Removal of mercaptans from a gas stream using continuous adsorption-regeneration

The removal of the mercaptan, 1-methyl-1-propanethiol, from aqueous solutions using a non-porous, electrically conducting carbon-based adsorbent (Nyex 1000) was investigated. The adsorption process was found to be rapid (equilibrium capacity achieved within 5 minutes) with low adsorptive capacity (of the order of 0.4 mg g(-1)) when compared with activated carbon. Electrochemical regeneration of the Nyex 1000 in a simple divided electrochemical cell within a sequential batch treatment unit restored 100% of the adsorbent's adsorptive capacity using treatment times as low as 20 minutes by passing a current of 0.5 A. The sorptive characteristics of a Nyex-water slurry were also modelled and investigated both in a bubble column and in a continuous adsorption-regeneration treatment system. It was demonstrated that the continuous removal-destruction system could achieve a step reduction in challenge gas concentration of approximately 75% for a period of 35 minutes with a current of 5 Amps. This was attributed to mass transfer enhanced by a combination of adsorption and chemical reaction with free chlorine species generated in the electrochemical process.     

A method for real power transfer allocation using multivariable regression analysis

A multivariable regression (MVR) approach is proposed to identify the real power transfer between generators and loads. Based on solved load flow results, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then, the results of MNE method and load flow information are utilized to determine suitable regression coefficients using MVR model to estimate the power transfer. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of the MVR output compared to that of the MNE method. The error of the estimate of MVR method ranges from 0.001 4 to 0.007 9. Furthermore, when compared to MNE method, MVR method computes generator contribution to loads within 26.40 ms whereas the MNE method takes 360 ms for the calculation of same real power transfer allocation. Therefore, MVR method is more suitable for real time power transfer allocation.     

Probabilistic assessment of loss in revenue generation in demand-driven production

In Demand-driven Production with Just-in-Time inputs, there are several sources of uncertainty which impact on the manufacturer??s ability to meet the required customer??s demand within the given time frame. This can result in a loss of revenue and customers, which will have undesirable impacts on the financial aspects and on the viability of the manufacturer. Hence, a key concern for manufacturers in just-in-time production is to determine whether they can meet a specific level of demand within a given time frame, to meet the customers?? orders and also to achieve the required revenue target for that period of time. In this paper, we propose a methodology by which a manufacturer can ascertain the probability of not meeting the required demand within a given period by considering the uncertainties in the availability of production units and raw materials, and the loss of financial revenue that it would experience as a result.     

Absorption and emission properties of Ho doped lead-zinc-borate glasses

This paper reports on the affect of lead content on the absorption and emission spectra of the Ho³⁺ ion doped lead-zinc-borate glasses in the composition (mol%) of (20 − x)PbO-20ZnO-(59 + x)B₂O₃-1.0Ho₂O₃ where x = 0, 5,10,15 of PbO content with λ_exc = 405 nm. The experimental absorption band energies have satisfactorily been correlated with the theoretical results with an r.m.s deviation of zero with the following correction factors obtained by a least square fit analysis: ΔE¹ = 348.495936 cm^− 1, ΔE² = 1.436043 cm^− 1, ΔE³ =  46.481575 cm^− 1, Δξ_4f = − 28.512979 cm^− 1, Δα = 55.508936 cm^− 1, Δβ = − 1394.339908 cm^− 1 and Δγ = 1208.424336 cm^− 1. By applying the Judd-Ofelt intensity parameter Ω₂ has been found to be linearly decreasing with the PbO content from 5 to 10 mol% and then increasing. And also radiative (A, A_T, β, τ_r) characteristic factors of the luminescent transitions (⁵I₈ ← ⁵F_3,4,5 and ⁵S₂) of the glasses have been evaluated. Stimulated emission cross-sections (σ_p^E) of the measured emission transitions of holmium glasses have also been computed.     

Adaptive reconfiguration of data networks using genetic algorithms

Genetic algorithms are applied to an important, but little investigated, network design problem, that of reconfiguring the topology and link capacities of an operational network to adapt to changes in its operating conditions. These conditions include: which nodes and links are unavailable; the traffic patterns; and the quality of service (QoS) requirements and priorities of different users and applications. Dynamic reconfiguration is possible in networks that contain links whose endpoints can be easily changed, such as satellite channels, terrestrial wireless connections, and certain types of optical connections. We report preliminary results that demonstrate the feasibility of performing genetic search quickly enough for online adaptation.     

Recent developments in catalyst synthesis using DBD plasma for reforming applications

The catalyst has a significant role in gas processing applications such as reforming technologies for H₂ and syngas production. The stable catalyst is requisite for any industrial catalysis application to make it commercially viable. Several methods are employed to synthesize the catalysts. However, there is still a challenge to achieve a controlled morphology and pure catalyst which majorly influences the catalytic activity in reforming applications. The conventional methods are expansive, and the removal of the impurities are major challenges. Nevertheless, it is not straightforward to achieve the desired structure and stability. Therefore, significant interest has been developed on the advanced techniques to take control of the physicochemical properties of the catalyst through non-thermal plasma (NTP) techniques. In this review, the systematic evolution of the catalyst synthesis using NTP technique is elucidated. The emerging DBD plasma to synthesized and effective surface treatment is reviewed. DBD plasma synthesized catalyst performance in reforming application for H₂ and syngas production is summarised. Furthermore, the status of DBD plasma for catalyst synthesis and proposed future avenues to design environmentally suitable and cost-effective synthesis techniques are discussed.     

In vitro mesenchymal stem cell responses on laser-welded NiTi alloy

The biocompatibility of NiTi after laser welding was studied by examining the in vitro (mesenchymal stem cell) MSC responses at different sets of time varying from early (4 to 12 h) to intermediate phases (1 and 4 days) of cell culture. The effects of physical (surface roughness and topography) and chemical (surface Ti/Ni ratio) changes as a consequence of laser welding in different regions (WZ, HAZ, and BM) on the cell morphology and cell coverage were studied. The results in this research indicated that the morphology of MSCs was affected primarily by the topographical factors in the WZ: the well-defined and directional dendritic pattern and the presence of deeper grooves. The morphology of MSCs was not significantly modulated by surface roughness. Despite the possible initial Ni release in the medium during the cell culture, no toxic effect seemed to cause to MSCs as evidenced by the success of adhesion and spreading of the cells onto different regions in the laser weldment. The good biocompatibility of the NiTi laser weldment has been firstly reported in this study.     

Optimization of friction stir welding process using NSGA-II and DEMO

In welding processes, the selection of optimal process parameter settings is very important to achieve best weld qualities. In this work, neuro-multi-objective evolutionary algorithms (EAs) are proposed to optimize the process parameters in friction stir welding process. Artificial neural network (ANN) models are developed for the simulation of the correlation between process parameters and mechanical properties of the weld using back-propagation algorithm. The weld qualities of the weld joint, such as ultimate tensile strength, yield stress, elongation, bending angle and hardness of the nugget zone, are considered. In order to optimize those quality characteristics, two multi-objective EAs that are non-dominated sorting genetic algorithm II and differential evolution for multi-objective are coupled with the developed ANN models. In the end, multi-criteria decision-making method which is technique for order preference by similarity to the ideal solution is applied on the Pareto front to extract the best solutions. Comparisons are conducted between results obtained from the proposed techniques, and confirmation experiments are performed to verify the simulated results.

     

Dominant Mechanisms for Metal Removal from Acidic Aqueous Solutions by Cement Kiln Dust

Copper and zinc ions were removed from synthetic acidic aqueous solutions onto cement kiln dust (CKD) particles in a single component system. The objectives of this study were to: distinguish between adsorption and precipitation when both mechanisms are occurring simultaneously; define their individual contributions; and consequently, specify the dominant mechanism. This was achieved by conducting a new experimental procedure for the precipitation phase that depended on CKD leachate in combination with a derivation of a simultaneous adsorption-precipitation equation. High removal efficiencies, approaching 100?%, of the Cu and Zn ions, were attained. Precipitation was the dominant mechanism for removing low concentrations of these metals, while adsorption appears to be more significant in removal of high metal concentrations.