The power market is a typical imperfectly competitive market where power suppliers gain higher profits through strategic bidding behaviors.Most existing studies assume that a power supplier is accessible to the suffic...The power market is a typical imperfectly competitive market where power suppliers gain higher profits through strategic bidding behaviors.Most existing studies assume that a power supplier is accessible to the sufficient market information to derive an optimal bidding strategy.However,this assumption may not be true in reality,particularly when a power market is newly launched.To help power suppliers bid with the limited information,a modified continuous action reinforcement learning automata algorithm is proposed.This algorithm introduces the discretization and Dyna structure into continuous action reinforcement learning automata algorithm for easy implementation in a repeated game.Simulation results verify the effectiveness of the proposed learning algorithm.展开更多
In the recent past,the potential benefits of wraparound geosynthetic reinforcement technique for constructing the reinforced soil foundations have been reported.This paper presents the experimental study on the behavi...In the recent past,the potential benefits of wraparound geosynthetic reinforcement technique for constructing the reinforced soil foundations have been reported.This paper presents the experimental study on the behaviour of model strip footing resting on sandy soil bed reinforced with geosynthetic in wraparound and planar forms under monotonic and repeated loadings.The geosynthetic layers were laid according to the reinforcement ratio to minimise the scale effect.It is found that for the same amount of reinforcement material,the wraparound reinforced model resulted in less settlement in comparison to planar reinforced models.The efficiency of wraparound reinforced model increased with the increase in load amplitude and the rate of total cumulative settlement substantially decreased with the increase in number of load cycles.The wraparound reinforced model has shown about 45% lower average total settlement in comparison to unreinforced model,while the double-layer reinforced model has about 41% lower average total settlement at the cost of approximately twice the material and 1.5 times the occupied land width ratio.Moreover,wraparound models have shown much greater stability in comparison to their counterpart models when subjected to incremental repeated loading.展开更多
A series of dynamic model tests that were performed on a geogrid-reinforced square footing are presented.The dynamic(sinusoidal)loading was applied using a mechanical testing and simulation(MTS)electro-hydraulic servo...A series of dynamic model tests that were performed on a geogrid-reinforced square footing are presented.The dynamic(sinusoidal)loading was applied using a mechanical testing and simulation(MTS)electro-hydraulic servo loading system.In all the tests,the amplitude of loading was±160 kPa;the frequency of loading was 2 Hz.To better ascertain the effect of reinforcement,an unreinforced square footing was first tested.This was followed by a series of tests,each with a single layer of reinforcement.The reinforcement was placed at depths of 0.3B,0.6B and 0.9B,where B is the width of footing.The optimal depth of reinforcement was found to be 0.6B.The effect of adopting this value versus the other two depths was quantified.The single layer of geogrid had an effective reinforcement depth of 1.7B below the footing base.The increase of the depth between the topmost geogrid layer and the bottom of the footing(within the range of 0.9B)did not change the failure mode of the foundation.展开更多
基金This work was supported by the National Natural Science Foundation of China(No.U1866206).
文摘The power market is a typical imperfectly competitive market where power suppliers gain higher profits through strategic bidding behaviors.Most existing studies assume that a power supplier is accessible to the sufficient market information to derive an optimal bidding strategy.However,this assumption may not be true in reality,particularly when a power market is newly launched.To help power suppliers bid with the limited information,a modified continuous action reinforcement learning automata algorithm is proposed.This algorithm introduces the discretization and Dyna structure into continuous action reinforcement learning automata algorithm for easy implementation in a repeated game.Simulation results verify the effectiveness of the proposed learning algorithm.
基金funded by the Higher Education Commission(HEC),Government of the Islamic Republic of Pakistan and Edith Cowan University,Perth,Australia。
文摘In the recent past,the potential benefits of wraparound geosynthetic reinforcement technique for constructing the reinforced soil foundations have been reported.This paper presents the experimental study on the behaviour of model strip footing resting on sandy soil bed reinforced with geosynthetic in wraparound and planar forms under monotonic and repeated loadings.The geosynthetic layers were laid according to the reinforcement ratio to minimise the scale effect.It is found that for the same amount of reinforcement material,the wraparound reinforced model resulted in less settlement in comparison to planar reinforced models.The efficiency of wraparound reinforced model increased with the increase in load amplitude and the rate of total cumulative settlement substantially decreased with the increase in number of load cycles.The wraparound reinforced model has shown about 45% lower average total settlement in comparison to unreinforced model,while the double-layer reinforced model has about 41% lower average total settlement at the cost of approximately twice the material and 1.5 times the occupied land width ratio.Moreover,wraparound models have shown much greater stability in comparison to their counterpart models when subjected to incremental repeated loading.
基金Projects(41962017,51469005)supported by the National Natural Science Foundation of ChinaProject(2017GXNSFAA198170)supported by the Natural Science Foundation in Guangxi Province,China+1 种基金Project supported by the Guangxi University of Science and Technology Innovation Team Support Plan,ChinaProject supported by the High Level Innovation Team and Outstanding Scholars Program of Guangxi Institutions of Higher Learning,China。
文摘A series of dynamic model tests that were performed on a geogrid-reinforced square footing are presented.The dynamic(sinusoidal)loading was applied using a mechanical testing and simulation(MTS)electro-hydraulic servo loading system.In all the tests,the amplitude of loading was±160 kPa;the frequency of loading was 2 Hz.To better ascertain the effect of reinforcement,an unreinforced square footing was first tested.This was followed by a series of tests,each with a single layer of reinforcement.The reinforcement was placed at depths of 0.3B,0.6B and 0.9B,where B is the width of footing.The optimal depth of reinforcement was found to be 0.6B.The effect of adopting this value versus the other two depths was quantified.The single layer of geogrid had an effective reinforcement depth of 1.7B below the footing base.The increase of the depth between the topmost geogrid layer and the bottom of the footing(within the range of 0.9B)did not change the failure mode of the foundation.
