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Persistent URL http://purl.org/net/epubs/work/25359
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Record Id 25359
Title Response function estimation from multi-input systems
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Abstract In this work a novel formalism to estimate the vector linear impulse response functions from the experimental data observed from a multi-input system, allowing for correlation between the inputs, is developed. Time series statistical moments are estimated from the data and used as the basis of a set of simultaneous equations in the unknown response functions. These simultaneous equations are solved using standard matrix methods for the unknown linear response functions. The ability of the technique to correctly estimate the response functions of a multi-input linear system to a high degree of accuracy is demonstrated, using a numerical example where the properties of the system are known and there is strong correlation between the input data. This novel technique is then used to estimate the response functions of the coupled convective and radiative processes, that act at the internal surface of the ceiling of an experimental building. The area under the estimated response function of each process is the gain or heat transfer coefficient for that process. The estimated response functions from a multi-input analysis are compared with those obtained from a set of analyses where each input is treated as being independant of the others. The response functions, of each process, estimated by the two approaches (single- and multi- input) were employed to predict the surface heat flux, given the convective and radiative driving forces, which could be compared with the measured heat flux. The differences between the results obtained from the two approaches are explained by considering the correlation between the driving forces of the convective and radiative processes.
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Language English (EN)
Type Details URI(s) Local file(s) Year
Report RAL Technical Reports RAL-93-017. 1993. RAL-TR-1993-017.pdf 1993