The APS Control System Network Upgrade

When it was installed,the Advanced Photon Source (APS) control system network was at the state-of-the-art. Different aspects of the system have been reported at previous meetings [1,2]. As loads on the controls network have increased due to newer and faster workstations and front-end computers, we have found performance of the system declining and have implemented an upgraded network. There have been dramatic advances in networking hardware in the last several years. The upgraded APS controls network replaces the original FDDI backbone and shared Ethernet hubs with redundant gigabit uplinks and fully switched 10/100 Ethernet switches with backplane fabrics in excess of 20 Gbits/s (Gbps). The central collapsed backbone FDDI concentrator has been replaced with a Gigabit Ethernet switch with greater than 30 Gbps backplane fabric. Full redundancy of the system has been maintained. This paper will discuss this upgrade and include performance data and performance comparisons with the original network

Neural modelling for calculating the heat transfer coefficient and required isolation layer of wall barier

W referacie przedstawiono zastosowanie sztucznych sieci neuronowych do obliczania współczynnika przenikania ciepła U oraz model odwrotny, polegający na obliczaniu grubości warstwy izolacyjnej przy zadanym współczynniku. Opisano metodykę sporządzenia zbioru uczącego sztuczne sieci neuronowe oraz opisano zbiór przetestowanych sieci neuronowych. Metody sztucznej inteligencji, w tym sztuczne sieci neuronowe, pozwalają uwzględnić w obliczeniach wiele zjawisk i procesów trudnych do opisu matematycznego ze względu na swoją nieliniowość, stąd uzyskane modele neuronowe będą uzupełniane w przyszłości o dodatkowe parametry obliczeniowe.The report presents the usage of artificial neural networks to calculate heat transfer coefficient U and the opposite model, which consists on calculating the thickness of the isolation layer with given coefficient. The methodology of making a set teaching artificial neural networks and the set of tested neural networks were described. The methods of artificial intelligence, including neural networks, let include in calculations many phenomena and processes hard to describe mathematically because of their nonlinearity, so obtained neural models will be completed by additional computable parameters in future

An accelerator controls network designed for reliability and flexibility

The APS accelerator control system is a typical modern system based on the standard control system model, which consists of operator interfaces to a network and computer-controlled interfaces to hardware. The network provides a generalized communication path between the host computers, operator workstations, input/output crates, and other hardware that comprise the control system. The network is an integral part of all modern control systems and network performance will determine many characteristics of a control system. This paper describes the methods used to provide redundancy for various network system components as well as methods used to provide comprehensive monitoring of this network. The effect of archiving tens of thousands of data points on a regular basis and the effect on the controls network will be discussed. Metrics are provided on the performance of the system under various conditions

The APS control system network upgrade.

When it was installed,the Advanced Photon Source (APS) control system network was at the state-of-the-art. Different aspects of the system have been reported at previous meetings [1,2]. As loads on the controls network have increased due to newer and faster workstations and front-end computers, we have found performance of the system declining and have implemented an upgraded network. There have been dramatic advances in networking hardware in the last several years. The upgraded APS controls network replaces the original FDDI backbone and shared Ethernet hubs with redundant gigabit uplinks and fully switched 10/100 Ethernet switches with backplane fabrics in excess of 20 Gbits/s (Gbps). The central collapsed backbone FDDI concentrator has been replaced with a Gigabit Ethernet switch with greater than 30 Gbps backplane fabric. Full redundancy of the system has been maintained. This paper will discuss this upgrade and include performance data and performance comparisons with the original network

A highly sensitive assay for adenosine triphosphate employing an improved firefly luciferase reagent

An improved firefly luciferase reagent allowed reliable detection of as little as 80 fmo1/1 adenosine triphosphate (ATP). Contamination by ATP of the deionized water diluent limited the sensitivity of the assay in some laboratories. The reagent can be used to measure ATP from less than ten bacterial cells if care is taken to eliminate ATP from equipment and reagents