Dynamic Crash Research Articles

An ALNS-based approach for the traffic-police-routine-patrol-vehicle assignment problem in resource allocation analysis of traffic crashes

Objectives Imbalances between limited police resource allocations and the timely handling of road traffic crashes are prevalent. To optimize resource allocations and route choices for traffic police routine patrol vehicle (RPV) assignments, a dynamic crash handling response model was developed. Methods This approach was characterized by two objective functions: the minimum waiting time and the minimum number of RPVs. In particular, an adaptive large neighborhood search (ALNS) was designed to solve the model. Then, the proposed ALNS-based approach was examined using comprehensive traffic and crash data from Ningbo, China. Results Finally, a sensitivity analysis was conducted to evaluate the bi-objective of the proposed model and simultaneously demonstrate the efficiency of the obtained solutions. Two resolution methods, the global static resolution mode, and real-time dynamic resolution mode, were applied to explore the optimal solution. Conclusions The results show that the optimal allocation scheme for traffic police is 13 RPVs based on the global static resolution mode. Specifically, the average waiting time for traffic crash handling can be reduced to 5.5 min, with 53.8% less than 5.0 min and 90.0% less than 10.0 min.

On the crashworthiness of aperiodic chiral mechanical metamaterials: design and modeling method

Chiral mechanical metamaterial has become topical in energy absorption for the unusual compression-to-twist deformation determined by the asymmetric chirality geometry of their microstructures. However, the insufficient research on the dynamic crash behavior with high nonlinearity and the lack of efficient design and modeling method have blocked the development of chiral mechanical metamaterials considering crashworthiness. In this work, the structure-property relationship of chiral mechanical metamaterials under medium-strain-rate impact was systematically investigated. We proposed an aperiodic framework considering additive manufacturing which enabled both the ordered and disordered chiral mechanical metamaterials utilizing a screw-theory-based assembly rule. The strut components had variable cross-sections and the joints were fillet-enhanced in order to improve the compressive performance. Meanwhile, the corresponding efficient modeling method for finite element analysis (FEA) was introduced. The constitutive relation, damage criteria, and damage revolution of the 316L stainless steel were established considering strain rate effect. Finally, the deformation mechanisms and energy absorbing capabilities of the proposed chiral mechanical metamaterials were demonstrated and discussed based on the mechanical behaviors and the proposed chirality indexes. The numerical results indicated that the proposed design and modeling method provided an effective paradigm for the crashworthiness design of light-weight materials and structures, facilitating the further applications in fields of automobile, civil engineering, aerospace, etc.

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.

Adjunctive Damage Model to Describe the Interaction of Different Defect Types in Textile Composites on the Strain-Rate-Dependent Material Behaviour

Textile composites are predestined for crash-loaded lightweight structures due to their adjustable energy absorption capacity, but they can exhibit different types of defects that occur during production (voids) and in operation (fatigue). The influence of such defects, especially the interaction of several defect types on the strain-rate-dependent material behaviour, is still insufficiently researched and can represent a safety risk. Therefore, this paper presents a phenomenological model that can be used to mathematically describe the strain-rate-dependent stress-strain behaviour of nominally defect-free and defect-affected textile composites. An adjunctive damage model in the sense of continuum damage mechanics is introduced, which also considers the interaction of both defect types for the first time. For the model validation, extensive experimental tests on glass fibre non-crimp fabrics reinforced epoxy (GF-NCF/EP) composites are performed. The focus is put on the influence of voids and fatigue-related pre-damage under subsequent tensile loading at strain rates up to 40 s−1. The theoretical studies show a good coincidence with the experimental results. The novel model provides a method for the efficient generation of material maps for numerical highly dynamic crash and impact analyses for defect-free and defective textile composites. As a result, a flexible and practice-oriented model approach is available, which makes a significant contribution to an improved understanding of materials and enables a future defect-tolerant design of textile composites.

Full data imputation for freeway time-specific safety performance functions' estimation

Time-specific Safety Performance Functions (SPFs) were proposed to achieve accurate and dynamic crash frequency predictions. Unfortunately, some states do not have or archive the needed high-resolution traffic data to develop time-specific SPFs. This study proposes a novel iterative imputation method to impute the 100% missing volume and speed data from different states with similar crash rates. First, this study calculated the crash rates for 18 states and applied the One-Way Analysis of variance (ANOVA) test to group the states with similar crash rates. Second, as an example FL and VA, which both have traffic data, were used to test the proposed iterative imputation method. The results indicated that the imputed traffic data could capture the same traffic pattern as the real-collected traffic data. Further, the Mean Absolute Error (MAE) between the imputed Ln Volume and the real-collected Ln Volume for FL is only 2.47 vehicles for each segment for three hours. The MAE between the imputed Ln AvgSpeed and the real-collected Ln AvgSpeed for FL is only 1.36 mph. The Mean Absolute Percentage Error (MAPE) between the imputed Ln Volume and the real-collected Ln Volume is 11.07%. Meanwhile, the MAPE between the imputed Ln AvgSpeed and the real-collected Ln AvgSpeed is 7.40%. Finally, this study applied the proposed iterative imputation method to develop time-specific SPFs for the state without traffic data and compared the results. The results illustrated that the time-specific SPFs developed by imputed traffic data perfectly reflected the significant variables for both morning and afternoon peak models, with a prediction accuracy of 87.1% for the morning peak model.

Investigation of the effect of friction force on the energy absorption characteristics of thin-walled structures loaded with axial impact force

In recent years, there has been a significant increase in studies aimed at enhancing the energy absorption capabilities of thin-walled structures used in vehicles. These studies aim to mitigate the adverse effects of shock waves released during crashes by incorporating recesses that trigger folding on the walls of crash boxes, thereby increasing energy absorption. This particular study investigates the energy absorption and crushing behaviors of interpenetrating thin-walled structures under axial crushing conditions. Two different configurations were modeled to determine the contribution of friction force in dampening impacts in thin-walled structures. One configuration exhibited classical folding, while the other initiated folding after interpenetration upon the application of an axial impact load. The interpenetrating structures generate friction forces through recesses and protrusions on the surface of the crash box to provide energy absorption. The simulations were conducted using the finite element method (FEM) in a non-linear explicit dynamic collision scenario. The crash scenarios for both configurations were analyzed under identical conditions using two different materials (DP-600 and DP-800) and three different thicknesses (1.2 mm, 1.4 mm, and 1.5 mm). The dynamic crash simulations were compared based on Specific Energy Absorption (SEA), Total Energy (ET), Peak Crush Force (PK), Crush Force Efficiency (CE), and Mean Crushing Force (FM) values to examine the effects of friction force on energy absorption capabilities and crushing behaviors of the crash boxes. The analysis results demonstrated that friction force and energy absorption play a positive role in the crashworthiness characteristics of thin-walled structures.

Effect of naturalistic seating postures and seatbelt routing on booster-seated Q6 ATD kinematics and kinetics in frontal impacts

Research questions / objectiveTest protocols evaluate restraint performance with pediatric ATDs placed in an ideal seating posture. However, real-world evidence suggests that ideal test conditions do not always reflect actual occupant positions. Prior studies have also shown that booster seat designs affect the position of the seatbelt around the child. Occupants in naturalistic seating postures, coupled with potentially unfavorable seatbelt positions, could result in adverse kinematics and kinetics in a crash. Therefore, the aim of this study was to quantify the effect of different naturalistic seating postures on the response of the Q6 ATD restrained on boosters with varying initial static belt fit in a frontal impact. Methods/data sourcesThe Q6 ATD was positioned on two booster seats of similar design but varying static belt fit metrics in three seating postures: reference, leaning forward, and leaning inboard. These booster seats were chosen from extensive belt fit studies on human volunteers and ATDs, and were defined as follows:•Booster A: more inboard shoulder belt position, more inferior lap belt position, larger gap size.•Booster B: more outboard shoulder belt position, more superior lap belt position, smaller gap size.The booster-seated ATD was restrained on the simulated Consumer Reports test buck (2010 Ford Flex 2nd row seat) with a front blocker plate using a 3-point lap-shoulder belt with a retractor and pretensioner. The sled environment was subjected to the FMVSS 213 frontal impact pulse, and each booster and seating posture was evaluated twice (n = 12 sled tests). Kinematic and kinetic measures were recorded. A linear regression analysis was conducted across postures on each booster. Further, a paired t-test analysis was conducted across booster seats for each seating posture. ResultsAcross seating postures, the reference posture exhibited similar or higher kinematic and kinetic metric values compared to the leaning forward and leaning inboard postures on both boosters. However, both leaning forward (Booster A = 279.5 ± 21.6 mm; Booster B = 298.8 ± 1.5 mm) and leaning inboard (Booster A = 308.7 ± 1.1 mm; Booster B = 331.4 ± 8.5 mm) postures generally resulted in greater head excursion than the reference posture (Booster A = 285.0 ± 16.9 mm; Booster B = 288.1 ± 1.5 mm), indicating greater potential for head contact.Between boosters, Booster A resulted in significantly lower head 3 ms clip acceleration (p = 0.0026), HIC15 (p = 0.0008), upper neck tensile force (Fz)(p = 0.0057), chest 3 ms clip acceleration (p = 0.0013), and right abdominal pressure (p = 0.0163), and significantly higher left ASIS force (Fx)(p = 0.0150) and left (p = 0.0489) and right (p = 0.0088) ASIS moment (My) than Booster B. Upper neck tensile forces on Booster B crossed the 20% and 50% thresholds for AIS3 + injury. Lower abdominal pressure and higher ASIS forces and moments on Booster A suggest that the lap belt loaded the ASIS appropriately, and hence, relatively better kinematics than Booster B. Significance of resultsThis study shows that booster design affects static belt fit which can have an effect on dynamic crash performance and assessment criteria. By connecting static belt fit to dynamic performance, these effects may have the potential to help guide booster seat design.

Real-time safest route identification: Examining the trade-off between safest and fastest routes

Several studies have shown that crash risk is a dynamic quantity that is frequently changing with considerable spatial and temporal variations. Recent advances in safety evaluation techniques such as using extreme value theory (EVT) models provided the opportunity to use traffic conflict data obtained from road user trajectories to estimate real time safety metrics. These metrics can aggregate crash risk along a certain route based on the duration of exposure to unsafe road conditions. This paper applies a Bayesian hierarchal extreme value theory model to trajectories obtained from a drone dataset from Athens, Greece, to develop a safest route algorithm capable of informing users about the safest route in an urban network in real time. The study area selected consists of a rectangular grid made up of 102 signalized and unsignalized intersections. The dynamic crash risk for each link in the network was obtained and used to identify the safest route between any origin–destination pair and the corresponding fastest route. The safest routes were then compared to the fastest routes and were found to be 22% safer on average, resulting in an 11% increased travel time. Moreover, the safest route was identical to the fastest route in 23% of the origin–destination pairs analyzed and had an average similarity of 54% in terms of links. Recognizing the trade-off between safety and mobility, a multi-objective routing methodology was proposed which balances travel time and crash risk using a weighted preference for safety. This work has considerable potential for improving the safety of all road users and may also be used for fleet routing applications as part of multi-objective routing systems.

Changes in the Mechanical Behavior of Electrically Aged Lithium-Ion Pouch Cells: In-Plane and Out-of-Plane Indentation Loads with Varying Testing Velocity and State of Charge

The knowledge about the influence of electrical aging on the behavior of lithium-ion cells under mechanical loads is of high importance to ensure a safe use of batteries over the lifetime in electric vehicles. In order to describe the mechanical behavior in relation to electrical aging, fresh and electrically aged NCM pouch cells were investigated under different mechanical crash loads. For the first time, the aged cells’ behavior under quasistatic lateral loading was taken into account. Aged cells showed lower maximum forces compared to the fresh cells. The reason of the changed mechanical cell behavior was explained with the different buckling behavior of fresh and aged cells by experimental images. Furthermore, quasistatic and dynamic crash tests in cell’s thickness direction were performed at varying state of charge (SOC) and compared to the results of a previously published study. Independently of the testing velocity, the electrically aged cells failed at increased deformation values. This observation was justified by an increased cell thickness due to an additional softer layer, formed on the aged graphite particle surface, which was observed by the means of scanning electron microscopy. Furthermore, the aged cells showed lower failure forces of up to −11% under quasistatic and dynamic loads at 0% SOC. It was also illustrated that electrical aging causes a deeper voltage drop after cell failure, which suggests a higher energy release after the internal short circuit. The investigations show that electrical aging has a significant influence on the mechanical properties of lithium-ion cells and must be taken into account in the safety assessment.

Analytical Approach for Vehicle Body Structures Behaviour Under Crash at Aspects of Overloading and Crumple Zone Length

Abstract Road safety problem is still topical, especially since the number of vehicles and the volume of traffic are increasing. It is possible to increase the safety of road users through systemic changes in many areas related to transport. The deformation of the vehicle body during an accident has an impact on the loads acting on the passengers. Vehicle body deformation depends on complex parameters, and knowledge of these parameters is essential for designing crumple zones and the accident reconstruction process. Knowledge of the mechanical parameters of the vehicle structure during deformation is also a reference to passenger injury indicators assessment. This paper reports results from the analytical approach for determining the protection level of personal vehicles. The proposed conception is based on the results from the static stiffness characteristic of the Ford Taurus, which gives the possibility of phenomenological and simple body crumple analytical description at a speed equal to 10 km/h, 40 km/h, 56 km/h and 60 km/h, which is an original part of the work. The approach enables us to describe the vehicle crash by focusing on variations of deformation in time, stiffness, vehicle collision time (duration), deceleration and dynamic crash force. Basing on the body stiffness data of the personal vehicle, the length of the deformation zone in the front of the car and the maximum values of force at the crash for a speed of 60 km/h are presented. Results obtained by the authors show that is possible to estimate the overloading level during the crash time of a vehicle based on the stiffness characteristic of the car body. The proposed methodology can be developed and the advantage of the presented procedure is an uncomplicated useful tool for solving complex problems of a vehicle crash.

Time-specific hierarchical models for predicting crash frequency of reversible and high-occupancy vehicle lanes

Time-specific Safety Performance Functions (SPFs) were proposed to achieve accurate and dynamic crash frequency predictions. This study contributes to the literature by developing time-specific SPFs for freeways that include reversible lanes (RL) and freeways that include High-Occupancy Vehicle lanes (HOV) using Microwave Vehicle Detection System (MVDS) data from Virginia, Arizona and Washington States. Variables that capture the time-specific traffic turbulence were prepared and considered in the developed SPFs. Moreover, two different hierarchical models were proposed to identify factors associated with the different crash types or severity in crash frequency prediction. The results indicated that the variables representing the volume difference between reversible and general-purpose lanes (GPL) were positively associated with crash frequency. Further, the variable that indicated the design of the access point of the reversible lane was positively associated with crash frequency. The models comparison results showed that the hierarchical models outperformed the corresponding Poisson lognormal model with lower AIC and MAE values. This study also tested the proposed hierarchical models on High-Occupancy Vehicle freeway sections and reached the same conclusion on model comparison results. The significant variables representing the logarithm of volume were found to be significant and positive with crash frequency. Moreover, the difference in average speed between the HOV lanes and GPL was also found to be positive and significant with the crash frequency. In general, this study successfully identified the factors associated with the different crash types or severity in crash frequency prediction models.

Crash Performance of Strength Gradient Tube Induced by Selective Laser Patterning.

This paper presents an investigation of the performance of a 22 MnB5 tube after local heat treatment according to a patterning shape under dynamic crash test conditions to propose the patterning shape with the best energy absorption efficiency. Numerical simulations support experimental results to validate the deformation mode during dynamic crash test as well as the strain distribution of the specimen. The helical patterning not only demonstrates the highest axial loading force and energy absorbance in both static and dynamic crash tests, but also can be easily fabricated in a short time. The helical pattern can optimize different pitch sizes according to the thickness and diameter of the cylindrical tube, and it has the highest energy absorption rate with 83.0% in dynamic conditions.

Short-Term Safety Performance Functions for Freeways Including High Occupancy Vehicle Lanes

Short-term safety performance functions (SPFs) were proposed to achieve accurate and dynamic crash frequency predictions and bridge the gap between annual crash frequency prediction and real-time crash likelihood prediction. The proposed short-term SPFs consider the temporal variation in crashes and traffic characteristics. This study contributes to the literature by developing short-term SPFs at hourly aggregation levels for freeways that include high-occupancy vehicle (HOV) lanes using loop detector data from Arizona State, U.S. Variables that capture the short-term traffic turbulence were prepared and considered in the developed SPFs. Further, this study investigated the factors contributing to crash frequency using three different ways to represent the hourly traffic: annual average hourly traffic, annual average weekday hourly traffic (AAWDHT), and annual average weekday peak hour traffic (AAWDPT). The results indicated that the traffic volume variable was found to be significant in all the developed models. Further, the variables that represent the speed and occupancy differences between HOV lanes and general-purpose lanes were positively associated with crash frequency. This study proposed a series of variables that reflect the short-term traffic turbulence. The models comparison results showed an improvement in [Formula: see text] from 2.4% to 12.8% when including the proposed variables. Further, the results indicated that the Poisson-lognormal approach outperformed the basic negative binomial model in both AAWDHT, and AAWDPT models. Further, the AAWDPT model was found to have the best performance in relation to Akaike information criterion and [Formula: see text].

Experimental and numerical analysis on suitability of S-Glass-Carbon fiber reinforced polymer composites for submarine hull

Suitability of S-Glass/carbon fiber reinforced polymer composite for submarine hull subjected to hydrostatic pressure has been investigated in the present study. Metallic materials have raised concerns owing to their decomposition due to low resistance towards salinity and hence polymer composites have been explored to showcase their mechanical stability to withstand transverse and impact loads. To this end, the mechanical properties of S-Glass/carbon fiber reinforced polymer composite were experimentally investigated and higher specific strength and stiffness of the composite in comparison to many metallic materials used for submarine hull were reported. The obtained experimental values were used for the static and dynamic crash analysis of the bow, stern and foil through Finite Element Analysis (FEA); where depth of travel was varied from sea surface level of 0–7000 m. Submarine assembly was later developed with the optimum shape and thickness of each part. We also report the nonlinear crash analysis upon impact at velocity ranging from 3 to 21 m/s. Besides, kinetic energy, acceleration peak and internal energy in struck submarine revealed that travel depth 1750 m and 3500 m is recommendable, more particularly, crash safety factor of the submarine is found to be within limit when submarine encounters crash at 1750 m.

Identification of dynamic traffic crash risk for cross-area freeways based on statistical and machine learning methods

Freeway traffic safety should be given great attention due to the frequent and serious consequences that arise from freeway traffic crashes. With the possibility of obtaining high resolution traffic big data, traditional freeway safety promotion methods are gradually replaced by the emerging technology of active safety control based on the real-time traffic data. However, there is still a lack of cross-area pertinence towards dynamic traffic safety currently. To overcome the defects of existing dynamic traffic crash precursors identification studies and provide precise theoretical basis for freeway dynamic safety control, this research took cross-area freeways as the research object. Firstly, based on the LOS (level of service) A–F theory and the consideration of area types, six units to be evaluated were generated (two dimensions totally: saturated/unsaturated flow, urban/suburban/mountainous). Then, conditional logistic regression based on Markov chain Monte Carlo method was adopted to quantitatively evaluate the dynamic risk of cross-area freeways. Finally, 20 related traffic flow variables were extracted from five dimensions which can reflect the dynamic traffic flow characteristics, and the machine learning approaches including random forest algorithm and Bayesian logistics regression were applied for analysis and modeling; then, crash precursors were identified for each type of freeway area, and the statistical relationship between traffic flow variables and crash risk was established via the statistical models. The results show the area types and traffic conditions of freeway are significantly correlated with dynamic traffic safety, and the crash risk in the urban area/saturated flow condition is the highest, which is 29.6 times of that in the condition of suburban area/unsaturated flow. When the traffic operates at the freeway of urban/unsaturated flow, the formation of small fleets and the lane changing behavior play a dominant role influencing crash risk; when operating at urban/saturated flow, frequent acceleration or deceleration in the fleet and frequent lane changes during the formation of the fleet have great impact towards crash risk. When traffic operates at suburban/unsaturated flow, the main crash precursors are the sudden change of occupancy and volume in a short period, as well as the formation of a small fleet. When operating at suburban/saturated flow, the crash-prone variables are the sudden increase of speed and occupancy in a short period and the change of volume. When traffic operates at mountainous/unsaturated flow, the changes of speed and occupancy in a short period and the formation of small fleets are the main factors influencing crash. When operating at mountainous/saturated flow, lane changing behavior, the sudden increase of volume, and the speed mutation of some vehicles in saturated flow are the significant precursors. The results indicate every area type of freeway has a different mechanism of traffic crash. Moreover, with the consideration of freeway area types and traffic state differences, the machine learning and statistical combination models proposed in this research can identify the relationship and mechanism between dynamic traffic flow characteristics and traffic safety more comprehensively and accurately, and the identification results in this research can refer to the further dynamic crash prediction work for cross-area freeway.

Strain rate-dependent crash simulation of woven glass fabric thermoplastic composites

Woven fabric thermoplastic composites possess high specific strength and stiffness along with thermoformability. To utilize the full potential of these materials to achieve better crash-safe designs in automotive structural parts, their crash behavior must be predicted accurately. For reliable crash simulations, strain rate-dependent material data and equally capable material modeling are required. In this study, quasi-static and high-speed tests are carried out to measure tensile and in-plane shear properties. A strain rate-dependent continuum damage mechanics model is formulated to describe the deformation and damage behavior of woven glass fabric composites. Tensile and in-plane shear tests on a lab scale are used to calibrate the material parameters of the model. The model was implemented as a user-defined material subroutine (VUMAT) for Abaqus. Experimental results from coupon tests were used to verify the results of a single-element simulation. Finally, a structural level dynamic crash test of a u-profile on a drop tower was used to validate the predictions of the user material model.

Exploring implicit relationships between pavement surface friction and vehicle crash severity using interpretable extreme gradient boosting method

Pavement friction has been identified as crucial in traffic safety. Since the Highway Safety Manual prediction algorithm is often based on crash frequency, the crash severity distribution might be assumed unchanged before and after the countermeasure. However, pavement surface treatments can improve the friction to different levels, by which crash severity outcomes may vary greatly. To explore the implicit effects of pavement friction on vehicle crash severity, this paper first validates the extreme gradient boosting model performance and then the Shapley additive explanations interaction values are employed to interpret individual features and the nonlinear interactions among predictors. Under various scenarios, the extreme gradient boosting (XGBoost) output probability is utilized to convert into dynamic crash severity distributions. Results also indicate that friction becomes more significant when the friction number is less than 38, and immediate corrective actions are needed when the friction number is below 20.

Dynamic frontal crash performance of old and used child restraint systems

Objective To examine the effect of age on the dynamic performance of child restraint systems in frontal crashes. Methods A sample of used (3-269 months from manufacture) and newly purchased child restraints were subjected to frontal crash simulations of more than 56 km/h and peak deceleration approximately 33 g on a deceleration sled. Restraints were monitored for evidence of damage before and after each impact. Anthropometric test device (ATD) head and chest responses and peak head excursions were recorded for rearward facing restraints using the Q1 ATD and for forward facing restraints and booster seats using the Q6 ATD. The influence of restraint age on peak 3 ms head acceleration, HIC15, head excursion, peak 3 ms chest acceleration and restraint damage were analyzed. Results In all impacts, the ATD remained within the restraint and secured to the test bench demonstrating the crash protection offered by the old and used restraints. There was no apparent relationship between ATD responses and restraint age for any restraint type. Older forward facing restraint systems had a very modest increase in forward head excursion (R2 = 0.59, p = 0.001) of 0.27 mm for each month of age (95% CI, 0.13 mm − 0.42 mm). This equates to a 0.7% increase in the minimum measured excursion per year of restraint age. There was also a small increased likelihood of critical damage to the restraints in the simulated crashes per month of restraint age (OR 1.031, 95% CI 1.010-1.069). Conclusions Overall, degradation in restraint dynamic performance in older restraints, including some that are much older than the currently recommended 10-year lifetime, is minimal. However newer restraints may provide better protection due to marginal improvements in restraint design over time. Furthermore, the results of this study confirm previous recommendations that restraints should not be re-used after crash involvement.

Targeting the acceleration-time response of vehicle structures under crash impact using equivalent dynamic loads

This work introduces an optimization procedure derived from the targeting force-displacement response (TFDR) method to improve the crashworthiness of full-size vehicle structures. The proposed method aims at targeting the vehicle’s acceleration-time response (ATR) under a crash event using topometry (thickness) optimization. In contrast to the original TFDR method, the proposed targeting method uses a moving coordinate system (MCS) that allows addressing fully dynamic crash models with initial velocity. By setting a proper target ATR curve, the proposed method can improve several crashworthiness indicators including specific energy absorption, maximum deceleration, dynamic penetration, and crash load efficiency. The result of the topometry optimization could be a guideline for the further design. In the proposed method, the nonlinear optimization problem is discretized into a series of analytical subproblems using equivalent dynamic load (EDL). In each iteration, the dynamic response from an explicit dynamic finite element (FE) analysis is utilized to define and solve a subproblem. To demonstrate the proposed iterative method, the baseline FE model of a Dodge Grand Caravan vehicle, obtained from the US National Highway Traffic Safety Administration (NHTSA) website, is optimized. The results show the effectiveness of the algorithm finding the element thickness distribution to make the acceleration-time response of the vehicle’s center of gravity (VCG) gradually approach a target curve. The proposed EDL algorithm finds a converged solution using less than 15 crash simulations. This makes it possible to solve problems involving full-size vehicle FE models.

Coupled crash mechanics and biomechanics of aircraft structures and passengers

The DYCAST (Dynamic Crash Analysis of Structures) experiments that started at NASA Langley Research Center during the late 1970s have greatly influenced the methodology and thinking of aircraft crashworthiness and survivability studies, and was continued and refined at other aerospace establishments. Nevertheless, so far most of the existing work has emphasized the impact damage to the aircraft section. Issues related to potential passenger injuries have not been properly addressed in the literature, to the best of our knowledge. Here, we study the DYCAST problem integrally by treating and combining impact damage and passenger injuries altogether. We develop the biomechanics by way of modal analysis of passenger dummy motions coupled with the vibration of aircraft structures in order to understand their basic interactions. Two types of mechanical dummies are used in this study. Such a modal analysis can help identify basic injury types, but is valid only in the constructed models, linear regime. However, we are able to extend the linear elastic model to a nonlinear elastoplastic computational model by using the versatile software LS-DYNA as the platform. Computer simulations are carried out on the supercomputer clusters and the numerical results are rendered into video animations for visualization and analysis. One can see, for example, how the passenger-dummy interactive motions with the fuselage and fixtures and the potential injuries caused in the event of general aircraft crashes on a fractal domain.