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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=PHNlYXJjaD48cGFyYW1zPjxwYXJhbSBuYW1lPSJkYXRlaW4iIHZhbHVlPSJhbGwiIC8+PHBhcmFtIG5hbWU9InN1YmplY3Rsb2dpYyIgdmFsdWU9Im9yIiAvPjxwYXJhbSBuYW1lPSJ0ZXJtc2xvZ2ljIiB2YWx1ZT0ib3IiIC8+PHBhcmFtIG5hbWU9ImxvY2F0aW9uIiB2YWx1ZT0iMCIgLz48L3BhcmFtcz48ZmlsdGVycz48ZmlsdGVyIGZpZWxkPSJpbmRleHRlcm1zIiB2YWx1ZT0iJnF1b3Q7QWVyb2R5bmFtaWMgY29tcG9uZW50cyZxdW90OyIgb3JpZ2luYWxfdmFsdWU9IiZxdW90O0Flcm9keW5hbWljIGNvbXBvbmVudHMmcXVvdDsiIC8+PC9maWx0ZXJzPjxyYW5nZXMgLz48c29ydHM+PHNvcnQgZmllbGQ9InB1Ymxpc2hlZCIgb3JkZXI9ImRlc2MiIC8+PC9zb3J0cz48cGVyc2lzdHM+PHBlcnNpc3QgbmFtZT0icmFuZ2V0eXBlIiB2YWx1ZT0icHVibGlzaGVkZGF0ZSIgLz48L3BlcnNpc3RzPjwvc2VhcmNoPg==" rel="self" type="application/rss+xml" />
    <description></description>
    <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>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>A Fluid-Structure- Interaction based Methodology to Evaluate Aero-Thermal Performance of Deformable Air Guides</title>
      <link>https://trid.trb.org/View/2663523</link>
      <description><![CDATA[The present work demonstrates a Fluid-Structure Interaction (FSI) based methodology that couples a Finite Volume Method (FVM) and Finite Element Method (FEM) based tools to estimate air guide deformation, thereby predicting accurate aerothermal performance. The method starts with a digital assembly step where the assembly shape and the induced stress due to assembly is predicted. A full vehicle Aerodynamic simulation is performed to extract the surface pressure on the air guide which is then used to estimate the extent of deformation of the air guides. Based on the extent a subsequent Aerodynamic simulation may be carried out to predict thermal efficiency.Comparison against pressure data and deflection data extracted from the wind tunnel experiments of vehicles has shown reasonable match demonstrating the accuracy and usefulness of the method.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663523</guid>
    </item>
    <item>
      <title>Model experimental research of the air injection drag reduction system without air maintenance devices for a 2600 DWT bulk carrier</title>
      <link>https://trid.trb.org/View/2660709</link>
      <description><![CDATA[Air Injection Drag Reduction (AIDR) holds significant potential for energy savings and emission reduction in maritime vessels. Current AIDR systems depend on Air Maintenance Devices (AMDs), such as air cavities, which are challenging to install and exhibit high appendage resistances. This study presents a novel AIDR system for a 2600 DWT bulk carrier that eliminates the need for AMDs. The system employs rectangular slots in staggered positions on the ship's bottom, and its performance was evaluated through a model test in a circulating water channel (CWC) and numerical simulations, with airflow rate determined by nominal air layer thickness (T). The results showed that at T = 3.521 and 8.621 mm, the air-water mixed flows were divided into three regions: an air layer at the front, an air layer tearing in the parallel middle body, and air escaping at the ship's sides. As ship speed increased, the beneficial air layer length first increased and then decreased, with the air escape path tending to angle toward the stern, reducing the disturbances of the air on the free surface. At varying airflow rates, AIDR exhibited three forms similar to those observed on flat plates: bubble drag reduction (BDR), transitional air layer drag reduction (TALDR), and air layer drag reduction (ALDR). A large air coverage area and an air emerging position near the stern demonstrated high drag reduction effects. Reducing the exit widths of air injection decreased the air spreading angle, but required a higher airflow rate to establish an effective air layer. Under conditions of high speed, shallow draft, and low airflow rate, narrow slots positioned away from the ship's sides exhibited reduced spreading angles, effectively suppressing air escape. The air-water mixed flow was sensitive to the ship's attitude. Heeling and stern trimming reduced air coverage area and increased air escape, while bow trimming aided airflow spread. Therefore, a collaborative design of the AIDR system and the ship's attitudes is crucial when planning AIDR installation on new vessels. The experimental data will inform the development of numerical methods used for ship AIDR system without AMDs and guide design of the system.]]></description>
      <pubDate>Wed, 11 Feb 2026 15:10:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2660709</guid>
    </item>
    <item>
      <title>Investigation of aerodynamic performance and operational optimization of wing sails at varying spacings</title>
      <link>https://trid.trb.org/View/2661482</link>
      <description><![CDATA[The aerodynamic performance of sails determines the effectiveness of wind-assisted propulsion, with spacing being a key factor in sail interaction and thrust contribution. Investigating the aerodynamic performance and optimization of operation modes for sails under varying spacing will guide ship energy savings and emission reduction. The aerodynamic characteristics of crescent sails within 0°–60° angle of attack (AOA) range are systematically analyzed using a three-dimensional computational fluid dynamics (CFD) method validated by experiments. Based on the CFD results, an optimization procedure for the AOA under varying spacing is developed by integrating a surrogate model with a genetic algorithm. The variation of thrust coefficient (CT) and Energy Efficiency Design Index (EEDI) are examined. Specifically, desynchronized operation indicated a substantial advantage in enhancing the CT over synchronized operation; however, the improvement potential decreases with increasing spacing, from 12.6 % to 1.6 %. Meanwhile, the improvements in EEDI range from 1.7 % to 13.7 % on a 300,000-ton tanker. In the synchronized operation, the sail interaction effect is directly proportional to AOA and inversely proportional to spacing. In desynchronized operation, the optimized AOA configuration enables more wind energy to reach the downstream sail, which effectively enhances its thrust and hence the performance of the whole system.]]></description>
      <pubDate>Wed, 11 Feb 2026 15:10:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2661482</guid>
    </item>
    <item>
      <title>Optimisation of drag coefficient of a car with integrated canards</title>
      <link>https://trid.trb.org/View/2582201</link>
      <description><![CDATA[The objective of this study is to investigate the impact of canards geometric design on the airflow field at the rear of a sedan, with the aim of reducing the drag coefficient of the vehicle. Four key design variables were analyzed: canard angle (θ), length (L1), radius (R), and thickness (H). Using these variables, Latin hypercube sampling generated 50 DOE points, which were simulated in ANSYS Fluent® to calculate the drag coefficient (CD). A comprehensive performance comparison was performed. Ultimately, a backpropagation neural network (BPNN) coupled with a genetic algorithm (GA) was adopted as the optimal method for canard design optimization. A random forest model identified θ as the most influential factor on CD. The optimized design achieved a 21% reduction in drag, minimized the rear vortex region, and significantly accelerated the optimization process.]]></description>
      <pubDate>Fri, 24 Oct 2025 14:25:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2582201</guid>
    </item>
    <item>
      <title>Wind Tunnel Tests on Aerodynamic Noise from the Head Car of a High-speed Train</title>
      <link>https://trid.trb.org/View/2407675</link>
      <description><![CDATA[Characteristics of aerodynamic noise is always difficult to extract by both experimental and numerical methods. Based on the aero-acoustic wind tunnel test results of a 1:8 scale high-speed trains model with three cars, the properties of the aerodynamic noise sources of the head car were analyzed. In view of the fact that dipole source is the main aerodynamic noise source of the high-speed train, the acoustic similarity relationship between the different models was deduced. Subsequently, the aerodynamic noise properties of the 1:1 scale model (approximate full-scale train) were analyzed. The results show that the main noise sources of the 1:1 scale model are the bogie regions and the noise energy of 80 Hz–4 kHz is dominant at the train speed of 250 km/h. The noise is the strongest at the frequency of 160–400 Hz, and the noise of the nose tip and the obstacles is the same order as that of the bogie area after 2.5 kHz. The acoustic similarities between the different models are related to the third power of the speed, and the first power of the model length, the propagation distance and the frequency. The noise difference between the different models is related to scale size and frequency. The frequency at full scale has an exponential relationship with the scale model’s frequency, not following a liner relationship with the scale.]]></description>
      <pubDate>Mon, 18 Aug 2025 08:51:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2407675</guid>
    </item>
    <item>
      <title>Features of the Aerodynamics of the Undercar Space of the High-Speed Rolling Stock</title>
      <link>https://trid.trb.org/View/2408006</link>
      <description><![CDATA[The article is devoted to the study of the aerodynamics of the undercar space. The aim of the study is to solve the scientific problem of calculating the movement of air masses in the undercar during the movement of a high-speed train and to determine the mechanism of entrainment of a particle by an air flow from the surface of a railway track. To achieve the aim, the following methods were used: design of solid models, embodiment of cfd analysis by the finite volume method in the Flow Simulation module of the SolidWorks software package and in the Fluent module of the Ansys software package based on the numerical solution of the Navier – Stokes system of equations, also the use of the Motion module of the SolidWorks software package for dynamic analysis. According to the results of the study, a picture of the movement of air flows in the undercar space was established, a stable circulation of air masses in the overhead area was determined. This is dangerous in that the particles caught up, during the lifting process, move to the level bogies and can cause damage to the car body elements. Using the designed dynamic model, there is observed the weakening of the adhesion forces of the particle during the movement of the rolling stock, and a particle of ballast can be carried away by the air flow generated by the high-speed rolling stock.]]></description>
      <pubDate>Mon, 28 Jul 2025 08:55:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2408006</guid>
    </item>
    <item>
      <title>CFD-based design of novel drag-reducing appendages for container ships</title>
      <link>https://trid.trb.org/View/2551259</link>
      <description><![CDATA[Container ships, as cornerstones of modern global trade, have significantly increased in size in recent years. This growth necessitates minimizing resistance to environmental forces to improve operability, enhance safety, and reduce fuel consumption. While aerodynamic optimization has traditionally focused on windshields and container stacking configurations, this study introduces a novel drag-reducing appendage inspired by sports aerodynamics engineering. The research follows a two-stage approach. First, a numerical model was validated against experimental wind tunnel results, achieving a high correlation with less than a 2 % difference in drag coefficient. Second, the validated model was used in computational fluid dynamics (CFD) simulations to assess the effectiveness of various appendage designs. A parametric study was conducted to optimize appendage placement, size, and orientation, leading to two configurations that achieved maximum drag reductions of 9.47 % and 9.22 %, respectively. Results indicate that these appendages mitigate adverse pressure effects and streamline flow around the accommodation block, effectively reducing aerodynamic drag. This study demonstrates the feasibility of integrating simple, cost-effective appendages to enhance the aerodynamic performance of post-panamax container ships without compromising cargo capacity. The findings provide a practical approach for reducing fuel consumption and emissions, supporting ongoing efforts toward sustainable shipping.]]></description>
      <pubDate>Mon, 16 Jun 2025 09:17:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2551259</guid>
    </item>
    <item>
      <title>Enhancing aerodynamics performance: A redesign approach for the forward-swept fixed-wing UAV</title>
      <link>https://trid.trb.org/View/2528612</link>
      <description><![CDATA[The aerodynamic design plays a crucial role in vehicle performance and energy consumption. This study undertakes significant modifications to enhance the performance of the forward-swept fixed-wing unmanned aerial vehicle (UAV), particularly focusing on achieving higher lift/drag ratios. These modifications include implementing a backward-swept (normal) fixed-wing design. A simulation model using the vortex lattice method (VLM) by OPENVSP is conducted to determine forces and aerodynamic characteristics at 0 to 30-degree angles of attack. The accuracy of the model is verified against numerical and experimental data. The findings indicate that the UAV’s aerodynamic performance is enhanced by approximately 20% with the backward (normal) fixed-wing design compared to the existing model, which utilized a forward-swept fixed-wing on the UAV.]]></description>
      <pubDate>Fri, 16 May 2025 09:33:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2528612</guid>
    </item>
    <item>
      <title>Analysis and evaluation of CFD simulation uncertainty based on aerodynamic drag of the Ahmed car</title>
      <link>https://trid.trb.org/View/2505714</link>
      <description><![CDATA[To identify the key factors affecting aerodynamic drag prediction in the aerodynamic shape optimization design of ground transportation, a quantitative and sensitivity analysis of aerodynamic drag uncertainty was conducted with the Ahmed car as the object. Grid size, turbulence model, pressure velocity coupling and spatial discretization scheme are selected as variables, and their values are assumed. Then, an orthogonal experimental design scheme was used to calculate aerodynamic drag using the computational fluid dynamics (CFD) method. Multi-factor CFD uncertainty quantification and sensitivity analysis were conducted, and verified with wind tunnel experimental data. The results show that the degree of effect on the aerodynamic drag of the Ahmed car is in the order of spatial discretization scheme, grid size, pressure velocity coupling, and turbulence model. The best simulation strategies for aerodynamic drag are: QUICK scheme, fine grid, SIMPLEC algorithm, and SST k-ω turbulence model.]]></description>
      <pubDate>Tue, 18 Mar 2025 15:48:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2505714</guid>
    </item>
    <item>
      <title>Research on aerodynamic attachments parameter optimisation by integrating BP neural network and genetic algorithm</title>
      <link>https://trid.trb.org/View/2506051</link>
      <description><![CDATA[In this study, aerodynamic attachments at the rear of a vehicle are optimized using CFD simulation and Latin hypercube design to reduce drag and improve high speed performance. Models are constructed based on four design variables and simulated using ANSYS fluent and realizable k-ε models. Neural networks and genetic algorithms were combined to find the optimal solution, resulting in a drag reduction of more than 11.7%. The study also analyses the effect of each variable on drag using random forest and verifies the reliability of the results. Ultimately, it provides a new approach to optimizing the aerodynamic performance of vehicles, helping to reduce energy consumption.]]></description>
      <pubDate>Tue, 18 Mar 2025 15:48:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2506051</guid>
    </item>
    <item>
      <title>Experimental analysis of car drag reduction through contour bump application</title>
      <link>https://trid.trb.org/View/2506050</link>
      <description><![CDATA[The study explores the impact of aerodynamic drag on vehicle performance, focusing on its reduction to enhance fuel efficiency and stability. A NOAH car model was analyzed using both numerical simulations and experimental tests, featuring various rooftop contour bump configurations. Eleven 3D designs, including the base model, were simulated to assess airflow, with results validated through wind tunnel experiments using 3D-printed models. Drag force (FD) and drag coefficient (DC) were calculated for each configuration. The most effective designs, featuring eight, four, and three streamwise bumps, achieved drag reductions of 6.31%, 5.94%, and 5.76%, respectively, with experimental results closely aligning, showing a maximum deviation of 3.27%. This reduction corresponded to fuel consumption decreases of 3.79% in simulations and 3.67% in experiments, so using a bump to the rear roof of the car can reduce almost 770 ml of fuel per 500 km. The findings demonstrate the potential of contour bumps in optimizing vehicle aerodynamics without altering the car's design.]]></description>
      <pubDate>Tue, 18 Mar 2025 15:48:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2506050</guid>
    </item>
    <item>
      <title>Multi-objective optimisation of wheel-rail adhesion for high-speed trains with aerodynamic lift wings</title>
      <link>https://trid.trb.org/View/2491054</link>
      <description><![CDATA[A high-speed train with aerodynamic lift wings (aero-wings) is designed to improve train speed and mitigate energy consumption. Nevertheless, the impact of aero-wings on wheel-rail adhesion and safety remains uncertain. In this examination, a multi-body dynamics (MBD) model of a high-speed train integrated with aero-wings was first created. The influences of train speed, wheel-rail contact conditions, and aerodynamic lift on the wheel-rail adhesion, wheel wear, and dynamics performance were briefly investigated, indicating that aerodynamic lift degrades wheel-rail adhesion and dynamics performance but reduced wheel wear. Then, the multi-parameters matching optimisation design for sufficient wheel-rail adhesion and minimal wheel wear was conducted. The results indicate that, under dry contact and traction conditions, the minimum wear and optimal wheel-rail adhesion can be achieved when the train speed is about 440.62 km/h, the aerodynamic lift is about 24.48% of the vehicle weight, and the wheel wear optimisation rate is 25.38%. While the train speed of 549.54 km/h and an aerodynamic lift of 12.39% corresponds to the optimal results with wear reduction of 11.62%, under wet and braking conditions. This study provides valuable insights for determining aerodynamic load limits and formulating traction/braking control strategies for high-speed trains with aero-wings.]]></description>
      <pubDate>Tue, 18 Feb 2025 11:32:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2491054</guid>
    </item>
    <item>
      <title>Passenger vehicle tyre aerodynamics</title>
      <link>https://trid.trb.org/View/2491309</link>
      <description><![CDATA[Road vehicles are an essential part of society, enabling the movement of people and goods. They are, however, responsible for a large part of greenhouse gas emissions. Therefore, automotive companies strive to constantly increase the energy efficiency of their fleets. For cars, aerodynamic drag is one of the main resistive forces and a substantial part of the total energy consumption. A significant contribution to the total drag originates from the wheels, making the understanding of their flows essential for creating efficient vehicles. Factors such as the wheels' rotation, bluff-body shape and small geometrical details result in complex flow fields that are sensitive to, for example, wind tunnel setup, vehicle velocity and small geometrical changes. Due to this sensitivity, the experimental and numerical methods used to assess wheel aerodynamics should be carefully evaluated. Full-scale wind tunnel tests are compared to simulations with an open road domain and with adomain containing a detailed model of the wind tunnel. Including the wind tunnel improves the prediction of both absolute drag values and the drag delta between configurations. The importance of considering the parasitic lift acting on the wheel drive units (WDUs) of thewind tunnel is also evaluated. In the second part of the thesis, the effects of various geometrical tyre features and their impacton the total drag and flow field around the vehicle are considered.]]></description>
      <pubDate>Fri, 17 Jan 2025 15:18:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2491309</guid>
    </item>
    <item>
      <title>Optimisation of drag coefficient of a car based on back propagation neural network and genetic algorithm</title>
      <link>https://trid.trb.org/View/2437946</link>
      <description><![CDATA[In order to reduce the time cost of automotive aerodynamic performance development, this paper proposes a new method that combines error back propagation neural networks and optimization algorithms for global optimization based on the traditional method, with the aim of achieving a reduction in the time cost of optimal design. In this paper, a simplified car model is chosen as the research object, and the aerodynamic characteristics of the vehicle are enhanced by modifying key geometric parameters of the simplified car body. The target is to minimize the aerodynamic drag coefficient. Five pivotal geometric parameters are selected as design variables, and a Latin hypercube sampling method is employed to generate 50 sets of sample data. Subsequently, the samples are modelled using ANSYS Fluent 2021 R1 software in order to calculate the drag coefficients. The resulting data, including the calculated drag coefficients and the geometric parameters, are employed to train a BP neural network. Subsequently, genetic algorithms are applied to identify the optimal design. The findings demonstrate that the optimized vehicle model achieves a 24.52% reduction in drag coefficient.]]></description>
      <pubDate>Fri, 22 Nov 2024 14:56:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2437946</guid>
    </item>
    <item>
      <title>Surrogate-based aerodynamic shape optimization of high-speed train heads: A review of four key technologies</title>
      <link>https://trid.trb.org/View/2434990</link>
      <description><![CDATA[With the increase in running speed, the aerodynamic characteristics of high-speed trains have a significant impact on running stability, energy consumption and passenger comfort. Since the shape of the high-speed train head can directly influence the surrounding airflow, optimizing the head shape is the primary way to improve the aerodynamic performance of the train. This paper reviews current research studies on the surrogate-based aerodynamic shape optimization of high-speed train heads, aiming to provide a comprehensive reference for designers to enhance design efficiency and optimization performance. The entire optimization process is divided into four essential steps, and the key optimization technologies in each step are discussed, including parametric modeling, computational fluid dynamics (CFD) simulation, surrogate model and optimization algorithm. By introducing the practical applications of these technologies, we summarize their advantages and disadvantages and suggest four potential research directions for the future.]]></description>
      <pubDate>Thu, 17 Oct 2024 09:15:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2434990</guid>
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