Car Hood Research Articles

Energy absorption and frequency analysis of the nanocomposites reinforced car’s hood under airflow pressure

This study focuses on the energy absorption and frequency analysis of a car’s hood reinforced with graphene platelets nanocomposites under airflow pressure. The integration of nanocomposites aims to enhance the mechanical properties and energy absorption capacity of the hood, crucial for improving vehicle safety and performance. We investigate the dynamic response of the hood structure subjected to varying airflow pressures, utilizing advanced computational models to simulate real-world conditions. The analysis employs numerical method to evaluate the frequency characteristics and energy absorption efficiency of the nanocomposite-reinforced hood. Results indicate significant improvements in both energy absorption and frequency response, highlighting the potential of nanocomposite materials to optimize the dynamic performance and structural resilience of automotive components. This research provides valuable insights into the design and application of nanocomposite materials in the automotive industry, promoting the development of safer and more efficient vehicles. The findings suggest that incorporating nanocomposites in car hoods can lead to superior impact resistance and vibration dampening, which are critical for maintaining the integrity and functionality of the vehicle under operational conditions.

Investigating thermal and free vibrational properties of fabric sandwich composite materials for car hood application

Textile fabric wastes are the second most polluting materials in the world after plastic. This study investigated the thermal and free vibrational properties of the sandwich composites prepared from recycled fabric materials. Grey cotton fabric(C) and wool garment waste (G) reinforced a polyester matrix in a different layer arrangement (CCCC, CGCG, CGGC, GCCG, GGGG, and chopped). Thermogravimetric analysis (TGA) and dilatometry were performed to determine the thermal properties. TGA results showed similar initial weight loss for GCCG, CCCC, and CGGC (within a range of 25 °C–800°C) and for GCGC, GGGG, and chopped arrangements. All composites exhibited thermal stability up to 305°C. Between 310°C and 405°C, a gradual mass loss was observed, followed by more significant degradation above 405°C and residual mass loss observed at 655°C. Dilatometry tests reveal minimal volume change up to a heating temperature of 300°C for all durations (20 min, 40 min, and 60 min). In addition, the free-vibration analysis indicated poor energy-absorbing properties for CCCC, while CGGC sandwich composite specimen exhibited better energy-absorbing properties. Based on these results, it can be concluded that these composite materials are suitable for applications such as car hoods, which typically function below 105°C temperatures.

Introducing advanced nanocomposites to enhance the efficiency and stability of the car’s hood door subjected to axial loading via deep neural networks in the mathematical framework

In order to improve the efficiency and stability of automobile hood doors under axial loading circumstances, this research investigates the reinforcing of these doors using graphene oxide powders (GOP). This work is separated into two different parts. In the first part, using the mathematical modeling, the results of the presented applicable structure are obtained. After that using the datasets of the mathematical modeling section, the results of deep neural networks (DNN) are trained, tested, and validated. The work focuses on double-curved panels’ linear strain fields, which are an essential part of vehicle construction. We solve the governing equations and boundary conditions for the reinforced automobile hood doors by using Navier’s solutions. GOP greatly enhances the mechanical characteristics by offering better load-carrying capability and deformation resistance. Our results show that DNNs can reliably and effectively forecast the performance of GOP-reinforced structures, providing a useful tool for improving automobile hood door designs. Enhanced automobile safety and durability are made possible by the combination of cutting-edge computational methodologies and novel materials, which also meet the increasing need for high-performance car components. This work highlights the revolutionary power of both technologies on contemporary vehicle design and manufacture, underscoring the mutually beneficial relationship between nanomaterial reinforcement and machine learning in the advancement of automotive engineering.

Investigation of the Influence of Layer Orientation on the Free Vibration Characteristics of Sandwich Composite Materials Utilizing Fabric Waste for Car Hood Application

Investigation of the Influence of Layer Orientation on the Free Vibration Characteristics of Sandwich Composite Materials Utilizing Fabric Waste for Car Hood Application

Radiocesium-bearing microparticles found in dry deposition fallout samples immediately after the Fukushima nuclear accident in the Kanto region, Japan

Radiocesium released by the Fukushima Dai-ichi Nuclear Power Plant (FDNPP) accident still exists in the environment in two forms: adsorbed species on mineral particles in the soil and microparticles containing radiocesium mainly composed of silicate glass (CsMPs). CsMPs are dispersed not only around the FDNPP but also over a wide area of the Kanto region. The behavior and characteristics of CsMPs must be investigated to evaluate the impact of the FDNPP accident. Deposited particles including radiocesium were wiped from metal handrails on balconies and car hoods using tissue papers at six locations in the Kanto region (Tokai village, Ushiku City, Abiko City, Chiba City, Kawaguchi City, and Arakawa Ward) between March 15 and 21, 2011. CsMPs were isolated from the samples, and their characteristics were investigated. In total, 106 CsMPs derived from Unit 2 were successfully separated from 13 tissue paper samples. The radiation images of the two types of CsMPs discovered in Ushiku City demonstrate that CsMPs can easily become susceptible to fragmentation over time, even in the absence of weathering effects.

Characterizing the time-dependent external force on the cars’ hood door in accident using deep neural networks

The car hood door is a very important part of a car, especially in the time of an accident. So, in this report for the first time, the innovative applicable model is presented to simulate the transient dynamics of a car’s hood door under axial mechanical shock loading at the time of the accident. Due to axial mechanical shock excitation, it is very important to improve the stability of the structure in the axial direction. So, the composite structure is reinforced by graphene nanoplatelets in the axial direction. For modeling the current structure, the differential conditions are translated into Laplace space in order to determine how the system will react as a function of time. At this stage, Laplace space is employed to infer a temporal perception of the system's reaction using Abate and Dubner's modified message of strategy. To verify the results, the current results are compared to open-source results from the literature and deep neural networks (DNN). To anticipate the system's vibrational behavior, DNN incorporates a supervised neural network based on physical data. In this situation, data-driven research and solutions are used to determine natural frequencies. The results highlight how important GPL characteristics are to transient and forced vibrations of the composite system. The findings of the present research may serve as a reference point and as helpful suggestions for the next structural design methods with improved qualities.

Utilization of textile fabric waste as reinforcement for composite materials in car body applications: A review

Materials are one of the basic elements or needs for continuing human beings’ life living and they are used for structural and nonstructural, biomedical, thermal, or other applications. In many types of materials, Composite materials are used in different sectors. The increasing need for eco-friendly, low-density, and lightweight product production prompted the development of fiber-reinforced polymer composites for usage in a variety of home items and automobile parts. The automobile manufacturing sectors have recently attempted to manufacture lighter and lighter parts. Shortly, automobiles must be lighter to meet demands for lower fuel usage and fewer CO2 emissions. On the other side that textile waste is still simply thrown into a landfill in the environment resulting in and causing pollution. So, the objective of this review was to show the ability of these waste materials used as reinforcing material for composite fabrication products like car hoods, Car bumpers, and lightweight automotive parts. also, it tries to explain the roles of lightweight materials for automotive body parts and also the reduction of wastes in the textile industry by recycling and converting them into useable products, making the environment free of pollution. This waste reduction is a current world issue.

Learning hyperparameter predictors for similarity-based multidisciplinary topology optimization

Topology optimization (TO) plays a significant role in industry by providing engineers with optimal material distributions based exclusively on the information about the design space and loading conditions. Such approaches are especially important for current multidisciplinary design tasks in industry, where the conflicting criteria often lead to very unintuitive solutions. Despite the progress in integrating manufacturing constraints into TO, one of the main factors restricting the use of TO in practice is the users’ limited control of the final material distribution. To address this problem, recently, a universal methodology for enforcing similarity to reference structures in various TO methods by applying scaling of elemental energies was proposed. The method, however, requires an expensive hyperparameter sampling, which involves running multiple TO processes to find the design of a given similarity to a reference structure. In this article, we propose a novel end-to-end approach for similarity-based TO, which integrates a machine learning model to predict the hyperparameters of the method, and provide the engineer, at minimal computational cost, with a design satisfying multidisciplinary criteria expressed by the similarity to a reference. The training set for the model is generated based on an academic linear elastic problem, but the model generalizes well to both nonlinear dynamic crash and industrial-scale TO problems. We show the latter by applying the proposed methodology to a real-world multidisciplinary TO problem of a car hood frame, which demonstrates the usefulness of the approach in industrial settings.

Point of Departure

"Point of Departure" features a speaker who sees a car's hood fly off on her drive over a viaduct, which triggers a memory about a miscarriage.

Non-uniform [formula omitted] patches around extraordinary points with applications to analysis-suitable unstructured T-splines

This article extends the subset of analysis-suitable unstructured T-splines (ASUT-splines) that have C1 continuity in irregular regions to allow non-uniform knots at extraordinary points. That is, we remove the preceding restriction that required uniform spoke edge knot spans of ASUT-splines. To achieve this, the degenerate-patch (D-patch) framework, which has been demonstrated to be an effective approach for generating refinable spline spaces over unstructured quadrilateral meshes, is generalized to the non-uniform case. We prove that uniform smoothing matrices are also valid for non-uniform knots. However, we also show that nested refinements of ASUT-splines are not available if using these matrices in the non-uniform case. Therefore, a new idempotent smoothing matrix is introduced to overcome this limitation. The detailed construction of this smoothing matrix is given, which helps to study more kinds of smoothing matrices in the future. Then, the non-uniform D-patch framework is employed for ASUT-splines. We provide a thorough discussion of the differences between the uniform and non-uniform cases. A new refinement strategy for the design space of ASUT-splines is also presented. Numerical experiments show that our extension of ASUT-splines can construct non-uniform parameterization around extraordinary points while maintaining the C1 continuity of the surface and optimal convergence rates for isogeometric analysis of both the Poisson problem and the biharmonic problem. A car hood model with complex shape features is used to demonstrate the ability of the proposed method to design and analyze practical models within a seamlessly integrated framework.

CarHoods10k: An Industry-Grade Data Set for Representation Learning and Design Optimization in Engineering Applications

Large-scale, high-quality data sets are central to the development of advanced machine learning techniques that increase the effectiveness of existing optimization methods or even inspire novel ones. Especially in the engineering domain, such high-quality data sets are rare due to confidentiality concerns and generation costs, be it computational or manual efforts. We, therefore, introduce the OSU-Honda Automobile Hood Dataset (CarHoods10k), an industry-grade 3-D vehicle hood data set of over 10 000 shapes along with mechanical performance data that were validated against real-world hood designs by industry experts. CarHoods10k offers researchers and practitioners the unique opportunity to develop novel methods on realistic data with relevance to real-world vehicle design. To illustrate central use cases, we first apply methods from geometric deep learning to learn a compact latent representation for design space exploration. Second, we use machine learning models to predict mechanical hood performance from the learned latent representation. We thus demonstrate the effectiveness of machine learning for building metamodels, which are used in design optimization whenever possible to replace costly engineering simulations. Third, we integrate CarHoods10k in a topology optimization approach based on evolutionary algorithms to demonstrate its capability to search for high-performing structures, while maintaining manufacturability constraints.

Characteristics of human movement and injury in a side collision between the front of a small car and a bicycle

ObjectiveOur research groups have studied the movement and injury characteristics of the human body in a side collision between the front of a small car and a pedestrian. This study discusses the movement and injury characteristics of the human body in a side collision between the front of a small car and bicycle. MethodsA total of 31 cases of traffic accidents caused by small car collisions when riding a bicycle across a road were collected. Through on-site inspection and trace inspection of the accident vehicles and bicycles, the speed of the car during the collision was calculated, the collision relationship between the small car and bicycle was determined, and the injury site and degree were determined through autopsy. The car speed was divided into two groups: <60 km/h and >60 km/h. Injuries of the skull, cervical spine, ribs, pelvis, femur and tibiofibular were analysed, and the correlations with the height of the bicycle controller, the height of the bicycle seat, the height of the car hood and the length of hood were discussed. PC-Crash was used for simulation analysis to further clarify the injury process. ResultsThe ratio of the height of the bicycle seat to the height of the hood plus the length of the hood in the windshield-damaged group was larger than that in the undamaged windshield group (P < 0.05). No cervical fracture was found when V < 60 km/h, and 52.94% of cases had cervical fracture when V > 60 km/h. The ratio of the height of the bicycle seat to the height of the hood in the pelvic fracture group was smaller than that in the nonpelvic fracture group (P < 0.05). The incidence of tibiofibular fracture was less than 65%. ConclusionsWhen a side impact between a car front and a bicycle occurs, the resulting human injury is related not only to the speed but also to the height of the bicycle seat and the height and length of the hood of the car. The incidence of tibiofibular fractures was significantly lower than that of small car front-pedestrian side impacts.

Static Structural Analysis of Automobile Hood using Natural Hybrid Fiber Composite

Natural fibres are a kind of renewable source and a replacement generation of reinforcements and supplements for polymer-based materials. The event of natural fibres composite materials or environmentally friendly composites has been a hot topic recently because of the increasing environmental awareness. Natural fibres are one such skilful material that replaces the artificial materials and its connected product for the less weight and energy conservation applications. the appliance of natural fibres bolstered compound composites and natural-based resins for replacement existing synthetic polymer or glass fibres reinforced materials in large. Automotive and aircrafts industries are actively developing different styles of natural fibres, primarily on hemp, flax and sisal and bio resins systems for their interior components. High specific properties with lower costs of natural fibres composites are making it attractive for various applications. within the gift study automobile hood is analysed for hybrid material. From the analysis it's evident that the material is maintaining its structural integrity for given loading condition.

Hood Flutter Under Transient Aerodynamic Loads

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Automobile hood design is driven by many factors, such as strict government regulations, fuel economy, weight, manufacturability, aerodynamic performance, aesthetics, structural integrity, and pedestrian safety standards. The requirement of improved fuel economy and safety regulations like pedestrian protection drive designers to reduce the thickness of the hood parts and use lighter materials. This leads to significant reduction in the hood stiffness. The hood needs to withstand steady and unsteady aerodynamic loads and meet deflection and vibration targets. The susceptibility of the hood to adverse aero load response is increased as the stiffness of the hood is reduced.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;The objective of this study is to develop a methodology to simulate hood behavior under transient aerodynamic loads in controlled environments. This study mainly focuses on developing fluid structure interaction methodology to simulate the behavior of the hood system under transient aerodynamic loads.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;A flat plate approach was applied to create disturbance in wind flow to simulate a vehicle in front of the target vehicle in wind tunnel. This situation is simulated using computational fluid dynamics (CFD) software to generate transient aerodynamic loads.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;The CAE simulations help to understand the hood behavior under transient aero load and mitigate the risk of excessive hood vibration in early development stages of the hood design.&lt;/div&gt;&lt;/div&gt;

An end-to-end approach to autonomous vehicle control using deep learning

The objective of this work is to develop an autonomous vehicle controller inside Grand Theft Auto V game, used as a simulation environment. It is used an end-to-end approach, in which the model maps directly the inputs from the image of a car hood camera and a sequence of speed values to three driving commands: steering wheel angle, accelerator pedal pressure and brake pedal pressure. The developed model is composed of a convolutional neural network and a recurring neural network. The convolutional network processes the images and the recurrent network processes the speed data. The model learns from data generated by a human driver´s commands. Two interfaces are developed: one for collecting in-game training data and another to verify the performance of the model for the autonomous vehicle control. The results show that the model after training is capable to drive the vehicle as well as a human driver. This proves that a combination of a convolutional network with a recurrent network, using an end-to-end approach, is capable of obtaining a good driving performance even using only images and speed velocity as sensory data.

Kajian Penggunaan Serat Batang Pinang Raja Dengan Komposisi 50% Serat Sebagai Material Peredam Suara Pada Kap Mesin Mobil

This study aims to determine the characteristics of silencers, thermal properties, noise reduction with variations in measurement distance, and the process of making natural fibre acoustic materials into silencers on the car hood. The process of making sound-absorbing material using the casting method is then emphasized using a mould lock. The composition of the sound-absorbing material is 50% rod areca nut fibre with 32 mesh and 50% is a mixture of gypsum and polyurethane. The results obtained for the maximum sound dampening characteristic value (α) of 0.7162 occur at a frequency of 125 Hz and a minimum of 0.4532 at a frequency of 1500 Hz. The thermal properties of the sound-absorbing material were obtained by using DTA. The results of the DTA test showed that at a temperature of 318oC the sound-absorbing material started to burn. The reduction in noise level is obtained by comparing the hood using a silencer and without using a silencer with an SPL measuring instrument on a stationary engine without load and under load. The measurement results show that the percentage of the average decrease on the X- side is 1.01% and X-' is 10.14%, X+ side is 7.54% and X+' is 4.81%, Z- side is 2, 77% and Z-' is 11.46%, Z+ side is 13.25% and Z+' is 3.86%. The conclusions obtained from this study indicate that the silencer made of rod areca nut raja mesh 32 with a polyurethane and gypsum matrix is suitable for use as a sound absorber on a car hood

Implementation of Laminate Structure in Car Hood and Study of its NVH Parameters

This paper examines the implementation of Laminate structure and aluminium panels in Hood in place of conventional steel hood. In laminate structure, 3 layers is considered with aluminum as a face material and PVC Solid as a core material which helps in efficient energy absorption and provide necessary stiffness for the panel. It has been observed that the natural frequency is improved over conventional steel bonnets with benefit of weight reduction in hood assembly. To validate its NVH performance static stiffness, natural frequency and torsional stiffness has been calculated and it has been found that Laminate structure Hood has better performance than steel hood with overall weight reduction of 41.36%.

Fabrication of doubly-curved CFRP shell structures with control over fiber directions

We introduce a fabrication method of doubly-curved shell structures by CFRP with control over fiber directions. Doubly-curved surfaces are tessellated into structured quadrilateral patches according to the purpose of use. One can design the tessellation in the parameter space, and map it to the 3D parametric surface, or use the orthogonal net of curves on surfaces such as lines of curvature, principal stretch lines, and principal stress lines. These patches, which we call generalized principal patches, are flattened onto a plane, and connected one by one by aligning the equi-length adjacent edges using translations and rotations forming generalized principal strips. Carbon fiber tows are placed onto these strips with one stroke by tailored fiber placement embroidery machines so that the fibers are not disconnected within strips. Preforms are stacked layer by layer into a mold of particular parts, and VaRTM or L-RTM method is employed to fabricate CFRP parts. We demonstrated the effectiveness of our proposed method by manufacturing an automobile hood and a marine propeller blade.

Elastic properties and multi-scale design of long carbon fiber nonwoven reinforced plane-based isotropic composite

Carbon fiber reinforced composite is considered as a potential substitutes used in the lightweight of automotive engineering. Nevertheless, the high price and complicated manufacturing process remain challenges for the large-scale application of conventional carbon fibers. In this study, a novel plane isotropic composite reinforced by long carbon fiber non-woven is introduced, which overcomes the obstacles in the application of carbon fiber at present. A multi-scale optimization method is proposed to realize the performance optimization and lightweight design of composite components. The linear elastic properties of long carbon fiber non-woven composite (LCFNC) were studied experimentally and analytically. The predictions of homogenization theory were found to be very similar to the experimental results within an interval of volume fraction. Then the relationship between microstructure and material performance was evaluated in detail. The results showed that there is a critical point for the influence of aspect ratio to the material properties. Thirdly, thickness of LCFNC at macro scales and the fiber parameters at micro scales were simultaneously optimized by Non-dominated sorting genetic algorithm-II (NSGA- II) to enforce multi-objective optimization design. Finally, the lightweight design of automobile hood was performed by the LCFNC and the proposed method. The results showed that the weight of automobile hood was reduced by 37%, while exhibiting better stiffness and strength performance compared with the conventional steel.

Geometric Modeling of Compound NURBS Surfaces

The design of sculptured surfaces occupies an essential area in the field of modern industrial, aerospace, and medical applications. The challenge is to design products that have complex features efficiently with great flexibility of editing in certain regions without affecting other regions, which the designer has no intent to modify. In this paper, we propose a surface design method based on compound NURBS surface to model automotive parts with 400 control points. First, a Non-Uniform B-Spline basis function is derived with a cubic degree and 20 control points. This method is utilized to design car posterior door, car hood, and rear car door as case studies.