Search Results (14)

Hybrid propulsion systems have become a focal point of low-carbon aviation research due to their advantages in energy savings, emissions reduction, and noise abatement. This study develops an integrated design methodology for hybrid propulsion systems for aircraft, incorporating multidisciplinary algorithms to establish an overall performance model. Building on this model, a comprehensive aircraft design platform was constructed, and its simulation capabilities were validated. Focusing on the mission requirements of a 180-seat narrow-body airliner, this study analyzed and compared the characteristics of three hybrid propulsion architectures, optimized their design schemes, and evaluated the key technologies for each architecture. A sensitivity analysis was conducted for critical technologies within the turboelectric architecture. The results indicate that, based on current data and future projections, a turboelectric system featuring batteries with a specific energy of 500 Wh/kg and installed motor power of 3 MW demonstrates superior performance, reduced fuel consumption, and no additional energy storage burden, making it the preferred propulsion solution. Furthermore, enhancing the utilization of aft-mounted fans and increasing the power blending coefficient can improve system performance. However, the maximum power blending coefficient is constrained to 27.25% by the specific motor power capacity. Full article

Aircraft hangars are essential in the aviation industry, providing crucial maintenance and protection for aviation assets. However, constructing these upper structures involves significant safety risks. Due to the complexity of upper structure construction, it is vital to prioritize safety to prevent workplace accidents. Ensuring construction safety is not only crucial for operational efficiency but also aligns with several Sustainable Development Goals (SDGs), such as Decent Work and Economic Growth (SDG 8) and Industry, Innovation, and Infrastructure (SDG 9). This study assesses the safety risks associated with hangar construction using activity-based failure modes and effects analysis (FMEA). A mixed-method approach is adopted, incorporating insights from five construction safety experts and data from 100 individuals directly involved in the upper structure construction of the spaceframe hangar. Descriptive data analysis was employed to establish the foundation for computing risk priority numbers (RPNs) using the FMEA technique. Three primary activities were identified as having extremely high risks: workers falling from heights during the lifting and erection of the space frame, workers falling from heights during basement excavation while installing floor slab formwork, and workers falling from heights during the casting of floor slabs. These activities present safety risks with RPN values ranging from 64 to 100, including incidents of workers falling from heights and being struck by materials. This study serves as a crucial reference for formulating construction safety plans that encompass risk identification, assessment, and control measures. The findings provide essential insights into various safety hazards in construction projects, particularly those related to military infrastructure. By identifying and assessing these risks, the research facilitates the development of more effective and comprehensive safety protocols. Implementing the recommended control measures ensures a proactive approach to mitigating potential accidents and injuries. Consequently, this research contributes to academic knowledge and enhances safety standards and practices within the construction industry. Full article

The applications of Artificial Intelligence (AI) in the airport industry are significantly transforming operational efficiency, safety, and passenger experiences. This study investigates the integration of AI within aviation construction projects, with a focus on the United Arab Emirates (UAE). While AI technologies such as facial recognition, IoT, and biometric systems have advanced airport security and operations, their use in construction project management remains limited. A survey was conducted among 101 engineering professionals and experts with experience or involvement in managing aviation-related construction projects. Participants, many of whom had familiarity with AI tools, provided insights into the applicability of AI in areas such as planning, scheduling, and safety monitoring. The majority agreed that AI has the potential to revolutionize project management processes, improving decision-making, and efficiency. AI tools can predict delays, optimize workflows, and enhance safety through real-time data analytics and machine learning algorithms, reducing risks and human error. Despite the UAE’s leadership in AI-driven security advancements, its use in aviation construction is still underdeveloped. This research highlights the potential for broader AI integration across the entire lifecycle of aviation projects. By adopting AI in these areas, UAE airports could set new benchmarks for cost effectiveness, sustainability, and project delivery, reinforcing the region’s status as a leader in technological innovation within the aviation industry. Full article

This article contributes to the existing literature by modeling and automating the learning process from previous aviation construction projects (ACPs) using artificial intelligence tools, where it will be easier to characterize aviation construction projects and identify the specifications of different aspects of the projects throughout their entire life cycle. An artificial intelligence (AI) framework is proposed for the categorization of aviation construction projects using different machine-learning (ML) methods with a focus on the UAE as a source of data. Airport construction projects have been seen to share a good deal of similar attributes, which should simplify the decision-making process regarding layouts, design, equipment, labor, budget, complexity, etc. However, the gap in reality is that the huge and scattered sources of data, project specifications, characteristics, and the knowledge from past projects are not utilized in an automated way that could simplify the navigation through projects for better future decision-making. The utilization of AI/ML tools is expected to be useful here in order to reduce the revisions of design and construction rework by classifying the projects and the elements that managers need to consider. The planning, design, and construction of new projects can be improved by identifying the attributes of past projects and categorizing them according to similarities, differences, and complexities. Specifically speaking, a framework of hierarchical clustering and neural networks is integrated together to form the classification model. Upon implementing hierarchical classification and neural networks, it was found that neural networks could demonstrate remarkable classification results; the error in classification was minimal in most of the cases. The advantage of such classification is to help decision-makers utilize best practice from the groups of previous projects, which were classified using both hierarchical and neural networks models. With this classification, rework can be minimized, overhead costs may be reduced, and past best practices can be utilized. Full article

This study addresses the challenges that high-noise environments and complex multi-speaker scenarios present in civil aviation radio communications. A novel radiotelephone communications speaker diffraction network is developed specifically for these circumstances. To improve the precision of the speaker diarization network, three core modules are designed: voice activity detection (VAD), end-to-end speaker separation for air–ground communication (EESS), and probabilistic knowledge-based text clustering (PKTC). First, the VAD module uses attention mechanisms to separate silence from irrelevant noise, resulting in pure dialogue commands. Subsequently, the EESS module distinguishes between controllers and pilots by levying voice print differences, resulting in effective speaker segmentation. Finally, the PKTC module addresses the issue of pilot voice print ambiguity using text clustering, introducing a novel flight prior knowledge-based text-related clustering model. To achieve robust speaker diarization in multi-pilot scenarios, this model uses prior knowledge-based graph construction, radar data-based graph correction, and probabilistic optimization. This study also includes the development of the specialized ATCSPEECH dataset, which demonstrates significant performance improvements over both the AMI and ATCO2 PROJECT datasets. Full article

Due to the development of printing materials, light-cured 3D printing is playing an increasingly important role in industrial and consumer markets for prototype manufacturing and conceptual design due to its advantages in high-precision and high-surface finish. Despite its widespread use, it is still difficult to achieve the 3D printing requirements of large volume, high resolution, and high speed. Currently, traditional light-cured 3D printing technologies based on stereolithography, such as regular DLP and SLA, can no longer meet the requirements of the processing size and processing rate. This paper introduces a dynamic projection of 3D printing technology utilizing a digital micro-mirror device (DMD). By projecting the ultraviolet light pattern in the form of “animation”, the printing resin is continuously cured in the exposure process to form the required three-dimensional structure. To print large-size objects, the three-dimensional model is sliced into high-resolution sectional images, and each layer of the sectional image is further divided into sub-regional images. These images are dynamically exposed to the light-curing material and are synchronized with the scanning motion of the projection lens to form a static exposure pattern in the construction area. Combined with the digital super-resolution, this system can achieve the layering and fine printing of large-size objects up to 400 × 400 × 200 mm, with a minimum feature size of 45 μm. This technology can achieve large-size, high-precision structural printing in industrial fields such as automobiles and aviation, promoting structural design, performance verification, product pre-production, and final part processing. Its printing speed and material bending characteristics are superior to existing DLP light-curing 3D printing methods. Full article

This article presents the effects of work performed during a software project for generative models and spreadsheets, allowing the quick creation of conceptual models for aircraft. The presented software at the current stage is suitable for the creation of glider representation; however, a modular structure allows for developing and extrapolating the presented application to match the requirements of planes and UAV (unmanned aerial vehicle) design. The subject of this work is a response to the current trends and needs prevailing in the field of CAD (computer-aided design) and aviation. In the initial sections of this paper, theoretical issues related to the work being carried out are introduced, and the methodology for creating software for the construction and verification of the aircraft structure along with the need for interchange between databases of generative models is presented. In the following sections, the concepts and selected solutions for the user interface that supports the knowledge base are presented along with a set of procedures for its operation. Furthermore, a method for database integration with the methods used to determine design features for the developed generative models and the Siemens NX system is introduced. Problems encountered during software development, as well as solution examples for model applications, are specified. The results obtained and the models generated on their basis were tested with a strength analysis using Autodesk Inventor software and analysed in terms of meeting the initial assumptions. In the end, conclusions and observations were formulated resulting from the effects of the work performed during the project. Full article

Life without mobility is inconceivable. To enable this connectivity, one must find a way to progress towards a more sustainable transportation. In the aviation industry, a comprehensive understanding of greening technologies such as electrification of the propulsion system for commercial aircraft is required. A hybrid-electric propulsion concept applied to a regional aircraft is studied in the context of the FutPrInt50 project. To this end, the hybrid-electric propulsive system components are modeled, validated, and evaluated using computational and experimental data presented in the literature. The components are then assembled to construct the three powertrains for the hybrid-electric propulsion systems (Series, Parallel and Turboelectric) and parametric studies are carried out to study the influence of various battery parameters and hybridization factor. The performance results for a simple mission profile are generated. Together with a thermal management system, multi-objective optimization studies for the different architectures are then performed, with the power hybridization factor as the design variable and minimization of total mass and emissions as objective functions. Full article

Carbon emissions have become a focus of political and academic concern in the global community since the launch of the Kyoto Protocol. As the largest carbon emitter, China has committed to reaching the carbon peak by 2030 and carbon neutrality by 2060 in the 75th United Nations High-level Meeting. The transport sector needs to be deeply decarbonized in China to achieve this goal. Previous studies have shown that the carbon emissions of the railway sector are small compared to highways, waterways, and civil aviation. However, these studies only consider the operation stage and do not consider the carbon emissions caused by large-scale railway infrastructure construction during the construction stage. As an essential source of carbon emissions and the focus of emissions reduction, the carbon emission of railway construction projects (RCPs) is in urgent need of relevant research. Based on a systematic literature review (SLR), this paper sorts out the carbon emission factors (CEFs) related to RCPs; combines semi-structured expert interviews to clarify the carbon emissions measurement boundary of RCPs; modifies and calibrates CEFs; constructs the carbon emission measurement model of RCPs including building material production stage, building material transportation stage, and construction stage; and conducts empirical analysis to validate carbon emission factors and measurement models. This study effectively complements the theoretical research on CEFs and measurement models in the construction stage of railway engineering and contributes to guiding the construction of low-carbon railways practically. Full article

The following paper presents the key design and test activities associated with the development of POLON—a green microsatellite propulsion module using 98% Hydrogen Peroxide (HTP). POLON, which stands for “Polish Propulsion Module”, is the first step toward the development of a full, ready-to-be-commercialized satellite propulsion system at the Łukasiewicz—Institute of Aviation (Ł-IoA). The development of an entire microsatellite propulsion system within the frame of the POLON project effort is the natural milestone on the Ł-IoA green propulsion roadmap, which so far embodied research on fundamental HTP chemistry, work on elementary propulsion technologies, as well as the development of individual propulsion components. Within this article, POLON propulsion development logic is introduced first, and the major challenges associated with utilizing HTP for an orbital propulsion system are described. Consequently, the specific R&D activities aimed at mitigating the identified issues and risks are discussed. Those cover analytical as well as experimental work, including, but not limited to, HTP compatibility studies with candidate construction materials, waterhammer effect studies, HTP catalyst testing and evaluation, and propellant tank manufacturing studies. The initial results for those activities are presented and, finally, further development plans are discussed. Full article

The vast Brazilian territory and the accelerated economic growth of the cities of the country’s interior in recent years have created a favourable environment for the expansion of regional aviation. In 2015, the Brazilian Government launched a program of investments in regional airports equipping them to receive commercial flights. However, the economic crisis and the scarcity of resources drive the prioritisation of projects with a greater economic and social return. This article aims to present a multicriteria decision aid (MCDA) model to measure cities’ attractiveness to receive investments in regional airports. The MCDA approach can deal with multiple indicators and different points of view and provide systematised steps for supporting decision-makers. For this purpose, we selected 12 criteria among the evaluation parameters identified in the literature, which led to the construction of the evaluation model and elaborating the ranking of the localities participating in the investment program. This study can contribute scientifically by proposing the use of an MCDA approach to support decisions related to logistics and infrastructure. It can help managers and practitioners provide a structured and systematised model to address decisions related to airport investments. Full article

Unlike other developmental relationships, BRI is the most promising icon in transforming the construction industry and built environment in Africa; the infrastructure developments like highways, bridges, skyscrapers, and aviation take in advanced construction technologies, methods, and skills. However, the technological capability of Chinese construction firms is not transferred in the highest capacity to the host countries. Nevertheless, the main focus is on delivering modern railways, highways, and skyscrapers. Thus, this research aimed to propose an adaptable technology transfer model by identifying the theoretical concepts in the body of knowledge, exploring the prior technology transfer models and the best experiences. The findings indicated that the BRI inclusive countries in Africa benefit from infrastructure development with an investment amount of more than US$33 billion with potential technology spillovers, but in an unplanned, and not best suited to their conditions because of the lack of a single-country-based technology, transfer model ahead of project implementation. Using a systems thinking approach and a causal loop diagram tool, the authors created a conceptual model to guide the Africa’s construction technology transfer through BRI. The research also examined case study projects in Ethiopia to assert the new model’s practicability over the existing processes. Moreover, the university–industry linkage structures, can facilitate the process through R&D and innovation in the whole project life cycle. Full article

The problem of staff scheduling in the airline industry is extensively investigated in operational research studies because efficient staff employment can drastically reduce the operational costs of airline companies. Considering the flight schedule of an airline company, staff scheduling is the process of assigning all necessary staff members in such a way that the airline can operate all its flights and construct a roster line for each employee while minimizing the corresponding overall costs for the personnel. This research uses a rostering case study of the ground staff in the aviation industry as an example to illustrate the application of integrating monthly and daily schedules. The ground staff in the aviation industry case is a rostering problem that includes three different types of personnel scheduling results: fluctuation-centered, mobility-centered, and project-centered planning. This paper presents an integrated mixed integer programming (MIP) model for determining the manpower requirements and related personnel shift designs for the ground staff at the airline to minimize manpower costs. The aim of this study is to complete the planning of the monthly and daily schedules simultaneously. A case study based on real-life data shows that this model is useful for the manpower planning of ground services at the airline and that the integrated approach is superior to the traditional two-stage approach. Full article

This paper presents an analysis of the land use and land cover change (LUCC) of major infrastructure construction as exemplified by the case of Hangzhou International Airport (HIA, Hangzhou, China), which is one of the busiest airports in Eastern China. The airport’s effect on LUCC is evaluated by comparing the actual pattern from 1996 to 2001 with a counterfactual simulated land use pattern that would have occurred without the intervention of airport construction. This research is based on land use maps from Landsat images that were analyzed by supervised classification and visual interpretation. To simulate the land use pattern occurring without airport construction, the counterfactual, we applied a cellular automata (CA)–Markov model. Through before and after comparison, we found that cultivated land has decreased and that constructed land has increased because of airport construction. However, according to the counterfactual scenario, airport construction to some extent prevented a decrease in cultivated land and decelerated the expansion of constructed land at a small scale and in the short term. We discuss several reasons for this result, including governmental regulations, such as the setting of the airport clearance area for the safety of plane take-off and landing, the adverse effects of aviation noise or pollution, which may limit the construction activities in the surrounding areas of the airport, and, importantly, the unique land use and land management system in China, mainly the cultivated land requisition-compensation balance policy. We conclude that (1) the counterfactual CA–Markov model simulation is a suitable and unbiased way of evaluating the effect of infrastructure on LUCC that can solve the deficiency in the previous literature relying on before and after comparisons and (2) regulatory, economic, and institutional factors should be considered when explaining and assessing the LUCC due to large infrastructure projects, such as airports, in China and in other countries. Full article