Progress in Aerospace Sciences最新文献

To ensure the secure operation of space assets, it is crucial to employ ground and/or space-based surveillance sensors to observe a diverse array of anthropogenic space objects (ASOs). This enables the monitoring of abnormal behavior and facilitates the timely identification of potential risks, thereby enabling the provision of continuous and effective Space Situational Awareness (SSA) services. One of the primary challenges in this endeavor lies in optimizing the tasking of surveillance sensors to maximize SSA capabilities. However, the complexity of the space environment, the vast number of ASOs, and the limitations imposed by available sensor resources present significant obstacles to effective sensor management. To tackle these challenges, various sensor tasking methods have been developed over the past few decades. In this paper, we comprehensively outline the fundamental characteristics of sensor tasking missions, and later examine the corresponding objective functions and algorithms employed for efficient optimization, respectively. Furthermore, we explore the practical application of sensor tasking methods in diverse organizations and provide insights into potential directions for future research, aiming to stimulate further advancements in this field.

The Cislunar region is crucial for expanding human presence in space in the forthcoming decades. This paper presents a comprehensive review of recent and anticipated Earth–Moon missions, and ongoing space domain awareness initiatives. An introduction to the dynamics as well as periodic trajectories in the Cislunar realm is presented. Then, a review of modern Cislunar programs as well as smaller missions are compiled to provide insights into the key players pushing towards the Moon. Trends of Cislunar missions and practices are identified, including the identification of regions of interest, such as the South Pole and the Near-rectilinear halo orbit. Finally, a review of the current state and short-comings of space domain awareness (SDA) in the region is included, utilizing the regions of interest as focal points for required improvement. The SDA review is completed through the analysis of the Artemis 1 trajectory.

Concentrated vortex flows contribute to the aerodynamic performance of aircraft at elevated load conditions. For military interests, the vortex flows are exploited at maneuver conditions of combat aircraft and missiles. For transport interests, the vortex flows are exploited at takeoff and landing conditions as well as at select transonic conditions. Aircraft applications of these vortex flows are reviewed with a historical perspective followed by a discussion of the underlying physics of a concentrated vortex flow. A hierarchy of computational fluid dynamics simulation technology is then presented followed by findings from a capability survey for predicting concentrated vortex flows with computational fluid dynamics. Results are focused on military and civil fixed-wing aircraft; only limited results are included for missiles, and rotary-wing applications are not assessed. Opportunities for predictive capability advancement are then reported with comments related to digital transformation interests. A hierarchical approach that merges a physics-based perspective of the concentrated vortex flows with a systems engineering viewpoint of the air vehicle is also used to frame much of the discussion.

The academic community has extensively studied fault management in dynamical and cyber-physical systems, leading to the development of various model-based and data-driven/learning-enabled methods. Although these advanced designs show promise for improving conventional practices in aircraft systems, there is a noticeable disparity between academic methodologies and the specific needs of the aviation industry. The paper begins with an examination of the current practices within the aviation industry alongside the academic state of the art. It highlights commonly overlooked issues that hinder the transition from laboratory development to practical flight applications. Looking ahead, the paper anticipates evolving needs driven by the transition towards greater autonomy and intelligence within connected and distributed cyber-physical flight environments. This includes the emerging trend towards the introduction of Single Pilot Operations (SPO). The paper presents an outline of a combined model-based/data-driven vision, under human oversight, to navigate this complex transition.

Compared with traditional deflagration-based systems, detonation-based propulsion systems offer significant potential benefits in terms of efficiency and specific impulses in the field of advanced aerospace propulsion technologies. However, the successful implementation of these technologies faces several key challenges, particularly in achieving reliable, stable, and robust detonation wave propagation. This paper examines the use of Jet in Cross-Flow (JICF) as a means of enhancing detonation propulsion performance. The fundamental principles of the three main detonation propulsion systems are first outlined, along with the primary techniques employed to stimulate detonation wave propagation, such as the use of solid and fluidic obstacles. This paper provides an in-depth analysis of how JICF can be leveraged to improve the deflagration-to-detonation transition (DDT) and overall detonation propulsion. The influences of key JICF parameters, including the jet delay time, pressure, temperature, nozzle width, and location, are investigated in detail. The underlying flow physics and mechanisms by which the JICF enhances detonation are also explored, encompassing the formation of precursor shock waves, flow instabilities, flame evolution dynamics, etc. Finally, the practical application of the JICF in different detonation engines is discussed, highlighting the benefits it can provide in terms of improved operation, efficiency, and reliability. The current research challenges and future research directions for the application of JICF in detonation propulsion are discussed. The results present a thorough and up-to-date assessment of the state-of-the-art in utilizing JICF to advance the development of high-performance detonation-based propulsion systems.

This paper presents a comprehensive review of recent advancements in modelling approaches, design strategies, and testing techniques applied to friction damping in turbomachinery. It critically evaluates experimental testing, design processes, and optimisation studies, along with the latest developments in numerical modelling techniques. The review begins with an overview of vibration mitigation methods and the historical development of friction dampers for bladed disk systems. Subsequent sections explore research efforts aimed at enhancing numerical and simulation modelling capabilities, encompassing contact friction models, reduced-order modelling methods, and numerical solvers suitable for real-world applications and industrial high-fidelity models. The paper also delves into available testing rigs for experimental validation and characterisation of various friction damper types, as well as the literature on uncertainty quantification in friction damping. It concludes by highlighting recent trends in novel concepts, modelling techniques, and testing technologies shaping the design of next-generation friction dampers.

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.

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.

In recent years, high-order discontinuous Galerkin (DG) methods have emerged as an attractive approach for numerical simulations of compressible flows. This paper presents an overview of the recent development of DG methods for compressible flows with particular focus on hypersonic flows. First, we survey state-of-the-art DG methods for computational fluid dynamics. Next, we discuss both matrix-based and matrix-free iterative methods for the solution of discrete systems stemming from the spatial DG discretizations of the compressible Navier–Stokes equations. We then describe various shock capturing methods to deal with strong shock waves in hypersonic flows. We discuss adaptivity techniques to refine high-order meshes, and synthetic boundary conditions to simulate free-stream disturbances in hypersonic boundary layers. We present a few examples to demonstrate the ability of high-order DG methods to provide accurate solutions of hypersonic laminar flows. Furthermore, we present direct numerical simulations of hypersonic transitional flow past a flared cone at Reynolds number $10.8\times 10^6$, and hypersonic transitional shock wave boundary layer interaction flow over a flat plate at Reynolds number $3.97\times 10^6$. These simulations run entirely on hundreds of graphics processing units (GPUs) and demonstrate the ability of DG methods to directly resolve hypersonic transitional flows, even at high Reynolds numbers, without relying on transition or turbulence models. We end the paper by offering our perspectives on error estimation, turbulence modeling, and real gas effects in hypersonic flows.

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.