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Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

A method for automatically generating hex-dominant meshes for Computational Fluid Dynamics (CFD) applications is presented in this article. Two important regions of the mesh for any CFD simulation are the interior mesh and the boundary layer mesh. The interior mesh needs to be fine in the critical flow regions to ensure accurate solutions. The proposed method uses Bubble Mesh algorithm which packs bubbles inside the geometry to generate the mesh nodes. Algorithm was tested for sample flow problems and improvements were made to interior and boundary layer mesh generation methods. The interior mesh is generated using directionality and sizing control functions specified on the points of a 3D grid generated over the entire geometry. This offers a flexible control over mesh sizing and local mesh refinement. Boundary layer mesh is important to accurately model the physics of boundary layer near the geometry walls.

The CFD tools in aerodynamic design process have been commonly used in aerospace industry in last three decades. Although there are many CFD software algorithms developed for aerodynamic applications, the nature of a complex, three-dimensional geometry in incompressible highly separated, viscous flow made computational simulation of ground vehicle aerodynamics more difficult than aerospace applications. However, recent developments in computational hardware and software industry enabled many new engineering applications on computational environment. Traditional production process has largely influenced by computational design, analysis, manufacturing and visualization. Different aspects of linking advanced computational tools and aerodynamic vehicle design challenges are discussed in the present work. Key technologies like parallel computation, turbulence modeling and CFD/wind tunnel compatibility issues are presented.

The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as local, globally lean, low-temperature combustion strategies are setting the path towards a more efficient and environmentally sustainable use of energy resources in transportation. In this paper, we assessed the computational efficiency of a recently developed sparse analytical Jacobian chemistry solver, namely ‘SpeedCHEM’, that features both direct and Krylov-subspace solution methods for maximum efficiency for both small and large mechanism sizes. The code was coupled with a high-dimensional clustering algorithm for grouping homogeneous reactors into clusters with similar states and reactivities, to speed-up the chemical kinetics solution in multi-dimensional combustion simulations.

The performance of a structural design significantly depends upon the assumptions made on input load. In order to estimate the input load, during the design and development stage of the suspension assembly of a BAJA car, designers and analysts invest immense amount of time and effort to formulate the mathematical model of the design. These theoretical formulations may include idealization errors which can affect the performance of the car as a final product. Due to the errors associated with the assumption of design load, several components might have more weight or may have less strength than needed. This discrepancy between the assumed input load (lab or theoretical studies) and the actual load from the environment can be eliminated by performing a real life testing process using load recovery methodology. Commercial load cells exist in industry to give engineers insight to understanding the complex real world loading of their structures.

Increasingly sophisticated vehicle automation can perform steering and speed control, allowing the driver to disengage from driving. However, vehicle automation may not be capable of handling all roadway situations and driver intervention may be required in such situations. The typical approach is to indicate vehicle capability through displays and warnings, but control algorithms can also signal capability. Psychophysical methods can be used to link perceptual experiences to physical stimuli. In this situation, trust is an important perceptual experience related to automation capability that is revealed by the physical stimuli produced by different control algorithms. For instance, precisely centering the vehicle in the lane may indicate a highly capable system, whereas simply keeping the vehicle within lane boundaries may signal diminished capability.

A detailed mathematical model of the thermodynamic events of a crankcase scavenged, two-stroke, SI engine is described. The engine is divided into three thermodynamic systems: the cylinder gases, the crankcase gases, and the inlet system gases. Energy balances, mass continuity equations, the ideal gas law, and thermodynamic property relationships are combined to give a set of coupled ordinary differential equations which describe the thermodynamic states encountered by the systems of the engine during one cycle of operation. A computer program is used to integrate the equations, starting with estimated initial thermodynamic conditions and estimated metal surface temperatures. The program iterates the cycle, adjusting the initial estimates, until the final conditions agree with the beginning conditions, that is, until a cycle results.

Distracted driving remains a serious risk to motorists in the US and worldwide. Over 3,000 people were killed in 2013 in the US because of distracted driving; and over 420,000 people were injured. A system that can accurately detect distracted driving would potentially be able to alert drivers, bringing their attention back to the primary driving task and potentially saving lives. This paper documents an effort to develop an algorithm that can detect visual distraction using vehicle-based sensor signals such as steering wheel inputs and lane position. Additionally, the vehicle-based algorithm is compared with a version that includes driving-based signals in the form of head tracking data. The algorithms were developed using machine learning techniques and combine a Random Forest model for instantaneous detection with a Hidden Markov model for time series predictions.