Uncertainty Propagation in Floating Raft System by FRF-Based Substructuring Method for Elastic Coupling

2013 ◽  
pp. 165-173 ◽  
Author(s):  
Huang Xiuchang ◽  
Hua Hongxing ◽  
Chen Feng ◽  
Xu Shiyin
Keyword(s):  
Uncertainty Propagation ◽  
Elastic Coupling ◽  
Floating Raft

Respon Pertumbuhan dan Produksi Tiga Varietas Selada pada Hidroponik Sistem Floating Raft

2018 ◽  
Vol 6 (03) ◽  
pp. 273-282
Author(s):  
Carmia Dwi Pratiwi ◽  
Ari Susatyo Nugroho ◽  
Muhammad Anas Dzakiy
Keyword(s):  
Random Sampling ◽  
Simple Random Sampling ◽  
Floating Raft

Penelitian ini bertujuan untuk mengetahui respon pertumbuhan dan produksi tiga varietas selada dengan teknik hidroponik menggunakan sistem Floating Raft ditinjau dari tinggi tanaman, jumlah daun dan berat basah di dekat input, tengah dan dekat output. Waktu penelitian yaitu 19 Mei – 13 Juni 2018 di PT. Hidroponik Agrofarm Bandungan. Pengambilan sampel dilakukan dengan cara simple random sampling pada ketiga varietas selada yaitu selada Jonction varietas L. sativa capitata, selada Romaine varietas L. sativa longifolia dan selada Red Saladbowl varietas L. sativa crispa. Penelitian menggunakan Rancangan Acak Lengkap dengan 3 kali ulangan. Data dianalisis menggunakan uji sidik ragam (ANOVA) dan dilanjut menggunakan uji BNT 5%. Hasil penelitian menunjukkan bahwa respon pertumbuhan dan produksi tertinggi dari tiga varietas selada pada hidroponik sistem Floating Raft terjadi pada selada yang ditempatkan di dekat input nutrisi.

scholarly journals Deep Neural Network and Polynomial Chaos Expansion-Based Surrogate Models for Sensitivity and Uncertainty Propagation: An Application to a Rockfill Dam

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1830
Author(s):  
Gullnaz Shahzadi ◽  
Azzeddine Soulaïmani
Keyword(s):  
Polynomial Chaos ◽  
Complex Structure ◽  
Uncertainty Propagation ◽  
Surrogate Models ◽  
Polynomial Chaos Expansion ◽  
Soil Parameters ◽  
Chaos Expansion ◽  
Rockfill Dam ◽  
Parametric Studies ◽  
The Impact

Computational modeling plays a significant role in the design of rockfill dams. Various constitutive soil parameters are used to design such models, which often involve high uncertainties due to the complex structure of rockfill dams comprising various zones of different soil parameters. This study performs an uncertainty analysis and a global sensitivity analysis to assess the effect of constitutive soil parameters on the behavior of a rockfill dam. A Finite Element code (Plaxis) is utilized for the structure analysis. A database of the computed displacements at inclinometers installed in the dam is generated and compared to in situ measurements. Surrogate models are significant tools for approximating the relationship between input soil parameters and displacements and thereby reducing the computational costs of parametric studies. Polynomial chaos expansion and deep neural networks are used to build surrogate models to compute the Sobol indices required to identify the impact of soil parameters on dam behavior.

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