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With the advent of modern parallel computing systems, larger and more accurate simulation models have been developed to simulate real-world hardware. These models require verification and validation (V&V), the latter using data acquired from representative hardware to ascertain the uncertainty of the model. An understanding of the errors introduced by the measurement system into the validation assessment allows for the model assessor to attribute errors to the measurement system as opposed to the model or experimental setup. Once the model(s) have been through the validation process, decision makers can better understand the risk associated with using these models. This paper describes one possible procedure to quantify the uncertainty of the data acquisition (DAQ) system.