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May 30 - June 2, 2019 │ Barrie, ON, Canada │ Barrie Molson Centre

Explore AeroTech's Key Tracks, Sessions, and Presentations on hot topics in the Aerospace industry.

May 30 - June 2, 2019 │ Barrie, ON, Canada │ Barrie Molson Centre

June 19-22, 2019 │ Lincoln, NE, USA │ Lincoln Airpark

May 8-11, 2019 │ Brooklyn, MI, USA │ Michigan International Speedway

The increasing complexity of aerospace products and programs and the growing competitive pressure is facilitating the aggregation of small, medium and large enterprises of certain geographical regions into more integrated and collaborative entities (clusters). Clusters are by their same nature formed by heterogeneous companies, with huge differences not only in size but also for their core competences: such a diversity is a strength of the cluster, but it also increases its complexity. The purpose of this paper is to describe a benchmarking methodology that can be adopted to assess the performances of companies belonging to a cluster from different perspectives: economics and financials, competitive differentiators, specific know how, business strategies, production and logistic effectiveness, quality of core and supporting processes.

The objective of this paper is to develop a robust methodology to study internal combustion (IC) engine block vibrations and to quantify the contribution of combustion pressure loads and inertial loads (mechanical loads) in overall vibration levels. An established technique for noise separation that, until recently, has not been applied to engine noise is Wiener filtering. In this paper, the harmonic part of the overall vibration response of the IC engine block is removed, resulting in a residual broadband response which is uncorrelated to the source signal. This residue of the response signal and the similarly calculated residue of the combustion pressure represent the dynamic portion of their respective raw signals for that specific operating condition (engine speed and load). The dynamic portion of the combustion pressure is assumed to be correlated only to the combustion event.

In any new aircraft development program there are many important design decisions that determine profitability potential. The key to making new aircraft profitable is to design features that will command more money than the cost to provide them within the market's ability to absorb them. The business model in this paper shows how to predict or find: 1) the costs to provide various aircraft features; 2) the values that aircraft buyers place on these features; 3) the amount of money that buyers have to commit to them, 4) the open spaces in the market in which to place new designs and 5) the predicted profits from new designs. In this process, this paper extends previous work on the law of value and demand, which states that attributes determine value; value determines price; and that price determines demand. This four-dimensional, non-negative system hosts a business model that describes the features needed to enable aircraft designs to go from concepts to profitable assembly lines.

New Holland extends agriculture lineup

At its first Tech Day presentation, the company showed off the capable T4 Electric Power light utility tractor and its more powerful sibling, the T7 Methane LNG.

In the last decade, the equivalent circuit model has been utilized to model lithium-ion batteries for electric vehicle applications. Different researchers have proposed a variety of equivalent circuit models from simple to complex ones. The parameters required to describe and build these equivalent circuit models are being extracted from the Hybrid Pulse Power Characterization (HPPC) Test data. This paper describes the process of the extraction of the equivalent circuit model parameters to build the battery models using different test methodologies such as HPPC and its modified versions. It also presents a case study with validated test results for a commercial light weight EV. Firstly, showing how the cell is characterized and then how the pack level cooling is developed to reach the required range based on an aggressive drive cycle.

The intent of this paper is to document comprehensive test-based approach to analyze the door-closing event and associated sound using structural and acoustic loads developed during the event. This study looks into the door-closing phenomenon from the structural interaction point of view between the door and the body of the vehicle. The study primarily focuses on distributing the door and body interaction as discrete multiple structural and acoustic phenomena. It also emphasizes on the structural and acoustic loads developed by the discretized interactions at the interfaces between the door and the body frame. These interfaces were treated to be the load paths from the door to the body. The equivalent structural and acoustic loads were calculated indirectly using the well-known Transfer Path Analysis (TPA) methodology for structural loads and the Acoustic Source Quantification (ASQ) methodology for acoustic loads.

Simulation of interior vehicle structure-borne noise is typically performed with coupled acoustic-structure finite element models. The structure body mesh and acoustic cavity mesh are usually non-conformal, hence finite element solvers use coupling algorithms based on projected areas to develop the connection between the fluid pressure degree of freedom and the structure displacement degrees of freedom. Robust coupling algorithms need to account for various challenges such as separation and penetration of the meshes, openings in the structure mesh, and overlapping panels in the structure mesh. A new coupling algorithm that uses precise area projections addresses these issues and has been implemented in an FE solver code base. The robustness and accuracy solution is demonstrated by comparison to existing methods. Another challenge with acoustic simulation is to join dissimilar acoustic meshes.

“Every industry we serve – from aerospace and automotive to electronic design – is transforming,” Siemens PLM Software officials in Plano, Texas, acknowledge. Siemens PLM Software, too, is undergoing a transformation, having just changed its name to Siemens Digital Industries Software. ...Siemens PLM Software has transformed into Siemens Digital Industries Software, reaffirming its focus on enabling digital industries and merging virtual and real worlds in software, hardware, design, and manufacturing. 

Granta Design second-generation MI:Materials Gateway integration technology provides traceable access to materials data and applications within CAD, CAE, and PLM software.

Companies like Gamma Technologies and Siemens PLM Software are developing simulation tools to help drive the design and development of more powerful, fuel-efficient off-highway engines.

Development of new, competitive vehicles in the context of stricter regulations to reduce greenhouse gas emissions and increase fuel economy is driving OEM of commercial vehicles to further explore options for reducing aerodynamic drag in a real-world setting. To facilitate this in regards to the aerodynamics of a vehicle, virtual design methods such as CFD are often used to compliment experiments to help reduce physical testing time and costs. Once validated against experiments, CFD models can then act as predictive models to help speed development. In this paper, a wind tunnel experiment of a Class 8 truck is compared to a CFD simulation which replicates said experiment, validating the CFD model as a predictive tool in this instance. CFD is then used to evaluate the drag and flow around the vehicle in an open road scenario, and the results between the open road and wind tunnel scenarios are compared.

Flight loads calculations play a fundamental role in the development and certification of an aircraft and have an impact on the structural sizing and weight. The number of load cases required by the airworthiness regulations is in the order of tens of thousands and the analysis must be repeated for each design iteration. On large aircraft, CS-25 explicitly requires taking into account for loads prediction, airframe flexibility, unsteady aerodynamics and interaction of systems and structure, leading to computationally expensive numerical models. Thus there is a clear benefit in speeding-up this calculation process. This paper presents a methodology aiming to significantly reduce the computational time to predict loads due to gust and maneuvers. The procedure is based on Model Order Reduction, whose goal is the generation of a Reduced Order Model (ROM) able to limit the computational cost compared to a full analysis whilst retaining accuracy.

This paper proposes a solution for utilizing multi-body models in nonlinear state observers, to directly estimate the loads acting on the aircraft structure from measurement data of sensors that are commonly available on modern aircraft, such as accelerometers on the wing, rate gyros and strain gages. A high-fidelity aeroelastic multi-body model of a fixed-wing large passenger aircraft is presented, suitable for the monitoring of landing maneuvers. The model contains a modally reduced flexible airframe and aerodynamic forces modeled with a doublet-lattice method. In addition, detailed multi-body models of the nose and main landing gear are attached to the flexible structure, allowing to accurately capture the loads during a hard landing event. It is expected that this approach will make way for embedding non-linear multi-body models, with a high number of degrees of freedom, in state estimation algorithms, and hence improve health monitoring applications.