Abrasion Resistance of Field-Assisted Ion-Exchanged Glass

The fracture strength of HF-etched samples was measured as a function of field-assisted K-Na ion exchange depth, as well as the severity of abrasion. As expected, the more severe the abrasion, the greater the depth required to make the strength insensitive to abrasion. An abrasion-independent weakening mechanism that increased with exchange depth was also found to be operative.     

MODELING AND PREDICTIVE CONTROL OF MIMO NONLINEAR SYSTEMS USING WIENER-LAGUERRE MODELS

In this work, a Weiner-type nonlinear black box model was developed for capturing dynamics of open loop stable MIMO nonlinear systems with deterministic inputs. The linear dynamic component of the model was parameterized using orthogonal Laguerre filters while the nonlinear state output map was constructed either using quadratic polynomial functions or artificial neural networks. The properties of the resulting model, such as open loop stability and steady-state behavior, are discussed in detail. The identified Weiner-Laguerre model was further used to formulate a nonlinear model predictive control (NMPC) scheme. The efficacy of the proposed modeling and control scheme was demonstrated using two benchmark control problems: (a) a simulation study involving control of a continuously operated fermenter at its optimum (singular) operating point and (b) experimental verification involving control of pH at the critical point of a neutralization process. It was observed that the proposed Weiner-Laguerre model is able to capture both the dynamic and steady-state characteristics of the continuous fermenter as well as the neutralization process reasonably accurately over wide operating ranges. The proposed NMPC scheme achieved a smooth transition from a suboptimal operating point to the optimum (singular) operating point of the fermenter without causing large variation in manipulated inputs. The proposed NMPC scheme was also found to be robust in the face of moderate perturbation in the unmeasured disturbances. In the case of experimental verification using the neutralization process, the proposed control scheme was found to achieve much faster transition to a set point close to the critical point when compared to a conventional gain-scheduled PID controller.     

INFLUENCE OF DESIGN AND OPERATING CONDITIONS ON THE SYSTEM PERFORMANCE OF A TWO-STAGE ADSORPTION CHILLER

This article aims at clarifying the possible design and operating conditions for silica gel-water adsorption refrigeration cycles driven by near-ambient temperature waste heat sources (between 45 and 75°C) with relatively small regenerating temperature lifts (15 to 45 K). A two-stage silica gel-water advanced adsorption chiller is introduced and a simulation model of the chiller was developed to analyze the influence of operating and design conditions on the system performance (coefficient of performance, COP, and cooling capacity). It was hypothesized that the proposed chiller can be driven by low temperature waste heat at 55°C to produce effective cooling. Simulation results show that the operating conditions such as cycle time and hot and cooling water inlet temperature have an influential effect on cooling capacity and COP. COP is proportional to cycle time and heat transfer coefficient as well as inversely proportional to the cooling water inlet temperature, while there are optimum values of hot water temperature and silica gel weight for maximum COP. Cooling capacity mainly improves with the addition of silica gel weight and decreases as cooling water temperature increases. Simulation results also revealed that the system performance can be improved significantly by setting the design and operating conditions optimally.     

Absorption of carbon dioxide in alkanolamines in the presence of fine activated carbon particles

The rates of absorption of CO₂ into water and 0.1 kmol/m³ aqueous solutions of MEA, DEA and AMP were measured in a stirred cell with a flat gas-liquid interface in the presence of fine activated carbon particles. Experiments showed that the rates of absorption increased significantly with increases in the loading of activated carbon up to about 6 kg/m³ and thereafter remained constant.     

Harmony search algorithm for infinite impulse response system identification

In this paper, optimal sets of filter coefficients are searched by a meta-heuristic optimization technique called Harmony Search (HS) algorithm for infinite impulse response (IIR) system identification problem. For different optimization problems, HS algorithm undergoes three basic rules; namely Random Selection (RS), Harmony Memory Consideration (HMC), and Pitch Adjustment (PA) rules, which are inspired from the process that the musicians use to improvise a perfect state of harmony with the consummate skill of blending notes in tune. With the help of the properly selected control parameters, a perfect balance is achieved in exploration and exploitation in searching phases. The detailed analysis of simulation results emphasizes the strength of HS algorithm to find the near-global optimal solution, quality of convergence profile and the speed of convergence while tested against standard benchmark examples for same and reduced order models.     

Influence of Distributed Particle Size on the Determination of the Parabolic Rate Constant for Oxidation by the Powder Method

The established analysis for the study of oxidation using powder specimens is based on the assumption of monosized particles. The experiments, however, are conducted on powders with a distributed particle size. Here we present a statistical approach for the calculation of the rate constant for oxidation. The results of the analysis are applied to new data on oxidation studies of dense powders of silicon carbonitride amorphous ceramics. The monosized model requires a wide range of values for the rate constant to fit the short term and the long-term data, leading to considerable ambiguity in the estimate of the parabolic rate constant, k _p, for oxidation. In contrast the statistical model fits over the entire range of data, yielding a much more reliable value for k _p. For example, the monosized approach gave a value in the range 19.7 × 10⁻¹⁸ < k _p < 2.7 × 10⁻¹⁸ m²/s. In contrast, the statistical model yields a specific value of 4.5 × 10⁻¹⁸ m²/s.     

Estimation of gross calorific value of coals using artificial neural networks

The gross calorific value (GCV) is an important property defining the energy content and thereby efficiency of fuels, such as coals. There exist a number of correlations for estimating the GCV of a coal sample based upon its proximate and/or ultimate analyses. These correlations are mainly linear in character although there are indications that the relationship between the GCV and a few constituents of the proximate and ultimate analyses could be nonlinear. Accordingly, in this paper a total of seven nonlinear models have been developed using the artificial neural networks (ANN) methodology for the estimation of GCV with a special focus on Indian coals. The comprehensive ANN model developed here uses all the major constituents of the proximate and ultimate analyses as inputs while the remaining six sub-models use different combinations of the constituents of the stated analyses. It has been found that the GCV prediction accuracy of all the models is excellent with the comprehensive model being the most accurate GCV predictor. Also, the performance of the ANN models has been found to be consistently better than that of their linear counterparts. Additionally, a sensitivity analysis of the comprehensive ANN model has been performed to identify the important model inputs, which significantly affect the GCV. The ANN-based modeling approach illustrated in this paper is sufficiently general and thus can be gainfully extended for estimating the GCV of a wide spectrum of solid, liquid and gaseous fuels.     

Polydimethylsiloxane based polyurethane and its composite with layered double hydroxide: Synthesis and its thermal properties

This investigation reports the synthesis of a new class of polyurethane (PU) based on bis(hydroxyalkyl) polydimethylsiloxane (PDMS) as diol and isophorone diisocyanate as diisocyanate followed by the preparation of PU/layered double hydroxide (PU/LDH) nanocomposite via ex-situ technique. Nuclear magnetic resonance and Fourier-transform infrared spectroscopy studies confirm the formation of PU and incorporation of PDMS into the PU backbone. Thermogravimetry analysis revealed that thermal stability of the composite improves significantly with incorporation of LDH into the PU matrix. This may be accredited to the barrier effect rendered by the LDH layers. Differential scanning calorimetry study reveals that with the incorporation of LDH, glass transition temperature (T_g) of the composite increases for an optimum level of loading beyond which it remains constant.     

Study of the antiferromagnetic phase in Sm(Mn1−xCrx)2Ge2

Magnetic and thermal expansion measurements have been carried out on the polycrystalline Sm(Mn_1−xCr_x)₂Ge₂ samples to see how the antiferromagnetie (AFMII) region in SmMn₂Ge₂ is affected by Cr substitution. It is found that the antiferromagnetic region disappears for samples with less than 2 at.% of Cr. Sharp changes in the thermal expansivity (Δl/l) at FMI–AFMII and AFMII–FMII transitions are observed, indicating first order transitions. The decrease in relative thermal expansivity at the two transitions with the increase of Cr concentration is related to the decrease in the stability and the temperature-range of the AFMII phase observed in magnetization measurements. A spin reorientation transition (T_SR) has been observed for x=0, at 148 K. It is found that the T_SR increases with the increase of Cr concentration. A magnetic phase diagram as a function of Cr concentration in Sm(Mn_1−xCr_x)₂Ge₂ has been constructed.