Multibody model of the human upper extremity for fracture simulation

About 3.8 million people are injured in accidents at work in Europe every year. The resulting high costs are incurred by the victims themselves, their families, employers and society. We have used a numerical simulation to reconstruct accidents at work for several years. To reconstruct these accidents MADYMO R7.5 with a numerical human model (pedestrian model) is used. However, this model is dedicated to the analysis of car-to-pedestrian accidents and thus cannot be fully used for reconstructing accidents at work. Therefore, we started working on the development of a numerical model of the human body for the purpose of simulating accidents at work. Developing a new numerical model which gives an opportunity to simulate fractures of the upper extremity bones is a stage of that work.     

Analysis of car-to-bicycle approach patterns for developing active safety devices

Objective: To reduce the severity of injuries and the number of cyclist deaths in traffic accidents, active safety devices providing cyclist detection are considered to be effective countermeasures. The features of car-to-bicycle collisions need to be known in detail to develop such safety devices.

Methods: The study investigated near-miss situations captured by drive recorders installed in passenger cars. Because similarities in the approach patterns between near-miss incidents and real-world fatal cyclist accidents in Japan were confirmed, we analyzed the 229 near-miss incident data via video capturing bicycles crossing the road in front of forward-moving cars. Using a video frame captured by a drive recorder, the time to collision (TTC) was calculated from the car's velocity and the distance between the car and bicycle at the moment when the bicycle initially appeared.

Results: The average TTC in the cases where bicycles emerged from behind obstructions was shorter than that in the cases where drivers had unobstructed views of the bicycles. In comparing the TTC of car-to-bicycle near-miss incidents to the previously obtained results of car-to-pedestrian near-miss incidents, it was determined that the average TTC in car-to-bicycle near-miss incidents was significantly longer than that in car-to-pedestrian near-miss incidents.

Conclusions: When considering the TTC in the test protocol of evaluation for safety performance of active safety devices, we propose individual TTCs for evaluation of cyclist and pedestrian detections, respectively. In the test protocols, the following 2 scenarios should be employed: bicycle emerging from behind an unobstructed view and bicycle emerging from behind obstructions.     

Traffic accident reconstruction and an approach for prediction of fault rates using artificial neural networks: A case study in Turkey

Objective: Currently, in Turkey, fault rates in traffic accidents are determined according to the initiative of accident experts (no speed analyses of vehicles just considering accident type) and there are no specific quantitative instructions on fault rates related to procession of accidents which just represents the type of collision (side impact, head to head, rear end, etc.) in No. 2918 Turkish Highway Traffic Act (THTA 1983). The aim of this study is to introduce a scientific and systematic approach for determination of fault rates in most frequent property damage–only (PDO) traffic accidents in Turkey.

Methods: In this study, data (police reports, skid marks, deformation, crush depth, etc.) collected from the most frequent and controversial accident types (4 sample vehicle–vehicle scenarios) that consist of PDO were inserted into a reconstruction software called vCrash. Sample real-world scenarios were simulated on the software to generate different vehicle deformations that also correspond to energy-equivalent speed data just before the crash. These values were used to train a multilayer feedforward artificial neural network (MFANN), function fitting neural network (FITNET, a specialized version of MFANN), and generalized regression neural network (GRNN) models within 10-fold cross-validation to predict fault rates without using software. The performance of the artificial neural network (ANN) prediction models was evaluated using mean square error (MSE) and multiple correlation coefficient (R).

Results: It was shown that the MFANN model performed better for predicting fault rates (i.e., lower MSE and higher R) than FITNET and GRNN models for accident scenarios 1, 2, and 3, whereas FITNET performed the best for scenario 4. The FITNET model showed the second best results for prediction for the first 3 scenarios. Because there is no training phase in GRNN, the GRNN model produced results much faster than MFANN and FITNET models. However, the GRNN model had the worst prediction results. The R values for prediction of fault rates were close to 1 for all folds and scenarios.

Conclusions: This study focuses on exhibiting new aspects and scientific approaches for determining fault rates of involvement in most frequent PDO accidents occurring in Turkey by discussing some deficiencies in THTA and without regard to initiative and/or experience of experts. This study yields judicious decisions to be made especially on forensic investigations and events involving insurance companies. Referring to this approach, injury/fatal and/or pedestrian-related accidents may be analyzed as future work by developing new scientific models.     

Driver's obesity and road crash risks in the United States

Objective: We assessed obesity trends in U.S. drivers involved in fatal crashes since 1999 and distinguished whether crash risk factors were different between obese and nonobese drivers.

Methods: We included only drivers of passenger cars involved in fatal traffic crashes between January 1, 1999, and December 31, 2012. Obesity was classified according to the World Health Organization guidelines and profiled between 1999 and 2012 using the adjusted prevalence ratio (aPR) from log-binomial regression models. Differences in crash risks (e.g., driver's fatality, drunk driving, seat belt nonuse) between obese and nonobese drivers were estimated as adjusted odds ratios (aORs) using logistic regression models.

Results: A total of 753,024 U.S. drivers were involved in fatal crashes, for which obesity information was available for 534,887. About 56% (n = 299,078) were driving passenger cars. The prevalence of class I obesity increased from 10% in 1999 to 14% in 2012 (aPR = 1.50, 95% confidence interval [CI], 1.42–1.58), class II obesity from 3 to 5% (aPR = 2.22, 95% CI, 2.05–3.01), and class III obesity from 1 to 2% (aPR = 2.65; 95% CI, 2.27–3.10). Compared to nonobese controls, obese drivers had significantly higher risks for fatality (1.10 ≤ aOR ≤ 1.47), seat belt nonuse (1.00 ≤ aOR ≤ 1.21), need for extrication (1.01 ≤ aOR ≤ 1.23), and ambulance transport time ≥30 min (1.01 ≤ aOR ≤ 1.28). Compared to nonobese controls, obese drivers were less likely to drink drive (0.41 ≤ aOR ≤ 0.72) or speed >65 mph (0.78 ≤ aOR ≤ 0.93).

Conclusion: The rising national prevalence of obesity extends to U.S. drivers involved in fatal crashes and indicates the need to improve seat belt use, vehicle design, and postcrash care for this vulnerable population.     

Model experiment on the dynamic process of oil leakage from the double hull tanker

This paper presents an experimental investigation on oil leakage from the double hull tanker (DHT). It is designed to explore the dynamic process of oil leakage from bottom-rupture hole of DHT. The experimental test shows the leakage resistance mechanism of ballast tank space. The behavior of oil leakage from damaged DHT and dynamic features of flow in the overall process are demonstrated from experimental results. The overall process of oil leakage is divided into free-leakage and resistance-leakage stage according to the corresponding power to study the dynamic features of oil-water flow inside or outside the tank. The corresponding dominated factors of oil leakage in different stage are also pointed out, and the unsteady Bernoulli’s equation is used to verify experimental results. Meanwhile, viscous effect in leakage process is discussed and the importance of hydrodynamic features associated with the mechanism of oil leakage is explored from experimental results.     

Risk management in operations of petrochemical plants: Can better planning prevent major accidents and save money at the same time?

This paper presents an argument that improvement in operational safety can be achieved concurrently with increased operational efficiency. This is a fundamentally different viewpoint on the investment in safety. Traditionally, the cost of providing safety barriers is offset by the expected benefits of reducing the occurrence and severity of accidents. Our approach departs from this method of accounting for safety improvements and focuses on planning as a means of managing systems' response uncertainty and consequently reducing both major accident risk and the cost of operations. The scope of the paper is limited to interventions such as maintenance and repairs and defined in the context of major accident prevention e.g. hydrocarbon leaks. However, the developed methodology is general enough to be applied across the spectrum of process industry facilities and operations.     

炼油行业泄漏检测与修复技术实践研究

炼油行业排放的大气污染物主要是挥发性有机物,是形成二次污染物的重要前体物,也是引发大气环境问题的重要污染物.以天津某炼油企业泄漏检测与修复技术的工作实践为例,结合炼油行业生产装置的工艺特点,介绍在该行业开展泄漏检测与修复技术时的工作流程,包括设备和管线组件密封点位的建档、检测、泄漏点位的修复、复测以及泄漏量核算方法,对炼油行业开展泄漏检测与修复工作减少挥发性有机物无组织的排放起到借鉴作用.     

钱塘江突发水污染事故应急系统开发与应用

采用网络信息平台和水环境模型相结合的技术手段,构建了钱塘江突发水污染事故应急系统。该系统旨在帮助应急管理部门快速应对钱塘江流域突发性水污染事故,以及保障G20峰会期间钱塘江流域的饮用水源地安全。该系统以水动力模型、溢油和化学品泄漏模型为核心,采用空间关系型中央数据库作为数据管理系统,基于网络GIS技术开发而成。通过对钱塘江流域历史事故的反演,验证了该系统的准确度和可靠性。在该系统的基础上,构建了钱塘江流域典型流场库和典型突发水污染事故情景库,以实现快速应对G20峰会期间钱塘江流域突发水污染事故风险。     

试论突发性环境污染事故的应急监测

文章集中阐述了突发性污染事故的类型以及具有的基础特性,分析了环境污染事故的严重性与危害性。论述了突发性污染事故的应急监测体系的建立,应急监测工作的开展,应急监测的要求,为污染事故的应急监测起到了重要指导作用。