Mechanical Engineering

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https://hdl.handle.net/10323/11894

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Browsing Mechanical Engineering by Author "Drignei, Dorin"

Now showing 1 - 4 of 4
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    A Simulation-Based Fatigue Life Estimation Method for Nonlinear Systems under Non-Gaussian Loads
    (2023-01-01) Mande, Onkar K; Mourelatos, Zissimos P.; Gu, Randy J; Monroe, Ryan; Drignei, Dorin
    In the fields of durability and stochastic structural dynamics, it is customary to focus on linear structures subjected to Gaussian excitations. However, real-world engineering systems often exhibit nonlinear behavior and are exposed to non-Gaussian loads. Calculating fatigue life for such nonlinear systems under non-Gaussian loading presents many challenges such as complex nonlinear dynamics, multifaceted statistical characteristics, and time-dependent effects resulting in a very high computational effort. To overcome these hurdles, this research uses non-Gaussian Karhunen-Loeve expansion (NG-KLE) to not only predict the expected fatigue life but also obtain the Probability Density Function (PDF) of fatigue life. It integrates a sub-domain-based technique to significantly reduce the computational demands while preserving accuracy, by efficiently obtaining long time trajectories of random processes. This development is very useful for excitation signals that far exceed the process correlation length. The NG-KLE method serves as the main tool for characterizing the excitation process by estimating its non-Gaussian marginal distribution and autocorrelation function. A Karhunen-Loeve (KL) expansion is executed only for the first subdomain, and then extended to subsequent subdomains by establishing correlations between the KL expansion coefficients of adjacent subdomains. This innovative approach is adapted to non-Gaussian (NG) excitation, allowing for efficient characterization of both the input and output random processes using NG-KLE, enabling the generation of very long synthetic output random stress process samples. The fatigue life corresponding to each output stress trajectory contributes to the estimation of the PDF of fatigue life. The proposed generalized fatigue life estimation approach accommodates both Gaussian and non-Gaussian processes for both narrow and wide band signals. To demonstrate its effectiveness, we use a duffing oscillator system and a practical example involving a truck assembly modeled by the Finite Element Method (FEM).
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    A Vibro-acoustic CAE Approach for Active Noise Control Prediction
    (2024-01-01) Abbas, Ahmad A; Mourelatos, Zissimos P; Latcha, Michael; Yang, Lianxiang; Drignei, Dorin; Sturla, Francisco
    This research focuses on a comprehensive analysis and prediction of Active Noise Cancellation (ANC) system performance in vehicles, with particular emphasis on the structural and acoustic aspects. While acknowledging the significance of electronic components and control algorithms in ANC systems, this study focuses on predicting the ANC performance using a full vibro-acoustic vehicle model. Additionally, the integration of noise management supplier control systems with CAE ANC models is explored. The development of a predictive CAE methodology is demonstrated using a road noise cancellation example. The process involves several steps including the structural behavior of the Trim Body in White (TBIW) structure, the development of a vehicle cavity model, the derivation of accurate speaker models, the assessment of speaker integration with vehicle doors, and the development of Transfer Paths (TP) from speakers to microphones. A novel methodology is presented to quantify the door stiffness requirements for optimal speaker ANC performance, incorporating substructuring methods and physical testing. The accuracy of the developed CAE models is validated using physical testing of circular and oval-shaped speakers integrated into vehicle doors and the calculation of transfer paths between each door speaker and microphone locations is demonstrated. The significance of microphone and speaker locations relative to driver or passenger ear positions highlights their influence on ANC performance. Finally, a controller is developed to test the CAE model and illustrate its functionality using a supplier’s controller for sound management. Overall, this research establishes a reliable vibro-acoustic CAE ANC model capable of predicting ANC system performance accurately by integrating a full vehicle vibro-acoustic model with an ANC controller. Such a predictive capability enables optimization and enhancement of vehicle performance for noise cancellation, unlocking its full potential in mitigating vehicle noise.
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    Experimental Implementation of a New Durability / Accelerated Life Testing Time Reduction Method
    (2021-11-13) Baseski, Igor; Mourelatos, Zissimos P.; Latcha, Michael; Drignei, Dorin; Wang, Xia
    Fatigue can be defined as a cyclic degradation process resulting in a failure at lower stress levels than the ultimate load. Fatigue reliability is defined as the probability that a structure will perform its intended function throughout its lifetime without any fatigue failure. Durability testing aims to predict fatigue damage in order to estimate the remaining useful life (RUL) based on fatigue. The latter is a useful metric in design for life-cycle cost. The objective of this research is to develop a new durability time reduction method to experimentally estimate the fatigue life of a vehicle component or system with accuracy using a short duration test. We assume that the loading random process (e.g. terrain configuration) is stationary and ergodic so that a single time trajectory can quantify the loading statistics. For the single time trajectory of the load process, we measure the corresponding output stress trajectory at a specified location on the structure. The latter is cycle counted using the 4-point rainflow counting algorithm. The cycle counting identifies all signal (stress) peaks and valleys using a peak picking algorithm and uses them to identify the range of all individual fatigue damage cycles and the time they occur based on a chosen fatigue damage model. Using this information (range of each cycle and the time it occurs), we build a synthetic signal exhibiting the same fatigue damage cycles in the sequence they occur in the actual stress signal. The sequence can be important in order to properly account for the cumulative damage accumulation. Finally, based on the fact that the cycle damage is independent of the time it occurs, we compress the synthetic signal so that its Power Spectral Density (PSD) does not exceed an upper limit dictated by the durability equipment. This proposed durability approach achieves therefore, the same cumulative damage with the original signal in a much shorter testing time. We demonstrate the new durability approach with two examples, and validate it experimentally using a commonly used Belgian block terrain excitation on the suspension coil spring of a military HMMWV (High Mobility Multi-purpose Wheeled Vehicle).
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    Generation of Internal Combustion Engine Maps and Spark Timing Profiles Using Metamodels
    (2022-03-14) Tafreshi, Ali; Mourelatos, Zissimos; Sangeorzan, Brian; Drignei, Dorin; Maisonneuve, Jonathan
    With the growth of computing technologies, many leading automotive companies tend to use simulation tools to reduce the number of actual engine testing for evaluating the performance of Internal Combustion (IC) engines. However, a high-fidelity engine model which is very complex and computationally demanding, is needed. In this dissertation, we present efficient and accurate metamodels to predict an engine fuel map and to also obtain the spark timing profile to generate a specified torque curve. Time-dependent Kriging metamodels using Singular Value Decomposition (SVD) and Nonlinear Autoregressive metamodels with Exogenous inputs (NARX) in conjunction with Neural Networks (NN) are developed and used. A sequential process was first developed to generate steady-state engine fuel maps using Kriging accounting for different engine characteristics at different operating conditions. The generated map predicts engine output parameters such as Brake Mean Effective Pressure (BMEP) and fuel flow rate. The Kriging metamodels are created sequentially to ensure acceptable accuracy with a small number of expensive engine simulations. Two optimization problems are solved for full load and part load conditions, respectively. We demonstrate that the estimated fuel map is of high accuracy compared to the actual map. The internal combustion engine is a source of unwanted vehicle vibration produced by engine mount forces which depend on the engine torque profile during a transient tip-in or tip-out maneuver. A methodology was also developed to obtain the desired engine torque profile to minimize the unwanted vibration by controlling a set of engine calibration parameters. A set of design coefficients defining a spark timing profile and the corresponding engine torque profiles are used to construct time-dependent metamodels using SVD and Kriging. The accuracy of the approach is demonstrated using GT-Power engine simulations. In addition, we developed a time-dependent NARX-NN metamodel to predict engine spark timing and cylinder pressure profiles corresponding to a desired torque profile. The NARX-NN metamodel predicts the spark timing accurately using a very small number of engine simulations.