Prediction of the Brisance of Energetic Materials

The brisance parameter can be used to show the shattering power of an energetic compound and the speed to reach its peak pressure. It determines the effectiveness with which an explosive can fragment a shell. Nowadays, the sand test or sand crushing test is the preferred method for brisance measurements but there is no reliable method for the prediction of the brisance parameter. In this paper, a method for the prediction of the brisance through sand test for pure and mixed energetic materials as well as aluminized explosives is reported. It is based on the molecular structure of the desired compound and once the conclusion is established any experimental data is redundant. The calculated brisance relative to 2,4,6‐trinitrotoluene (=100) shows good agreement with the measured values.     

Simple Method for Prediction of the Standard Gibbs Free Energy of Formation of Energetic Compounds

A reliable simple method for prediction of the standard Gibbs energy of formation (Δ_fG^θ) of energetic compounds containing nitroaromatic, acyclic, and cyclic nitramine, nitrate ester, and nitroaliphatic compounds is introduced herein. The method is based on the contribution of elemental composition (Δ_fG_elem^θ) and the correcting function for the presence of additive and non‐additive molecular fragments (Δ_fG_corr^θ). In presence of some molecular moieties, Δ_fG_corr^θ may increase or decrease the value of Δ_fG_elem^θ, depending on the intermolecular interactions. The experimental root‐mean‐square error (RMSE) of the novel correlation (22.7 kJ mol⁻¹) is quite good. For some energetic compounds, where the computed values of two complex models of the quantitative structure‐property relationship (QSPR) theory were available, the experimental RMSE developed by the new method is smaller than the values obtained by QSPR method.     

[Hmim][HSO4], a Green and Recyclable Acidic Ionic Liqiud Medium for the One‐Pot Nitration of TADB to HNIW

An efficient and mild procedure for the one‐pot preparation of CL‐20 from TADB in the presence of the Brønsted acidic ionic liquid 1‐methylimidazolium hydrogen sulfate [Hmim][HSO₄] as catalyst was developed. The ionic liquid was stable during the reaction process and could also be reused several times with steady activity. In order to optimize the process parameters to obtain higher yield and purity, a study was carried out with variation of the ionic liquids and some parameters like temperature, mole ratio of [Hmim][HSO₄] and nitric acid. This procedure may be a practical alternative to the existing procedures to meet the nees of academics as well as industry.     

Surface defect detection in tiling Industries using digital image processing methods: Analysis and evaluation

Ceramic and tile industries should indispensably include a grading stage to quantify the quality of products. Actually, human control systems are often used for grading purposes. An automatic grading system is essential to enhance the quality control and marketing of the products. Since there generally exist six different types of defects originating from various stages of tile manufacturing lines with distinct textures and morphologies, many image processing techniques have been proposed for defect detection. In this paper, a survey has been made on the pattern recognition and image processing algorithms which have been used to detect surface defects. Each method appears to be limited for detecting some subgroup of defects. The detection techniques may be divided into three main groups: statistical pattern recognition, feature vector extraction and texture/image classification. The methods such as wavelet transform, filtering, morphology and contourlet transform are more effective for pre-processing tasks. Others including statistical methods, neural networks and model-based algorithms can be applied to extract the surface defects. Although, statistical methods are often appropriate for identification of large defects such as Spots, but techniques such as wavelet processing provide an acceptable response for detection of small defects such as Pinhole. A thorough survey is made in this paper on the existing algorithms in each subgroup. Also, the evaluation parameters are discussed including supervised and unsupervised parameters. Using various performance parameters, different defect detection algorithms are compared and evaluated.     

Stabilization loop of a two axes gimbal system using self-tuning PID type fuzzy controller

The application of inertial stabilization system is to stabilize the sensor's line of sight toward a target by isolating the sensor from the disturbances induced by the operating environment. The aim of this paper is to present two axes gimbal system. The gimbals torque relationships are derived using Lagrange equation considering the base angular motion and dynamic mass unbalance. The stabilization loops are constructed with cross coupling unit utilizing proposed fuzzy PID type controller. The overall control system is simulated and validated using MATLAB. Then, the performance of proposed controller is evaluated comparing with conventional PI controller in terms of transient response analysis and quantitative study of error analysis. The simulation results obtained in different conditions prove the efficiency of the proposed fuzzy controller which offers a better response than the classical one, and improves further the transient and steady-state performance.     

A hybrid electromagnetism algorithm for multi-depot periodic vehicle routing problem

Electromagnetism algorithm is a meta-heuristic proposed to derive approximate solutions for computationally hard problems. In the literature, several successful applications have been reported for graph-based optimization problems, such as scheduling problems. This paper presents a novel hybrid electromagnetism algorithm called SA_EM to solve the multi-depot periodic vehicle routing problem (MDPVRP). The main feature of the hybrid algorithm is to hybridize the solution construction mechanism of the electromagnetism (EM) with simulated annealing (SA). Moreover, during implementing the hybrid algorithm, cyclic transfers, an effective class of neighborhood search is applied. The objective consists of two terms as follows: total traveled distance at each depot and total waiting time of all customers to take service. Distances are assumed Euclidean or straight line. These conditions are exactly consistent with the real-world situation and have little attention in the literature. Finally, the experimental results have shown that the proposed hybrid method is competitive to solve the vehicle routing problem compared with the best existing methods in terms of solution quality.     

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.     

Constrained grinding optimization for time,cost, and surface roughness using NSGA-II

Selection of parameters in machining process significantly affects quality, productivity, and cost of a component. This paper presents an optimization procedure to determine the optimal values of wheel speed, workpiece speed, and depth of cut in a grinding process considering certain grinding conditions. Experimental studies have been carried out to obtain optimum conditions. Mathematical models have also been developed for estimating the surface roughness based on experimental investigations. A non-dominated sorting genetic algorithm (NSGA II) is then used to solve this multi-objective optimization problem. The objectives under investigation in this study are surface finish, total grinding time, and production cost subjected to the constraints of production rate and wheel wear parameters. The Pareto-optimal fronts provide a wide range of trade-off operating conditions which an appropriate operating point can be selected by a decision maker. The results show the proposed algorithm demonstrates applicability of machining optimization considering conflicting objectives.     

Optimisation of probiotic yoghurt production enriched with phytosterols

To optimise the formulation of phytosterol‐enriched probiotic yoghurt, the effect of different concentrations of phytosterols, fat and the probiotic inoculation rate on the survival of Lactobacillus acidophilus LA‐5, Bifidobacterium lactis BB‐12 and physicochemical indices over 14 days of storage was explored. Data analysis showed that the phytosterol concentration and fat content were two crucial factors affecting probiotic viability. Addition of phytosterols had no adverse effect on the overall scores for sensory attributes. Regarding maximisation of viability and storage time, the optimum conditions were found to be fat = 8.07% (w/v), phytosterol = 18 g/L, probiotic inoculation rate = 71.42 mg/L and storage time = 12 days.