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Relating the response of idealized analogue particles and real sands
Published in Heinz Konietzky, Numerical Modeling in Micromechanics via Particle Methods, 2017
Catherine O’Sullivan, Jonathan D. Bray
This paper discusses the development of a new type of particle, the overlapping sphere cluster, for use in three-dimensional discrete element analysis. Firstly a review of previous studies considering the sensitivity of the response of granular materials to particle shape is presented. Details of the implementation and validation of the overlapping sphere cluster are then outlined. Using quantitative shape analysis, the ability of the proposed new particle shape to capture the geometry of real sands is explored. Finally, a discrete element simulation of a plane strain compression test using overlapping sphere clusters is compared with a simulation using uniform spheres. The simulation method is validated using physical test data from a plane strain compression test on uniform balls.
Concrete DIF and its application in modelling the behaviour of FRP-concrete bond
Published in Alphose Zingoni, Insights and Innovations in Structural Engineering, Mechanics and Computation, 2016
Three loading rates were then simulated, namely 5, 50 and 200 mm/s (ε˙=0.1,1.0 and 4.0 s−1), respectively. The results are compared with Ross’s (1989) test data together with the global DIF curve proposed by Malvar et al. (2000). The achieved apparent DIF are plotted against the corresponding engineering strain rates and compared with the empirical curve and some physical test data in Figure 2.
Post-Repair Application Quality Assurance
Published in Heslehurst Rikard Benton, Engineered Repairs of Composite Structures, 2019
Product Quality Assurance Testing is the physical test of a product to show or demonstrate that it meets a set of known acceptance standards. This is to say, the product achieves the required level of mechanical strength, stiffness, durability properties, etc. for which it is designed. Quality assurance testing is the final proof of a successful quality control implementation.
Optimization of vehicle pulse index parameters based on validated vehicle-occupant finite element model
Published in International Journal of Crashworthiness, 2023
M. S. Abdul Samad, M. K. Mohd Nor, M. M. Abdul Majid, K. K. Abu Kassim
Numerical calculations are performed and through optimization, the configuration of restraint systems that can fit both FRB56 and ODB64 load cases are tabulated in Table 2. The difference of configurations is only the time to fire (TTF) for both seatbelt pre-tensioner and airbag deployment. Different load cases have different logic gates that were programmed inside the airbag control unit (ACU). It allows the ACU to classify the type of crashes, thus determine the correct TTF depending on crash load cases. The different TTF also applies when the vehicle is subjected to different impact speed, as listed in Table 1. To address this issue, the TTF will be determined based on the displacement of the vehicle, which is the same approach made by NHTSA in their MADYMO simulation model [14]. Figures 4 and 5 shows the animation for the simulation result. As for the correlation, FRB56 and the ODB64 load case has achieved the CORA rating of 0.722 and 0.705 respectively, thus it meets the initial target discussed in the previous section. A detailed comparison between the time history measurement extracted from both simulation and the physical test is depicted in Figures 6 and 7. The FRB56 and the ODB64 physical test data is obtained from NHTSA [11] and IIHS database respectively [19]. Referring to Figure 7, it can be seen that the measurement of pelvis acceleration, shoulder belt load and lap belt load in the physical test is not available. The reason is the aforementioned measurement has no meaningful injury assessment, thus it can be omitted from the test. Regardless, the additional data is useful for correlation purposes.
Mathematical models for assessment of vehicle crashworthiness: a review
Published in International Journal of Crashworthiness, 2022
Gulshan Noorsumar, Svitlana Rogovchenko, Kjell G. Robbersmyr, Dmitry Vysochinskiy
The research by Elkady et al. [43, 44] focuses on developing mathematical models for replicating a vehicle crash using non-linear springs for the vehicle bumper. The lumped parameter model developed in [43] and [45] uses a lumped mass representing the vehicle body and four spring damper units to replicate the suspension and wheels. It is assumed that the vehicle is moving on a flat asphalted road and the vertical motion of the tyres is neglected. The model is designed to explore the effects of Vehicle Dynamics Control Systems (VDCS) on the crash mitigation for an offset impact with a rigid barrier. The effect of ABS (anti-lock braking system) is also simulated by using a braking force component in the equation of motions. The front deformable members are presented by non-linear springs with force deformation characteristics and the forces on the springs during the crash are calculated using numerical methods. The model is validated by comparing the acceleration and deformation of the front end structures to the physical test data. The study concludes that the values of the post impact speed of the vehicle in the mathematical model and in the physical test agree well. The variation in the curves for the front end deformation suggests shortcomings of the model due to the inaccurate values of the system parameters. The article also discusses the effects of VDCS on the collision response for a 50 percent offset impact (Figure 4).
How well a single-track linear model captures the lateral dynamics of long combination vehicles
Published in Vehicle System Dynamics, 2019
M. M. Islam, N. Fröjd, S. Kharrazi, B. Jacobson
In VTM, payload heights are defined as the vertical height of the upper surface of box-type payloads measured from ground. These are independent parameters. In this paper, within each vehicle considered, all the payloads are of box-type with uniform density and the height of each payload takes equal values within a given combination vehicle. For the test vehicle, takes the value of 1.6 m in all three units. In VTM, all the corresponding depended parameters, e.g. mass-moment of inertia etc., are calculated automatically when the vehicle masses and dimension and the payload mass and distribution for all the vehicle units are given. The VTM model with the nonlinear Pacejka PAC2002 tire [43] was numerically simulated with the random steering input, recorded during the physical test at the test track, in computer and the results were compared. The benchmark comparison between the simulation and physical test results is shown in Figure 3(b), which indicates the validity of the high-fidelity VTM model. A certain fitting of the tire cornering stiffness was needed.