Adsorption Characteristics of Reactive Dyes in Columns of Activated Carbon

Abstract: Adsorption behaviour of reactive dyes in fixed-bed adsorber was evaluated in this work. The characteristics of mass transfer zone (MTZ), where adsorption in column occurs, were affected by carbon bed depth and influent dye concentration. The working lifetime (t(x)) of MTZ, the height of mass transfer zone (HMTZ), the rate of mass transfer zone (RMTZ), and the column capacity at exhaustion (q(column)) were estimated for the removal of remazol reactive yellow and remazol reactive black by carbon adsorber. The results showed that column capacity calculated at 90% of column exhaustion was lower than carbon capacity obtained from equilibrium studies. This indicated that the capacity of activated carbon was not fully utilized in the fixed-bed adsorber. The bed-depth service time model (BDST) was applied for analysis of reactive yellow adsorption in the column. The adsorption capacity of reactive yellow calculated at 50% breakthrough point (No) was found to be 0.1 kg kg(-1) and this value is equivalent to about 14% of the available carbon capacity. The results of this study indicated the applicability of fixed-bed adsorber for removing remazol reactive yellow from solution. (C) 2008 Elsevier B.V. All rights reserved.

Development and Longer Term In Situ Evaluation of Fiber-Optic Sensors for Monitoring of Structural Concrete

In this paper, new solutions to the problem of making measurements, of carbonation and chloride ingress, in particular, in concrete structures are considered. The approach has focused on the design, development, and use of fiber-optic sensors (FOSs), recognizing the need in that conventional devices are often either inaccurate, expensive, or unsuitable for encapsulation in the material. The sensors have been designed to monitor, in situ and nondestructively, relevant physical, and chemical changes in cementitious materials. Three different types of FOS were constructed, tested, and evaluated specifically for this application, these being a temperature sensor (based on the fluorescence decay) and pH and chloride sensors, based on sol-gel (solidified gel) technology with appropriate impregnated indicators. The sensors were all designed to be inserted into the structures and evaluated under the harshest conditions, i.e., being mounted when the mortar is poured and thus tested in situ, with the temperature and pH sensors successfully embedded in mortar. The outcomes of these tests have shown that both the temperature sensor and the pH sensor were able to function correctly for the duration of the work - for over 18 months after placement. The laboratory tests on the chloride sensor showed it was able to make measurements but was not reversible, limiting its potential utility for in situ environments. Research is ongoing to refine the sensor performance and extend the testing.

Strengthening an in-service reinforcement concrete bridge with prestressed CFRP bar

Carbon fiber reinforced polymer (CFRP) bars were prestressed for the structural strengthening of 8 T-shaped reinforced concrete (RC) beams of a 21-year-old bridge in China. The ultimate bearing capacity of the existing bridge after retrofit was discussed on the basis of concrete structures theory. The flexural strengths of RC beams strengthened with CFRP bars were controlled by the failure of concrete in compression and a prestressing method was applied in the retrofit. The field construction processes of strengthening with CFRP bars—including grouting cracks, cutting groove, grouting epoxy and embedding CFRP bars, surface treating, banding with the U-type CFRP sheets, releasing external prestressed steel tendons—were introduced in detail. In order to evaluate the effectiveness of this strengthening method, field tests using vehicles as live load were applied before and after the retrofit. The test results of deflection and concrete strain of the T-shaped beams with and without strengthening show that the capacity of the repaired bridge, including the bending strength and stiffness, is enhanced. The measurements of crack width also indicate that this strengthening method can enhance the durability of bridges. Therefore, the proposed strengthening technology is feasible and effective.

Analysis of compressive membrane action in concrete slabs

This paper summarises the results obtained from non-linear finite-element analysis (NLFEA) of a series of reinforced-concrete one-way slabs with various boundary conditions representative of a bridge deck slab strip in which compressive membrane action governs the structural behaviour. The application of NLFEA for the optimum analysis and design of in-plane restrained concrete slabs is explored. An accurate material model and various equation solution methods were assessed to find a suitable finite-element method for the analysis of concrete slabs in which arching action occurs. Finally, the results from the NLFEA are compared and validated with those from various experimental test data. Significantly, the numerical analysis was able to model the arching action that occurred as a result of external in-plane restraint at the supports and which enhanced the ultimate strength of the slab. The NLFEA gave excellent predictions for the ultimate load-carrying capacity and far more accurate predictions than those obtained using standard flexural or elastic theory.

Prediction of Fresh and Hardened Properties of Self-Consolidating Concrete Using Neurofuzzy Approach

Self-consolidating concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work conditions and also reduce the impact on the environment by elimination of the need for compaction. This investigation aimed at exploring the potential use of the neurofuzzy (NF) approach to model the fresh and hardened properties of SCC containing pulverised fuel ash (PFA) as based on experimental data investigated in this paper. Twenty six mixes were made with water-to-binder ratio ranging from 0.38 to 0.72, cement content ranging from 183 to 317 kg/m3 , dosage of PFA ranging from 29 to 261 kg/m3 , and percentage of superplasticizer, by mass of powder, ranging from 0 to 1%. Nine properties of SCC mixes modeled by NF were the slump flow, JRing combined to the Orimet, JRing combined to cone, V-funnel, L-box blocking ratio, segregation ratio, and the compressive strength at 7, 28, and 90 days. These properties characterized the filling ability, the passing ability, the segregation resistance of fresh SCC, and the compressive strength. NF model is constructed by training and testing data using the experimental results obtained in this study. The results of NF models were compared with experimental results and were found to be quite accurate. The proposed NF models offers useful modeling approach of the fresh and hardened properties of SCC containing PFA.

Genetic programming based formulation for fresh and hardened properties of self-compacting concrete containing pulverised fuel ash

Self-compacting concrete (SCC) flows into place and around obstructions under its own weight to fill the formwork completely and self-compact without any segregation and blocking. Elimination of the need for compaction leads to better quality concrete and substantial improvement of working conditions. This investigation aimed to show possible applicability of genetic programming (GP) to model and formulate the fresh and hardened properties of self-compacting concrete (SCC) containing pulverised fuel ash (PFA) based on experimental data. Twenty-six mixes were made with 0.38 to 0.72 water-to-binder ratio (W/B), 183–317 kg/m³ of cement content, 29–261 kg/m³ of PFA, and 0 to 1% of superplasticizer, by mass of powder. Parameters of SCC mixes modelled by genetic programming were the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength at 7, 28 and 90 days. GP is constructed of training and testing data using the experimental results obtained in this study. The results of genetic programming models are compared with experimental results and are found to be quite accurate. GP has showed a strong potential as a feasible tool for modelling the fresh properties and the compressive strength of SCC containing PFA and produced analytical prediction of these properties as a function as the mix ingredients. Results showed that the GP model thus developed is not only capable of accurately predicting the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength used in the training process, but it can also effectively predict the above properties for new mixes designed within the practical range with the variation of mix ingredients.