Binders for jute-reinforced unsaturated polyester resin

Reinforcement of polyester resin with jute cloth under constant load is studied, The pretreatment of jute cloth with tetrahydrofuran and the effect of binding properties of poly(vinyl acetate) and acrylic acid and their effect on the impact, tensile, and water absorptions of jute cloth polyester composites are reported and their chemical reactions are discussed.     

Equilibrium,kinetic and thermodynamic study of removal of reactive orange 12 on platinum nanoparticle loaded on activated carbon as novel adsorbent

The proposed research describes the synthesis and characterization of platinum nanoparticles loaded on activated carbon (Pt-NP-AC) and its efficient application as novel adsorbent for efficient removal of reactive orange 12 (RO-12). The influences of effective parameters following the optimization of variables on removal percentages, their value was set as 0.015 g Pt-NP-AC, pH 1, contact time of 13 min. At optimum values of all variables at 25 and 50 mgL⁻¹ of RO-12 enthalpy (ΔH⁰) and entropy (ΔS⁰) changes was found to be 59.89 and 225.076, respectively, which negative value of ΔG⁰ shows a spontaneous nature, and the positive values of ΔH⁰ and ΔS⁰ indicate the endothermic nature and adsorption organized of dye molecule on the adsorbent surface. Experimental data was fitted to different kinetic models including first-order, pseudo-second-order, Elovich and intra-particle diffusion models, and it was seen that the adsorption process follows pseudo-second-order model in consideration to intra-particle diffusion mechanism. At optimum values of all variables, the adsorption process follows the second-order kinetic and Langmuir isotherm model with adsorption capacity 285.143 mg g⁻¹ at room temperature.     

Effect of thermal damage on mechanical behavior and transport properties of self-compacting concrete incorporating polypropylene fibers

Explosive spalling of cementitious composites when it is heated from surface is considered to be the most dangerous effect of damage of concrete structures subjected to fire attack, especially when it occurs in restricted areas such as underground tunnels. The main objective of the study presented in this paper is to investigate the influence of high temperature on mechanical behavior, pore size distribution and transport properties of self-compacting concrete reinforced with polypropylene fibers (PPF). The experiment investigation was carried out using two mixtures with a constant water-to-binder ratio (w/b) of 0.37. Two SCCs mixtures were manufactured using an industrial cements according to European standard EN 197 1: CEM I 52.5?N (Portland cement), the difference between the mixtures is the presence of PPF. The amount of fibers used was fixed in 2?kg/m³, as recommends Eurocode 2 for high performance concrete to avoid explosive spalling. The specimens were subjected to various heating-cooling cycles from the room temperature 20?°C to 200?°C, 300?°C, 400?°C and 500?°C. The chloride resistance of the two SCC produced with the different mixtures in damaged and undamaged state are measured using a chloride migration test accelerated by an external applied electrical field. Intrinsic permeability is measured using the nitrogen gas. Klinkenberg approach is used for the determination of the intrinsic permeability. Torrent permeability measurement method was applied in this article, and a correlation was obtained between measure of intrinsic permeability and the Torrent permeability measurement. Finally, a relationship between thermal damage indicators and the increase in permeability and migration coefficients is also obtained.     

A CUSUM-based method for monitoring simple linear profiles

In most statistical process control applications, the quality of a process or product is characterized by univariate or multivariate quality characteristics and monitored by the corresponding univariate and multivariate control charts, respectively. However, sometimes, the quality of a process or a product is better characterized by a relationship between a response variable and one or more explanatory variables. This relationship, which can be linear, nonlinear, or even a complicated model, is referred to as a profile. So far, several methods have been proposed for monitoring simple linear profiles. In this paper, a new method based on cumulative sum statistics is proposed to enhance monitoring of linear profiles in phase II. The performance of the proposed method is evaluated by average run length criterion. A comprehensive comparison is also conducted between the performance of the proposed method and the existing methods for monitoring simple linear profiles. The results show that the proposed method performs satisfactorily. In addition, the effects of reference value, sample size, and corrected sum of squares of explanatory variables on the performance of the proposed method are investigated.     

Simultaneous minimization of total tardiness and waiting time variance on a single machine by genetic algorithms

This paper considers a single machine scheduling problem, with the objective of minimizing a linear combination of total tardiness and waiting time variance in which the idle time is not allowed. Minimizing total tardiness is always regarded as one of the most significant performance criteria in practical systems to avoid penalty costs of tardiness, and waiting time variance is an important criterion in establishing quality of service (QoS) in many systems. Each of these criteria is known to be non-deterministic polynomial-time hard (NP-hard); therefore, the linear combination of them is NP-hard too. For this problem, we developed a genetic algorithm (GA) by applying its general structure that further improves the initial population, utilizing some of heuristic algorithms. The GA is shown experimentally to perform well by testing on various instances.     

A new link function in GLM-based control charts to improve monitoring of two-stage processes with Poisson response

In this paper, a new procedure is developed to monitor a two-stage process with a second stage Poisson quality characteristic. In the proposed method, log and square root link functions are first combined to introduce a new link function that establishes a relationship between the Poisson variable of the second stage and the quality characteristic of the first stage. Then, the standardized residual statistic, which is independent of the quality characteristic in the previous stage and follows approximately standardized normal distribution, is computed based on the proposed link function. Then, Shewhart and exponentially weighted moving average (EWMA) cause-selecting charts are utilized to monitor standardized residuals. Finally, two examples and a case study with a Poisson response variable are investigated, and the performance of the charts is evaluated by using average run length (ARL) criterion in comparison with the best literature method.     

Influence of Xanthan–Curdlan Hydrogel Complex on Freeze‐Thaw Stability and Rheological Properties of Whey Protein Isolate Gel over Multiple Freeze‐Thaw Cycle

The effect of adding xanthan–curdlan hydrogel complex (XCHC) at 2 concentrations (0.25 and 0.5% w/w) on the freeze‐thaw stability of heat‐induced whey protein isolate (WPI) gel was investigated. Samples were stored at 4 °C for 24 h before subjected to 5 freeze‐thaw cycles alternating between ?16 °C (18 h) and 25 °C (6 h). Adding XCHC to the WPI solution resulted in the reduction of a significant amount of syneresis up to 5 repeated freeze‐thaw cycles. Addition of XCHC decreased the amount of syneresis from 45% in the control sample (pure WPI gel) to 31.82% and 5.44% in the samples containing 0.25% and 0.5% gum, respectively, after the 5th freeze‐thaw cycle. XCHC increased the storage modulus (G′) of the gels and minimized the changes of the G′ values over the 5 freeze‐thaw cycles, indicating improvement of the stability of the system. Furthermore, the minimum protein concentration for gel formation decreased in the presence of the XCHC. Scanning electron microscopy (SEM) images showed that addition of XCHC resulted in the formation of a well‐structured gel with numerous small pores in the network, which consequently improved the water retention ability during the temperature abuses up to 5 freeze‐thaw cycles. These results have important implications for using XCHC in the formulation of the frozen WPI‐based products with improved freeze‐thaw stability and rheological properties.     

Nadir compromise programming: A model for optimization of multi-objective portfolio problem

In problem of portfolio selection, financial Decision Makers (DMs) explain objectives and investment purposes in the frame of multi-objective mathematic problems which are more consistent with decision making realities. At present, various methods have introduced to optimize such problems. One of the optimization methods is the Compromise Programming (CP) method. Considering increasing importance of investment in financial portfolios, we propose a new method, called Nadir Compromising Programming (NCP) by expanding a CP-based method for optimization of multi-objective problems. In order to illustrate NCP performance and operational capability, we implement a case study by selecting a portfolio with 35 stock indices of Iran stock market. Results of comparing the CP method and proposed method under the same conditions indicate that NCP method results are more consistent with DM purposes.     

AMBO: All Members-Based Optimizer for Solving Optimization Problems

There are many optimization problems in different branches of science that should be solved using an appropriate methodology. Population-based optimization algorithms are one of the most efficient approaches to solve this type of problems. In this paper, a new optimization algorithm called All Members-Based Optimizer (AMBO) is introduced to solve various optimization problems. The main idea in designing the proposed AMBO algorithm is to use more information from the population members of the algorithm instead of just a few specific members (such as best member and worst member) to update the population matrix. Therefore, in AMBO, any member of the population can play a role in updating the population matrix. The theory of AMBO is described and then mathematically modeled for implementation on optimization problems. The performance of the proposed algorithm is evaluated on a set of twenty-three standard objective functions, which belong to three different categories: unimodal, high-dimensional multimodal, and fixed-dimensional multimodal functions. In order to analyze and compare the optimization results for the mentioned objective functions obtained by AMBO, eight other well-known algorithms have been also implemented. The optimization results demonstrate the ability of AMBO to solve various optimization problems. Also, comparison and analysis of the results show that AMBO is superior and more competitive than the other mentioned algorithms in providing suitable solution.