Dummy Model Research Articles

Contextual prediction of parking spot availability: A step towards sustainable parking

One of the challenges of living in today's cities is parking availability. Searching for available parking spots can be a time-consuming task that simultaneously increases traffic congestion and greenhouse gas pollution by a significant 40%. A solution that would increase drivers' ability to locate an empty parking spot would represent an important step towards more sustainable parking as it would have a direct impact on reducing greenhouse gas pollution in urban areas. This paper proposes how data science can help by evaluating the prediction performance of four machine learning models. Analysed machine learning models are based on different machine learning methods (i.e., CatBoost and Random Forest) and use different real-world data sets (i.e., parking sensor data only or contextually enriched parking sensor data). The dummy (baseline) model is considered as well, but with a R2 score of 61.29% is outperformed by more advanced data science approaches. Prediction performance in the case of using parking sensor data only gives R2 score of 84.31% and 88.16% for Random Forest and CatBoost, respectively. The best prediction performance is achieved using CatBoost and contextually enriched data, resulting in the high-performing machine learning model with the R2 value of 88.83%, thus outperforming the Random Forest model by 1.7%. In fact, for both machine learning methods, the contextually enriched data approach gives better results for predicting parking spot availability. This suggests that parking data should be enriched with contextual data when designing and building sustainable parking solutions for smart cities of the future.

Developing and Assessing Nonbonded Dummy Models of Magnesium Ion with Different Hydration Free Energy References.

A large diversity in the targeted hydration free energies (HFEs) during model parameterization of metal ions was reported in the literature with a difference by dozens of kcal/mol. Here, we developed a series of nonbonded dummy models of the Mg2+ ion targeting different HFE references in TIP3P water, followed by assessments of the designed models in the simulations of MgCl2 solution and biological systems. Together with the comparison of existing models, we conclude that the difference in the targeted HFEs has a limited influence on the model performance, while the usability of these models differs from case to case. The feasibility of reproducing more properties of Mg2+ such as diffusion constants and water exchange rates using a nonbonded dummy model is demonstrated. Underestimated activity derivative and osmotic coefficient of MgCl2 solutions in high concentration reveal a necessity for further optimization of ion-pair interactions. The developed dummy models are applicable to metal coordination with Asp, Glu, and His residues in metalloenzymes, and the performance in predicting monodentate or bidentate binding modes of Asp/Glu residues depends on the complexity of metal centers and the choice of protein force fields. When both the binding modes coexist, the nonbonded dummy models outperform point charge models, probably in need of considering polarization of metal-binding residues by, for instance, charge calibration in classical force fields. This work is valuable for the use and further development of magnesium ion models for simulations of metal-containing systems with good accuracy.

Determination of material properties of laminates of 15T and T3 tram faces

The article concerns the testing two thin-walled fiberglass materials. The aim of this work was to perform tensile tests at room temperature in order to determine the stress-relative deformation dependence in selected directions and to compare the properties of each individual material in these directions. Characteristics determined in this way are to be used as inputs in simulation models forming a part of the process of validating the dummy model’s behaviour in simulations of collisions of the tram front with a pedestrian. Tests have been conducted of such properties of those materials used for external panelling of 15T and T3 tram fronts. The knowledge of these properties is crucial in terms of the mentioned validation. The output of the measurement includes tensile diagrams, including the evaluation of the ultimate tensile strength, elastic modulus and relative elongation at the ultimate tensile strength. Also, the conversion of the elastic modulus for the fibreglass with a different fibre volume part is presented.

Modeling method of rider-two-wheeler-road coupled system in two-wheeler traffic accident reconstrucitons

In order to more accurately simulate the injury of riders and the motion characteristics of two-wheelers, the modeling method and the simulation model of two-wheeler traffic accidents are studied in this paper. Firstly, the rider dummy model is established by using the module combination method. Then, taking into account the manipulation of riders on two-wheelers and the interaction between the two-wheeler and the road, the hand grip model and the two-wheeler model are established respectively. On this basis, a rider-two-wheeler-road coupled system model is proposed. The analysis of driving dynamics shows that the coupled model has good motion stability. The coupled model is applied to the simulation of real two-wheeler accident. The simulation results are consistent with the on-site monitoring videos and investigation reports, which verified the feasibility and effectiveness of the modeling method.

Computational and SAXS-based structure insights of pectin acetyl esterase (CtPae12B) of family 12 carbohydrate esterase from Clostridium thermocellum ATCC 27405

Pectin is a complex form of polysaccharide and is composed of several structural components that require the concerted action of several pectinases for its complete degradation. In this study, in silico and solution structure of a pectin acetyl esterase (CtPae12B) of family 12 carbohydrate esterase (CE12) from Clostridium thermocellum was determined. The CtPae12B modelled structure, showed a new α/β hydrolase fold, similar to the fold found in the crystal structures of its nearest homologues from CE12 family, which differed from α/β hydrolase fold found in glycoside hydrolases. In the active site of CtPae12B, two loops (loop1 and loop6) play an important role in the formation of a catalytic triad Ser15-Asp187-His190, where Ser15 acts as a nucleophile. The structural stability of CtPae12B and its catalytic site was detected by performing molecular dynamic (MD) simulation which showed stable and compact conformation of the structure. Molecular docking method was employed to analyse the conformations of various suitable ligands docked at the active site of CtPae12B. The stability and structural specificity of the catalytic residues with the ligand, 4-nitrophenyl acetate (4-NPA) was confirmed by MD simulation of CtPae12B-4NPA docked complex. Moreover, it was found that the nucleophile Ser15, forms hydrophobic interaction with 4-NPA in the active site to complete covalent catalysis. Small angle X-ray scattering analysis of CtPae12B at 3 mg/mL displayed elongated, compact and monodispersed nature in solution. The ab initio derived dummy model showed that CtPae12B exists as a homotrimer at 3 mg/mL which was also confirmed by dynamic light scattering. Communicated by Ramaswamy H. Sarma

Head injury of Vietnamese pedestrian in crash accident with SUV using numerical simulation

Crash test simulation using finite-element method is more and more popular in the automobile industry because of its feasibility and cost saving. The majority of finite element dummy models used in crash simulation are built based on anthropometrical and biomechanical data of the USA and European bodies. Thus, it is necessary to develop a scaling algorithm to scale a reference dummy size into a desired one without rebuilding the entire model. In this paper, the Hybrid III dummy model provided by LS-DYNA software is scaled to suit Vietnamese biomechanical characteristics. Then a standard criterion for head injuries called HIC is introduced. In addition, the Hybrid III dummy model is validated by comparing experimental data with simulation results obtained from computer model.

Nonbonded Zr4+ and Hf4+ Models for Simulations of Condensed Phase Metal–Organic Frameworks

Recently, the practical applications of tetravalent metal-based metal–organic frameworks (MOFs) have been drawing increasing attention due to their excellent stability and varied functionality. Understanding the behavior of MOFs at the atomic level is important for their rational design and postsynthetic optimization. In classical simulations, the cationic dummy atom model, where the charge of the metal ion is distributed to surrounding dummy particles, has shown robustness in providing the appropriate coordination geometry while retaining the flexibility in the metal ligand interaction. Here, we present a set of eight-coordinated tetravalent metal (Zr4+, Hf4+) dummy model force fields with 12-6-4 type Lennard–Jones potential for describing ion-induced dipole interactions. This model can reproduce both the experimental solvation free energy of the bare ion and good metal–ligand distances and has been validated as useful and transferable among MOFs with the same metal-core topology. The model is inherently modular since nodes and linkers are independently parametrized. It was tested with three different solvents which all led to stable structures. It also was been further validated with different metal node structures and different linkers, Zr/Hf mixed MOFs, and defects containing MOFs. Since the model is nonbonded, the process of metal–ligand substitutions could be studied. The flexibility of the model makes its applicability to chemical problems broad.

Analysis of the Head of a Simulation Crash Test Dummy with Speed Motion

The article presents a model of an anthropometric dummy designed for low velocity crash tests, designed in ADAMS. The model consists of rigid bodies connected with special joints with appropriately selected stiffness and damping. The simulation dummy has the appropriate dimensions, shape, and mass of individual elements to suit a 50 percentile male. The purpose of this article is to draw attention to low speed crash tests. Current dummies such as THOR and Hybrid III are used for crash tests at speeds above 40 km/h. In contrast, the low-speed test dummy currently used is the BioRID-II dummy, which is mainly adapted to the whiplash test at speeds of up to 16km/h. Thus, it can be seen that there is a gap in the use of crash test dummies. There are no low-speed dummies for side and front crash tests, and there are no dummies for rear crash tests between 16 km/h and 25 km/h. Which corresponds to a collision of a passenger vehicle with a hard obstacle at a speed of 30 km/h. Therefore, in collisions with low speeds of 20 km/h, the splash airbag will probably not be activated. The article contains the results of a computer simulation at a speed of 20 km/h vehicle out in the ADAMS program. These results were compared with the experimental results of the laboratory crash test using volunteers and the Hybrid III dummy. The simulation results are the basis for building the physical model dummy. The simulation aims to reflect the greatest possible compliance of the movements of individual parts of the human body during a collision at low speed.

Impact of Disabled Driver’s Mass Center Location on Biomechanical Parameters during Crash

Adapting a car for a disable person involves adding additional equipment to compensate for the driver’s disability. During this process, the change in the driver’s position and kinematics and their impact on safety levels during crash is not considered. There is also a lack of studies in the literature on this problem. This paper describes a methodology for conducting a study of the behavior of a disabled driver during a crash using the finite element method, based on an explicit time integration method. A validated car model and a commercial dummy model were used. The results show that the use of a handle on the steering wheel and a hand control unit causes dangerous lateral displacements relative to the seat. Amputation of the left leg or right arm causes significant shoulder rotations, amputation of the left leg causes increased thoracic loads. Amputation or additional equipment have no significant impact on head injuries.

A model study of resonance effect on ocular vestibular-evoked myogenic potential

This study measured the acceleration magnitude using a dummy model filled with various air-material ratios to elucidate the mechanism of resonance effect on ocular vestibular-evoked myogenic potential (oVEMP). With the percentages of air volume altered by filling various materials (water, glycerol, or ethanol) in an acrylic-made hollow spherical model, a minishaker was utilized to deliver vibration stimuli to the model. Then, acceleration magnitude of each model was measured. Since the air was most occupied at the upper part of the model (z-axis), acceleration magnitude along the z-axis was selected for comparison. An increasing trend of the z-axis acceleration magnitude ranging 0.110-0.759g was identified in air-water model with air volume percentage ranged 40-100%. On the other hand, a significant increasing trend of acceleration magnitude along the z-axis (0.157-0.759g) was noted in air-glycerol model with 80-100% of air volume. While in air-ethanol model, a significant increasing trend in acceleration magnitude along the z-axis ranged 0.121-0.759g correlating with 40-100% of air volume. The mechanism for eliciting oVEMP is via the first-order bone vibration coupled with the second-order resonance effect. Both percentage of air volume (i.e. frontal sinus) and density of filling media (i.e. skull property) may contribute to the resonance effect, which then increases the acceleration magnitude so as to enhance the elicitation of oVEMP.

Time-Series Causality with Missing Data

Over the past years, researchers have proposed various methods to discover causal relationships among time-series data as well as algorithms to fill in missing entries in time-series data. Little to no work has been done in combining the two strategies for the purpose of learning causal relationships using unevenly sampled multivariate time-series data. In this paper, we examine how the causal parameters learnt from unevenly sampled data (with missing entries) deviates from the parameters learnt using the evenly sampled data (without missing entries). However, to obtain the causal relationship from a given time-series requires evenly sampled data, which suggests filling the missing data values before obtaining the causal parameters. Therefore, the proposed method is based on applying a Gaussian Process Regression (GPR) model for missing data recovery, followed by several pairwise Granger causality equations in Vector Autoregssive form to fit the recovered data and obtain the causal parameters. Experimental results show that the causal parameters generated by using GPR data filling offers much lower RMSE than the dummy model (fill with last seen entry) under all missing values percentage, suggesting that GPR data filling can better preserve the causal relationships when compared with dummy data filling, thus should be considered when dealing with unevenly sampled time-series causality learning.

STAR laboratory at Politecnico di Torino: a facility to develop educational space projects

The hands-on practice programmes in technical universities provide a relevant value added for the students’ careers because allows them to create hard and soft skills, training them through real and complex projects. In this sense, the STAR Team of Politecnico di Torino operates in order to prepare students for their future works. Students are the backbone for any activity of educational projects that are ongoing since 2008 (and before). The hands-on practice activities are strongly supported by STARLab facilities and tools developed to support the development of space mission for the entire product lifecycle. The present paper shows how the STARLab activities: development, verification and operations of end-to-end missions of small satellites (mainly Cubesats), development and validation of tools and test benches for mission analysis, system and subsystem devices design, manufacturing and testing of prototypes, dummy models, and flight units are presented.

The Influence of Occupant Grip on Ceiling Handrail and Injury Assessment in Collision

With the rapid increase in the number of cars, to bring a variety of convenience to mankind, at the same time, a number of traffic safety problems also followed, which causing serious injuries and property losses, bring more pain and regret to the people. Therefore, to accurately assess the damage of the personnel in the collision safety accident is very useful to improve the safety performance and functionality of the vehicle. so, the crash dummy plays an important role in the research of crash safety. At present, in the study of human body injury in the collision with dummy, the influence of roof handrails grasping state was not considered. Therefore, the software of LS-PREPOST and Oasys PRIM-ER are used to build model of automobile cockpit and dummy with hand grip ability, the acceleration environment of frontal crash was simulated by adding B-pillar acceleration curve from real vehicle crash test. Comparing injuries of dummies in free sitting posture and holding the roof armrest in collision. he simulation results show that when the dummy was grasping the roof armrest, the peak value of head acceleration and HIC values were 6.1% and 30.2% lower than the dummy was sitting freely, the maximum value of shear force, tensile force and bending moment of the neck were reduced by 87.4%, 76.9% and 42.9% respectively, and the maximum value of chest compression was reduced by 16.9%. The results provide a reference for the research of passive safety in collision.

Analysis on head rotational velocity during baseball impact using finite element dummy model

Analysis on head rotational velocity during baseball impact using finite element dummy model

_

Purpose: The purpose of this study was to evaluate the capability of a detailed FE human body lower limb mode, called HALL (Human Active Lower Limb) model, in predicting real world pedestrian injuries and to investigate injury mechanism of pedestrian lower limb in vehicle collisions. Methods: Two real world vehicle-to-pedestrian crashes with detailed information were selected. Then, a pedestrian model combining the HALL model and the upper body of the 50th% Chinese dummy model and vehicle front models were developed to reconstruct the selected real world crashes, and the predictions of the simulations were analyzed together with observations from the accident data. Results: The results show that the predictions of the HALL model for pedestrian lower limb long bone fractures match well with the observation from hospital data of the real world accidents, and the predicted thresholds of bending moment for tibia and femur fracture are close to the average values calculated from cadaver test data. Analysis of injury mechanism of pedestrian lower limb in collisions indicates that the relatively sharper bumper of minivan type vehicles can produce concentrated loading to the lower leg and a high risk of tibia/fibula fracture, while the relatively sharper and lower bonnet leading edge may cause concentrate loading to the thigh and high femur fracture risk. Conclusions: The findings imply that the HALL model could be used as an effective tool for predicting pedestrian lower limb injuries in vehicle collisions and improvements to the minivan bumper and sedan bonnet leading edge should be concerned further in vehicle design.

RANS-Based CFD Calculation for Pressure Drop and Mass Flow Rate Distribution in an MTR Fuel Assembly

This work presents a Reynolds-averaged Navier Stokes–based computational fluid dynamics methodology for the calculation of pressure drop and mass flow rate distribution in a material test reactor flat-plate-type standard fuel assembly (SFA) of the IEA-R1 Brazilian research reactor to predict future improvements in newer SFA designs. The results improve the understanding of the origin of fuel plate oxidation due to high temperatures, and consequently, due to the internal flow dynamics. All numerical analyses were performed with the ANSYS-CFX® commercial code. The observed results show that the movement pin decreases the central channel mass flow due to the length of the vortex at the inlet region. However, the outlet nozzle showed greater general influence in the flow dynamics. It should have a more gradual cross-section transition being away from the fuel plates or a squarer-shaped design to get a more homogeneous mass flow distribution. Optimizing both regions could lead to a better cooling condition. The validation of the IEA-R1 numerical methodology was made by comparing the McMaster University’s dummy model experiment with a numerical model that uses the same numerical methodology. The experimental data were obtained with laser Doppler velocimetry, and the comparison showed good agreement for both pressure drop and mass flow rate distribution using the Standard k-ω turbulence model.

Analysis of chest injury characteristics in frontal vehicle collision under three typical overlaps

In view of the relatively serious situation of chest injuries in current vehicle accidents, this study aims to determine the chest injuries characteristics in frontal vehicle collisions under different overlaps. The frontal impact simulation was first established and conducted based on the latest THOR dummy model with different overlaps. By comparing chest dynamic output indicators under three different overlap rates in frontal impact conditions, the relationship between chest injuries and collision overlap rates was analyzed in terms of the chest deflection and stress/strain distribution. Results show that changes of the thoracic stress/strain distribution and the amplitude of chest deflection are more sensitive to frontal impact load under a great impact overlap. In the kinematics analysis, there is a significant twist along the seatbelt route to the occupant’s chest. The changes of the chest deflection and stress/strain based on the design parameter changes at different overlap rates are consistent, and the highest injury risk is captured in the ribcage structure of mid-chest in full frontal impact. The research results can provide a reference for the optimal design of the constraint system for the future.

Classification of Parkinson\u2019s disease and essential tremor based on balance and gait characteristics from wearable motion sensors via machine learning techniques: a data-driven approach

BackgroundParkinson’s disease (PD) and essential tremor (ET) are movement disorders that can have similar clinical characteristics including tremor and gait difficulty. These disorders can be misdiagnosed leading to delay in appropriate treatment. The aim of the study was to determine whether balance and gait variables obtained with wearable inertial motion sensors can be utilized to differentiate between PD and ET using machine learning. Additionally, we compared classification performances of several machine learning models.MethodsThis retrospective study included balance and gait variables collected during the instrumented stand and walk test from people with PD (n = 524) and with ET (n = 43). Performance of several machine learning techniques including neural networks, support vector machine, k-nearest neighbor, decision tree, random forest, and gradient boosting, were compared with a dummy model or logistic regression using F1-scores.ResultsMachine learning models classified PD and ET based on balance and gait characteristics better than the dummy model (F1-score = 0.48) or logistic regression (F1-score = 0.53). The highest F1-score was 0.61 of neural network, followed by 0.59 of gradient boosting, 0.56 of random forest, 0.55 of support vector machine, 0.53 of decision tree, and 0.49 of k-nearest neighbor.ConclusionsThis study demonstrated the utility of machine learning models to classify different movement disorders based on balance and gait characteristics collected from wearable sensors. Future studies using a well-balanced data set are needed to confirm the potential clinical utility of machine learning models to discern between PD and ET.

Numerical investigation of occupant injury risks in car-to-end terminal crashes using dummy-based injury criteria and vehicle-based crash severity metrics

Guardrails were designed to deter vehicle access to off-road areas and consequently prevent hitting rigid fixed objects alongside the road (e.g. trees, utility poles, traffic barriers, etc.). However, guardrails cause 10 % of deaths in vehicle-to-fixed-object crashes, which recently attracted attention in the highway safety community on the vehicle-based injury criteria used in regulations. The objectives of this study were to investigate both full-body and body-region driver injury probabilities using finite element (FE) simulations, to quantify the influence of pre-impact conditions on injury probabilities, and to analyze the relationship between the vehicle-based crash severity metrics currently used in regulations and the injury probabilities assessed using dummy-based injury criteria.A total of 20 FE impact simulations between a car (Toyota Yaris) with a Hybrid III M50 dummy model in the driver seat and an end terminal model (ET-Plus) were performed in various configurations (e.g. pre-impact velocities, offsets, and angles). The driver’s risk of serious injuries (AIS 3+) was estimated based on kinematic and kinetic responses of the dummy during the crashes. A non-linear regression approach was used to compare the injury probabilities assessed in this study to the vehicle-based crash severity metrics used in the testing regulations. In particular, the US Manual for Assessing Safety Hardware (MASH) guideline and European procedures (EN1317) were used for the study.All the recorded dummy-based injury criteria values pass the Federal Motor Vehicle Safety Standard (FMVSS) 208 limits which indicated a low driver risk of serious injury. Overall, the pre-impact vehicle velocity showed to have the highest influence in almost all injury probabilities (59 %, 79 %, 62 %, and 44 % in full-body, head, neck, and chest injuries, respectively). The offset between vehicle midline and the guardrail barrier was the most important variable for thigh injuries (56 %). The assessed injury probabilities were compared to vehicle-based severity metrics. The full-body and chest injuries showed the highest correlation with Occupant Impact Velocity (OIV), Acceleration Severity Index (ASI), and Theoretical Head Impact Velocity (THIV) (R2 > 0.6). Lower correlations of thigh injuries were recorded to OIV (R2 = 0.59) and THIV (R2 = 0.46). Meanwhile, weak correlations were observed between all the other regressions which indicated that no vehicle-based criteria could be used to predict head and neck injuries.Car-to-end terminal crash FE simulations involving a dummy model were performed for the first time in this study. The results pointed out the limitations of the standard vehicle-based injury methods in terms of head and neck injury prediction. The dummy-based injury assessment methodology presented in this study could supplement the crash tests for various impact conditions. In addition, the models could be used to design new advanced guardrail end terminals.

Assessment of lumbar spinal disc injury in frontal crashes

Frontal vehicle crashes have been a leading cause of spinal injuries in recent years. Reconstruction of frontal crashes using computational models and spinal load analysis helps us understand the patterns of injury and load propagation during frontal crashes. By reconstructing a real crash test and using a viscoelastic crash dummy model, spinal injury patterns were analyzed. The results indicated that a moderate crash with an impact speed of 56 km/h leads to injuries in L1-L2 and L5-S1 levels (L for lumbar and S for sacral vertebrae). The largest spinal loads and injuries were mainly observed immediately after the airbag deployment when the peak of the crash acceleration transpires. Also, the effects of impulse magnitude on the spinal loads and head injury criterion (HIC) showed that HIC is more sensitive than compressive forces to the magnitude of impulse. Moreover, the effects of disc preconditioning as a major factor in the risk of injury was evaluated. The results demonstrate that as the lumbar spine is subjected to a longer preloading, it will be more vulnerable to injury; preconditioning of the discs more adversely affected the risk of injury than a 10% increase in the crash impulse. Overall the results highlight the importance of spinal injury prevention in frontal crashes.