Probabilistic Modeling of Updating Epistemic Uncertainty In Pile Capacity Prediction With a Single Failure Test Result

Indra Djati Sidi

Abstract


Abstract

The model error N has been introduced to denote the discrepancy between measured and predicted capacity of pile foundation. This model error is recognized as epistemic uncertainty in pile capacity prediction. The statistics of N have been evaluated based on data gathered from various sites and may be considered only as a general-error trend in capacity prediction, providing crude estimates of the model error in the absence of more specific data from the site. The results of even a single load test to failure, should provide direct evidence of the pile capacity at a given site. Bayes theorem has been used as a rational basis for combining new data with previous data to revise assessment of uncertainty and reliability. This study is devoted to the development of procedures for updating model error (N), and subsequently the predicted pile capacity with a results of single failure test.

Abstrak

Rasio antara kapasitas aksial pondasi tiang yang diukur melalui percobaan uji beban dengan kapasitas yang dihitung melalui formula dapat dianggap sebagai model error N yang menggambarkan kesalahan epistemic dalam perhitungan pondasi tiang. Data statistik N yang diperoleh dari berbagai lokasi dapat dianggap sebagai kecendrungan umum kesalahan (general error trend) yang melekat pada formula yang digunakan. Hasil percobaaan beban pada lokasi tertentu dimana bangunan terletak harus menjadi indikator langsung akan variasi kapasitas aksial tiang pada lokasi tertentu. Pada studi ini model error awal sebagai nilai kecendrungan umum dapat di update melalui kerangka teorema Bayes. Pengaruh kesalahan akibat friksi dalam alat tekan hidrolik disertakan dalam formulasi. Statistik nilai N yang baru dapat digunakan untuk menentukan kapasitas tiang ataupun angka keamanan yang dipakai dalam perencanaan untuk mencapai target keandalan tertentu.


Keywords


Axial pile capacity, bayesian theorem, epistemic uncertainty, factor of safety, model error.

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References


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DOI: http://dx.doi.org/10.5614%2Fjts.2017.24.3.1

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