Standard Guide for Selection and Use of Mathematical Methods for Calculating Absorbed Dose in Radiation Processing Applications

Importancia y uso:

4.1 Use as an Analytical Tool—Mathematical methods provide an analytical tool to be employed for many applications related to absorbed dose determinations in radiation processing. Mathematical calculations may not be used as a substitute for routine dosimetry in some applications (for example, medical device sterilization, food irradiation).

4.2 Dose Calculation—Absorbed-dose calculations may be performed for a variety of photon/electron environments and irradiator geometries.

4.3 Evaluate Process Effectiveness—Mathematical models may be used to evaluate the impact of changes in product composition, loading configuration, and irradiator design on dose distribution.

4.4 Complement or Supplement to Dosimetry—Dose calculations may be used to establish a detailed understanding of dose distribution, providing a spatial resolution not obtainable through measurement. Calculations may be used to reduce the number of dosimeters required to characterize a procedure or process (for example, dose mapping).

4.5 Alternative to Dosimetry—Dose calculations may be used when dosimetry is impractical (for example, granular materials, materials with complex geometries, material contained in a package where dosimetry is not practical or possible).

4.6 Facility Design—Dose calculations are often used in the design of a new irradiator and can be used to help optimize dose distribution in an existing facility or radiation process. The use of modeling in irradiator design can be found in Refs (2-7).

4.7 Validation—The validation of the model should be done through comparison with reliable and traceable dosimetric measurements. The purpose of validation is to demonstrate that the mathematical method makes reliable predictions of dose and other transport quantities. Validation compares predictions or theory to the results of an appropriate experiment. The degree of validation is commensurate with the application. Guidance is given in the documents referenced in Annex A2.

4.8 Verification—Verification is the confirmation of the mathematical correctness of a computer implementation of a mathematical method. This can be done, for example, by comparing numerical results with known analytic solutions or with other computer codes that have been previously verified. Verification should be done to ensure that the simulation is appropriate for the intended application. Refer to 3.1.24.

Note 2: Certain applications of the mathematical model deal with Operational Qualification (OQ), Performance Qualification (PQ) and process control in radiation processing such as the sterilization of healthcare products. The application and use of the mathematical model in these applications may have to meet regulatory requirements. Refer to Section 6 for prerequisites for application of a mathematical method and Section 8 for requirements before routine use of the mathematical method.

4.9 Uncertainty—An absorbed dose prediction should be accompanied by an estimate of overall uncertainty, as it is with absorbed-dose measurement (refer to ASTM 51707 and JCGM100:2008 and JCGM200:2012). In many cases, absorbed-dose measurement helps to establish the uncertainty in the dose calculation.

4.10 This guide should not be used as the only reference in the selection and use of mathematical models. The user is encouraged to contact individuals who are experienced in mathematical modelling and to read the relevant publications in order to select the best tool for their application. Radiation processing is an evolving field and the references cited in the annotated examples of Annex A6 are representative of the various published applications. Where a method is validated with dosimetry, it becomes a benchmark for that particular application.

Subcomité:

E61.04

Referida por:

E2628-20, E3270-21E01, E2628-20E01, E1608-15R22E01, E1702-13R21E01, E2303-24E01, E1649-22E01, E1707-22E01, E1818-20E01, E1900-23E01

Volúmen:

12.02

Número ICS:

07.020 (Mathematics), 17.240 (Radiation measurements)

Palabras clave:

benchmarking; deterministic method; discrete ordinates; empirical method; mathematical models; modeling; modelling; Monte Carlo; point kernel; radiation processing; radiation transport; stochastic; validation; verification;