Scaling Laws for Modeling Nuclear Reactor Systems
Amir N. Nahavandi, Frank S. Castellana, Edick N. Moradkhanian
Abstract
Amir N. Nahavandi, Frank S. Castellana, Edick N. Moradkhanian
Abstract
Scale models are used to predict the behavior of nuclear reactor systems during normal and abnormal operation as well as under accident conditions. Three types of scaling procedures are considered: time-reducing, time-preserving volumetric, and time-preserving idealized model/prototype. The necessary relations between the model and the full-scale unit are developed for each scaling type. Based on these relationships, it is shown that scaling procedures can lead to distortion in certain areas that are discussed. It is advised that, depending on the specific unit to be scaled, a suitable procedure be chosen to minimize model-prototype distortion.
OpenAlex reports 113 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Scale models are used to predict the behavior of nuclear reactor systems during normal and abnormal operation as well as under accident conditions. Three types of scaling procedures are considered: time-reducing, time-preserving volumetric, and time-preserving idealized model/prototype. The necessary relations between the model and the full-scale unit are developed for each scaling type. Based on these relationships, it is shown that scaling procedures can lead to distortion in certain areas that are discussed. It is advised that, depending on the specific unit to be scaled, a suitable procedure be chosen to minimize model-prototype distortion.
Key concepts: Scaling, Scaling law, Distortion (music), Computer science, Nuclear reactor, Scale (ratio), Nuclear engineering, Statistical physics