Military ground vehicle design must consider the threat posed by underbody blasts to new vehicles and their occupants, while also accounting for weight reduction goals for improving fuel economy and mobility. A two-stage process is presented to model the blast event, using LS-DYNA for simulating vehicle response and MADYMO for the occupant's response. Issues including computational expense, objective function formulation and multi-objective seating system design optimisation are addressed in detail, and three different blastworthiness optimisation formulations are presented and evaluated

We present an overview of our most recent and ongoing research efforts to develop a comprehensive framework for simulation-based design validation of vehicle systems. Specifically, we present the three major building blocks of our framework: (1) the introduction of an appropriate validation metric for dealing with the multivariate functional data that are the output of dynamic vehicle systems; (2) the robust implementation of a Bayesian interval-based hypothesis testing technique for quantifying the confidence in simulation models used for design under uncertainty; (3) the development of a sequential design optimisation and calibration-based validation methodology that addresses the inadequacy of current validation practices in simulation-based design optimisation. We present a simple yet illustrative example and discuss the techniques being developed currently that will complete the proposed framework

In motor-vehicle crashes, young school-aged children restrained by vehicle seat belt systems often suffer from abdominal injuries due to submarining. However, the current anthropomorphic test device, so-called “crash dummy”, is not adequate for proper simulation of submarining. In this study, a modified Hybrid-III six-year-old dummy model capable of simulating and predicting submarining was developed using MADYMO (TNO Automotive Safety Solutions). The model incorporated improved pelvis and abdomen geometry and properties previously tested in a modified physical dummy. The model was calibrated and validated against four sled tests under two test conditions with and without submarining using a multi-objective optimization method. A sensitivity analysis using this validated child dummy model showed that dummy knee excursion, torso rotation angle, and the difference between head and knee excursions were good predictors for submarining status. It was also shown that restraint system design variables, such as lap belt angle, D-ring height, and seat coefficient of friction (COF), may have opposite effects on head and abdomen injury risks; therefore child dummies and dummy models capable of simulating submarining are crucial for future restraint system design optimization for young school-aged children

This paper presents a preliminary design optimization study of a jet engine structure using a knowledge-based master modeling approach. The objective function is derived based on input-output relationships of a cost-performance model, where specific fuel consumption, pressure loss and direct cost are considered. The advantage of this problem formulation is that it entails a single composite objective function that takes into account mass, structural characteristics, dynamic response and translates them to a direct operational cost function to be minimized. A fan-blade-off scenario is considered as the loading case in this paper. The loss of one fan blade during nominal operation causes a rotor imbalance and structural deformation.

Sliding contacts in laminar flow regimes have been investigated extensively in recent years. The results indicate the possibility to increase load carrying capacity in a slider bearing for more than 10% with the addition of dimples. Parametric studies have been performed to determine optimal size and position, with emphasis in the optimal shape and position of the dimple for an operating condition. In this article, the numerical analysis of a 2D textured slider bearing with a dimple is initially considered with an isothermal laminar fluid. Position, depth, width and convergence ratio are optimized, the results demonstrate the importance of the width and convergence ratio to increase load. Then, the numerical analysis of a 3D textured slider bearing with fore-region and extended channels at the outlet and on the sides of a pad is considered. The simulations are also carried out for a laminar isothermal flow. Three dimples are considered and their depth is optimized.

Total Offers, Functional Products, and Integrated Product Service Engineering reflect a shift toward service offers from manufacturing industry captured within the term Product-Service Systems (PSS). Manufacturing companies have traditionally focused design and development activities on realizing technical and engineered aspects of physical artifacts, while PSS include deeper understanding of customers’ expectation, needs and perceived value, hence calling for modelling of additional aspects. The change in early design processes and the effects on virtual modelling of product properties are discussed in this paper through aerospace industry examples to clarify ‘parameters of change’, giving suggestions for a simulation driven design (SDD) approach.

The jet engine industry relies on product models for early design predictions of attributes such as structural behavior, mass and cost. When the required analysis models are not linked to the governing product model, effective coordination of design changes is a challenge, making design space exploration time-consuming. Master modeling (MM) approaches can help alleviate such analysis overhead; the MM concept has its origins in the computer-aided design (CAD) community, and mandates that manual changes in one model automatically propagate to assembly, computer-aided manufacturing (CAM) and computer-aided engineering (CAE) models within the CAD platform. Knowledge-based master models can also be used to communicate changes in the product definition to models that are external to the CAD platform. This paper presents details of the knowledge-based master modeling approach as applied to mechanical jet engine analysis and design, where different fidelity models and analysis tools are supported in the early design stages.

Novel rotating machinery design concepts and architectures are being explored to reduce mass, energy consumption, manufacturing costs, and environmental impact while increasing performance. As component manufacturers supply parts to original equipment manufacturers, it is desirable to design the components using a systems approach so that they are optimized for system-level performance. To accomplish that, suppliers must be able to model and predict the behavior of the whole machinery. Traditional computer-aided design/computer-aided engineering master-modeling approaches enable manual changes to be propagated to linked models. Novel knowledge-based master-modeling approaches enable automated coordination of multidisciplinary analyses. In this article, we present a specific implementation of such a knowledge-based master-modeling approach that facilitates multidisciplinary design optimization of rotating machinery. The master-model (MM) approach promotes the existence of a single governing version of the product definition as well as operating scenarios. Rules, scripts, and macros link the MM to domain-specific models. A simple yet illustrative industry application is presented, where rotor-dynamics and displacement analyses are performed to evaluate relocation alternatives for the rear bearing position of a rotating machinery under a ‘fan-blade-off’ load case.

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. The proposed methodology is illustrated using a thermal, one-dimensional, linear heat conduction problem in a solid slab with heat flux boundary conditions