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Using renewable fuels is a reliable approach for decarbonization of combustion engines. iso-Butanol and n-butanol are known as longer chain alcohols and have the potential of being used as gasoline substitute or a renewable fraction of gasoline. The combustion behavior of renewable fuels in modern combustion engines and advanced combustion concepts is not well understood yet. Low-temperature combustion (LTC) is a concept that is a basis for some of the low emissions-high efficiency combustion technologies. Fuel ɸ-sensitivity is known as a key factor to be considered for tailoring fuels for these engines. The Lund ɸ-sensitivity method is an empirical test method for evaluation of the ɸ-sensitivity of liquid fuels and evaluate fuel behavior in thermal. iso-Butanol and n-butanol are two alcohols which like other alcohol exhibit nonlinear behavior when blended with (surrogate) gasoline in terms of RON and MON.

Predicting and preventing combustion anomalies leads to safe and efficient operation of the hydrogen internal combustion engine. This research presents the application of three machine learning (ML) models – K-Nearest Neighbors (KNN), Random Forest (RF) and Logistic Regression (LR) – for the prediction of combustion anomalies in a hydrogen internal combustion engine. A small experimental dataset was used to train the models and posterior experiments were used to evaluate their performance and predicting capabilities (both in operating points -speed and load- within the training dataset and operating points in other areas of the engine map). KNN and RF exhibit superior accuracy in classifying combustion anomalies in the training and testing data, particularly in minimizing false negatives, which could have detrimental effects on the engine.

This study investigates the role of turbulent-chemistry interaction in simulations of diesel spray combustion phenomena after end-of-injection (EOI), using the commercially-available CFD code CONVERGE. Recent experimental and computational studies have shown that the spray flame dynamics and mixture formation after EOI are governed by turbulent entrainment, coupled with rapid evolution of the thermo-chemical state of the mixture field. A few studies have shown that after EOI, mixtures between the injector nozzle and the lifted diffusion flame can ignite and appear to propagate back towards the injector nozzle via an auto-ignition reaction sequence; referred to as “combustion recession”.

The Conceptual Aerospace Systems Design and Analysis Toolkit (CASDAT) provides a baseline assessment capability for the Air Force Research Laboratory. The historical development of CASDAT is of benefit to the design research community because considerable effort was expended in the classification of the analysis tools. Its implementation proves to also be of importance because of the definition of assessment use cases. As a result, CASDAT is compatible with accepted analysis tools and can be used with state-of-the-art assessment methods, including technology forecasting and probabilistic design.

This article begins by describing the need for a new method and tool for performing a sustainability assessment for manufacturing processes and systems. A brief literature survey is done to highlight the major existing methods and tools, their function, and their shortcomings. The article goes on to describe the general approach of the method before describing a computer aided tool that has been developed to implement the method. The article concludes with a walk through of a generic use case that describes where such a method would be useful and how such a tool would be implemented.

Dual-mode dual-fuel combustion is a promising combustion concept to achieve the required emissions and CO2 reductions imposed by the next standards. Nonetheless, the fuel formulation requirements are stricter than for the single-fuel combustion concepts as the combustion concept relies on the reactivity of two different fuels. This work investigates the effect of the low reactivity fuel sensitivity (S=RON-MON) and the octane number at different operating conditions representative of the different combustion regimes found during the dual-mode dual-fuel operation. For this purpose, experimental tests were performed using a PRF 95 with three different sensitivities (S0, S5 and S10) at operating conditions of 25% load/950 rpm, 50%/1800 rpm and 100%/2200 rpm. Moreover, air sweeps varying ±10% around a reference air mass were performed at 25%/1800 rpm and 50%/1800 rpm. Conventional diesel fuel was used as high reactivity fuel in all the cases.

With ever-demanding emission legislations in Compression Ignition (CI) engines, new premixed combustion strategies have been developed in recent years seeking both, emissions and performance improvements. Since it has been shown that in-cylinder air flow affects the combustion process, and hence the overall engine performance, the study of swirling structures and its interaction with fuel injection are of great interest. In this regard, possible Turbulent Kinetic Energy (TKE) distribution changes after fuel injection may be a key parameter for achieving performance improvements by reducing in-cylinder heat transfer. Consequently, this paper aims to gain an insight into spray-swirl interaction through the analysis of in-cylinder velocity fields measured by Particle Image Velocimetry (PIV) when PCCI conditions are proposed. Experiments are carried out in a single cylinder optical Diesel engine with bowl-in-piston geometry.

The spatial and temporal locations of autoignition depend on fuel chemistry and the temperature, pressure, and mixing trajectories in the fuel jets. Dual-fuel systems can provide insight into fuel-chemistry aspects through variation of the proportions of fuels with different reactivities, and engine operating condition variations can provide information on physical effects. In this context, the spatial and temporal progression of two-stage autoignition of a diesel-fuel surrogate, n-heptane, in a lean-premixed charge of synthetic natural gas (NG) and air is imaged in an optically accessible heavy-duty diesel engine. The lean-premixed charge of NG is prepared by fumigation upstream of the engine intake manifold.

In the past few years’ various studies have shown how the application of a highly premixed dual fuel combustion for CI engines leads a strong reduction for both pollutant emissions and fuel consumption. In particular a drastic soot and NOx reduction were achieved. In spite of the most common strategy for dual fueling has been represented by using two different injection systems, various authors are considering the advantages of using a single injection system to directly inject blends in the chamber. In this scenario, a characterization of the behavior of such dual-fuel blend spray became necessary, both in terms of inert and reactive ambient conditions. In this work, a light extinction imaging (LEI) has been performed in order to obtain two-dimensional soot distribution information within a spray flame of different diesel/gasoline commercial fuel blends. All the measurements were conducted in an optically accessible two-stroke engine equipped with a single-hole injector.

Schlieren/shadowgraphy has been adopted in the combustion research as a standard technique for tip penetration analysis of sprays under diesel-like engine conditions. When dealing with schlieren images of reacting sprays, the combustion process and the subsequent light emission from the soot within the flame have revealed both limitations as well as considerations that deserve further investigation. Seeking for answers to such concerns, the current work reports an experimental study with this imaging technique where, besides spatial filtering at the Fourier plane, both short exposure time and chromatic filtering were performed to improve the resulting schlieren image, as well as the reliability of the subsequent tip penetration measurement. The proposed methodology has reduced uncertainties caused by artificial pixel saturation (blooming).

This presentation is an assessment of the turbulence-stress scale-similarity in an IC engine, which is used for modeling subgrid dissipation in LES. Residual stresses and Leonard stresses were computed after applying progressively smaller spatial filters to measured and simulated velocity distributions. The velocity was measured in the TCC-II engine using planar and stereo PIV taken in three different planes and with three different spatial resolutions, thus yielding two and three velocity components, respectively. Comparisons are made between the stresses computed from the measured velocity and stress computed from the LES resolved-scale velocity from an LES simulation. The results present the degree of similarity between the residual stresses and the Leonard stresses at adjacent scales. The specified filters are systematically reduced in size to the resolution limits of the measurements and simulation.

In this paper, we describe our work and experiences with integrating environmental and economic performance monitoring in a production facility of Interface Flooring Systems, Inc. The objective of the work is to create a ‘dashboard’ that integrates environmental and economic monitoring and assessment of manufacturing processes, and provides engineers and managers an easy to use tool for obtaining valid, comparable assessment results that can be used to direct attention towards necessary changes. To this purpose, we build upon existing and familiar cost management principles, in particular Activity-Based Costing and Management (ABC&ABM), and we extend those into environmental management in order to obtain a combined economic and environmental performance measurement framework (called Activity-Based Cost and Environmental Management).

Split injection processes have been analyzed by means of a Quasi-1D spray model that has been recently coupled to a laminar tabulated unsteady-flamelet progress-variable (UFPV) combustion model. The modelling approach can predict ignition delay and lift-off for long injection profiles, and it is now extended to a two-pulse injection scheme. In spite of the simplicity of the approach, relevant phenomena are adequately reproduced. In particular, the faster penetration of the second injection pulse compared to the first one is captured by the model both under inert and reacting conditions. The second pulse ignites much faster than the first one due to the injection into the remnants of the first one, where high temperature oxygen-depleted regions can be found. Ignition of the second pulse happens as soon as the first pulse reaches this region, with a faster low- to high-temperature transition.

In this study we identify components of a typical biodiesel fuel and estimate both their individual and mixed thermo-physical and transport properties. We then use the estimated mixture properties in computational simulations to gauge the extent to which combustion is modified when biodiesel is substituted for conventional diesel fuel. Our simulation studies included both conventional diesel combustion (DI) and premixed charge compression ignition (PCCI). Preliminary results indicate that biodiesel ignition is significantly delayed due to slower liquid evaporation, with the effects being more pronounced for DI than PCCI. The lower vapor pressure and higher liquid heat capacity of biodiesel are two key contributors to this slower rate of evaporation. Other physical properties are more similar between the two fuels, and their impacts are not clearly evident in the present study.

This work investigates the particulates size distribution of reactivity controlled compression ignition combustion, a dual-fuel concept which combines the port fuel injection of low-reactive/gasoline-like fuels with direct injection of highly reactive/diesel-like fuels. The particulates size distributions from 5-250 nm were measured using a scanning mobility particle sizer at six engine speeds, from 950 to 2200 rpm, and 25% engine load. The same procedure was followed for conventional diesel combustion. The study was performed in a single-cylinder engine derived from a stock medium-duty multi-cylinder diesel engine of 15.3:1 compression ratio. The combustion strategy proposed during the tests campaign was limited to accomplish both mechanical and emissions constraints. The results confirms that reactivity controlled compression ignition promotes ultra-low levels of nitrogen oxides and smoke emissions in the points tested.

With demanding emissions legislations and the need for higher efficiency, new technologies for compression ignition engines are in development. One of them relies on reducing the heat losses of the engine during the combustion process as well as to devise injection strategies that reduce soot formation. Therefore, it is necessary a better comprehension about the turbulent kinetic energy (TKE) distribution inside the cylinder and how it is affected by the interaction between air flow motion and fuel spray. Furthermore, new diesel engines are characterized by massive decrease of NOx emissions. Therefore, considering the well-known NOx-soot trade-off, it is necessary a better comprehension and overall quantification of soot formation and how the different injection strategies can impact it.

Dual-fuel combustion engines have shown the potential to extend the operating range of Homogeneous Charge Compression Ignition (HCCI) by using several combustion modes, e.g. Reactivity Controlled Compression Ignition (RCCI) at low/medium load, and Partially Premixed Compression (PPC) at high load. In order to optimize the combustion mode operation, the respective sensitivity to the control inputs must be addressed. To this end, in this work the extremum seeking algorithm has been investigated. By definition, this technique allows to detect the control input authority over the system by perturbing its value by a known periodic signal. By analyzing the system response and calculating its gradient, the control input can be adjusted to reach optimal operation. This method has been applied to a dual-fuel engine under fully, highly and partially premixed conditions where the feedback information was provided by in-cylinder pressure and NOx sensors.

Emissions regulations for engine and vehicle manufacturers are bound to become more limiting to prevent greenhouse gas emissions and mitigate the negative effects that potentiate global warming. To fulfill the energy demand necessary in the transportation sector for the short-to-medium term, a parallel optimization of the internal combustion engine, powertrain and fuels is necessary. The combination of novel combustion modes like the reactivity-controlled compression ignition (RCCI), that seeks the benefits of both compression ignition and spark ignition engines, with the so-called e-fuels, that reduce the carbon footprint from well-to-wheel, is worth exploring. This work investigates the potential of the RCCI concept using OMEx-gasoline to reduce the engine-out emissions beyond the current EURO VI legislation. To do so, eight representative operating conditions from several driving cycles for heavy-duty vehicles will be explored experimentally.

Actual combustion strategies in internal combustion engines rely on fast and accurate injection systems to be successful. One of the injector designs that has shown good performance over the past years is the direct-acting piezoelectric. This system allows precise control of the injector needle position and hence the injected mass flow rate. Therefore, understanding how nozzle flow characteristics change as function of needle dynamics helps to choose the best lift law in terms of delivered fuel for a determined combustion strategy. Computational fluid dynamics is a useful tool for this task. In this work, nozzle flow of a prototype direct-acting piezoelectric has been simulated by using CONVERGE. Unsteady Reynolds-Averaged Navier-Stokes approach is used to take into account the turbulence. Results are compared with experiments in terms of mass flow rate. The nozzle geometry and needle lift profiles were obtained by means of X-rays in previous works.

Focusing on the dual-mode dual-fuel (DMDF) combustion concept, a combined optimization of the piston bowl geometry with the fuel injection strategy was conducted at low, mid, and high loads. By coupling the KIVA-3V code with the enhanced genetic algorithm (GA), a total of 14 parameters including the piston bowl geometric parameters and the injection parameters were optimized with the objective of meeting Euro VI regulations while improving the fuel efficiency. The optimal piston bowl shape coupled with the corresponding injection strategy was summarized and integrated at various loads. Furthermore, the effects of the key geometric parameters were investigated in terms of organizing the in-cylinder flow, influencing the energy distribution, and affecting the emissions. The results indicate that the behavior of the DMDF combustion mode is further enhanced in the aspects of improving the fuel economy and controlling the emissions after the bowl geometry optimization.