Search Results

Vehicle restraint system design is a difficult optimization problem to solve because (1) the nature of the problem is highly nonlinear, non-convex, noisy, and discontinuous; (2) there are large numbers of discrete and continuous design variables; (3) a design has to meet safety performance requirements for multiple crash modes simultaneously, hence there are a large number of design constraints. Based on the above knowledge of the problem, it is understandable why design of experiment (DOE) does not produce a high-percentage of feasible solutions, and it is difficult for response surface methods (RSM) to capture the true landscape of the problem. Furthermore, in order to keep the restraint system more robust, the complexity of restraint system content needs to be minimized in addition to minimizing the relative risk score to achieve New Car Assessment Program (NCAP) 5-star rating.

Variant modeling techniques have been developed to allow systems engineers to model multiple similar variants in a product line as a single variant model. In this paper, we expand on this past work to explore the extent to which variant modeling in SysML can be applied to a broad range of dissimilar systems, covering the entire domain of ground vehicles, in single reference architecture model. Traditionally, a system’s structure is decomposed into subsystems and components. However, this method is found to be ineffective when modeling variants that are functionally similar but structurally different. We propose to address this challenge by first decomposing the system not only by subsystem but also by high-level function. This pattern is particularly useful for situations where two variants perform the same function, but one variant performs the function using one subsystem, whereas the other variant performs the same function using one or more different subsystems.

We propose a new metamodeling method to characterize the output (response) random process of a dynamic system with random parameters, excited by input random processes. The metamodel can be then used to efficiently estimate the time-dependent reliability of a dynamic system using analytical or simulation-based methods. The metamodel is constructed by decomposing the input random processes using principal components or wavelets and then using a few simulations to estimate the distributions of the decomposition coefficients. A similar decomposition is also performed on the output random process. A kriging model is then established between the input and output decomposition coefficients and subsequently used to quantify the output random process corresponding to a realization of the input random parameters and random processes. What distinguishes our approach from others in metamodeling is that the system input is not deterministic but random.

Design optimization often relies on computational models, which are subjected to a validation process to ensure their accuracy. Because validation of computer models in the entire design space can be costly, a recent approach was proposed where design optimization and model validation were concurrently performed using a sequential approach with both fixed and variable-size local domains. The variable-size approach used parametric distributions such as Gaussian to quantify the variability in test data and model predictions, and a maximum likelihood estimation to calibrate the prediction model. Also, a parametric bootstrap method was used to size each local domain. In this article, we generalize the variable-size approach, by not assuming any distribution such as Gaussian. A nonparametric bootstrap methodology is instead used to size the local domains. We expect its generality to be useful in applications where distributional assumptions are difficult to verify, or not met at all.

A simulation-based, system reliability-based design optimization (RBDO) method is presented that can handle problems with multiple failure regions and correlated random variables. Copulas are used to represent the correlation. The method uses a Probabilistic Re-Analysis (PRRA) approach in conjunction with a trust-region optimization approach and local metamodels covering each trust region. PRRA calculates very efficiently the system reliability of a design by performing a single Monte Carlo (MC) simulation per trust region. Although PRRA is based on MC simulation, it calculates “smooth” sensitivity derivatives, allowing therefore, the use of a gradient-based optimizer. The PRRA method is based on importance sampling. It provides accurate results, if the support of the sampling PDF contains the support of the joint PDF of the input random variables. The sequential, trust-region optimization approach satisfies this requirement.

Understanding reliability is critical in design, maintenance and durability analysis of engineering systems. A reliability simulation methodology is presented in this paper for vehicle fleets using limited data. The method can be used to estimate the reliability of non-repairable as well as repairable systems. It can optimally allocate, based on a target system reliability, individual component reliabilities using a multi-objective optimization algorithm. The algorithm establishes a Pareto front that can be used for optimal tradeoff between reliability and the associated cost. The method uses Monte Carlo simulation to estimate the system failure rate and reliability as a function of time. The probability density functions (PDF) of the time between failures for all components of the system are estimated using either limited data or a user-supplied MTBF (mean time between failures) and its coefficient of variation.

The automotive industry has a strong need for lightweight materials capable of withstanding large mechanical loads. Advanced high-strength steels (AHSS), which have high tensile strength and formability, show great promise for automotive applications, yet if they are to be more widely used, it's important to understand their deformation behavior; this is particularly important for the development of forming limit diagrams (FLD) used in stamping processes. The goal of the present study was to determine the extent to which anisotropy introduced by the rolling direction affects the local fracture strain. Three grades of dual-phase AHSS and one high-strength low-alloy (HSL A) 50ksi grade steel were tested under plane strain conditions. Half of the samples were loaded along their rolling direction and the other half transverse to it. In order to achieve plane strain conditions, non-standard dogbone samples were loaded on a wide-grip MTS tensile test machine.

A common approach to the validation of simulation models focuses on validation throughout the entire design space. A more recent methodology validates designs as they are generated during a simulation-based optimization process. The latter method relies on validating the simulation model in a sequence of local domains. To improve its computational efficiency, this paper proposes an iterative process, where the size and shape of local domains at the current step are determined from a parametric bootstrap methodology involving maximum likelihood estimators of unknown model parameters from the previous step. Validation is carried out in the local domain at each step. The iterative process continues until the local domain does not change from iteration to iteration during the optimization process ensuring that a converged design optimum has been obtained.

A significant challenge for wheel- and propeller-driven amphibious vehicles during swimming operations involves the egress from bodies of water. The vehicle needs to be able to swim to the bank, and then propel itself up the bank using water propellers and wheels simultaneously. To accurately predict the ability of the vehicle to climb the bank, it is important to accurately model: (1) the interaction of the flow through the propellers, around the vehicle hull, and over the bank; (2) the wheel / bank interaction; (3) the suspension system spring, damping, and motion-limiting forces, tire deformation and loading characteristics, and wheel and hull motions (both translation and rotation); and (4) the drivetrain power distribution to the wheels. Detailed modeling and simulation of these physics and processes - such as the wheel, hull, and suspension system motions and force interactions, propeller rotation and resulting flow, etc. - would be highly computationally expensive.

A Computational Fluid Dynamics (CFD) study was conducted on four-vehicle platoons, and the aerodynamic data is then coupled with a high-fidelity truck simulation software (TruckSim) to determine fuel efficiency. Previous studies typically have focused on identical two vehicle platoons, whereas this study accounted for more complex platoon configurations. Heavy duty vehicles (HDVs), both military and commercial, make up a significant percentage of fuel consumption. This study aimed to quantify fuel savings of a platoon consisting of dissimilar trucks and trailers, thus reducing vehicle operational cost. The vehicle platoon featured two M915 trucks and two Peterbilt 579 trucks with dissimilar trailer configurations. An unloaded flatbed trailer, a centered 20 ft shipping container, two 20 ft shipping containers, and a 53 ft box trailer configurations were utilized.

Imposing tensile stress on an edge of a sheet metal blank is a common condition in many sheet metal forming operations, making edge formability a very important factor to consider. Because edge formability varies greatly among different materials, cutting methods (and their control parameters), it is very important to have access to an experimental technique that would allow for quick and reliable evaluation of edge formability for a given case. In this paper, two existing techniques are compared: the hole expansion test and the tensile test. It is shown that the hole expansion test might not be adequate for many cases, and is prone to overestimating the limiting strain, because the burr on the sheared edge is typically smaller than what is observed in production. The tensile test represents an effective alternative to the hole expansion test. Advantages and disadvantages of each case are discussed.

In this paper, experimental study and FEA simulation are performed to investigate the effect of three different methods for joining dissimilar metal coupons in terms of their strength and load transferring capacity. The joining techniques considered include adhesive bonding, bolting and hybrid bolting-and-bonding. Elastic-plastic material model with damage consideration is used for each of the joint components. Traction-separation rule and failure criterion is defined for adhesive. Load transfer capacity and the failure mode are assessed for each type of joining. Joint strength is examined in terms of the effects of adhesive property, bolt preload level, and friction coefficient. Results show that load transferred and failure mechanism vary significantly between samples with different joint methods; preload evolution in bolt changes with friction coefficient; hybrid joint generally has advantage over the other two methods, namely, bolting-only and bonding-only.

Vehicular control systems are characterized with numerous complex interactions with a steady rise of autonomous functions, which makes it more challenging for designers and safety engineers to identify unexpected failures. These systems tend to be highly integrated and exhibit features like concurrency for which traditional verification and validation techniques (i.e. testing and simulation) are insufficient to provide rigorous and complete assessment. Model Checking, a well-known formal verification technique, can be used to rigorously prove the correctness of such systems according to design Requirements. In particular, Model Checking is a method for formally verifying finite-state concurrent systems. Specifications about the system are expressed as temporal logic formulas, and efficient symbolic algorithms are used to traverse the model defined by the system and check if the specification holds or not.

Automotive systems engineering addresses the system throughout its life cycle, including requirement, specification, design, implementation, verification and validation of systems, modeling, simulation, testing, manufacturing, operation and maintenance. This four-volume set features 49 papers, originally published from 1999 through 2010, that cover the latest research and developments on various aspects of automotive systems engineering. The four-volume set consists of these individual volumes: Automotive Systems Engineering - Overview Automotive Systems Engineering - Requirements and Testing Automotive Systems Engineering - Modeling Automotive Systems Engineering - Approach and Verification

Automotive systems engineering addresses the system throughout its life cycle, including requirement, specification, design, implementation, verification and validation of systems, modeling, simulation, testing, manufacturing, operation and maintenance. This book is the fourth in a series of four volumes on this subject and features 12 papers, published between 2002-2009, that address the challenges and importance of systems approach in system verification and validation, stressing the use of advanced tools and approaches. Topics covered include: Systems integration and verification Software engineering in future automotive systems development Configuration management of the model-based design process Buy the Set and Save!

Automotive systems engineering addresses the system throughout its life cycle, including requirement, specification, design, implementation, verification and validation of systems, modeling, simulation, testing, manufacturing, operation and maintenance. This book - the third in a series of four volumes on this subject - features 11 papers, published between 1999-2010, that address the challenges and importance of systems modeling, stressing the use of advanced tools and approaches. Topics covered include: Automotive systems modeling Model-based design culture Applications Buy the Set and Save! Automotive Systems Engineering The four-volume set consists of these individual volumes: Automotive Systems Engineering - Overview Automotive Systems Engineering - Requirements and Testing Automotive Systems Engineering - Modeling Automotive Systems Engineering - Approach and Verification

Automotive systems engineering addresses the system throughout its life cycle, including requirement, specification, design, implementation, verification and validation of systems, modeling, simulation, testing, manufacturing, operation and maintenance. This book is the first in a series of four volumes on this subject and features 15 papers, published between 2004-2010, that emphasize the importance of systems concepts in the automotive area, and stress the use of advanced tools and approaches. Topics covered include: Technology transfer Six Sigma deployment Systems engineering capability in automotive systems In addition to 11 SAE technical papers, this volume also includes two invited papers: "Systems Engineering Definitions" by editor Subramaniam Ganesan and "Systems Engineering for Military Ground Vehicles" by M. Mazzara and R. Iyer. Buy the Set and Save!

Automotive systems engineering addresses the system throughout its life cycle, including requirement, specification, design, implementation, verification and validation of systems, modeling, simulation, testing, manufacturing, operation and maintenance. This book - the second in a series of four volumes on this subject - features 11 papers, published between 2000-2010, that address the challenges and importance of requirements and testing in systems engineering, stressing the use of advanced tools and approaches. Topics covered include: Creating correct requirements Requirement analysis Document management Development Management Architecture for military vehicles Buy the Set and Save! Automotive Systems Engineering The four-volume set consists of these individual volumes: Automotive Systems Engineering - Overview Automotive Systems Engineering - Requirements and Testing Automotive Systems Engineering - Modeling Automotive Systems Engineering - Approach and Verification

Frames are important structures found in many transportation applications such as automotive bodies and train cars. They are also widely employed in buildings, bridges, and other load bearing designs. When a frame is carrying multiple loads, it can potentially risk a catastrophic buckling failure. The loads on the frame may be non-proportional in that one force stays constant while the other is increased until buckling occurs. In this study the buckling problem is formulated as a constrained eigenvalue problem (CEVP). As opposed to other CEVP in which the eigenvectors are forced to comply with a number of the constraints, the eigenvalues in the current CEVP are subject to some equality constraints. A numerical algorithm for solving the constrained eigenvalue problem is presented. The algorithm is a simple trapping scheme in which the computation starts with an initial guess and a window containing the potential target for the eigenvalue is identified.

In recent years, implementation of dual phase (DP) Advanced High Strength Steels (AHSS) and Ultra High Strength Steels (UHSS) is increasing in automotive components due to their superior structural performance and vehicle weight reduction capabilities. However, these materials are often sensitive to trimmed edge cracking if stretching along sheared edge occurs in such processes as stretch flanging. Tool wear is another major issue in the trimming of UHSS because of higher contact pressures at the interface between cutting tools and sheet metal blank caused by UHSS’s higher flow stresses and the presence of a hard martensitic in the microstructure. The objective of the present paper is to study the influence of trimming conditions and tool wear on quality of trimmed edge of DP980 steel sheet. For this purpose, mechanically trimmed edges were characterized for DP980 steel, sheared with six different cutting clearances (from 4% to 40% of the sheet thickness).