Guardian Energy


Fukushima: robot images show massive deposits thought to be melted nuclear fuel

Guardian Energy

Images captured by an underwater robot on Saturday showed massive deposits believed to be melted nuclear fuel covering the floor of a damaged reactor at Japan's destroyed Fukushima nuclear plant. The robot found large amounts of solidified lava-like rocks and lumps in layers as thick as 1m on the bottom inside a main structure called the pedestal that sits underneath the core inside the primary containment vessel of Fukushima's Unit 3 reactor, said the plant's operator, Tokyo Electric Power Co. On Friday, the robot spotted suspected debris of melted fuel for the first time since the 2011 earthquake and tsunami caused multiple meltdowns and destroyed the plant. Locating and analysing the fuel debris and damage in each of the plant's three wrecked reactors is crucial for decommissioning the plant. During this week's probe, cameras mounted on the robot showed extensive damage caused by the core meltdown, with fuel debris mixed with broken reactor parts, suggesting the difficult challenges ahead in the decades-long decommissioning of the plant.


Robot shows suspected melted nuclear fuel at Fukushima reactor – video

Guardian Energy

An underwater robot has captured images of what is believed to be suspected debris of melted nuclear fuel inside one of the reactors at the Fukushima nuclear plant in Japan.


Weather system revamp hopes to bring sunshine to US economy

Guardian Energy

The legislation empowers the National Oceanic Atmospheric Administration (NOAA) to boost its ability to predict major weather-related events, such as hurricanes, droughts, floods and wildfires. Using faster, more powerful computers and more detailed data of weather patterns could increase the accuracy, Seitter says. Businesses have been able to access accurate, customizable weather forecasting online only in the last decade or so, says Bill Gail, chief technology officer at private forecaster Global Weather Corporation. Xcel Energy, who uses Gail's firm to anticipate wind energy production, improved its wind forecasting accuracy by nearly 35% from 2009 to 2015.