4 research outputs found
Electrical and mechanical behaviour of copper tufted CFRP composite joints
Electrical continuity of dissimilar joints controls the current and thermal pathways during lightning strike. Tufting using carbon, glass or Kevlar fibres is a primary to introduce through thickness reinforcement for composite structures and assemblies. Replacing the conventional tuft thread material with metallic conductive wire presents an opportunity for enhancing current dissipation and deal with electrical bottlenecks across dissimilar joints. Simulation of the electro-thermo-mechanical behaviour of joints was carried out to assess the influence of metallic tufting. The finite element solver MSC.Marc was utilised. Mechanical models incorporate continuum damage mechanics (CDM) to capture progressive damage in both composite and aluminium components of the joint. The mechanical models were coupled with electrical and thermal simulations of reference and copper tufted carbon fibre epoxy composite joints to assess both the lightning strike response and mechanical robustness of the assembly as well as the improvements offered by tufting. Validation of the model is based on electrical conduction and temperature measurements alongside delamination tests.European Union funding: 88704
Phytoremediation of Heavy Metals by Vetiver Plant Species in Unconventional Water
The use of natural processes, including the physiological potential of plants, is a suitable solution. In this study in order to assess the effect of waste leachate and industrial wastewater on the absorption of heavy metals by the Vetiver plant, two separate factorial experiments were performed in the crop year 2020-2021 as a completely randomized design. Experiment treatments factors included waste leachate and industrial wastewater use separately on 5 levels (0, 25, 50, 75, and 100%) in three replications (B1, B2, B3) and two irrigation periods of 5 and 10 days (A5, A10). The amount of iron, zinc, copper, manganese, potassium, and sodium measured in vetiver showed waste leachate had a significant effect at the level of 5% (P 0.05). R4A1 and W5A1 treatments showed a relatively good response with a decrease in biomass production below 10% compared to the control treatment. According to the results, the Vetiver species has relatively high compatibility in the absorption of heavy metals with unconventional waters and can have a special application for soil and water protection
Manufacture of a rotor blade pitch horn using binder yarn fabrics
The use of binder yarn fabrics in rotor blade applications is investigated in this work. A
preforming procedure is incorporated in manufacturing, resulting in higher degree of
automation and a reduction of process steps. The performance of the process is
evaluated with respect to cost savings compared to prepregging technologies
Optimal operation of the dam reservoir in real time based on generalized structure of group method of data handling and optimization technique
Abstract The historical data on water intake into the reservoir is collected and used within the framework of a deterministic optimization method to determine the best operating parameters for the dam. The principles that have been used to extract the best values of the flow release from the dam may no longer be accurate in the coming years when the inflow to dams will be changing, and the results will differ greatly from what was predicted. This represents this method’s main drawback. The objective of this study is to provide a framework that can be used to guarantee that the dam is running as efficiently as possible in real time. Because of the way this structure is created, if the dam’s inflows change in the future, the optimization process does not need to be repeated. In this case, deep learning techniques may be used to restore the ideal values of the dam’s outflow in the shortest amount of time. This is achieved by accounting for the environment’s changing conditions. The water evaluation and planning system simulator model and the MOPSO multi-objective algorithm are combined in this study to derive the reservoir’s optimal flow release parameters. The most effective flow discharge will be made feasible as a result. The generalized structure of the group method of data handling (GSGMDH), which is predicated on the results of the MOPSO algorithm, is then used to build a new model. This model determines the downstream needs and ideal release values from the reservoir in real time by accounting for specific reservoir water budget factors, such as inflows and storage changes in the reservoir. Next, a comparison is drawn between this model’s performance and other machine learning techniques, such as ORELM and SAELM, among others. The results indicate that, when compared to the ORELM and SAELM models, the GSGMDH model performs best in the test stage when the RMSE, NRMSE, NASH, and R evaluation indices are taken into account. These indices have values of 1.08, 0.088, 0.969, and 0.972, in that order. It is therefore offered as the best model for figuring out the largest dam rule curve pattern in real time. The structure developed in this study can quickly provide the best operating rules in accordance with the new inflows to the dam by using the GSGMDH model. This is done in a way that makes it possible to manage the system optimally in real time