Properties of self-compacting mortars with binary and ternary cementitious blends of fly ash and metakaolin

The link between flow properties and the formulation is actually one of the key-issues for the design of self-compacting concretes (SCC). As an integral part of a SCC, self-compacting mortars (SCMs) may serve as a basis for the design of concrete since the measurement of the rheological properties of SCCs is often impractical due to the need for complex equipment. This paper discusses the properties of SCMs with mineral admixtures. Portland cement (PC), metakaolin (MK), and fly ash (FA) were used in binary (two-component) and ternary (three-component) cementititios blends. Within the frame work of this experimental study, a total of 16 SCMs were prepared having a constant water-binder (w/b) ratio of 0.40 and total cementitious materials content of 550 kg/m³. Then, the fresh properties of the mortars were tested for mini-slump flow diameter, mini-V-funnel flow time, setting time, and viscosity. Moreover, development in the compressive strength and ultrasonic pulse velocity (UPV) of the hardened mortars were determined at 1, 3, 7, 14, and 28 days. Test results have shown that using of FA and MK in the ternary blends improved the fresh properties and rheology of the mixtures when compared to those containing binary blends of FA or MK.     

Distributed multilevel optimization for complex structures

Optimization problems concerning complex structures with many design variables may entail an unacceptable computational cost. This problem can be reduced considerably with a multilevel approach: A structure consisting of several components is optimized as a whole (global) as well as on the component level. In this paper, an optimization method is discussed with applications in the assessment of the impact of new design considerations in the development of a structure. A strategy based on fully stressed design is applied for optimization problems in linear statics. A global model is used to calculate the interactions (e.g., loads) for each of the components. These components are then optimized using the prescribed interactions, followed by a new global calculation to update the interactions. Mixed discrete and continuous design variables as well as different design configurations are possible. An application of this strategy is presented in the form of the full optimization of a vertical tail plane center box of a generic large passenger aircraft. In linear dynamics, the parametrization of the component interactions is problematic due to the frequency dependence. Hence, a modified method is presented in which the speed of component mode synthesis is used to avoid this parametrization. This method is applied to a simple test case that originates from noise control.     

Distributed model predictive control of an experimental four-tank system

A distributed model predictive control (DMPC) framework is proposed. The physical plant structure and the plant mathematical model are used to partition the system into self-sufficient estimation and control nodes. Local measurements at the nodes are used to estimate the relevant plant states. This information is then used in the model predictive control calculations. Communication among relevant nodes during estimation and control calculations provides improvement over the performance of completely decentralized controllers. The DMPC framework is demonstrated for the level control of an experimental four-tank system. The performance of the DMPC system for disturbance rejection is compared with other control configurations. The results indicate that the proposed framework provides significant improvement over completely decentralized MPC controllers, and approaches the performance of a fully centralized design.     

Formation of chlorination by-products in waters with low SUVA--correlations with SUVA and differential UV spectroscopy

The formation of THMs and HAAs after chlorination of bulk water fractions of low-SUVA (specific UV absorbance) surface waters was investigated, and the applicability of SUVA and differential UV spectroscopy for monitoring THMs and HAAs in such waters was evaluated. Samples from two reservoirs were fractionated employing XAD-8, XAD-4, MIEX resin and granular activated carbon adsorption. A total of 83 bulk water NOM fractions (i.e., the remaining solutions after contact with the adsorbent or resin at various doses) were obtained and chlorinated. The majority of NOM in both waters was found to have average molecular weights <2000 Da and SUVA values <2L/mg Cm, indicating that NOM in the tested waters contained dominantly lower molecular weight fractions and low aromaticity. SUVA did not correlate well with the formation and speciation of THMs and HAAs, suggesting that SUVA does not capture the reactive sites on NOM moieties responsible for DBP formation in low-SUVA waters. Similarly, no correlations were found among THMs/HAAs formations and differential UV spectroscopy, indicating the formation of DBPs independent of destruction in UV-absorbing sites. In all fractions, concentrations of THMs were higher than those of HAAs. Chlorinated DBP species were dominant over brominated ones due to low bromide concentrations. The results overall suggested that low- or non-UV-absorbing NOM moieties play important roles in the formation of DBPs in waters with low SUVA, low DOC and low bromide levels.     

Prediction of the pH and the temperature-dependent swelling behavior of -alginate hydrogels by artificial neural networks

This paper considers the possibility of using artificial neural network models to identify model for swelling behavior as new techniques. Multi-layer feed-forward, radial basis function and generalized regression neural network models were employed to predict the swelling behaviors of Ca²⁺-alginate hydrogels under different environmental conditions of pH and temperature. The results show that an excellent correlation between the experimental and predicted swelling ratios was obtained by the artificial neural networks. Generalized regression neural network has a better performance than the other neural network models. The absolute mean error, the determination coefficient and the standard error of prediction were used as performance criteria. In addition, the performances of the neural network models are significantly superior compared with those of second-order swelling kinetics, quadratic and cubic models of response surface methodology.     

Preparation and characterization of Cr- and Fe-pillared bentonites by using CrCl3, FeCl3, Cr(acac)3 and Fe(acac)3 as precursors

Four pillared bentonites (Cr-PILB, Cr(acac)₃-PILB, Fe-PILB and Fe(acac)₃-PILB were prepared and characterized by X-ray diffraction (XRD), nitrogen sorption measurements and thermogravimetric (TG) analysis. The surface acidities of the samples and their structures were also investigated in the gas phase adsorption data of pyridine by the aid of FT-IR spectroscopic techniques. The XRD data and FT-IR spectra of the samples reflected mainly the structure of bentonite. The nitrogen adsorption–desorption isotherms of the samples were Type II shaped and showed in general mesoporous structures with pore openings of 4 nm. Two steps mass losses were observed in the TGA thermograms of B, Cr-PILB and Fe-PILB, while three steps mass losses were detected in the case of Cr(acac)₃-PILB and Fe(acac)₃-PILB. IR study by the adsorption of pyridine on the samples showed both Lewis and Brönsted acid sites on their surfaces.     

Three-dimensional application of the Johnson-King turbulence model for a boundary-layer direct method

The Johnson-King turbulence model[1; AIAA Paper 84-0175 (1984)] as extended to three-dimensional flows was evaluated using a finite-difference boundary-layer direct method. Calculations were compared against the experimental data of the well-known van den Berg-Elsenaar[2; Report NLR-TR-72092U (1972)] incompressible flow over an infinite swept-wing, as well as with some other boundary-layer methods. The Johnson-King turbulence model, which includes the non-equilibrium effects in a developing turbulent boundary layer, was found to significantly improve the predictive quality of a direct boundary-layer method. The improvement was especially visible in the computations with increased three-dimensionality of the mean flow, larger integral parameters and decreasing eddy-viscosity and shear-stress magnitudes in the streamwise direction; all in better agreement with the experiment than simple mixing-length-based methods.     

Light‐curing of a sol–gel‐derived silicate‐based epoxy‐functional polymer nanocomposite material system

In an effort to explore the potential of certain types of polymer nanocomposites to be successful candidates as dental restoration/adhesion materials, a Ti‐ or Zr‐containing and organically modified silicate‐based material system with epoxy functionality was prepared by use of a sol–gel synthesis method, and ultraviolet light‐ and visible light (VL)‐curing processes. Comparative influences of certain synthesis/processing parameters on the properties of the system were detailed. It was shown that both Ti‐ and Zr‐containing species could play significant roles in determining the structure and hence the properties of the nanocomposites. VL‐curing was demonstrated to be a relatively advantageous process that could be employed in applications such as dental restoration/adhesion. Moreover, the mechanical properties of the nanocomposites were shown to be promisingly high. Overall observations and results indicated a prospective opportunity for this material system to be utilized in dental restoration/adhesion applications. POLYM. COMPOS., 35:1879–1887, 2014. © 2014 Society of Plastics Engineers