Synergistic effects of modified TiO2/multifunctionalized graphene oxide nanosheets as functional hybrid nanofiller in enhancing the interface compatibility of PLA/starch nanocomposites

The aim of this study is to investigate the synergistic effects of modified TiO₂/multifunctionalized graphene oxide nanosheets at different ratios on the interface compatibility between starch and poly(lactic acid) (PLA). To this end, silanylated nano-TiO₂ (MTiO₂, 1 and 2%) and alkylated maleic anhydride grafted graphene oxide (f-GO, 0.1, 0.2, and 0.4%) at different combinations are blended with the PLA-starch composites using solution blending technique. Then, the synergistic effects of MTiO₂ and f-GO on PLA/starch matrix are investigated in terms of the morphology, crystallinity, structural characterization, thermal stability, dynamic mechanical, and antiaging properties, and the related mechanisms. The Raman and Fourier transform infrared spectroscopy spectra verify the successful synthesis of the two modified nanofillers (f-GO and MTiO₂) and the formation of strong hydrogen bond within the PLA-starch nanocomposites. Due to the strong interfacial interaction and the synergistic effect from the combination of 1% MTiO₂ and 0.2% f-GO, obvious improvement was observed in PLA-starch versus other nanocomposites in terms of morphology, thermal stability, surface hydrophobicity, storage modulus, ultraviolet-shielding capacity, and aging-resistance. Furthermore, differential scanning calorimeter (DSC), isothermal crystallization kinetic, and X-ray diffraction analysis demonstrate that f-GO and the M-TiO₂ significantly synergize in enhancing the crystallization rate and crystallinity of PLA/starch matrix. These results provide novel insights for constructing high-performance nanocomposites and facilitate their applications in food packaging.     

Human mobility synthesis using matrix and tensor factorizations

Human mobility prediction is of great advantage in route planning and schedule management. However, mobility data is a high-dimensional dataset in which multi-context prediction is difficult in a single model. Mobility data can usually be expressed as a home event, a work event, a shopping event and a traveling event. Previous works have only been able to learn and predict one type of mobility event and then integrate them. As the tensor model has a strong ability to describe high-dimensional information, we propose an algorithm to predict human mobility in tensors of location context data. Using the tensor decomposition method, we extract human mobility patterns with multiple expressions and then synthesize the future mobility event based on mobility patterns. The experiment is based on real-world location data and the results show that the tensor decomposition method has the highest accuracy in terms of prediction error among the three methods. The results also prove the feasibility of our multi-context prediction model.     

Improving the multi-objective evolutionary optimization algorithm for hydropower reservoir operations in the California Oroville–Thermalito complex

This study demonstrates the application of an improved Evolutionary optimization Algorithm (EA), titled Multi-Objective Complex Evolution Global Optimization Method with Principal Component Analysis and Crowding Distance Operator (MOSPD), for the hydropower reservoir operation of the Oroville–Thermalito Complex (OTC) – a crucial head-water resource for the California State Water Project (SWP). In the OTC's water-hydropower joint management study, the nonlinearity of hydropower generation and the reservoir's water elevation–storage relationship are explicitly formulated by polynomial function in order to closely match realistic situations and reduce linearization approximation errors. Comparison among different curve-fitting methods is conducted to understand the impact of the simplification of reservoir topography. In the optimization algorithm development, techniques of crowding distance and principal component analysis are implemented to improve the diversity and convergence of the optimal solutions towards and along the Pareto optimal set in the objective space. A comparative evaluation among the new algorithm MOSPD, the original Multi-Objective Complex Evolution Global Optimization Method (MOCOM), the Multi-Objective Differential Evolution method (MODE), the Multi-Objective Genetic Algorithm (MOGA), the Multi-Objective Simulated Annealing approach (MOSA), and the Multi-Objective Particle Swarm Optimization scheme (MOPSO) is conducted using the benchmark functions. The results show that best the MOSPD algorithm demonstrated the best and most consistent performance when compared with other algorithms on the test problems. The newly developed algorithm (MOSPD) is further applied to the OTC reservoir releasing problem during the snow melting season in 1998 (wet year), 2000 (normal year) and 2001 (dry year), in which the more spreading and converged non-dominated solutions of MOSPD provide decision makers with better operational alternatives for effectively and efficiently managing the OTC reservoirs in response to the different climates, especially drought, which has become more and more severe and frequent in California.     

Maneuverability modeling and trajectory tracking for fish robot

This study develops a 6-DOF mathematical model for a robotic fish that considers surge, sway, heave, roll, pitch, and yaw. The model considers the conditions of a fish swimming in ocean current perturbations similar to the ocean current perturbations of the slender-body autonomous underwater vehicles. For swimming and turning behaviors, a nonlinear, dynamic, carangiform locomotion model is derived by using a planar four-link model. A 2-DOF barycenter mechanism is proposed to provide body stabilization and to serve as an actuating device for active control design. A barycenter control scheme is developed to change the center of gravity of the robot fish body by moving balancing masses along two axes. The projected torque on x and y axes propel pitch and roll angles to the desired settings. A Stabilizing controller, fish-tail mechanism, rigid body dynamics, and kinematics are incorporated to enable the fish robot to move in three dimensional space. Simulation results have demonstrated maneuverability and control system performance of the developed controller which is proposed to conduct path tracking of the robot fish as it swims under current perturbations.     

Improved synergetic excitation control for transient stability enhancement and voltage regulation of power systems

This paper proposes decentralized improved synergetic excitation controllers (ISEC) for synchronous generators to enhance transient stability and obtain satisfactory voltage regulation performance of power systems. Each generator is considered as a subsystem, for which an ISEC is designed. According to the control objectives, a manifold, which is a linear combination of the deviation of generator terminal voltage, rotor speed and active power, is chosen for the design of ISEC. Compared with the conventional synergetic excitation controller (CSEC), a parameter adaptation scheme is proposed for updating the controller parameter online in order to improve the transient stability and voltage regulation performance simultaneously under various operating conditions. Case studies are undertaken on a single-machine infinite-bus power system and a two-area four-machine power system, respectively. Simulation results show the ISEC can provide better damping and voltage regulation performance, compared with the CSEC without parameter adaptation scheme and the conventional power system stabilizer.     

Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.     

Performance improvement of conventional and inverted polymer solar cells with hydrophobic fluoropolymer as nonvolatile processing additive

The morphology of the photoactive layer critically affects the performance of the bulk heterojunction polymer solar cells (PSCs). To control the morphology, we introduced a hydrophobic fluoropolymer polyvinylidene fluoride (PVDF) as nonvolatile additive into the P3HT:PCBM active layer. The effect of PVDF on the surface and the bulk morphology were investigated by atomic force microscope and transmission electron microscopy, respectively. Through the repulsive interactions between the hydrophilic PCBM and the hydrophobic PVDF, much more uniform phase separation with good P3HT crystallinity is formed within the active layer, resulting enhanced light harvesting and improved photovoltaic performance in conventional devices. The PCE of the conventional device can improve from 2.40% to 3.07% with PVDF additive. The PVDF distribution within the active layer was investigated by secondary ion mass spectroscopy, confirming a bottom distribution of PVDF. Therefore, inverted device structure was designed, and the PCE can improve from 2.81% to 3.45% with PVDF additive. Our findings suggest that PVDF is a promising nonvolatile processing additive for high performance polymer solar cells.     

Lead-free sodium niobate nanowires with strong piezo-catalysis for dye wastewater degradation

In this work, the hydrothermally-synthesized sodium niobate nanowires were used to decompose Rhodamine B dye solution through the piezo-catalytic effect. With the sodium niobate catalyst, a high piezo-catalytic degradation ratio of ～80% was achieved under the excitation of vibration for the Rhodamine B dye solution (～5?mg/l). These active species in the catalytic process, hydroxyl radicals and superoxide radicals with the strong oxidation ability, were also observed, which confirmed the key role of piezoelectric effect for piezo-catalysis. The piezo-catalysis of sodium niobate nanowires provides a high-efficiency and reusable tool in application in depredating the dye wastewater.     

Electromagnetism-like algorithms for optimized tool path planning in 5-axis flank machining

Optimization of tool path planning using metaheuristic algorithms such as ant colony systems (ACS) and particle swarm optimization (PSO) provides a feasible approach to reduce geometrical machining errors in 5-axis flank machining of ruled surfaces. The optimal solutions of these algorithms exhibit an unsatisfactory quality in a high-dimensional search space. In this study, various algorithms derived from the electromagnetism-like mechanism (EM) were applied. The test results of representative surfaces showed that all EM-based methods yield more effective optimal solutions than does PSO, despite a longer search time. A new EM-MSS (electromagnetism-like mechanism with move solution screening) algorithm produces the most favorable results by ensuring the continuous improvement of new searches. Incorporating an SPSA (simultaneous perturbation stochastic approximation) technique further improves the search results with effective initial solutions. This work enhances the practical values of tool path planning by providing a satisfactory machining quality.