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Porous wall permeability is one of the most critical factors for the estimation of backpressure, a key performance indicator in automotive particulate filters. Current experimental and analytical filter models could be calibrated to predict the permeability of a specific filter. However, they fail to provide a reliable estimation for the dependence of the permeability on key parameters such as wall porosity and pore size. This study presents a novel methodology for experimentally determining the permeability of filter walls. The results from four substrates with different porosities and pore sizes are compared with several popular permeability estimation methods (experimental and analytical), and their validity for this application is assessed. It is shown that none of the assessed methods predict all permeability trends for all substrates, for cold or hot flow, indicating that other wall properties besides porosity and pore size are important.

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.

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.

The present work represents the continuation of the introductory study presented in part I [11] where the experimental plan, the measurement system and the tools developed for the testing of a modern Wankel engine were illustrated. In this paper the motored data coming from the subsequent stage of the testing are presented. The AIE 225CS Wankel rotary engine produced by Advanced Innovative Engineering UK, installed in the test cell of the University of Bath and equipped with pressure transducers selected for the particular application, has been preliminarily tested under motored conditions in order to validate the data acquisition software on the real application and the correct determination of the Top Dead Centre (TDC) location which is of foremost importance in the computation of parameters such as the indicated work and the combustion heat release when the engine is tested later under fired conditions.

Permanent magnet (PM) electrical machine has far-reaching impacts in aviation electrification due to the continuous development in high power density and high efficiency electrical drives. The primary barrier to acceptance of permanent magnet machines for safety-critical starter-generator systems is its low fault-tolerance capability and low reliability (for the conventional designs). This article investigates a modular triple three-phase PM starter-generator comprehensively, including the tradeoff of fault-tolerant topology, optimization design process, analysis of electromagnetic (highlight the post-fault analysis) and thermal behavior, respectively. The triple three-phase segmented topology proposed meet the fault-tolerant requirement along with complete electrical, magnetic, and thermal isolation. There would be cost penalty on the proposed topology, but it gets offset by the ease of manufacturing of coils and their insertion.

Electric machines in aerospace applications are subjected to extremely high operating temperatures. This increases coercivity or decreases saturation flux density of the electrical steel resulting in increased core loss. The need for high power density and increased operating speed favours the use of thin gauge Silicon Steel (Si-Fe) and Cobalt Iron (Co-Fe) laminations for aerospace applications. Therefore, the variation in iron loss is studied for three grades of Si-Fe laminations by subjecting them to controlled ageing in laboratory. The analysis is also provided over a range of flux density and frequency to generalize the phenomenon over the operating domain. The results of ageing the laminations are in turn used to predict the degradation in performance of a 1.15 MW, 16-pole 48-slot propulsion machine for aerospace application. The degradation is estimated in terms of variation in iron loss.

Evolving of aircraft design towards further electrification requires safe and fault-free operation of all the components. More electric aircraft are increasingly utilizing electro-mechanical actuators (EMA). EMAs are prone to jamming and subsequent failure due to large forces on the shaft. Large forces are generated due to the high reflected inertia of the electric machine rotor. To limit the force acting on the shaft, a torque limiting device is connected to the power train which can separate the rotating mass of the electric machine from the power train. In this paper, a concept of integration of torque limiter and the electric machine rotor is presented to reduce overall volume and mass. It is connected closely with the rotor, within the motor envelope. A commercially available torque limiter and an electric machine designed for actuator application are used to demonstrate the concept. While essential for safety, the torque limiter adds to the mass and size of the overall EMA.

Electric machines offering a high power density are required for aerospace applications. Soft magnetic material with a high saturation flux density is one of the key component which is required to realize these power density targets. The need for a high saturation flux density necessitates the use of cobalt iron lamination over the conventional silicon steel. However, cobalt iron is very expensive i.e. order of 10 in comparison to silicon steel. Stator segmentation is identified as an appropriate method to reduce the wastage and cost associated with lamination. Consequently, in this paper, stator segmentation is analyzed on a 1.35 MW, 16-pole 48-slot propulsion machine. The impact of manufacturing is accounted by controlling the resulting airgap between the segmented structures. Electromagnetic performance for various segmented topologies are compared in terms of torque, torque ripple, and iron loss.

Particulate emissions from gasoline direct injection (GDI) engines continue to be a topic of substantial research interest. Forthcoming regulation both in the USA and the EU will further reduce their emission and drive innovation. Substantial research effort is spent undertaking experiments to understand, characterize, and research particle number (PN) emissions from engines and vehicles. Recent advances in computing power, data storage, and understanding of artificial intelligence algorithms now mean that these are becoming an important tool in engine research. In this work a random forest (RF) algorithm is used for the prediction of PN emissions from a highly boosted (up to 32 bar BMEP) GDI engine. Particle size, concentration, and the accumulation mode geometric standard deviation (GSD) are all predicted by the model. The results are analysed and an in depth study on parameter importance is carried out.

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 use of Wankel rotary engines as a range extender has been recognised as an appealing method to enhance the performance of Hybrid Electric Vehicles (HEV). They are effective alternatives to conventional reciprocating piston engines due to their considerable merits such as lightness, compactness, and higher power-to-weight ratio. However, further improvements on Wankel engines in terms of fuel economy and emissions are still needed. The objective of this work is to investigate the engine modelling methodology that is particularly suitable for the theoretical studies on Wankel engine dynamics and new control development. In this paper, control-oriented models are developed for a 225CS Wankel rotary engine produced by Advanced Innovative Engineering (AIE) UK Ltd. Through a synthesis approach that involves State Space (SS) principles and the artificial Neural Networks (NN), the Wankel engine models are derived by leveraging both first-principle knowledge and engine test data.

Dynamical Energy Analysis (DEA) has recently been introduced as a mesh-based high frequency method modelling structure borne sound for complex built-up structures. Using DEA, the structure-borne sound of an assembled agricultural tractor was calculated and good agreement between measurement and DEA calculations has been shown. However, it is still difficult to model a solid structure as currently DEA is based on wave-transmission calculations through plates and plate-to-plate junctions. Additionally, it is often difficult to generate accurate FE meshes of assembled complex structures because of welds, bolts, and rubber brushes between components. In this paper, we propose a novel method to generate DEA elements based on measurement data in order to model solid parts of a complex structures. The method of Advanced Transfer Path Analysis (ATPA) is employed to extract energy-transmission characteristics of a structure.

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.

Reconfigurable tooling frames consisting of steel box sections and bolted friction clamps offer an opportunity to replace traditional expensive welded steel tooling. This well publicized reconfigurable reusable jig tooling has been investigated for use in the assembly of a prototype compound helicopter wing. Due to the aircraft configuration, the wing design is pinned at both ends and therefore requires a higher degree of end to end accuracy, over the 4m length, than conventional wings. During the investigation some fundamental issues are approached, including: Potential cost savings and variables which effect the business case. Achievable Jig accuracy. Potential sources of instability that may affect accuracy over time. Repeatability of measurements with various features and methods. Typical jig stability over 24hrs including effects of small temperature fluctuations. Deflections that occur due to loading.

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 Rapid And Cost Effective Rotorcraft (RACER) is being developed by Airbus Helicopters (AH) to demonstrate a new Vertical Take-Off and Landing configuration to fill the mobility gap between conventional helicopters and aeroplanes. RACER is a compound rotorcraft featuring wings and multiple rotors. The wing arrangement suggested by AH is defined as a staggered bi-plane joined configuration with an upper and a lower straight wing, either side of the fuselage, connected at their outboard extent to form a triangular structure. The ASTRAL consortium, consisting of the University of Nottingham and GE Aviation Systems, are responsible for the design, manufacture, assembly and testing of the wings. Producing an optimised strategy to assemble a joined-wing configuration for a passenger carrying rotorcraft is challenging and novel. The objective of this work concerns all aspects of assembling the joined-wing structure.

Reducing emissions from light duty vehicles is critical to meet current and future air quality targets. With more focus on real world emissions from light-duty vehicles, the interactions between engine and exhaust gas aftertreatment are critical. For modern engines, most emissions are generated during the warm-up phase following a cold start. For Diesel engines this is exaggerated due to colder exhaust temperatures and larger aftertreatment systems. The De-NOx aftertreatment can be particularly problematic. Engine manufacturers are required to take measures to address these temperature issues which often result in higher fuel consumption (retarding combustion, increasing engine load or reducing the Diesel air-fuel ratio). In this paper we consider an inner-insulated turbocharger as an alternative, passive technology which aims to reduce the exhaust heat losses between the engine and the aftertreatment. Firstly, the concept and design of the inner-insulated turbocharger is presented.

The objective of this paper is to present a numerical method to rank thick ice shapes for aircraft by comparing the ice accretion effects for different icing scenarios in order to determine the more critical ice shape. This ranking allows limiting the demonstration of the aerodynamic characteristics of the aircraft in iced condition during certification to a reduced number of ice shapes. The usage of this numerical method gives more flexibility to the determination of the critical ice shapes, as it is not dependent of the availability of physical test vehicles and/or facilities. The simulation strategy is built on the Lattice Boltzmann Method (LBM) and is validated based on a representative test case, both in terms of aircraft geometry and ice shapes. Validation against existing experimental results shows the method exhibits an adequate level of reliability for the ranking of thick ice shapes.