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Co-Optimization of Fuels and Engines initiative (Co-Optima) of the U.S Department of Energy started investigations on several candidates of biofuels and blends for internal combustion engines. At this stage, only a few biomass-derived fuel blendstocks (including ethanol) for advanced spark-ignition engines have been selected using enhanced screening criteria, which included boiling point, toxicity, research octane number, octane sensitivity, and economical distribution system, etc. Ethanol, of which this paper is focused on, is also an important fuel because of its high-octane number which in turn promotes advance ignition timing and higher thermal efficiencies in reciprocating engines. Measurements of laminar burning velocity (LBV) is a key metric to understand fuel performance and applicability in engines. Furthermore, in order to quantify more complicated, and practical, burning regimes such as turbulent combustion much of the underlying theory requires knowledge of LBV.

The biofuel and engine co-development framework was initiated at Sandia National Labs. Here, the synthetic biologists develop and engineer a new platform for drop-in fuel production from lignocellulosic biomass, using several endophytic fungi. Hence this process has the potential advantage that expensive pretreatment and fuel refining stages can be optimized thereby allowing scalability and cost reduction; two major considerations for widespread biofuel utilization. Large concentrations of ketones along with other volatile organic compounds were produced by fungi grown over switchgrass media. The combustion and emission properties of these new large ketones are poorly known.

The 2,4-dimethyl-3-pentanone (DIPK) is a promising biofuel candidate for automotive applications that is produced by the endophytic fungal conversion process which can be optimized for widespread utilization. There are some studies in the literature on combustion properties of DIPK, such as ignition delay times and laminar burning velocity (LBV) measurements. However, most studies are conducted one atmospheric (atm) pressure which are far away from the high-pressure conditions present inside reciprocating engines. Therefore, we present LBV measurements at high pressures up to 10 atm for this fuel using a spherical flame speed facility. It is known that the flame in a constant volume chamber develops cellular structure (hydrodynamic instability) as the initial pressure increases because of the reduction in flame thickness. In addition, the diffusional-thermal instability prevents experiments for rich mixtures because of the reduction of Lewis number (Le).

A gasoline engine with an electronically controlled fuel injection system has substantially better fuel economy and lower emissions than a carburetted engine. In general, the stability of engine operation is improved with fuel injector, but the stability of engine operation at idle is not improved compared with a carburetted gasoline engine. In addition, the increase in time that an engine is at idle due to traffic congestion has an effect on the engine stability and vehicle reliability. Therefore, in this research, we will study the influence of fuel injection timing, spark timing, dwell angle, and air-fuel ratio on engine stability at idle.

This paper reviews the literature which identifies the causes, consequences and cures for engine knock as it affects high performance engines. The physical events of normal and abnormal combustion are described. The observed variations in combustion phenomenon are explained through chemical kinetics. A mathematical model of combustion which can predict knock in an engine cylinder is summarized. Several mechanisms of knock induced damage are outlined. Design and operating considerations which affect an engine's propensity to knock are discussed. Terms that have become associated with combustion in general and the knocking phenomenon in particular are collected and examined

A power electronics module was equipped with an evaporative spray cooling nozzle assembly that served to remove waste heat from the silicon devices. The spray cooling nozzle assembly took the place of the standard heat sink, which uses single phase convection. The purpose of this work was to test the ability of spray cooling to enable higher power density in power electronics with high temperature coolant, and to be an effective and lightweight system level solution to the thermal management needs of aerospace vehicles. The spray cooling work done here was with 95 °C water, and this data is compared to 100 °C water/ propylene glycol spray cooling data from a previous paper so as to compare the spray cooling performance of a single component liquid to that of a binary liquid such as WPG. The module used during this work was a COTS module manufactured by Semikron, Inc., with a maximum DC power input of 180 kW (450 VDC and 400 A).

The application of Statistical Process Control and Design of Experiment methods in the research laboratory can lead to significant gains in the Powertrain development process. Empirical methods such as Design of Experiments, Regression, and Neural Network techniques can be applied to help researchers gain better understanding of the cause and effect relationships of emission, alternative fuel source, performance, fuel economy, and engine management system - calibration studies. The use of these empirical modeling techniques along with model based Genetic Algorithm, Gradient, or Constraint based solution search methods will help identify the “process settings” that improve fuel economy, improve performance, and reduce pollutants. Since empirical methods are fundamentally based on the acquired test data, it is vitally important that the laboratory measurements are repeatable, consistent, and void of sources of variance that have a significant effect on the acquired test data.

Calibrating the engine control unit to satisfy pollutant and performance objectives can be a challenging task. Due to the large number of variables and their interactive complexities, many firms apply design of experiment methods and modeling techniques to the acquired test data. This establishes a “black box” or “gray box” simulation model that predicts power and emissions as a function of the engine parameters. An offline optimization procedure on the fitted model(s) will identify the engine control strategy that best satisfies pollutant and performance objectives. A review of the literature reveals that the General Linear Modeling method and Neural Network modeling architectures are widely used in the development of “black box” or “gray box” simulation models. While Neural Network methods are “assumption free”, the General Linear Model method is limited to those problems in which the errors, ε, are normally distributed and have constant variance, σ2.

Effective thermal management and removal of the waste heat generated at diode arrays is critical to the development of high-power solid-state lasers. Thermal design must be considered in the packaging of these arrays. Two different packages with heat dissipation through spray cooling are evaluated experimentally and numerically. Their overall performance is compared with other packaging configurations using different heat removal approaches. A novel packaging design is proposed that can fulfill the requirements of low thermal resistance, temperature uniformity among emitters in the diode array, low coolant flow rate, simplicity and low assembly cost. The effect of temperature uniformity on the pumping efficiency for gain media is examined for our novel packaging design. The thermal stress induced by temperature variation within an emitter is also considered.

The purpose of this study was to increase IC engine performance by “tuning” the exhaust system to different induction system pressures using an empirical based modeling approach. The two distinct induction pressures are atmospheric and 13-15 mmHg above atmospheric. The above atmospheric induction pressure occurs when the race car is in the lead; the atmospheric pressure occurs with the race car is following the lead or “in the draft.” Since it is ideal to achieve optimum performance for both induction pressures, the problem was formulated and optimized using an empirical Multiple Response Surface Method (MRSM) approach. MRSM is a process that “extracts” multiple objective performance information through carefully controlled experiments and data modeling techniques. An analysis of the experimental data will identify the ideal header length configuration that maximizes performance for both induction pressure extremes.

For aircraft electromechanical actuator (EMA) cooling applications using forced air produced by axial fans, the main objective in fan design is to generate high static pressure head, high volumetric flow rate, and high efficiency over a wide operating range of rotational speed (1x∼3x) and ambient pressure (0.2∼1 atm). In this paper, a fan design based on a fan diameter of 86 mm, fan depth (thickness) of 25.4 mm, and hub diameter of 48 mm is presented. The blade setting angle and the chord lengths at the leading and trailing edges are varied in their suitable ranges to determine the optimal blade profiles. The fan static pressure head, volumetric flow rate, and flow velocity are calculated at various ambient pressures and rotational speeds. The optimal blade design in terms of maximum total-to-total pressure ratio and efficiency at the design point is obtained via CFD simulation. A 5-blade configuration yields the best performance in terms of efficiency and total pressure ratio.

The aircraft electromechanical actuator (EMA) cooling fan is a critical component because an EMA failure caused by overheating could lead to a catastrophic failure in aircraft. Fault tree analysis (FTA) is used to access the failure probability of EMA fans with the goal of improving their mean time to failure (MTTF) from ∼O(5×104) to ∼ O(2.5×109) hours without incurring heavy weight penalty and high cost. The dual-winding and dual-bearing approaches are analyzed and a contra rotating dual-fan design is proposed. Fan motors are assumed to be brushless direct current (BLDC) motors. To have a full understanding of fan reliability, all possible failure mechanisms and failure modes are taken into account. After summarizing the possible failure causes and failure modes of BLDC fans by focusing on each failure mechanism, the life expectancy of fan ball bearings based on a major failure mechanism of lubricant deterioration is calculated and compared to that provided in the literature.

Peak pressure, crank angle and induction pressure were measured in cylinder number one of a Ford 4.6 liter Modular engine. Chaos analysis was conducted on these measurements and the phase, waveform, Poincare, and FFT plots are presented. These plots show conclusively that the pressure fluctuation inside a cylinder is a broadband chaos.

Engine dynamometer testing of homogeneous charge, spark ignition lean burn engines fueled by natural gas, hydrogen/natural gas blends and neat hydrogen was conducted to determine if NOx emissions from blended fuel operation can be reduced below those generated from natural gas operation, approaching those due to a 100% hydrogen fueled engine. The preliminary tests were conducted at the University of Central Florida/Florida Solar Energy Center on an eight cylinder automotive engine. The results indicate that the hydrogen/natural gas fuel has the potential of meeting highly restrictive NOx levels. Sandia National Laboratories conducted follow-on, comparative tests using a single cylinder research engine. The Sandia results indicate that the proposed CARB EZEV standard for NOx can be met without exhaust gas aftertreatment using a 30% hydrogen (by volume) / 70% natural gas blend fuel in a constant speed/power, hybrid vehicle application which achieves 60 MPG gasoline equivalent efficiency.

Optimizing IC engine performance currently requires an exhaustive experimental search to determine the combination of internal components that maximizes torque or power. An alternate and more structured approach using Response Surface Methods will lead the experimenter to the optimum combination with the least number of trials. Using simulation software to evaluate IC engine configurations, this method improved the estimated power from 439 to 516 KW. Results of the study indicate that Response Surface Methods are a viable and robust method of converging to an IC engine configuration which achieves optimum performance.

Preliminary investigations of nonlinear modeling of aircraft synchronous generators using neural networks are presented. Aircraft synchronous generators with high power density tend operate at current-levels proportional to the magnetic saturation region of the machine's material. The nonlinear model accounts for magnetic saturation of the generator, which causes the winding flux linkages and inductances to vary as a function of current. Finite element method software is used to perform a parametric sweep of direct, quadrature, and field currents to extract the respective flux linkages. This data is used to train a neural network which yields current as a function of flux linkage. The neural network is implemented in a Simulink synchronous generator model and simulation results are compared with a previously developed linear model. Results show that the nonlinear neural network model can more accurately describe the responsiveness and performance of the synchronous generator.

This paper describes the development of a distributed environment for spaceport simulation modeling. This distributed environment is the result of the applications of the High-Level Architecture (HLA) and integration frameworks based on software agents and XML. This distributed environment is called the Virtual Test Bed (VTB). A distributed environment is needed due to the nature of the different models needed to represent a spaceport. This paper provides two case studies: one related to the translation of a model from its native environment and the other one related to the integration of real-time weather.

In this paper, we introduce the use of ontologies to implement the information developed and organized by resource planning tools into standard project management documents covering integrated cost, resource modeling and analysis, and visualization. The basic upper ontology used for NASA Space Operations is explained and the results obtained are discussed. This ontology-centered approach is looking for tighter connections between software, hardware, and systems engineering.

In planning, simulation models create microcosms, small universes that operate based on assumed principles. While this can be powerful, the information it can provide is limited by the assumptions made and the designed operation of the model. When performing schedule planning and analysis, modelers are often provided with timelines representing project tasks, their relationships, and estimates related to durations, resource requirements, etc. These timelines can be created with programs such as Microsoft Excel or Microsoft Project. There are several important attributes these timelines have; they represent a nominal flow (meaning they do not represent stochastic processes), and they are not necessarily governed by dates or subjected to a calendar. Attributes such as these become important in project planning since timelines often serve as the basis for creating schedules.

The making of a quilt is an interesting process. Historically, a quilt is a canvas of work made from old pieces of cloth cut into squares or whatever shape that make a nice connected pattern and then stitched together. The quilt could be random pieces that is not related to each other. In most recent years and more common cases, a quilt is made of different pieces of patches that are connected and laid out in a special way to tell a story. Not only does it portray a story that is put together in a certain sequence, but it also stiches the pieces of the quilt into a nice and complete narrative. A story that one can understand just by looking at the quilt spread and unfolded. Much like the making of a quilt that has a story to tell, a Product Digital Quilt will tell the story of a product. The Digital Product Quilt replaces the conventional way of telling a product story. The traditional product story is a method that is serially connecting multiple product life cycle silos together.