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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Learning from Healthcare: A Perspective Review on Incorporating Soft Constraints into Aviation Maintenance Scheduling</title>
      <link>https://trid.trb.org/View/2724638</link>
      <description><![CDATA[A key consideration in effective aviation maintenance scheduling is the satisfaction of maintenance personnel in relation to allocating tasks and work scheduling. Research that reflects the satisfaction of aviation maintenance staff is limited. Studies focusing on soft constraints in aviation maintenance are nearly non-existent. Soft constraints encompass flexible factors such as employee preferences, workload distribution, and work environment, which significantly impact employee satisfaction and job performance. Aircraft maintenance optimisation needs to consider both hard and soft constraints. Soft constraints have been extensively studied in healthcare and, as this perspective review argues, this can provide valuable insights for aviation maintenance scheduling management. Specifically, aviation maintenance requirements, such as task-based scheduling, necessitate the development of tailored tools to efficiently accommodate the sector’s particulari-ties. This perspective review of aviation maintenance scheduling literature was focused on identifying gaps in the consideration of soft constraints. While there are some studies on incorporating soft constraints into an effective fatigue management system, there is a paucity of research in this area in aviation maintenance. Conversely, the reviewed literature reveals that hard constraints have received greater attention in modelling. This perspective review proposes the development of designated soft constraints to measure the satisfaction of aviation maintenance personnel.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:32:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2724638</guid>
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    <item>
      <title>Bionic Flapping Wing Structural Parameter Optimization Based on Lift Maximization</title>
      <link>https://trid.trb.org/View/2720250</link>
      <description><![CDATA[To address the issues of short endurance and poor flight performance of flapping wing aircraft, this study focuses on the double-crank double-rocker two-segment flapping wing mechanism and conducts structural parameter optimization research based on lift maximization. First, the complex vector method is used to derive the kinematic models of the four-bar mechanism and the two-segment flapping wing mechanism, establishing the intrinsic relationship between “geometric parameters and flapping wing motion laws”. Combined with the lift formula, a quantitative relationship between “geometric parameters, flapping velocity, and lift” is constructed. With the goal of maximizing the average lift, the genetic algorithm is applied to optimize the key geometric parameters of the mechanism. Finally, numerical simulations of the aerodynamic characteristics of the flapping wing mechanism before and after optimization are carried out to verify the optimization effect. The results show that after optimization, the swing range of the inner wing expands from approximately 57° to 90°; the folding speed of the inner and outer wings during the upstroke is significantly increased, reducing the resistance in the upstroke process; the deployment speed during the downstroke is increased, enhancing the lift in the downstroke process. Meanwhile, as the incoming flow velocity or flapping frequency increases, the growth rates of the net lift and net thrust of the optimized flapping wing are significantly higher than those before optimization. The research results of this paper provide theoretical support and technical references for the selection and parameter design of transmission mechanisms for high-performance flapping wing aircraft.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2720250</guid>
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    <item>
      <title>Application of Lstm Neural Networks with Multivariate Numerical Analysis to Aviation Wind Gust Forecasting</title>
      <link>https://trid.trb.org/View/2717184</link>
      <description><![CDATA[This paper presents a long short-term memory (LSTM) framework developed for predicting wind gusts 1 h in advance at Taiwan Taoyuan International Airport (RCTP) during typhoons. Hourly surface observations were collected from 12 landfalling typhoons (2010–2020) and used to compare three feature-selection strategies: Pearson correlation, recursive feature elimination with cross validation, and random-forest importance. Models were trained on 12-h multivariate histories. A leave-one-typhoon-out cross-validation scheme revealed that the LSTM model with random-forest selection achieved a mean root-mean-square error of 2.33 m/s and mean absolute percentage error of 21.12%. Although these statistics are comparable to those of a 1-h persistence baseline model on average, the proposed model considerably outperformed the persistence baseline model during rapid intensification and decay phases, reducing errors by approximately 45%. Forecast errors generally remained within the ±5 m/s operational advisory threshold. The results of this case study for RCTP suggest that feature selection can be combined with sequence-based deep learning to provide robust decision support for aviation operations during extreme weather events.]]></description>
      <pubDate>Wed, 24 Jun 2026 11:31:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2717184</guid>
    </item>
    <item>
      <title>Infrastructure and Socioeconomic Characteristics of Small Airports with Regular Commercial Aviation Services on Thin-Demand Routes Operated by Low-Capacity Aircraft</title>
      <link>https://trid.trb.org/View/2714345</link>
      <description><![CDATA[The existing literature on the aviation market has focused more on analysing high-capacity airports served by larger aircraft, often overlooking smaller airports that operate low-capacity planes on routes with low demand. This study examines Azul Conecta’s operations in Brazil using Cessna Grand Caravan aircraft, focusing on the key features of the airports served by this niche service. It applies k-means clustering to 189 airports in Brazil and examines the characteristics of the services they provide. It aims to fill the knowledge gap regarding the characteristics of airports used in this niche market. The findings indicate that airport characteristics associated with the presence of flight service, including socioeconomic variables, are typically associated with regular commercial aviation, whereas infrastructure characteristics are identified as differentiation factors in airports with more limited resources.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:14:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714345</guid>
    </item>
    <item>
      <title>A Sectoral Strategic Roadmapping Framework for Combining Regulatory and Industry Perspectives: The Case of Advanced Air Mobility in Canada</title>
      <link>https://trid.trb.org/View/2714344</link>
      <description><![CDATA[This paper presents a sectoral roadmap development framework-testing process for the Canadian Advanced Air Mobility (AAM) industry, to evaluate a methodology for expanding technological roadmaps into comprehensive sectoral frameworks. The procedural framework incorporates the regulatory perspective to the technological, infrastructural, social, and economic ones, using the S-PLAN framework to identify important strategies and practical actions. Insights were gathered from interviews with cross-disciplinary experts in the public (regulatory) and private (industry) sectors across the industry using the Delphi method to consolidate strategic topics and crucial tactical insights for the sector evolution. The research aims at proposing a methodology for broadening the scope of existing technological roadmaps, applying it in the case of Canada. This methodology is then illustrated in its application to establish the foundation for iterative advancements in the AAM sector, emphasizing a collaborative approach to address the identified challenges. The concluding strategic topics, classified by Advanced Air Mobility Maturity Levels, serve as foundations for the ongoing transformation of Canada’s aviation landscape from its current state towards a more autonomous and expansive future. While this study focuses on the AAM sector, the framework’s design offers broader applicability, providing a valuable tool for other emerging, complex, and rigidly regulated industries.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:14:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714344</guid>
    </item>
    <item>
      <title>From Emissions to Illness: Aviation and Transport Pollution and Respiratory Mortality in Europe</title>
      <link>https://trid.trb.org/View/2712030</link>
      <description><![CDATA[This study explores the association between aviation-related CO₂ emissions and asthma mortality in 15 European Union countries with the highest levels of air traffic between 2008 and 2021. The analysis finds a strong and statistically significant relationship: a 1% increase in aviation emissions is linked to up to a 0.125% rise in asthma-related deaths, underscoring the hidden public health burden of air transport pollution. Emissions from road transport and industrial activity also exhibit strong long-run effects; notably, a 1% rise in road transport emissions corresponds to a 0.79% increase in asthma mortality. Economic expansion, measured by GDP, is indirectly associated with higher asthma mortality, likely through increased demand for aviation and growing urban density. Urban population growth itself is also linked to heightened asthma risks in both the short and long term. These findings highlight the health risks posed by transport emissions and support the need for stronger environmental and public health policy responses. Recommended measures include enhancing emission limits for aviation, promoting sustainable aviation fuels, and integrating air quality indicators into urban and transport planning.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:14:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712030</guid>
    </item>
    <item>
      <title>AI-based calibration of 8-beam LiDAR for fault detection in fixed-wing UAV flaps</title>
      <link>https://trid.trb.org/View/2698369</link>
      <description><![CDATA[Flap deflection monitoring plays a significant role in flight safety of the fixed-wing UAVs. The proposed research lies on a low-cost, lightweight framework with high-fidelity sensing capability of flap aerodynamics using LiDAR. Experimental validation of the system is carried out in a controlled environment in a laboratory where the LiDAR monitors the motion of the flaps by means of a variation in a known flat. It is small, has a wide horizontal FOV which makes it suited to on-board and real-time monitoring. A Python calibration algorithm takes care of the offset bias, sensor tilt, noise, based on distance normalisation, symmetry, outlier removal and smoothing. A post-calibration of the LiDAR data leads to a smoothing and a symmetrical data, which enables a separation of the flap deflection and noise on the sensors. The method will make the UAV safer by recognising faults that can be detected using lightweight and non-redundant sensors.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:14:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2698369</guid>
    </item>
    <item>
      <title>Socio-economic stratification of urban air mobility based on income and transport demand: a case study of New York City</title>
      <link>https://trid.trb.org/View/2698368</link>
      <description><![CDATA[Understanding the main factors driving urban air mobility (UAM) demand is essential for better planning of operations for this emerging air transport mode in large cities. Using New York City as a case study, this research aims to analyse the geographic distribution of potential UAM passengers by income and demand for air taxi services through exploratory data analysis. The results show that during the initial phase of operations, airport shuttle services connecting high-income and high-demand areas, such as the route between Manhattan and John F. Kennedy International Airport, can serve as a reference for experimental business cases in operational planning. The theoretical and practical implications of this study offer insights for the development of new air transport services and infrastructure in UAM.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:14:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2698368</guid>
    </item>
    <item>
      <title>A review on the use of next-generation sustainable fuels in aviation</title>
      <link>https://trid.trb.org/View/2698367</link>
      <description><![CDATA[The aviation sector is undergoing a significant transformation in terms of environmental sustainability due to its energy-intensive nature and high carbon emissions. At the heart of this transformation lies sustainable aviation fuel (SAF), which aims to reduce environmental impacts and ensure long-term energy security as an alternative to fossil fuels. This study examines the current state of SAF usage in the industry, its potential advantages, and the challenges encountered. This study looks at how SAF is currently used in the industry, as well as its possible benefits and difficulties. The study used a mixed-method approach, gathering quantitative data from surveys given to a larger sample group and qualitative data from semi-structured interviews with professionals in the aviation industry. Based on the data obtained, it was determined that although SAFs offer considerable environmental benefits, high production costs, infrastructure deficiencies, and regulatory uncertainties hinder their widespread adoption. This study aims to contribute to the strategic planning efforts of sector stakeholders and provide data to guide policymakers during the transition to sustainable aviation.]]></description>
      <pubDate>Tue, 02 Jun 2026 14:31:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2698367</guid>
    </item>
    <item>
      <title>Enhanced mechanical performance of additively manufactured PLA/TPU blend compatibilised with chain extender: a green material for sustainable aviation</title>
      <link>https://trid.trb.org/View/2698366</link>
      <description><![CDATA[The aviation industry is actively pursuing the '2050 net zero goal' to mitigate petroleum-based fuel consumption and carbon emissions. A promising approach to achieving this target involves the use of sustainable aviation fuels, usage of bio-based materials and the adoption of lightweight components. This study explores the application of additive manufacturing (AM) to produce lightweight polylactide based parts for aircraft cabin interiors, which allows the creation of complex geometries in a cost-effective manner. Although flammability regulations present challenges for polylactide based components, small parts may qualify for exemption. We developed PLA/TPU blends, compatibilised with Joncryl 4468, using a twin-screw extruder and then produced filaments for 3D printing of small components in commercial airplanes. Mechanical and thermal properties of the additively manufactured blend samples were characterised in order to find an optimal formulation. An ecological and economic assessment demonstrated that this blend appears as a highly cost-effective and sustainable alternative.]]></description>
      <pubDate>Fri, 29 May 2026 14:09:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2698366</guid>
    </item>
    <item>
      <title>Green technologies in the airline industry: a review of adoption, maturity, and future directions</title>
      <link>https://trid.trb.org/View/2698365</link>
      <description><![CDATA[This review article examines the integration of green technologies in the airline industry, focusing on their categories, developmental status, and prospective trajectories. It delineates four primary domains: sustainable aviation fuels (SAFs), aircraft design and propulsion, cabin and in-flight services, and digital technologies. Hydroprocessed esters and fatty acids - synthetic paraffinic kerosene (HEFA-SPK) and advanced turbofan engines have reached full maturity, whereas alcohol-to-jet-synthetic paraffinic kerosene (ATJ-SPK), the power-to-liquid synthetic paraffinic kerosene (PtL-SPK), hybrid-electric propulsion, and blended wing bodies remain in preliminary development phases. Numerous cabin and digital innovations are presently in broad implementation. Key future priorities include expanding the utilisation of SAFs and advancing hybrid-electric propulsion systems. Overcoming technical, economic, and regulatory challenges will require coordinated efforts to achieve substantial decarbonisation and sustainability.]]></description>
      <pubDate>Fri, 29 May 2026 14:09:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2698365</guid>
    </item>
    <item>
      <title>Enhancing Ant Colony Optimization with Genetic Algorithm and 3-Opt for Multiple Drone Spraying Path Planning in Precision Agriculture</title>
      <link>https://trid.trb.org/View/2686143</link>
      <description><![CDATA[Efficient and environmentally responsible pesticide application is a major challenge in precision agriculture. Excessive pesticide use in conventional farming increases costs, harms the environment, and poses health risks. Recent advancements in unmanned aerial vehicles (UAVs) or drones have enabled targeted spraying, yet optimizing multiple-drone route planning and task allocation remains complex due to dynamic field conditions and limited drone capacity. To address this gap, this study proposes a hybrid optimization approach that integrates Ant Colony Optimization (ACO), Genetic Algorithm (GA), and 3Opt to generate efficient flight routes for multiple sprayer drones based on plant health levels. In this framework, ACO assigns drones to target points, GA automatically tunes key ACO parameters, and 3Opt enhances route efficiency through local optimization. Experimental results show that GA effectively automates the tuning of four key ACO parameters and that drone capacity significantly affects route length. The integration of GA, ACO and 3Opt further reduces total route length, achieving up to 13.6% improvement in efficiency compared to traditional ACO. These findings demonstrate the potential of the proposed method to enhance route efficiency, reduce energy consumption, shorter mission completion time and offers a practical solution for improving the performance and sustainability of multiple-drone spraying operations.]]></description>
      <pubDate>Wed, 15 Apr 2026 10:30:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686143</guid>
    </item>
    <item>
      <title>Quantifying Safety-II in Aviation Maintenance: An Integrated Design-and-Validation Framework for Communication-Resilience KPIs</title>
      <link>https://trid.trb.org/View/2686141</link>
      <description><![CDATA[This study addresses human factors in aviation maintenance by converting routine e-log text into computable communication-resilience indicators – closure-loop ratio, read-back adherence, ambiguity density, temporal/referential completeness, error-catch latency, and cross-shift continuity – and testing whether strengthening these signals reduces defects with minimal operational burden. An integrated design-and-validation pipeline was deployed in a Maintenance, Repair and Overhaul (MRO) setting using a phased rollout (Baseline -- Assist -- Nudge), and causal effects were estimated via interrupted time-series analysis and, where applicable, stepped-wedge Generalized Linear Mixed Model (GLMM). A Natural Language Processing (NLP) stack (Term Frequency–Inverse Document Frequency (TF-IDF) + regularized logistic regression, with an optional compact transformer) extracts linguistic cues; the predicted probabilities are calibrated to support reliable dashboard thresholds. Results show immediate reductions in level and sustained improvements in slope in sign-off error rates after Assist, with larger step-downs under Nudge. Mediation analyses indicate that gains operate through improved communication KPIs rather than generic attentional effects. Model diagnostics light-strong discrimination with low calibration error; robustness checks and a cross-shift/fleet evaluation show stable transfer with minimal recalibration. Governance emphasizes de-identification, advisory-only AI with human-in-the-loop, and transparent, non-punitive use. Findings operationalize Safety-II as quantifiable communication behavior and demonstrate a scalable, low-friction pathway – advisory Assist plus light User Interface (UI) nudges – that advances Air Transport Technologies & Development while improving safety and quality in maintenance operations.]]></description>
      <pubDate>Wed, 15 Apr 2026 10:30:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686141</guid>
    </item>
    <item>
      <title>Analysis of the Impact of Passenger Preparation on the Throughput of Security Screening at Airport Checkpoints</title>
      <link>https://trid.trb.org/View/2686142</link>
      <description><![CDATA[Efficient passenger screening is a critical component of airport security operations, directly influencing both safety standards and the overall passenger experience. As global air traffic continues to grow, optimizing the throughput of security checkpoints while maintaining regulatory compliance has become a major operational challenge. This study investigates one often overlooked factor affecting checkpoint performance – the level of passenger preparation prior to screening. The research combines experimental and simulation-based analyses to assess how improper passenger preparation contributes to the frequency of alarms at walk-through metal detectors (WTMDs). The study focuses on a security lane operating under a free passenger flow configuration equipped with a WTMD. The results demonstrate that better passenger preparation significantly improves checkpoint throughput and overall lane capacity. This microscopic analysis, which quantifies the operational impact of passenger behavior on system performance, addresses a gap not previously covered in the literature. The findings provide practical insights for airport security managers and system designers, emphasizing the importance of targeted passenger guidance and education in enhancing checkpoint efficiency.]]></description>
      <pubDate>Wed, 15 Apr 2026 10:30:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686142</guid>
    </item>
    <item>
      <title>Improved Method for Determining Rheological Parameters of Composite Materials during Creep under Torsional Deformation</title>
      <link>https://trid.trb.org/View/2686140</link>
      <description><![CDATA[This paper presents an improved method for determining rheological function parameters of viscoelastic-plastic materials, demonstrated through creep under torsional deformation. The approach is based on the heredity theory (Boltzmann’s principle), using curve fitting to identify parameters (A, a, and ß). The improved method from previous studies uses precise graph construction via computational tools, with curve alignment performed using a least square–like approach. An extended database of theoretical rheological function graphs and tables, developed from complex mathematical models and prior research, was employed in the analysis. Importantly, the study highlights that modern aircraft structures, where a significant portion of elements are made of advanced composite materials, are exposed during flight to complex, time-dependent loading conditions. Under these conditions, creep phenomena may develop within structural components, leading to residual deformations and gradual degradation of mechanical properties over time. Even with initially high safety margins, such effects can eventually cause the failure of critical elements after prolonged operation. Therefore, the presented method provides a scientific and practical tool for assessing and predicting the long-term viscoelastic–plastic behavior of aviation composites, ensuring structural integrity, flight safety, and an extended operational lifetime of aircraft.]]></description>
      <pubDate>Wed, 15 Apr 2026 10:30:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686140</guid>
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