Dynamic Reliability Assessment of Heavy Vehicle Crossing a Prototype Bridge Deck by Using Simulation Technology and Health Monitoring Data

Overloads of vehicle may cause damage to bridge structures, and how to assess the safety influence of heavy vehicles crossing the prototype bridge is one of the challenges. In this report, using a large amount of monitored data collected from the structural health monitoring system (SHMS) in service of the prototype bridge, of which the bridge type is large-span continuous rigid frame bridge, and adopting FEM simulation technique, we suggested a dynamic reliability assessment method in the report to assess the safety impact of heavy vehicles on the prototype bridge during operation. In the first place, by using the health monitored strain data, of which the selected monitored data time range is before the opening of traffic, the quasi dynamic reliability around the embedded sensor with no traffic load effects is obtained; then, with FEM technology, the FEM simulation model of one main span of the prototype bridge is built by using ANSYS software and then the dynamic reliability when the heavy vehicles crossing the prototype bridge corresponding to the middle-span web plate is comprehensively analyzed and discussed. At last, assuming that the main beam stress state change is in the stage of approximately linear elasticity under heavy vehicle loads impact, the authors got the impact level of heavy vehicles effects on the dynamic reliability of the prototype bridge. Based on a large number of field measured data, the dynamic reliability value calculated by our proposed methodology is more accurate. The method suggested in the paper can do good for not only the traffic management but also the damage analysis of bridges

Chance-constrained optimal dispatch of integrated electricity and natural gas systems considering medium and long-term electricity transactions

A novel stochastic optimal dispatch model considering medium and long-term electricity transaction for a wind power integrated energy system by using chance constrained programming is proposed. The electricity contract decomposition problem is introduced into the day-ahead optimal dispatch plan formulation progress. Considering the case that decomposition results may be not executable in the dispatch plan, a coordinated optimization strategy based on Lagrange multiplier is proposed to locate the infeasible factors and eliminate the non executable electric quantity. At the same time, the uncertainties and correlation of wind power are considered in the dispatch model, and the original stochastic dispatch problem is transformed into a mixed integer second-order cone programming problem based on second-order cone relaxation and deterministic transformation of chance constraints. Case study results demonstrate the validity of the proposed metho

An adaptive forecasting method for the aggregated load with pattern matching

Electrical load forecasting plays a vital role in the operation of power system. In this paper, a novel adaptive short-term load forecasting method for the aggregated load is built. The proposed method consists of two stages: load forecast model preparation stage and adaptive load forecast model selection stage. In the first stage, based on historical load data of all consumers, the typical monthly load patterns are firstly identified in an optimal fashion with the aid of the cosine similarity. Then, for each identified monthly load pattern, a stacking ensemble learning method is proposed to train the load forecasting model. In the second stage, according to the similarity between individual load data of the latest month and the identified monthly load pattern, all the consumers are firstly classified into different groups where each group corresponds to a particular load pattern. Then, for each group, the corresponding trained load forecasting model is employed for short-term load forecast and the final forecast of the aggregated load is calculated as a simple aggregation of the produced load forecast for each group of consumers. Case studies conducted on open dataset show that, compared with the single forecasting model, the proposed adaptive load forecasting method can effectively improve the load forecasting accuracy

Elucidating the molecular programming of a nonlinear non-ribosomal peptide synthetase responsible for fungal siderophore biosynthesis

Siderophores belonging to the ferrichrome family are essential for the viability of fungal species and play a key role for virulence of numerous pathogenic fungi. Despite their biological significance, our understanding of how these iron-chelating cyclic hexapeptides are assembled by non-ribosomal peptide synthetase (NRPS) enzymes remains poorly understood, primarily due to the nonlinearity exhibited by the domain architecture. Herein, we report the biochemical characterization of the SidC NRPS, responsible for construction of the intracellular siderophore ferricrocin. In vitro reconstitution of purified SidC reveals its ability to produce ferricrocin and its structural variant, ferrichrome. Application of intact protein mass spectrometry uncovers several non-canonical events during peptidyl siderophore biosynthesis, including inter-modular loading of amino acid substrates and an adenylation domain capable of poly-amide bond formation. This work expands the scope of NRPS programming, allows biosynthetic assignment of ferrichrome NRPSs, and sets the stage for reprogramming towards novel hydroxamate scaffolds

Research of Wireless Congestion Control Algorithm Based on EKF

The random variation of bandwidth in wireless networks causes some significant challenges to the congestion control protocols based on bandwidth estimation. In this paper, a wireless congestion control scheme based on extended Kalman filtering and bandwidth (CSEKB) is proposed. The CSEKB can effectively perceive the bandwidth oscillation of wireless networks and distinguish the type of packet loss by establishing a noise perception factor. According to the congestion factor, the congestion control parameters are adjusted to correspondingly improve the performance of the wireless network. Moreover, the variation trend of the size of the congestion window presents a law of similar normal distribution curve, which has a certain degree of local symmetry. The CSEKB was implemented in Network simulator 3 (NS3) and compared with TCP Westwood (TCPW), CUBIC, and extended Kalman filtering-based bandwidth estimation (EBE). Through extensive simulation studies, the proposed CSEKB demonstrated the significant performance in wireless networks. First, the CSEKB can achieve congestion control based on the accurate prediction of available bandwidth, and improve average throughput and link utilization. In addition, the CSEKB has good fairness and friendliness compared with several other well-known congestion control methods