Concurrent multi-scale design optimization of composite frame structures using the Heaviside penalization of discrete material model

This paper deals with the concurrent multi-scale optimization design of frame structure composed of glass or carbon fiber reinforced polymer laminates. In the composite frame structure, the fiber winding angle at the micro-material scale and the geometrical parameter of components of the frame in the macro-structural scale are introduced as the independent variables on the two geometrical scales. Considering manufacturing requirements, discrete fiber winding angles are specified for the micro design variable. The improved Heaviside penalization discrete material optimization interpolation scheme has been applied to achieve the discrete optimization design of the fiber winding angle. An optimization model based on the minimum structural compliance and the specified fiber material volume constraint has been established. The sensitivity information about the two geometrical scales design variables are also deduced considering the characteristics of discrete fiber winding angles. The optimization results of the fiber winding angle or the macro structural topology on the two single geometrical scales, together with the concurrent two-scale optimization, is separately studied and compared in the paper. Numerical examples in the paper show that the concurrent multi-scale optimization can further explore the coupling effect between the macro-structure and micro-material of the composite to achieve an ultralight design of the composite frame structure. The novel two geometrical scales optimization model provides a new opportunity for the design of composite structure in aerospace and other industries.

Stiffness Degradation Modeling for Composite Wind Turbine Blades Based on Full-Scale Fatigue Testing

In order to provide more insights into the damage propagation composite wind turbine blades(blade)under cyclic fatigue loading,a stiffness degradation model for blade is proposed based on the full-scale fatigue testing of a blade.A novel non-linear fatigue damage accumulation model is proposed using the damage assessment theories of composite laminates for the first time.Then,a stiffness degradation model is established based on the correlation of fatigue damage and residual stiffness of the composite laminates.Finally,a stiffness degradation model for the blade is presented based on the full-scale fatigue testing.The scientific rationale of the proposed stiffness model of blade is verified by using full-scale fatigue test data of blade with a total length of 52.5 m.The results indicate that the proposed stiffness degradation model of the blade agrees well with the fatigue testing results of this blade.This work provides a basis for evaluating the fatigue damage and lifetime of blade under cyclic fatigue loading.

Optimization of the Active Composition of the Wind Farm Using Genetic Algorithms

The article presents the results of research on the possibilities of using genetic algorithms for solving the multicriteria optimization problem of determining the active components of a wind farm.Optimization is carried out on two parameters:efficiency factor of wind farm use(integrated parameter calculated on the basis of 6 parameters of each of the wind farm),average power deviation level(average difference between the load power and energy generation capabilities of the active wind farm).That was done an analysis of publications on the use of genetic algorithms to solve multicriteria optimization problems.Computer simulations were performed,which allowed us to analyze the obtained statistical data and determine the main optimization indicators.That was carried out a comparative analysis of the obtained results with other methods,such as the dynamic programming method;the dynamic programming method with the general increase of the set loading;the modified dynamic programming method,neural networks.It is established that the average power deviation for the genetic algorithm and for the modified dynamic programming method is located at the same level,33.7 and 28.8 kW,respectively.The average value of the efficiency coefficient of wind turbine used for the genetic algorithm is 2.4%less than for the modified dynamic programming method.However,the time of finding the solution by the genetic algorithm is 3.6 times less than for the modified dynamic programming method.The obtained results provide an opportunity to implement an effective decision support system in energy flow management.

Vertical structure of longitudinal differences in electron densities at mid-latitudes

By using Constellation Observing System for Meteorology, Ionosphere, and Climate satellite observa- tions, and Global Ionosphere and Thermosphere Model simulations, the altitudinal dependences of the longitudinal differences in electron densities Ne were studied at mid- latitudes for the first time. Distinct altitudinal dependences were revealed： （1） In the northern （southern） hemisphere, there were wave-1 variations mainly in the daytime in the altitudes below 180 km, but wave-2 （wave-l） variations over a whole day above 220 km; （2） a transition （or sep- aration） layer occurred mainly in the daytime within 180 and 220 km, showing reversed longitudinal variation from that at lower altitudes. Solar illumination was one of the plausible mechanisms for the zonal difference of Ne at lower altitudes. At higher altitudes, both neutral winds and solar illumination played important roles. The neutral winds effects accounted for the longitudinal differences in Ne in the European-Asian sector. Neutral composition changes and neutral wind effects both contributed to the formation of the transition layer.

Lifetime Prediction of Wind Turbine Blade Based on Full-Scale Fatigue Testing

In order to predict the lifetime of products appropriately with long lifetime and high reliability,the accelerated degradation testing(ADT)has been proposed.Composite wind turbine blade is one of the most important components in wind turbine system.Its fatigue cycle is very long in practice.A full-scale fatigue testing is usually used to verify the design of a new blade.In general,the full-scale fatigue testing of blade is accelerated on the basis of the damage equivalent principle.During the full-scale fatigue test ing,blade is subjected to higher testing load than normal operat ing conditions;consequently,the performance degradation of the blade is hastened over time.The full-scale fatigue testing of blade is regarded as a special ADT.According to the fatigue failure criterion,we choose blade stiffness as the characteristic quantity of the blade performance,and propose an accelerated model(AM)for blade on the basis of the theories of ADT.Then,degradation path of the blade stiffness is modeled by using Gamma process.Finally,the lifet ime prediction of full-scale megawatt(MW)blade is conducted by combining the proposed AM and blade stiffness degradation model.The prediction results prove the reasonability and validity of this study.This can supply a new approach to predict the lifetime of the full-scale MW blade.