An experimental study on polymer cathode materials in lead-acid battery energy storage systems

Davoud Jahani,Amin Nazari,Mohammadreza Yazdan Panah,Nader Javani,Fatemeh Moharaminezhad 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.8

The replacement of lead grids with acrylonitrile butadiene styrene (ABS) polymer grids in the negativeelectrode of lead-acid batteries was studied experimentally, while the positive electrode remained unchanged. A polymergrid was activated by nickel plating using a chemical solution, and then coated with chrome and copper conductiveplating. The polymer grid was coated with a layer of lead. Using a lead-coated polymer grid, a 30-amp 12-voltbattery was produced and tested, and the results were compared with a 30-hour production line lead-acid battery. Theresults show that the polymer grid has a strong ability to generate an appropriate voltage in the charge and dischargecycle and create a stable capacity. The results also show the polymer grid weight has decreased significantly (about50%) compared to the conventional lead grid. In this work, the adhesion of a negative paste to the surface of the polymergrid covered with the lead-exposed expand grid was studied, and the results show that the polymer grid canadhere to the negative dough perfectly.

A New Adaptive Importance Sampling Monte Carlo Method for Structural Reliability

Ehsan Jahani,Mohsen A. Shayanfar,Mohammad A. Barkhordari 대한토목학회 2013 KSCE Journal of Civil Engineering Vol.17 No.1

Monte Carlo simulation is a useful method for reliability analysis. But in Monte Carlo, a large number of simulations are required to assess small failure probabilities. Many methods, such as Importance sampling, have been proposed to reduce the computational time. In this paper, a new importance sampling Monte Carlo method is proposed that reduces the numbers of calculation of the limit state function. On the other hand, the proposed algorithm does not need the knowledge about the position of the design point or the shape of the limit state function. The key-idea of the proposed algorithm is that the mean of sampling density function is changed throughout the simulation. In fact, in random point generating process each point with lower absolute value of limit state function and nearer distance from space center is considered the mean of the sampling density function. Based on this, the centralization of the sampling will be on the important area.

Comparison of Predictive Models for the Early Diagnosis of Diabetes

Meysam Jahani,Mahdi Mahdavi 대한의료정보학회 2016 Healthcare Informatics Research Vol.22 No.2

Objectives: This study develops neural network models to improve the prediction of diabetes using clinical and lifestyle characteristics. Prediction models were developed using a combination of approaches and concepts. Methods: We used memetic algorithms to update weights and to improve prediction accuracy of models. In the first step, the optimum amount for neural network parameters such as momentum rate, transfer function, and error function were obtained through trial and error and based on the results of previous studies. In the second step, optimum parameters were applied to memetic algorithms in order to improve the accuracy of prediction. This preliminary analysis showed that the accuracy of neural networks is 88%. In the third step, the accuracy of neural network models was improved using a memetic algorithm and resulted model was compared with a logistic regression model using a confusion matrix and receiver operating characteristic curve (ROC). Results: The memetic algorithm improved the accuracy from 88.0% to 93.2%. We also found that memetic algorithm had a higher accuracy than the model from the genetic algorithm and a regression model. Among models, the regression model has the least accuracy. For the memetic algorithm model the amount of sensitivity, specificity, positive predictive value, negative predictive value, and ROC are 96.2, 95.3, 93.8, 92.4, and 0.958 respectively. Conclusions: The results of this study provide a basis to design a Decision Support System for risk management and planning of care for individuals at risk of diabetes.

Identifying the frequency dependent material property of a hydraulic engine mount through an iterative procedure using 3D finite element modeling

Kamal Jahani,Masoud Dehnad 대한기계학회 2014 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.28 No.6

Achieving very restricted noise, vibration and harshness targets in modern vehicles, makes using the hydraulic engine mount crucial. Hydraulic engine mounts have both solid and fluid media in their structures that make their dynamic behavior complex to figure out. Wepresent a three-dimensional model of HEM with using finite element method that encompasses elastomeric material’s nonlinearity andfluid-structure-interaction. Dynamic equivalent modulus of elasticity for elastomeric material is identified through iterative model updatingprocedure. To do model updating, the results (here, namely, natural frequencies and frequency response function graphs) are comparedwith real hydraulic engine mount behavior that derived from modal tests. The results showed that the dynamic characteristic ofelastomeric material is frequency dependent and can be divided into two distinct regions: below 30 Hz (low frequency) and above 30 Hz(high frequency) with different trends.

Voltammetric Determination of Droxidopa in the Presence of Tryptophan Using a Nanostructured Base Electrochemical Sensor

Yaghoubian, Halimeh,Jahani, Shohreh,Beitollahi, Hadi,tajik, Somayeh,Hosseinzadeh, Rahman,Biparva, Pouria The Korean Electrochemical Society 2018 Journal of electrochemical science and technology Vol.9 No.2

A novel carbon paste electrode modified with $Cu-TiO_2$ nanocomposite, 2-(ferrocenylethynyl)fluoren-9-one (2FF) and ionic liquid (IL) (2FF/$Cu-TiO_2$/IL/CPE) was fabricated and employed to study the electrocatalytic oxidation of droxidopa, using cyclic voltammetry (CV), chronoamperometry (CHA) and differential pulse voltammetry (DPV) as diagnostic techniques. It has been found that the oxidation of droxidopa at the surface of modified electrode occurs at a potential of about 295 mV less positive than that of an unmodified CPE. DPV exhibits a linear dynamic range from $5.0{\times}10^{-8}$ to $4.0{\times}10^{-4}M$ and a detection limit of 30.0 nM for droxidopa. Finally this modified electrode was used for simultaneous determination of droxidopa and tryptophan. Also the 2FF/$Cu-TiO_2$/IL/CPE shows excellent ability to determination of droxidopa and tryptophan in real samples.

Reliability sensitivities with fuzzy random uncertainties using genetic algorithm

Parinaz Jafari,Ehsan Jahani 국제구조공학회 2016 Structural Engineering and Mechanics, An Int'l Jou Vol.60 No.3

A sensitivity analysis estimates the effect of the change in the uncertain variable parameter on the probability of the structural failure. A novel fuzzy random reliability sensitivity measure of the failure probability is proposed to consider the effect of the epistemic and aleatory uncertainties. The uncertainties of the engineering variables are modeled as fuzzy random variables. Fuzzy quantities are treated using the ??- cut approach. In fact, the fuzzy variables are transformed into the interval variables using the ??-cut approach. Genetic approach considers different possible combinations within the search domain (??-cut) and calculates the parameter sensitivities for each of the combinations.

Experimental and numerical investigation of bubble nucleation and growth in supercritical CO2-blown poly(vinyl alcohol)

Hamidreza Azimi,Davoud Jahani,Sogand Aghamohammadi,Mohammadreza Nofar 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.8

Bubble nucleation and growth was experimentally and numerically investigated in polyvinyl alcohol (PVA)while using supercritical carbon dioxide (scCO2) as a blowing agent. The solubility and diffusivity of CO2 in PVA werefirst evaluated using a magnetic suspension balance (MSB). Bubble nucleation and growth during foaming was thenexamined using a batch foaming setup equipped with a visualization system. It was observed that the increase indepressurization rate during the foaming increased the average bubble density. The average bubble size during thefoaming was also evaluated through three different numerical models based on the integral method. Moreover, accordingto the bubble pressure profile, the PVA viscosity and CO2 diffusion control the bubble growth. According to thesensitivity analysis, the bubble growth seems to be more affected by the changes of thermodynamic parameters thanthe PVA rheological properties. Eventually, the average CO2 concentration and the critical free energy were numericallycalculated using the classic nucleation theory.

Effects of a specific blend of essential oils on apparent nutrient digestion, rumen fermentation and rumen microbial populations in sheep fed a 50:50 alfalfa hay:concentrate diet

N. Khateri,O. Azizi,Jahani-Azizabadi 아세아·태평양축산학회 2017 Animal Bioscience Vol.30 No.3

Objective: An experiment was conducted to investigate the effects of a specific mixture of essential oils (MEO), containing thyme, clove and cinnamon EO, on rumen microbial fermentation, nutrient apparent digestibility and blood metabolites in fistulated sheep. Methods: Six sheep fitted with ruminal fistulas were used in a repeated measurement design with two 24-d periods to investigate the effect of adding MEO at 0 (control), 0.8, and 1.6 mL/d on apparent nutrient digestibility, rumen fermentation characteristics, rumen microbial population and blood chemical metabolites. Animals were fed with a 50:50 alfalfa hay:concentrate diet. Results: Ruminal pH, total volatile fatty acids (VFA) concentration, molar proportion of individual VFA, acetate: propionate ratio and methane production were not affected with MEO. Relative to the control, Small peptides plus amino acid nitrogen and large peptides nitrogen concentration in rumen fluid were not affected with MEO supplementation; while, rumen fluid ammonia nitrogen concentration at 0 and 6 h after morning feeding in sheep fed with 1.6 mL/d of MEO was lower (p<0.05) compared to the control and 0.8 mL/d of MEO. At 0 h after morning feeding, ammonia nitrogen concentration was higher (p<0.05) in sheep fed 0.8 mL/d of MEO relative to 1.6 mL/d and control diet. Ruminal protozoa and hyper ammonia producing (HAP) bacteria counts were not affected by addition of MEO in the diet. Relative to the control, no changes were observed in the red and white blood cells, hemoglobin, hematocrit, glucose, beta-hydroxybutyric acid, cholesterol, total protein, albumin, blood urea nitrogen and aspartate aminotransferase and alanine aminotransferase concentration. Apparent total tract digestibility of dry matter, crude proten, organic matter, and neutral detergent fiber were not influenced by MEO supplementation. Conclusion:The results of the present study suggested that supplementation of MEO may have limited effects on apparent nutrient digestibility, ruminal fermentation and protozoa and HAP bacteria count, blood cells and metabolites.

Predicting of compressive strength of recycled aggregate concrete by genetic programming

Gholamreza Abdollahzadeh,Ehsan Jahani,Zahra Kashir 사단법인 한국계산역학회 2016 Computers and Concrete, An International Journal Vol.18 No.2

This paper, proposes 20 models for predicting compressive strength of recycled aggregate concrete (RAC) containing silica fume by using gene expression programming (GEP). To construct the models, experimental data of 228 specimens produced from 61 different mixtures were collected from the literature. 80% of data sets were used in the training phase and the remained 20% in testing phase. Input variables were arranged in a format of seven input parameters including age of the specimen, cement content, water content, natural aggregates content, recycled aggregates content, silica fume content and amount of superplasticizer. The training and testing showed the models have good conformity with experimental results for predicting the compressive strength of recycled aggregate concrete containing silica fume.

Improved analytical formulation for Steel-Concrete (SC) composite walls under out-of-plane loads

Saeid Sabouri-Ghomi,Arman Nasri,Younes Jahani,Anjan K. Bhowmick 국제구조공학회 2021 Steel and Composite Structures, An International J Vol.38 No.4

The concept of using Steel-concrete (SC) composite walls as retaining walls has recently been introduced by the authors and their effectiveness of resisting out-of-plane loads has also been demonstrated. In this paper, an improved analytical formulation based on partial interaction theory, which has previously been developed by the authors, is presented. The improved formulation considers a new loading condition and also accounts for cracking in concrete to simulate the real conditions. Due to a limited number of test specimens, further finite element (FE)simulations are performed in order to verify the analytical procedure in more detail. It is observed that the results from the improved analytical procedure are in excellent agreement with both experimental and numerical results. Moreover, a detailed parametric study is conducted using the developed FE model to investigate effects of different parameters, such as distance between shear connectors, shear connector length, concrete strength, steel plate thickness, concrete cover thickness, wall’s width to thickness ratio, and wall’s height to thickness ratio, on the behavior of SC composite walls subjected to out-of-plane loads.