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Division Spotlight
Fuel Cycle & Waste Management
Devoted to all aspects of the nuclear fuel cycle including waste management, worldwide. Division specific areas of interest and involvement include uranium conversion and enrichment; fuel fabrication, management (in-core and ex-core) and recycle; transportation; safeguards; high-level, low-level and mixed waste management and disposal; public policy and program management; decontamination and decommissioning environmental restoration; and excess weapons materials disposition.
Meeting Spotlight
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
Reboot: Nuclear needs a success . . . anywhere
The media have gleefully resurrected the language of a past nuclear renaissance. Beyond the hype and PR, many people in the nuclear community are taking a more measured view of conditions that could lead to new construction: data center demand, the proliferation of new reactor designs and start-ups, and the sudden ascendance of nuclear energy as the power source everyone wants—or wants to talk about.
Once built, large nuclear reactors can provide clean power for at least 80 years—outlasting 10 to 20 presidential administrations. Smaller reactors can provide heat and power outputs tailored to an end user’s needs. With all the new attention, are we any closer to getting past persistent supply chain and workforce issues and building these new plants? And what will the election of Donald Trump to a second term as president mean for nuclear?
As usual, there are more questions than answers, and most come down to money. Several developers are engaging with the Nuclear Regulatory Commission or have already applied for a license, certification, or permit. But designs without paying customers won’t get built. So where are the customers, and what will it take for them to commit?
Werner Burkart
Nuclear Technology | Volume 62 | Number 1 | July 1983 | Pages 81-93
Technical Paper | Radiation Biology and Environment | doi.org/10.13182/NT83-A33235
Articles are hosted by Taylor and Francis Online.
The carcinogenic effects of high levels of ionizing radiation are better understood than those of any other environmental agent. However, the somatic risk from low doses is highly disputed. The uncertainties stem from the fact that due to a multitude of confounding factors a direct estimation of small risks requires impracticably large samples. Therefore, risk estimates for low doses have to be derived indirectly by extrapolation from high-exposure data and are heavily dependent on assumptions about the shape of the dose-response curve. Although radiobiological theories tested mostly on in vitro systems predict a quadratic term in the dose-response equation, which should dominate the shape of the curve at least for sparsely ionizing radiation, the epidemiological data available are not yet sufficient to exclude the possibility of a purely linear relationship. In some cases, apparent thresholds may result from latent periods inversely related to dose. Besides depending on the quality of the radiation, the shape also seems to differ with the type of cancer induced The huge epidemiological data base on atomic bomb survivors, irradiated patients, miners, and other exposed groups can most consistently be fitted to a linear quadratic model For lung cancer in miners resulting from high linear energy transfer alpha radiation and for female breast cancer, the linear component seems to be dominant. A review of some highly publicized reports claiming a large cancer risk from low levels of radiation shows that their credibility is generally low and that most “effects” can be explained by the relatively large statistical fluctuations generally encountered in small samples