Operator Training Simulator for Ethylene Plant

Common reasons for local failures in power transformers are partial discharges (PD) in the electric insulation. The ultra-high frequency (UHF) PD measurement method gained in importance for transformer diagnosis and monitoring within the last years. Due to its robustness against external noise, it is suitable for both, factory acceptance tests (FAT) and site acceptance tests (SAT). For the application at acceptance tests, it is necessary that the UHF technique is a reliable testing method and also comparable between different UHF measurement systems. Therefore, the UHF sensor's characteristic has to be included in a calibration procedure by using its antenna factor (AF). This contribution implements a custom-built oil-filled Gigahertz-Transversal-Electromagnetic cell (GTEM cell) for the AF evaluation. In the first part, the GTEM cell's design and dimensioning are illustrated and the cell is evaluated in terms of its high frequency behavior. The second part determines the AF of two different UHF sensor types: UHF Drain Valve Sensors and UHF Plate Sensors using the GTEM cell. Additionally, the influences of insertion depths and standardized gate valves on the Drain Valve Sensor's AF are taken into account.

Many structures like bridges are ageing and the necessity to measure the uncertain parameters is relevant. Crack-related parameters can be measured with traditional techniques like crack gauges and displacement transducers. A method that can detect and localise cracks as well as measure crack width is most favourable. Several distributed and quasi-distributed systems were introduced to the market and tested in recent years. This paper presents a large-scale Structural Health Monitoring project based on stimulated Brillouin scattering in optical fibres for an old bridge. The Gotaalv Bridge is a continuous steel girder bridge with concrete bridge deck. Steel girders suffer from fatigue and mediocre steel quality and some severe cracking and also a minor structural element collapse have taken place. The system installed on the bridge measures strain profiles along the whole length of the bridge and detects cracks that are wider than 0.5 mm. Procedures like factory acceptance test, site acceptance test, laboratory testing and field testing are presented and analysed. Innovative technology was developed, tested and applied on the bridge. Heuristic knowledge was collected; conclusions are presented and discussed for future development.

Large synchronous generators are the main source of electrical energy and special care should be paid both to those units that are already in operation and to the new ones that are about to begin their lifespan. Prior to the site acceptance tests (SAT) at the power plant, the new synchronous generator may be subjected to factory acceptance tests (FAT) at the manufacturer's plant. The purpose of the FAT is to check the quality and performance of the new generator during and immediately after the production process. Furthermore, the results of FAT and SAT tests serve as a fingerprint for the future prophylactic tests. The scope of testsing is defined by an appropriate standard or is part of contractual obligations. The paper describes the importance of factory tests of turbogenerator and presents an example of factory acceptance tests of a new synchronous turbogenerator with rated power of 412 MVA

Research in the training simulation sector to improve the realism and immersive experience of operator training simulators (OTSs) entails combining cutting-edge technologies such as virtual reality (VR) and augmented reality (AR). Although most of the existing studies has been about troubleshooting training, research into the response to chemical accidents through mutual cooperation between the participants has been insufficient. Therefore, we developed an immersive OTS that can facilitate mutual cooperation. Training processes to educate trainees in general chemical facilities were selected, while changes that can occur in facilities during an accident and the corresponding responses in various scenarios were used as the training content. A communication system that relays information between the worksite and the control room was implemented using a distributed control system (DCS) and AR technology. We installed a pilot plant and developed a DCS, thereby establishing an infrastructure that allows the boardman and field operator to cooperate during accident scenarios. Furthermore, we developed an OTS that allowed trainees to learn prompt and accurate responses to chemical accidents through operation of the actual equipment. The training effect of the OTS was found to be approximately 4.5 times better than traditional training methods. It is, therefore, anticipated that the developed OTS will minimize losses or damage caused by chemical accidents.

A new motivation and perspective on teaching simulation and design: The development of a dynamic process model in conjunction with an operator training simulator (OTS) Dr. Richard Turton P.E., West Virginia University Dr. Richard Turton, P.E., has taught the Senior Design course at West Virginia University for the past 27 years. Prior to this, he spent five years in the design and construction industry. His main interests are in design education and process modeling.

The distributed control system (DCS) is the most prevalent means of implementing batch and continuous control in the process industry. The DCS platform may also be effectively used for the evaluation and demonstration of innovative algorithms developed at a university. The integrated online advanced controls, diagnostics, data analytics, and process modeling capability of a DCS facilitate university research. This working environment also prepares students for careers in industry. The paper discusses the industrial standards adopted by the DCS that allow students and researchers to concentrate on the application of new control capabilities. External applications such as Matlab can be used with the DCS to explore control and process modeling. In this environment, the student and researchers may take advantage of preconfigured and automated features of the DCS. Process simulations may be integrated into the DCS to create a virtual plant capability that is capable of running faster than real-time. The DCS supports wireless and internet access to the virtual plant which increases ease of use in a lab or pilot plant. The DCS system enables rapid exploration, discovery, and prototyping of process modeling and control technologies in a university environment and deployment in industry.

Mobatec Modeller — A flexible and transparent tool for building dynamic process models

This paper describes the implementation of an Automatic Dewatering System in one of ADNOC Offshore's crude oil storage tanks, carried out as a pilot project. The system automates tank dewatering, reducing Health, Safety & Environmental (HSE) hazards and removing the need for standby operators during the process. Automated dewatering in crude oil storage tanks is achieved by installing two oil-water interface detector probes in each draw-off sump, resulting in a total of eight probes distributed across four sumps. These probes operate in conjunction with both the Local Control Panel and the Distributed Control System (DCS) to manage the dewatering process automatically. The primary probe, designated as the Control Probe, is situated at the upper section of the draw-off sump and governs the actuation of the water draining motor-operated valve (MOV) based on the detected oil-water interface level. The secondary probe, referred to as the Alarm Probe, is installed at the lower portion of the sump and serves as a safety feature by triggering an alarm and ensuring closure of the MOV should the Control Probe malfunction. This arrangement significantly reduces the risk of oil contamination in the water drain line. As a result, the system reliably discharges only clean, oil-free water from the tank via the dewatering lines connected to the sumps. Automatic dewatering technology was successfully integrated into an existing Crude Storage Tank, with installation and commissioning completed without interruption to ongoing operations. Comprehensive testing during the Site Acceptance Test (SAT) encompassed multiple operational scenarios, all of which yielded satisfactory results and confirmed effective system integration. The technology substantially reduced oil carryover, consistently achieving the process guarantee of 50 ppm oil in produced water. The system has operated efficiently for over nine months, reducing the need for full-time field operators and lowering operating costs and HSE risks during dewatering. Its successful implementation in one of ADNOC Offshore's crude oil storage tanks automated the dewatering process, eliminated standby operator requirements, and paved the way for adopting similar technologies in other tanks.

This paper reports a preliminary study for use of a fully dynamic vehicle process model in combined underwater communication and navigation (cooperative navigation) of underwater vehicles equipped with an acoustic modem, attitude, and depth sensors, but lacking a Doppler velocity log (DVL), and a surface vehicle equipped with an acoustic modem and GPS. We report both simulation and at-sea experimental trials with the JHU Iver3 autonomous underwater vehicle (AUV). The case of underwater vehicle navigation without a DVL is of interest in several use-cases including (a) small and low-cost underwater vehicles for which DVLs may be impractical or infeasible due to their size and cost and (b) for missions in which the vehicle's altitude above the sea floor (or depth beneath overhead ice) exceeds the DVL acoustic bottom-lock range. To the best of our knowledge, all previous studies on cooperative navigation have reported use of a kinematic process model, which works well in the presence of frequent, high-accuracy velocity measurements, as is the case when the vehicle is equipped with a DVL. This preliminary study suggests that the dynamical process model may offer a significant advantage over the purely kinematic model in the absence of frequent, high-accuracy velocity measurements, as is the case when the submerged vehicle is not equipped with a DVL.

The Gran Telescopio Canarias (GTC) has been recently received two Folded Cassegrain Sets (FC-Sets) composed of an instrument rotator and the corresponding Acquisition and Guiding (AG) optomechanics. IDOM has been the responsible for the design, manufacturing, assembly and commissioning of the two units of FC-Sets. The design combines a compact layout of the mechanical system, enhanced by an innovative cable wrap design, resulting in a smooth and precise movement, whilst guaranteeing good access to important components and maximizing the maintainability. The custom design of the cable wrap as an evolution of the rolling loop type eliminates the need for a cable chain static housing, minimizing weight and impact on the telescope tube. The AG Mechanics provides the required pointing and focusing capabilities in a compact configuration. In January 2010, IDOM is awarded the design and procurement of the two FC-Sets. The final design is approved by GRANTECAN and the fabrication process starts in Nov 2011. The assembly and commissioning of both units are completed in April 2011. Once the Factory Acceptance Tests finishes in Dec 2011, all the elements are delivered to the Observatorio del Roque de los Muchachos (ORM). The Site Acceptance Tests are completed in Feb 2012.

We propose and investigate dynamic spatial-temporal point process models for independent and interacting events. The models for independent events are dynamic spatial-temporal Poisson point process (DSTPPP) model that account for temporal and spatial clustering. The models proposed for events with interaction are Markov (Gibbs) space-time point process models. We model the intensity function of a DSTPPP via conditioning arguments that allow for additional interpretations and inclusion of well-known point process models as special cases. Depending on the nature of the questions to be answered, the in- tensity function of a DSTPPP can be modeled in several ways. First, we develop models via conditioning on the time component of the events and then consider conditioning on the location component of the events. Modeling, simulation and computation are accomplished in a fully hierarchical Bayesian framework. Finally, we focus on dynamic marked Markov space-time point processes, where the events are allowed to interact with each other across time and space. Once again the hierarchical Bayesian framework is invaluable in this case, since it allows us to introduce dynamic process models via conditioning. The methodolo- gies are illustrated using simulated data, and several applications, including modeling and inference for earthquake events in California, and tornado events in Missouri.

Development of an adaptive fuzzy logic-based inverse dynamic model for laser cladding process

Dynamic Process Model Development and Validation with Transient Plant Data Collected from an MEA Test Campaign at the CO2 Technology Center Mongstad

This report documents acceptance test results for the 242-A Evaporator distributive control system upgrade to D/3 version 9.0-2 for year 2000 compliance. This report documents the test results obtained by acceptance testing as directed by procedure HNF-2695. This verification procedure will document the initial testing and evaluation of the potential 242-A Distributed Control System (DCS) operating difficulties across the year 2000 boundary and the calendar adjustments needed for the leap year. Baseline system performance data will be recorded using current, as-is operating system software. Data will also be collected for operating system software that has been modified to correct year 2000 problems. This verification procedure is intended to be generic such that it may be performed on any D/3{trademark} (GSE Process Solutions, Inc.) distributed control system that runs with the VMSTM (Digital Equipment Corporation) operating system. This test may be run on simulation or production systems depending upon facility status. On production systems, DCS outages will occur nine times throughout performance of the test. These outages are expected to last about 10 minutes each.

The productivity of chemical plants and petroleum refineries depends on the performance of alarm systems. Alarm history collected from distributed control systems (DCS) provides useful information about past plant alarm system performance. However, the discovery of patterns and relationships from such data can be very difficult and costly. Due to various factors such as a high volume of alarm data (especially during plant upsets), huge amounts of nuisance alarms, and very large numbers of individual alarm tags, manual identification and analysis of alarm logs is usually a labor-intensive and time-consuming task. This chapter describes a data mining approach for analyzing alarm logs in a chemical plant. The main idea of the approach is to investigate dependencies between alarms effectively by considering the temporal context and time intervals between different alarm types, and then employing a data mining technique capable of discovering patterns associated with these time intervals. A prototype has been implemented to allow an active exploration of the alarm grouping data space relevant to the tags of interest.