Rational Fuel Design for Low Temperature Internal Combustion Engines

This work introduces a new methodology to design transportation fuels offering improved efficiency and reduced emissions, aimed to complement both traditional and emerging engine technologies. Many of these emerging technologies are centered around exploiting low temperature combustion (LTC) strategies that offer improved efficiency and reduced emissions. However, a standardized fuel does not exist to effectively operate in a LTC mode. Through engine simulations, supervised machine learning, and multivariate optimization, this work provides a tool to create fuels tailored to a specific LTC engine application. Engine simulations in this work characterize the LTC performance for hundreds of fuel samples, quantified by a fuel performance metric called the LTC index. Supervised machine learning provides correlations between measured fuel infrared absorbance spectra to various fuel performance metrics: the LTC index, Research Octane Number (RON) and Motor Octane Number (MON). The predictive models of these metrics circumvent the need for costly and time consuming engine experiments to explore the performance of uncharacterized fuels. The success of this work is heavily reliant on the ability of the models to make accurate predictions of the fuel performance metrics, viz. the LTC index, which is assessed through two efforts. The first effort is generating a robust validation data set to benchmark model predictive performance. Here, multivariate optimization is also used to create surrogates for the FACE gasolines. These surrogates are paired with engine simulations to determine the true LTC index and compare to predicted values. LTC indices of most FACE gasolines are found to be accurately predicted within 3 units, and at worst within 6. The second effort toward predictive model validation is a novel experimental campaign, measuring first and second-stage fuel-spray ignition delays in a constant volume combustion chamber (CVCC). The novelty comes by using ultra-short injections to enhance mixing prior to ignition phenomena, quantified by a state-of-the-art optical diagnostic---developed in this work---that images spatiotemporal fuel-spray concentrations. The mixture data are compared to a spray-ignition model with simplified fluid mechanics, found to capture spray mixing exceedingly well. The validated spray physical model is paired with a comprehensive chemical mechanism to predict and compare to experimentally-obtained spray-ignition onsets, thereby establishing a novel way to assess the accuracy of chemical mechanisms and surrogate fuels. The validated LTC index predictive model is finally paired with multivariate optimization techniques to design a fuel tailored to a dual mode engine. In theory, this engine would operate in LTC mode where possible for efficiency improvements, and switch to traditional spark-ignition where needed. The tools developed in this work simultaneously point fuel and vehicle technology in a unique direction for designing high efficiency, next-generation combustion systems

Fourier-Transform Infrared Absorption Spectroscopy in Binary Hydrocarbon-Alcohol Single Droplet Evaporation

Broadband absorption spectroscopy, by way of FTIR, was used to investigate the vapor cloud of a single millimeter sized liquid droplet suspended by a syringe as it evaporates at standard conditions. Single beam data were collected every 8 seconds resulting in a time-resolved record. Species concentrations were tracked using their resonant absorption peaks and correlated with a multidimensional numerical model. The numerical model combined a Gaussian beam transmission through a temporally changing spherical vapor cloud with radial concentration gradients, informed by the D² law and interpreted using the Abel transform. There was fair agreement with temporal evaporation trends for single component runs. Multicomponent experiments of ethanol and isooctane showed synergistic blending effects and preferential evaporation of ethanol. Droplets were also suspended by a thermocouple to track the droplet temperature over time as they were subject to evaporative cooling. This work is the foundation of a basic technique for collecting useful data to inform a complex transport problem.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Hindawi Publishing Corporation. The published article can be found at: http://www.hindawi.com/journals/jspec

Investigation of the LTC fuel performance index for oxygenated reference fuel blends

A new metric for ranking the suitability of fuels in LTC engines was recently introduced, based on the fraction of potential fuel savings achieved in the FTP-75 light-duty vehicle driving cycle. In the current study, this LTC fuel performance index was calculated computationally and analyzed for a number of fuel blends comprised of n-heptane, isooctane, toluene, and ethanol in various combinations and ratios corresponding to octane numbers from 0 to 100. In order to calculate the LTC index for each fuel, computational driving cycle simulations were first performed using a typical light-duty passenger vehicle, providing pairs of engine speed and load points. Separately, for each fuel blend considered, single-zone naturally aspirated HCCI engine simulations with a compression ratio of 9.5 were performed in order to determine the operating envelopes. These results were combined to determine the varying improvement in fuel economy offered by fuels, forming the basis for the LTC fuel index. The resulting fuel performance indices ranged from 36.4 for neat n-heptane (PRF0) to 9.20 for a three-component blend of n-heptane, isooctane, and ethanol (ERF1). For the chosen engine and chosen conditions, in general lower-octane fuels performed better, resulting in higher LTC fuel index values; however, the fuel performance index correlated poorly with octane rating for less-reactive, higher-octane fuels.Keywords: HCCI engines, Low-temperature combustion, Gasoline, Octane numberKeywords: HCCI engines, Low-temperature combustion, Gasoline, Octane numbe

A Novel Fuel Performance Index for Low-Temperature Combustion Engines Based on Operating Envelopes in Light-Duty Driving Cycle Simulations

Low-temperature combustion (LTC) engine concepts such as homogeneous charge compression ignition (HCCI) offer the potential of improved efficiency and reduced emissions of NOₓ and particulates. However, engines can only successfully operate in HCCI mode for limited operating ranges that vary depending on the fuel composition. Unfortunately, traditional ratings such as octane number poorly predict the autoignition behavior of fuels in such engine modes, and metrics recently proposed for HCCI engines have areas of improvement when wide ranges of fuels are considered. In this study, a new index for ranking fuel suitability for LTC engines was defined, based on the fraction of potential fuel savings achieved in the FTP-75 light-duty vehicle driving cycle. Driving cycle simulations were performed using a typical light-duty passenger vehicle, providing pairs of engine speed and load points. Separately, single-zone naturally aspirated HCCI engine simulations were performed for a variety of fuels in order to determine the operating envelopes for each. These results were combined to determine the varying improvement in fuel economy offered by fuels, forming the basis for a fuel performance index. Results showed that, in general, lower octane fuels performed better, resulting in higher LTC fuel index values; however, octane number alone did not predict fuel performance

Folate catabolites in spot urine as non-invasive biomarkers of folate status during habitual intake and folic acid supplementation.

Folate status, as reflected by red blood cell (RCF) and plasma folates (PF), is related to health and disease risk. Folate degradation products para-aminobenzoylglutamate (pABG) and para-acetamidobenzoylglutamate (apABG) in 24 hour urine have recently been shown to correlate with blood folate. Since blood sampling and collection of 24 hour urine are cumbersome, we investigated whether the determination of urinary folate catabolites in fasted spot urine is a suitable non-invasive biomarker for folate status in subjects before and during folic acid supplementation. Immediate effects of oral folic acid bolus intake on urinary folate catabolites were assessed in a short-term pre-study. In the main study we included 53 healthy men. Of these, 29 were selected for a 12 week folic acid supplementation (400 µg). Blood, 24 hour and spot urine were collected at baseline and after 6 and 12 weeks and PF, RCF, urinary apABG and pABG were determined. Intake of a 400 µg folic acid bolus resulted in immediate increase of urinary catabolites. In the main study pABG and apABG concentrations in spot urine correlated well with their excretion in 24 hour urine. In healthy men consuming habitual diet, pABG showed closer correlation with PF (rs = 0.676) and RCF (rs = 0.649) than apABG (rs = 0.264, ns and 0.543). Supplementation led to significantly increased folate in plasma and red cells as well as elevated urinary folate catabolites, while only pABG correlated significantly with PF (rs = 0.574) after 12 weeks. Quantification of folate catabolites in fasted spot urine seems suitable as a non-invasive alternative to blood or 24 hour urine analysis for evaluation of folate status in populations consuming habitual diet. In non-steady-state conditions (folic acid supplementation) correlations between folate marker (RCF, PF, urinary catabolites) decrease due to differing kinetics

X-linked primary ciliary dyskinesia due to mutations in the cytoplasmic axonemal dynein assembly factor PIH1D3

By moving essential body fluids and molecules, motile cilia and flagella govern respiratory mucociliary clearance, laterality determination and the transport of gametes and cerebrospinal fluid. Primary ciliary dyskinesia (PCD) is an autosomal recessive disorder frequently caused by non-assembly of dynein arm motors into cilia and flagella axonemes. Before their import into cilia and flagella, multi-subunit axonemal dynein arms are thought to be stabilized and pre-assembled in the cytoplasm through a DNAAF2–DNAAF4–HSP90 complex akin to the HSP90 co-chaperone R2TP complex. Here, we demonstrate that large genomic deletions as well as point mutations involving PIH1D3 are responsible for an X-linked form of PCD causing disruption of early axonemal dynein assembly. We propose that PIH1D3, a protein that emerges as a new player of the cytoplasmic pre-assembly pathway, is part of a complementary conserved R2TP-like HSP90 co-chaperone complex, the loss of which affects assembly of a subset of inner arm dyneins

Associations of common breast cancer susceptibility alleles with risk of breast cancer subtypes in BRCA1 and BRCA2 mutation carriers

Introduction: More than 70 common alleles are known to be involved in breast cancer (BC) susceptibility, and several exhibit significant heterogeneity in their associations with different BC subtypes. Although there are differences in the association patterns between BRCA1 and BRCA2 mutation carriers and the general population for several loci, no study has comprehensively evaluated the associations of all known BC susceptibility alleles with risk of BC subtypes in BRCA1 and BRCA2 carriers. Methods: We used data from 15,252 BRCA1 and 8,211 BRCA2 carriers to analyze the associations between approximately 200,000 genetic variants on the iCOGS array and risk of BC subtypes defined by estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and triple-negative- (TN) status; morphologic subtypes; histological grade; and nodal involvement. Results: The estimated BC hazard ratios (HRs) for the 74 known BC alleles in BRCA1 carriers exhibited moderate correlations with the corresponding odds ratios from the general population. However, their associations with ER-positive BC in BRCA1 carriers were more consistent with the ER-positive as