Progress in Aerospace Sciences最新文献

{"title":"A Scientometric Investigation of Artificial Intelligence for Fluid Mechanics: Emerging Topics and Active Groups","authors":"Weiwei Zhang ,&nbsp;Mingkun Xia ,&nbsp;Jiaqing Kou","doi":"10.1016/j.paerosci.2025.101130","DOIUrl":"10.1016/j.paerosci.2025.101130","url":null,"abstract":"<div><div>Fluid mechanics, as one of the core disciplines of engineering technology, faces dual challenges of theoretical limitations and high computational costs when addressing complex flow problems, promoting the integration of artificial intelligence into the field. This paper systematically reviews the paradigm shift in fluid mechanics driven by AI technologies. Through a bibliometric analysis of 18,776 relevant publications up to May 2025 from the Web of Science Core Collection, we investigated the interdisciplinary intersection between two keyword sets: 22 artificial-intelligence-related terms (including Machine Learning, Neural Networks, Symbolic Regression, Reinforcement Learning, etc.) and 22 fluid-mechanics-related terms (including CFD, Aerodynamics, Fluid-Structure-Interaction, etc.). Our systematic investigation employs a modeling-computation-application framework to analyze this interdisciplinary field, presenting the most active countries, institutions, research groups, and leading scholars while mapping the overall research landscape. Key findings include: (1) From 2000 to 2014, the number of publications and citations grew slowly, but since 2014, both have shown a significant increase. (2) AI applications in fluid mechanics are categorized into modeling (dimensionality reduction and knowledge discovery, machine learning-based turbulence modeling), computation (reduced-order models and feature extraction, machine learning-based CFD simulations), and applications (data fusion and reconstruction, multi-physics and multi-disciplinary coupling, intelligent flow control, aerodynamic shape optimization). (3) The United States dominates foundational research, while China leads in technological applications. (4) Multi-dimensional network analysis—including author, institutional, and national collaboration networks, along with co-citation patterns—reveals a pronounced spotlight effect among leading global universities and research teams. The twenty representative teams selected from them have important value in the academic and engineering fields and deserve further attention. This study provides a clear and comprehensive framework for researchers in the field and offers guidance for future research in intelligent fluid mechanics.</div></div>","PeriodicalId":54553,"journal":{"name":"Progress in Aerospace Sciences","volume":"157 ","pages":"Article 101130"},"PeriodicalIF":11.5,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144570464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review of data-driven computational guidance for unmanned aerospace vehicles","authors":"Shaoming He ,&nbsp;Haowen Luo ,&nbsp;Chang-Hun Lee ,&nbsp;Hyo-Sang Shin ,&nbsp;Antonios Tsourdos","doi":"10.1016/j.paerosci.2025.101129","DOIUrl":"10.1016/j.paerosci.2025.101129","url":null,"abstract":"<div><div>This paper explores the application of data-driven computational guidance in unmanned aerospace vehicles, emphasizing improving the optimality of guidance strategies through data-driven approaches. Unmanned aerospace vehicles are engineered to execute predetermined missions while adhering to a variety of physical and operational constraints. Both their design and operational strategies prioritize the efficient utilization of onboard resources. Data-driven methods can learn from data to develop well-trained neural networks that uncover underlying guidance patterns. These trained neural networks can rapidly generate optimal outputs in response to inputs with minimal computational cost. This characteristic of data-driven methods is particularly well-suited for guidance applications in scenarios with limited onboard computational resources. This paper reviews the state-of-the-art achievements in data-driven computational guidance. Simultaneously, we categorize these advancements based on the role of neural networks within the guidance system, referring to them as neural-end-to-end computational guidance and neural-assisted fixed-structure guidance, respectively. Additionally, the paper highlights several open problems and potential future research directions.</div></div>","PeriodicalId":54553,"journal":{"name":"Progress in Aerospace Sciences","volume":"157 ","pages":"Article 101129"},"PeriodicalIF":11.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of airborne Doppler lidar for wind-sensing","authors":"Rui Ling Yew ,&nbsp;Brett C. Johnson ,&nbsp;Brant C. Gibson ,&nbsp;Abdulghani Mohamed","doi":"10.1016/j.paerosci.2025.101127","DOIUrl":"10.1016/j.paerosci.2025.101127","url":null,"abstract":"<div><div>Turbulence detection and mitigation represent significant challenges in aviation, particularly for Advanced Air Mobility (AAM) systems encountering thermal and mechanicalturbulence at low altitudes. Early detection of such flow disturbances is crucial, as it allows for timely evasive manoeuvres or countermeasures to ensure safe operations. While Doppler light detection and ranging (lidar) sensing has been developed for large passenger aircraft, their size, weight, and power requirements has so far limited their utility in AAM vehicles. This paper reviews advancements in airborne Doppler lidar technology and evaluates the trade-offs which promise to enable the miniaturisation of these sensors. A case study is performed to examine the effects of sensor mass and power consumption on the range of three air taxi configurations. Advancements in optical technology are expected to facilitate the integration of efficient, compact lidar sensors into smaller AAM vehicles, enhancing their ability to detect and respond to turbulence, thereby improving their safety.</div></div>","PeriodicalId":54553,"journal":{"name":"Progress in Aerospace Sciences","volume":"157 ","pages":"Article 101127"},"PeriodicalIF":11.5,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144491668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plasma-enabled additive manufacturing in space: Perspectives, innovative material processing technologies, and emerging challenges","authors":"Igor Levchenko ,&nbsp;Michael Keidar ,&nbsp;Oleg Baranov ,&nbsp;Katia Alexander","doi":"10.1016/j.paerosci.2025.101125","DOIUrl":"10.1016/j.paerosci.2025.101125","url":null,"abstract":"<div><div>Satellite technology is the cornerstone of space exploration. Recently, satellite constellations have emerged as an affordable and efficient way to expand the range of possible missions. Small satellites offer impressive capabilities and can be mass-produced and deployed. However, the long-term growth of the small satellite economy will depend on adopting sustainable product life-cycle management. This includes maximizing the efficiency and effectiveness of space operations by developing functional platforms for repair, servicing, and upgrading of assets after they have been deployed in space. Additive techniques, particularly those enhanced by the use of plasma, could become key tools in this endeavour as the use of charged particles may help overcome some of the challenges presented by the space environment, such as microgravity and extreme temperatures, reducing the risks and costs associated with repairs and upgrades. Our review examines the level of technological readiness of plasma-enhanced and plasma-enabled additive manufacturing technologies in view of their possible use for various in-space satellite repair and servicing tasks, concluding that it is sufficient to initiate its implementation in space. Looking towards the future, key obstacles and benefits of incorporating 3D plasma printing technology in both open space and microgravity environments are explored.</div></div>","PeriodicalId":54553,"journal":{"name":"Progress in Aerospace Sciences","volume":"157 ","pages":"Article 101125"},"PeriodicalIF":11.5,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144336024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Initial results from the first field expedition of UAPx to study unidentified anomalous phenomena","authors":"Matthew Szydagis ,&nbsp;Kevin H. Knuth ,&nbsp;Benjamin Kugielsky ,&nbsp;Cecilia Levy","doi":"10.1016/j.paerosci.2025.101099","DOIUrl":"10.1016/j.paerosci.2025.101099","url":null,"abstract":"<div><div>In July 2021, faculty from the UAlbany Department of Physics participated in a week-long field expedition with the organization UAPx to collect data on UAPs in Avalon, California, located on Catalina Island, and nearby. This paper reviews both the hardware and software techniques which this collaboration employed, and contains a frank discussion of the successes and failures, with a section about how to apply lessons learned to future expeditions. Both observable-light and infrared cameras were deployed, as well as sensors for other (non-EM) emissions. A pixel-subtraction method was augmented with other similarly simple methods to provide initial identification of objects in the sky and/or the sea crossing the cameras’ fields of view. The first results will be presented based upon approximately one hour in total of triggered visible/night-vision-mode video and over 600 h of untriggered (far) IR video recorded, as well as 55 h of (background) radiation measurements. Following multiple explanatory resolutions of several ambiguities that were potentially anomalous at first, we focus on the primary remaining ambiguity captured at approximately 4am Pacific Time on Friday, July 16: a dark spot in the visible/near-IR camera possibly coincident with ionizing radiation that has so far resisted prosaic explanation. We conclude with quantitative suggestions (3–5<span><math><mi>σ</mi></math></span> rules) for serious researchers in the still-maligned field of hard-science-based UAP studies, with an ultimate goal of identifying UAPs without confirmation bias toward mundane/speculative conclusions.</div></div>","PeriodicalId":54553,"journal":{"name":"Progress in Aerospace Sciences","volume":"156 ","pages":"Article 101099"},"PeriodicalIF":11.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144231611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The new science of Unidentified Aerospace-Undersea Phenomena (UAP)","authors":"Kevin H. Knuth ,&nbsp;Philippe Ailleris ,&nbsp;Hussein Ali Agrama ,&nbsp;Eamonn Ansbro ,&nbsp;Phyllis A. Budinger ,&nbsp;Tejin Cai ,&nbsp;Thibaut Canuti ,&nbsp;Michael C. Cifone ,&nbsp;Walter Bruce Cornet Jr. ,&nbsp;Frédéric Courtade ,&nbsp;Richard Dolan ,&nbsp;Laura Domine ,&nbsp;Luc Dini ,&nbsp;Baptiste Friscourt ,&nbsp;Ryan Graves ,&nbsp;Richard F. Haines ,&nbsp;Richard Hoffman ,&nbsp;Hakan Kayal ,&nbsp;Sarah Little ,&nbsp;Garry P. Nolan ,&nbsp;Wesley A. Watters","doi":"10.1016/j.paerosci.2025.101097","DOIUrl":"10.1016/j.paerosci.2025.101097","url":null,"abstract":"<div><div>After decades of dismissal and secrecy, it has become clear that a significant number of the world’s governments take Unidentified Aerospace-Undersea Phenomena (UAP), formerly known as Unidentified Flying Objects (UFOs), seriously—yet still seem to know little about them. As a result, these phenomena are increasingly attracting the attention of scientists around the world, some of whom have recently formed research efforts to monitor and scientifically study UAP. In this paper, we review and summarize approximately 20 historical government studies dating from 1933 to the present (in Scandinavia, WWII, US, Canada, France, Russia, China), several historical private research studies (France, UK, US), and both recent and current scientific research efforts (Ireland, Germany, Norway, Sweden, US). In doing so, our objective is to clarify the existing global and historical scientific narrative around UAP. Studies range from field station development and deployment to the collection and analysis of witness reports from around the world. We dispel the common misconception that UAPs are an American phenomenon and show that UAP can be, and have been, scientifically investigated. Our aim here is to enable future studies to draw on the great depth of prior documented experience.</div></div>","PeriodicalId":54553,"journal":{"name":"Progress in Aerospace Sciences","volume":"156 ","pages":"Article 101097"},"PeriodicalIF":11.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144231750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unidentified aerospace-undersea phenomena (UAP) status and outlook","authors":"Max F. Platzer","doi":"10.1016/j.paerosci.2025.101095","DOIUrl":"10.1016/j.paerosci.2025.101095","url":null,"abstract":"<div><div>This special issue on unidentified aerospace-undersea phenomena (UAP) contains five papers that attempt to provide an overview of the status of past and present UAP events and research projects. It also addresses the question whether the aerospace science and engineering community needs to initiate a UAP monitoring effort that is based on rigorous scientific evaluation criteria.</div></div>","PeriodicalId":54553,"journal":{"name":"Progress in Aerospace Sciences","volume":"156 ","pages":"Article 101095"},"PeriodicalIF":11.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144231609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimates of radiative energy values in ground-level observations of an unidentified aerial phenomenon: New physical data","authors":"Jacques F. Vallée ,&nbsp;Luc Dini ,&nbsp;Geoffrey Mestchersky","doi":"10.1016/j.paerosci.2025.101098","DOIUrl":"10.1016/j.paerosci.2025.101098","url":null,"abstract":"<div><div>An exceptional observation of an anomalous object, recorded as ‘unidentified’ by the US Air Force and in the1969 final report of the University of Colorado (“Condon”) study of UAPs, has been re-examined by a Franco-American scientific team.</div><div>The observation took place on the evening of December 30, 1966, on an isolated highway traversing a forest near Haynesville, Louisiana. Early in 1967 the main witness, a professor of atomic physics named Louie A. Galloway, reported the case to Project Blue Book of the USAF. Pro-active investigation by one of the authors (JV) brought it to the attention of Professor Edward Condon, himself a noted atomist who had worked under Project Manhattan. Dr. Condon and his team had just begun an official re-examination of UFO (UAP) phenomena under funding of the US Air Force.</div><div>The case, which centered on a well-defined luminous object at ground level, led to energy estimates from 500 to 1400 MW, in the range of a small modern nuclear power plant. Significantly, it was one of a number of cases carried as ‘Unidentified’ in Dr. Condon's final report to the National Academy of Sciences in 1969.</div><div>Subsequent to that Academy report, significant work was continued at the site by civilian investigators who confirmed the data, augmented by night photography flights. The team returned to the area with the primary witness, located the exact place of observation and gathered new data, notably about the nature of burns evidenced on the trees, which had not been available to Dr. Condon and his assistants.</div><div>Samples of the burned and intact bark were obtained by our own team, and they were preserved until it became possible to properly analyze the material.</div><div>The burn analysis data presented here was obtained at the laboratories of the French Atomic Energy Commission in Saclay, France. We present our results with the understanding that the study will benefit from further discussion within the larger scientific community.</div></div>","PeriodicalId":54553,"journal":{"name":"Progress in Aerospace Sciences","volume":"156 ","pages":"Article 101098"},"PeriodicalIF":11.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144231610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The state of hybrid artificial intelligence for interstellar missions","authors":"Alex Ellery","doi":"10.1016/j.paerosci.2025.101100","DOIUrl":"10.1016/j.paerosci.2025.101100","url":null,"abstract":"<div><div>Interstellar missions will require a high degree of autonomy mediated through artificial intelligence (AI). All interstellar missions are characterised by 50-100-year transits to extrasolar systems. High system availability demands that interstellar spacecraft are self-repairable imposing significant demands on onboard intelligence. We review the current status of artificial intelligence to assess its capabilities in providing such autonomy. In particular, we focus on hybrid AI methods as these appear to offer the richest capabilities in offsetting weaknesses inherent in paradigmic approaches. Symbolic manipulation systems offer logical and comprehensible rationality with predictable behaviours but are brittle beyond their specific applications (a charge that may be levelled at neural networks unless the transfer learning problem can be resolved). More modern approaches to expert systems include Bayesian networks that incorporate probabilistic treatment to accommodate uncertainty. Artificial neural networks are fundamentally different. They are opaque to analysis but potentially offer greater adaptability in application by virtue of their ability to learn. Indeed, deep machine learning is a variation on neural networks with unsupervised neural front ends and supervised neural back ends. Reinforcement learning offers a promising approach for learning directly from the environment. There are inherent weaknesses in neural approaches regarding their hidden mechanisms rendering their distributed representations opaque to analysis. Hybridising symbolic processing techniques with artificial neural networks appears to offer the advantages of both. Human cognition appears to implement both neural learning and symbolic processing. There are several approaches to such hybridisation that we explore including knowledge-based artificial neural networks, fuzzy neural networks, Bayesian methods such as Markov logic networks and genetic methods such as learning classifier systems. Markov logic networks propose a natural correlation between Bayesian probability and neural weights but mapping representation of symbols into switching neurons is less clear (though vector symbolic architectures present an approach) while learning classifier systems are reinforcement learning methods that are promising for interacting with the physical world. We conclude that current AI may not yet be up to the task of interstellar transits and flybys let alone for physical interaction with unknown planetary environments. Certainly, AI is incapable of interactive encounters with extraterrestrial intelligence.</div></div>","PeriodicalId":54553,"journal":{"name":"Progress in Aerospace Sciences","volume":"156 ","pages":"Article 101100"},"PeriodicalIF":11.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144231613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the need for rigorous scientific research on unidentified aerial phenomena (UAP)","authors":"Max F. Platzer","doi":"10.1016/j.paerosci.2025.101096","DOIUrl":"10.1016/j.paerosci.2025.101096","url":null,"abstract":"","PeriodicalId":54553,"journal":{"name":"Progress in Aerospace Sciences","volume":"156 ","pages":"Article 101096"},"PeriodicalIF":11.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144231603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}