Gradient based hyper-parameter optimisation for well conditioned kriging metamodels

In this work a two step approach to efficiently carrying out hyper parameter optimisation, required for building kriging and gradient enhanced kriging metamodels, is presented. The suggested approach makes use of an initial line search along the hyper-diagonal of the design space in order to find a suitable starting point for a subsequent gradient based optimisation algorithm. During the optimisation an upper bound constraint is imposed on the condition number of the correlation matrix in order to keep it from being ill conditioned. Partial derivatives of both the condensed log likelihood function and the condition number are obtained using the adjoint method, the latter has been derived in this work. The approach is tested on a number of analytical examples and comparisons are made to other optimisation approaches. Finally the approach is used to construct metamodels for a finite element model of an aircraft wing box comprising of 126 thickness design variables and is then compared with a sub-set of the other optimisation approaches

Sub-space approximations for MDO problems with disparate disciplinary variable dependence

The research leading to these results have been funded by the European Union Seventh Framework Programme FP7-PEOPLE-2012-ITN under grant agreement 316394, Aerospace Multidisciplinarity Enabling DEsign Optimization (AMEDEO) Marie Curie Initial Training Network

Trženjska strategija za prodajo avtomobilskih nadomestnih delov blagovne znamke Motrio

The literature on information aggregation predicts that market growth unambiguously reduces uncertainty about the value of traded goods. The results were developed within the classical model, which assumes that traders’ values for the exchanged good are determined by fundamental (common) shocks. At the same time, design innovation in contemporaneous markets seems to exploit demand interdependence among agents with similar tastes or common information sharing (e.g., Facebook ads, the practice of customer targeting). This paper demonstrates that with heterogeneous interdependence among agents’ values or noise in signals about values, opportunities to innovate in smaller or less connected (in the network-theoretic sense) markets may dominate those in larger or better connected markets

United States Bureau of Mines Bulletin 4251

Report issued by the Bureau of Mines over exploratory work conducted on the bauxite deposits of Arkansas. Descriptions of geophysical characteristics and core drilling results are presented. This report includes tables, maps, illustrations, and photographs

Multidisciplinary Design Optimisation Research Contributions from the AMEDEO Marie Curie Initial Training Network

This paper reviews the key research activities and results produced during the AMEDEO (Aerospace Multidisciplinarity-Enabling Design Optimisation) Marie Curie Initial Training Network (ITN). AMEDEO brought together optimisation researchers and practitioners from European universities, research organisations, multinationals and SMEs to develop innovative Multidisciplinary Design Optimisation (MDO) methods for the design of energy-efficient aircraft. A range of new results are presented in the areas of: 1) efficient High Performance Computing techniques for MDO, 2) efficient metamodel-based robust MDO frameworks, 3) the application of advanced MDO methods to aircraft engine design and 4) novel applications of MDO to the design of composite aeronautical structures. The future challenges that need to be overcome to embed MDO methods more effectively within commercial design cycles in the aerospace industry are also briefly discussed