Towards a Framework for Non-intrusive Uncertainty Propagation in the Preliminary Design of Aircraft Systems

Ιωάννου, Ιωάννα; Hristov, P.O.; Yong, Hau Kit; Marsh, Robert; Silva, Edmar; Sóbester, András; Ferson, Scott

doi:10.2514/6.2023-2373

Cited by 2 publications

(1 citation statement)

References 40 publications

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“…Furthermore, assuming a distributional shape for the data will produce tighter results, but will often be unjustified, especially at small sample sizes. It must be noted here that tolerance intervals provide statistical rather than mathematical confidence and as such if propagated through all but the simplest subsequent analyses their values may no longer possess the same level of confidence or population bounding, even with the use of purpose-made intrusive (Moore, 2009) or non-intrusive (Ioannou, 2023) techniques. Instead, advanced uncertain numbers, such as confidence boxes, translated to the tolerance domain need to be used to obtain these guarantees (Ferson, et al, 2013).…”

Section: Tolerance Analysismentioning

confidence: 99%

Towards Energy Atlas of Sofia City in Bulgaria

Vitanova,

Petrova-Antonova,

Hristov

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. This paper proposes the first energy atlas of Sofia in Bulgaria. The research uses a geographical information system (GIS) approach and a statistical tolerance methodology to estimate building energy consumption. The buildings were classified into ten categories, and tolerance intervals were computed, which provide a distribution-free summary for the consumption in each class, suitable for spatial visualisation. GIS is used to classify and visualise the results. The results show a clear contrast in the energy consumption between buildings in highly urbanised areas and those in the suburbs. It was found that the high energy consumption belongs to the areas where the shopping, commercial, industrial and sports buildings are located and already developed. The energy consumption bounds were used to enrich a semantic 3D city model of Sofia. This model can be used for further analysis of energy supply, climate change, urban heat islands, and urban health as well as for calculating the climate scenarios. An extensive outline of the utility and directions for future development of the atlas are provided.

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Section: Tolerance Analysismentioning

confidence: 99%

Towards Energy Atlas of Sofia City in Bulgaria

Vitanova,

Petrova-Antonova,

Hristov

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Data Fusion of Wing Pressure Distributions Using Scalable Gaussian Processes

Anhichem,

Timme,

Castagna

et al. 2024

AIAA Journal

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Aircraft design requires a large volume of aerodynamic data to characterize various flight conditions throughout the aircraft’s flight envelope, and the data are typically obtained through wind tunnel testing and numerical analysis. Data acquisition can be costly and inevitably entails multiple sources of uncertainty. Data fusion techniques aim to bring together the strengths and mitigate the limitations of data from various information sources. A multifidelity data fusion framework employing Gaussian process regression is adopted herein and applied to the surface pressure data of a large aircraft wing model. The modeling approach is non-hierarchical in that there is no established hierarchy of accuracy among the information sources. Scalability issues arising from the large volume of data required for the study of pressure distributions are overcome by using an approximate Gaussian process regression based on stochastic variational inference, enabling the data fusion framework to be applied effectively to industry-relevant analysis and design challenges. The approach is demonstrated for a high-dimensional data set generated through wind tunnel testing in an industrial setting and numerical analysis.

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Towards a Framework for Non-intrusive Uncertainty Propagation in the Preliminary Design of Aircraft Systems

Cited by 2 publications

References 40 publications

Towards Energy Atlas of Sofia City in Bulgaria

Towards Energy Atlas of Sofia City in Bulgaria

Data Fusion of Wing Pressure Distributions Using Scalable Gaussian Processes

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