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In a recent study, quantitative measurements were presented of in-cylinder spatial distributions of mixture equivalence ratio in a single-cylinder light-duty optical diesel engine, operated with a non-reactive mixture at conditions similar to an early injection low-temperature combustion mode. In the experiments a planar laser-induced fluorescence (PLIF) methodology was used to obtain local mixture equivalence ratio values based on a diesel fuel surrogate (75% n-heptane, 25% iso-octane), with a small fraction of toluene as fluorescing tracer (0.5% by mass). Significant changes in the mixture's structure and composition at the walls were observed due to increased charge motion at high swirl and injection pressure levels. This suggested a non-negligible impact on wall heat transfer and, ultimately, on efficiency and engine-out emissions.

A system was developed which provides nutrients and water to plants while maintaining good aeration at the roots and preventing water from escaping in reduced gravity. The nutrient solution is circulated through porous tubes under negative pressure and moves through the tube wall via capillary forces into the rooting matrix, establishing a non-saturated condition in the root zone. Tests using prototypes of the porous tube water and nutrient delivery system indicate that plant productivity in this system is equivalent to standard soil and solution culture growing procedures. The system has functioned successfully in short-term microgravity during parabolic flight tests and will be flown on the space shuttle. Plants are one of the components of a bioregenerative life support system required for long duration space missions.

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.

The objective of this study was to investigate the effects of fuel viscosity and the effects of nozzle inlet configuration on the characteristics of high injection pressure sprays. Three different viscosity fuels were used to reveal the effects of viscosity on the spray characteristics. The effects of nozzle inlet configuration on spray characteristics were studied using two mini-sac six-hole nozzles with different inlet configurations. A common rail injection system was used to introduce the spray at 90 MPa injection pressure into a constant volume chamber pressurized with argon gas. The information on high pressure transient sprays was captured by a high speed movie camera synchronized with a pulsed copper vapor laser. The images were analyzed to obtain the spray characteristics which include spray tip penetration, spray cone angle at two different regions, and overall spray Sauter Mean Diameter (SMD).

A transport equation residual model incorporating refined G-equation and detailed chemical kinetics combustion models has been developed and implemented in the ERC KIVA-3V release2 code for Gasoline Direct Injection (GDI) engine simulations for better predictions of flame propagation. In the transport equation residual model a fictitious species concept is introduced to account for the residual gases in the cylinder, which have a great effect on the laminar flame speed. The residual gases include CO2, H2O and N2 remaining from the previous engine cycle or introduced using EGR. This pseudo species is described by a transport equation. The transport equation residual model differentiates between CO2 and H2O from the previous engine cycle or EGR and that which is from the combustion products of the current engine cycle.

Identifying edge cases for designed algorithms is critical for functional safety in autonomous driving deployment. In order to find the feasible boundary of designed algorithms, simulations are heavily used. However, simulations for autonomous driving validation are expensive due to the requirement of visual rendering, physical simulation, and AI agents. In this case, common sampling techniques, such as Monte Carlo Sampling, become computationally expensive due to their sample inefficiency. To improve sample efficiency and minimize the number of simulations, we propose a tailored active learning approach combining the Support Vector Machine (SVM) and the Gaussian Process Regressor (GPR). The SVM learns the feasible boundary iteratively with a new sampling point via active learning. Active Learning is achieved by using the information of the decision boundary of the current SVM and the uncertainty metric calculated by the GPR.

The simulation of combustion chemistry in internal combustion engines is challenging due to the need to include detailed reaction mechanisms to describe the engine physics. Computational times needed for coupling full chemistry to CFD simulations are still too computationally demanding, even when distributed computer systems are exploited. For these reasons the present paper proposes a time scale separation approach for the integration of the chemistry differential equations and applies it in an engine CFD code. The time scale separation is achieved through the estimation of a characteristic time for each of the species and the introduction of a sampling timestep, wherein the chemistry is subcycled during the overall integration. This allows explicit integration of the system to be carried out, and the step size is governed by tolerance requirements.

Despite numerous research efforts, there is no reliable and widely accepted tool for the prediction of erosion prone material surfaces due to collapse of cavitation bubbles. In the present paper an Erosion Aggressiveness Index (EAI) is proposed, based on the pressure loads which develop on the material surface and the material yield stress. EAI depends on parameters of the liquid quality and includes the fourth power of the maximum bubble radius and the bubble size number density distribution. Both the newly proposed EAI and the Cavitation Aggressiveness Index (CAI), which has been previously proposed by the authors based on the total derivative of pressure at locations of bubble collapse (DP/Dt>0, Dα/Dt<0), are computed for a cavitating flow orifice, for which experimental and numerical results on material erosion have been published. The predicted surface area prone to cavitation damage, as shown by the CAI and EAI indexes, is correlated with the experiments.

Today’s business climate and economy demand new, innovative strategies from the initial kickoff of research and development - to the mining of ore from the earth - to the final inspection of a finished product in a mid-western factory. From startup companies with two employees to the largest companies, the world faces new and challenging requirements every day. The demands from companies, customers, executives, and shareholders continue to drive for higher outputs with more efficient use of personnel and investments. Fortunately, the rate of technology continues to exponentially accelerate, which allows those at the cutting edge of technology to capitalize. Caterpillar has been a pioneer in advanced technology since its inception and has been developing the foundation for autonomy over the past four decades.

Airflow characteristics surrounding non-evaporating transient diesel sprays were investigated using a 6-hole injector. Particle Image Velocimetry (PIV) was used to measure the gas velocities surrounding a spray plume as a function of space and time. A hydraulically actuated, electronically controlled unit injector (HEUI) system was used to supply the fuel into a pressurized constant volume chamber at room temperature. The chamber gas densities in this study were 10 kg/m3, 20 kg/m3 and 30 kg/m3. The injection pressure was 96.5 MPa. Two frequency doubled (532 nm) Nd:YAG lasers were used to create coincident laser sheets to illuminate the test section at two instances after start of injection (ASI). The double exposed images of sprays and Al2O3 seed particles were developed and velocity vectors of the gas surrounding the transient diesel sprays were obtained using a numerical autocorrelation PIV method.

Two distinct atomization strategies are contrasted through the measurement of time and spatially dependent mass flux. The two systems investigated include a pressure atomizer (6.9 MPa opening pressure) and an air-assist atomizer. Both systems have potential for use in direct injection spark ignition engines. The mass flux data presented were obtained using a spray patternator that was developed to allow phased sampling of the spray. The temporal mass related history of the spray was reconstructed as volume versus time plots and interpolated mass flux contour plots. Results indicate substantial differences in the distribution of both mass and mass flux in space and time for the two injection systems. For example, the pressure atomizer at high mass delivery rates produced a spray that collapsed into a dispersed cylindrical shape while at low rates, generated a hollow cone structure.

This paper presents the results of an experimental program in which a Texaco L-163S engine was fueled with methanol and operated in its traditional stratified charge mode and then modified to run as a homogeneous charge spark ignited engine. The primary data taken were the aldehyde and unburned fuel emissions (UBF). These data were taken using a continuous time-averaging sampling probe at the exhaust tank and at the exhaust port and with a rotary time-resolving sampling valve located at the exhaust port. The data are for two loads, 138.1 kPa (20 psi) and 207.1 kPa (30 psi) BMEP and three speeds, 1000, 1400 and 1800 rpm. The data indicate that for both the stratified charge and the homogeneous charge modes of operation formaldehyde was the only aldehyde detected in the exhaust and it primarily originated in the cylinder.

The adaptation to changes in human operator dynamics and changes in working environment dynamics can be an important issue in designing high performance telerobotic systems. This paper describes an approach to force control in telerobotic hand systems in which model reference adaptive control techniques are used to adapt to changes in human operator and working environment dynamics. The techniques have been applied to force-reflective control of a single degree-of-freedom telerobotic gripper system at Wisconsin Center for Space Automation and Robotics (WCSAR). This adaptive gripping system is described in the paper along with results of experiments with human subjects in which the performance of the adaptive system was analysed and compared to the performance of a conventional non-adaptive system. These experiments emphasized adaptation to changes in compliance of gripped objects and adaptation to the on-set of human operator fatigue.

This paper identifies potential performance benefits and computational costs of applying advanced multivariable control theory concepts to coordinate the control of a general multi-degree-of-freedom fuel system. The control variables are injection duration and pressure. The focus is on the design of a robust multi-input multi-output controller using H-infinity and mu synthesis methodology to coordinate the control of injection duration and pressure; reduce overshoots and system sensitivity to parameter variations caused by component aging. Model reduction techniques are used to reduce the order of the H-infinity controller to make it practically implementable. Computer simulation is used to test the robust performance of a generic engine and fuel system model controlled by the reduced order H-infinity controller and a traditional proportional plus integral controller.

With stringent emission regulations, many subsystems that abate engine tailpipe-out emissions become a necessary part for engines. The increased level of complexity poses technical challenges for the quality and reliability for modern engines. Among the spectrum of quality control methodologies, one conventional methodology focuses on every component's quality to ensure that the accumulative deviation is within predetermined limits. This conventional methodology tightens the component tolerance during the manufacturing process and typically results in increased cost. Another conventional methodology that is on the other side of the spectrum focuses on tailoring an engine calibration solution to offset the manufacturing differences. Although the tailored engine calibration solution reduces manufacturing cost for components, it increases the development and validation cost for engines. Given the cost and time constraints, system integration plays an important role in engine development.

Three distinct types of diesel particulate matter (PM) are generated in selected engine operating conditions of a single-cylinder heavy-duty diesel engine. The three types of PM are trapped using typical Cordierite diesel particulate filters (DPF) with different washcoat formulations and a commercial Silicon-Carbide DPF. Two systems, an external electric furnace and an in-situ burner, were used for regeneration. Furnace regeneration experiments allow the collected PM to be classified into two categories depending on oxidation mechanism: PM that is affected by the catalyst and PM that is oxidized by a purely thermal mechanism. The two PM categories prove to contribute differently to pressure drop and transient filtration efficiency during in-situ regeneration.

An experimental study was performed to investigate diesel particulate filter (DPF) performance during filtration with the use of real-time measurement equipment. Three operating conditions of a single-cylinder 2.3-liter D.I. heavy-duty diesel engine were selected to generate distinct types of diesel particulate matter (PM) in terms of chemical composition, concentration, and size distribution. Four substrates, with a range of geometric and physical parameters, were studied to observe the effect on filtration characteristics. Real-time filtration performance indicators such as pressure drop and filtration efficiency were investigated using real-time PM size distribution and a mass analyzer. Types of filtration efficiency included: mass-based, number-based, and fractional (based on particle diameter). In addition, time integrated measurements were taken with a Rupprecht & Patashnick Tapered Element Oscillating Microbalance (TEOM), Teflon and quartz filters.

Diesel particulate filters are designed to reduce the mass emissions of diesel particulate matter and have been proven to be effective in this respect. Not much is known, however, about their effects on other unregulated chemical species. This study utilized source dilution sampling techniques to evaluate the effects of a catalyzed diesel particulate filter on a wide spectrum of chemical emissions from a heavy-duty diesel engine. The species analyzed included both criteria and unregulated compounds such as particulate matter (PM), carbon monoxide (CO), hydrocarbons (HC), inorganic ions, trace metallic compounds, elemental and organic carbon (EC and OC), polycyclic aromatic hydrocarbons (PAHs), and other organic compounds. Results showed a significant reduction for the emissions of PM mass, CO, HC, metals, EC, OC, and PAHs.

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.

Diesel exhaust particulate trap system is one of the most effective means to control diesel particulate emissions from diesel vehicles. In this paper, a recently developed diesel exhaust particulate trap system was described and experimentally studied. This system employed a wall-flow ceramic foam filter, which was made of silicon carbide or chromium oxide. And this system was equipped with a microwave heater for the purpose of filter regeneration. Engine dynamometer testing, vehicle bench testing and on-road evaluation of this system were conducted. The experiments studied on the filtration efficiency of this system, the effectiveness of filter regeneration, the power penalty of the vehicle, the ability of noise suppression of this system, and the durability of this particulate trap system. The experimental results showed that this diesel particulate trap system was effective, reliable, and durable.