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Φ-sensitivity is a fuel characteristic that has important benefits for the operation and control of low-temperature gasoline combustion (LTGC) engines. A fuel is φ-sensitive if its autoignition reactivity varies with the fuel/air equivalence ratio (φ). Thus, multiple-injection strategies can be used to create a φ-distribution that leads to several benefits. First, the φ-distribution causes a sequential autoignition that reduces the maximum heat release rate. This allows higher loads without knock and/or advanced combustion timing for higher efficiencies. Second, combustion phasing can be controlled by adjusting the fuel-injection strategy. Finally, experiments show that intermediate-temperature heat release (ITHR) increases with φ-sensitivity, increasing the allowable combustion retard and improving stability. A detailed mechanism was applied using CHEMKIN to understand the chemistry responsible for φ-sensitivity.

All around the world, steps are being taken to improve the quality of our environment. Prominent among these are the definition, implementation, and attainment of increasingly stringent emissions regulations for all types of engines, including off-highway diesels. These rigorous regulations have driven use of technologies like after-treatment, advanced air systems, and advanced fuel systems. Fuel dispensed off-highway is routinely and significantly dirtier than fuel from on-highway outlets. Furthermore, fuels used in developing countries can be up to 30 times dirtier than the average fuels in North America. Poor fuel cleanliness, coupled with the higher pressures and performance demands of modern fuel systems, create life challenges greater than encountered with cleaner fuels. This can result in costly disruption of operations, loss of productivity, and customer dissatisfaction in the off-highway market.

This paper covers the development of computer simulation models of the Vapor Compression Distillation (VCD) process, the Super Critical Water Oxidation (SCWO) process, and two versions of a Vapor Phase Catalytic Ammonia Reduction (VPCAR) process. These process level models have combined into two Integrated Water Reclamation Systems (IWRS). Results from these integrated models, in conjunction with other data sources, have been used to develop a preliminary comparison of the two systems. Also discussed in this paper is the development of a Vapor Phase Catalytic Ammonia Reduction teststand and the development of a new urine analog for use with the teststand and computer models.

Since the mid 1980s, NASA has developed advanced waste management technologies that collect and process waste. These technologies include incineration, hydrothermal oxidation, pyrolysis, electrochemical oxidation, activated carbon production, brine dewatering, slurry bioreactor oxidation, composting, NOx control, compaction, and waste collection. Some of these technologies recover resources such as water, oxygen, nitrogen, carbon dioxide, carbon, fuels, and nutrients. Other technologies such as the Waste Collection System (WCS - the commode) collect waste for storage or processing. The need for waste processing varies greatly depending upon the mission scenario. This paper reviews the waste management technology development activities conducted by NASA since the mid 1980s and explores the drivers that determine the application of these technologies to future missions.

For the last two years, the University of Utah and Reaction Engineering International, in cooperation with NASA Ames Research Center (ARC), have been developing a waste incineration system for regenerative life support systems. The system is designed to burn inedible plant biomass and human waste. The goal is to obtain an exhaust gas clean enough to recycle to either the plant or human habitats. The incineration system, a fluidized bed reactor, has been designed for a 4-person mission. This paper will detail the design of the units. In addition, results will be presented from testing at the University of Utah. Presently, the unit has been shipped to Ames Research Center for more tests prior to delivery to Johnson Space Center for testing in a 90-day, 4-person test.

Waste management is a critical component of life support systems for manned space exploration. Human occupied spacecraft and extraterrestrial habitats must be able to effectively manage the waste generated throughout the entire mission duration. The requirements for waste systems may vary according to specific mission scenarios but all waste management operations must allow for the effective collection, containment, processing, and storage of unwanted materials. NASA's Crew Exploration Vehicle usually referred to as the CEV, will have limited volume for equipment and crew. Technologies that reduce waste storage volume free up valuable space for other equipment. Waste storage volume is a major driver for the Orion waste compactor design. Current efforts at NASA Ames Research Center involve the development of two different prototype compactors designed to minimize trash storage space.

In recent years, Nearfield Acoustical Holography (NAH) has been used to identify stationary vehicle exterior noise sources. However that application has usually been limited to individual components. Since powertrain noise sources are hidden within the engine compartment, it is difficult to use NAH to identify those sources and the associated partial field that combine to create the complete exterior noise field of a motor vehicle. Integrated Nearfield Acoustical Holography (INAH) has been developed to address these concerns: it is described here. The procedure entails sensing the sources inside the engine compartment by using an array of reference microphones, and then calculating the associated partial radiation fields by using NAH. In the second part of this paper, the use of farfield arrays is considered. Several array techniques have previously been applied to identify noise sources on moving vehicles.

We investigate the mixing, penetration, and ignition characteristics of high-pressure n-dodecane sprays having a split injection schedule (0.5/0.5 dwell/0.5 ms) in a pre-burn combustion vessel at ambient temperatures of 750 K, 800 K and 900 K. High-speed imaging techniques provide a time-resolved measure of vapor penetration and the timing and progression of the first- and second-stage ignition events. Simultaneous single-shot planar laser-induced fluorescence (PLIF) imaging identifies the timing and location where formaldehyde (CH2O) is produced from first-stage ignition and consumed following second-stage ignition. At the 900-K condition, the second injection penetrates into high-temperature combustion products remaining in the near-nozzle region from the first injection. Consequently, the ignition delay for the second injection is shorter than that of the first injection (by a factor of two) and the second injection ignites at a more upstream location near the liquid length.

Shadowgraph/schlieren imaging techniques have often been used for flow visualization of reacting and non-reacting systems. In this paper we show that high-speed shadowgraph visualization in a high-pressure chamber can also be used to identify cool-flame and high-temperature combustion regions of diesel sprays, thereby providing insight into the time sequence of diesel ignition and combustion. When coupled to simultaneous high-speed Mie-scatter imaging, chemiluminescence imaging, pressure measurement, and spatially-integrated jet luminosity measurements by photodiode, the shadowgraph visualization provides further information about spray penetration after vaporization, spatial location of ignition and high-temperature combustion, and inactive combustion regions where problematic unburned hydrocarbons exist. Examples of the joint application of high-speed diagnostics include transient non-reacting and reacting injections, as well as multiple injections.

In the last years the number of electronic controllers of vehicle dynamics applied to chassis components has increased dramatically. They use lookup table of the primary order vehicle global parameters as yaw rate, lateral acceleration, steering angle, car velocity, that define the ideal behavior of the vehicle. They are usually based on PID controllers which compare the actual behavior of every measured real vehicle data to the desired behavior, from look up table. The controller attempts to keep the measured quantities the same as the tabled quantities by using ESP, TC (brakes and throttle), CDC (control shocks absorbers), EDIFF(active differential) and 4WS (rear wheels active toe). The performances of these controls are good but not perfect. The improvement can be achieved by replacement of the lookup tables with a fast vehicle model running in parallel to the real vehicle.

This paper discusses the development of a Vapor Phase Catalytic Ammonia Reduction (VPCAR) teststand and the results of an experimental program designed to evaluate the potential of the technology as a water purification process. In the experimental program the technology is evaluated based upon product water purity, water recovery rate, and power consumption. The experimental work demonstrates that the technology produces high purity product water and attains high water recovery rates at a relatively high specific power consumption. The experimental program was conducted in 3 phases. In phase I an Igepon™ soap and water mixture was used to evaluate the performance of an innovative Wiped-Film Rotating-Disk evaporator and associated demister. In phase II a phenol-water solution was used to evaluate the performance of the high temperature catalytic oxidation reactor.

A generalized re-normalization group (RNG) turbulence model based on the local "dimensionality" of the flow field is proposed. In this modeling approach the model coefficients C₁, C₂, and C₃ are all constructed as functions of flow strain rate. In order to further validate the proposed turbulence model, the generalized RNG closure model was applied to model the backward facing step flow (a classic test case for turbulence models). The results indicated that the modeling of C₂ in the generalized RNG closure model is reasonable, and furthermore, the predictions of the generalized RNG model were in better agreement with experimental data than the standard RNG turbulence model. As a second step, the performance of the generalized RNG closure was investigated for a complex engine flow.

Diesel engine combustion is simulated using Large Eddy Simulation (LES) with a multi-mode combustion (MMC) model. The MMC model is based on the combination of chemical kinetics, chemical equilibrium, and quasi-steady flamelet calculations in different local combustion regimes. The local combustion regime is identified by two combustion indices based on the local temperature and the extent of mixture homogeneity. The LES turbulence model uses the dynamic structure model (DSM) for sub-grid stresses. A new spray model in the LES context is used, and the Reynolds-averaged Navier-Stokes (RANS) based wall model is retained with the LES derived scales. These models are incorporated in the KIVA3V-ERC-Release 2 code for engine combustion simulations. A wide range of diesel engine operating conditions were chosen to validate the combustion model.

In the last few years, the effect of diabatic test conditions on compressor performance maps has been widely investigated, leading some Authors to propose different correction models. The accuracy of turbocharger performance map constitute the basis for the tuning and validation of a numerical method, usually adopted for the prediction of engine-turbocharger matching. Actually, it is common practice in automotive applications to use simulation codes, which can either require measured compression ratio and efficiency maps as input values or calculate them “on the fly” throughout specific sub-models integrated in the numerical procedures. Therefore, the ability to correct the measured performance maps taking into account internal heat transfer would allow the implementation of commercial simulation codes used for engine-turbocharger matching calculations.

Detailed and fast combustion models are necessary to support design of Diesel engines with low emission and fuel consumption. Over the years, the importance of turbulence chemistry interaction to correctly describe the diffusion flame structure was demonstrated by a detailed assessment with optical data from constant-volume vessel experiments. The main objective of this work is to carry out an extensive validation of two different combustion models which are suitable for the simulation of Diesel engine combustion. The first one is the Representative Interactive Flamelet model (RIF) employing direct chemistry integration. A single flamelet formulation is generally used to reduce the computational time but this aspect limits the capability to reproduce the flame stabilization process. To overcome such limitation, a second model called tabulated flamelet progress variable (TFPV) is tested in this work.

Remotely operating complex robotic mechanisms in unstructured natural environments is difficult at best. When the communications time delay is large, as for a Mars exploration rover operated from Earth, the difficulties become enormous. Conventional approaches, such as rate control of the rover actuators, are too inefficient and risky. The Intelligent Mechanisms Laboratory at the NASA Ames Research Center has developed over the past four years an architecture for operating science exploration robots in the presence of large communications time delays. The operator interface of this system is called the Virtual Environment Vehicle Interface (VEVI), and draws heavily on Virtual Environment (or Virtual Reality) technology. This paper describes the current operational version of VEVI, which we refer to as version 2.0. In this paper we will describe the VEVI design philosophy and implementation, and will describe some past examples of its use in field science exploration missions.

The development of virtual environment technology at NASA Ames Research Center and other research institutions has created opportunities for enhancing human performance. The application of this technology to training astronaut flight crews planning to go onboard the International Space Station has already begun at the NASA Johnson Space Center. A unique application of virtual environments to crew training is envisioned at NASA Ames Research Center which combines state of the art technology with haptic feedback to create a method for training crewmembers on critical life sciences operations which require fine motor skills. This paper describes such a concept, known as the Virtual Glovebox, as well as surveys other applications of virtual environments to astronaut crew training.

A full calibration exercise of a diesel engine air path can take months to complete (depending on the number of variables). Model-based calibration approach can speed up the calibration process significantly. This paper discusses the overall calibration process of the air-path of the Cat® C7.1 engine using statistical machine learning tool. The standard Cat® C7.1 engine's twin-stage turbocharger was replaced by a VTG (Variable Turbine Geometry) as part of an evaluation of a novel air system. The changes made to the air-path system required a recalculation of the air path's boost set point and desired EGR set point maps. Statistical learning processes provided a firm basis to model and optimize the air path set point maps and allowed a healthy balance to be struck between the resources required for the exercise and the resulting data quality.

Previous research has shown that the homogeneous charge compression ignition (HCCI) combustion concept holds promise for reducing pollutants (i.e. NOx, soot) while maintaining high thermal efficiency. However, it can be difficult to control the operation of the HCCI engines even under steady state running conditions. Power density may also be limited if high inlet air temperatures are used for achieving ignition. A methodology using a small pilot quantity of diesel fuel injected during the compression stroke to improve the power density and operation control is considered in this paper. Multidimensional computations were carried out for an HCCI engine based on a CAT3401 engine. The computations show that the required initial temperature for ignition is reduced by about 70 K for the cases of the diesel pilot charge and a 25∼35% percent increase in power density was found for those cases without adversely impacting the NOx emissions.

Carefully controlled intake valve deposit (IVD) cleanup testing is found to be an effective method for differentiating the effect of the deposit control additives on combustion chamber deposits (CCD). The IVD buildup procedure produces a consistent initial level of CCD that the cleanup additive, the additive of interest, continues to build on until the end of the cleanup test. This “end of cleanup” CCD is found to be as repeatable and differentiable a measurement as tests run under the more common “keep clean” type operation. While IVD cleanup testing induces a mid-test disturbance in the form of the end of buildup measurement, it aligns well with two key CCD protocols in terms of the higher additive treat rates used and the extended total test length. In an analysis of results from IVD cleanup tests run using four different engine/vehicle procedures on seven different additives, several findings stood out.