements:Causes, models, experimental tools and future challenges

In the last decades,a new type of distress has been observed more and more frequently on asphalt pavements.This distress,ascribable to fatigue failure,has been named top-down cracking(TDC) because it consists in longitudinal cracks that initiate on the pavement surface and then propagate downwards.A series of surveys recently carried out on Italian motorways highlighted that TDC can affect up to 20%-30% of the slow traffic lane.Therefore,in order to achieve a better understanding of such distress,this paper reviews causes,models and experimental tools and highlights future challenges for TDC.The literature review indicates that TDC can evolve on the pavement surface in three stages(i.e.,single crack,sister cracks,alligator cracking) and,below a certain depth,the cracks can form angles of 20°-40° with respect to the vertical plane.Even though multiple factors contribute to TDC development,thick pavements are more likely to fail due to TDC induced by tire-pavement contact stresses,especially in the presence of open-graded friction courses(OGFCs).Moreover,in literature there are several TDC models based on mechanics(e.g.,fracture mechanics or continuum damage mechanics) which allow a rigorous study of crack initiation and propagation.Future challenges include the identification of a reliable and feasible test method,among those proposed in literature,to study the TDC performance of asphalt mixtures and the implementation of TDC in pavement management systems(PMSs) through the definition of criteria for TDC recognition in the field as well as for the rehabilitation depth evaluation.Finally,more research is needed for open-graded asphalt mixtures,which present critical drawbacks in terms of TDC.

Framework based on building information modeling, mixed reality, and a cloud platform to support information flow in facility management

The quality of information flow management has a remarkable effect on the entire life cycle of buildings.Manual retrieval of technical specifications and features of building components and their performance assessment leads to increased cost and time and efficiency reduction,especially during the facility management(FM)stage.The introduction of building information modeling(BIM)in the construction industry can provide a valuable means of improving the organization and exchange of information.BIM tools integrate multiple levels of information within a single digital model of a building.Nevertheless,the support given by BIM to FM is far from being fully effective.Technicians can benefit from real-time communication with the data repository whenever the need for gathering contextual information and/or updating any data in the digital model arises.The framework proposed in this study aims to develop a system that supports on-site operations.Information requirements have been determined from the analyses of procedures that are usually implemented in the building life cycle.These studies set the standard for the development of a digital model of a building,which will be shared among various actors in charge of FM and accessed via a cloud platform.Moreover,mixed reality is proposed to support specific information that is relevant to geometric features and procedures to be followed by operators.This article presents three use-cases supported by the proposed framework.In addition,this research article describes the first proof of concept regarding real-time support for FM.

Horizontal accuracy assessment of very high resolution Google Earth images in the city of Rome,Italy

Google Earth(GE)has recently become the focus of increasing interest and popularity among available online virtual globes used in scientific research projects,due to the free and easily accessed satellite imagery provided with global coverage.Nevertheless,the uses of this service raises several research questions on the quality and uncertainty of spatial data(e.g.positional accuracy,precision,consistency),with implications for potential uses like data collection and validation.This paper aims to analyze the horizontal accuracy of very high resolution(VHR)GE images in the city of Rome(Italy)for the years 2007,2011,and 2013.The evaluation was conducted by using both Global Positioning System ground truth data and cadastral photogrammetric vertex as independent check points.The validation process includes the comparison of histograms,graph plots,tests of normality,azimuthal direction errors,and the calculation of standard statistical parameters.The results show that GE VHR imageries of Rome have an overall positional accuracy close to 1 m,sufficient for deriving ground truth samples,measurements,and large-scale planimetric maps.

Vibration-based crack prediction on a beam model using hybrid butterfly optimization algorithm with artificial neural network

Vibration-based damage detection methods have become widely used because of their advantages over traditional methods.This paper presents a new approach to identify the crack depth in steel beam structures based on vibration analysis using the Finite Element Method(FEM)and Artificial Neural Network(ANN)combined with Butterfly Optimization Algorithm(BOA).ANN is quite successful in such identification issues,but it has some limitations,such as reduction of error after system training is complete,which means the output does not provide optimal results.This paper improves ANN training after introducing BOA as a hybrid model(BOA-ANN).Natural frequencies are used as input parameters and crack depth as output.The data are collected from improved FEM using simulation tools(ABAQUS)based on different crack depths and locations as the first stage.Next,data are collected from experimental analysis of cracked beams based on different crack depths and locations to test the reliability of the presented technique.The proposed approach,compared to other methods,can predict crack depth with improved accuracy.

Integrating VGI and 2D hydraulic models into a data assimilation framework for real time flood forecasting and mapping

Crowdsourced data can effectively observe environmental and urban ecosystem processes.The use of data produced by untrained people into flood forecasting models may effectively allow Early Warning Systems(EWS)to better perform while support decision-making to reduce the fatalities and economic losses due to inundation hazard.In this work,we develop a Data Assimilation(DA)method integrating Volunteered Geographic Information(VGI)and a 2D hydraulic model and we test its performances.The proposed framework seeks to extend the capabilities and performances of standard DA works,based on the use of traditional in situ sensors,by assimilating VGI while managing and taking into account the uncertainties related to the quality,and the location and timing of the entire set of observational data.The November 2012 flood in the Italian Tiber River basin was selected as the case study.Results show improvements of the model in terms of uncertainty with a significant persistence of the model updating after the integration of the VGI,even in the case of use of few-selected observations gathered from social media.This will encourage further research in the use of VGI for EWS considering the exponential increase of quality and quantity of smartphone and social media user worldwide.

A semi-empirical model for top-down cracking depth evolution in thick asphalt pavements with open-graded friction courses

Thick asphalt pavements with open-graded friction course(OGFC) are exposed to topdown cracking(TDC), a distress consisting of longitudinal cracks that initiate on the pavement surface close to the wheel path and propagate downwards. The main objective of this study is to develop a semi-empirical model for the prediction of TDC depth evolution for such pavements. For this purpose, a series of cores were taken from different Italian motorway pavements affected by TDC and analyzed in the laboratory. Cracked cores taken from the wheel path area were analyzed to determine TDC depth, whereas intact cores taken from the middle of the lane(not affected by traffic loadings) were tested to obtain the volumetric and mechanical properties of the OGFC mixture. The proposed model, developed on the basis of the results already available in literature and on the findings of the laboratory investigation, predicts the evolution of TDC depth as a function of the applied traffic loadings(in terms of 12-ton fatigue equivalent single axle loads, i.e., ESALs). The model is sigmoidal with a maximum TDC depth assumed equal to 150 mm. The shape parameter of the sigmoidal function depends on the indirect tensile strength(ITS) of the OGFC mixtures(which takes into account indirectly also the volumetrics and stiffness of the OGFC), whereas the evolutive translation factor depends on the age of the OGFC mixture. After excluding some outliers, the model was able to predict the measured TDC depth very well. Moreover, in-situ observations allowed a preliminary validation of the proposed model. This model can be used in pavement management systems(PMSs) to plan surface repairs due to TDC in a timely manner, thus minimizing pavement damage and maintenance costs.

Development of a BIM-based holonic system for real-time monitoring of building operational efficiency

In the wide context of facility management,several processes,such as operations,maintenance,retrofitting,and renovations,ensure that buildings comply with the principles of efficiency,cost-effectiveness,and indoor comfort.Apart from ordinary operation,facility management is responsible for the renovation of and long-term performance improvement of building facilities.In such a scenario,the cyber–physical system(CPS)paradigm with holonic architecture,which is the focus of this study,can successfully guide the operation management and long-term refurbishment processes of buildings.Analogous to the manufacturing field,the developed CPS maximizes holons’self-configuration and self-organization and overall throughput effectiveness metrics to detect the best corrective actions toward system improvements.Consequently,suggestions and lessons learned from the evaluation of building efficiency are redirected to the building information model.Hence,the digital model acts as a repository of currently available equipment for operations management and the history of diagnoses that support decision-making during the maintenance,retrofitting,and renovation processes.Evidently,the repeated detection of a specific issue,which is unaffected by operations management,should be considered an opportunity to act and enhance the performances of existing building components.Similar to a goods-producing industry,the building management system developed in this study applies the aforementioned methodology to provide services related to indoor comfort and building health.This approach indicates that a method for automatic real-time diagnosis is tested in a case study consisting of a multi-use and large public building.The current paper,which is an extended version of the one presented in the Creative Construction Conference 2018,deepens the decision support tool and the supervision policy.Moreover,the developed system is contextualized by providing an example of use case and highlighting the step forward in the field of smart buildings.

Chemical,morphological and rheological characterization of bitumen partially replaced with wood bio-oil:Towards more sustainable materials in road pavements

Nowadays,sustainability and circular economy are two principles to be pursued in all fields.In road pavement engineering,they can be put into practice through the partial substitution of bitumen with industrial residues and by-products deriving from renewable materials.Within this framework,this paper presents an extensive investigation of the chemical,morphological and rheological properties of bio-binders obtained by mixing a conventional 50/70 bitumen with different percentages by weight(0,5%,10%and 15%)of a renewable bio-oil,generated as a residue in the processing of wood into pulp and paper.Results show that overall the bio-oil provides a softening effect,which,in terms of performance,leads to an improvement of the low-temperature behaviour and fatigue resistance with respect to the control bitumen,in spite of an increased tendency to permanent deformation.Although no chemical reaction appears to occur after blending,the peculiarities of the bio-oil affect the chemistry of the resulting bio-binders,whereas no phase separation is observed from the microscopic analysis.In addition,a Newtonian behaviour,an unchanged temperature susceptibility and a good fitting of 1 S2 P1 D model to the rheological data are found,regardless of the bio-oil percentage considered.These promising outcomes suggest that such bio-binders can be favourably employed for several applications in road pavements.