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sample_load_profile

Residential load profile


Description

sample_load_profile contains the default residential load profile. It can be invoked via sample_load_profile. Its parameters can be modified with sample_load_profile["parameterName"].

Usage

sample_load_profile

Format

An object of class data.frame with 1 rows and 13 columns.

Details

- The load is defined as

τ(t) = φ*R_o*(γ*D_d+D_s(t)+D_e(t)) / (γ*α_d+α_l)

- Following the National Building Code of Canada (NBCC) standards document CAN/CSA-O86, assume that γ = 0.25, α_d = 1.25, α_l = 1.5.

- R_o is the characteristic value depending on the lumber population. By default, R_o = 2722psi.

- φ is the performance factor.

- According to Foschi, Folz, and Yao(1989)

1. D_d is the normalized dead load for the weight of the structure, and D_d ~ N(load_d_mean, load_d_sd). By default, load_d_mean = 1, load_d_sd = 0.01.

2. D_s(t) is the sustained load. D_e(t) is the extraordinary load. D_s(t) and D_e(t) are two independent processes.

3. The sizes of the loads are modelled using gamma distributions G(k,θ) where k and θ represent the shape and scale parameters. The random times between and during live load events are modeled using exponential distributions Exp(λ) with mean λ^(-1). Parameters for these models were previously fitted using survey data.

4. The process D_s(t) consists of a sequence of successive periods of sustained occupancy each with iid duration T_s ~ Exp(1 / mean_Ts). During these periods of occupancy D_ls ~ G(load_s_shape, load_s_scale) iid. By default, mean_Ts = 10, load_s_shape = 3.122, and load_s_scale = 0.0481.

5. The process D_e(t) consists of brief periods of extraordinary loads, separated by longer periods with no load T_e ~ Exp(mean_Te) of expected duration 1 year. When extraordinary loads occur, they last for iid periods of random duration T_p ~ Exp(1 / mean_Tp). The normalized loads D_le during these brief periods are iid with gamma distribution D_le ~ G(load_p_shape, load_p_scale). By default, mean_Te = 1, mean_Tp = 0.03835, load_p_shape = 0.826, and load_p_scale = 0.1023.

References

Foschi, R. O., Folz, B., and Yao, F. (1989), Reliability-Based Design of Wood Structures (Vol. 34), Vancouver, BC: Department of Civil Engineering, University of British Columbia.

Corotis, R. B., and Doshi, V. A. (1977), “Probability Models for Live-Load Survey Results,” Journal of the Structural Division, 103, 1257–1274.

Chalk, P. L., and Corotis, R. B. (1980), “Probability Model for Design Live Loads,” Journal of the Structural Division, 106, 2017–2033.

Harris, M. E., Bova, C. J., and Corotis, R. B. (1981), “Area-Dependent Pro-cesses for Structural Live Loads,” Journal of the Structural Division, 107,857–872.

Yang, C. H., Zidek, J. V., & Wong, S. W. (2019). Bayesian analysis of accumulated damage models in lumber reliability. Technometrics, 61(2), 233-245.


abcADM

Fit Accumulated Damage Models and Estimate Reliability using ABC

v1.0
GPL-3
Authors
Zongjun Liu [aut], Chun-Hao Yang [aut], John Burkardt [ctb], Samuel W.K. Wong [aut, cre]
Initial release

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