A data‐driven approach to study the role of interconnectors in a future low‐carbon electricity supply system

This paper investigates the potential role of the electricity interconnectors in improving the security of supply in Great Britain (GB) in 2030. Real electricity demand and price data for GB and France in 2016 were used to understand the relationship between power exchange between the two countries and their wholesale electricity prices. A linear programming optimisation model was developed to find the economic power dispatch. Two interconnection links were considered; two‐way trade interconnector with a capacity of 5.4 GW and a 12.3 GW import‐only interconnector between GB and other states. The GB–France link transmits electricity from cheaper system to the more expensive one. The total electricity demand in 2030 will be 406 TWh. Gas‐fired power plants w/wo CCS will provide 83 TWh of the total electricity demand, whereas nuclear power plants will produce 74 TWh. In addition, wind farms and solar PVs are expected to deliver ~120 TWh electricity. CHP units will provide 88 TWh electricity in 2030. The electricity traded between GB and France in 2030 was found to be 33 TWh, which is 160% larger compared with 2016. The power import from France is about 27 TWh and occurs in 59% of the time. For 64% of the time, the interconnector with France is fully loaded. The electricity imported via the 12.3 GW interconnector in 2030 is 1 TWh and mainly occurs during winter‐time when the demand in GB is high. De‐rated capacity margin was calculated based on instantaneous electricity demand and varies between ?2% and 139%. The impact of the price of the imported electricity via the 12.3 GW link was investigated. Increasing the price of the imported electricity via the 12.3 GW link results in a higher capacity factor for all the generation options except the 12.3 GW interconnector link.     

An output‐feedback adaptive control architecture for mitigating actuator attacks in cyber‐physical systems

In this paper, we present a control design framework wherein an adaptive‐based corrective signal is augmented to the output of the nominal controller in order to suppress or counteract the effect of malicious actuator attacks. Due to the unavailability of full‐state measurements, a nonminimal controllable realization of the nominal closed‐loop system is used to design the corrective signal predicated on partial state information. Two illustrative numerical examples are given to demonstrate the efficacy of the proposed adaptive control architecture.     

Spatial estimation of aquifer’s hydraulic parameters by a combination of borehole data and inverse solution

Bulletin of Engineering Geology and the Environment - A combination of borehole data interpretation and inverse solution method used to estimate the spatial distribution of hydraulic conductivity...     

Potential of Ge-adopted Boron Nitride Nanotube as Catalyst for Sulfur Dioxide Oxidation

Protection of Metals and Physical Chemistry of Surfaces - In recent years, the discovery of efficient catalyst with low price to sulfur dioxide (SO2) oxidation in normal temperature is a major...     

Risk measurement and prioritization of auto parts manufacturing processes based on process failure analysis,interval data envelopment analysis and grey relational analysis

Nowadays, decision-making process is faced with different challenges. There are many aspects that must be considered and planned, especially programs in the automotive industry that is associated with human vital factors are not structured. Therefore, managerial and engineering techniques should be used to solve the existing problems. In this regard, the process failure mode and effects nalysis (PFMEA) technique is one of the ways to assess the potential product or process failures and their effects, designs from the beginning to the end of the product life cycle, and identifies actions to eliminate the failures or reduce their effects. The well-known method for piriortizing these failures is risk priority number (RPN). Because the RPN has problems in prioritization of critical processes, a new approach is needed to remove these problems.Thus, in a real case study, first PFMEA technique has been implemented with the help of multidisciplinary teams for the parts of Peugeot 206, Peugeot 405 and Samand (three types of automobiles produced by Iran-khodro company) and affected factors have been obtained as an interval. Then, interval data envelopment analysis (DEA) have been used to prioritize and analyze all failures that are identified by the PFMEA technique for every part. Finally, by combining the results of the interval DEA and Grey relational analysis (GRA), the manufacturing processes are prioritized based on their criticality. Moreover, the proposed actions for all the items associated with each process are provided to prevent some potential failures. The results show that pouring and core making are the most crucial processes in this study, respectively. According to the proposed approach, the decision makers may determine critical processes and plan and do appropriate actions for removing failures or reducing their effects.     

Influence of fabrication stresses on fatigue life of friction stir welded aluminium profiles

Influence of clamping and welding procedure on fatigue life of a friction stir (FS) welded aluminium profile has been analysed. Two series of aluminium profiles (series A and B) have been fatigue tested. The different clamping conditions in series A and B gave rise to different failure positions that could not be explained neither by the effective notch stress method, nor by the critical distance methods. The clamping in series A introduced plastic deformation at the weld notch that gave rise to tensile residual stresses. The failure position could be explained from the value of the stress intensity factor provided that the residual stresses were considered.     

Microstructural Evolutions During Reversion Annealing of Cold-Rolled AISI 316 Austenitic Stainless Steel

Metallurgical and Materials Transactions A - Microstructural evolutions during reversion annealing of a plastically deformed AISI 316 stainless steel were investigated and three distinct stages...     

Carbon nanotube–polymer interactions in nanocomposites: A review

The interaction between carbon nanotubes and polymers is critically reviewed. The interfacial characteristics directly influence the efficiency of nanotube reinforcements in improving mechanical, thermal, and electrical properties of the polymer nanocomposite. In this review, various techniques of interaction measurements, including experimental and modelling studies, are described. From the experimental approaches, wetting, spectroscopy and probe microscopy techniques are discussed in detail. Molecular dynamics, coarse grain simulation and density functional theory are also explained as the main modelling approaches in interaction measurement studies. Different methods of interaction improvement, mainly categorized under covalent and noncovalent interactions, are described afterwards. Modelling predictions of nanocomposite properties, such as Young’s modulus, are compared with the experimental results in the literature and the challenges are discussed. Finally, it is concluded that an optimum carbon nanotube–polymer interaction is a key factor towards reaching the full potential of carbon nanotubes in nanocomposites.