The design and implementation of a functional interface for the attribute-based multi-lingual database system.

Traditionally, the design and implementation of a conventional database system begins with the selection of a data model, followed by the specification of a model-based data language. Hence, the database system is restricted to a single data model and a specific data language. One alternative to this traditional approach to database-system development is the multi-lingual database system (MLDS). This alternative approach affords the user the ability to access and manage a large collection of databases, via several data models and their corresponding data languages, without the aforementioned limitations. This thesis presents a methodology for supporting the Functional Data Model and the Data Language DAPLEX for the MLDS. Specifically, we design an interface which translates DAPLEX data language calls into attribute-based data language (ABDL) requests. A description of the software engineering aspects of the implementation and an overview of the modules which comprise our DAPLEX language interface are provided.http://archive.org/details/designimplementa00mackLieutenant, United States NavyApproved for public release; distribution is unlimited

Computational modelling of aerodynamic disturbances on spacecraft within a concurrent engineering framework

This research was motivated by the need to perform an accurate aerodynamic analysis of the drag deorbit device concept under development within the Space Research Centre, Cranfield University. Its purpose is to deorbit satellites from low Earth orbit at the end of the useful lives, in order to help reduce the growing problem of space debris. It has been found that existing spacecraft aerodynamic analysis tools do not adequately support concurrent engineering. Furthermore, use of concurrent engineering in the space industry is currently limited to Phase A (preliminary design studies). To remedy this, the Spacecraft Engineering, Design, and Analysis Tools (SEDAT) Concept has been proposed. Inspired by the approach employed by enterprise applications, it proposes that all the computer tools used on a spacecraft project should be incorporated into one system as separate modules, presented via a single client, and connected to a centralised Relational Database Management System. To demonstrate the concept and assess its potential a SEDAT System and accompanying Free Molecular Flow (FMF) spacecraft aerodynamic analysis module have been developed. The FMF Module is explicitly designed to facilitate concurrent engineering and make use of the maximum variety of Gas-Surface Interaction Models (GSIMs) and their associated data. It also incorporates a new Hybrid method of FMF analysis that combines the Ray-Tracing Panel (RTP) and Test-Particle Monte Carlo (TPMC) methods, enabling it to analyse complex geometries that are subject to surface shielding and multiple molecular reflections. Studies have been performed using a Hybrid version of the Schaaf and Chambre GSIM. One of these studies analysed a drag deorbit device design using a range of accommodation coefficients, including the latest empirically based incidence-dependent coefficients. Based on this analysis, recommendations have been made regarding the material selection and structural design of the device

DFM synthesis approach based on product-process interface modelling. Application to the peen forming process.

Engineering design approach are curently CAD-centred design process. Manufacturing information is selected and assessed very late in the design process and above all as a reactive task instead of being proactive to lead the design choices. DFM appraoches are therefore assesment methods that compare several design alternatives and not real design approaches at all. Main added value of this research work concerns the use of a product-process interface model to jointly manage both the product and the manufacturing data in a proactive DFM way. The DFM synthesis approach and the interface model are presented via the description of the DFM software platform

A Computationally Efficient Ground-Motion Selection Algorithm for Matching a Target Response Spectrum Mean and Variance

Dynamic structural analysis often requires the selection of input ground motions with a target mean response spectrum. The variance of the target response spectrum is usually ignored or accounted for in an ad hoc manner, which can bias the structural response estimates. This manuscript proposes a computationally efficient and theoretically consistent algorithm to select ground motions that match the target response spectrum mean and variance. The selection algorithm probabilistically generates multiple response spectra from a target distribution, and then selects recorded ground motions whose response spectra individually match the simulated response spectra. A greedy optimization technique further improves the match between the target and the sample means and variances. The proposed algorithm is used to select ground motions for the analysis of sample structures in order to assess the impact of considering ground-motion variance on the structural response estimates. The implications for code-based design and performance-based earthquake engineering are discussed

Selection of earthquake ground motions for multiple objectives using genetic algorithms

Existing earthquake ground motion (GM) selection methods for the seismic assessment of structural systems focus on spectral compatibility in terms of either only central values or both central values and variability. In this way, important selection criteria related to the seismology of the region, local soil conditions, strong GM intensity and duration as well as the magnitude of scale factors are considered only indirectly by setting them as constraints in the pre-processing phase in the form of permissible ranges. In this study, a novel framework for the optimum selection of earthquake GMs is presented, where the aforementioned criteria are treated explicitly as selection objectives. The framework is based on the principles of multi-objective optimization that is addressed with the aid of the Weighted Sum Method, which supports decision making both in the pre-processing and post-processing phase of the GM selection procedure. The solution of the derived equivalent single-objective optimization problem is performed by the application of a mixed-integer Genetic Algorithm and the effects of its parameters on the efficiency of the selection procedure are investigated. Application of the proposed framework shows that it is able to track GM sets that not only provide excellent spectral matching but they are also able to simultaneously consider more explicitly a set of additional criteria