Target reliability index for serviceability limit state of single piles

The objective is to develop an approach for the determination of the target reliability index for serviceability limit state(SLS) of single piles. This contributes to conducting the SLS reliability-based design(RBD) of piles. Based on a two-parameter,hyperbolic curve-fitting equation describing the load-settlement relation of piles, the SLS model factor is defined. Then, taking into account the uncertainties of load-settlement model, load and bearing capacity of piles, the formula for computing the SLS reliability index(βsls) is obtained using the mean value first order second moment(MVFOSM) method. Meanwhile, the limit state function for conducting the SLS reliability analysis by the Monte Carlo simulation(MCS) method is established. These two methods are finally applied to determine the SLS target reliability index. Herein, the limiting tolerable settlement(slt) is treated as a random variable. For illustration, four load test databases from South Africa are compiled again to conduct reliability analysis and present the recommended target reliability indices. The results indicate that the MVFOSM method overestimates βsls compared to that computed by the MCS method. Besides, both factor of safety(FS) and slt are key factors influencing βsls, so the combination of FS and βsls is welcome to be used for the SLS reliability analysis of piles when slt is determined. For smaller slt, pile types and soils conditions have significant influence on the SLS target reliability indices; for larger slt, slt is the major factor having influence on the SLS target reliability indices. This proves that slt is the most key parameter for the determination of the SLS target reliability index.

Experimental Study on Flexural Behavior of Post-Tensioning Bonded Partially Prestressed Ultra-High Strength Concrete Beams

This paper presents the results of four partially prestressed ultra-high strength concrete beams in flexure. The test results are used to evaluate the effects of prestressing tendon depth and area on flexure behavior of specimen beams. The test results indicate that: the cracking load,yielding load,peak load and stiffness postcracking of specimen beams are enhanced by reducing prestressing tendon depth or increasing prestressing tendon area, and the flexural ductility is improved by increasing prestressing tendon depth or reducing prestressing tendon area. The effect of complex reinforcement index considering the strength of the equivalence principle and the reinforcement position on loading levels under serviceability limit state,flexural strength and displacement ductility factor are studied. The influence coefficient of prestressing tendon kpis introduced in the complex reinforcement index. As the complex reinforcement index increases, the loading levels under serviceability limit state and flexural strength increases linearly,and the displacement ductility factor decreases linearly. The test results also verify the conventional beam flexural theory based on the plane cross-section assumption for predicting ultimate flexural strength of partially prestressed ultra-high strength concrete beams is valid. After the introduction of the coefficient kp,the calculation method of cracks in code for design of concrete structure in china are appropriated for the specimen beams.

Degradation process assessment of prestressed concrete continuous bridges in life-cycle

To accurately evaluate the degradation process of prestressed concrete continuous bridges exposed to aggressive environments in life-cycle,a finite element-based approach with respect to the lifetime performance assessment of concrete bridges was proposed.The existing assessment methods were firstly introduced and compared.Some essential mechanics problems involved in the degradation process,such as the deterioration of materials properties,the reduction of sectional areas and the variation of overall structural performance caused by the first two problems,were investigated and solved.A computer program named CBDAS(Concrete Bridge Durability Analysis System) was written to perform the above-metioned approach.Finally,the degradation process of a prestressed concrete continuous bridge under chloride penetration was discussed.The results show that the concrete normal stress for serviceability limit state exceeds the threshold value after 60 a,but the various performance indicators at ultimate limit state are consistently in the allowable level during service life.Therefore,in the case of prestressed concrete bridges,the serviceability limit state is more possible to have durability problems in life-cycle;however,the performance indicators at ultimate limit state can satisfy the requirements.

Lifetime Reliability Analysis of Flexural Cracking for Prestressed Concrete Bridge

Time-dependant reliability is analyzed for the flexural cracking of prestressed concrete bridges under service limit state. The limit state function and random variables are derived from Chinese highway bridge design specifications. For deterioration of structural performances, chloride-induced reinforcement corrosion is emphasized. Through integrating first order reliability method （FORM） and time discretized approach, the time-variant reliability is evaluated. For illustrative propose, the reliability of a typical simply supported prestressed concrete beam is exemplified.

Risk of Flash Floods in Urban and Rural Municipalities Triggered by Intense Precipitation in Wielkopolska of Poland

This research analyzed interventions of State Fire Service(SFS)units in the Wielkopolska region of Poland that were triggered by extreme precipitation for the period 2010-2021.Our results demonstrated that the most populated and urbanized towns in the Wielkopolska(Greater Poland,west of Warsaw)region are at the most risk in the event of extreme precipitation occurrence as measured by the total number of interventions made by the SFS.The number of SFS unit interventions in towns,standardized to 10,000 inhabitants,indicates that the highest proportional volume of interventions also occurred in smaller towns.In the rural municipalities the number of SFS unit interventions increases along with higher population density and proportion of infrastructure areas.As analyzed in this study,the 12 years from 2010 to 2021 were characterized by a higher number of days with heavy precipitation,for example,20,30,40,and 50 mm,in comparison to the previous periods 1961-2010 and 1981-2010.Intervention databases collected by emergency services are a valuable source of information for hazard mapping.Based on those and other available data,a statistical model was created and factors influencing the local and regional occurrence of interventions were determined.Increasing suburbanization,the rising proportion of impermeable surfaces,and the impact of climate change are of considerable importance in urban flood risk.It is necessary to help municipalities develop abilities to absorb larger amounts of rainwater.

HWM： a hybrid workload migration mechanism of metadata server cluster in data center

In data center, applications of big data analytics pose a big challenge to massive storage systems. It is signif- icant to achieve high availability, high performance and high scalability for PB-scale or EB-scale storage systems. Meta- data server （MDS） cluster architecture is one of the most effective solutions to meet the requirements of applications in data center. Workload migration can achieve load balance and energy saving of duster systems. In this paper, a hybrid workload migration mechanism of MDS cluster is proposed and named as HWM. In HWM, workload of MDS is classi- fied into two categories： metadata service and state service, and they can be migrated rapidly from a source MDS to a target MDS in different ways. Firstly, in metadata service migration, all the dirty metadata of one sub file system is flushed to a shared storage pool by the source MDS, and then is loaded by the target MDS. Secondly, in state service mi- gration, all the states of that sub file system are migrated from source MDS to target MDS through network at file granular- ity, and then all of the related structures of these states are reconstructed in target MDS. Thirdly, in the process of work- load migration, instead of blocking client requests, the source MDS can decide which MDS will respond to each request according to the operation type and the migration stage. The proposed mechanism is implemented in the Blue Whale MDS cluster. The performance measurements show that the HWM mechanism is efficient to migrate the workload of a MDS cluster system and provides low-latency access to metadata and states.

Forecasting soil temperature at multiple-depth with a hybrid artificial neural network model coupledhybrid firefly optimizer algorithm

Forecasting soil temperature at multiple depths is considered to be a core decision-making task for examining future changes in surface and sub-surface meteorological processes,land-atmosphere energy exchange,resilient agricultural systems for improved crop health and eco-environmental risk assessment.The aim of this paper is to estimate monthly soil temperature(ST)at multiple depth:5,10,20,50 and 100 cm with a hybrid multi-layer perceptron algorithm integrated with the firefly optimizer algorithm(MLP-FFA).To develop the hybrid MLP-FFA model,the monthly ST and relevant meteorological variables for the city of Adana(Turkey)are collated for the period of 2000–2007.Construction of hybrid MLP-FFA model is drawn upon a limited set of predictors,denoted as soil depth,periodicity(or the respective month),air temperature,pressure and solar radiation,while the objective variable for MLP-FFA model is the forecasted ST at multiple depths.To the evaluate MLPFFA,statistical metrics applied to test the model’s performance are:the root mean square error(RMSE),mean absolute error(MAE),mean absolute percentage error(MAPE)and mean bias error(MBE)where the sign of the difference is also considered.In conjunction with statistical metrics,a Taylor diagram is utilized to visualize the degree of similarity between the observed and forecasted soil moisture.In terms of the forecasted results,the hybrid MLPFFA model is seen to outperform the standalone MLP model.The optimal MLP-FFA is attained for soil temperature forecasting at a depth of 20 cm(RMSE,MAPE of 0.546
C,2.40%)whereas the optimal MLP is attained for soil temperature forecasting at a depth of 50 cm(RMSE of 0.544℃,2.21%).Conclusively,the study advocates through statistical metrics attained the better utility of the hybrid MLP-FFA hybrid model.Given its superior performance,it is ascertained that the hybrid MLP model integrated with Firefly optimizer is a qualified ancillary tool that can be applied to generate precise soil temperature forecasts at multiple soil depths.