Stable haptic rendering in interactive virtual control laboratory

Stable control of haptic interfaces is one of the most important challenges in haptic simulations, because any instability of a haptic interface can cause it to get far from the realistic sense. In this paper, the control strategies employed for a stable haptic rendering in an interactive virtual control laboratory are presented. In this interactive virtual laboratory, there are different scenarios to teach the control concepts, in which a haptic interface is used in the two cases of force control and position control. In this regard, two control strategies are employed to avoid instability. An energy-compensating controller is utilized to remove energy leakage. Besides, a fuzzy impedance control is used along with the energy-compensating controller for the position control scenarios. The results obtained indicate the proposed approaches practically guarantee the stability of the haptic interface for an educational application in practice.     

Modeling and optimization of lipase‐catalyzed synthesis of dilauryl adipate ester by response surface methodology

BACKGROUND: Adipate esters are used as low‐temperature and low‐viscosity plasticizers for polyvinyl chloride and its copolymers. In this work, optimization of lipase‐catalyzed production of dilauryl adipate was carried out using response surface methodology (RSM) based on a four‐factor‐five‐level central composite rotatable design (CCRD). Immobilized lipase from Candida antarctica (Novozym 435) was used as catalyst in this reaction. Various reaction parameters affecting the synthesis of adipate ester, including alcohol/acid molar ratio, amount of enzyme, temperature and reaction time, were investigated. RESULTS: Statistical analysis showed that the amount of enzyme was less significant than the other three factors. The optimal conditions for the enzymatic reaction were obtained at 5.7:1 substrate molar ratio using 0.18 g of enzyme at 53.1 °C for 282.2 min. Under these conditions the esterification percentage was 96.0%. CONCLUSIONS: The results demonstrated that response surface methodology can be applied effectively to optimize the lipase‐catalyzed synthesis of adipate ester. The optimum conditions can obtained be used to scale up the process. Copyright © 2008 Society of Chemical Industry     

Amperometric Determination of Quercetin in Some Foods by Magnetic Core/Shell Fe<Subscript>3</Subscript>O<Subscript>4</Subscript>@ZnO Nanoparticles Modified Glassy Carbon Electrode

In this paper, Fe₃O₄@ZnO core/shell magnetic nanoparticles (MNPs) have been synthesized by a simple method, to modify carbon paste/glassy carbon electrode and improve its efficiency for determination of quercetin. The synthesized MNPs were characterized by X-ray powder diffraction (XRD), transmission electronic microscope (TEM), and scanning electronic microscope (SEM). SEM and TEM results show that the prepared Fe₃O₄@ZnO MNPs are made of the spherical shape particles with an average size of about 15 nm. The electrochemical behavior of quercetin at the surface of modified electrode was investigated. Under the optimal conditions, a linearity range of quercetin was 7.9?×?10^?7 to 6.1?×?10^?5 mol/L (0.24–18.44 mg/L) with detection limit (S/N?=?3) and sensitivity of 0.16 μmol/L (0.048 mg/L) and 0.04 μA/μM, respectively. The validated method was applied successfully for determination of quercetin in some foods and human breast milk.     

THERMO-HYDRAULIC BEHAVIOR MODELING OF PASSIVE HEAT TRANSFER ENHANCEMENT TECHNIQUES USING A SOFT COMPUTING APPROACH

The main aim of this research is to demonstrate effectiveness of soft computing techniques in thermo-hydraulic behavior modeling of passive heat transfer enhancement (HTE) techniques. An artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS), two effective modeling methods, have been used to model Nusselt numbers and friction factors of wire coil and twisted tape inserts in various flow regimes. The experimental data sets were utilized for training and validation of these models, and their results were compared with the corresponding correlations. The mean relative error (MRE) between the predicted results and experimental data of ANN and ANFIS models were found to be less than 3% and 1.5% for thermo-hydraulic behavior modeling of wire coil and twisted tape inserts, respectively. Depending on model complexity, performance of both ANN and ANFIS models was found to be superior to that of the corresponding power-law regressions. Hence, application of the soft computing approach to predict the performance of thermal systems in engineering applications is recommended.     

Long-term corrosion resistance of zinc-rich paint using functionalised multi-layer graphene-tripolyphosphate: in situ creation of zinc phosphate as corrosion inhibitor

ABSTRACT

This study investigates the effect of hybrid multilayer graphene-tripolyphosphate on long-term corrosion protection efficiency of zinc-rich paint. The hybrid nanomaterial as a corrosion resistance modifier was prepared trough a simple method by the addition of sodium tripolyphosphate aqueous solution to a dispersed multi-layer graphene in water/ethanol during stirring. The performance of the hybrid nanomaterial was studied by salt spray, electrochemical impedance spectroscopy, scanning electron microscopy, X-ray diffraction, cathodic delamination and pull-off adhesion test. The experimental results showed that in the presence of 1?wt-% of the hybrid nanomaterial, cathodic protection duration increased from 28 days to more than 50 days. The improvement in the barrier property and the cathodic delamination resistance was significant in the presence of the nanomaterial after two years long-term study. X-ray diffraction analysis showed that the formation of zinc phosphate was responsible for the higher corrosion protection efficiency.     

Modeling of membrane bioreactor treating hypersaline oily wastewater by artificial neural network

A membrane sequencing batch reactor (MSBR) treating hypersaline oily wastewater was modeled by artificial neural network (ANN). The MSBR operated at different total dissolved solids (TDSs) (35,000; 50,000; 100,000; 150,000; 200,000; 250,000 mg/L), various organic loading rates (OLRs) (0.281, 0.563, 1.124, 2.248, and 3.372 kg COD/(m³ day)) and cyclic time (12, 24, and 48 h). A feed-forward neural network trained by batch back propagation algorithm was employed to model the MSBR. A set of 193 operational data from the wastewater treatment with the MSBR was used to train the network. The training, validating and testing procedures for the effluent COD, total organic carbon (TOC) and oil and grease (O&G) concentrations were successful and a good correlation was observed between the measured and predicted values. The results showed that at OLR of 2.44 kg COD/(m³ day), TDS of 78,000 mg/L and reaction time (RT) of 40 h, the average removal rate of COD was 98%. In these conditions, the average effluent COD concentration was less than 100 mg/L and met the discharge limits.     

Maximum allowable fouling detection in industrial fired heater furnaces

Journal of Mechanical Science and Technology - Fouling is one the most serious problems in refineries that can have irreparable consequences. In this study, fouling detection inside the tubes in...     

Biological treatment of high salinity produced water by microbial consortia in a batch stirred tank reactor: Modelling and kinetics study

This study was performed to evaluate the potential of acclimated halophilic microorganisms, commercial microorganisms, and microorganisms from polluted soil to degrade crude oil in high salinity oily wastewater (synthetic produced water) at different salt concentrations ranging from zero to 250,000?mg?L^?1 of total dissolved solids (TDS). The highest degradation of crude oil (>60%) was found for acclimated halophilic microorganisms at TDS of 35,000?mg?L^?1. An increase in the TDS concentrations above 145,000?mg?L^?1 leads to a significant decrease in the growth of microorganisms. The results showed that efficiency of the commercial microorganisms was less than the acclimated halophilic microorganisms. The oil biodegradation followed substrate inhibition kinetics and the specific growth rate were fitted to the Haldane model. The biokinetic constants for the saline oily water at TDS of 35,000?mg?L^?1, i.e., Y, K_s, µ_max, and 1/K_i, were 0.21?mg?MLSS/mg crude oil, 0.27?mg?L^?1, 0.019?h^?1, and 0.002?mg?L^?1, respectively.