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Traditional User/Maintenance Manuals provide useful information when dealing with simple machines. However, when dealing with complex systems of systems and highly miniaturized technologies, like UAVs, or with machines with millions of parts, a commercial aircraft is a case in point, new technologies taking advantage of Augmented Reality can rapidly and effectively support the maintenance operations. This paper presents a User/Maintenance Manual based on Augmented Reality to help the operator in the detection of parts and in the sequence to be followed to assemble/disassemble systems and subsystems. The proposed system includes a handheld device and/or an head mounted display or special goggles, to be used by on-site operators, with software management providing data fusion and overlaying traditional 2D user/maintenance manual information with an augmented reality software and appropriate interface.

Added masses computation is a crucial aspect to be considered when the density of a body moving in a fluid is comparable to the density of the fluid displaced: added mass can be defined as the inertia added to a system because an accelerating or decelerating body displaces some volume of neighboring fluid as it moves through it. The motion of vehicles like airships and ships can be addressed only by keeping into account the effect of added masses, while in case of aircrafts and helicopters this contribution is usually neglected. Lighter Than Air flight simulation, unmanned airships flight control system, airships flight dynamics are typical applications in which added masses are fundamental to achieve an effective and realistic modeling. A panel based method using the mesh of an airship external shape is developed to account for the added massed.

Nowadays, an automotive DI Diesel engine is demanded to provide an adequate power output together with limit-complying NOx and soot emissions so that the development of a specific combustion concept is the result of a trade-off between conflicting objectives. In other words, the development of a low-emission DI diesel combustion concept could be mathematically represented as a multi-objective optimization problem. In recent years, genetic algorithm and CFD simulations were successfully applied to this kind of problem. However, combining GA optimization with actual CFD-3D combustion simulations can be too onerous since a large number of simulations is usually required, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes.

The flight simulation of airships and hot air balloons usually considers the envelope geometry as a fixed shape, whose volume is eventually reduced by ballonets. However, the dynamic pressure or helium leaks in airships, and the release of air to allow descent in hot air balloons can significantly change the shape of the envelope leading to potential dangerous situations. In fact, in case of semi-rigid and non-rigid airships a reduction in envelope internal pressure can reduce the envelope bending stiffness leading to the loss of the typical axial-symmetric shape. For hot air balloons thing goes even worse since the lost of internal pressure can lead to the collapsing of the balloon shape to a sort of vertically stretched geometry (similar to a torch) which is not able to sustain the attached basket and its payload.

This paper describes the design and development of a virtual environment conceived to support flight operations of an Unmanned Air Vehicle (UAV) used for wind mapping in the proximity of existing or planned wind farms. The virtual environment can be used in pre-flight briefings aiming to define a trajectory from a list of waypoints, to change and eventually re-plan the mission in case of intersection with no fly zones, to simulate the mission, and to preview images/videos taken from the UAV on-board cameras. During flight, the tool can be used to compute the wind speed along the trajectory by analyzing the data streaming from the UAV. The integration of Augmented Reality (AR) techniques in the flight environment provides assistance in remotely piloted landings, and allows visualizing flight and environmental information that are critical to the mission.

Compression-ignited engines are still considered the most efficient and reliable technology for automotive applications. However, current and future emission regulations, which severely limit the production of NOx, particulate matter and CO2, hinder the use of diesel-like fuels. As a matter of fact, the spontaneous ignition of directly-injected Diesel leads to a combustion process that is heterogeneous by nature, therefore characterized by the simultaneous production of particulate matter and NOx. In this scenario, several innovative combustion techniques have been investigated over the past years, the goal being to benefit from the high thermal efficiency of compression-ignited engines, which results primarily from high Compression Ratio and lean and unthrottled operation, while simultaneously mitigating the amount of pollutant emissions.

Large Eddy Simulation (LES) represents nowadays one of the most promising techniques for the evaluation of the dynamics and evolution of turbulent structures characterizing internal combustion engines (ICE). In the present paper, subdivided into two parts, the capabilities of the open-source CFD code OpenFOAM® v2.3.0 are assessed in order to evaluate its suitability for engine cold flow LES analyses. Firstly, the code dissipative attitude is evaluated through an inviscid vortex convection test to ensure that the levels of numerical dissipation are compatible with LES needs. Quality and completeness estimators for LES simulations are then proposed. In particular the Pope M parameter is used as a LES completeness indicator while the LSR parameter provides useful insights far calibrating the grid density. Other parameters such as the two-grid LESIQk index are also discussed.

The next steps of the current European and US legislation, EURO 6c and LEV III, and the incoming new test cycles will impose more severe restrictions on pollutant emissions for Gasoline Direct Injection (GDI) engines. In particular, soot emission limits will represent a challenge for the development of this kind of engine concept, if injection and after-treatment systems costs are to be minimized at the same time. The paper illustrates the results obtained by means of a numerical and experimental approach, in terms of soot emissions and combustion stability assessment and control, especially during catalyst-heating conditions, where the main soot quantity in the test cycle is produced. A number of injector configurations has been designed by means of a CAD geometrical analysis, considering the main effects of the spray target on wall impingement.

During the last years the deep re-examination of the engine design for lowering engine emissions involved two-wheel vehicles too. The IC engine overall efficiency plays a fundamental role in determining final raw emissions. From this point of view, the optimization of the in-cylinder flow organization is mandatory. In detail, in SI engines the generation of a coherent tumble vortex having dimensions comparable to the engine stroke could be of primary importance to extend the engines' ignition limits toward the field of the dilute/lean mixtures. For motorbike and motor scooter applications, the optimization of the tumble generation is considered an effective way to improve the combustion system efficiency and to lower emissions, considering also that the two-wheels layout represents an obstacle in adopting the advanced post-treatment concepts designed for automotive applications.

Combustion phasing is crucial to achieve high performance and efficiency: for gasoline engines control variables such as Spark Advance (SA), Air-to-Fuel Ratio (AFR), Variable Valve Timing (VVT), Exhaust Gas Recirculation (EGR), Tumble Flaps (TF) can influence the way heat is released. The optimal control setting can be chosen taking into account performance indicators, such as Indicated Mean Effective Pressure (IMEP), Brake Specific Fuel Consumption (BSFC), pollutant emissions, or other indexes inherent to reliability issues, such as exhaust gas temperature, or knock intensity. Given the high number of actuations, the calibration of control parameters is becoming challenging.

The recent advance in the development of various hybrid vehicle technologies comes along with the need of establishing optimal energy management strategies, in order to minimize both fuel economy and pollutant emissions, while taking into account an increasing number of state and control variables, depending on the adopted hybrid architecture. One of the objectives of this research was to establish benchmarking performance, in terms of fuel economy, for real time on-board management strategies, such as ECMS (Equivalent Consumption Minimization Strategy), whose structure has been implemented in a SIMULINK model for different hybrid vehicle concepts.

The high number of hull losses is a main concern in the UAV field, mostly due to the high cost of on-board equipment. A crashworthiness design can be helpful to control the extent and position of crash impact damage, minimizing equipment losses. However, the wide use of composite materials has recently put the accent on the lack of data about the behavior of these structures under operative loads, such as the crash conditions. This paper presents the outcome of a set of tests carried out to achieve a controlled crush of UAV structures, and to maximize the Specific Energy Absorption. In this work, a small-scale experimental test able to characterize the energy absorption of a Carbon-fiber-reinforced polymer under compression was developed introducing self-supporting sinusoidal shape specimens, which avoid the need for complex anti-buckling devices.

This paper presents an optimization algorithm, based on discrete dynamic programming, that aims to find the optimal control inputs both for energy and thermal management control strategies of a Plug-in Hybrid Electric Vehicle, in order to minimize the energy consumption over a given driving mission. The chosen vehicle has a complex P1-P4 architecture, with two electrical machines on the front axle and an additional one directly coupled with the engine, on the rear axle. In the first section, the algorithm structure is presented, including the cost-function definition, the disturbances, the state variables and the control variables chosen for the optimal control problem formulation. The second section reports the simplified quasi-static analytical model of the powertrain, which has been used for backward optimization. For this purpose, only the vehicle longitudinal dynamics have been considered.

Fork system is a primary component for motorcycles because it assures the contact between tires and road, therefore the safety and the driving feeling. Usually fork optimization and tuning are experimentally made involving the generation of a high large number of prototypes and an expensive experimental campaign. To reduce the design and the tuning phases of a generic damper system, the numerical simulation should be considered. In this paper, a one-dimensional (1D) model of fore-carriage forks for road applications is presented. The model was built-up in AMESim code. In particular, the authors’ attention was focused on the detection and analysis of cavitation phenomenon inside the fork. As well known, the cavitation is a complex three-dimensional (3D) phenomenon that implies the phase transition.

Unmanned Aerial Vehicles (UAVs) provide the ability to perform a variety of experimental tests of systems and unproven research technologies, including new autopilot systems and obstacle avoidance capabilities, without risking the lives of human pilots. This paper describes the activities of design, optimization, and flight operations of a UAV conceived at Clarkson University (USA) and equipped to perform wind speed measurements to support wind farmsite planning. The UAV design has been assisted and validated by the use of an automatic virtual environment for the assisted design of civil UAVs. This tool can be used as a “computing machine” for civil UAVs. The operator inputs the mission profile and other generic parameters and data about performance, aerodynamics, and weight breakdown are extracted. A mathematical model of the UAV for flight simulation and its dynamic computations, along with automatic drawing is also produced.

This work focuses on the development and validation of a data-driven model capable of predicting the maximum in-cylinder pressure during the operation of an internal combustion engine, with the least possible computational effort. The model is based on two parameters, one that represents engine load and another one the combustion phase. Experimental data from four different gasoline engines, two turbocharged Gasoline Direct Injection Spark Ignition, a Naturally Aspirated SI and a Gasoline Compression Ignition engine, was used to calibrate and validate the model. Some of these engines were equipped with technologies such as Low-Pressure Exhaust Gas Recirculation and Water Injection or a compression ignition type of combustion in the case of the GCI engine. A vast amount of engine points were explored in order to cover as much as possible of the operating range when considering automotive applications and thus confirming the broad validity of the model.

In order to reduce both polluting emissions and fuel costs, many countries allow mixing ethanol to gasoline either in fixed percentages or in variable percentages. The resulting fuel is labeled E10 or E22, where the number specifies the ethanol percentage. This operation significantly changes way the stoichiometric value, which is the air-to-fuel mass ratio theoretically needed to completely burn the mixture. Ethanol concentration must be correctly estimated by the Engine Management System to optimally control exhaust emissions, fuel economy and engine performance. In fact, correct fuel quality recognition allows estimating the actual stoichiometric value, thus allowing the catalyst system to operate at maximum efficiency in any engine working point. Moreover, also other essential engine control functions should be adapted in real time by taking into account the quality of the fuel that is being used.

The maturity reached in the development of Unmanned Air Vehicles (UAVs) systems is making them more and more attractive for a vast number of civil missions. Clearly, the introduction of UAVs in the civil airspace requiring practical and effective regulation is one of the most critical issues being currently discussed. As several civil air authorities report in their regulations “Sense and Avoid” or “Detect and Avoid” capabilities are critical to the successful integration of UAV into the civil airspace. One possible approach to achieve this capability, specifically for operations beyond the Line-of-Sight, would be to equip air vehicles with a vision-based system using cameras to monitor the surrounding air space and to classify other air vehicles flying in close proximity. This paper presents an image-based application for the supervised classification of air vehicles.

Diesel engine CFD simulation is challenged by the need to improve the accuracy in the spray modeling due to the strong influence played by spray dynamics on evaporation rate, flow field, combustion process and emissions. This paper aims to present a hybrid model able to describe both primary and secondary breakup of high-dense high-pressure sprays. According to this approach, the model proposed by Huh and Gosman is used to compute the atomization of the liquid jet (primary breakup) while a modified version of the TAB model of O'Rourke and Amsden is used for the secondary breakup. The atomization model considers the jet turbulence at the nozzle exit and the growth of unstable wave on the jet surface. In order to validate the hybrid model, a free non-evaporating high-pressure-driven spray at engine like conditions has been simulated. The accuracy of the breakup time evaluation has been improved by tuning the TAB constant Ck according to the Pilch's experimental correlations.

The mixture composition heavily influences the combustion process of Port Fuel Injection (PFI) engines. The local mixture air-index at the spark plug is closely related to combustion instabilities and the cycle-by-cycle Indicated Mean Effective Pressure (IMEP) Coefficient of Variation (CoV) well correlates with the variability of the flame kernel development. The needs of reducing the engine emissions and consumption push the engine manufactures to implement techniques providing a better control of the mixture quality in terms of homogeneity and variability. Simulating the mixture formation of a PFI engine by means of CFD techniques is a critical issue, since involved phenomena are highly heterogeneous and a two phase flow must be considered. The aim of the paper is to present a multi-cycle methodology for the simulation of the injection and the mixture formation processes of high performance PFI engine, based on the validation of all the main physical sub-models involved.