SAGT Project dissemination report – No. 31 November, 2014
Background
The following series of articles provide a brief insight into the framework adopted for simulating grain sorting equipment (such as gravity sorters, destoners etc.). The limited effort invested in this domain have prompted the need to develop efficient tools for virtually designing and developing these equipment. The objective of this effort is to be able to describe a grain sorting process using a virtual prototype. The modelling of this system would be done by employing a computational fluid dynamics based approach where a set of numerical methods are applied to obtain approximate solutions to problems with fluid/granular flow.
This section introduces some basics of data management and its need in computational research.
The Relational Database: An organized collection of data
Detailed empirical and computational modelling studies generate large chunks of data that are invaluable in characterizing the performance of a system. The challenge that several researchers are faced with today is the efficient and structured storage of these generated data so as to enable a logical evaluation of the obtained results. A database fulfils this requirement by serving as a collection of information that is logically organized so that it can easily be accessed, managed, and updated. Several research efforts hinge on proper data management and the work undertaken by the SAGT group also strongly depends on logical data storage.
The need for such a database within the project framework arises from the fact that data such as the gravity separator operating parameters over time, grain images, grain data such as type, origin and harvest date etc. need to be stored so that end users could easily setup the relevant gravity separators using the stored preset values. Hence a database where relevant data is stored in a consistent manner (preventing redundant data accumulation) is a primary requirement for any computational study. Such a database uses the Structured Query Language (SQL) as a standard programming interface and consists of the simple UI shown in figure 1. The corresponding
‘scenario’ parameter can be loaded/accessed from this database. The designed database has been linked to the machine software to enable seamless data transfer between the two in order to generate the requisite data trunk needed during operation.
Figure 1- SAGT Relation database front-end

SAGT Project dissemination report – No. 31 November, 2014
The simplified UI depicted above is the front end to a relatively complex set of ‘stored’ procedures that enable storage and retrieval of relevant data points. The relational database management system (RDBMS) employs tables that follow certain integrity rules to ensure that the data they contain stay accurate and are always accessible. Firstly, the rows in a relational table should all be distinct; secondly, column values must not be repeating groups or arrays and thirdly a null value indicates that a value is missing and does not equate to a blank or zero. Hence, a relational database
(RDB) is a collective set of multiple data sets organized by tables, records and columns with welldefined relationships between database entries. (tables communicate and share information) facilitating data searchability, organization and reporting (1).
Acknowledgements:
This project is supported by the SEVENTH FRAMEWORK PROGRAMME of EU, Industry-
Academia Partnerships and Pathways (IAPP) - Marie Curie Actions. Grant no.: 324433.
References:
1) The Java™ Tutorials : A Relational Database Overview. Retrieved from http://docs.oracle.com/javase/tutorial/jdbc/overview/database.html
[Accessed 18th March
2015]