A new metaheuristic for optimization: Optics inspired optimization (OIO)

Due to the law of reflection, a concave reflecting surface/mirror causes the incident light rays to converge and a convex surface/mirror causes the light rays to reflect away so that they all appear to be diverging. These converging and diverging behaviors cause that the curved mirrors show different image types depending on the distance between the object and the mirror. We model such optical phenomena metaphorically into the searching process of numerical optimization by a new algorithm called optics inspired optimization (OIO). OIO treats the surface of the numerical function to be optimized as a reflecting surface in which each peak is assumed to reflect as a convex mirror and each valley to reflect as a concave one. Each individual is assumed to be an artificial object (or light point) that its artificially glittered ray is reflected back by the function surface, given that the surface is convex or concave, and the artificial image is formed (a candidate solution is generated within the search domain) based on the mirror equations adopted from physics of optics. Besides OIO, we introduce different variants of it, called ROIO (Rotation based OIO), and COIO (Convex combination based OIO) algorithms and conduct an extensive computational effort to find out the merit of the new algorithms. Our comparisons on benchmark test functions and a real world engineering design application (i.e., optimization of a centrifuge pump) demonstrate that the new algorithms are efficient and compete better than or similar to most of state of the art optimization algorithms with the advantage of accepting few input parameters.     

Optimal resilient power grid operation during the course of a progressing wildfire

We study a two-stage stochastic and nonlinear optimization model for operating a power grid exposed to a natural disaster. Although this approach can be generalized to any natural hazard of continuous (and not instantaneous) nature, our focus is on wildfires. We assume that an approaching wildfire impacts the power grid by reducing the transmission capacity of its overhead lines. At the time when proactive decisions have to be taken, the severity of the wildfire is not known. This introduces uncertainty. In this paper, we extend previous work by more realistically capturing this uncertainty and by strengthening the mathematical programming formulation through standard reformulation techniques. With these reformulation techniques, the resulting two-stage, convex mixed-integer quadratically constrained programming formulation can be efficiently solved using commercial quadratic programming solvers as demonstrated on a case study on a modified version of the IEEE 123-bus test system with 100 scenarios. We also quantify the uncertainties through a second case study using the following three standard metrics of two-stage stochastic optimization: the expected value of perfect information, the expected result of using the expected value solution and the value of the stochastic solution.     

Quality and Emulsion Stability of Milk from Ettawah Crossed Bred Goat During Frozen Storage

Goat milk has specific chemical composition and physical properties. The purpose of this study was to investigate the change of milk quality and emulsion stability during 60 d frozen storage. Milk sample was taken from three Ettawah Crossedbred goats that were divided into three groups. Samples were frozen and stored for 0, 30 and 60 days. At the end of each storage periode, milk sample was thawed in the refrigerator and analyzed for total number of bacteria, chemical (acidity, pH, free fatty acids), physical (alcohol test, clot on boiling test) quality, and emulsion stability. The microbiological and chemical data were analyzed statistically using one way ANOVA, whereas physical quality and emulsion stabilty were expressed qualitatively. There were no change in the total bacteria, acidity, pH and free fatty acid (FFA) of milk during storage, whereas the assessment by 70% alcohol showed positive since 0 d. Emulsions stability changed after 30 d of storage. While, the clot on boiling (COB) test of milk was positive at 60 d of storage. Recommendation is frozen storage of goat milk should not longer than 30 d.     

An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

Fault detection, isolation and optimal control have long been applied to industry. These techniques have proven various successful theoretical results and industrial applications. Fault diagnosis is considered as the merge of fault detection (that indicates if there is a fault) and fault isolation (that determines where the fault is), and it has important effects on the operation of complex dynamical systems specific to modern industry applications such as industrial electronics, business management systems, energy, and public sectors. Since the resources are always limited in real-world industrial applications, the solutions to optimally use them under various constraints are of high actuality. In this context, the optimal tuning of linear and nonlinear controllers is a systematic way to meet the performance specifications expressed as optimization problems that target the minimization of integral- or sum-type objective functions, where the tuning parameters of the controllers are the vector variables of the objective functions. The nature-inspired optimization algorithms give efficient solutions to such optimization problems. This paper presents an overview on recent developments in machine learning, data mining and evolving soft computing techniques for fault diagnosis and on nature-inspired optimal control. The generic theory is discussed along with illustrative industrial process applications that include a real liquid level control application, wind turbines and a nonlinear servo system. New research challenges with strong industrial impact are highlighted.     

Improvement of dielectric breakdown strength and energy storage performance in Er2O3–modified 0.95Sr0.7Ba0.3Nb2O6-0.05CaTiO3 lead-free ceramics

In this study, 0.95?Sr_0.7Ba_0.3Nb₂O₆-0.05CaTiO₃-x wt% Er₂O₃ ceramics (SBNCTEx; x?=?0–5) were synthesized using traditional solid-state method, and we investigated the microstructure, energy storage properties as well as the relationship between dielectric breakdown strength and interfacial polarization. As compared with pure 0.95?Sr_0.7Ba_0.3Nb₂O₆-0.05CaTiO₃ ceramics, the Er₂O₃ dopants suppressed the grain growth of SBNCTEx, and the doped ones showed the dense microstructure. The secondary phase was found for x?≥?1 according to the EDS results, and the influence of the secondary phase on relative dielectric breakdown strength has also been studied. The dielectric breakdown strength increased from 18.1?kV/mm to 34.4?kV/mm, which is good for energy storage. The energy storage density of 0.28?J/cm³ and the energy storage efficiency of 91.4% were obtained in the SBNCTE5 ceramics. The results indicate that SBNCTE ceramics can be used as energy storage capacitors.     

The effect of charge on the dihydrogen storage capacity of Sc2–C6H6

The effect of charge on the dihydrogen storage capacity of Sc₂–C₆H₆ has been investigated at B3LYP-D3/6-311G(d,p) level. The neutral system Sc₂–C₆H₆ can store 8H₂ with gravimetric density of 8.76 wt %, and one H₂ dissociates and bonds atomically on the scandium atom. The adsorption of 8H₂ on Sc₂–C₆H₆ is energetically favorable below 155 K. The atom-centered density matrix propagation (ADMP) molecular dynamics simulations show that Sc₂–C₆H₆ can adsorb 3H₂ within 1000 fs at 300K. Compared with Sc₂–C₆H₆, the charged systems can adsorb more hydrogen molecules with higher gravimetric density, and all the H₂ are adsorbed in the molecular form. The gravimetric densities of Sc₂–C₆H₆⁺ and Sc₂–C₆H₆²⁺ are 9.75 and 10.71 wt%. Moreover, the maximum adsorption of charged systems are favorable in wider temperature range. Most importantly, the ADMP-MD simulations indicate that Sc₂–C₆H₆²⁺ can adsorb 6 hydrogen molecules within 1000 fs at 300K. It can be found that the gravimetric density (6.72 wt%) of Sc₂–C₆H₆²⁺ still exceeds the target of US Department of Energy (DOE) under ambient conditions.     

Parameter estimation for a morphochemical reaction-diffusion model of electrochemical pattern formation

The process of electrodeposition can be described in terms of a reaction-diffusion partial differential equation (PDE) system that models the dynamics of the morphology profile and the chemical composition. Here we fit such a model to the different patterns present in a range of electrodeposited and electrochemically modified alloys using PDE constrained optimization. Experiments with simulated data show how the parameter space of the model can be divided into zones corresponding to the different physical patterns by examining the structure of an appropriate cost function. We then use real data to demonstrate how numerical optimization of the cost function can allow the model to fit the rich variety of patterns arising in experiments. The computational technique developed provides a potential tool for tuning experimental parameters to produce desired patterns.     

Hydrogenation process in multiphase alloys of Ti-Zr-Mn-V system on the example of Ti42.75Zr27Mn20.25V10 alloy

The influence of phase composition and microstructure of Ti_42.75Zr₂₇Mn_20.25V₁₀ alloy on its hydrogenation kinetic and phase composition of hydrogenated product was studied. It is established that the process of dissociation of hydrogen molecules begins on the surface of Laves phase crystallites. The dissolution of atomic hydrogen in the material volume leads to the formation of cracks in the intermetallic crystallites, which further appear as additional centers of dissociation of hydrogen molecules and noticeably accelerate the diffusion of hydrogen into the bulk material. It was shown that the Laves phase acts as a donor of atomic hydrogen for the BCC solid solution during hydrogenation of two-phase structure, initiating intensive hydrogenation of the BCC phase at room temperature.     

Polyetherimide-LaNi5 composite films for hydrogen storage applications

This study investigates the preparation of polyetherimide (PEI) – LaNi₅ composites films for hydrogen storage. Prior to the polymer addition, LaNi₅ was ball-milled at different conditions (250, 350, and 450 RPM) and annealed at 500 °C for 1 h under vacuum. The composites were produced with BM-LaNi₅-350 (PEI/LaNi₅-350) and annealed BM-LaNi₅-350 (PEI/LaNi₅-350-TT). Membranes were successfully produced through solvent casting assisted by an ultrasonic bath. The particles dispersion and the film morphology did not change after hydrogenation cycles. In the H₂ sorption experiments at 43 °C and 20 bar, the films stored H₂ without incubation time; both samples reached a capacity of ~0.6 wt%. The H₂ sorption kinetics of PEI/LaNi₅-350 was comparable to that of BM-LaNi₅-350, whereas PEI/LaNi₅-350-TT presented significantly slower kinetics. LaNi₅ oxidation was hindered by PEI, showing that it can be explored to improve metal hydrides air resistance. The results demonstrated that PEI films filled with LaNi₅ are promising materials for hydrogen storage.