Biomedical subjects

Charley Yu

Publications and source records attributed to Charley Yu.

3 recordsLinked to original sources

PubMed2005

Model testing for the remediation assessment of a radium contaminated site in Olen, Belgium.

Environmental assessment models are used as decision-aiding tools in the selection of remediation options for radioactively contaminated sites. In most cases, the effectiveness of the remedial actions in terms of dose savings cannot be demonstrated directly, but can be established with the help of environmental assessment models, through the assessment of future radiological impacts. It should be emphasized that, given the complexity of the processes involved and our current understanding of how they operate, these models are simplified descriptions of the behaviour of radionuclides in the environment and therefore imperfect. One way of testing and improving the reliability of the models is to compare their predictions with real data and/or the predictions of other models. Within the framework of the Remediation Assessment Working Group (RAWG) of the BIOMASS (BIOsphere Modelling and ASSessment) programme coordinated by IAEA, two scenarios were constructed and applied to test the reliability of environmental assessment models when remedial actions are involved. As a test site, an area of approximately 100 ha contaminated by the discharges of an old radium extraction plant in Olen (Belgium) has been considered. In the first scenario, a real situation was evaluated and model predictions were compared with measured data. In the second scenario the model predictions for specific hypothetical but realistic situations were compared. Most of the biosphere models were not developed to assess the performance of remedial actions and had to be modified for this purpose. It was demonstrated clearly that the modeller's experience and familiarity with the mathematical model, the site and with the scenario play a very important role in the outcome of the model calculations. More model testing studies, preferably for real situations, are needed in order to improve the models and modelling methods and to expand the areas in which the models are applicable.

Belgium↗

PubMed2005

Deterministic vs. probabilistic analyses to identify sensitive parameters in dose assessment using RESRAD.

The dose assessments for sites containing residual radioactivity usually involve the use of computer models that employ input parameters describing the physical conditions of the contaminated and surrounding media and the living and consumption patterns of the receptors in analyzing potential doses to the receptors. The precision of the dose results depends on the precision of the input parameter values. The identification of sensitive parameters that have great influence on the dose results would help set priorities in research and information gathering for parameter values so that a more precise dose assessment can be conducted. Two methods of identifying site-specific sensitive parameters, deterministic and probabilistic, were compared by applying them to the RESRAD computer code for analyzing radiation exposure for a residential farmer scenario. The deterministic method has difficulty in evaluating the effect of simultaneous changes in a large number of input parameters on the model output results. The probabilistic method easily identified the most sensitive parameters, but the sensitivity measure of other parameters was obscured. The choice of sensitivity analysis method would depend on the availability of site-specific data. Generally speaking, the deterministic method would identify the same set of sensitive parameters as the probabilistic method when 1) the baseline values used in the deterministic method were selected near the mean or median value of each parameter and 2) the selected range of parameter values used in the deterministic method was wide enough to cover the 5th to 95th percentile values from the distribution of that parameter.

Agriculture↗

PubMed2004

Resrad-recycle: a computer model for analyzing radiation exposures resulting from recycling radioactively contaminated scrap metals or reusing radioactively surface-contaminated materials and equipment.

RESRAD-RECYCLE is a computer code designed by Argonne National Laboratory (ANL) to be used in making decisions about the disposition of radioactively contaminated materials and scrap metals. It implements a pathway analysis methodology to evaluate potential radiation exposures resulting from the recycling of contaminated scrap metals and the reuse of surface-contaminated materials and equipment. For modeling purposes, it divides the entire metal recycling process into six steps: (1) scrap delivery, (2) scrap melting, (3) ingot delivery, (4) product fabrication, (5) product distribution, and (6) use of finished product. RESRAD-RECYCLE considers the reuse of surface-contaminated materials in their original forms. It contains representative exposure scenarios for each recycling step and the reuse process; users can also specify scenarios if desired. The model calculates individual and collective population doses for workers involved in the recycling process and for the public using the finished products. The results are then used to derive clearance levels for the contaminated materials on the basis of input dose restrictions. The model accounts for radiological decay and ingrowth, dilution and partitioning during melting, and distribution of refined metal in the various finished products, as well as the varying densities and geometries of the radiation sources during the recycling process. A complete material balance in terms of mass and radioactivity during the recycling process can also be implemented. In an international validation study, the radiation doses calculated by RESRAD-RECYCLE were shown to agree fairly well with actual measurement data.

Body Burden↗