Risk Management for Nuclear Power Plant in US

To date, our global society is endlessly threatened by disasters. This article devotes to describe both risks and crises on disaster, and especially it deals with the nature of Fukushima case caused by accident of nuclear power plant (aftermath of the disaster at 11th Mar. 2011). Since the human history, this case was one of extreme disasters and multiplied tragedies damaged by quakes, tsunamis, and nuclear power plant accidents. Still now, it presents a number of challenges indeed to be overcome. One of the hardest problems from the inventory of the Fukushima case was characterized as intensive purifications of nuclear pollutions around Fukushima and collective migration of evacuees caused by both natural and human-made disasters. And ongoing disputes against safety seem to vary widely such as compensations, socioeconomic reasons, environmental restorations, and community reconstructions. The author intends to review these issues and discuss future design for the lessons from the disaster.

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RISIKO KONSTRUKSI PADA PEMBANGKIT LISTRIK KONVENSIONAL, SEBAGAI MASUKAN UNTUK KONSTRUKSI PLTN PERTAMA DI INDONESIA

Jurnal Sains dan Teknologi Indonesia ◽

10.29122/jsti.v14i2.914 ◽

2013 ◽

Vol 14 (2) ◽

Author(s):

Dharu Dewi

Keyword(s):

Risk Management ◽

Power Plant ◽

Nuclear Power Plant ◽

Nuclear Power ◽

Power Plants ◽

Risk Identification ◽

Construction Risk ◽

Project Risks ◽

Construction Risks ◽

Conventional Power Plant

In general, Construction Risks of the Conventional Power Plants are almost the same with the Construction Risks at the Nuclear Power Plant (NPP). Construction Risks Experience in the Conventional Power Plant can be used as a lesson learned for Construction of the Nuclear Power Plant. This study method covers the survey, the relevant publication and empiric assessment on the real project risk implementation. The input data have been provided from experiences in conventional power plant. Hence, project risks must be control to make sure that construction activities in accordance to agreed shedule and free from cost overruns. This study can be expected will provide a valuable input to project risks of Construction of the NPP. It is concluded that the risk management can be carried out by risk identification, and implement the selected technique or strategyfor reduction of risk, transfer of risk and retention of risk to anticipate the all risks which is take place at the construction. Risk management system must be carried out by well in order to risk can be minimized.

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Comprehensive Health Risk Management after the Fukushima Nuclear Power Plant Accident

Clinical Oncology ◽

10.1016/j.clon.2016.01.001 ◽

2016 ◽

Vol 28 (4) ◽

pp. 255-262 ◽

Cited By ~ 12

Author(s):

S. Yamashita ◽

Hitoshi Ohto ◽

Masafumi Abe ◽

Koichi Tanigawa ◽

Shunichi Yamashita ◽

...

Keyword(s):

Risk Management ◽

Power Plant ◽

Nuclear Power Plant ◽

Health Risk ◽

Nuclear Power ◽

Nuclear Power Plant Accident ◽

Comprehensive Health ◽

Health Risk Management

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Mathematical Modeling for Contingency Determination for Nuclear Power Plant Construction Projects

Volume 6: Nuclear Education, Public Acceptance and Related Issues; Instrumentation and Controls (I&C); Fusion Engineering; Beyond Design Basis Events ◽

10.1115/icone22-31254 ◽

2014 ◽

Author(s):

Wei Zhao ◽

Shenjun Xu

Keyword(s):

Monte Carlo Simulation ◽

Risk Management ◽

Monte Carlo ◽

Power Plant ◽

Nuclear Power Plant ◽

Construction Projects ◽

Nuclear Power ◽

Historical Data ◽

Plant Construction ◽

Lump Sum

This paper uses the China AP1000 project as an example to exhibit the application of quantitative risk management in nuclear power plant construction projects. For those lump sum contracts, one of the most significant purposes of quantitative risk management is to determine the contingency, i.e. the reserved money and time for projects. This paper studies the application of Monte Carlo simulation in determining the contingency, taking into account the distinctive features of nuclear power projects. Most nuclear power projects, especially advanced ones such as Generation III and above, meet one common obstacle in estimating key economic indicators — the absence of historical data due to its avant-garde design. As cost estimators of the coal power plant contractors may collect their data from thousands of previous cases, nuclear power plant contractors, especially in many developing countries, do not have a shared database of financial data. Some first-of-a-kind nuclear power plants have absolutely no historical data to look up. This paper aims to provide a resolution to this problem. First, the feasibility and representativeness of different probability distributions are compared based on their respective skewness and kurtosis to determine the best-suited distribution in nuclear power projects. This paper also analyzes the use of second-order Monte Carlo simulation in reducing the error caused by the biased estimation of inexperienced risk assessment engineers.

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