ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering

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The friction force at joints of engineering structures is usually unknown and not directly identifiable. This contribution explores a procedure for obtaining the governing equation of motion and correctly identifying the unknown Coulomb friction force of a mass-spring-dashpot system. In particular, a single degree-of-freedom system is investigated both numerically and experimentally. The proposed procedure extends the state-of-the-art data-driven sparse identification of nonlinear dynamics (SINDy) algorithm by developing a methodology that explicitly imposes constraints encoding knowledge of the nonsmooth dynamics experienced during stick-slip phenomena. The proposed algorithm consists of three steps: (i) data segregation of mass-motion from mass-sticking during stick-slip response; (ii) application of SINDy on the mass-motion dataset to obtain the functional form of the governing equation; and (iii) applying sticking and slipping conditions to identify the unknown system parameters. It is shown that the proposed approach yields an improved estimate of the uncertain system parameters such as stiffness, viscous damping, and magnitude of friction force (all mass normalized) for various signal-to-noise ratios compared to SINDy. This article is available in the ASME Digital Collection at .

Reusable spacecraft has great potential in reducing space launch cost. Structural reliability evaluation is critical for mission planning of reusable spacecraft. A dynamic reliability prognosis method based on digital twin framework is proposed for mission planning in the paper. In this method, Uncertainties integration and dynamic model updating are implemented through a dynamic Bayesian network. A maintenance point is set when the predicted structural reliability level is lower than a threshold or unexpected conditions such as landing impact occur. Then, inspected data can be assimilated by the framework to dynamically update the structural reliability. Thus, it supports dynamic adjustment of maintenance interval, early warning of structure failure, and mission planning with quantified risk. A numerical example considering single point crack growth under fatigue load and landing impact of a simplified spacecraft structure is used for demonstration. Results show that the crack size predictions can be calibrated by inspected data and its uncertainties can be reduced. The proper selection of landing impact probability in reliability prediction is helpful to control the maintenance interval. The reliability of the spacecraft can be increased through model updating with new inspected data, representing a potential lifetime extension can be realized by the proposed method. This article is available in the ASME Digital Collection at .

Bolted joints have been widely used in engineering structures because of their advantages of simplicity, economy, and assembly. However, material nonlinearities, interface nonlinearities and uncertainties in the assembly process will lead to the dynamic response to become very complex. This work investigated the effect of assembly uncertainties on shock propagation through a bolted lap joint under impact loading. The object of the study was a bolted lap joint subjected to separate Hopkinson pressure bar (SHPB) test. First, a high-fidelity finite element model of the bolted lap joint was developed, and the model was validated by comparing with the experimental results. The error between simulation and experimental results prompted the necessary to consider the uncertainty effect. Then, the effects of multiple uncertainties were considered to identify important input random variables related to the impact response of the joint. The results showed that the slip between the connected parts has the most significant effect on energy dissipation and stress wave propagation. Finally, useful conclusions for the design of bolted joints were obtained from the computational results and discussions. This article is available in the ASME Digital Collection at .

Self-excited vibrations can occur in the spline-shafting system due to internal friction of the tooth surface. However, due to manufacturing errors, design tolerances, and time-varying factors, the parameters that induce self-excited vibrations are always uncertain. This study provides new insights into the uncertainty quantification and sensitivity analysis of a spline-shaft system suffering from self-excited vibrations. The nonintrusive generalized polynomial chaos expansion (gPCE) with unknown deterministic coefficients is used to represent the propagation of uncertainties in the rotor dynamics, which allows rapid estimation of the statistics of the nonlinear responses. Furthermore, the global sensitivity analysis of the stochastic self-excited vibration response of the rotor system with probabilistic uncertain parameters is evaluated by Sobol indices. The relative influence of different random parameters on the vibration behavior and initial displacement conditions for the occurrence of self-excited vibration is investigated. The accuracy of the adopted method based on the gPCE metamodel is validated by conventional Monte Carlo simulation (MCS). Finally, the effects of parameter uncertainties considering random distribution characteristics on the stochastic vibration characteristics of the rotor system are discussed, which demonstrates the need to consider input uncertainties in analysis and design to ensure robust system performance. This article is available in the ASME Digital Collection at .

Taking the key welds of the heavy-duty gondola carbody as the research object, first, the fatigue assessment of the carbody is carried out based on the quasi-static the main S–N curve method, and the quasi-static evaluation method is discussed; second, the typical welds are selected. Based on the full-size bench physical test and virtual test of railway freight carbody, the quasi-static method is discussed; finally, the line test is used to verify the results. The results show that: (1) among all the load conditions in the quasi-static analysis of railway freight cars, the damage of the core plate needs to be considered according to different parts of the carbody, and this condition is effective for the evaluation of the bearing area of the linear load transfer of the carbody for the welds with nonlinear load transfer such as floor, the stress response caused by core plate load has the problem of over-estimation of damage. (2) The lap weld of floor and beam is less damaged under heavy load, but the stress response is larger in empty state, which indicates that the vibration effect should be considered in the design. (3) The virtual test can make up for the problem of traditional quasi-static analysis. The combination of the two can better realize the fatigue reliability evaluation of carbody. This article is available in the ASME Digital Collection at .

Converting mechanical vibrations into electrical power with vibratory energy harvesters can ensure the portability, efficiency, and sustainability of electronic devices and batteries. Vibratory energy harvesters are typically modeled as nonlinear oscillators subject to random excitation, and their design requires a complete characterization of their probabilistic responses. However, simulation techniques such as Monte Carlo are computationally prohibitive when the accurate estimation of the response probability distribution is needed. Alternatively, approximate methods such as stochastic averaging can estimate the probabilistic response of such systems at a reduced computational cost. In this paper, the Hilbert transform based stochastic averaging is used to model the output voltage amplitude as a Markovian stochastic process with dynamics governed by a stochastic differential equation with nonlinear drift and diffusion terms. Moreover, the voltage amplitude dependent damping and stiffness terms are determined via an appropriate equivalent linearization, and the stationary probability distribution of the output voltage amplitude is obtained analytically by solving the corresponding Fokker–Plank equation. Two examples are used to demonstrate the accuracy of the obtained analytical probability distributions via comparisons with Monte Carlo simulation data. This article is available in the ASME Digital Collection at .

The reverse engineering of a valid algebraic inequality often leads to a novel physical reality characterized by a distinct signature: the algebraic inequality itself. This paper uses reverse engineering of valid algebraic inequalities for generating new knowledge and substantially improving the reliability of common series-parallel systems. Our study emphasizes that in the case of series-parallel systems with interchangeable redundant components, the asymmetric arrangement of redundancies always leads to higher system reliability than a symmetric arrangement. This finding remains valid, irrespective of the particular reliabilities characterizing the components. Next, the paper also presents algebraic inequalities whose reverse engineering enabled significant enhancement of the reliability of series-parallel systems with asymmetric arrangements of redundant components, irrespective of the component reliabilities. Lastly, the paper presents a new technique for validating complex algebraic inequalities associated with reliability of series-parallel systems. This technique relies on a permutation of variable values and the method of segmentation. This article is available in the ASME Digital Collection at .