Abstract: In this study of ultimate response guideline (URG), Kuosheng BWR/6 nuclear power plant (NPP) TRACE model was established. The reactor depressurization, low pressure water injection, and containment venting are the main actions of URG. This research focuses to evaluate the efficiency of URG under Fukushima-like conditions. Additionally, the sensitivity study of URG was also performed in this research. The analysis results of TRACE present that URG can keep the peak cladding temperature (PCT) below 1088.7 K (the failure criteria) under Fukushima-like conditions. It implied that Kuosheng NPP was at the safe situation.
Abstract: After the measurement uncertainty recapture (MUR) power uprates, Kuosheng nuclear power plant (NPP) was uprated the power from 2894 MWt to 2943 MWt. For power upgrade, several codes (e.g., TRACE, RELAP5, etc.) were applied to assess the safety of Kuosheng NPP. Hence, the main work of this research is to establish a RELAP5/MOD3.3 model of Kuosheng NPP with SNAP interface. The establishment of RELAP5/SNAP model was referred to the FSAR, training documents, and TRACE model which has been developed and verified before. After completing the model establishment, the startup test scenarios would be applied to the RELAP5/SNAP model. With comparing the startup test data and TRACE analysis results, the applicability of RELAP5/SNAP model would be assessed.
Abstract: In this research, TRACE model of Chinshan BWR/4
nuclear power plant (NPP) has been developed for the simulation and
analysis of ultimate response guideline (URG).The main actions of
URG are the depressurization and low pressure water injection of
reactor and containment venting. This research focuses to verify the
URG efficiency under Fukushima-like conditions. TRACE analysis
results show that the URG can keep the PCT below the criteria
1088.7 K under Fukushima-like conditions. It indicated that Chinshan
NPP was safe.
Abstract: Kuosheng nuclear power plant (NPP) is a BWR/6 type
NPP and located on the northern coast of Taiwan. First, Kuosheng
NPP TRACE model were developed in this research. In order to assess
the system response of Kuosheng NPP TRACE model, startup tests
data were used to evaluate Kuosheng NPP TRACE model. Second, the
overpressurization transient analysis of Kuosheng NPP TRACE model
was performed. Besides, in order to confirm the mechanical property
and integrity of fuel rods, FRAPTRAN analysis was also performed in
this study.
Abstract: This analysis of Kuosheng nuclear power plant (NPP)
was performed mainly by TRACE, assisted with FRAPTRAN and
FRAPCON. SNAP v2.2.1 and TRACE v5.0p3 are used to develop the
Kuosheng NPP SPU TRACE model which can simulate the turbine
trip without bypass transient. From the analysis of TRACE, the
important parameters such as dome pressure, coolant temperature and
pressure can be determined. Through these parameters, comparing
with the criteria which were formulated by United States Nuclear
Regulatory Commission (U.S. NRC), we can determine whether the
Kuoshengnuclear power plant failed or not in the accident analysis.
However, from the data of TRACE, the fuel rods status cannot be
determined. With the information from TRACE and burn-up analysis
obtained from FRAPCON, FRAPTRAN analyzes more details about
the fuel rods in this transient. Besides, through the SNAP interface, the
data results can be presented as an animation. From the animation, the
TRACE and FRAPTRAN data can be merged together that may be
realized by the readers more easily. In this research, TRACE showed
that the maximum dome pressure of the reactor reaches to 8.32 MPa,
which is lower than the acceptance limit 9.58 MPa. Furthermore,
FRAPTRAN revels that the maximum strain is about 0.00165, which
is below the criteria 0.01. In addition, cladding enthalpy is 52.44 cal/g
which is lower than 170 cal/g specified by the USNRC NUREG-0800
Standard Review Plan.
Abstract: Ontology-based modelling of multi-formatted
software application content is a challenging area in content
management. When the number of software content unit is huge and
in continuous process of change, content change management is
important. The management of content in this context requires
targeted access and manipulation methods. We present a novel
approach to deal with model-driven content-centric information
systems and access to their content. At the core of our approach is an
ontology-based semantic annotation technique for diversely
formatted content that can improve the accuracy of access and
systems evolution. Domain ontologies represent domain-specific
concepts and conform to metamodels. Different ontologies - from
application domain ontologies to software ontologies - capture and
model the different properties and perspectives on a software content
unit. Interdependencies between domain ontologies, the artifacts and
the content are captured through a trace model. The annotation traces
are formalised and a graph-based system is selected for the
representation of the annotation traces.