Low-Noise Design of Medium-Range Aircraft for Energy Efficient Aviation

Promising low-noise aircraft architectures have been identified over the last few years at DLR. A set of DLR aircraft concepts was selected for further assessment in the context of sustainable and energy-efficient aviation and was established at the TU Braunschweig in 2019, the Cluster of Excellence for Sustainable and Energy-Efficient Aviation (SE2A). Specific Top-Level aircraft requirements were defined by the cluster and the selected DLR aircraft designs were improved with focus on aircraft noise, emissions, and contrail generation. The presented paper specifically addresses the reduction of aviation noise with focus on noise shielding and modifications to the flight performance. This article presents the state of the art of the simulation process at DLR and demonstrates that the novel aircraft concepts can reduce the noise impact by up to 50% in terms of sound exposure level isocontour area while reducing the fuel burn by 6%, respective to a conventional aircraft for the same mission. The study shows that a tube-wing architecture with a top-mounted, forward-swept wing and low fan pressure ratio propulsors installed above the fuselage at the wing junction can yield significant noise shielding at improved low-speed performance and reduce critical fuel burn and emissions.

Noise shielding surrogate models using dynamic artificial neural networks

The optimal design methodologies in aeronautics are known to be constrained by the computational burden required by direct simulations. Due to this reason, the development of efficient metamodelling techniques represents nowadays an imperative need for the designers. In fact, surrogate models has been demonstrated to significantly reduce the number of high-fidelity evaluations, thus alleviating the computing effort. Over the last years, the aeronautical designers community has switched from a design approach predominantly based on direct simulations to an extensive use of metamodels. Recently, to further improve the efficiency, several dynamic approaches based on parameters self-tuning have been developed to support the metamodel construction. This work deals with the use of surrogate models based on Artificial Neural Network for the noise shielding of unconventional aircraft configurations. Here, the insertion loss field of the a Blended Wing Body is reproduced by means of advanced machine learning techniques. The relevant framework is the calculation of the noise emitted by innovative aircraft configurations by means of suitable corrections of existing well-assessed noise prediction tools. The self-tuning algorithm has demonstrated to be accurate and efficient, and the observed performance discloses the possibility to implement numerical strategies for the reliable and robust unconventional aircraft optimal design

Uncertainty Analysis for Low-Cost Transformer-Type Inductive Conductivity Sensors

Transformer-type inductive conductivity sensors (TICS) are the industry standard for long-term conductivity measurement in fluids. This paper analyzes the potential of TICS as a low-cost alternative to the cost-effective type of conductivity cells by an implementation with reduced complexity. Sensor characteristics and performance in comparison to high precision sensor are described in the study. Linearity and hysteresis error in measurement, reproducibility and permeability influenced by the temperature change are quantified through the experiments. The results were interpreted in regard to core material, geometric properties and noise shielding. The study presented in this paper provides a better understanding of performance and uncertainty characteristics in order to improve the design of low-cost transformer-type inductive conductivity sensors.

Changes in the Soundscape of the Public Space Close to a Highway by a Noise Control Intervention

The deployment of measures to mitigate sound during propagation outdoors is most often a compromise between the acoustic design, practical limitations, and visual preferences regarding the landscape. The current study of a raised berm next to a highway shows a number of common issues like the impact of the limited length of the noise shielding device, initially non-dominant sounds becoming noticeable, local drops in efficiency when the barrier is not fully continuous, and overall limited abatement efficiencies. Detailed assessments of both the objective and subjective effect of the intervention, both before and after the intervention was deployed, using the same methodology, showed that especially the more noise sensitive persons benefit from the noise abatement. Reducing the highest exposure levels did not result anymore in a different perception compared to more noise insensitive persons. People do react to spatial variation in exposure and abatement efficiency. Although level reductions might not be excessive in many real-life complex multi-source situations, they do improve the perception of the acoustic environment in the public space.

Sound quality assessment of a medium-range aircraft with enhanced fan-noise shielding design

The investigation of technologies that can improve the sustainability of the air transport system requires not only the development of alternative fuel concepts and novel vehicle technologies but also the definition of appropriate assessment strategies. Regarding noise, the assessment should reflect the situation of communities living near airports, i.e., not only addressing sound levels but also accounting for the annoyance caused by aircraft noise. For this purpose, conventional A-weighted sound pressure level metrics provide initial but limited information as the level- and frequency-dependency of the human hearing is accounted for in a simplified manner. Ideally, subjective evaluations are required to adequately quantify the perceived short-term annoyance associated with aircraft noise. However, listening tests are time-consuming and not suitable to be applied during the conceptual aircraft design stage, where a large solution space needs to be explored. Aiming at bridging this gap, this work presents a methodology for the sound quality assessment of computational aircraft noise predictions, which is hereby conducted in terms of objective psychoacoustic metrics. The proposed methodology is applied to a novel medium-range vehicle with fan noise shielding architecture during take-off and landing procedures. The relevance of individual sound sources, i.e., airframe and engine noise contributions, and their dependencies on the aircraft architecture and flight procedures are assessed in terms of loudness, sharpness, and tonality. Moreover, the methodology is steered towards community noise assessment, where the impacts on short-term annoyance brought by the novel aircraft design are analysed. The assessment is based on the modified psychoacoustic annoyance, a metric that provides a quantitative description of human annoyance as a combination of different hearing sensations. The present work is understood as an essential step towards low-annoyance aircraft design.

Multifunctional Magnetic Nanocomposite Encapsulant for EMI Shielding in Power Electronics

As power densities and switching frequencies dramatically increase, a potential area of advancement for encapsulant technologies is to utilize them to mitigate electromagnetic interference, which directly impacts device efficiency at high switching frequencies; one promising topic involves the creation of magnetic nanoparticle-enhanced encapsulants, with intrinsic sensitivity to electromagnetic fields that could provide additional noise shielding for power electronic devices. A nanocomposite encapsulant was created by directly incorporating magnetic iron oxide nanoparticles into a silicone matrix. The nanoparticles, with an average size of 100 nm, achieved excellent dispersion in the silicone polymer, even at high concentrations, with no additive or surfactants needed to improve stability. Material testing, including thermo mechanical analysis and thermal conductivity measurements were performed to determine if the addition of the nanoparticles altered the thermal or mechanical properties of the base silicone. The nanocomposites at different concentrations observed thermal conductivities of 0.5 W/m-K and coefficient of thermal expansions of 280 ppm/°C, which resembles that of normal silicone; however, the addition of the iron oxide reduced the dielectric breakdown strength of the silicone matrix exponentially with respect to concentration from 20 kV/mm to 3 kV/mm. Further efforts to optimize the dielectric properties of the nanocomposites with respect to the nanoparticle loading is necessary in order to directly apply this technology; however, the results indicate magnetic nanocomposites could be a potential avenue towards mitigating electromagnetic interference in power devices.