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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.

In order to provide effective cooling for astronauts during extravehicular activities (EVAs), a liquid cooling and ventilation garment (LCVG) is used to remove heat by a series of tubes through which cooling water is circulated. To better predict the effectiveness of the LCVG and determine possible modifications to improve performance, computer simulations dealing with the interaction of the cooling garment with the human body have been run using the Wissler Human Thermal Model. Simulations have been conducted to predict the heat removal rate for various liquid cooled garment configurations. The current LCVG uses 48 cooling tubes woven into a fabric with cooling water flowing through the tubes. The purpose of the current project is to decrease the overall weight of the LCVG system. In order to achieve this weight reduction, advances in the garment heat removal rates need to be obtained.

Spacecraft radiators reject heat to their surroundings. Radiators can be deployable or mounted on the body of the spacecraft. NASA's Crew Exploration Vehicle is to use body mounted radiators. Coatings play an important role in heat rejection. The coatings provide the radiator surface with the desired optical properties of low solar absorptance and high infrared emittance. These specialized surfaces are applied to the radiator panel in a number of ways, including conventional spraying, plasma spraying, or as an appliqué. Not specifically designed for a weathering environment, little is known about the durability of conventional paints, coatings, and appliqués upon exposure to weathering and subsequent exposure to solar wind and ultraviolet radiation exposure. In addition to maintaining their desired optical properties, the coatings must also continue to adhere to the underlying radiator panel.

As connected and automated vehicle technologies emerge and proliferate, lower frequency vehicle trajectory data is becoming more widely available. In some cases, entire fleets are streaming position, speed, and telemetry at sample rates of less than 10 seconds. This presents opportunities to apply powertrain simulators such as the National Renewable Energy Laboratory’s Future Automotive Systems Technology Simulator to model how advanced powertrain technologies would perform in the real world. However, connected vehicle data tends to be available at lower temporal frequencies than the 1-10 Hz trajectories that have typically been used for powertrain simulation. Higher frequency data, typically used for simulation, is costly to collect and store and therefore is often limited in density and geography. This paper explores the suitability of lower frequency, high availability, connected vehicle data for detailed powertrain simulation.

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.

One way to increase the load range in an HCCI engine is to increase boost pressure. In this modeling study, we investigate the effect of increased boost pressure on the fuel chemistry in an HCCI engine. Computed results of HCCI combustion are compared to experimental results in a HCCI engine. We examine the influence of boost pressure using a number of different detailed chemical kinetic models - representing both pure compounds (methylcyclohexane, cyclohexane, iso-octane and n-heptane) and multi-component models (primary reference fuel model and gasoline surrogate fuel model). We examine how the model predictions are altered by increased fueling, as well as reaction rate variation, and the inclusion of residuals in our calculations. In this study, we probe the low temperature chemistry (LTC) region and examine the chemistry responsible for the low-temperature heat release (LTHR) for wide ranges of intake boost pressure.

The combined anticipated trends of vehicle sharing (ride-hailing), automated control, and powertrain electrification are poised to disrupt the current paradigm of predominately owner-driven gasoline vehicles with low levels of utilization. Shared, automated, electric vehicle (SAEV) fleets offer the potential for lower cost and emissions and have garnered significant interest among the research community. While promising, unmanaged operation of these fleets may lead to unintended negative consequences. One potentially unintended consequence is a high quantity of SAEVs charging during peak demand hours on the electric grid, potentially increasing the required generation capacity. This research explores the flexibility associated with charging loads demanded by SAEV fleets in response to servicing personal mobility travel demands. Travel demand is synthesized in four major United States metropolitan areas: Detroit, MI; Austin, TX; Washington, DC; and Miami, FL.

This paper introduces and develops the concept of “Type X” and “Type Y” errors in model validation and calibration, and their implications on extrapolative prediction. Type X error is non-detection of model bias because it is effectively hidden by the uncertainty in the experiments. Possible deleterious effects of Type X error can be avoided by mapping uncertainty into the model until it envelopes the potential model bias, but this likely assigns a larger uncertainty than is needed to account for the actual bias (Type Y error). A philosophy of Best Estimate + Uncertainty modeling and prediction is probably best supported by taking the conservative choice of guarding against Type X error while accepting the downside of incurring Type Y error. An associated methodology involving data- and model- conditioning is presented and tested on a simple but rich test problem.

Laser excitation wavelengths for two-line planar laser-induced fluorescence (PLIF) of 3-pentanone have been optimized for simultaneous imaging of temperature and composition under engine-relevant conditions. Validation of the diagnostic was performed in a motored optical IC engine seeded homogeneously with 3-pentanone. PLIF measurements of the uniform mixture during the compression stroke were used to measure the average temperature and to access the random uncertainty in the measurements. To determine the accuracy of the temperature measurements, experimental average temperatures were compared to values computed assuming isentropic compression and to the output of a tuned 1-D engine simulation. The comparison indicated that the absolute accuracy of the temperature measurements is better than ±5%. Probability density functions (PDFs) calculated from the single-shot images were used to estimate the precision of the measurements.

Transients in the rate of injection (ROI) with respect to time are ever-present in direct-injection engines, even with common-rail fueling. The shape of the injection ramp-up and ramp-down affects spray penetration and mixing, particularly with multiple-injection schedules currently in practice. Ultimately, the accuracy of CFD model predictions used to optimize the combustion process depends upon the accuracy of the ROI utilized as fuel input boundary conditions. But experimental difficulties in the measurement of ROI, as well as real-world affects that change the ROI from the bench to the engine, add uncertainty that may be mistaken for weaknesses in spray modeling instead of errors in boundary conditions. In this work we use detailed, time-resolved measurements of penetration at the Spray A conditions of the Engine Combustion Network to rigorously guide the necessary ROI shape required to match penetration in jet models that allow variable rate of injection.

Diesel low-temperature combustion strategies often rely on early injection timing to allow sufficient fuel-ambient mixing to avoid NOx and soot-forming combustion. However, these early injection timings permit the spray to penetrate into a low ambient temperature and density environment where vaporization is poor and liquid impingement upon the cylinder liner and piston bowl are more likely to occur. The objective of this study is to measure the transient liquid and vapor penetration at early-injection conditions. High-speed Mie-scatter and shadowgraph imaging are employed in an optically accessible chamber with a free path of 100 mm prior to wall impingement and using a single-spray injector. The ambient temperature and density within the chamber are well-controlled (uniform) and selected to simulate in-cylinder conditions when injection occurs at -40 crank-angle degrees (CAD) or fewer before top-dead center (TDC).

An accurate prediction of internal nozzle flow in fuel injector offers the potential to improve predictions of spray computational fluid dynamics (CFD) in an engine, providing a coupled internal-external calculation or by defining better rate of injection (ROI) profile and spray angle information for Lagrangian parcel computations. Previous research has addressed experiments and computations in transparent nozzles, but less is known about realistic multi-hole diesel injectors compared to single axial-hole fuel injectors. In this study, the transient injector opening and closing is characterized using a transparent multi-hole diesel injector, and compared to that of a single axial hole nozzle (ECN Spray D shape). A real-size five-hole acrylic transparent nozzle was mounted in a high-pressure, constant-flow chamber. Internal nozzle phenomena such as cavitation and gas exchange were visualized by high-speed long-distance microscopy.

Development of a second generation Electronic Nose at JPL is focusing on optimization of the sensing films to increase sensitivity and optimization of the array. Toward this goal, studies have focused on sources of noise in the films, alternatives to carbon black as conductive medium, measurement techniques, and development of an analytical approach to polymer selection to maximize the abilities of the array to distinguish among compounds.

Several configurations of truck tractor sleeper cabs were tested and modeled to investigate the potential to reduce heating and cooling loads. Two trucks were tested outdoors and a third was used as a control. Data from the testing were used to validate a computational fluid dynamics (CFD) model and this model was used to predict reductions in cooling loads during daytime rest periods. The test configurations included the application of standard-equipped sleeper privacy curtain and window shades, an optional insulated or arctic sleeper curtain, and insulated window coverings. The standard curtain reduced sleeper area heating load by 21% in one test truck, while the arctic curtain decreased it by 26%. Insulated window coverings reduced the heating load by 16% in the other test truck and lowered daytime solar temperature gain by 8°C. The lowered temperature resulted in a predicted 34% reduction in cooling load from the model.

Increased market penetration of electric drive vehicles (EDVs) requires overcoming a number of hurdles, including limited vehicle range and the elevated cost in comparison to conventional vehicles. Climate control loads have a significant impact on range, cutting it by over 50% in both cooling and heating conditions. To minimize the impact of climate control on EDV range, the National Renewable Energy Laboratory has partnered with Hyundai America and key industry partners to quantify the performance of thermal load reduction technologies on a Hyundai Sonata plug-in hybrid electric vehicle. Technologies that impact vehicle cabin heating in cold weather conditions and cabin cooling in warm weather conditions were evaluated. Tests included thermal transient and steady-state periods for all technologies, including the development of a new test methodology to evaluate the performance of occupant thermal conditioning.

A transient thermal analysis of a Carbon/Carbon (C/C) Mars Entry Non-Ablative Aeroshell Assembly was performed to determine the maximum temperatures it would reach during a Mars entry. The purpose of this thermal analyses was to (1) determine the maximum temperatures of the 5 layers and the close-out which make up the aerothermal shield and (2) to transmit these temperatures from SINDA/G finite difference format to finite element format in COSMOS/M structures/dynamic models using Technical Alliance Group (TAG) developed SINDA/ G temperature translator software (STT).

This is Part 3 of a development program to evaluate candidate nonablative aeroshell designs. The primary goal of this C/C aeroshell development task was to demonstrate the feasibility and performance of a lightweight C/C non-ablative aeroshell design that integrates advanced C/C materials and structural configurations. The thermal performance was evaluated by Arc Jet testing at NASA Ames of representative structural models. In this phase of the program, new carbon-carbon materials and structural core designs were evaluated, as well as an alternative aerogel material. The test models were composed of a quasi-isotropic Carbon/Carbon(C/C) front face sheet (F/S), eggcrate or honeycomb core, C/C back F/S, Carbon and resorcinol-formaldehyde aerogel insulation. Part One of this work [1] demonstrated the feasibility through arc-jet testing and Part Two [2] included analytical modeling of the test geometry to validate the design.

Candidate Aeroshell Test models composed of a quasi-isotropic Carbon/Carbon(C/C) front face sheet (F/S), eggcrate core, C/C back F/S, Carbon Aerogel insulation, C/C radiation shield and the C/C close-out were constructed based on the analytical temperature predictions presented in Part One of this work[1]. The analytical results obtained for a simulated Mars entry of a 2.9 meter diameter cone shaped Carbon-Carbon Aeroshell demonstrated the feasibility of the design. These results showed that the maximum temperature the front F/S reached during the decent was 1752 °C with the resulting rear temperature reaching 326 °C in the thermal model. Part Two of this work documents the thermal modeling and correlation for the Mars Aeroshell test sample and fixture. A finite difference, SINDA/G, thermal math model of the test fixture and sample was generated and correlated to data from an arc jet test conducted at the NASA Ames Research Center's interactive heating facility.

The Tropospheric Emission Spectrometer (TES) is a cryogenic instrument which will be launched on NASA's Earth Observation System (EOS) Chemistry Platform in the year 2003. The overall mission lifetime for the instrument is 5 years with an additional period of 2 years required for ground test and calibration. The EOS Chemistry Platform will be placed in a sun-synchronous near-circular polar orbit with an inclination of 98.2 degrees and a mean altitude of 705 km. The overall objective of TES is the investigation and quantification of global climate change, both natural and anthropogenic. It is a high resolution infrared imaging (1×16 pixels) Fourier Transform Spectrometer with spectral coverage of 3.3-15.4 μm at a spectral resolution of 0.10 cm−1 or 0.025 cm−1 intended for the measurement and profiling of essentially all infrared-active molecules present in the Earth's lower atmosphere (0-30+ km).