The article is devoted to the substantiation of the procedure for testing complex technical systems to assess the probability of performing the task, taking into account a priori data obtained from the results of modeling, field tests of components and prototypes, operation of analogues, etc. The conditions for the formation of a combined sample consisting of field experiments and experiments counted on the results of modeling are justified. Data uniformity is checked using the Student's criterion. The minimum volume of full-scale tests is determined by the requirement of equality of the amount of Fischer information about the estimated parameter obtained during full-scale tests and at the expense of a priori data A strategy for conducting field experiments is proposed, in which the required quality of evaluating the probability of completing the task is achieved with the minimum possible number of field experiments. At the first stage, a series of experiments with a volume equal to half of the required sample size is performed. At the second stage, the experiments are conducted sequentially with an assessment after each experiment of the requirements for the amount of information about the evaluated parameter and for the uniformity of data. Experiments are terminated when the specified requirements are met, and then a combined sample is formed, which is used to evaluate the probability of the system performing the task. A model example is considered. The estimation of the gain in the number of experiments performed at different probability values was carried out.
Developing potency factors for thyroid hormone disruption by PFASs using TTR-TRβ CALUX® bioassay and assessment of PFASs mixtures in technical products