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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.

This study presents the results of the ICE GENESIS 2021 Swiss Jura Flight Campaign in a way that is readily usable for ice accretion modelling and aims at improving the description of snow particles for model inputs. 2D images from two OAP probes, namely 2D-S and PIP, have been used to extract 3D shape parameters in the oblate spheroid assumption, as there are the diameter of the sphere of equivalent volume as ellipsoid, sphericity, orthogonal sphericity, and an estimation of bulk density of individual ice crystals through a mass-geometry parametrization. Innovative shape recognition algorithm, based on Convolutional Neural Network, has been used to identify ice crystal shapes based on these images and produce shape-specific mass particle size distributions to describe cloud ice content quantitatively in details. 3D shape descriptors and bulk density have been extracted for all the data collected in cloud environments described in the regulation as icing conditions.

Measurements in snow conditions performed in the past were rarely initiated and best suited for pure and extremely detailed quantification of microphysical properties of a series of microphysical parameters, needed for accretion modelling. Within the European ICE GENESIS project, a considerable effort of natural snow measurements has been made during winter 2020/21. Instrumental means, both in-situ and remote sensing were deployed on the ATR-42 aircraft, as well as on the ground (ground station at ‘Les Eplatures’ airport in the Swiss Jura Mountains with ATR-42 overflights). Snow clouds and precipitation in the atmospheric column were sampled with the aircraft, whereas ground based and airborne radar systems allowed extending the observations of snow properties beyond the flight level chosen for the in situ measurements.

In the framework of the European ICE GENESIS project (https://www.ice-genesis.eu/), a field experiment was conducted in the Swiss Jura in January 2021 in order to characterize snow microphysical properties and document snow conditions for aviation industry purposes. Complementary to companion papers reporting on snow properties, this study presents an investigation on mixed-phase conditions sampled during the ICE GENESIS field campaign. Using in situ measurement of the liquid and total water content, the ice mass fraction is calculated and serves as a criteria to identify mixed-phase conditions. In the end, mixed phase conditions were identified in almost 30 % of the 3800 km long cloud samples included in the ICE GENESIS dataset. The data suggests that the occurrence of mixed-phase does not clearly depend on temperature in the 0 to -10 °C range, but varies significantly from one cloud system to another.

Traditional solutions developed for the aerospace industry must overcome challenges posed for automation systems like design, requalification, large manual content, restricted access, and tight tolerances. At the same time, automated systems should avoid the use of dedicated equipment so they can be shared between jigs; moved between floor levels and access either side of the workpiece. This article describes the development of a robotic system for drilling and inspection for small aerostructure manufacturing specifically designed to tackle these requirements. The system comprises three work packages: connection within the digital thread (from concept through to operational metrics including Statistical Process Control), innovative lightweight / low energy drill, and auto tool-change with in-process metrology. The validation tests demonstrating Technology Readiness Level 6 are presented and results are shown and discussed.

In its entirety, automation is part of an integrated, multi-disciplinary product development process including the design, process, production, logistics, and systems approach—it depends on all these areas, but it also influences them as well. Automation in aerospace manufacturing is present throughout the entire supply chain, from elementary part manufacturing at suppliers up to final assembly, and a clear understanding of all the benefits (and drawbacks) of automation would help designers and engineers select the right designs for and levels of automation. The Right Level of Automation Within Industry 4.0 examines all impacts of automation that should be known by designers, manufacturers, and companies before investments in automation-related decisions are made—regardless of the which industry they work in. The process and the set of criteria discussed in this report will help decision makers select the right level of automation.

Active prechamber combustion systems for SI engines represent a feasible and effective solution in reducing fuel consumption and pollutant emissions for both marine and ground heavy-duty engines. However, reliable and low-cost numerical approaches need to be developed to support and speed-up their industrial design considering their geometry complexity and the involved multiple flow length scales. This work presents a CFD methodology based on the RANS approach for the simulation of active prechamber spark-ignition engines. To reduce the computational time, the gas exchange process is computed only in the prechamber region to correctly describe the flow and mixture distributions, while the whole cylinder geometry is considered only for the power-cycle (compression, combustion and expansion). Outside the prechamber the in-cylinder flow field at IVC is estimated from the measured swirl ratio.

In the challenge to reduce CO2, NOx and PM emissions, the application of natural gas or biogas in engines is a viable approach. In heavy duty and marine, either a conventional dual fuel (CDF), or a reactivity-controlled compression ignition (RCCI) approach is feasible on existing diesel engines. In both technologies a pilot diesel injection is used to ignite the premixed natural gas. However, the influence of injection-timing and -pressure on the start of combustion timing (SOC) is opposite between both modes. For a single operating point these relations can be explained by a detailed CFD simulation, but an intuitive overall explanation is lacking. This makes it difficult to incorporate both modes into one engine application, using a single controller. In an experimental campaign by the authors, on a medium speed engine, the lowest emissions were found to be very close to the SOC corresponding to the transition from RCCI to CDF.

This paper investigates the FPGA resources for the implementation of in-cycle closed-loop combustion control algorithms. Closed-loop combustion control obtains feedback from fast in-cylinder pressure measurements for accurate and reliable information about the combustion progress, synchronized with the flywheel encoder. In-cycle combustion control requires accurate and fast computations for their real-time execution. A compromise between accuracy and computation complexity must be selected for an effective combustion control. The requirements on the signal processing (evaluation rate and digital resolution) are investigated. A common practice for the combustion supervision is to monitor the heat release rate. For its calculation, different methods for the computation of the cylinder volume and heat capacity ratio are compared. Combustion feedback requires of virtual sensors for the misfire detection, burnt fuel mass and pressure prediction.

Increased production rates and cost reduction are affecting manufacturing in all mobility industry sectors. One enabling methodology that could achieve these goals in the burgeoning “Industry 4.0” environment is the optimized deterministic assembly (DA) approach. It always forms the same final structure and has a strong link to design-for-assembly and design-for-automation. The entire supply chain is considered, with drastic savings at the final assembly line level through recurring costs and lead-time reduction. Unsettled Technology Areas in Deterministic Assembly Approaches for Industry 4.0 examines the evolution of previous assembly principles that lead up to and enable the DA approach, related simulation methodologies, and undefined and unsolved links between these domains. Click here to access the full SAE EDGETM Research Report portfolio.

The constrained indicated efficiency optimization of the set-point reference for in-cycle closed-loop combustion regulators is investigated in this article. Closed-loop combustion control is able to reduce the stochastic cyclic variations of the combustion by the adjustment of multiple-injections, a pilot and main injection in this work. The set-point is determined by the demand on engine load, burned pilot mass reference and combustion timing. Two strategies were investigated, the regulation of the start of combustion (SOC) and the center of combustion (CA50). The novel approach taken in this investigation consists of including the effect of the controlled variables on the combustion dispersion, instead of using mean-value models, and solve the stochastic optimization problem. A stochastic heat release model is developed for simulation and calibrated with extensive data from a Scania D13 six-cylinder engine. A Monte Carlo approach is taken for the simulations.

The new edition of the well known Care and Repair of Advanced Composites, 3rd Edition, improves on the usefulness of this practical guide geared towards the aerospace industry. Keith B. Armstrong, the original lead author of the first edition was still in charge of this project, counting on the expert support of Eric Chesmar, senior composites specialist at United Airlines. Mr. Chesmar is also an active member of SAE International's CACRC (Commercial Aircraft Composite Repair Committee), an elite group of industry experts dedicated to the standardization, safety, security, and efficiency of composite repairs in the airline industry. Mr. Francois Museux (Airbus) and Mr. William F. Cole II also contributed. Care and Repair of Advanced Composites, 3rd Edition, presents a fully updated approach to the training syllabus recommended for repair design engineers and composite repair mechanics.

Partially premixed combustion (PPC) is a promising way to achieve high thermal efficiency and low emissions, especially by using multiple injection strategies. The mechanisms behind PPC efficiency are still to be explained and explored. In this paper, multiple injections have been used to affect the gross indicated efficiency in an optical PPC engine modified from a Volvo MD13 heavy-duty diesel engine. The aim is both to improve and impair the gross indicated efficiency to understand the differences. The combustion natural luminosity is captured by a high-speed camera, and the distribution of fuel, oxygen, and temperature during the combustion process has been further explored by CFD simulation. The results show that with the right combination of the pilot, main, and post injection the gross indicated efficiency can be improved.

The partially premixed combustion (PPC) concept is regarded as an intermediate process between the thoroughly mixed Homogeneous charge compression ignition (HCCI) combustion and compression ignition (CI) combustion. It’s a combination of auto-ignition mode, a fuel-rich premixed combustion mode, and a diffusion combustion mode. The concept has both high efficiency and low soot emission due to low heat losses and less stratified fuel and air mixtures compared to conventional diesel CI. The mechanisms behind the combustion process are not yet very well known. This work focuses on the efficiency and the in-cylinder process in terms of fuel distribution and the initial phase of the combustion. More specifically, double injection strategies are compared with single injection strategies to achieve different levels of stratification, ranging from HCCI to PPC like combustion as well as poor (43%) to good (49%) of gross indicated efficiency.

Partially premixed combustion (PPC) has shown to produce high gross indicated efficiencies while yielding lower pollutant emissions, such as oxides of nitrogen and soot, than conventional diesel combustion. Gasoline fuels with a research octane number (RON) of 60-70 have been proposed as optimal for PPC as they balance the trade-off between ensuring good combustion stability at low engine loads and avoiding excessive peak pressure rise rates at high loads. However, measures have to be taken when optimizing the engine operating parameters to avoid soot emissions. In contrast, methanol has a much lower propensity for soot formation. However, due to a higher RON of methanol the required intake temperature is higher for the same engine compression ratio to ensure auto-ignition at an appropriate timing. Increasing the compression ratio allows a lower intake temperature and improves combustion stability as well as engine brake efficiency.

Most of the decisions taken every day are based on the results of measurements of all different events that occur around us. The reliability of these measurements depends basically on the environment in which they are carried out, the procedure defined and the equipment used, evaluating their different contributions through the uncertainty of measurement. In the case of the measuring equipment, the calibration process associated with adequate traceability provides part of the information necessary to contribute positively to the generation of reliability. However, the physical nature of the instruments means that all of them have a certain degree of drift in their metrological characteristics, which requires users to establish time intervals to confirm the maintenance of the goodness of measurement of such equipment.

The paper presents the numerical approach to simulation and optimization of A350 S19 splice assembly process. The main goal is to reduce the number of installed temporary fasteners while preventing the gap between parts from opening during drilling stage. The numerical approach includes computation of residual gaps between parts, optimization of fastener pattern and validation of obtained solution on input data generated on the base of available measurements. The problem is solved with ASRP (Assembly Simulation of Riveting Process) software. The described methodology is applied to the optimization of the robotized assembly process for A350 S19 section.

ASRP (Assembly Simulation of Riveting Process) software is a special tool for assembly process modelling for large scale airframe parts. On the base of variation simulation, ASRP provides a convenient way to analyze, verify and optimize the arrangement of temporary fasteners. During the assembly of airframe certain criteria on residual gap between parts must be fulfilled. The numerical approach implemented in ASRP allows to evaluate the quality of contact on every stage of assembly process and solve verification and optimization problems for temporary fastener patterns. The paper is devoted to description of several specialized approaches that combine statistical analysis of measured data and numerical simulation using high-performance computing for optimization of fastener patterns, calculation of forces in fasteners needed to close initial gaps, and identification of hazardous areas in junction regions via ASRP software.

The present work describes the numerical modeling of medium-speed marine engines, operating in a fumigated dual-fuel mode, i.e. with the second fuel injected in the ports. This engine technology allows reducing engine-out emissions while maintaining the engine efficiency and can be fairly easily retrofitted from current diesel engines. The main premixed fuel that is added can be a low-carbon one and can additionally be of a renewable nature, thereby reducing or even completely removing the global warming impact. To fully optimize the operational parameters of such a large marine engine, computational fluid dynamics can be very helpful. Accurately describing the combustion process in such an engine is key, as the prediction of the heat release and the pollutant formation is crucial. Auto-ignition of the diesel fuel needs to be captured, followed by the combustion and flame propagation of the premixed fuel.

In partially premixed combustion engines high octane number fuels are injected into the cylinder during the late part of the compression cycle, giving the fuel and oxidizer enough time to mix into a desirable stratified mixture. If ignited by auto-ignition such a gas composition can react in a combustion mode dominated by ignition wave propagation. 3D-CFD modeling of such a combustion mode is challenging as the rate of fuel consumption can be dependent on both mixing history and turbulence acting on the reaction wave. This paper presents a large eddy simulation (LES) study of the effects of stratification in scalar concentration (enthalpy and reactant mass fraction) due to large scale turbulence on the propagation of reaction waves in PPC combustion engines. The studied case is a closed cycle simulation of a single cylinder of a Scania D13 engine running PRF81 (81% iso-octane and 19% n-heptane).