Aerodynamic Optimization of Rocket Control Surface Geometry Using Cartesian Methods and CAD Geometry

Aerodynamic design is an iterative process involving geometry manipulation and complex computational analysis subject to physical constraints and aerodynamic objectives. A design cycle consists of first establishing the performance of a baseline design, which is usually created with low-fidelity engineering tools, and then progressively optimizing the design to maximize its performance. Optimization techniques have evolved from relying exclusively on designer intuition and insight in traditional trial and error methods, to sophisticated local and global search methods. Recent attempts at automating the search through a large design space with formal optimization methods include both database driven and direct evaluation schemes. Databases are being used in conjunction with surrogate and neural network models as a basis on which to run optimization algorithms. Optimization algorithms are also being driven by the direct evaluation of objectives and constraints using high-fidelity simulations. Surrogate methods use data points obtained from simulations, and possibly gradients evaluated at the data points, to create mathematical approximations of a database. Neural network models work in a similar fashion, using a number of high-fidelity database calculations as training iterations to create a database model. Optimal designs are obtained by coupling an optimization algorithm to the database model. Evaluation of the current best design then gives either a new local optima and/or increases the fidelity of the approximation model for the next iteration. Surrogate methods have also been developed that iterate on the selection of data points to decrease the uncertainty of the approximation model prior to searching for an optimal design. The database approximation models for each of these cases, however, become computationally expensive with increase in dimensionality. Thus the method of using optimization algorithms to search a database model becomes problematic as the number of design variables is increased

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to demonstrate the use of design and analysis of computer experiments (DACE) methods in Sandias DAKOTA software package for surrogate modeling and optimization. These methods were applied to a flow- path fueled with an interdigitated flushwall injector suitable for scramjet applications at hyper- velocity conditions and ascending along a constant dynamic pressure flight trajectory. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. Because the RAS of this case are computationally expensive, surrogate models are used for optimization. To build a surrogate model a RAS database is created. The sequence of the design variables comprising the database were generated using a Latin hypercube sampling (LHS) method. A methodology was also developed to automatically build geometries and generate structured grids for each design point. The ensuing RAS analysis generated the simulation database from which the two objective functions were computed using a one-dimensionalization (1D) of the three-dimensional simulation data. The data were fitted using four surrogate models: an artificial neural network (ANN), a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model predicted an optimal solution set that exhibited high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts may be required to lower the surrogate model errors and perform more accurate surrogate-model-based optimization

E-Commerce untuk Mendukung Business To Business Menggunakan Dynamic Dbmss: Studi Kasus pada Perusahaan Dagang Cross Tech

The purpose of this study is to develop an e-commerce that can distribute any information about the products of PD Cross Tech. The e-commerce is supported by dynamic DBMS and can be connected via database reseller server so that it can do information sharing. The distribution is performed using the Distributed Relational Database Management System (DRDBMS), supported by the File Transfer Protocol and Virtual Private Network. In other words the e-Commerce supports multiplatform database. Research methodologies used are analytical methods, design methods, and literature study. Results showed that PD Cross Tech needs a new e-Commerce that supports multiplatform database. With this e-Commerce, it is expected that similar computer equipment needs for many organization in Indonesia can be designed in the same way

Assessment of classical database models for representing solids

Solid modeling is being explored as a method of representing three dimensional parts for mechanical design and manufacturing. This work analyzes the data storage requirements of the Boundary Representation and Constructive Solid Geometry methods of representing solid models. The ability of the database models (Hierarchical, Network, and Relational) to support solid modeling needs is evaluated. The goal is to determine the database model(s) best suited to store and manage the graphical data for solid model representat ions . Background information about mechanical engineering, graphics, and database models is presented. Entity-Relationship diagrams are used to define data requ irements

STAMP: SMTP server topological analysis by message headers parsing

This paper presents STAMP: a tool to analyse SMTP servers overlay topology. STAMP builds a weighted and oriented graph from an email database, an email log or just a simple email header allowing a post-analysis of the SMTP overlay structure and the identification of the paths used by an email. The objective of this tool is twofold. STAMP allows to automatically perform an analysis of the SMTP topology for debugging (e.g, message delay, emails loop, ...) and for metrology purposes. While several traceroute-like measurements projects try to map the Internet, to the best of our knowledge, no tool allows to drive an analysis of the SMTP overlay network. Thus, the goal of the resulting graph is to develop methods (from graph theory, statistical analysis, ...) to identify relaying problems. We aim to explore the impact of IP network problems over emails delivery (and respectively: emails’ traffic over IP networks) in conjunction with IP measurements driven synchronously. In the present paper, we introduce the design and the measurement methodology of the STAMP software and as second contribution, bring out to the networking community the tool and some measurements databases