PARETO FRONT CAPTURE USING DETERMINISTIC OPTIMIZATION METHODS IN MULTI-CRITERION AERODYNAMIC DESIGN

Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary algorithms （EAs） and the Pareto front concept are used to solve practical design problems in industry for its robustness in capturing convex, concave, discrete or discontinuous Pareto fronts of multi-objective optimization problems. However, the process is time-consuming. Therefore, deterministic optimization methods are introduced to capture the Pareto front, and the types of the captured Pareto front are explained. Numerical experiments show that the deterministic optimization method is a good alternative to EAs for capturing any convex and some concave Pareto fronts in multi-criterion aerodynamic optimization problems due to its efficiency.

A DETERMINISTIC VORTEX METHOD FOR SOLVING THE NAVIER-STOKES EQUATIONS

In this paper, a new 2-D vortex method is developed, which treats the vorticity diffusion in a deterministical way. The Laplacian operator, which describes vorticity diffusion, is approximated by a contour integral. The numerical results of two model problems show that this method has a good accuracy. A primary error estimation is given, and the self-adaptive vortex blob and the boundary conditions are discussed.

A METHOD FOR CALCULATING TRANSIENT FUNCTIONS OF EQUIVALENT DETERMINISTIC INPUT

In the present paper the analytical formulas for calculating the equivalent deterministic transients for multivariable cross correlated random processes are developed.The formulas permit the determination of the Root-mean-square of the responses of a linear time-invariant system to stationary multiple random inputs in the time domain.The method is applicable in the study of flight of airplanes in atmospheric turbulence and is also useful for general engineering applications of stochastc processes control.

Mapping of the Water Table Levels of Unconfined Aquifers Using Two Interpolation Methods

The spatial prediction of the water table can be used for many applications related to civil works (foundations, excavations) and other urban and environmental management activities. Deterministic and geostatistical interpolation methods were used to predict the spatial distribution of water table levels (unconfined aquifers) of important geological formations of the Joao Pessoa City (capital of Paraiba State, Brazil) with dense urban occupation and high demand for new civil works. The deterministic (topo to raster) and geostatistical (ordinary kriging) interpolation methods were evaluated using a Geographic Information System (GIS)-based investigation. The water table levels were obtained from 276 boring logs of Standard Penetration Test (SPT) in situ investigation distributed over the geological formations studied (an area of 59.8 km2, covering 40 districts of the Joao Pessoa City). The Nspt values and textural characterization data are stored for levels of 1 m depth. Some boreholes located in the area investigated were not included in the interpolation processes in order to be compared with estimated values (validation of the results). Maps of the water table depths were also produced to further analyze the quality of the water table surfaces interpolated by both methods. The phreatic surface interpolations provided satisfactory results for both methods (RMSE = 1.8 m). The topo to raster method showed a slight general tendency to be less affected by local values in relation to the kriging method and also has the advantage of integrating the drainage flow system, which is a relevant aspect for spatial models of the water table levels of unconfined aquifers. The ordinary kriging (geostatistical method) provides a prediction surface and some measure of the certainty or accuracy of the predictions.

Evaluation of oil sands resources──A case study in the Athabasca Oil Sands,NE Alberta,Canada

Oil sands are the most important of the oil and gas resources in Canada. So the distribution and evaluation of oil sands form a critical basis for risk investment in Canada. Distribution of oil sands resources is severely controlled by the reservoir heterogeneity. Deterministic modeling is commonly used to solve the heterogeneity problems in the reservoir, but rarely used to evaluate hydrocarbon resources. In this paper, a lithofacies based deterministic method is employed to assess the oil sands resources for a part of a mining project in northern Alberta. The statistical analysis of Dean Stark water and oil saturation data and study of the core description data, regional geology and geophysical logs reveal that the lithofacies in the study area can be classified into reservoir facies, possible reservoir facies and non-reservoir facies. The indicator krigging method is used to build a 3D lithofacies model based on the classification of sedimentary facies and the ordinary krigging method is applied to petrophysical property modeling. The results show that the krigging estimation is one of the good choices in oil sand resources modeling in Alberta. Lithofacies-grade based modeling may have advantages over the grade-only based modeling.

Numerical Analysis of a Blocking Mass Attenuating Wave Propagation

Based on wave theory, blocking mass impeding propagation of flexural waves was analyzed with force excitation applied on a ship pedestal. The analysis model of a complex structure was developed by combining statistical energy analysis and the finite element method. Based on the hybrid FE-SEA method, the vibro-acoustic response of a complex structure was solved. Then, the sound radiation of a cylindrical shell model influenced by blocking mass was calculated in mid/high frequency. The result shows that blocking mass has an obvious effect on impeding propagation. The study provides a theoretical and experimental basis for application of the blocking mass to structure-borne sound propagation control.

Computing Multivalued Solutions of Pressureless Gas Dynamics by Deterministic Particle Methods

We compute multivalued solutions of one-and two-dimensional pressureless gas dynamics equations by deterministic particle methods.Point values of the computed solutions are to be recovered from their singular particle approximations using some smoothing procedure.We study several recovery strategies and demonstrate ability of the particle methods to achieve high resolution.

Ultra-efficient and parameter-free computation of submicron thermal transport with phonon Boltzmann transport equation

Understanding thermal transport at the submicron scale is crucial for engineering applications,especially in the thermal management of electronics and tailoring the thermal conductivity of thermoelectric materials.At the submicron scale,the macroscopic heat diffusion equation is no longer valid and the phonon Boltzmann transport equation(BTE)becomes the governing equation for thermal transport.However,previous thermal simulations based on the phonon BTE have two main limitations:relying on empirical parameters and prohibitive computational costs.Therefore,the phonon BTE is commonly used for qualitatively studying the non-Fourier thermal transport phenomena of toy problems.In this work,we demonstrate an ultra-efficient and parameter-free computational method of the phonon BTE to achieve quantitatively accurate thermal simulation for realistic materials and devices.By properly integrating the phonon properties from first-principles calculations,our method does not rely on empirical material properties input.It can be generally applicable for different materials and the predicted results can match well with experimental results.Moreover,by developing a suitable ensemble of advanced numerical algorithms,our method exhibits superior numerical efficiency.The full-scale(from ballistic to diffusive)thermal simulation of a 3-dimensional fin field-effect transistor with 13 million degrees of freedom,which is prohibitive for existing phonon BTE solvers even on supercomputers,can now be completed within two hours on a single personal computer.Our method makes it possible to achieve the predictive design of realistic nanostructures for the desired thermal conductivity.It also enables accurately resolving the temperature profiles at the transistor level,which helps in better understanding the self-heating effect of electronics.