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The effect of temperature and preload on the bolt load retention (BLR) behavior of AZ91D and AE42 magnesium die castings was investigated. The results were compared to those of 380 aluminum die castings. Test temperatures from 125 to 175°C and preloads from 7 to 28 kN were investigated. The loss of preload for AZ91D was more sensitive to temperature than that observed for AE42, especially at low preloads. In general, retained bolt-load was lowest in AZ91D. All test assemblies were preloaded at room temperature and load levels increased when the assemblies reached test temperature. The load-increase was dependent on the preload level, test temperature, alloy, and results from thermal expansion mismatch between the steel bolt and the magnesium alloy components, mitigated by the onset of primary creep. Thermal exposure (aging) of AZ91D at 150°C improved BLR behavior.

This paper presents a method of balancing the cylinder to cylinder torque fluctuation of an idling engine by controlling the individual spark timing. This method has the capability to compensate for individual fuel/air imbalance that might occur for example due to miscalibration of a fuel injector. The method is based upon noncontacting crankshaft angular speed flucuations and upon a control system that regulates individual spark timing in response to imbalance in that speed variation. The theory of the method is explained and experimental verification of the method is presented for a 4 cylinder engine.

Thermal distortions of friction disks caused by frictional heating modify pressure distribution on friction surfaces. Pressure distribution, in turn, determines distribution of generated frictional heat. These interdependencies create a complex thermoelastic system that, under some conditions, may become unstable and may lead to severe pressure concentrations with very high local temperature and stress. The phenomenon is responsible for many common thermal failure modes of friction elements and is known as frictionally excited thermoelastic instability (TEI). In the paper, one of the cases of TEI is investigated theoretically and experimentally. The study involves a two-disk structure with one fiction disk and one matching steel disk that have one friction interface. An unsteady heat conduction problem and an elastic contact problem are modeled as axisymmetric ones and are solved using the finite element method.

A copula-based approach for model bias characterization was previously proposed [18] aiming at improving prediction accuracy compared to other model characterization approaches such as regression and Gaussian Process. This paper proposes an adaptive copula-based approach for model bias identification to enhance the available methodology. The main idea is to use cluster analysis to preprocess data, then apply the copula-based approach using information from each cluster. The final prediction accumulates predictions obtained from each cluster. Two case studies will be used to demonstrate the superiority of the adaptive copula-based approach over its predecessor.

Quantification of residual stresses is an important engineering problem impacting manufacturabilty and durability of metallic components. An area of particular concern is residual stresses that can develop during heat treatment of metallic components. Many heat treatments, especially in heat treatable cast aluminum alloys, involve a water-quenching step immediately after a solution-treatment cycle. This rapid water quench has the potential to induce high residual stresses in regions of the castings that experience large thermal gradients. These stresses may be partially relaxed during the aging portion of the heat treatment. The goal of this research was to develop a test sample and quench technique to quantify the stresses created by steep thermal gradients during rapid quenching of cast aluminum. The development and relaxation of residual stresses during the aging cycle was studied experimentally with the use of strain gauges.

In applications of the Energy Finite Element Analysis (EFEA) there is an increasing need for developing comprehensive models with a large number of elements which include both structural and interior fluid elements, while certain parts of the structure are considered to be exposed to an external fluid loading. In order to accommodate efficient computations when using simulation models with a large number of elements, joints, and domains, a substructuring computational capability has been developed. The new algorithm is based on dividing the EFEA model into substructures with internal and interface degrees of freedom. The system of equations for each substructure is assembled and solved separately and the information is condensed to the interface degrees of freedom. The condensed systems of equations from each substructure are assembled in a reduced global system of equations. Once the global system of equations has been solved the solution for each substructure is pursued.

Over the decades, several attempts have been made to develop new fatigue analysis methods for welded joints since most of the incidents in automotive structures are joints related. Therefore, a reliable and effective fatigue damage parameter is needed to properly predict the failure location and fatigue life of these welded structures to reduce the hardware testing, time, and the associated cost. The nodal force-based structural stress approach is becoming widely used in fatigue life assessment of welded structures. In this paper, a new nodal force-based structural stress recovery procedure is proposed that uses the least squares method to linearly smooth the stresses in elements along the weld line. Weight function is introduced to give flexibility in choosing different weighting schemes between elements. Two typical weighting schemes are discussed and compared.

A global, systems-level model which characterizes the thermal behavior of internal combustion engines is described in this paper. Based on resistor-capacitor thermal networks, either steady-state or transient thermal simulations can be performed. A two-zone, quasi-dimensional spark-ignition engine simulation is used to determine in-cylinder gas temperature and convection coefficients. Engine heat fluxes and component temperatures can subsequently be predicted from specification of general engine dimensions, materials, and operating conditions. Emphasis has been placed on minimizing the number of model inputs and keeping them as simple as possible to make the model practical and useful as an early design tool. The success of the global model depends on properly scaling the general engine inputs to accurately model engine heat flow paths across families of engine designs. The development and validation of suitable, scalable submodels is described in detail in this paper.

Due to magnesium alloy's poor weldability, other joining techniques such as laser assisted self-piercing rivet (LSPR) are used for joining magnesium alloys. This research investigates the fatigue performance of LSPR for magnesium alloys including AZ31 and AM60. Tensile-shear and coach peel specimens for AZ31 and AM60 were fabricated and tested for understanding joint fatigue performance. A structural stress - life (S-N) method was used to develop the fatigue parameters from load-life test results. In order to validate this approach, test results from multijoint specimens were compared with the predicted fatigue results of these specimens using the structural stress method. The fatigue results predicted using the structural stress method correlate well with the test results.

This paper presents a distributed control system framework for next-generation automotive control systems, in which various control units are connected with CAN bus. The framework is a software platform that performs communication between control units and invocation of application programs. The framework includes necessary functions for data transmission to meet end-to-end timing constraints in distributed control systems. Application programmers don't have to write any communication procedure but focus on developing application programs with appropriate API (Application Program Interface). The framework is based on driving force management and also OSEK, which is a standard real-time operating system (OSEK-OS) and a communication protocol (CAN) for automotive control. We are now applying our prototype framework to an adaptive cruise control system in our experimental vehicle.

Available methodologies for model bias identification are mainly regression-based approaches, such as Gaussian process, Bayesian inference-based models and so on. Accuracy and efficiency of these methodologies may degrade for characterizing the model bias when more system inputs are considered in the prediction model due to the curse of dimensionality for regression-based approaches. This paper proposes a copula-based approach for model bias identification without suffering the curse of dimensionality. The main idea is to build general statistical relationships between the model bias and the model prediction including all system inputs using copulas so that possible model bias distributions can be effectively identified at any new design configurations of the system. Two engineering case studies whose dimensionalities range from medium to high will be employed to demonstrate the effectiveness of the copula-based approach.

To advance vehicle lightweighting, chopped carbon fiber sheet molding compound (SMC) is identified as a promising material to replace metals. However, there are no effective tools and methods to predict the mechanical property of the chopped carbon fiber SMC due to the high complexity in microstructure features and the anisotropic properties. In this paper, a Representative Volume Element (RVE) approach is used to model the SMC microstructure. Two modeling methods, the Voronoi diagram-based method and the chip packing method, are developed to populate the RVE. The elastic moduli of the RVE are calculated and the two methods are compared with experimental tensile test conduct using Digital Image Correlation (DIC). Furthermore, the advantages and shortcomings of these two methods are discussed in terms of the required input information and the convenience of use in the integrated processing-microstructure-property analysis.