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Time-averaged temperatures at critical locations on the piston of a direct-fuel injected, two-stroke, 388 cm3, research engine were measured using an infrared telemetry device. The piston temperatures were compared to data [7] of a carbureted version of the two-stroke engine, that was operated at comparable conditions. All temperatures were obtained at wide open throttle, and varying engine speeds (2000-4500 rpm, at 500 rpm intervals). The temperatures were measured in a configuration that allowed for axial heat flux to be determined through the piston. The heat flux was compared to carbureted data [8] obtained using measured piston temperatures as boundary conditions for a computer model, and solving for the heat flux. The direct-fuel-injected piston temperatures and heat fluxes were significantly higher than the carbureted piston. On the exhaust side of the piston, the direct-fuel injected piston temperatures ranged from 33-73 °C higher than the conventional carbureted piston.

Single-cylinder engine experiments and computational fluid dynamics (CFD) modeling were used in this study to conduct a comprehensive evaluation of the accuracy of the modeling approach, with a focus on soot emissions. A semi-empirical soot model, the classic two-step Hiroyasu model with Nagle and Strickland-Constable oxidation, was used. A broad range of direct-injected (DI) combustion systems were investigated to assess the predictive accuracy of the soot model as a design tool for modern DI diesel engines. Experiments were conducted on a 2.5 liter single-cylinder engine. Combustion system combinations included three unique piston bowl shapes and seven variants of a common rail fuel injector. The pistons included a baseline “Mexican hat” piston, a reentrant piston, and a non-axisymmetric piston similar to the Volvo WAVE design. The injectors featured six or seven holes and systematically varied included angles from 120 to 150 degrees and hole sizes from 170 to 273 μm.

Hybrid vehicle engines modified for high exhaust gas recirculation (EGR) are a good choice for high efficiency and low NOx emissions. Such operation can result in an HEV when a downsized engine is used at high load for a large fraction of its run time to recharge the battery or provide acceleration assist. However, high EGR will dilute the engine charge and may cause serious performance problems such as incomplete combustion, torque fluctuation, and engine misfire. An efficient way to overcome these drawbacks is to intensify tumble leading to increased turbulent intensity at the time of ignition. The enhancement of turbulent intensity will increase flame velocity and improve combustion quality, therefore increasing engine tolerance to higher EGR. It is accepted that the detailed experimental characterization of flow field near top dead center (TDC) in an engine environment is no longer practical and cost effective.

Today's engine and combustion process development is closely related to the intake port layout. Combustion, performance and emissions are coupled to the intensity of turbulence, the quality of mixture formation and the distribution of residual gas, all of which depend on the in-cylinder charge motion, which is mainly determined by the intake port and cylinder head design. Additionally, an increasing level of volumetric efficiency is demanded for a high power output. Most optimization efforts on typical homogeneous charge spark ignition (HCSI) engines have been at low loads because that is all that is required for a vehicle to make it through the FTP cycle. However, due to pumping losses, this is where such engines are least efficient, so it would be good to find strategies to allow the engine to operate at higher loads.

A framework to study the response of seated operators to whole-body vibration (WBV) is presented in this work. The framework consists of (i) a six-degree-of-freedom man-rated motion platform to play back ride files of typical heavy off-road machines; (ii) an optical motion capture system to collect 3D motion data of the operators and the surrounding environment (seat and platform); (iii) a computer skeletal model to embody the tested subjects in terms of their body dimensions, joint centers, and inertia properties; (iv) a marker placement protocol for seated positions that facilitates the process of collecting data of the lower thoracic and the lumbar regions of the spine regardless of the existence of the seatback; and (v) a computer human model to solve the inverse kinematics/dynamic problem for the joint profiles and joint torques. The proposed framework uses experimental data to answer critical questions regarding human response to WBV.

The performance of five positive k-factor injector tips has been assessed in this work by analyzing a comprehensive set of injected mass, momentum, and spray measurements. Using high speed shadowgraphs of the injected diesel plumes, the sensitivities of measured vapor penetration and dispersion to injection pressure (100-250MPa) and ambient density (20-52 kg/m3) have been compared with the Naber-Siebers empirical spray model to gain understanding of second order effects of orifice diameter. Varying in size from 137 to 353μm, the orifice diameters and corresponding injector tips are appropriate for a relatively wide range of engine cylinder sizes (from 0.5 to 5L). In this regime, decreasing the orifice exit diameter was found to reduce spray penetration sensitivity to differential injection pressure. The cone angle and k-factored orifice exit diameter were found to be uncorrelated.

Traditional Lagrangian spray modeling approaches for internal combustion engines are highly grid-dependent due to insufficient resolution in the near nozzle region. This is primarily because of inherent restrictions of volume fraction with the Lagrangian assumption together with high computational costs associated with small grid sizes. A state-of-the-art grid-convergent spray modeling approach was recently developed and implemented by Senecal et al., (ASME-ICEF2012-92043) in the CONVERGE software. The key features of the methodology include Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, which enables use of cell sizes smaller than the nozzle diameter. This modeling approach was rigorously validated against non-evaporating, evaporating, and reacting data from the literature.

A computational methodology has been developed for loss prediction in intake regions of internal combustion engines. The methodology consists of a hierarchy of four major tasks: (1) proper computational modeling of flow physics; (2) exact geometry and high quality and generation; (3) discretization schemes for low numerical viscosity; and (4) higher order turbulence modeling. Only when these four tasks are dealt with properly will a computational simulation yield consistently accurate results. This methodology, which is has been successfully tested and validated against benchmark quality data for a wide variety of complex 2-D and 3-D laminar and turbulent flow situations, is applied here to a loss prediction problem from industry. Total pressure losses in the intake region (inlet duct, manifold, plenum, ports, valves, and cylinder) of a Caterpillar diesel engine are predicted computationally and compared to experimental data.

Virtual Product Development (VPD) is a key enabler in CAE and depends upon accurate implementation of multibody dynamics. This paper discusses the formulation and implementation of a large-scale multibody dynamics simulation code. In the presented formulation, the joint variables are used as the generalized coordinates and spatial algebra is used to formulate the system equations of motion. Although the presented formulation utilizes the joint variables as the generalized coordinates, closed-loop mechanisms can be easily modeled using impeded constraints. Baumgart stabilization approach is used to eliminate the constraint violations without using the expensive Newton-Raphson iterations. Integrated rigid and flexible body dynamic simulation allows accurate prediction of structural loads, stress, and strains. Both modal and nodal flexible body approaches are discussed in the paper.

Development of Caterpillar Fuel Systems' MEUI-B injector has involved application of Computational Fluid Dynamics (CFD) in order to improve performance of the high pressure spill valve. Initial performance bench testing with concept stage experimental injectors indicated that the chamber pressure was decaying at an unacceptably slow rate, and the valve demonstrated erratic behavior at some operating conditions. The slow pressure decay and inconsistent spill valve motion were believed to be caused by flow forces generated during the low lift portion of the spill valve opening event. This theory was pursued by utilizing CFD to design two valves for testing in the next phase of the injector development cycle: A baseline geometry, similar to the original concept injector valve, and a new design incorporating localized seat geometry changes for inducing flow force assisted valve opening.

This paper summarizes the successful application of Computational Fluid Dynamics (CFD) analysis to predict and control the cavitation erosion in a hydraulic control valve. The accurate control of different vehicle operations demands very fine spool modulations in a hydraulic valve. The precise spool modulations create very high flow rates and high-pressure drops in the valve. The low local fluid pressure regions create cavitation inside the valve. Due to the explosion of bubbles there is a high erosion damage to the valve body as well as the spool surface. The CFD analysis has been used to predict the location of cavitation origination and also used to control the cavitation by redistributing the flow inside the valve.

Computational fluid dynamic (CFD) simulations that include realistic combustion/emissions chemistry hold the promise of significantly shortening the development time for advanced high-efficiency, low-emission engines. However, significant challenges must be overcome to realize this potential. This paper discusses these challenges in the context of diesel combustion and outlines a technical program based on the use of surrogate fuels that sufficiently emulate the chemical complexity inherent in conventional diesel fuel.

Increasingly, the exchanges of data in complex ECM (Electronic Control Module) systems rely on multiple communication networks across various physical and network layers. This has greatly increased system flexibility and provided an excellent medium to create well-defined exchangeable interfaces between components; however this added flexibility comes with increased network complexity. A system-level approach allows for the optimization of data exchange and network configuration as well as the development of a comprehensive network failure strategy. Many current ECM systems utilize complex multi-network communication strategies to exchange and control data to components. Recently, Caterpillar implemented an HIL (Hardware-In-the-Loop) test system that provides an approach for developing and testing a comprehensive ECM network strategy.

Natural gas quality, in terms of the volume fraction of higher hydrocarbons, strongly affects the auto-ignition characteristics of the air-fuel mixture, the engine performance and its controllability. The influence of natural gas composition on engine operation has been investigated both experimentally and through chemical kinetic based cycle simulation. A range of two component gas mixtures has been tested with methane as the base fuel. The equivalence ratio (0.3), the compression ratio (19.8), and the engine speed (1000 rpm) were held constant in order to isolate the impact of fuel autoignition chemistry. For each fuel mixture, the start of combustion was phased near top dead center (TDC) and then the inlet mixture temperature was reduced. These experimental results have been utilized as a source of data for the validation of a chemical kinetic based full-cycle simulation.

The Society of Automotive Engineers Fatigue Design & Evaluation Committee [SAE FD&E] is actively working on a total life project for weldments, in which the welding residual stress is a key contributor to an accurate assessment of fatigue life. Physics-based welding process simulation and various types of residual stress measurements were pursued to provide a representation of the residual stress field at the failure location in the fatigue samples. A well-controlled and documented robotic welding process was used for all sample fabrications to provide accurate inputs for the welding simulations. One destructive (contour method) residual stress measurement and several non-destructive residual stress measurements-surface X-ray diffraction (XRD), energy dispersive X-ray diffraction (EDXRD), and neutron diffraction (ND)-were performed on the same or similarly welded samples.

NVH is gaining importance in the quality perception of off-highway machines' performance and operator comfort. Booming noise, a low frequency NVH phenomenon, can be a significant sound issue in a motor grader when it is used under certain operating conditions that cause low frequency excitations to the machine. In order to increase operator comfort by decreasing the noise levels and noise annoyance, both simulation and testing techniques were leveraged to reduce the booming noise of a motor grader. Simultaneous structural/acoustics simulations and experimental modal tests were performed to evaluate this phenomenon. The simulation models were validated using test results and then used to evaluate solutions to this noise problem. Further field tests confirmed the validity of these recommended solutions.

Premixed Charge Compression Ignition (PCCI), a Low Temperature Combustion (LTC) strategy for diesel engines is of increasing interest due to its potential to simultaneously reduce soot and NOx emissions. However, the influence of mixture preparation on combustion phasing and heat release rate in LTC is not fully understood. In the present study, the influence of injection timing on mixture preparation, combustion and emissions in PCCI mode is investigated by experimental and computational methods. A sequential coupling approach of 3D CFD with a Stochastic Reactor Model (SRM) is used to simulate the PCCI engine. The SRM accounts for detailed chemical kinetics, convective heat transfer and turbulent micro-mixing. In this integrated approach, the temperature-equivalence ratio statistics obtained using KIVA 3V are mapped onto the stochastic particle ensemble used in the SRM.

A two-zone NOx model intended for 1-D engine simulations was developed and used to model NOx emissions from a 2.5 L single-cylinder engine. The intent of the present work is to understand key aspects of a simple NOx model that are needed for predictive accuracy, including NOx formation and destruction phenomena in a DI Diesel combustion system. The presented two-zone model is fundamentally based on the heat release rate and thermodynamic incylinder data, and uses the Extended Zeldovich mechanism to model NO. Results show that the model responded very well to changes in speed, load, injection timing, and EGR level. It matched measured tail pipe NOx levels within 20%, using a single tuning setup. When the model was applied to varied injection rate shapes, it showed correct sensitivity to speed, load, injection timing, and EGR level, but the absolute level was well outside the target accuracy. The same limitation was seen when applying the Plee NOx model.

Faced with competitive environments, pressure to lower development costs and aggressive timelines engineers are not only increasingly adopting numerical simulation techniques but are also embracing design optimization schemes to augment their efforts. These techniques not only provide more understanding of the trade-offs but are also capable of proactively guiding the decision making process. However, design optimization and exploration tools have struggled to find complete acceptance and are typically underutilized in many applications; especially in situations where the algorithms have to compete with existing swift decision making processes. In this paper we demonstrate how the type of setup and algorithmic choice can have an influence and make optimization more lucrative in a new product development atmosphere. We also present some results from a design exploration activity, involving linkage and structural development, of an earth moving machine application.

The increase in computational power in recent times has led to multidimensional computational fluid dynamics (CFD) modeling tools being used extensively for optimizing the diesel engine piston design. However, it is still common practice in engine CFD modeling to use constant uniform boundary temperatures. This is either due to the difficulty in experimentally measuring the component temperatures or the lack of measurements when simulation is being used predictively. This assumption introduces uncertainty in heat flux predictions. Conjugate heat transfer (CHT) modeling is an approach used to predict the component temperatures by simultaneously modeling the heat transfer in the fluid and the solid phase. However, CHT simulations are computationally expensive as they require more than one engine cycle to be simulated to converge to a steady cycle-averaged component temperature.