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Aviation safety is one of the key focus areas of the aerospace industry as it involves safety of passengers, crew, assets etc. Due to advancements in technology, aviation safety has reached to safest levels compared to last few decades. In spite of declining trends in in-air accident rate, ground accidents are increasing due to ever increasing air traffic and human factors in the airport. Majority of the accidents occur during initial and final phases of the flight. Rapid increase in air traffic would pose challenge in ensuring safety and best utilization of Airports, Airspace and assets. In current scenario multiple systems like Runway Debris Monitoring System, Runway Incursion Detection System, Obstacle avoidance system and Traffic Collision Avoidance System are used for collision prediction and alerting in airport environment. However these approaches are standalone in nature and have limitations in coverage, performance and are dependent on onboard equipment.

Cooling drag is a metric that measures the influence of air flow travelling through the open grille of a ground vehicle on overall vehicle drag, both internally (engine air flow) and externally (interference air flow). With the interference effects considered, a vehicles cooling drag can be influenced by various air flow fields around the vehicle, not just the air flow directly entering or leaving the engine bay. For this reason, computational fluid dynamics (CFD) simulations are particularly difficult. With insights gained from a previously conducted set of experimental studies, a CFD validation effort was undergone to understand which air flow field characteristics contribute to CFD/test discrepancies. A Lattice-Boltzmann Large Eddy Simulation (LES) method was used to validate several test points. Comparison using integral force values, surface pressures, and cooling pack air mass flows was presented.

Cavitation erosion in aircraft engine and control systems is a major concern in hydrodynamic power units. In developing turbulent flow of low pressure and high velocities, a certain amount of cavitation erosion is not unusual. Cavitation can occur with the presence of fuel vapor or air bubbles dissolved in the fuel tank that are transported through the system. Cavitation erosion is caused by collapse of the bubble, which occurs violently and creates a pressure shock wave of fluid. Striking a solid surface, the shock wave can cause progressive damage if it persists. A kinetic cavitation power rate is developed to make a meaningful estimation of the cavitation erosion rate theoretically, which then can be validated with laboratory experiments. Theoretically, we manipulate parameters such as bubble size, collapse pressure, and energy for a given fuel system design, finding variation within each component of the system.

Cloud phase discrimination, coupled with measurements of liquid water content (LWC) and ice water content (IWC) as well as the detection and discrimination of supercooled large droplets (SLD), are of primary importance in aviation safety due to several high-profile incidents over the past two decades. The UTC Aerospace Systems Optical Ice Detector (OID) is a prototype laser sensor intended to discriminate cloud phase, to quantify LWC and IWC, and to detect SLD and differentiate SLD conditions from those of Appendix C. Phase discrimination is achieved through depolarization scattering measurements of a circularly polarized laser beam transmitted into the cloud. Optical extinction measurements indicate the liquid and ice water contents, while the differential backscatter from two distinct probe laser wavelengths implies an effective droplet size. The OID is designed to be flush-mounted with the aircraft skin and to sample the air stream beyond the boundary layer of the aircraft.

Elastokinematic parameters of the axle stiffness are one of the important effects for vehicle dynamics, which are usually considered in full-vehicle real-time models. In order to integrate such effects into real-time models, a multibody axle model is placed on the suspension test rig and is clamped at mounting points. Statically defined load cases are applied on the wheel, and finally, lookup tables are generated, which represent the elastokinematics for the real-time environment. In this case, the Body-In-White (BIW) is considered to be ideally stiff. However, the elasticity of BIW significantly influences the elastokinematics behavior as well and should be integrated into real-time models. The present paper introduces an efficient approach to integrate the BIW compliance effects into lookup tables in addition to the suspension stiffness under consideration of the Elastokinematics By Inertia Force method (EBIF method).

Statistical Energy Analysis (SEA) is an established high-frequency analysis technique for generating acoustic and vibration response predictions in the automotive, aerospace, machinery, and ship industries. SEA offers unique NVH prediction and target-setting capabilities as a design tool at early stages of vehicle design where geometry is still undefined and evolving and no prototype hardware is available yet for testing. The exact frequencies at which SEA can be used effectively vary according to the size and the amount of damping in the vehicle subsystems; however, for automotive design the ability to predict acoustic and vibration responses due to both airborne and structure-borne sources has been established to frequencies of 500 Hz and above. This paper presents the background, historical use, and current industrial applications of structure-borne SEA. The history and motivation for the development of structure-borne SEA are discussed.

Gliders can climb to substantial altitudes without employing any on-board energy resources but using proper piloting skills to utilize rising air currents called thermals. Recent experiments on small Unmanned Aerial Vehicles (UAVs) indicate a significant potential to increase both the flight velocity and the range of gliders by means of such maneuvers. In these experiments the velocity to approach a thermal has been recognized as a critical performance factor, and is chosen as the controlled variable. Accurate longitudinal controllers are required to track the optimal flight trajectories generated using path planning algorithms. These controllers are challenged by the presence of uncertain and time-varying aircraft dynamics, gust disturbances, and control actuator limitations.

Objective: This study analyzed available rear impact sled tests with Starcraft-type seats that use a diagonal belt behind the seatback. The study focused on neck responses for out-of-position (OOP) and in-position seated dummies. Methods: Thirteen rear sled tests were identified with out-of-position and in-position 5 th , 50 th and 95 th Hybrid III dummies in up to 47.6 mph rear delta Vs involving Starcraft-type seats. The tests were conducted at Ford, Exponent and CSE. Seven KARCO rear sled tests were found with in-position 5 th and 50 th Hybrid III dummies in 21.1-29.5 mph rear delta Vs involving Starcraft-type seats. In all of the in-position and one of the out-of-position series, comparable tests were run with production seats. Biomechanical responses of the dummies and test videos were analyzed.

Computer Aided Engineering (CAE) has become a vital tool for product development in automotive industry. Increasing computer models are developed to simulate vehicle crashworthiness, dynamic, and fuel efficiency. Before applying these models for product development, model validation needs to be conducted to assess the validity of the models. However, one of the key difficulties for model validation of dynamic systems is that most of the responses are functional responses, such as time history curves. This calls for the development of an objective metric which can evaluate the differences of both the time history and the key features, such as phase shift, magnitude, and slope between test and CAE curves. One of the promising metrics is Error Assessment of Response Time Histories (EARTH), which was recently developed. Three independent error measures that associated with physically meaningful characteristics (phase, magnitude, and slope) were proposed.

A laboratory study was performed to assess the effectiveness of LNT+SCR systems for NOx control in lean exhaust. The effects of the catalyst system length and the spatial configuration of the LNT & SCR catalysts were evaluated for their effects on the NOx conversion, NH₃ yield, N₂O yield, and HC conversion. It was found that multi-zone catalyst architectures with four or eight alternating LNT and SCR catalyst zones had equivalent gross NOx conversion, lower NH₃ and N₂O yield, and significantly higher net conversion of NOx to N₂ than an all-LNT design or a standard LNT+SCR configuration, where all of the SCR volume is placed downstream of the LNT. The lower NH₃ emissions of the two multi-zone designs relative to the standard LNT+SCR design were attributed to the improved balance of NOx and NH₃ in the SCR zones.

Aircraft weight and center of mass are two critical design and operational parameters that have to be within a design envelope to ensure a safe and efficient operation of aircraft. Previous efforts to accurately determine aircraft weight and center of mass before takeoff using landing gear shock strut pressures have failed due to the distortion of measured pressures by shock strut seal friction. Currently, aircraft loading process is controlled with loading sheets and passenger/cargo weight estimation as there are no online measurement systems that can accurately and efficiently estimate aircraft weight and determine the center of mass location before takeoff. However, errors in loading sheets, shifting cargo and errors in weight estimation could lead to incorrect loading of aircraft and, consequently, increase the risk of accidents, particularly in cargo flights.

There are many identical large solid-state switching Multi-Purpose Motor Controllers on board of one of the More Electric Aircrafts (MEA). The controllers drive over twice as many different machines with wide torque and speed ranges. The common motor controllers are installed in a central location. The machines are located at diverse and distant positions. Power is delivered and routed from the controllers to machines via a large network comprising of unshielded feeders and multiplexing units. The controllers are required to produce sine wave voltage output to machines, and draw clean power from the source to meet Power Quality (PQ) and Electromagnetic Interference (EMI) requirements. There are significant aircraft level weight savings with that concept. However, designing such a clean motor controller was a major power density challenge beyond switches, accounting for high torque main propulsion engine start and high speed Cabin Air Compressors.

This paper will present a multi-domain (electrical and thermal) model of a three phase voltage source converter and its implementation in Modelica language. An averaged model is utilised for the electrical domain, and a power balance method is used for linking the DC and AC sides. The thermal domain focuses in deriving the converter losses by deriving the analytical equations of the space vector modulation to derive a function for the duty cycle of each converter leg. With this, the conduction and switching losses are calculated for the individual switches and diodes, without having to model their actual switching behaviour. The model is very fast to simulate, as no switching events are needed, and allows obtaining the simulation of the electrical and thermal behaviour in the same simulation package..

In modern aircraft power systems, active power converters are promising replacements for transformer rectifier units concerning efficiency and weight. To assess the benefits of active power converters, converter design and optimization should be carefully done under the operation requirements of aircraft applications: electromagnetic interference (EMI) standards, power quality standards, etc. Moreover, certain applications may have strict limits on other converter specifications: weight, size, converter loss, etc. This paper presents the methodology for performance optimization of different active power converters (active front-ends, isolated DC/DC converters and three-phase isolated converters) for aircraft applications. Key methods for power converter component (e.g. inductors, semiconductor devices, etc.) performance optimization and loss calculation are introduced along with the converter optimization procedure.

This paper proposes a method of optimizing aircraft system architectures by considering the efficiencies of each energy conversion step necessary to fulfill the intended function. In addition, these conversion efficiencies need to be evaluated at all critical operating points for the systems involved (e.g. engine, generator, loads, etc.). The methodology starts with examining the energy sources on the aircraft, the energy loads and the energy transfer efficiencies between the sources and the loads. Modern aircraft architecture trends are broadly addressed along with a framework for applying this methodology, but specific aircraft are not analyzed due to the proprietary nature of some of the conversion efficiency data.

This paper presents an overview of a project called “Modelling and Simulation Tools for Systems Integration on Aircraft (MISSION)”. This is a collaborative project being developed under the European Union Clean Sky 2 Program, a public-private partnership bringing together aeronautics industrial leaders and public research organizations based in Europe. The provision of integrated modeling, simulation, and optimization tools to effectively support all stages of aircraft design remains a critical challenge in the Aerospace industry. In particular the high level of system integration that is characteristic of new aircraft designs is dramatically increasing the complexity of both design and verification. Simultaneously, the multi-physics interactions between structural, electrical, thermal, and hydraulic components have become more significant as the systems become increasingly interconnected.

Most of the real world problems pose practical challenges for making decisions primarily due to availability of limited data. Quantification of risk and assessment of structural reliability becomes difficult in such scenarios. Techniques for performing safety analysis for such problems are discussed in this paper. While complete characterization of a system behavior may be difficult with limited data of its response, statistical models based on extreme value theory provide the basis for making decisions with reasonable confidence. The same may not be true, however, for such structures early in their design cycle due to limited experience of their performance. In such cases response surface methodology can be very useful in determination of risk and suitably making modifications to the design to improve the reliability of the component or system. Applications of these methods for some real world scenarios are demonstrated.

Modern aircraft systems employ numerous processors to achieve system functionality. In particular, engine controls and power distribution subsystems rely heavily on software to provide safety-critical functionality, and are expected to move toward multicore architectures. The computing hardware-layer of avionic systems must be able to execute many concurrent workloads under tight deterministic execution guarantees to meet the safety standards. Single-chip multicores are attractive for safety-critical embedded systems due to their lightweight form factor. However, multicores aggressively share hardware resources, leading to interference that in turn creates non-deterministic execution for multiple concurrent workloads. We propose an approach to remove on-chip interference via a set of methods to spatio-temporally partition shared multicore resources.

Auto transformer rectifier units (ATRUs) are commonly used in aircraft applications such as electric actuation for harmonic mitigation due to their high reliability and relative low cost. However, those components and the magnetic filter components associated to it are the major contributors to the overall size and weight of the system. Optimization of the magnetic components is essential in order to minimize weight and size, which are major market drivers in aerospace industry today. This requires knowledge of the harmonic content of the current. This can be obtained by simulation, but the process is slow. In order to enable fast and efficient design space exploration of optimal solutions, an algebraic calculation process is proposed in this paper for multi-pulse ATRUs (e.g. 12-pulse and 18-pulse rectifiers), starting from existing solution proposed for 6 pulse rectifier in the literature.

The exponential increase in the number of aircrafts and air travelers has triggered new innovations which aim to make airline services more reliable and consumer friendly. Quick and efficient maintenance actions with minimum downtime are the need of the hour. Areas that have a large potential for improvement in this regard are the real time use of diagnostic data, filtering/elimination of nuisance faults and machine learning capabilities with respect to maintenance actions. Although, numerous LRUs installed on the aircraft generate massive amounts of diagnostic data to detect any possible issue or LRU failure, it is seldom used in real time. The turnaround time for LRU maintenance can be greatly reduced if the results of the diagnostics conducted during LRU normal operation is relayed to ground stations in real-time. This enables the maintenance engineers to plan ahead and initiate maintenance actions well before the aircraft lands and becomes available for maintenance.