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Top-seat angle connection is known as one of the usual uncomplicated beam-to-column joints used in steel structures. This article investigates the fire performance of welded top-seat angle connections.

A finite element (FE) model, including nonlinear contact interactions, high-temperature properties of steel, and material and geometric nonlinearities was created for accomplishing the fire performance analysis. The FE model was verified by comparing its simulation results with test data. Using the verified model, 24 steel-framed top-seat angle connection assemblies are modeled. Parametric studies were performed employing the verified FE model to study the influence of critical factors on the performance of steel beams and their welded angle joints.

The results obtained from the parametric studies illustrate that decreasing the gap size and the top angle size and increasing the top angles thickness affect fire behavior of top-seat angle joints and decrease the beam deflection by about 16% at temperatures beyond 570 °C. Also, the fire-resistance rating of the beam with seat angle stiffener increases about 15%, compared to those with and without the web stiffener. The failure of the beam happens when the deflections become more than span/30 at temperatures beyond 576 °C. Results also show that load type, load ratio and axial stiffness levels significantly control the fire performance of the beam with top-seat angle connections in semi-rigid steel frames.

Development of design methodologies for these joints and connected beam in fire conditions is delayed by current building codes due to the lack of adequate understanding of fire behavior of steel beams with welded top-seat angle connections.

A progressive hybrid censoring scheme (PHCS) becomes impractical for ensuring dependable outcomes when there is a low likelihood of encountering a small number of failures prior to the predetermined terminal time T. The generalized progressive hybrid censoring scheme (GPHCS) efficiently addresses to overcome the limitation of the PHCS.

In this article, estimation of model parameter, survival and hazard rate of the Unit-Lindley distribution (ULD), when sample comes from the GPHCS, have been taken into account. The maximum likelihood estimator has been derived using Newton–Raphson iterative procedures. Approximate confidence intervals of the model parameter and their arbitrary functions are established by the Fisher information matrix. Bayesian estimation procedures have been derived using Metropolis–Hastings algorithm under squared error loss function. Convergence of Markov chain Monte Carlo (MCMC) samples has been examined. Various optimality criteria have been considered. An extensive Monte Carlo simulation analysis has been shown to compare and validating of the proposed estimation techniques.

The Bayesian MCMC approach to estimate the model parameters and reliability characteristics of the generalized progressive hybrid censored data of ULD is recommended. The authors anticipate that health data analysts and reliability professionals will get benefit from the findings and approaches presented in this study.

The ULD has a broad range of practical utility, making it a problem to estimate the model parameters as well as reliability characteristics and the significance of the GPHCS also encourage the authors to consider the present estimation problem because it has not previously been discussed in the literature.