Fatigue Life Evaluation of Concrete Bridge Deck Slabs Reinforced with Glass FRP Composite Bars

Since bridge deck slabs directly sustain repeated moving wheel loads, they are one of the most bridge elements susceptible to fatigue failure. Recently, glass fiber-reinforced polymer (FRP) composites have been widely used as internal reinforcement for concrete bridge deck slabs as they are less expensive compared to the other kinds of FRPs (carbon and aramid). However, there is still a lack of information on the performance of FRP–reinforced concrete elements subjected to cyclic fatigue loading. This research is designed to investigate the fatigue behavior and fatigue life of concrete bridge deck slabs reinforced with glass FRP bars. A total of five full-scale deck slabs were constructed and tested under concentrated cyclic loading until failure. Different reinforcement types (steel and glass FRP), ratios, and configurations were used. Different schemes of cyclic loading (accelerated variable amplitude fatigue loading) were applied. Results are presented in terms of deflections, strains in concrete and FRP bars, and crack widths at different levels of cyclic loading. The results showed the superior fatigue performance and longer fatigue life of concrete bridge deck slabs reinforced with glass FRP composite bars.     

Data‐driven model for river flood forecasting based on a Bayesian network approach

Uncertainty analysis of hydrological models often requires a large number of model runs, which can be time consuming and computationally intensive. In order to reduce the number of runs required for uncertainty prediction, Bayesian networks (BNs) are used to graphically represent conditional probability dependence between the set of variables characterizing a flood event. Bayesian networks (BNs) are relevant due to their capacity to handle uncertainty, combine statistical data and expertise and introduce evidences in real‐time flood forecasting. In the present study, a runoff–runoff model is considered. The discharge at a gauging station located is estimated at the outlet of a basin catchment based on discharge measurements at the gauging stations upstream. The BN model shows good performances in estimating the discharges at the basin outlet. Another application of the BN model is to be used as a reverse method. Knowing discharges values at the outlet of the basin, we can propagate back these values through the model to estimate discharges at upstream stations. This turns out to be a practical method to fill the missing data in streamflow records which are critical to the sustainable management of water and the development of hydrological models.     

A C5 parallel robot identification and control

The paper proposes a controller scheme based on a priori identification for a C5 parallel robot. First we realize the identification of dynamic parameters of the robot using the Least Squares technique. Different data are used for this step of identification. The cross validation permitted to select and confirm the identified parameters. After, a control scheme (computed torque) is applied to control the C5 parallel robot. The functions of this control scheme are based on precedent identified parameters. In order to reduce the effect of the identification error, we have added a robustness term based on sliding mode technique. The stability of the system in closed loop is presented using the Lyapunov principle. Experimental results of identification and control are presented and show the effectiveness of our methodology.     

A two-phase framework for quality-aware Web service selection

Service-oriented computing is gaining momentum as the next technological tool to leverage the huge investments in Web application development. The expected large number of Web services poses a set of new challenges for efficiently accessing these services. We propose an integrated service query framework that facilitates users in accessing their desired services. The framework incorporates a service query model and a two-phase optimization strategy. The query model defines service communities that are used to organize the large and heterogeneous service space. The service communities allow users to use declarative queries to retrieve their desired services without worrying about the underlying technical details. The two-phase optimization strategy automatically generates feasible service execution plans and selects the plan with the best user-desired quality. In particular, we present an evolutionary algorithm that is able to “co-evolve” multiple feasible execution plans simultaneously and allows them to compete with each other to generate the best plan. We conduct a set of experiments to assess the performance of the proposed algorithms.     

A new scalable multicast routing algorithm for interactive real-time applications

Quality of service (QoS) provisioning generally assumes more than one QoS measure that implies that QoS routing can be categorized as an instance of routing subject to multiple constraints: delay jitter, bandwidth, cost, etc. We study the problem of constructing multicast trees to meet the QoS requirements of real-time interactive applications where it is necessary to provide bounded delays and bounded delay variation among the source and all destinations while keeping overall cost of the multicast tree low. The main contribution of our work is a new strategy for constructing multiconstrained multicast trees. We first derive mathematically a new delay-variation estimation scheme and prove its efficiency. Thereafter, we propose a simple and competitive (in terms of running time) heuristic algorithm, for delay and delay variation constrained routing problem based on the proposed delay-variation estimation scheme and using the Extended Prim-Dijkstra tradeoffs’ algorithm. Our contribution also extends previous works in providing some properties and analyses of delay bounded paths satisfying delay variation constraints. Extensive simulation results show that our algorithm outperforms DVDMR in terms of multicast delay variation with the same time complexity as DVDMR.     

Learning market prices in real-time supply chain management

This paper proposes a model for dynamic pricing that combines knowledge of production capacity and existing commitments, reasoning about uncertainty and learning of market conditions in an attempt to optimise expected profits. In particular, the market conditions are represented as a set of probabilities over the success rate of product prices, and those prices are learned online as the market develops. The dynamic pricing model is integrated into a real-time supply chain management agent using the Trading Agent Competition Supply Chain Management game as a test framework. We evaluate the agent experimentally in competition with other supply chain agents, and demonstrate the benefits of incorporating more market data into the dynamic pricing mechanism.     

Cost-Based Filtering Techniques for Stochastic Inventory Control Under Service Level Constraints

This paper¹ considers a single product and a single stocking location production/inventory control problem given a non-stationary stochastic demand. Under a widely-used control policy for this type of inventory system, the objective is to find the optimal number of replenishments, their timings and their respective order-up-to-levels that meet customer demands to a required service level. We extend a known CP approach for this problem using three cost-based filtering methods. Our approach can solve to optimality instances of realistic size much more efficiently than previous approaches, often with no search effort at all. This work was supported by Science Foundation Ireland under Grant No. 03/CE3/I405 as part of the Centre for Telecommunications Value-Chain-Driven Research (CTVR) and Grant No. 00/PI.1/C075. ¹This paper is an extended version of [19].     

纤维聚合物筋混凝土梁正截面性能的试验研究

进行了 6 2根截面尺寸分别为 130mm× 180mm× 180 0mm、2 0 0mm× 30 0mm× 3 30 0mm、2 0 0mm× 45 0mm× 3 30 0mm和 2 0 0mm× 5 5 0mm× 3 30 0mm的纤维聚合物筋混凝土梁的弯曲试验 ,重点研究了纤维聚合物筋类型、配筋率对梁的裂缝间距、宽度和分布 ,弯曲刚度和挠度、破坏形式和承载能力的影响。     

Kinetic of CO2 absorption and carbamate formation in aqueous solutions of diethanolamine

The absorption rates of CO₂ into aqueous solutions of Diethanolamine (DEA) with varying concentrations from 0.2 to 4M and temperature range from 293 to 323 K were measured by using a laboratory stirred reactor. The CO₂ partial pressure was varied in a range that the reaction would occur in pseudo first order regime. Experimental data were analyzed and the kinetic parameters associated with the reaction were determined. The activation energy for the deprotonation of the intermediate zwitterion was estimated at about 11.4 kcal/mol. The contribution of carbamate formation to the overall absorbed CO₂ was experimentally evaluated and found to be of the order of 100%.