It would not be possible to confidently qualify weapon systems performance or validate computer codes without knowing the uncertainty of the experimental data used. This report provides uncertainty estimates associated with thermocouple data for temperature measurements from two of Sandia's large-scale thermal facilities. These two facilities (the Radiant Heat Facility (RHF) and the Lurance Canyon Burn Site (LCBS)) routinely gather data from normal and abnormal thermal environment experiments. They are managed by Fire Science & Technology Department 09132.Uncertainty analyses were performed for several thermocouple (TC) data acquisition systems (DASs) used at the RHF and LCBS. These analyses apply to Type K, chromel-alumel thermocouples of various types: fiberglass sheathed TC wire, mineral-insulated, metal-sheathed (MIMS) TC assemblies, and are easily extended to other TC materials (e.g., copper-constantan). Several DASs were analyzed: 1) A HewlettPackard (HP) 3852A system, and 2) several National Instrument (NI) systems. The uncertainty analyses were performed on the entire system from the TC to the DAS output file. Uncertainty sources include TC mounting errors, ANSI standard calibration uncertainty for Type K TC wire, potential errors due to temperature gradients inside connectors, extension wire uncertainty, DAS hardware uncertainties including noise, common mode rejection ratio, digital voltmeter accuracy, mV to temperature conversion, analog to digital conversion, and other possible sources. Typical results for "normal" environments (e.g., maximum of 300-400 K) showed the total uncertainty to be about ±1% of the reading in absolute temperature. In high temperature or high heat flux ("abnormal") thermal environments, total uncertainties range up to ±2-3% of the reading (maximum of 1300 K). The higher uncertainties in abnormal thermal environments are caused by increased errors due to the effects of imperfect TC attachment to the test item. "Best practices" are provided in Section 9 to help the user to obtain the best measurements possible.

The objective of this report is to develop uncertainty estimates for three heat flux measurement techniques used for the measurement of incident heat flux in a combined radiative and convective environment. This is related to the measurement of heat flux to objects placed inside hydrocarbon fuel (diesel, JP-8 jet fuel) fires, which is very difficult to make accurately (e.g., less than 10%). Three methods will be discussed: a Schmidt-Boelter heat flux gage; a calorimeter and inverse heat conduction method; and a thin plate and energy balance method. Steady state uncertainties were estimated for two types of fires (i.e., calm wind and high winds) at three times (early in the fire, late in the fire, and at an intermediate time). Results showed a large uncertainty for all three methods. Typical uncertainties for a Schmidt-Boelter gage ranged from ±23% for high wind fires to ±39% for low wind fires. For the calorimeter/inverse method the uncertainties were ±25% to ±40%. The thin plate/energy balance method the uncertainties ranged from ±21% to ±42%. The 23-39% uncertainties for the Schmidt-Boelter gage are much larger than the quoted uncertainty for a radiative only environment (i.e., ±3%). This large difference is due to the convective contribution and because the gage sensitivities to radiative and convective environments are not equal. All these values are larger than desired, which suggests the need for improvements in heat flux measurements in fires.

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One of the recommendations that came from the NIST investigation of the World Trade Center disaster was the need for quantitative heat flux measurements in larger scale fire safety tests. These heat flux data are needed to support the development of engineering models to predict the performance of fire protection materials and systems. Current standardized fire resistance tests such as ASTM E119 or ISO 834 or IMO A754 are all qualitative tests. The furnace temperature is controlled to a standard time-temperature curve. Implicit assumptions are made that (1) the thermal exposure can be described solely by the measured furnace temperature history and (2) that exposure will be repeatable. Historical variations of 50 % or more in the qualitative fire protection ratings, such as a 1 h fire barrier, between different furnaces or laboratories indicate that these two assumptions are not well founded. This paper describes the use of a proven type of sensor called a directional flame thermometer (DFT) for making quantitative heat flux measurements in fire resistance tests. DFTs have been used for over 20 years to characterize the thermal environment in both large pool fires and in furnaces, to monitor flashover in structure fires, and in many other fire environments. DFTs are passive thermocouple-based sensors. They do not require calibration. Instead, the designs and materials with known thermal properties are fixed to provide a repeatable response. Using inverse heat conduction analysis techniques, heat fluxes are calculated using a heat conduction model of the DFT with temperature-dependent thermal properties and two or more thermocouple temperature measurements in a DFT. A fully nonlinear inverse heat conduction code is used for detailed post-test data analysis. A new data analysis tool for DFTs, called an inverse heat conduction-digital filter functions (IHC-DFF) has been developed for specific DFT designs to provide heat flux measurements in real-time, much like a calibration curve. IHC-DFFs are convolution-type digital filters that are used to provide real-time heat flux readouts during a test or for a quick-look capability for large sets of data. Simpler models are also used for analyzing early (<5–10 min) and late-time DFT data (>15 min). The current work demonstrates that DFT measurements can provide the quantitative data needed to support the development of performance models and improve our understanding of the thermal exposure in fire resistance tests.

The objective of this work was to provide experimental heat transfer boundary condition and reactor pressure vessel (RPV) section thermal response data that can be used to benchmark computer codes that simulate thermal annealing of RPVs. This specific project was designed to provide the Electric Power Research Institute (EPRI) with experimental data that could be used to support the development of a thermal annealing model. A secondary benefit is to provide additional experimental data (e.g., thermal response of concrete reactor cavity wall) that could be of use in an annealing demonstration project. The setup comprised a heater assembly, a 1.2 m x 1.2 m x 17.1 cm thick [4 ft x 4 ft x 6.75 in] section of an RPV (A533B ferritic steel with stainless steel cladding), a mockup of the "mirror" insulation between the RPV and the concrete reactor cavity wall, and a 25.4 cm [lo in] thick concrete wall, 2.1 m x 2.1 m [lo ft x 10 ft] square. Experiments were performed at temperature heat-upkooldown rates of 7, 14, and 2 8 " C h C12.5, 25, and SO'Fh] as measured on the heated face. A peak temperature of 454°C [850°F] was maintained on the heated face until the concrete wall temperature reached equilibrium. Results are most representative of those RPV locations where the heat transfer would be 1-dimensional. Temperature was measured at multiple locations on the heated and unheated faces of the RPV section and the concrete wall. Incident heat flux was measured on the heated face, and absorbed heat flux estimates were generated from temperature measurements and an inverse heat conduction code developed at Sandia National Laboratories called "Sandia One Dimensional Direct and Inverse Thermal" (SODDIT). Through-wall temperature differences, concrete wall temperature response, heat flux absorbed into the RPV surface and incident on the surface are presented. All of these data are useful to modelers developing codes to simulate RPV annealing. Additionally, incident heat flux measurements can be used to design the heater system required to anneal a full-scale RPV. ~\ I Results compare favorably with those reported in NUREGKR-4212.