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In the air conditioning system, flow-induced noise is very disturbing, including the noise generated in the expansion device and the heat exchangers. In the past few decades, most researches related to flow-induced noise focused on the relationship between the flow regimes near the expansion device and the amplitude of flow-induced noise when the measurements are not synched. In this paper, an experimental approach is used to explore the simultaneous relationships between flow-induced noise characteristics and flow regimes at the inlet of TXV of evaporators used in automobiles. A pumped R134a loop with microphones and transparent visualization sections is used to simulate the vapor compression system. Also, the paper evaluates the severity of flow-induced noise from not only the amplitude of noise but also the frequency of noise with a parameter called psychoacoustic annoyance (PA).

This paper presents a simulation model for a reversible air conditioning and heat pump system for electric vehicles. The system contains a variable speed compressor, three microchannel heat exchangers, an accumulator, and two electronic expansion valves. Heat exchangers are solved by discretizing into cells. Compressor and accumulator models are developed by fitting data with physical insights. Expansion valves are modeled by isenthalpic processes. System performance is calculated by connecting all parts in the same way as the physical system and solved iteratively. The model is reasonably validated against experimental data from a separate experimental study. Future improvement is needed to take into account maldistribution in outdoor heat exchanger working as an evaporator in HP mode. Charge retention in components also requires further study.

With the development of advanced ABE fermentation technology, the volumetric percentage of acetone, butanol and ethanol in the bio-solvents can be precisely controlled. To seek for an optimized volumetric ratio for ABE-diesel blends, the previous work in our team has experimentally investigated and analyzed the combustion features of ABE-diesel blends with different volumetric ratio (A: B: E: 6:3:1; 3:6:1; 0:10:0, vol. %) in a constant volume chamber. It was found that an increased amount of acetone would lead to a significant advancement of combustion phasing whereas butanol would compensate the advancing effect. Both spray dynamic and chemistry reaction dynamic are of great importance in explaining the unique combustion characteristic of ABE-diesel blend. In this study, a semi-detailed chemical mechanism is constructed and used to model ABE-diesel spray combustion in a constant volume chamber.

The modeling of fuel jet atomization is key in the characterization of Internal Combustion (IC) engines, and 3D Computational Fluid Dynamics (CFD) is a recognized tool to provide insights for design and control purposes. Multi-hole injectors with counter-bored nozzle are the standard for Gasoline Direct Injection (GDI) applications and the Spray-G injector from the Engine Combustion Network (ECN) is considered the reference for numerical studies, thanks to the availability of extensive experimental data. In this work, the behavior of the Spray-G injector is simulated in a constant volume chamber, ranging from sub-cooled (nominal G) to flashing conditions (G2), validating the models on Diffused Back Illumination and Phase Doppler Anemometry data collected in vaporizing inert conditions.

This paper develops a model for a parallel microchannel evaporator that incorporates quality variation at the tube inlets and variable mass flow rates among tubes. The flow distribution is based on the equal pressure drop along each flow path containing headers and tubes. The prediction of pressure drop, cooling capacity, and exit superheat strongly agree with 48 different experimental results obtained in four configurations using R134a. Predicted temperature profiles are very close to infrared images of actual evaporator surface. When compared to the uniform distribution model (that assumes uniform distribution of refrigerant mass flow rate and quality) results from the new model indicate superior prediction of cooling capacity, and exit superheat. Model results indicate maldistribution of refrigerant mass flow rate among the parallel tubes, caused primarily by pressure drop in the outlet header.

Intelligent convoy consisting of heavy duty vehicles is an implementation of IVHS believed to be one of the most practicable proposals to come into reality in the near feature. Control Strategy in the context of Autonomous Intelligent Vehicle Platoon is different from that in other “Lane-keeping” IVHS systems which have been well studied. In this paper, an Autonomous Platoon consisting two articulated commercial vehicles is studied and a model of tractor-trailer type commercial vehicles suitable for control studies is derived based on a single track three-axle bicycle model. The authors give perspectives on the implementation of intelligent convoy of articulated vehicles emphasizing safety issues in emergency situations, as opposed to normal following of the lead vehicle. An initial integrated braking and steering control is developed to avoid spinout or jack-knifing when specific axles are locked during braking process.

Legislation on vehicle emissions and the requirements for fuel efficiency are currently the key development driving factors in the automotive industry. Research activities to comply with these targets point to engine downsizing and new boosting technologies, which have adverse effects on the NVH performance, durability and component life. As a consequence of engine downsizing, substantial torsional oscillations are generated due to high combustion pressures. Meanwhile, to attenuate torsional vibrations, the manufacturers have implemented absorbers that are tuned to certain frequency ranges, including clutch dampers, Dual Mass Flywheel (DMF) and centrifugal pendulum dampers. These devices add mass/inertia to the system, potentially introducing negative effects on other vehicle attributes, such as weight, driving performance and gear shiftability.

A new approach of NOx reduction in the compression-ignition engine is introduced in this work. The previous research has shown that during the combustion stage, the high temperature ignition tends to occur early at the near-stoichiometric region where the combustion temperature is high and majority of NOx is formed; Therefore, it is desirable to burn the leaner region first and then the near-stoichiometric region, which inhibits the temperature rise of the near-stoichiometric region and consequently suppresses the formation of NOx. Such inverted ignition sequence requires mixture with inverted phi-sensitivity. Fuel selection is performed based on the criteria of strong ignition T-sensitivity, negligible negative temperature coefficient (NTC) behavior, and large heat of vaporization (HoV).

The motivation of the present work was to understand the mechanism by which alcohols produce less aromatic species in their combustion process than an equal amount of hydrocarbon with similar molecular structure does. Due to its numerous advantages over short-chain alcohols, butanol has been considered very promising in soot reduction. Excluding the influence of spray, vaporization and mixing process in engine cases, an adiabatic constant-pressure reactor model was applied to investigate the effect of butanol additives on aromatic species, which are known to be soot precursors, in fuel-rich butane flames. To keep the carbon flux constant, 5% and 10% oxygen by mass of the fuel were added to butane using butanol additive, respectively. Based on the soot reduction effects proposed in literature, effects on temperature, key radical concentrations and the carbon removal from the pathway to aromatic species were considered to identify the major mechanism of reduction in aromatic species.

This work presents a comprehensive computational study of diesel - natural gas (NG) dual fuel engine. A complete computational model is developed for the operation of a diesel - NG dual fuel engine modified from an AVL 5402 single cylinder diesel test engine. The model is based on the KIVA-3V program and includes customized sub-models. The model is validated against test cell measurements of both pure diesel and dual fuel operation. The effects of NG on ignition and combustion in dual fuel operation are analyzed in detail. Zero-dimensional computations with a diesel surrogate reaction mechanism are conducted to discover the effects of NG on ignition and combustion and to reveal the fundamental chemical mechanisms behind such effects. Backed by the detailed theoretical analysis, the engine operation parameters are optimized with genetic algorithm (GA) for the dual fuel operation of the modified AVL 5402 test engine.

Butanol, which is a renewable biofuel, has been regarded as a promising alternative fuel for internal combustion engines. When blended with diesel and applied to pilot ignited natural gas engines, butanol has the capability to achieve lower emissions without sacrifice on thermal efficiency. However, high blend ratio of butanol is limited by its longer ignition delay caused by the higher latent heat and higher octane number, which restricts the improvement of emission characteristics. In this paper, the potential of increasing butanol blend ratio by adding hot exhaust gas recirculation (EGR) is investigated. 3D CFD model based on a detailed kinetic mechanism was built and validated by experimental results of natural gas engine ignited by diesel/butanol blends. The effects of hot EGR is then revealed by the simulation results of the combustion process, heat release traces and also the emissions under different diesel/butanol blend ratios.

This research compares the responses of a vehicle modeled in the 3D vehicle simulation program SIMON in the HVE simulation operating system against instrumented responses of a 3-axle tractor, 2-axle semi-trailer combination. The instrumented tests were previously described in SAE 2001-01-0139 and SAE 2003-01-1324 as part of a continuous research effort in the area of vehicle dynamics undertaken at the Vehicle Research and Test Center (VRTC). The vehicle inertial and mechanical parameters were measured at the University of Michigan Transportation Research Institute (UMTRI). The tire data was provided by Smithers Scientific Services, Inc. and UMTRI. The series of tests discussed herein compares the modeled and instrumented vehicle responses during quasi-steady state, steady state and transient handling maneuvers, producing lateral accelerations ranging nominally from 0.05 to 0.5 G's.

Using neural networks, an algorithm has been developed to steer a wheel loader vehicle. Mathematical functions have been used in the past in an attempt to model a human in their operation of many types of vehicles. Since such functions can typically only be derived for situations in which the problem domain is thoroughly understood, research continues in an effort to develop a complete “operator model”. Neural Network algorithms were utilized in an attempt to determine the feasibility of accurately modeling the operator of a wheel loader construction vehicle. These algorithms were also used to determine how the control of different vehicle functions might be automated on a wheel loader.

Inlet valve deposits in gasoline engines have a significant effect on engine operation with particular reference to cold starting and driveability. Present methods of quantifying these deposits by weighing them or rating them with the aid of a visual rating scale are recognized as not being reliable indices of the detrimental effect of these deposits. A valve deposit quantification system was developed that relied on the use of machine vision. Algorithms were formulated to track the silhouetted edge profile of a backlit valve from which a valve volume was determined. The valve deposit volume was calculated as the difference in volume between the valve in its clean and coked states. The system was able to detect a minimum coke deposit level of 0.06g at the 95% confidence limit, the accuracy being based on the correlation between the volume as determined by the vision system and the mass of the deposit.

In this paper we demonstrate our work to date on our underactuated two link robot called the Pendubot. First we will overview the Pendubot's design, discussing the components of the linkage and the interface to the PC making up the controller. Parameter identification of the Pendubot is accomplished both by solid modeling methods and energy equation least squares techniques. With the identified parameters, mathematical models are developed to facilitate controller design. The goal of the control is to swing the Pendubot up and balance it about various equilibrium configurations. Two control algorithms are used for this task. Partial feedback linearization techniques are used to design the swing up control. The balancing control is then designed by linearizing the dynamic equations about the desired equilibrium point and using LQR or pole placement techniques to design a stabilizing controller.

Modern air vehicles face increasing internal heat loads that must be appropriately understood in design and managed in operation. This paper examines one solution to creating more efficient and effective thermal management systems (TMSs): vapor cycle systems (VCSs). VCSs are increasingly being investigated by aerospace government and industry as a means to provide much greater efficiency in moving thermal energy from one physical location to another. In this work, we develop the AFRL (Air Force Research Laboratory) Transient Thermal Modeling and Optimization (ATTMO) toolbox: a modeling and simulation tool based in Matlab/Simulink that is suitable for understanding, predicting, and designing a VCS. The ATTMO toolbox also provides capability for understanding the VCS as part of a larger air vehicle system. The toolbox is presented in a modular fashion whereby the individual components are presented along with the framework for interconnecting them.

Several types of noise exist in automobiles. The flow-induced noise in the expansion device can be very disturbing since the expansion device is located near the occupants. In many studies, the flow-induced noise is found to be mitigated when the orientation of the tube is changed. However, no study explores the reason why flow-induced noise changes when the orientation of the tube is changed. The flow-induced noise varies along with the flow regimes near the expansion devices. In this paper, an experimental based research is used to study how the tube orientation changes the flow regimes under the same operating conditions. A pumped R134a system with transparent tubes (1/4-inch ID) is used to visualize the flow regimes near the manual expansion valve. The transparent tube is a continuous connection of horizontal tubes, 45° inclined tubes, and vertical tubes.

A new Aircraft Accident Awareness Program (AAAP) was developed, evaluated, and is available to emergency response service provider organizations (firefighters, emergency medical technicians, trauma center personnel, law enforcement, clergy, coroners, and media) who would be called to an aircraft accident scene. Aircraft accident responder training is a critical factor in accident victim crash survivability and successful life-safety outcomes. This program was designed to teach participants about the unique conditions and safety hazards associated with aircraft crashes. A blend of academic classroom investigation, exposure to airworthy/ unairworthy aircraft including operating systems and components, computer accident simulations, “hands-on” (destructive) extrication protocol training, and participation in simulated in-the-field accident scenarios was used as an instructional delivery model.

Yield potential was predicted and mapped for three corn fields in Central Illinois, using digital aerial color infrared images. Three methods, namely statistical (regression) modeling, genetic algorithm optimization and artificial neural networks, were used for developing yield models. Two image resolutions of 3 and 6 m/pixel were used for modeling. All the models were trained using July 31 image and tested using images from July 2 and August 31, all from 1998. Among the three models, artificial neural networks gave best performance, with a prediction error less than 30%. The statistical model resulted in prediction errors in the range of 23 to 54%. The lower resolution images resulted in better prediction accuracy compared to resolutions higher than or equal to the yield resolution. Images after pollination resulted in better accuracy compared to images before pollination.

Air source heat pumps as the heating system for full electric vehicles are drawing more and more attention in recent years. Despite the high energy efficiency, frost accumulation on the heat pump evaporator is one of the major challenges associated with air source heat pumps. The evaporator needs to be actively defrosted periodically and heat pump heating will be interrupted during defrosting process. Proper defrost control is needed to obtain high average heat pump energy efficiency. In this paper, a new method for generating air source heat pump defrost control policy using reinforcement learning is introduced. This model-free method has several advantages. It can automatically generate optimal defrost control policy instead of requiring manually determination of the control policy parameters and logics.