ADAM: An Accident Diagnostic, Analysis and Management System — Applications to Severe Accident Simulation and Management

2002 ◽  
Author(s):  
M. J. Zavisca ◽  
M. Khatib-Rahbar ◽  
H. Esmaili ◽  
R. Schulz
Keyword(s):  
Real Time ◽  
Water Injection ◽  
Management Training ◽  
Computer Applications ◽  
Severe Accident ◽  
Diagnostic Analysis ◽  
Gas Generation ◽  
Accident Management ◽  
Accident Simulation ◽  
On Line

The Accident Diagnostic, Analysis and Management (ADAM) computer code has been developed as a tool for on-line applications to accident diagnostics, simulation, management and training. ADAM’s severe accident simulation capabilities incorporate a balance of mechanistic, phenomenologically based models with simple parametric approaches for elements including (but not limited to) thermal hydraulics; heat transfer; fuel heatup, meltdown, and relocation; fission product release and transport; combustible gas generation and combustion; and core-concrete interaction. The overall model is defined by a relatively coarse spatial nodalization of the reactor coolant and containment systems and is advanced explicitly in time. The result is to enable much faster than real time (i.e., 100 to 1000 times faster than real time on a personal computer) applications to on-line investigations and/or accident management training. Other features of the simulation module include provision for activation of water injection, including the Engineered Safety Features, as well as other mechanisms for the assessment of accident management and recovery strategies and the evaluation of PSA success criteria. The accident diagnostics module of ADAM uses on-line access to selected plant parameters (as measured by plant sensors) to compute the thermodynamic state of the plant, and to predict various margins to safety (e.g., times to pressure vessel saturation and steam generator dryout). Rule-based logic is employed to classify the measured data as belonging to one of a number of likely scenarios based on symptoms, and a number of “alarms” are generated to signal the state of the reactor and containment. This paper will address the features and limitations of ADAM with particular focus on accident simulation and management.

A Method for Online Calibration of MAAP Simulations in a Severe Accident Management System Database

2017 ◽  
Author(s):  
Weifeng Xu ◽  
Fangqing Yang ◽  
Peng Chen ◽  
Yehong Liao
Keyword(s):  
Management System ◽  
Reactor Vessel ◽  
Severe Accident ◽  
Outlet Temperature ◽  
Online Calibration ◽  
Support Plate ◽  
Initial Event ◽  
Accident Management ◽  
Accident Simulation ◽  
Plate Failure

During a nuclear plant accident, five accident events are usually considered, including core uncovery, core outlet temperature arrived at 650 °C, core support plate failure, reactor vessel failure and containment failure. In accident emergency aspect, when an accident happens, the initial event can be utilized in the severe accident management system which is based on MAAP to simulate the long process of the accident, so as to provide support for operators to take actions. However, in MAAP, many sensitivity parameters exist, which reflect phenomenological uncertainty or models uncertainty and will influence the happening time of the five accident events above. In this paper, based on MAAP5 and LOCAs, the CPR1000 is simulated to analyze the influences of MAAP5’s sensitivity parameters reflecting phenomenological uncertainty on the accident process, which is aimed to find out the sensitivity parameters associated to the five important accident events and build the database between these sensitivity parameters and five accident events’ happening time. Then, based on the research above, a preliminary approach to optimize the MAAP5’s accidents simulation is introduced, which is realized by adjusting sensitivity parameters. Finally, the application of this research will be showed in a severe accident management system developed by us. The research results offer great reference significance for the severe accident simulation and prediction in MAAP5.

Introduction of Three Methods Used for the Nuclear Accident Diagnosis

2017 ◽  
Author(s):  
Peng Chen ◽  
Weifeng Xu ◽  
Fangqing Yang ◽  
Yehong Liao
Keyword(s):  
Management System ◽  
Nuclear Power ◽  
Nuclear Accident ◽  
Severe Accident ◽  
Severe Accidents ◽  
Accident Management ◽  
Accident Simulation ◽  
Diagnosis Method ◽  
Nuclear Severe Accidents ◽  
Diagnosis Technique

In order to deal with the nuclear severe accidents, the severe accident management systems are popularly considered and developed at home and abroad recently. A severe accident management system usually includes these functional parts: accident monitor, accident diagnosis, accident simulation, accident prognosis and SAMG support. Here, the accident diagnosis part is mainly concerned, and three nuclear accident diagnosis methods are introduced here, including BP neural network method, SDG expert diagnosis technique and artificial diagnosis method, which are also applied to a severe accident management system developed by us. In this paper, firstly, the severe accident management system developed by us will be introduced briefly. Then, three accident diagnosis methods for nuclear power plant (NPP) are showed and described in detail. At last, two cases including LOCA and SGTR accidents are used for the verification of these accident diagnosis methods and some analyzing results and conclusions are given. The results show that the three diagnosis methods are very useful for the accident diagnosis of NPP, which can diagnose the accident type accurately and offer much information or support to the severe accident management system and operators. The paper offers some reference significance for the research of accident diagnosis methods and the development of severe accident management system.

scholarly journals Comparative Analysis of Calculation Possibilities of MACCS and RODOS Computer Codes for Emergency Response and Analysis of Radiation Consequences of Severe Accidents at NPPs

2017 ◽  
Author(s):  
V. Bogorad ◽  
T. Lytvynska ◽  
Ia. Bielov
Keyword(s):  
Comparative Analysis ◽  
Real Time ◽  
Equivalent Dose ◽  
Severe Accident ◽  
The Public ◽  
Severe Accidents ◽  
Analysis Of Results ◽  
On Line ◽  
Computer Codes ◽  
Accident Consequence

The paper presents a brief description of the Real-time On-line Decision Support System (RODOS) and MELCOR Accident Consequence Code System (MACCS) and evaluates the application of these codes for assessment of radiation impact on the public and environment in case of a severe accident at NPP in real time mode. The experts performed comparative analysis of results obtained from calculations using RODOS, WinMACCS and HotSpot codes. In the framework of the research, the chosen comparative criteria were assessed: total effective dose, thyroid equivalent dose, skin equivalent dose, I-131 and Cs-137 ground concentration at different distances up to 50 kilometers from the source of release.

Adaptive Signal Analysis and Interpretation for Real-time Intelligent Patient Monitoring

1994 ◽  
Vol 33 (01) ◽  
pp. 60-63 ◽  
Author(s):  
E. J. Manders ◽  
D. P. Lindstrom ◽  
B. M. Dawant
Keyword(s):  
Computer Architecture ◽  
Real Time ◽  
Data Abstraction ◽  
Monitoring Strategy ◽  
Intelligent Monitoring ◽  
Patient Status ◽  
On Line ◽  
Main Components ◽  
And Control ◽  
Adaptive Signal

Abstract:On-line intelligent monitoring, diagnosis, and control of dynamic systems such as patients in intensive care units necessitates the context-dependent acquisition, processing, analysis, and interpretation of large amounts of possibly noisy and incomplete data. The dynamic nature of the process also requires a continuous evaluation and adaptation of the monitoring strategy to respond to changes both in the monitored patient and in the monitoring equipment. Moreover, real-time constraints may imply data losses, the importance of which has to be minimized. This paper presents a computer architecture designed to accomplish these tasks. Its main components are a model and a data abstraction module. The model provides the system with a monitoring context related to the patient status. The data abstraction module relies on that information to adapt the monitoring strategy and provide the model with the necessary information. This paper focuses on the data abstraction module and its interaction with the model.

Application of two alternative shutdown severe accident management guideline (SSAMG) entry conditions for CPR1000

Kerntechnik ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. 22-28
Author(s):  
Z. Huang ◽  
H. Miao ◽  
H. Hsieh ◽  
N. Li ◽  
D. Gu
Keyword(s):  
Severe Accident ◽  
Management Guideline ◽  
Accident Management

Nitrogen Removal in a Real-Time Controlled Sequencing Batch Membrane Bioreactor

2010 ◽  
Vol 5 (3) ◽  
Author(s):  
Cheng-Nan Chang ◽  
Li-Ling Lee ◽  
Han-Hsien Huang ◽  
Ying-Chih Chiu
Keyword(s):  
Real Time ◽  
Nitrogen Removal ◽  
Membrane Bioreactor ◽  
Synthetic Wastewater ◽  
Real Time Control ◽  
Time Control ◽  
Cake Layer ◽  
On Line ◽  
Solid Liquid ◽  
Solid Liquid Separation

The performance of a real-time controlled Sequencing Batch Membrane Bioreactor (SBMBR) for removing organic matter and nitrogen from synthetic wastewater has been investigated in this study under two specific ammonia loadings of 0.0086 and 0.0045g NH4+-N gVSS−1 day−1. Laboratory results indicate that both COD and DOC removal are greater than 97.5% (w/w) but the major benefit of using membrane for solid-liquid separation is that the effluent can be decanted through the membrane while aeration is continued during the draw stage. With a continued aeration, the sludge cake layer is prevented from forming thus alleviating the membrane clogging problem in addition to significant nitrification activities observed in the draw stage. With adequate aeration in the oxic stage, the nitrogen removal efficiency exceeding 99% can be achieved with the SBMBR system. Furthermore, the SBMBR system has also been used to study the occurrence of ammonia valley and nitrate knee that can be used for real-time control of the biological process. Under appropriate ammonia loading rates, applicable ammonia valley and nitrate knee are detected. The real-time control of the SBMBR can be performed based on on-line ORP and pH measurements.

Modifications of rainfall runoff and decision finding models for on-line simulation in real time control

1999 ◽  
Vol 39 (9) ◽  
pp. 201-207
Author(s):  
Andreas Cassar ◽  
Hans-Reinhard Verworn
Keyword(s):  
Real Time ◽  
Urban Drainage ◽  
Rain Event ◽  
Rainfall Runoff ◽  
Real Time Control ◽  
Design Storm ◽  
Time Control ◽  
Timing Data ◽  
On Line ◽  
Rainfall Runoff Model

Most of the existing rainfall runoff models for urban drainage systems have been designed for off-line calculations. With a design storm or a historical rain event and the model system the rainfall runoff processes are simulated, the faster the better. Since very recently, hydrodynamic models have been considered to be much too slow for real time applications. However, with the computing power of today - and even more so of tomorrow - very complex and detailed models may be run on-line and in real time. While the algorithms basically remain the same as for off-line simulations, problems concerning timing, data management and inter process communication have to be identified and solved. This paper describes the upgrading of the existing hydrodynamic rainfall runoff model HYSTEM/EXTRAN and the decision finding model INTL for real time performance, their implementation on a network of UNIX stations and the experiences from running them within an urban drainage real time control project. The main focus is not on what the models do but how they are put into action and made to run smoothly embedded in all the processes necessary in operational real time control.

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