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Driveline and suspension notched components of off-road ground vehicles often experience multiaxial fatigue failures along notch locations. Large nominal load histories may induce local elasto-plastic stress and strain responses at the critical notch locations. Fatigue life prediction of such notched components requires detailed knowledge of local stresses and strains at notch regions. The notched components that are often subject to multiaxial loadings in services, experience complex stress and strain responses. Fatigue life assessment of the components utilizing non-linear Finite Element Analysis (FEA) require unfeasibly inefficient computation times and large data. The lack of more efficient and effective methods of elasto-plastic stress-strain calculation may lead to the overdesign or earlier failures of the components or costly experiments and inefficient non-linear FEA.

High surface area particles have drawn attention in the context of noise control due to their good sound absorption performance at low frequencies, which is an advantage compared with more traditional materials. That observation suggests that there is a good potential to use these particles in various scenarios, especially where low frequency noise is the main concern. To facilitate their application, composite materials are formed by dispersing particles within a fiber matrix, thus giving more flexibility in positioning those particles. In this work, a hybrid model that combines a model for limp porous materials and a model of high surface area particles is proposed to describe the acoustic performance of such composites. Two-microphone standing wave tube test results for several types of composites with different thickness, basis weight, and particle concentration are provided.

In this paper, a wall-modified interactive flamelet model is developed for improving the modeling of Diesel combustion. The objective is to include the effects of wall heat loss on the transient flame structure. The essential idea is to compute several flamelets with several representative enthalpy defects which account for wall heat loss. Then, the averaged flamelet profile can be obtained through a linear fit between the flamelets according to the enthalpy defect of the local gas which results from the wall heat loss. The enthalpy defect is estimated as the difference between the enthalpy in a flamelet without wall heat loss, which would correspond to the enthalpy in the gas without wall heat loss, and the gas with wall heat loss. The improved model is applied to model combustion in a Diesel engine. In the application, two flamelets, one without wall heat loss and one with wall heat loss, are considered.

The four-microphone standing wave tube system has proven useful for measuring the absorption and transmission loss of various fibrous and non-fibrous absorbers. The system is fast, repeatable, accurate and compact. This paper discusses the advantages of the four-microphone system for measuring the transmission loss in lateral-flow absorber systems. The original four-microphone round impedance tube system and the migration to a four-microphone square tube system are discussed. The four-microphone square tube system allows effective study of filled and partially filled cavities.

The most common and lethal weapons against military vehicles are the improvised explosive devices (IEDs). In an explosion, critical cabin’s penetrations and high accelerations can cause serious injuries and death of military personnel. This investigation uses single and multi-fidelity Bayesian optimization (BO) to design sandwich composite armors for blast mitigation. BO is an efficient methodology to solve optimization problems that involve black-box functions. The black-box function of this work is the finite element (FE) simulation of the armor subjected to blast. The main two components of BO are the surrogate model of the black-box function and the acquisition function that guides the optimization. In this investigation, the surrogate models are Gaussian Process (GP) regression models and the acquisition function is the multi-objective expected improvement (MEI) function. Information from low and high fidelity FE models is used to train the GP surrogates.

Sound transmission through door and window sealing systems is one important contributor to vehicle interior noise. The noise generation mechanism involves the vibration of the seal due to the unsteady wall pressures associated with the turbulent flow over the vehicle. For bulb seals, sound transmission through the seal is governed by the resonance of the seal membranes and the air cavity within the bulb (the so-called mass-air-mass resonance). The objective of this study was to develop a finite element (FE) model to predict the sound transmission loss of elastomeric bulb seals. The model was then exercized to perform a parametric study of the influence of seveal seal design parameters. The results suggest that the sound transmission loss increases as the membrane thicknesses and/or the separation distance between the two seal walls are increased. The addition of additional internal “webs” was found to have adverse effects on the sound barrier performance.

One dominant “wind noise” generating mechanism in road vehicles is the interaction between turbulent flows and flexible structures which include side glass windows. In this study, the effects of seal mechanical properties on the sound generated from flow-induced vibration of side glass windows were investigated. The primary goal was to assess the influence of seal support properties on the noise generated from a plate. Two different models to calculate the optimal support stiffness of the seal that minimizes the velocity response are presented. The results show that both the velocity response and the sound radiation are strongly influenced by dissipation of vibration energy at the edges. It is demonstrate that support tuning can yield significant noise and vibration reduction.

In the past decades, automotive structure design has sought to minimize its mass while maintaining or improving structural performance. As such, topology optimization (TO) has become an increasingly popular tool during the conceptual design stage. While the designs produced by TO methods provide significant performance-to-mass ratio improvements, they require considerable computational resources when solving large-scale problems. An alternative for large-scale problems is to decompose the design domain into multiple scales that are coupled with homogenization. The problem can then be solved with hierarchical multiscale topology optimization (MSTO). The resulting optimal, homogenized macroscales are de-homogenized to obtain a high-fidelity, physically-realizable design. Even so MSTO methods are still computationally expensive due to the combined costs of solving nested optimization problems and performing de-homogenization.

Experimental modal analysis (EMA) provides many parameters that are required in numerical modeling of dynamic and vibratory behavior of structures. This paper discusses EMA on an exhaust system of an off-road car. The exhaust structure is tested under three boundary conditions: free-free, supported with two elastomeric mounts, and mounted to the car. The free-free modal parameters are compared to finite element results. The two-mount tests are done with the mounts fixed to a rigid and heavy frame. The rigidity of the frame is verified experimentally. The on-car test is done with realistic boundary conditions, where the exhaust structure is fixed to the engine manifold as well as the two elastomeric mounts. The two-mount and the on-car tests result in highly complex mode shapes.

Fatigue damage prediction approaches in both time and frequency domains have been developed to simulate the operational life of mechanical structures under random loads. Fatigue assessment of mechanical structures and components subjected to those random loads is increasingly being addressed by frequency domain approaches because of time and cost savings. Current frequency-based fatigue prediction methods focus on stationary random loadings (stationary Power Spectral Density), but many machine components, such as jet engines, rotating machines, and tracked vehicles are subjected to non-stationary PSD conditions under real service loadings. This paper describes a new fatigue damage modeling approach capable of predicting fatigue damage for structures exposed to non-stationary (evolutionary) PSD loading conditions where the PSD frequency content is time-varying.

Electrical connectors and terminals are widely used in the automotive industry. It is desirable to mate the electrical connections using materials or coatings with low friction force to improve the ergonomics of the assembly process while maintaining good electrical conduction over the lifetime of the vehicle. We have previously shown that plasma-enhanced chemical vapor deposition (PECVD) of graphene on gold (Au) and silver (Ag) terminals can significantly reduce the insertion force (friction force during the terminal insertion process). However, the cost of this deposition method is rather high, and its high temperature process (> 400 oC) makes it impractical for materials with low melting temperatures. For example, tin (Sn) coating with a melting temperature of 232 oC is commonly used in electrical connectors, which cannot sustain the high temperature process. In this study, reduced graphene oxide was prepared using a low-cost solution process and applied onto metallic terminals.

Inside an automobile, hundreds of connectors and electrical terminals in various locations experience different corrosive environments. These connectors and electrical terminals need to be corrosion-proof and provide a good electrical contact for a vehicle’s lifetime. Saltwater and sulfuric acid are some of the main corrosion concerns for these electrical terminals. Currently, various thin metallic layers such as gold (Au), silver (Ag), or tin (Sn) are plated with a nickel (Ni) layer on copper alloy (Cu) terminals to ensure reliable electrical conduction during service. Graphene due to its excellent chemical stability can serve as a corrosion protective layer and prevent electrochemical oxidation of metallic terminals. In this work, effects of thin graphene layers grown by plasma-enhanced chemical vapor deposition (PECVD) on Au and Ag terminals and thin-film devices were investigated. Various mechanical, thermal/humidity, and electrical tests were performed.

In Diesel engines, the vapor phase of the fuel jet is known to impinge on the walls. This impingement is likely to have an effect on mixing characteristics, the structure of the diffusion flame and on pollutant formation and oxidation. These effects have not been studied in detail in the literature. In this work, the structure of a laminar wall jet that is generated from the impingement of a free laminar jet on a wall is discussed. We study the laminar jet with the belief that the local structure of the reaction zone in the turbulent reacting jet is that of a laminar flame. Results from non-reacting and reacting jets will be presented. In the case of the non-reacting jets, the focus of the inquiry is on assessing the accuracy of the computed results by comparing them with analytical results. Velocity profiles in the wall jet, growth rates of the half-width of the jet and penetration rates are presented.

In this paper, computations of pulsating flows in a duct with multiple inlets using the lattice Boltzmann method (LBM) are reported. As future emissions standards present a significant challenge for Diesel engine manufacturers, several options are being investigated to identify strategies to meet such regulations. Exhaust gas aftertreatment is one of the most important among them. As the performance of the various aftertreatment devices is sensitive to the flow conditions in the exhaust, a greater understanding of the flows under pulsating conditions in the presence of multiple cylinders is needed. The Lattice Boltzmann Method (LBM) is a relatively new and promising computational approach for applications to fluid dynamics problems. Two advantages of the method relative to traditional methods are ease of implementation and ease of parallelization and performance on parallel computers.

A methodology for modeling elastomeric mounts as nonlinear lumped parameter models is discussed. A key feature of this methodology is that it integrates dynamic test results under different conditions into the model. The first step is to model the mount as a linear model that is simple but reproduces accurately results from dynamic tests under small excitations. Frequency Response Functions (FRF) enables systematic calculation of the parameters for the model. Under more realistic excitation, the mount exhibits non-linearity, which is investigated in the next step. For nonlinear structures, a simple and intuitive method is to use time-domain force-displacement (F-x) curves. Experiments to obtain the F-x curves involve controlling the displacement excitation and measuring the induced forces. From the F-x curves, stiffness and damping parameters are obtained with an optimization technique.

This paper presents the continuation of the modeling work described in a companion paper “Modeling of Nonlinear Elastomeric Mounts. Part 1: Dynamic Testing and Parameter Identification” by the same authors. That paper discussed a dynamic test procedure and an optimization methodology to identify and model an elastomeric mount as a non-linear lumped parameter structure. This paper discusses a numerical modeling methodology to confirm or improve the agreement between the dynamic test results and the input-output relationship of the analytical model generated in the companion paper. In this paper, the model developed in the companion paper and the model parameters are input into a dynamic simulation model using a commercial simulation package. The model is then run to produce the numerical force-versus-displacement (F-x) curves of the mount. The numerical F-x curves are compared with the F-x curves obtained from the experiments.

In regions at war, the increasing use of improvised explosive devices (IEDs) is the main threat against military vehicles. Large cabin”s penetrations and high gross accelerations are primary threats against the occupants” survivability. The occupants” survivability under an IED event largely depends on the design of the vehicle armor. Under a blast load, a vehicle armor should maintain its structural integrity while providing low cabin penetrations and low gross accelerations. This investigation employs Bayesian global optimization (BGO) and non-uniform rational B-splines (NURBS) to design sandwich composite armors that simultaneously mitigate the cabin”s penetrations and the reaction force at the armor”s supports. The armors are made of four layers: steel, carbon fiber reinforced polymer (CFRP), aluminum honeycomb, and CFRP.

A common scenario in engineering design is the availability of several black-box functions that describe an event with different levels of accuracy and evaluation cost. Solely employing the highest fidelity, often the most expensive, black-box function leads to lengthy and costly design cycles. Multi-fidelity modeling improves the efficiency of the design cycle by combining information from a small set of observations of the high-fidelity function and large sets of observations of the low-fidelity, fast-to-evaluate functions. In the context of Bayesian optimization, the most popular multi-fidelity model is the auto-regressive (AR) model, also known as the co-kriging surrogate. The main building block of the AR model is a weighted sum of two Gaussian processes (GPs). Therefore, the AR model is well suited to exploit information generated by sources that present strong linear correlations.

The damping effect that is observed when a fibrous acoustical treatment is applied to a thin metal panel typical of automotive structures has been modeled by using three independent techniques. In the first two methods the fibrous treatment was modeled by using the limp frame formulation proposed by Bolton et al., while the third method makes use of a general poro-elastic model based on the Biot theory. All three methods have been found to provide consistent predictions that are in excellent agreement with one another. An examination of the numerical results shows that the structural damping effect results primarily from the suppression of the nearfield acoustical motion within the fibrous treatment, that motion being closely coupled with the vibration of the base panel. The observed damping effect is similar in magnitude to that provided by constrained layer dampers having the same mass per unit area as the fibrous layer.

Modern pulse-turbocharged systems produce a turbine operating environment that is dominated by unsteady flow. Effective utilization of the unsteady exhaust gas energy content at the turbine inlet is critical to achieving optimum system efficiency. This work presents predictions for turbocharger unsteady performance from a model based on the Euler equations with source terms (EEST). This approach allows the time-accurate performance of the turbine to be determined, allowing comparisons of actual energy utilization and that estimated from steady flow performance maps.