Development of an Operation Support System for the Blast Furnace in the Ironmaking Process: Large-scale Database-based Online Modeling and Integrated Simulators

2008 ◽  
Vol 1 (3) ◽  
pp. 199-206
Author(s):  
Harutoshi OGAI ◽  
Masatoshi OGAWA ◽  
Kenko UCHIDA ◽  
Shinroku MATSUZAKI ◽  
Masahiro ITO
Keyword(s):  
Blast Furnace ◽  
Support System ◽  
Large Scale ◽  
Online Modeling ◽  
Operation Support System ◽  
Ironmaking Process

scholarly journals Large Scale Database-based Online Modeling on Blast Furnace Operation

2004 ◽  
Vol 90 (11) ◽  
pp. 917-924 ◽  
Author(s):  
Masahiro ITO ◽  
Shinroku MATSUZAKI ◽  
Harutoshi OGAI ◽  
Naoki ODATE ◽  
Kenko UCHIDA ◽  
...  
Keyword(s):  
Blast Furnace ◽  
Large Scale ◽  
Furnace Operation ◽  
Blast Furnace Operation ◽  
Online Modeling

Blast furnace operation support system integrated with partial unsteady simulator and LOM

2006 ◽  
Author(s):  
Masatoshi Ogawa ◽  
Junichi Tajima ◽  
Harutoshi Ogai ◽  
Masahiro Ito ◽  
Shinroku Matsuzaki ◽  
...  
Keyword(s):  
Blast Furnace ◽  
Support System ◽  
Furnace Operation ◽  
Blast Furnace Operation ◽  
Operation Support System

Blast Furnace Operation Support System integrated with Partial Unsteady Simulator and LOM

2006 ◽  
Author(s):  
Masatoshi Ogawa ◽  
Junichi Tajima ◽  
Harutoshi Ogai ◽  
Masahiro Ito ◽  
Shinroku Matsuzaki ◽  
...  
Keyword(s):  
Blast Furnace ◽  
Support System ◽  
Furnace Operation ◽  
Blast Furnace Operation ◽  
Operation Support System

Development of Inherently Safe Technologies for Large Scale BWRs: (5) Operation Support System for Plant Accidents

2014 ◽  
Author(s):  
Masaki Kanada ◽  
Ryota Kamoshida ◽  
Yoshihiko Ishii ◽  
Tadaaki Ishikawa ◽  
Setsuo Arita ◽  
...  
Keyword(s):  
Support System ◽  
Large Scale ◽  
Three Dimensional ◽  
Plant Design ◽  
Three Dimensional Model ◽  
Event Identification ◽  
Plant Behavior ◽  
Operation Support System ◽  
Sensor Signals ◽  
Plant Simulation

When accident events are caused by a large-scale natural disaster, conditions beyond those at the plant site may affect the accident. As well, quick diagnosis and recognition of damaged equipment are necessary. We have been developing inherently safe technologies for boiling water reactor (BWR) plants in response to these. An operation support system for plant accident events is one of these technologies. Our operation support system identifies accident events and predicts the progression of plant behavior. The system consists of three main functions: sensor integrity diagnosis, accident event identification, and plant simulation functions. The sensor integrity diagnosis function diagnoses whether sensor signals have maintained their integrity by correlating redundant sensors with the plant design information. The accident event identification function extracts a few of candidate accident events using alarm and normal sensor signals received by the sensor integrity diagnosis function. The scale and position of the accident event are determined by comparing plant simulation results with normal sensor signals. The plant simulation function uses a detailed three-dimensional model of the nuclear reactor and plant. This simulation can predict future plant behavior on the basis of identified accident events. This proposed operation support system provides available results of accident event identification and plant condition prediction to plant operators. This system will reduce the occurrence of false identifications of accident events and human errors of operators.

Large scale database online modeling for blast furnace

2005 ◽  
Author(s):  
M. Ito ◽  
S. Matsuzaki ◽  
N. Odate ◽  
K. Uchida ◽  
H. Ogai ◽  
...  
Keyword(s):  
Blast Furnace ◽  
Large Scale ◽  
Online Modeling

scholarly journals Application of Improved Local Models of Large Scale Database-based Online Modeling to Prediction of Molten Iron Temperature of Blast Furnace

2010 ◽  
Vol 50 (7) ◽  
pp. 939-945 ◽  
Author(s):  
Norio Kaneko ◽  
Shinroku Matsuzaki ◽  
Masahiro Ito ◽  
Haruhisa Oogai ◽  
Kenko Uchida
Keyword(s):  
Blast Furnace ◽  
Large Scale ◽  
Molten Iron ◽  
Local Models ◽  
Online Modeling

Development of Inherently Safe Technologies for Large Scale BWRs: (1) Plant System

2014 ◽  
Author(s):  
Kazuaki Kitou ◽  
Naoyuki Ishida ◽  
Akinori Tamura ◽  
Ryou Ishibashi ◽  
Masaki Kanada ◽  
...  
Keyword(s):  
Support System ◽  
Large Scale ◽  
Cooling System ◽  
Hydrogen Gas ◽  
Air Cooling ◽  
Water Cooling ◽  
Infinite Time ◽  
Operation Support System ◽  
Air Cooling System ◽  
Water Cooling System

The Fukushima Daiichi nuclear accident and their consequences have led to some rethinking about the safety technologies used in boiling water reactors (BWRs). We have been developing the following various safe technologies: a passive water-cooling system, an infinite-time air-cooling system, a hydrogen explosion prevention system, and an operation support system to better deal with reactor accidents. The above mentioned technologies are referred to as “inherently safe technologies”. The passive water-cooling system and infinite-time air-cooling system achieve core cooling without electricity. These systems are intended to cope with a long-term station black out (SBO), such as that which occurred at the Fukushima facility. Both these cooling systems remove relatively high decay heat for the initial 10 days after an accident, and then the infinite-time air-cooling system is used alone to remove attenuated decay heat after 10 days. The hydrogen explosion prevention system consists of a high-temperature resistant fuel cladding made of silicon-carbide (SiC cladding) and a passive autocatalytic recombiner (PAR). Since the SiC cladding generates less hydrogen gas than the current zircaloy fuel cladding when core damage occurs, the risk of hydrogen leakage from a primary containment vessel (PCV) to a reactor building (R/B), such as an operating floor, can be reduced because the pressure in the PCV can be kept lower with less hydrogen gas generation. The leaked hydrogen gas is recombined by the PAR. When a large-scale natural disaster occurs, fast event diagnosis and recognition of damaged equipment are necessary. Therefore, the operation support system consists of event identification and progress prediction functions to reduce the occurrence of false recognitions and human errors. This paper describes the following items: the targeted plant system; the heat exchange tests conducted for both water-cooling and air-cooling systems; the air-cooling enhancing technology for air-cooling in a 4700 MW thermal power class reactor; hydrogen generation tests for SiC material; and the concept of the operation support system.

Blast Furnace Ironmaking Process with Super-High TiO2 in the Slag: Sulfide Capacity

2021 ◽  
Author(s):  
Jiawei Ling ◽  
Zhengde Pang ◽  
Yuyang Jiang ◽  
Zhiming Yan ◽  
Xuewei Lv
Keyword(s):  
Blast Furnace ◽  
Sulfide Capacity ◽  
Blast Furnace Ironmaking ◽  
Ironmaking Process

scholarly journals A Decision Support System for Public Funding of Experimental Development in Energy Research

Energies ◽  
2018 ◽  
Vol 11 (6) ◽  
pp. 1357 ◽  
Author(s):  
Simon Hirzel ◽  
Tim Hettesheimer ◽  
Peter Viebahn ◽  
Manfred Fischedick
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Large Scale ◽  
Public Funding ◽  
Evaluation Process ◽  
Decision Makers ◽  
Market Failures ◽  
Energy Research ◽  
Experimental Development

New energy technologies may fail to make the transition to the market once research funding has ended due to a lack of private engagement to conclude their development. Extending public funding to cover such experimental developments could be one way to improve this transition. However, identifying promising research and development (R&D) proposals for this purpose is a difficult task for the following reasons: Close-to-market implementations regularly require substantial resources while public budgets are limited; the allocation of public funds needs to be fair, open, and documented; the evaluation is complex and subject to public sector regulations for public engagement in R&D funding. This calls for a rigorous evaluation process. This paper proposes an operational three-staged decision support system (DSS) to assist decision-makers in public funding institutions in the ex-ante evaluation of R&D proposals for large-scale close-to-market projects in energy research. The system was developed based on a review of literature and related approaches from practice combined with a series of workshops with practitioners from German public funding institutions. The results confirm that the decision-making process is a complex one that is not limited to simply scoring R&D proposals. Decision-makers also have to deal with various additional issues such as determining the state of technological development, verifying market failures or considering existing funding portfolios. The DSS that is suggested in this paper is unique in the sense that it goes beyond mere multi-criteria aggregation procedures and addresses these issues as well to help guide decision-makers in public institutions through the evaluation process.

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