Keyword: lattice
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TUAAULT03 BLED: A Top-down Approach to Accelerator Control System Design database, controls, operation, EPICS 537
  • J. Bobnar, K. Žagar
    COBIK, Solkan, Slovenia
  In many existing controls projects the central database/inventory was introduced late in the project, usually to support installation or maintenance activities. Thus construction of this database was done in a bottom-up fashion by reverse engineering the installation. However, there are several benefits if the central database is introduced early in machine design, such as the ability to simulate the system as a whole without having all the IOCs in place, it can be used as an input to the installation/commissioning plan, or act as an enforcer of certain conventions and quality processes. Based on our experience with the control systems, we have designed a central database BLED (Best and Leanest Ever Database), which is used for storage of all machine configuration and parameters as well as control system configuration, inventory, and cabling. First implementation of BLED supports EPICS, meaning it is capable of storage and generation of EPICS templates and substitution files as well as archive, alarm and other configurations. With a goal in mind to provide functionality of several existing central databases (IRMIS, SNS db, DBSF etc.) a lot of effort has been made to design the database in a way to handle extremely large set-ups, consisting of millions of control system points. Furthermore, BLED also stores the lattice data, thus providing additional information (e.g. survey data) required by different engineering groups. The lattice import/export tools among others support MAD and TraceWin Tools formats which are widely used in the machine design community.  
slides icon Slides TUAAULT03 [4.660 MB]  
WEPKS012 Intuitionistic Fuzzy (IF) Evaluations of Multidimensional Model data-analysis, operation, software, fuzzy set 805
  • I.D. Valova
    ICER, Sofia, Bulgaria
  There are different logical methods for data structuring, but no one is perfect enough. Multidimensional model of data is presentation of data in a form of cube (referred as infocube or hypercube) with data or in form of "star" type scheme (referred as multidimensional scheme), by use of F-structures (Facts) and set of D-structures (Dimensions), based on the notion of hierarchy of D-structures. The data, being subject of analysis in a specific multidimensional model is located in a Cartesian space, being restricted by D-structures. In fact, the data is either dispersed or "concentrated", therefore the data cells are not distributed evenly within the respective space. The moment of occurrence of any event is difficult to be predicted and the data is concentrated as per time periods, location of performed event, etc. To process such dispersed or concentrated data, various technical strategies are needed. The use of intuitionistic fuzzy evaluations- IFE provide us new possibilities for alternative presentation and processing of data, subject of analysis in any OLAP application. The use of IFE at the evaluation of multidimensional models will result in the following advantages: analysts will dispose with more complete information for processing and analysis of respective data; benefit for the managers is that the final decisions will be more effective ones; enabling design of more functional multidimensional schemes. The purpose of this work is to apply intuitionistic fuzzy evaluations of multidimensional model of data.