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This paper investigates flow and combustion in a full-cycle simulation of a four-stroke, three-valve HCCI engine by visualizing the flow with pathlines. Pathlines trace massless particles in a transient flow field. In addition to visualization, pathlines are used here to trace the history, or evolution, of flow fields and species. In this study evolution is followed from the intake port through combustion. Pathline analysis follows packets of intake charge in time and space from induction through combustion. The local scalar fields traversed by the individual packets in terms of velocity magnitude, turbulence, species concentration and temperatures are extracted from the simulation results. The results show how the intake event establishes local chemical and thermal environments in-cylinder and how the species respond (chemically react) to the local field.

The ability to make fully resolved turbulent scalar field measurements has been demonstrated in an internal combustion engine using one-dimensional fluorobenzene fluorescence measurements. Data were acquired during the intake stroke in a motored engine that had been modified such that each intake valve was fed independently, and one of the two intake streams was seeded with the fluorescent tracer. The scalar energy spectra displayed a significant inertial subrange that had a −5/3 wavenumber power dependence. The scalar dissipation spectra were found to extend in the high-wavenumber regime, to where the magnitude was more than two decades below the peak value, which indicates that for all practical purposes the measurements faithfully represent all of the scalar dissipation in the flow.

A modular and scalable Dense Medium Plasma Water Purification Reactor was developed, which uses atmospheric-pressure electrical discharges under water to generate highly reactive species to break down organic contaminants and microorganisms. Key benefits of this novel technology include: (i) extremely high efficiency in both decontamination and disinfection; (ii) operating continuously at ambient temperature and pressure; (iii) reducing demands on the containment vessel; and (iv) requiring no consumables. This plasma based technology was developed to replace the catalytic reactor being used in the planned International Space Station Water Processor Assembly.

The fuel film thickness resulting from diesel fuel spray impingement was measured in a chamber at conditions representative of early injection timings used for low temperature diesel combustion. The adhered fuel volume and the radial distribution of the film thickness are presented. Fuel was injected normal to the impingement surface at ambient temperatures of 353 K, 426 K and 500 K, with densities of 10 kg/m3 and 25 kg/m3. Two injectors, with nozzle diameters of 100 μm and 120 μm, were investigated. The results show that the fuel film volume was strongly affected by the ambient temperature, but was minimally affected by the ambient density. The peak fuel film thickness and the film radius were found to increase with decreased temperature. The fuel film was found to be circular in shape, with an inner region of nearly constant thickness. The major difference observed with temperature was a decrease in the radial extent of the film.

The demand for highly flexible manipulation of plant growth generations, modification of specific plant processes, and genetically engineered crop varieties in a controlled environment has led to the development of a Commercial Plant Biotechnology Facility (CPBF). The CPBF is a quad-middeck locker playload to be mounted in the EXPRESS Rack that will be installed in the International Space Station (ISS). The CPBF integrates proven ASTROCULTURE” technologies, state-of-the-art control software, and fault tolerance and recovery technologies together to increase overall system efficiency, reliability, robustness, flexibility, and user friendliness. The CPBF provides a large plant growing volume for the support of commercial plant biotechnology studies and/or applications for long time plant research in a reduced gravity environment.

Neural networks are useful tools for optimization studies since they are very fast, so that while capturing the accuracy of multi-dimensional CFD calculations or experimental data, they can be run numerous times as required by many optimization techniques. This paper describes how a set of neural networks trained on a multi-dimensional CFD code to predict pressure, temperature, heat flux, torque and emissions, have been used by a genetic algorithm in combination with a hill-climbing type algorithm to optimize operating parameters of a diesel engine over the entire speed-torque map of the engine. The optimized parameters are mass of fuel injected per cycle, shape of the injection profile for dual split injection, start of injection, EGR level and boost pressure. These have been optimized for minimum emissions. Another set of neural networks have been trained to predict the optimized parameters, based on the speed-torque point of the engine.

Neural networks have been used for engine computations in the recent past. One reason for using neural networks is to capture the accuracy of multi-dimensional CFD calculations or experimental data while saving computational time, so that system simulations can be performed within a reasonable time frame. This paper describes three methods to improve upon neural network predictions. Improvement is demonstrated for in-cylinder pressure predictions in particular. The first method incorporates a physical combustion model within the transfer function of the neural network, so that the network predictions incorporate physical relationships as well as mathematical models to fit the data. The second method shows how partitioning the data into different regimes based on different physical processes, and training different networks for different regimes, improves the accuracy of predictions.

This paper describes how a blend of silicon polymers, mixed with the right combination of fillers, enables the production of durable rubber IC engine head and exhaust gaskets. The resin blend, when mixed with glass fiber reinforcement, produces a liquid sealant suitable for exhaust gasket applications. The exhaust sealant and laminate head gaskets were tested on Ford 460 truck engines at Jasper Engine Company and completed more than 5,000 hours of durability testing without incident. Fabric reinforced polymer (FRP) head and exhaust gaskets can be laser cut from molded laminates, creating a ceramic glass-sealed edge. Thermogravimetric scans of typical gasket laminate material reveal an 88%-yield at 1000°C. FRP head gaskets also enable the cost-effective production of multiple spark ignition (MSI) head gaskets.

The impingement of liquid fuels on surfaces in IC engines affects performance and emissions. To better understand liquid/solid interactions, the impact of single droplets on a healed surface was experimentally examined. The droplet impingement was photographed with a high speed cine camera to obtain a history of the hydrodynamics of the impingement process. Images obtained from the cine photography were inspected to determine hydrodynamic regimes: wetting, transition, and non-wetting, associated with the specific impingement conditions (droplet size, velocity, surface temperature, and ambient pressure). Images from selected impingement conditions were further analyzed to quantify the atomization resulting from the impingement.

Combustion under stratified operating conditions in a direct-injection spark-ignition engine was investigated using simultaneous planar laser-induced fluorescence imaging of the fuel distribution (via 3-pentanone doped into the fuel) and the combustion products (via OH, which occurs naturally). The simultaneous images allow direct determination of the flame front location under highly stratified conditions where the flame, or product, location is not uniquely identified by the absence of fuel. The 3-pentanone images were quantified, and an edge detection algorithm was developed and applied to the OH data to identify the flame front position. The result was the compilation of local flame-front equivalence ratio probability density functions (PDFs) for engine operating conditions at 600 and 1200 rpm and engine loads varying from equivalence ratios of 0.89 to 0.32 with an unthrottled intake. Homogeneous conditions were used to verify the integrity of the method.

Regenerative testing methods can be used to allow the testing of hydraulic pumps and motors at significantly higher power and flow levels than that of the power supply used. This method can also increase the accuracy of system efficiency measurements. The increase in accuracy is realized because only the power added to compensate for the system losses needs to be measured with great accuracy. Typically, for the operation points of interest this will be a much smaller quantity than the overall power of the system. Knowing that the error in flow measurements is a function of the quantity measured, the benefit of measuring the losses becomes clear. An additional, distinct advantage of regenerative testing is that no dynamometer or load is needed. This results in a much simpler test setup. This paper documents the development of such a test program at the University of Wisconsin-Madison.

A fuel film model has been developed and implemented into the KIVA-II code to help account for fuel distribution during combustion in diesel engines. Spray-wall interaction and spray-film interaction are also incorporated into the model. The model simulates thin fuel film flow on solid surfaces of arbitrary configuration. This is achieved by solving the continuity and momentum equations for the two dimensional film that flows over a three dimensional surface. The major physical effects considered in the model include mass and momentum contributions to the film due to spray drop impingement, splashing effects, various shear forces, piston acceleration, and dynamic pressure effects. In order to adequately represent the drop interaction process, impingement regimes and post-impingement behavior have been modeled using experimental data and mass, momentum and energy conservation constraints. The regimes modeled for spray-film interaction are stick, rebound, spread, and splash.

The hydrodynamic details of droplet-droplet and droplet-liquid film interactions on solid surfaces are believed to have a significant role in spray impingement phenomena, yet details of this interaction have not been clearly identified. The interaction among the droplets during impact affects their residence time on the surface, spreading, and droplet and liquid film stability. After impact, droplet interactions affect droplet collisions, coalescence and liquid splashing, This interaction affects secondary atomization and the droplet dispersion characteristics of the impingement process. In this study, details of droplet-droplet and droplet-liquid film interactions in solid surface impingement have been visualized using high speed photography. The effects of these interactions on secondary atomization and droplet dispersion have been quantified.

Control of the flow of thermal energy in an air-cooled engine is important to the overall performance of the engine because of potential effects on engine performance, durability, design, and emissions. A methodology is being developed for the assessment of thermal flows in air-cooled engines, which includes the use of cycle simulation and in-cylinder heat flux measurements. The mechanism for the combination of cycle simulation, the measurement of in-cylinder heat flux and wall temperatures, and comparison of predicted and measured heat flux in the methodology is presented. The methodology consists of both simulation and experimental phases. To begin, a one-dimensional gas dynamics code (WAVE) has been used in conjunction with a detailed in-cylinder flow and combustion model (IRIS) in order to simulate engine operation in a variety of operating conditions. The methods used to apply the model to the air-cooled engine case are described in detail.

Five potato (Solanum tuberosum L.) leaf cuttings were flown on STS-73 in late October, 1995 as part of the 16-day USML-2 mission. Pre-flight studies were conducted to study tuber growth, determine carbohydrate concentrations and examine the developing starch grains within the tuber. In these tests, tubers attained a fresh weight of 1.4 g tuber-1 after 13 days. Tuber fresh mass was significantly correlated to tuber diameter. Greater than 60% of the tuber dry mass was starch and the starch grains varied in size from 2 to 40 mm in the long axis. For the flight experiment, cuttings were obtained from seven-week-old Norland potato plants, kept at 5°C for 12 hours then planted into arcillite in the ASTROCULTURE™ flight hardware. The flight package was loaded on-board the orbiter 22 hours prior to launch.

A numerical study of air-fuel mixing in a direct-injection spark-ignition engine was carried out. In this paper, the numerical models are described and grid generation methods to represent a realistic port-valve-chamber geometry is discussed. To model a vaporizing hollow-cone spray resulting from an automotive pressure-swirl injector, a newly developed sheet spray atomization model was used to compute the processes of disintegration of the liquid sheet and breakup of the subsequent drops. Computations were performed of a particular 4-valve pent-roof engine configuration in which the intake process and an early fuel injection scheme were considered. After an analysis of the intake-generated flow structures in this engine configuration, the spray behavior and the spatial and temporal evolution of fuel liquid and vapor phases are characterized.

Transient operation of automobile engines is known to contribute significantly to regulated exhaust emissions, and is also an area of drivability concerns. Furthermore, many on-board diagnostic algorithms do not perform well during transient operation and are often temporarily disabled to avoid problems. The inability to quickly and repeatedly test engines during transient conditions in a laboratory setting limits researchers and development engineers ability to produce more effective and robust algorithms to lower vehicle emissions. To meet this need, members of the Powertrain Control Research Laboratory (PCRL) at the University of Wisconsin-Madison have developed a high-bandwidth, hydrostatic dynamometer system that will enable researchers to explore transient characteristics of engines and powertrains in the laboratory.

High-resolution planar laser-induced fluorescence (PLIF) measurements were performed on the scalar field in an optical engine. The measurements were of sufficient resolution to fully resolve all of the length scales of the flow field through the full cycle. The scalar dissipation spectrum was calculated, and by fitting the results to a model turbulent spectrum the Batchelor scale of the turbulent flow was estimated. The scalar inhomogeneity was introduced by a low-momentum gas jet injection. A consistent trend was observed in all data; the Batchelor scale showed a minimum value at top dead center (TDC) and was nearly symmetric about TDC. Increasing the engine speed resulted in a decrease of the Batchelor scale, and the presence of a shroud on the intake valve, which increased the turbulence intensity, also reduced the Batchelor scale. The effect of the shrouded valve was less significant compared to the effect of engine speed.

A procedure has been developed to build system level predictive models that incorporate physical laws as well as information derived from experimental data. In particular a soot model was developed, trained and tested using experimental data. It was seen that the model could fit available experimental data given sufficient training time. Future accuracy on data points not encountered during training was estimated and seen to be good. The approach relies on the physical phenomena predicted by an existing system level phenomenological soot model coupled with ‘weights’ which use experimental data to adjust the predicted physical sub-model parameters to fit the data. This approach has developed from attempts at incorporating physical phenomena into neural networks for predicting emissions. Model training uses neural network training concepts.

Lithium-ion and Lithium polymer batteries are fast becoming ubiquitous in high-discharge rate applications for military and non-military systems. Applications such as small aerial vehicles and energy transfer systems can often function at C-rates greater than 1. To maximize system endurance and battery health, there is a need for models capable of precisely estimating the battery state-of-charge (SoC) under all temperature and loading conditions. However, the ability to perform state estimation consistently and accurately to within 1% error has remained unsolved. Doing so can offer enhanced endurance, safety, reliability, and planning, and additionally, simplify energy management. Therefore, the work presented in this paper aims to study and develop experimentally validated mathematical models capable of high-accuracy battery SoC estimation.