Progress in Aerospace Sciences最新文献

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.

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.

Reducing the sonic boom to a community-acceptable level is a fundamental challenge in the configuration design of the next-generation supersonic transport aircraft. This paper conducts a survey of recent progress in developing efficient low-boom design and optimization methods, and provides a perspective on the state-of-the-art and future directions. First, the low- and high-fidelity sonic boom prediction methods used in metric of low-boom design are briefly introduced. Second, efficient low-boom inverse design methods are reviewed, such as the classic Jones–Seebass–George–Darden (JSGD) method (and its variants), the high-fidelity near-field-overpressure-based method, and the mixed-fidelity method. Third, direct numerical optimization methods for low-boom designs, including the gradient-, surrogate-, and deep-learning-based optimization methods, are reviewed. Fourth, the applications of low-boom design and optimization methods to representative low-boom configurations are discussed, and the challenging demands for commercially viable supersonic transports are presented. In addition to providing a comprehensive summary of the existing research, the practicality and effectiveness of the developed methods are assessed. Finally, key challenges are identified, and further research directions such as full-carpet-low-boom-driven multidisciplinary design optimization considering mission requirements are recommended.

The history of satellite development is at an inflection point: around half of all countries have made and launched satellites, while another half has not. In this context, the time appears right to take stock of lessons learnt from the development of country-first domestic satellites. These are defined as the first to have been designed, assembled, integrated, and/or tested with significant input from local engineers. This paper reviews, for the first time, the genealogy of the 90 country-first domestic satellites launched into orbit to date. The comprehensive, trans-disciplinary analysis is based on an extensive literature review in multiple languages. Firstly, a family tree of country-first domestic satellites is constructed, mapping out important stakeholders and lineages. Four major generations are identified. Although country-first domestic satellites are often associated with domestic identity, they are without exception the product of international collaboration and technological exchanges. In parallel, a growing global market for satellite development and launch services has played an increasingly important role in their development even in the absence of official country-to-country collaborations. Secondly, the birth traits, life, death, and legacy of such satellites is reviewed in detail. Sustainability of the Earth’s orbital environment has typically not been prioritised by mission teams. Most countries having developed a first domestic satellite have also developed a second, but there have been more one-off firsts since the 1990s: microsatellites and CubeSats can be used to test the waters of space engineering without having to make a big commitment. Looking to the future, access to a domestic satellite is becoming easier and easier. The challenge is instead shifting towards ensuring that such an initiative is actually aligned with domestic industry, technologies, and STEM education, as well as sustainability of the Earth’s orbital environment. Long-term planning and vision are important in this regard. It is hoped that this review paper will provide a useful reference point for space historians, policymakers, and the pioneers of diverse new satellite missions.

This review article offers an in-depth analysis of cooperative motion planning and control in aerial-ground autonomous systems, emphasizing their methods and applications. It explores the integration of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs), focusing on their synchronized planning and control mechanisms that enable efficient task execution in various settings, such as disaster response, environmental monitoring, and urban surveillance. The article addresses the motion planning strategies, and control mechanisms, while also highlighting the challenges and future trends in this domain. It serves as a comprehensive resource, shedding light on both the potentials and limitations of these systems, thereby providing valuable insights for researchers and practitioners in the field of autonomous systems.

Aero-optical effects have received increasing attention in recent decades with the continuous development of high-speed missiles’ imaging guidance systems, airborne laser systems, and laser communication systems. Numerous experiments and engineering practices have shown that the aero-optical effects of the supersonic turbulent shear layer can reveal the essential characteristics of general aero-optical effects. Practical engineering problems related to aero-optical effects are often the result of the superposition of the aero-optical effects of multiple shear layers. This paper mainly studies the shear layers represented by the supersonic turbulent boundary layers, mixing layers, and wall jets. The latest research progress on aero-optical effects is summarized to provide a reference for suppressing aero-optical distortion through flow control and adaptive optical correction.

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.