Effect of Mixed Vegetation of Different Heights on Open Channel Flows

Vegetation of different heights commonly grows in natural rivers, canals and wetlands and affects the biodiversity and morphological process. The role of vegetation has drawn great attention in river ecosystems and environmental management. Due to the complexity of the vegetated flow, most previous research focuses on the effect of uniformed one-layered vegetation on the flow structure and morphological process. However, less attention was paid to the impact of the mixing vegetation of different heights, which is more realistic and often occurs in natural riverine environments. This paper aims to investigate the effect of mixing three-layered vegetation on flow characteristics, particularly the velocity distrbution, via a novel experiment. Experiments were performed in a titling water flume fully covered with vegetation of three heights (10, 15 and 20 cm) arranged in a staggered pattern, which is partially submerged. Velocities at different positions along a half cross-section were measured using a mini propeller velocimeter. Observed results showed that the velocity has a distinct profile directly behind vegetation and behind the vegetation gap. The overall profile has two distinct reflections about ? below or near the top of short vegetation (h): the velocity remains almost constant in the bottom layer ( h) the velocities directly behind the middle after short vegetation increase much faster than those directly behind the short after tall vegetation. The finding in this study would help river riparian and ecosystem management. .

Topology-independent end-to-end learning model for improving the voltage profile in microgrids-integrated power distribution networks

With multiple microgrids(MGs)integrated into power distribution networks in a distributed manner,the penetration of renewable energy like photovoltaic(PV)power generation surges.However,the operation of power distribution networks is challenged by the issues of multiple power flow directions and voltage security.Accordingly,an efficient voltage control strategy is needed to ensure voltage security against ever-changing operating conditions,especially when the network topology information is absent or inaccurate.In this paper,we propose a novel data-driven voltage profile improvement model,denoted as system-wide composite adaptive network(SCAN),which depends on operational data instead of network topology details in the context of power distribution networks integrated with multiple MGs.Unlike existing studies that realize topology identification and decisionmaking optimization in sequence,the proposed end-to-end model determines the optimal voltage control decisions in one shot.More specifically,the proposed model consists of four modules,Pre-training Network and modified interior point methods with adversarial networks(Modified IPMAN)as core modules,and discriminator generative adversarial network(Dis-GAN)and Volt convolutional neural network(Volt-CNN)as ancillary modules.In particular,the generator in SCAN is trained by the core modules in sequence so as to form an end-to-end mode from data to decision.Numerical experiments based on IEEE 33-bus and 123-bus systems have validated the effectiveness and efficiency of the proposed method.

Uniquely determine fracture dimension and formation permeability from diagnostic fracture injection test

Estimating formation permeability is crucial for production estimation,hydraulic fracturing design optimization and rate transient analysis.Laboratory experiments can be used to measure the permeability of rock samples,but the results may not be representative at a field scale because of reservoir heterogeneity and pre-existing natural fracture systems.Diagnostic Fracture Injection Tests(DFIT)have now become standard practice to estimate formation pore pressure and formation permeability.However,in low permeability reservoirs,after-closure radial flow is often absent,which can cast significant uncertainties in interpreting DFIT data.Without knowing the fracture dimension prior,open fracture stiffness/compliance can't be determined,which is required for formation permeability estimation.Previous work has to assume a fracture radius or fracture height in order to estimate formation permeability,thus dent the confidence in the interpretation results.In the study,we present a new approach to determine fracture dimension,leak-off coefficient and formation permeability uniquely based on material balance and basic fracture mechanics,using data from shut-in to after-closure linear flow.Field examples are also presented to demonstrate the simplicity and effectiveness of this new approach.