Search Results

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.

Once the design of a door sheetmetal and accessories is confirmed, the acoustics of the door system depends on the sound package assembly. This essentially consists of a watershield which acts as a barrier and a porous material which acts as an absorber. The acoustical performance of the watershield and the reverberant sound build-up in the door cavity control the performance. This paper discusses the findings of a design study that was developed based on design of experiments (DOE) concepts to determine which parameters of the door sound package assembly are important to the door acoustics. The study was based on conducting a minimum number of tests on a five factor - two level design that covered over 16 different design configurations. In addition, other measurements were made that aided in developing a SEA model which is also compared with the findings of the results of the design study.

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.

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.

Laser lap welding quality is a non-linear response based on a host of categorical and numeric material and process variables. This paper describes a Grammatical Evolution approach to the structure identification of the laser lap welding process and compares its performance with linear regression and a neuro-fuzzy inference system.

The components in a hybrid electric vehicle (HEV) powertrain include the battery pack, an internal combustion engine, and the electric machines such as motors and possibly a generator. These components generate a considerable amount of heat during driving cycles. A robust thermal management system with advanced controller, designed for temperature tracking, is required for vehicle safety and energy efficiency. In this study, a hybridized mid-size truck for military application is investigated. The paper examines the integration of advanced control algorithms to the cooling system featuring an electric-mechanical compressor, coolant pump and radiator fans. Mathematical models are developed to numerically describe the thermal behavior of these powertrain elements. A series of controllers are designed to effectively manage the battery pack, electric motors, and the internal combustion engine temperatures.

In a gasoline engine, the unswept in-cylinder residual gas and introduction of external EGR is one of the important means of controlling engine raw NOx emissions and improving part load fuel economy via reduction of pumping losses. Since the trapped in-cylinder Residual Gas Fraction (RGF, comprised of both internal, and external) significantly affects the combustion process, on-line diagnosis and monitoring of in-cylinder RGF is very important to the understanding of the in-cylinder dilution condition. This is critical during the combustion system development testing and calibration processes. However, on-line measurement of in-cylinder RGF is difficult and requires an expensive exhaust gas analyzer, making it impractical for every application. Other existing methods, based on measured intake and exhaust pressures (steady state or dynamic traces) to calculate gas mass flowrate across the cylinder ports, provide a fast and economical solution to this problem.

The pulleys employed in automotive accessory drive systems very often consist of a two piece assembly; a multitude of fastening techniques are used in completing the assembly. There are numerous assembly methods and a variety of distinct pulley configurations dictated by the various automobile manufacturers in accordance with individual accessory drive needs. An expert system is being developed to evaluate the merit of multiple assembly alternatives for a specific pulley application. The expert system provides a consistent evaluation tool for assembly alternatives, balancing the influence of product cost, strength and quality considerations. The knowledge-based system is implemented in an expert system shell called AGNESS (A Generalized Network-based Expert System Shell). The expert system judges the acceptability of various pulley assembly techniques, assigning a high “merit value” to the better designs and proportionately lower values to less desirable designs.

With the increasing emphasis on Systems Engineering, there is a need to ensure that Electrical/Electronic (E/E) Systems Endurance Testing of vehicles, in a real world environment, prior to Production Launch, is performed in a manner and at a technological level that is commensurate with the high level of electronics and computers in contemporary vehicles. Additionally, validating the design and performance of individual standalone electronic systems and modules “on the bench” does not guarantee that all the permutations and combinations of real-world hardware, software, and driving conditions are taken into account. Traditional Proving Ground (PG) vehicle testing focuses mainly on powertrain durability testing, with only a simple checklist being used by the PG drivers as a reminder to cycle some of the electrical components such as the power window switches, turn signals, etc.

Accurate accounting for fresh charge (fuel and air) along with trapped RGF is essential for the subsequent thermodynamic analysis of combustion in gasoline engines as well as for on-line and real-time quantification as relevant to engine calibration and control. Cost and complexity of such techniques renders direct measurement of RGF impractical for running engines. In this paper, an empirically-based approach is proposed for on-line RGF, based on an existing semi-empirical model [1]. The model developed expands the range over which the semi-empirical model is valid and further improves its accuracy. The model was rigorously validated against a well correlated GT-POWER model as well as results from 1D gas exchange model [2]. Overall, using this model, RGF estimation error was within ∼1.5% for a wide range of engine operating conditions. The model will be implemented in Dyno development and calibration at Chrysler Group.

A special spot weld element (SWE) is presented for simplified representation of spot joints in complex structures for structural durability evaluation using the mesh-insensitive structural stress method. The SWE is formulated using rigorous linear four-node Mindlin shell elements with consideration of weld region kinematic constraints and force/moments equilibrium conditions. The SWEs are capable of capturing all major deformation modes around weld region such that rather coarse finite element mesh can be used in durability modeling of complex vehicle structures without losing any accuracy. With the SWEs, all relevant traction structural stress components around a spot weld nugget can be fully captured in a mesh-insensitive manner for evaluation of multiaxial fatigue failure.

Making manned and remotely-controlled wheeled and tracked vehicles easier to drive, especially off-road, is of great interest to the U.S. Army. If vehicles are easier to drive (especially closed hatch) or if they are driven autonomously, then drivers could perform additional tasks (e.g., operating weapons or communication systems), leading to reduced crew sizes. Further, poorly driven vehicles are more likely to get stuck, roll over, or encounter mines or improvised explosive devices, whereby the vehicle can no longer perform its mission and crew member safety is jeopardized. HMI technology and systems to support human drivers (e.g., autonomous driving systems, in-vehicle monitors or head-mounted displays, various control devices (including game controllers), navigation and route-planning systems) need to be evaluated, which traditionally occurs in mission-specific (and incomparable) evaluations.

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.

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.

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.

An experimental investigation of non-intrusive combustion sensing was performed using a tri-axial accelerometer mounted to the engine block of a small-bore high-speed 4-cylinder compression-ignition direct-injection (CIDI) engine. This study investigates potential techniques to extract combustion features from accelerometer signals to be used for cycle-to-cycle engine control. Selection of accelerometer location and vibration axis were performed by analyzing vibration signals for three different locations along the block for all three of the accelerometer axes. A magnitude squared coherence (MSC) statistical analysis was used to select the best location and axis. Based on previous work from the literature, the vibration signal filtering was optimized, and the filtered vibration signals were analyzed. It was found that the vibration signals correlate well with the second derivative of pressure during the initial stages of combustion.

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.

The present study introduces a modeling approach for investigating the effects of valve events and gas exchange processes in the framework of a full-cycle HCCI engine simulation. A multi-dimensional fluid mechanics code, KIVA-3V, is used to simulate exhaust, intake and compression up to a transition point, before which chemical reactions become important. The results are then used to initialize the zones of a multi-zone, thermo-kinetic code, which computes the combustion event and part of the expansion. After the description and the validation of the model against experimental data, the application of the method is illustrated in the context of variable valve actuation. It has been shown that early exhaust valve closing, accompanied by late intake valve opening, has the potential to provide effective control of HCCI combustion.

Simultaneous measurements of the radial and the tangential components of velocity are obtained in a high-speed, direct-injection diesel engine typical of automotive applications. Results are presented for engine operation with fuel injection, but without combustion, for three different swirl ratios and four injection pressures. With the mean and fluctuating velocities, the r-θ plane shear stress and the mean flow gradients are obtained. Longitudinal and transverse length scales are also estimated via Taylor's hypothesis. The flow is shown to be sufficiently homogeneous and stationary to obtain meaningful length scale estimates. Concurrently, the flow and injection processes are simulated with KIVA-3V employing a RNG k-ε turbulence model. The measured turbulent kinetic energy k, r-θ plane mean strain rates ( 〈Srθ〉, 〈Srr〉, and 〈Sθθ〉 ), deviatoric turbulent stresses , and the r-θ plane turbulence production terms are compared directly to the simulated results.

Charge motion is known to accelerate and stabilize combustion through its influence on turbulence intensity and flame propagation. The present work investigates the effect of charge motion generated by intake runner blockages on combustion characteristics and emissions under part-load conditions in SI engines. Firing experiments have been conducted on a DaimlerChrysler (DC) 2.4L 4-valve I4 engine, with spark range extending around the Maximum Brake Torque (MBT) timing. Three blockages with 20% open area are compared to the fully open baseline case under two operating conditions: 2.41 bar brake mean effective pressure (bmep) at 1600 rpm, and 0.78 bar bmep at 1200 rpm. The blocked areas are shaped to create different levels of swirl, tumble, and cross-tumble. Crank-angle resolved pressures have been acquired, including cylinders 1 and 4, intake runners 1 and 4 upstream and downstream of the blockage, and exhaust runners 1 and 4.