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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.

This study looks at the application of a titanium dioxide (TiO2) catalytic nanoparticle suspension to the surface of the combustion chamber as a coating, as well as the addition of hydrogen gas to a four-stroke spark-ignited carbureted engine as a possible technique for lowering engine-out emissions. The experiments were conducted on two identical Generac gasoline powered generators using two, four and six halogen work lamps to load the engine. One generator was used as a control and the second had key components of the combustion chamber coated with the catalytic suspension. In addition to the coating, both engines were fed a hydrogen and oxygen gas mixture and tested at low, medium and high loads. Using an unmodified engine as a control set, the following three conditions were tested and compared: addition of hydrogen only, addition of coating only, and addition of hydrogen to the coated engine.

In this work computational and experimental approaches are combined to characterize in-cylinder flow structures and local flow field properties during operation of the Sandia 1.9L light-duty optical Diesel engine. A full computational model of the single-cylinder research engine was used that considers the complete intake and exhaust runners and plenums, as well as the adjustable throttling devices used in the experiments to obtain different swirl ratios. The in-cylinder flow predictions were validated against an extensive set of planar PIV measurements at different vertical locations in the combustion chamber for different swirl ratio configurations. Principal Component Analysis was used to characterize precession, tilting and eccentricity, and regional averages of the in-cylinder turbulence properties in the squish region and the piston bowl.

While Low Temperature Combustion (LTC) strategies such as Reactivity Controlled Compression Ignition (RCCI) exhibit high thermal efficiency and produce low NOx and soot emissions, low load operation is still a significant challenge due to high unburnt hydrocarbon (UHC) and carbon monoxide (CO) emissions, which occur as a result of poor combustion efficiencies at these operating points. Furthermore, the exhaust gas temperatures are insufficient to light-off the Diesel Oxidation Catalyst (DOC), thereby resulting in poor UHC and CO conversion efficiencies by the aftertreatment system. To achieve exhaust gas temperature values sufficient for DOC light-off, combustion can be appropriately phased by changing the ratio of gasoline to diesel in the cylinder, or by burning additional fuel injected during the expansion stroke through post-injection.

In recent years society's demand and interest in clean and efficient internal combustion engines has grown significantly. Several ideas have been proposed and tested to meet this demand. In particular, dual-fuel Reactivity Controlled Compression Ignition (RCCI) combustion has demonstrated high thermal efficiency, and low engine-out NOx, and soot emissions. Unlike homogeneous charge compression ignition (HCCI) combustion, which solely relies on the chemical kinetics of the fuel for ignition control, RCCI combustion has proven to provide superior combustion controllability while retaining the known benefits of low emissions and high thermal efficiency of HCCI combustion. However, in order for RCCI combustion to be adopted as a high efficiency and low engine-out emission solution, it is important to achieve high-power operation that is comparable to conventional diesel combustion (CDC).

3-D Computational Fluid Dynamics (CFD) simulations have been performed to study particulate formation in a Spark-Ignition (SI) engine under premixed conditions. A semi-detailed soot model and a chemical kinetic model, including poly-aromatic hydrocarbon (PAH) formation, were coupled with a spark ignition model and the G equation flame propagation model for SI engine simulations and for predictions of soot mass and particulate number density. The simulation results for in-cylinder pressure and particle size distribution (PSDs) are compared to available experimental studies of equivalence ratio effects during premixed operation. Good predictions are observed with regard to cylinder pressure, combustion phasing and engine load. Qualitative agreements of in-cylinder particle distributions were also obtained and the results are helpful to understand particulate formation processes.

Knock in a Rotax-914 engine was modeled and investigated using an improved version of the KIVA-3V code with a G-equation combustion model, together with a reduced chemical kinetics model. The ERC-PRF mechanism with 47 species and 132 reactions [1] was adopted to model the end gas auto-ignition in front of the flame front. The model was validated by a Caterpillar SI engine and a Rotax-914 engine in different operating conditions. The simulation results agree well with available experimental results. A new engineering quantified knock criterion based on chemical mechanism was then proposed. Hydroperoxyl radical (HO2) shows obvious accumulation before auto-ignition and a sudden decrease after auto-ignition. These properties are considered to be a good capability for HO2 to investigate engine knock problems.

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.

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.

Engine experiments have revealed the importance of fuel condensation on the emission characteristics of low temperature combustion. However, direct in-cylinder experimental evidence has not been reported in the literature. In this paper, the in-cylinder condensation processes observed in optically accessible engine experiments are first illustrated. The observed condensation processes are then simulated using state-of-the-art multidimensional engine CFD simulations with a phase transition model that incorporates a well-validated phase equilibrium numerical solver, in which a thermodynamically consistent phase equilibrium analysis is applied to determine when mixtures become unstable and a new phase is formed. The model utilizes fundamental thermodynamics principles to judge the occurrence of phase separation or combination by minimizing the system Gibbs free energy.

Surface film formation is an important phenomenon during spray impingement in a combustion chamber. The film that forms on the chamber walls and piston bowl produces soot post-combustion. While some droplets stick to the wall surface, others splash and interact with the gas present inside the combustion chamber. Accurate prediction of both the film thickness and splashed mass is crucial for surface film model development since it leads to a precise estimation of the amount of soot and other exhaust gases formed. This information could guide future studies aimed at a comprehensive understanding of the combustion process and might enable development of engines with reduced emissions. Dynamic structure Large Eddy Simulation (LES) turbulence model implemented for in-cylinder sprays [1] has shown to predict the flow structure of a spray more accurately than the Reynolds-averaged Navier-Stokes turbulence model.

A computer program which rapidly calculates the equilibrium mole fractions and the partial derivatives of the mole fractions with respect to temperature, pressure and equivalence ratio for the products of combustion of any hydrocarbon fuel and air is described. A subroutine is also given which calculates the gas constant, enthalpy, internal energy and the partial derivatives of these with respect to temperature, pressure and equivalence ratio. Some examples of the uses of the programs are also given.