Optimization of Generator Based on Gaussian Process Regression Model with Conditional Likelihood Lower Bound Search

The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.

On fracture behavior of inner enamel:a numerical study

The ingenious hierarchical structure of enamel composed of rods and protein produces excellent fracture resistance.However,the fracture resistance mechanism in the inner enamel is unknown.The micromechanical models of enamel are constructed to numerically analyze the mechanical behaviors of the inner enamel with different decussation angles and different decussation planes.The results show that the manner of crack propagation in the inner enamel,including crack bridging,crack deflection,and crack bifurcation,is determined by both the rod decussation angle and the decussation plane.In the case of the strong decussation plane,the fracture strength and the required energy dissipation with the decussation angles of 15°and 30°are much higher than those without decussation,demonstrating that decussation is an important mechanism in improving the fracture resistance of enamel.The maximum tensile stress of enamel with the decussation angle of 15°is slightly higher than that of enamel with the decussation angle of 30°,illustrating that an optimal decussation angle exists which balances the strength and toughness.The synergetic mechanism of the decussation angle and the decussation plane on the crack propagation provides a new design hint for bionic composites.

Numerical Analysis of the Thermal Properties of Ecological Materials Based on Plaster and Clay

Most of the energy savings in the building sector come from the choice of the materials used and their microphysical properties.In the present study,through numerical simulations a link is established between the thermal performance of composite materials and their microstructures.First,a two-phase 3D composite structure is modeled,then the RSA(Random Sequential Addition)algorithm and a finite element method(FE)are applied to evaluate the effective thermal conductivity of these composites in the steady-state.In particular,building composites based on gypsum and clay,consolidated with peanut shell additives and/or cork are considered.The numerically determined thermal conductivities are compared with values experimentally calculated using the typical tools of modern metrology,and with available analytical models.The calculated thermal conductivities of the clay-based materials are 0.453 and 0.301 W.m^(−1).K^(−1) with peanut shells and cork,respectively.Those of the gypsum-based materials are 0.245 and 0.165 W.m^(−1).K^(−1) with peanut shells and cork,respectively.It is shown that,in addition to its dependence on the volume fraction of inclusions,the effective thermal conductivity is also influenced by other parameters such as the shape of inclusions and their distribution.The relative deviations,on average,do not exceed 6.8%,which provides evidence for the reliability of the used approach for random heterogeneous materials.

Thermal Behavior of Clay-Based Building Materials: A Numerical Study Using Microstructural Modeling

A large part of the energy savings in the building sector comes from the choice of materials used and their structures. We are interested, through a numerical study, in establishing the link between the thermal performance of composite materials and their microstructures. The work begins with the generation of a two-phase 3D composite structure, the application of the Random Sequential Addition (RSA) algorithm, and then the finite element method (FE) is used to evaluate, in steady-state, the effective thermal conductivity of these composites. The result of the effective thermal conductivity of composite building material based on clay and olive waste at a volume fraction of 10% obtained by simulation is 0.573 W·m?1·K?1, this result differs by 3.6% from the value measured experimentally using modern metrology methods. The calculated value is also compared to those of existing analytical models in the literature. It can be noticed also that the effective thermal conductivity is not only related to the volume fraction of the inclusions but also to other parameters such as the shape of the inclusions and their distribution. The small difference between the numerical and experimental thermal conductivity results shows the performance of the code used and its validation for random heterogeneous materials. The homogenization technique remains a reliable way of evaluating the effective thermal properties of clay-based building materials and exploring new composite material designs.

Valuable Impulses and Successful Models of Gearbox Development from Practice

Gears play an important role in mechanical engineering because of their moment and speed transmission possibilities. Design and optimization of a complete gearbox provide many requirements to the designer. The complex gearbox model consists of many machine elements （shafts, gears, bearings, housing, seals, and shaft-hub connections）. The gearbox must be understood as a system with interactive parts. Next to the calculation of kinematics, load capacities and life times of single elements, aspects of load distribution and efficiency and noise excitation of gearboxes become important. The wide range of knowhow needed mostly cannot be covered by a small number of engineers. The development of automated calculation routines with understandable and comprehensive results is the goal for these research projects that lead to sottware-realizing solutions for engineers to efficiently design, calculate, optimize and verify gearboxes with minimal resources in terms of calculation experts and time.