Prediction of blast-induced flyrock in Indian limestone mines using neural networks

Frequency and scale of the blasting events are increasing to boost limestone production. Mines areapproaching close to inhabited areas due to growing population and limited availability of land resourceswhich has challenged the management to go for safe blasts with special reference to opencast mining.The study aims to predict the distance covered by the flyrock induced by blasting using artificial neuralnetwork （ANN） and multi-variate regression analysis （MVRA） for better assessment. Blast design andgeotechnical parameters, such as linear charge concentration, burden, stemming length, specific charge,unconfined compressive strength （UCS）, and rock quality designation （RQD）, have been selected as inputparameters and flyrock distance used as output parameter. ANN has been trained using 95 datasets ofexperimental blasts conducted in 4 opencast limestone mines in India. Thirty datasets have been used fortesting and validation of trained neural network. Flyrock distances have been predicted by ANN, MVRA,as well as further calculated using motion analysis of flyrock projectiles and compared with the observeddata. Back propagation neural network （BPNN） has been proven to be a superior predictive tool whencompared with MVRA. 2014 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting byElsevier B.V. All rights reserved.

Opportunity Cost Model of Infrastructure Access Charges for Chinese Railways

For the suppliers of concerned services, theories about infrastructure pricing： SAT （Stand Alone economists such as Laffont, Tirole, etc. developed Test）, ECPR （Efficient Component Pricing Rule）. Especially, Sidak, Spulber, put forward M-ECPR （Market Efficient Component Pricing Rule） method for bottleneck infrastructures. In this article, we bring the M-ECPR principles into the study of Chinese railways pricing of its network infrastructures. Combined with our Engineer Model and Opportunity Cost Model, we analyzed the special conditions faced by Chinese railways, and developed a model for sharing infrastructure fees among freight and passenger transportations. Engineer Model split Variable Cost （VC） and Fixed Cost （FC） into freight and passenger activities, and Opportunity Cost Model take the insufficient supply of infrastructure capacity into consideration. Of course, the subsidy from the government greatly affected the price standard for bottleneck facilities, or so-called network infrastructures.

Should Apple Charge Fees for Tipping on Social Networking Apps?

Recently, Apple＇s decision to start taking a 30-percent cut on tips given by users of socia networking apps has sparked heated debates in China.

Robust Charging Demand Prediction and Charging Network Planning for Heterogeneous Behavior of Electric Vehicles

This study addresses a new charging station network planning problem for smart connected electric vehicles.We embed a charging station choice model into a charging network planning model that explicitly considers the heterogeneity of the charging behavior in a data-driven manner.To cope with the deficiencies from a small size and sparse behavioral data,we propose a robust charging demand prediction method that can significantly reduce the impact of sample errors and missing data.On the basis of these two building blocks,we form and solve a new optimal charging station location and capacity problem by minimizing the construction and charging costs while considering the charging service level,construction budget,and limit to the number of chargers.We use a case study of planning charging stations in Shanghai to validate our contributions and provide managerial insight in this area.

Are more charging piles imperative to future electrified transportation system?

Scholars and practitioners believe that the large-scale deployment of charging piles is imperative to our future electric transportation systems.Major economies ambitiously install charging pile networks,with massive construction spending,maintenance costs,and urban space occupation.However,recent developments in technology may significantly reduce the necessary charging capacity required by the system.This paper develops a linear programming model to characterize the effects of likely scenarios where vehicle-to-vehicle(V2V)charging is available via vehicle modularization or wireless charging.Specifically,we consider scenarios in which vehicles can transmit energy to each other(coordinated by a central platform)while traveling closely on the same road.We first estimate the number of charging piles needed for completing the travel plan of 73 cars from data,assuming a battery capacity of 400 km’s range and no V2V charging.Our results show that once V2V charging technologies with an efficiency of 50%are available,more than 2/3 of the charging piles investment would be wasted.Additionally,if the efficiency of V2V charging increases to 75%,we can easily reduce the battery capacity of vehicles to 200 km,which will reduce production costs and improve energy efficiency.These results may reveal us an alternative pathway towards transportation electrification.

Realizing compact three-dimensional charge transport networks of asymmetric electron acceptors for efficient organic solar cells

Asymmetry has been demonstrated an effective approach in recent years to tune the structural and energetic orders of nonfullerene electron acceptors(NFAs)to prepare efficient organic solar cells(OSCs).In this article,five asymmetric NFAs,namely C9BTP-BO-Th Cl-2F,C9BTP-BO-Cl-2F,C9BTP-BO-2Cl-2F,C7BTP-BO-2Cl-2F and C5BTP-BO-2Cl-2F possessing varied asymmetric end-groups and alkyl chains are synthesized to tune the charge transport networks formed within these NFAs.We found that the enhanced planarity in the asymmetric NFA can facilitate closerπ-πstacking distance in either the A-to-A or A-toD type NFA dimers,whilst the larger dipole moment can promote the formation of three-dimensional(3D)charge transport networks among NFAs.Taking those advantages,C7BTP-BO-2Cl-2F exhibit a compact 3D honeycomb network with a high packing coefficient of 72.1%and molecular packing density of 0.48 g/cm^(3),contributing to a superior power conversion efficiency of 18.0%when employing PM6 as the donor,with an open-circuit voltage of 0.85 V,short-circuit current of26.7 m A cm^(-2)and fill factor of 79.3%.Our work provides guidelines in engineering the end group and side chains of asymmetric NFAs to achieve compact charge transport networks for high efficiency OSCs.

P2P energy trading via public power networks:Practical challenges,emerging solutions,and the way forward

Peer-to-peer(P2P)energy trading is an emerging energy supply paradigm where customers with distributed energy resources(DERs)are allowed to directly trade and share electricity with each other.P2P energy trading can facilitate local power and energy balance,thus being a potential way to manage the rapidly increasing number of DERs in net zero transition.It is of great importance to explore P2P energy trading via public power networks,to which most DERs are connected.Despite the extensive research on P2P energy trading,there has been little large-scale commercial deployment in practice across the world.In this paper,the practical challenges of conducting P2P energy trading via public power networks are identified and presented,based on the analysis of a practical Local Virtual Private Networks(LVPNs)case in North Wales,UK.The ongoing efforts and emerging solutions to tackling the challenges are then summarized and critically reviewed.Finally,the way forward for facilitating P2P energy trading via public power networks is proposed.

Calculation Model and Allocation Strategy of Network Usage Charge for Peer-to-peer and Community-based Energy Transaction Market

The emergence of prosumers in distribution systems has enabled competitive electricity markets to transition from traditional hierarchical structures to more decentralized models such as peer-to-peer(P2P)and community-based(CB)energy transaction markets.However,the network usage charge(NUC)that prosumers pay to the electric power utility for network services is not adjusted to suit these energy transactions,which causes a reduction in revenue streams of the utility.In this study,we propose an NUC calculation method for P2P and CB transactions to address holistically economic and technical issues in transactive energy markets and distribution system operations,respectively.Based on the Nash bargaining(NB)theory,we formulate an NB problem for P2P and CB transactions to solve the conflicts of interest among prosumers,where the problem is further decomposed into two convex subproblems of social welfare maximization and payment bargaining.We then build the NUC calculation model by coupling the NB model and AC optimal power flow model.We also employ the Shapley value to allocate the NUC to consumers fairly for the NUC model of CB transactions.Finally,numerical studies on IEEE 15-bus and 123-bus distribution systems demonstrate the effectiveness of the proposed NUC calculation method for P2P and CB transactions.