Progress in Aerospace Sciences最新文献

The pressure distribution on a surface, over which a wall-jet is blowing, is altered by the wall jet's entrainment. It renders the boundary layer approximation – that justifies the use of an inviscid flow solution to determine the pressure over the surface – invalid. Thus, in order for Active Flow Control (AFC) by blowing to become a viable technology, some of the preconceptions associated with Boundary Layer Control (BLC) for many decades must be discarded. In particular, the momentum coefficient used to characterize BLC should be replaced by another variable that represents a conserved quantity that is independent of specific installations. Injected momentum is a vector quantity whose effect on a surface like a wing depends on its specific design, location, and orientation. Therefore, a new approach is proposed based on the AFC system's power consumption and its mass flowrate. Moreover, all flow installations suffer from unavoidable losses, which must be determined in an unambiguous manner, allowing for an impartial comparison of AFC systems. The present article provides examples from tests carried out at various universities and at NASA, exposing some popular misconceptions. It does not provide a design tool due to the complexity of the needed approach, but a method to assess the efficacy and efficiency of an evolving platform that includes AFC is suggested.

This paper reviews several decades’ worth of research on the topic of slat noise arising from high-lift systems of commercial aircraft. A high-lift system is commonly used for providing additional lift by deploying the leading-edge slat(s) and trailing-edge flap(s) during the takeoff and landing phases of flight. Slat noise can be one of the main sources of airframe noise, along with the deployed landing gear, and airframe noise can be dominant during the approach phase when aircraft engine noise is reduced. This review synthesizes historical investigations related to the generation/radiation of slat noise, including both experimental and numerical approaches. Characteristics of noise and corresponding generation mechanisms have been well investigated, and numerical tools have been developed to predict noise levels. Scaling laws to map the results from models to real aircraft are proposed based on the combined analytical and experimental investigations. Noise-reduction technologies are also discussed.

Performances are a key concern in aerospace vehicles, requiring safer structures with as little consumption as possible. Composite materials replaced aluminum alloys even in primary aerospace structures to achieve higher performances with lighter components. However, random events such as low-velocity impacts may induce damages that are typically more dangerous and mostly not visible than metals. The damage tolerance (DT) approach is adopted for the fatigue design of aircraft, but fracture mechanisms and propagation of failure prediction in composite structures are much more challenging. Consequently, the DT approach is still costly for these types of structures. It can be achieved only through expensive experimental testing and a drastic reduction of allowable stress levels and maintenance intervals by applying scattering factors due to the uncertainties involved in their original estimations. Structural health monitoring (SHM) systems deal mainly with sensorised structures providing signals related to their “load and health status” to reduce maintenance and weights. At the same time, the use of Deep Neural Networks (DNNs) based on strategic engineering criteria, for instance, may represent an effective and efficient analysis tool to promote faster data analysis and classification. In the field of aircraft maintenance, this approach may lead, for example, to a faster awareness of an aircraft/fleet situation or predict failures. Deep learning-based networks provide automatic feature extraction at different levels of abstraction. With the universal function approximation property of neural networks, it learns the inverse mapping from input space (signals) to target space (damage classes). Starting from the well-established Structural Health Monitoring (SHM) technologies, a network of distributed sensors embedded throughout the structure could be used for real-time structural monitoring and data acquisition. Structural data will constitute an enormous amount of information that can be adequately filtered with the help of specific DNNs designed and trained for the structural context and aimed to classify and identify significant parameters. The authors have collaborated for some years to collect wave propagation signals through experimental tests and validated numerical models of healthy and damaged composite structures, and developed machine learning algorithms (mainly dense and convolutional neural networks) aimed at signal classification and analysis for damage detection and localization. This paper presents a brief review of relevant works about SHM employing Machine Learning methodologies and summarizes the most promising approaches developed during the last years jointly by the two research groups and presents a critical analysis of obtained results and subsequent future activities.

Review and discussion of substantive to revolutionary concepts to enable a commercially viable, societally acceptable supersonic transport. Issues addressed include economic viability, take off noise, sonic boom, emissions and frontier aircraft configurations. Solution spaces include an enabler for most of the issues, which is doubling the lift-to-drag ratio. Approaches in most cases require serious further research for application to and optimization of frontier aircraft configurations.

Since the birth of bio-inspired flapping-wing micro air vehicles, a controversial topic, i.e., whether and to what extent a flapping wing can outperform conventional micro rotors, has existed in the field of micro-to pico-scale unmanned aircraft. However, instead of answering this debate, an alternative idea that combines the flapping-wing and rotary-wing layouts was proposed and has been extensively studied over the last ten years. By merging bionic features of flapping wings into micro rotors, this novel layout, i.e., flapping rotary wing (FRW), can maintain autorotation with no driving torque and achieve both a superb lift generation and a moderate efficiency at a Reynolds number between 10³ and 10⁴, presenting an additional choice for micro air vehicles when facing a task to balance the payload and energy cost. As the first review of FRW, this paper overviews the concept, bionic features, aerodynamic principles, and development of flyable prototypes since 2010, from fundamental aerodynamic mechanisms to key points in prototype design, including wing structure, actuator, transmission system, energy source, etc. The advantages and disadvantages of this novel layout over conventional flapping wings and micro rotors are discussed. Four challenging directions are then suggested to improve the flight performance of this layout and thus boost its application in military and civilian fields.

The elastic strain energy-driven thin-walled deployable composite structures, characterized by their integration of structure and functionality, have attracted considerable attention in the field of space applications. These structures utilize the stored strain energy accumulated during the folding process to achieve elastic deployment. Significant progress has been made in the understanding of deformation mechanisms, modeling, design, optimization, and applications of such structures based on existing research. This review critically discusses over 300 papers from the past few decades, providing a comprehensive exploration of the development of three representative types of deployable composite structures: deployable composite hinges, booms, and reflectors. Specifically, it starts by reviewing the structural design, functional mechanisms, theories, finite element modeling methods and experimental investigations for these three types of structures. It then introduces optimization design methods and their applications in deployable composite structures. Additionally, specific practical application cases of deployable composite structures are discussed. Finally, future challenges and prospects for deployable composite structures are outlined. This paper serves as a valuable reference and inspiration for the design and application of deployable composite structures. It is expected to promote further advancements in this field.

Trends in space technology development and rapidly increasing traffic in outer space are likely to lead to the emergence of a market for services for the removal of large debris objects to disposal orbits. The commercial benefits of Active Debris Removal missions are possible when multiple objects are removed by a single spacecraft-collector that flies between targets in an optimal sequence, trying to achieve a rational ratio between mission duration and fuel costs. Given the size of the large debris population, selecting candidates for removal and optimizing such a mission is a non-trivial task.

In this paper, a review of solutions, which are proposed in 65 publications between 2010 and 2023 for the problem of path planning between space debris objects in low orbits, is performed. These solutions could be categorized into three main types. The search for transfer chains in the first type of approaches is based solely on combinatorics, supplemented by various heuristics as required. In the second case, combinatorial-heuristic algorithms fully or partially utilize the secular effects of the Earth's polar compression. Solutions of the third type are based only on the use of precession of the Right Ascension of the Ascending Node of the orbit. For each analyzed work, the following information is given: objects of study, maneuvering scheme for a flight between two successive objects, method of choosing the transfer sequence, and main results. At the end of this paper, a subjective general evaluation of the analyzed works is proposed.

In order to deepen the reader's understanding of the problem of large space debris removal, this review also provides background information from related fields. The reasons for the growth of observable fragments in near-Earth space and the need to remove large objects to disposal orbits are shown. The history of experiments aimed at the development of ADR technology is given. The article contains a large number of explanatory illustrations.

In response to escalating environmental concerns and stringent economic constraints, there is an urgent need to develop aircraft technologies and configurations that substantially enhance efficiency. A prominent trend in aircraft design aimed at minimizing lift-induced drag, improving fuel efficiency, and mitigating emissions is the adoption of increased wing Aspect Ratio (AR). This paper examines the evolution and current advancements in High Aspect Ratio Wing (HARW) and Ultra-High Aspect Ratio Wing (UHARW) configurations for next-generation transport aircraft. Beginning with a historical overview of wing AR in transport, the paper examines the progress in designing both conventional and novel HARW/UHARW configurations. It reviews a range of promising concepts, such as strut-braced wing, truss-braced wing, twin-fuselage, and folding wingtips, for their potential in HARW applications. The paper emphasizes tailored conceptual design methods and tools specifically developed for HARW/UHARW configurations. It provides an in-depth analysis of preliminary design approaches for HARW aircraft, systematically covering aspects including aerodynamic, aeroelastic, aerostructural, and experimental designs. Key insights from leading-edge research are distilled, highlighting the significant advancements and pinpointing the current challenges in the field. The comprehensive review underscores the critical role of HARW/UHARW in enhancing aircraft performance, particularly in fuel efficiency and environmental impact, setting the stage for future transformative developments in aircraft efficiency.

Recent advances in Artificial Intelligence (AI) and Cyber-Physical Systems (CPS) for aerospace applications have brought about new opportunities for the fast-growing satellite industry. The progressive introduction of connected satellite systems and associated mission concepts is stimulating the development of intelligent CPS (iCPS) architectures, which can support high levels of flexibility and resilience in an increasingly congested near-Earth space environment. The need for higher levels of automation and autonomy in satellite operations has stimulated numerous research initiatives in recent years, focusing on the progressive enhancement of systemic performance (e.g., addressing safety, integrity and cyber-physical security metrics) and associated monitoring/augmentation approaches that can support Trusted Autonomous Satellite Operations (TASO). Despite these advances, in most contemporary satellite platforms, autonomy is restricted to a specific set of rules and cases, while the transition to TASO requires a paradigm shift in the design of both space vehicles and ground-based systems. In particular, the use of AI is seen as an essential enabler for TASO as it enhances system performance/adaptability and supports both predictive and reactive integrity augmentation capabilities, especially in Distributed Satellite Systems (DSS). This article provides a critical review of AI for satellite operations, with a special focus on current and likely future DSS architectures for communication, navigation and remote sensing missions. The aim is to identify key contemporary challenges and opportunities associated with space iCPS design methodologies to enhance the performance and resilience of satellite systems, supporting the progressive transition to TASO. A comprehensive review of relevant AI techniques is presented to critically assess the potential benefits and challenges of each method for different space applications. After describing the specificities of DSS and the opportunities offered by iCPS architectures, the co-evolution of space and control (ground and on-board) segments is highlighted as an essential next step towards enabling TASO. As an integral part of this evolutionary approach, the most important legal and regulatory challenges associated with the adoption of AI in TASO are also discussed.

The utilization of hybrid electric propulsion concept in aviation offers a viable solution to address the limitations posed by the relatively low energy density of batteries in fully electric aviation. These hybrid systems enable the aircraft to achieve a significant range while simultaneously minimizing carbon emissions. While the individual components of a Hybrid Electric Propulsion (HEP) system, such as electric motors and batteries, are designed with high efficiency, their integration presents a significant challenge in the realm of thermal management. Designing an efficient system for managing the substantial waste heat generated by heat sources and effectively transferring it to heat sinks during various flight phases is a complex task. This challenge becomes even more critical as the design must adhere to system weight limits and prioritize aviation safety considerations. In this review article, we performed a systematic review of the challenges related to the key elements in a thermal management system. These elements encompass every component or subsystem that contributes to the thermal management of a generic hybrid-electric propulsion system. This includes electric motors and generators, batteries, heat exchangers, power transmission systems, power distribution systems, storages, fuel cells, cooling fluids and pipes, control system, pumps and fans. Following the identification of the challenges, the paper provides a comprehensive summary of the existing solutions that have been offered and pursued by the community to address the challenges. Furthermore, the paper also discusses emerging technologies related to each element, highlighting their potential in overcoming these challenges.