A Voltage Control Method for a Distributed Line Feeder by means of Multiagent Approach

This paper proposes a method for the coordinated control of power factor by means of a multiagent approach. The proposed multiagent system consists of two types of agent: single feeder agent (F_AG) and bus agent (B_AG). In the proposed system, an F_AG plays as an important role, which decides the power factors of all distributed generators by executing the load flow calculations repeatedly. The voltage control strategies are implemented as the class definition of Java into the system. In order to verify the performance of the proposed method, it has been applied to a typical distribution model system. The simulation results show that the system is able to control very violent fluctuation of the demands and the photovoltaic (PV) generations.     

Piezoresistive in-situ strain sensing of composite laminate structures

Various methods have been developed to monitor the health and strain state of carbon fiber reinforced polymers, each with a unique set of pros and cons. This research assesses the use of piezoresistive sensors for in situ strain measurement of carbon fiber and other composite structures in multidirectional laminates. The piezoresistive sensor material and the embedded circuitry are both evaluated. For the piezoresistive sensor, a conductive nickel nanocomposite sensor is compared with the piezoresistivity of the carbon fiber itself. For the circuit, the use of carbon fibers already present in the structure is compared with the use of nickel coated carbon fiber. Successful localized strain sensing is demonstrated for several sensor and circuitry configurations. Numerous engineering applications are possible in the ever-growing field of carbon-composites.     

Economic growth,CO2 emissions,and energy consumption in the five ASEAN countries

This paper investigates the relationship between economic growth, carbon dioxide (CO₂) emissions, and energy consumption with an aim to test the validity of the Environmental Kuznets Curve (EKC) hypothesis in five ASEAN (Association of South East Asian Nations) countries (Indonesia, Malaysia, Philippines, Singapore, and Thailand) by applying the panel smooth transition regression (PSTR) model as a new econometric technique. The PSTR model is more flexible and appropriate for describing cross-country heterogeneity and time instability. Our empirical results strongly rejected the null hypothesis of linearity, and the test for no remaining nonlinearity indicated a model with one transition function and two threshold parameters. The first regime (levels of GDP per capita below 4686 USD) showed that environmental degradation increases with economic growth while the trend was reversed in the second regime (GDP per capita above 4686 USD). The results also showed that energy consumption with either the first or the second regime lead to increase CO₂. The overall results support the validity of the EKC hypothesis in the ASEAN countries.     

Simultaneous process optimization and heat integration based on rigorous process simulations

This paper introduces a simultaneous process optimization and heat integration approach, which can be used directly with the rigorous models in process simulators. In this approach, the overall process is optimized utilizing external derivative-free optimizers, which interact directly with the process simulation. The heat integration subproblem is formulated as an LP model and solved simultaneously during optimization of the flowsheet to update the minimum utility and heat exchanger area targets. A piecewise linear approximation for the composite curve is applied to obtain more accurate heat integration results. This paper describes the application of this simultaneous approach for three cases: a recycle process, a separation process and a power plant with carbon capture. Case study results indicate that this simultaneous approach is relatively easy to implement and achieves higher profit and lower operating cost and, in the case of the power plant example, higher net efficiency than the sequential approach.     

Impact of shape representation schemes used in discrete element modelling of particle packing

In different computer models, shape is represented using different methodologies, to varying degrees of precision. This paper examines two approaches to shape representation, and their effects on accuracy in the context of cylindrical particle packing. Two discrete element method (DEM) based software packages are used. A X-ray CT scan of a packed bed provides the experimental measurements for comparison. Eight sphere-composite representations of the same cylindrical pellet were tested. Two of these gave results that quantitatively follow experimental measurements. A range of factors that in theory could affect accuracy of the simulation results are examined, including edge roundedness, surface roughness and restitutional behaviour as a function of sphere-composite representations. The conclusion is that, for packing at least, matching the object's overall shape and dimensions is not enough. Only when a high enough resolution is applied to corners and edges, could the sphere-composite approach possibly match the experimental data quantitatively.     

Characterization of sea water ageing effects on mechanical properties of carbon/epoxy composites for tidal turbine blades

In recent years, many tidal turbine projects have been developed using composites blades. Tidal turbine blades are subject to ocean forces and sea water aggressions, and the reliability of these components is crucial to the profitability of ocean energy recovery systems. The majority of tidal turbine developers have preferred carbon/epoxy blades, so there is a need to understand how prolonged immersion in the ocean affects these composites. In this study the long term behaviour of different carbon/epoxy composites has been studied using accelerated ageing tests. A significant reduction of composite strengths has been observed after saturation of water in the material. For longer immersions only small further changes in these properties occur. No significant changes have been observed for moduli nor for composite toughness. The effect of sea water ageing on damage thresholds and kinetics has been studied and modelled. After saturation, the damage threshold is modified while kinetics of damage development remain the same.     

Recent progress of the gas diffusion layer in proton exchange membrane fuel cells: Material and structure designs of microporous layer

Proton exchange membrane fuel cells (PEMFCs) have become the most attractive power supply units for stationary and mobile applications. The operation, design characteristics, as well as performance of PEMFCs, are closely related to the multiphase transport of mass, heat, and electricity in the cell, a critical of which is the gas diffusion layer (GDL). It is very important to guarantee the transmission of water and gasses under high current density, and which is the weakness of PEMFCs at present. Microporous layer (MPL) is considered to be the key variable for mass transfer, so varieties of works focus on modification of MPL materials and its structure design. However, there is still a lack of special review to summarize and prospect the progress of MPL in recent years. This review article therefore focuses on the insights and comprehensive understanding of four critical issues of the MPL, the porosity, pore size distribution, wettability, structural design and the durability of MPL. At last, the conclusion and recommendations section summarized the future prospects and recommendations for possible research opportunities.     

Carbon nanotube filter for heavy metal ion adsorption

This study investigated carbon nanotube filtration technology using catalyst particles supported on silicalite-1–biomorphic carbon materials (BCMs). Aqueous solutions of Mn(II), Cu(II), Cr(III), Cd(II), and Pb(II) were used to test the efficiency of heavy metal ions removal. Carbon nanotubes (CNTs) were synthesized and grown on BCMs by the chemical vapor deposition method catalyzed with the catalyst (Co, Fe, and Ni). The synthesized CNTs with Co– and Fe– nanoparticles were typically multi-walled carbon nanotubes, and they showed good crystallinity (I_D/I_G = 1.05) and yield of (11.10 and 8.86) %. The removal efficiency of Mn(II), Cu(II), Cr(III), Cd(II), and Pb(II) ions using Co-catalyzed CNT filter was 97.57%, 98.01%, 97.89%, 97.42%, and 99.99%, respectively.     

Evolving an Accurate Decision Tree-Based Model for Predicting Carbon Dioxide Solubility in Polymers

Solubility is one of the most indispensable physicochemical properties determining the compatibility of components of a blending system. Research has been focused on the solubility of carbon dioxide in polymers as a significant application of green chemistry. To replace costly and time-consuming experiments, a novel solubility prediction model based on a decision tree, called the stochastic gradient boosting algorithm, was proposed to predict CO₂ solubility in 13 different polymers, based on 515 published experimental data lines. The results indicate that the proposed ensemble model is an effective method for predicting the CO₂ solubility in various polymers, with highly satisfactory performance and high efficiency. It produces more accurate outputs than other methods such as machine learning schemes and an equation of state approach.