Determination of transient surface heat flux from the temperature data is one of the traditional techniques applied in many engineering applications. With respect to high speed flight experiments, the time scale of measured temperature data is usually very small (∼ms). So, one-dimensional heat conduction analysis is expensively used to infer surface heating rates on the body. For an analytical modeling, it is necessary to obtain a closed form solution from experimentally measured temperature data. In this paper, a temperature data obtained from a nickel film sensor during a supersonic flight test is considered for analysis. Three different curve fitting techniques are used to recover the temperature history of real time flight, namely, piecewise linear fit, polynomial fitting, and cubic-spline method. A one-dimensional transient heat transfer modeling is used to infer surface heating rates from the closed form temperature solutions. Results obtained from these analysis are compared and it is seen that peak surface heat flux values match very closely for polynomial and cubic-spline fitting of temperature data. But, the piecewise linear fit of temperature data underpredicts the peak surface heat flux value by four times from its counterparts.

Prediction of surface heating rates is of prime importance for the hypersonic flow regime. Experimental and conventional computational efforts overlook the heat transfer phenomenon in the solid due to the rigid assumptions involved in the solution methodologies. In order to address this fact, conjugate heat transfer (CHT) studies are carried out using various coupling techniques to examine their implementation abilities. Three types of solution methodologies are adopted, namely, decoupled, strongly coupled, and loosely coupled analysis. This study is also focused on looking into the effect of a hypersonic flow field on wall heat flux for a finite thickness insulating cylinder at moderately large time scales. Increase in wall temperature and decrease in surface heat flux have been noticed using strong and loose coupling techniques with an increase in simulation time. Decoupled fluid and solid domain analysis is found to be useful for typical shock tunnel test durations (∼1 ms) while investigations with loose coupling techniques are advisable for time scales corresponding to flight testing (∼1 s). Efforts are also made to reason the discrimination in prediction of stagnation point heat flux using conventional computational and experimental analysis.

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Surface heat transfer measurement is an important aspect in many research problems. Thin film heat flux sensor (TFHFS) is mostly considered in such situations for heat flux measurement due to its quick response and high accuracy. In the present studies, multi-walled carbon nanotubes (MWCNTs) are mixed with platinum while making the TFHFSs. Such addition is noticed to increase the sensitivity and decrease the temperature coefficient of resistance (TCR) of the thin film sensors. Improved sensitivity by 151% and 119% for Macor and Quartz sensors has led to increase in strength of the temperature response of the sensors during dynamic calibration experiments. Though heat flux recovery is seen to have encouraging agreement for all the sensors, sensitivity enhancement is noticed to be more prominent and advantageous for Macor based sensors. Present studies recommend adequately finished substrate for better adhesion. Further, use of MWCNTs is advisable especially for low heat flux measurement and also for Macor substrate since either situation demands the higher sensitivity to increase the output response.

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Transient surface heat flux prediction, from temperature signals using one‐dimensional heat conduction modeling, is the major objective of present investigation. The techniques reported in the literature based on spline fitting (linear and cubic) and least square polynomial fitting of temperature data are evaluated for prediction of surface heat flux through various analytical modeling. In addition, a Laplace‐based technique is also incorporated here to predict surface heat flux where the least square polynomial fitting technique is used to discretize the temperature data. The temperature time histories obtained from an in‐house built, one‐dimensional finite volume computation solver, and experiments (i.e., shock tunnel testing and flight data) are considered for the performance assessment of these methods. Heat flux recovery from all the methods for smooth temperature signals is seen to be in good agreement with a reasonable accuracy of ±5%. However, it has been noticed that the spline based fitting techniques supersede the polynomial‐based fitting techniques for prediction of heat flux from discontinuous or noisy temperature signals. © 2013 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley Online Library (wileyonlinelibrary.com/journal/htj). DOI 10.1002/htj.21050