The sinking and trimming of the hull in the channel would directly affect the handling and navigation safety of the ship. In view of the ship sinking, a series of empirical formulas to estimate the subsidence have been put forward for vessel in spacious shallow water areas. However, most of the equations are based on seagoing vessels. They are not suitable for inland ships with small scales, shallow drafts, and narrow navigation width. Till now, research on ship squat in intermediate channel has not yielded more practical results. Here, a generalized physical model is used to study the sinking of 500t class ships in restricted intermediate channel under different channel widths, water depths, and speeds. The main factors affecting the squat are analyzed, the empirical relation is compared with the measured squat. The Barrass equation is modified, and the calculation relation of the settlement suitable for inland river ships is proposed. The correlation coefficient R2 of the modified equation is 0.818, the standard error is 0.046, and the maximum error is 0.14 m, which can be used as a reference for inland waterway design research.
{"title":"Experimental Study on Ship Squat in Intermediate Channel","authors":"Liji Long, Jilun Miao, Wanxing Zhao, Chenglin Huang","doi":"10.4271/09-12-01-0005","DOIUrl":"https://doi.org/10.4271/09-12-01-0005","url":null,"abstract":"<div>The sinking and trimming of the hull in the channel would directly affect the handling and navigation safety of the ship. In view of the ship sinking, a series of empirical formulas to estimate the subsidence have been put forward for vessel in spacious shallow water areas. However, most of the equations are based on seagoing vessels. They are not suitable for inland ships with small scales, shallow drafts, and narrow navigation width. Till now, research on ship squat in intermediate channel has not yielded more practical results. Here, a generalized physical model is used to study the sinking of 500t class ships in restricted intermediate channel under different channel widths, water depths, and speeds. The main factors affecting the squat are analyzed, the empirical relation is compared with the measured squat. The <i>Barrass</i> equation is modified, and the calculation relation of the settlement suitable for inland river ships is proposed. The correlation coefficient <i>R</i><sup>2</sup> of the modified equation is 0.818, the standard error is 0.046, and the maximum error is 0.14 m, which can be used as a reference for inland waterway design research.</div>","PeriodicalId":42847,"journal":{"name":"SAE International Journal of Transportation Safety","volume":" 28","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135290661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A research program has been launched in Iran to develop an evaluation method for comparing the safety performance of vehicles in real-world collisions with crash test results. The goal of this research program is to flag vehicle models whose safety performance in real-world accidents does not match their crash test results. As part of this research program, a metric is needed to evaluate the severity of side impacts in crash tests and real-world accidents. In this work, several vehicle-based metrics were analyzed and calculated for a dataset of more than 500 side impact tests from the NHTSA crash test database. The correlation between the metric values and the dummy injury criteria was studied to find the most appropriate metric with the strongest correlation coefficient values with the dummy injury criteria. Delta-V and a newly created metric , which is an indicator of the kinetic energy transferred to occupants in a 200 ms time interval and in the lateral direction, were found to be the most appropriate metric for assessing the crash severity of side impacts with strong correlation coefficients with head injury criteria such as HIC36 and HIC15, resultant spinal acceleration, and moderate correlation coefficients with average rib deflection and abdominal forces. Due to the need to calculate the metric based on EDR measurements, was chosen as the side impact severity metric for the research program.
{"title":"Study of Vehicle-Based Metrics for Assessing the Severity of Side Impacts","authors":"Emad Sadeghipour","doi":"10.4271/09-12-01-0004","DOIUrl":"https://doi.org/10.4271/09-12-01-0004","url":null,"abstract":"<div>A research program has been launched in Iran to develop an evaluation method for comparing the safety performance of vehicles in real-world collisions with crash test results. The goal of this research program is to flag vehicle models whose safety performance in real-world accidents does not match their crash test results. As part of this research program, a metric is needed to evaluate the severity of side impacts in crash tests and real-world accidents. In this work, several vehicle-based metrics were analyzed and calculated for a dataset of more than 500 side impact tests from the NHTSA crash test database. The correlation between the metric values and the dummy injury criteria was studied to find the most appropriate metric with the strongest correlation coefficient values with the dummy injury criteria. Delta-V and a newly created metric <span> <math> <mrow> <mi>T</mi> <msubsup> <mi>K</mi> <mrow> <mn>2</mn> <mn>0</mn> <mn>0</mn> </mrow> <mi>Y</mi> </msubsup> </mrow> </math> </span>, which is an indicator of the kinetic energy transferred to occupants in a 200 ms time interval and in the lateral direction, were found to be the most appropriate metric for assessing the crash severity of side impacts with strong correlation coefficients with head injury criteria such as HIC<sub>36</sub> and HIC<sub>15</sub>, resultant spinal acceleration, and moderate correlation coefficients with average rib deflection and abdominal forces. Due to the need to calculate the metric based on EDR measurements, <span> <math> <mrow> <mi>T</mi> <msubsup> <mi>K</mi> <mrow> <mn>2</mn> <mn>0</mn> <mn>0</mn> </mrow> <mi>Y</mi> </msubsup> </mrow> </math> </span> was chosen as the side impact severity metric for the research program.</div>","PeriodicalId":42847,"journal":{"name":"SAE International Journal of Transportation Safety","volume":"18 S1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136106808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The uncertainty of a driver’s state, the variability of the traffic environment, and the complexity of road conditions have made driving behavior a critical factor affecting traffic safety. Accurate predicting of driving behavior is therefore crucial for ensuring safe driving. In this research, an efficient framework, distilled routing transformer (DRTR), is proposed for driving behavior prediction using multiple modality data, i.e., front view video frames and vehicle signals. First, a cross-modal attention distiller is introduced, which distills the cross-modal attention knowledge of a fusion-encoder transformer to guide the training of our DRTR and learn deep interactions between different modalities. Second, since the multi-modal learning usually requires information from the macro view to the micro view, a self-attention (SA)-routing module is custom-designed for SA layers in DRTR for dynamic scheduling of global and local attentions for each input instance. Finally, a Mogrifier long short-term memory (Mogrifier LSTM) network is employed for DRTR to predict driving behaviors. We applied our approach to real-world data collected during drives in both urban and freeway environments by an instrumented vehicle. The experimental results demonstrate that the DRTR can predict the imminent driving behavior effectively while enjoying a faster inference speed than other state-of-the-art (SOTA) baselines.
{"title":"Distilled Routing Transformer for Driving Behavior Prediction","authors":"Jun Gao, Jiangang Yi, Yi Lu Murphey","doi":"10.4271/09-12-01-0003","DOIUrl":"https://doi.org/10.4271/09-12-01-0003","url":null,"abstract":"<div>The uncertainty of a driver’s state, the variability of the traffic environment, and the complexity of road conditions have made driving behavior a critical factor affecting traffic safety. Accurate predicting of driving behavior is therefore crucial for ensuring safe driving. In this research, an efficient framework, distilled routing transformer (DRTR), is proposed for driving behavior prediction using multiple modality data, i.e., front view video frames and vehicle signals. First, a cross-modal attention distiller is introduced, which distills the cross-modal attention knowledge of a fusion-encoder transformer to guide the training of our DRTR and learn deep interactions between different modalities. Second, since the multi-modal learning usually requires information from the macro view to the micro view, a self-attention (SA)-routing module is custom-designed for SA layers in DRTR for dynamic scheduling of global and local attentions for each input instance. Finally, a Mogrifier long short-term memory (Mogrifier LSTM) network is employed for DRTR to predict driving behaviors. We applied our approach to real-world data collected during drives in both urban and freeway environments by an instrumented vehicle. The experimental results demonstrate that the DRTR can predict the imminent driving behavior effectively while enjoying a faster inference speed than other state-of-the-art (SOTA) baselines.</div>","PeriodicalId":42847,"journal":{"name":"SAE International Journal of Transportation Safety","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136359488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reviewers","authors":"Warren Hardy","doi":"10.4271/09-11-03-0015","DOIUrl":"https://doi.org/10.4271/09-11-03-0015","url":null,"abstract":"<div>Reviewers</div>","PeriodicalId":42847,"journal":{"name":"SAE International Journal of Transportation Safety","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134945600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andrii Gavryliuk, Roman Yakovchuk, Yaroslav Ballo, Yuriy Rudyk
The world community is constantly and rapidly moving toward the search for alternative and ecologically clean energy sources, including for transport, and Russia’s war against Ukraine only intensified and accelerated such processes. This trend in transport is reflected in the spread of battery-powered electric vehicles (BEVs) with zero emission of harmful gases.
Electric cars are experiencing a rapid increase in numbers, accompanied by the emergence of lesser-known risks. Among these hazards are the occurrence of fires in electric vehicles, primarily caused by component failures, notably the widely prevalent lithium-ion batteries.
Fires of such cars have a different character compared to fires of vehicles powered by an internal combustion engine vehicle (ICEV). In this study, using the fire dynamics simulator developed by the National Institute of Standards and Technology, a BEV fire was simulated on the example of the Tesla Model S. For this, a description of the objects and their physical characteristics were carried out, the input parameters of the BEV and environmental parameters were set, and a mathematical model of the development dynamics of fire was formed. According to the modeling results, it was found that the minimum fire protection distance from a BEV to the wall of buildings of various functional purposes should be at least 3 m, provided that the free fire development time is 600 s.
{"title":"Thermal Modeling of the Electric Vehicle Fire Hazard Effects on Parking Building","authors":"Andrii Gavryliuk, Roman Yakovchuk, Yaroslav Ballo, Yuriy Rudyk","doi":"10.4271/09-11-03-0013","DOIUrl":"https://doi.org/10.4271/09-11-03-0013","url":null,"abstract":"<div>The world community is constantly and rapidly moving toward the search for alternative and ecologically clean energy sources, including for transport, and Russia’s war against Ukraine only intensified and accelerated such processes. This trend in transport is reflected in the spread of battery-powered electric vehicles (BEVs) with zero emission of harmful gases.</div> <div>Electric cars are experiencing a rapid increase in numbers, accompanied by the emergence of lesser-known risks. Among these hazards are the occurrence of fires in electric vehicles, primarily caused by component failures, notably the widely prevalent lithium-ion batteries.</div> <div>Fires of such cars have a different character compared to fires of vehicles powered by an internal combustion engine vehicle (ICEV). In this study, using the fire dynamics simulator developed by the National Institute of Standards and Technology, a BEV fire was simulated on the example of the Tesla Model S. For this, a description of the objects and their physical characteristics were carried out, the input parameters of the BEV and environmental parameters were set, and a mathematical model of the development dynamics of fire was formed. According to the modeling results, it was found that the minimum fire protection distance from a BEV to the wall of buildings of various functional purposes should be at least 3 m, provided that the free fire development time is 600 s.</div>","PeriodicalId":42847,"journal":{"name":"SAE International Journal of Transportation Safety","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136238020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Field data has shown that belt-positioning boosters help reduce the risk of injury to children in a crash. This study builds on prior submarining work (Slusher et al. 2022) and aims to analyze kinetic metrics (which can be easily recorded from anthropomorphic test devices in crash tests) in submarining and non-submarining conditions for a 6-year-old pediatric human occupant in frontal crashes.
{"title":"Analysis of Kinetic Metrics in Submarining vs Non-Submarining Conditions for a 6YO Pediatric Human Body Model in Frontal Impacts","authors":"Bethany Williams, Jalaj Maheshwari","doi":"10.4271/09-11-02-0020","DOIUrl":"https://doi.org/10.4271/09-11-02-0020","url":null,"abstract":"<div>Field data has shown that belt-positioning boosters help reduce the risk of injury to children in a crash. This study builds on prior submarining work (Slusher et al. 2022) and aims to analyze kinetic metrics (which can be easily recorded from anthropomorphic test devices in crash tests) in submarining and non-submarining conditions for a 6-year-old pediatric human occupant in frontal crashes.</div>","PeriodicalId":42847,"journal":{"name":"SAE International Journal of Transportation Safety","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136265332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lihan Lian, Michelle Baek, Sunwoo Ma, Monica Jones, Jingwen Hu
In this study, a parametric thoracic spine (T-spine) model was developed to account for morphological variations among the adult population. A total of 84 CT scans were collected, and the subjects were evenly distributed among age groups and both sexes. CT segmentation, landmarking, and mesh morphing were performed to map a template mesh onto the T-spine vertebrae for each sampled subject. Generalized procrustes analysis (GPA), principal component analysis (PCA), and linear regression analysis were then performed to investigate the morphological variations and develop prediction models. A total of 13 statistical models, including 12 T-spine vertebrae and a spinal curvature model, were combined to predict a full T-spine 3D geometry with any combination of age, sex, stature, and body mass index (BMI). A leave-one-out root mean square error (RMSE) analysis was conducted for each node of the mesh predicted by the statistical model for every T-spine vertebra. Most of the RMSEs were less than 2 mm across the 12 vertebral levels, indicating good accuracy. The presented parametric T-spine model can serve as a geometry basis for parametric human modeling or future crash test dummy designs to better assess T-spine injuries accounting for human diversity.
{"title":"A Parametric Thoracic Spine Model Accounting for Geometric Variations by Age, Sex, Stature, and Body Mass Index","authors":"Lihan Lian, Michelle Baek, Sunwoo Ma, Monica Jones, Jingwen Hu","doi":"10.4271/09-11-02-0012","DOIUrl":"https://doi.org/10.4271/09-11-02-0012","url":null,"abstract":"<div>In this study, a parametric thoracic spine (T-spine) model was developed to account for morphological variations among the adult population. A total of 84 CT scans were collected, and the subjects were evenly distributed among age groups and both sexes. CT segmentation, landmarking, and mesh morphing were performed to map a template mesh onto the T-spine vertebrae for each sampled subject. Generalized procrustes analysis (GPA), principal component analysis (PCA), and linear regression analysis were then performed to investigate the morphological variations and develop prediction models. A total of 13 statistical models, including 12 T-spine vertebrae and a spinal curvature model, were combined to predict a full T-spine 3D geometry with any combination of age, sex, stature, and body mass index (BMI). A leave-one-out root mean square error (RMSE) analysis was conducted for each node of the mesh predicted by the statistical model for every T-spine vertebra. Most of the RMSEs were less than 2 mm across the 12 vertebral levels, indicating good accuracy. The presented parametric T-spine model can serve as a geometry basis for parametric human modeling or future crash test dummy designs to better assess T-spine injuries accounting for human diversity.</div>","PeriodicalId":42847,"journal":{"name":"SAE International Journal of Transportation Safety","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136265333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Letter from the Special Issue Editors","authors":"Becky Mueller, Brian Bautsch, Julie Mansfield","doi":"10.4271/09-11-02-0009","DOIUrl":"https://doi.org/10.4271/09-11-02-0009","url":null,"abstract":"<div>Letter from the Special Issue Editors</div>","PeriodicalId":42847,"journal":{"name":"SAE International Journal of Transportation Safety","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136307936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Randolff L. Carpenter, Parker R. Berthelson, John-Paul Donlon, Jason L. Forman
Bilateral knee impacts were conducted on Hybrid III and THOR 5th percentile female anthropomorphic test devices (ATDs), and the results were compared to previously reported female PMHS data. Each ATD was impacted at velocities of 2.5, 3.5, and 4.9 m/s. Knee–thigh–hip (KTH) loading data, obtained either via direct measurement or through exercising a one-dimensional lumped parameter model (LPM), was analyzed for differences in loading characteristics including the maximum force, time to maximum force, loading rate, and loading duration. In general, the Hybrid III had the highest loading rate and maximum force, and the lowest loading duration and time to peak force for each point along KTH. Conversely, the PMHS generally had the lowest loading rate and maximum force, and the highest loading duration and time to peak force for each point along KTH. The force transfer from the knee to the femur was 79.2 ± 0.3% for the Hybrid III 5th female, 82.7 ± 0.4% for the THOR-05F, and 70.6 ± 1.7% for the PMHS. The force transfer from the knee to the hip was 60.6 ± 0.5% for the Hybrid III 5th female, 41.4 ± 0.4% for the THOR-05F, and 57.0 ± 3.0% for the PMHS. While the Hybrid III aligned more with the PMHS force transfer ratios, the loading characteristics of the THOR-05F were more similar to the PMHS.
{"title":"Comparison of the Knee–Thigh–Hip Response in Small Female ATDs with Female PMHS","authors":"Randolff L. Carpenter, Parker R. Berthelson, John-Paul Donlon, Jason L. Forman","doi":"10.4271/09-11-02-0013","DOIUrl":"https://doi.org/10.4271/09-11-02-0013","url":null,"abstract":"<div>Bilateral knee impacts were conducted on Hybrid III and THOR 5th percentile female anthropomorphic test devices (ATDs), and the results were compared to previously reported female PMHS data. Each ATD was impacted at velocities of 2.5, 3.5, and 4.9 m/s. Knee–thigh–hip (KTH) loading data, obtained either via direct measurement or through exercising a one-dimensional lumped parameter model (LPM), was analyzed for differences in loading characteristics including the maximum force, time to maximum force, loading rate, and loading duration. In general, the Hybrid III had the highest loading rate and maximum force, and the lowest loading duration and time to peak force for each point along KTH. Conversely, the PMHS generally had the lowest loading rate and maximum force, and the highest loading duration and time to peak force for each point along KTH. The force transfer from the knee to the femur was 79.2 ± 0.3% for the Hybrid III 5th female, 82.7 ± 0.4% for the THOR-05F, and 70.6 ± 1.7% for the PMHS. The force transfer from the knee to the hip was 60.6 ± 0.5% for the Hybrid III 5th female, 41.4 ± 0.4% for the THOR-05F, and 57.0 ± 3.0% for the PMHS. While the Hybrid III aligned more with the PMHS force transfer ratios, the loading characteristics of the THOR-05F were more similar to the PMHS.</div>","PeriodicalId":42847,"journal":{"name":"SAE International Journal of Transportation Safety","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136307700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eighteen research posters were prepared and presented by student authors at the 18th Annual Injury Biomechanics Symposium. The posters covered a wide breadth of works-in-progress and recently completed projects. Topics included a variety of body regions and injury scenarios such as:
Head: Defining the mass, center of mass, and anatomical coordinate system of the pig head and brain; the influence of friction on oblique helmet testing; validation of an in-ear sensor for measuring head impact exposure in American football
Neck and spine: Design of paramedic mannequin neck informed by adult passive neck stiffness and range of motion data; identifying injury from flexion-compression loading of porcine lumbar intervertebral disc
Thorax: Tensile material properties of costal cartilage perichondrium; finite element models of both an ovine thorax and adipose tissue for high-rate non-penetrating blunt impact
Pelvis: Injurious pelvis deformation in high-speed rear-facing frontal impacts
Lower extremities: Generation of 3D pediatric femur models from 2D radiographs; plantar thickness and stiffness using ultrasound; knee injuries in skiing and snowboarding using artificial intelligence 3D modeling; jumping kinematics, and kinetics in athletes with secondary task of heading a soccer ball
Full body, vehicle occupants: Comparison of Hybrid III, THOR mid-size male, and small female ATDs in frontal sled tests; effects of booster seat on reclined small females during lateral oblique low-acceleration impacts; airbag deployment for out-of-position 50th percentile male human body model
Full body, unique loading scenarios: Development of seat fixture and restraints for FE human body model during vertical loading; methodology for PMHS-occupied powered two wheeler and motor vehicle crash scenario
{"title":"Summary of Poster Abstracts","authors":"Becky Mueller, Brian Bautsch, Julie Mansfield","doi":"10.4271/09-11-02-0022","DOIUrl":"https://doi.org/10.4271/09-11-02-0022","url":null,"abstract":"<div>Eighteen research posters were prepared and presented by student authors at the 18th Annual Injury Biomechanics Symposium. The posters covered a wide breadth of works-in-progress and recently completed projects. Topics included a variety of body regions and injury scenarios such as:<ul><li><div><b>Head:</b> Defining the mass, center of mass, and anatomical coordinate system of the pig head and brain; the influence of friction on oblique helmet testing; validation of an in-ear sensor for measuring head impact exposure in American football</div></li><li><div><b>Neck and spine:</b> Design of paramedic mannequin neck informed by adult passive neck stiffness and range of motion data; identifying injury from flexion-compression loading of porcine lumbar intervertebral disc</div></li><li><div><b>Thorax:</b> Tensile material properties of costal cartilage perichondrium; finite element models of both an ovine thorax and adipose tissue for high-rate non-penetrating blunt impact</div></li><li><div><b>Pelvis:</b> Injurious pelvis deformation in high-speed rear-facing frontal impacts</div></li><li><div><b>Lower extremities:</b> Generation of 3D pediatric femur models from 2D radiographs; plantar thickness and stiffness using ultrasound; knee injuries in skiing and snowboarding using artificial intelligence 3D modeling; jumping kinematics, and kinetics in athletes with secondary task of heading a soccer ball</div></li><li><div><b>Full body, vehicle occupants:</b> Comparison of Hybrid III, THOR mid-size male, and small female ATDs in frontal sled tests; effects of booster seat on reclined small females during lateral oblique low-acceleration impacts; airbag deployment for out-of-position 50th percentile male human body model</div></li><li><div><b>Full body, unique loading scenarios:</b> Development of seat fixture and restraints for FE human body model during vertical loading; methodology for PMHS-occupied powered two wheeler and motor vehicle crash scenario</div></li></ul></div>","PeriodicalId":42847,"journal":{"name":"SAE International Journal of Transportation Safety","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136307930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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