基于野外数据建立大型底栖动物电导率水质基准的可行性探讨

科学合理地设定水质基准是水生生物保护和水生态系统恢复的基础。水体电导率数值的高低由溶解于其中的各种阴阳离子的浓度所决定,而较多的研究也证明电导率能够显著地影响水生生物类群,特别是大型底栖动物物种存活和群落结构的稳定性。离子组成的复杂性,导致无法开展基于室内实验的水生生物电导率基准值的推导。本文借鉴美国环境保护局基于野外调查数据建立电导率基准值的方法,采用流行病学打分方法,分别从电导率是否对大型底栖动物敏感物种存在毒性效应、人为干扰的增强是否会通过电导率产生毒性作用,以及其他环境因子是否对电导率基准值的制定产生影响3个方面,探讨了基于野外数据建立我国电导率基准的可行性。研究区域为辽河流域的浑河及太子河,野外调查数据采集于2009年8月至2010年5月。研究结果表明,电导率的升高显著降低了大型底栖动物敏感物种的出现频率。通过分析研究区域土地利用方式同电导率之间的相关性,证明了农业和城镇建设用地比例的增加显著地增加了水体中电导率的数值。对有可能引起物种消失的其他环境因子进行分析,结果表明电导率是引起大型底栖动物消失的主要原因。综合以上结果,基于野外调查数据来建立大型底栖动物电导率基准值是可行的,为我国水质基准的研究提供了新的思路和方法。     

喷嘴直径对降尘效果影响的试验研究

为提高喷雾降尘效率,以改善作业环境,有必要研究喷嘴直径与降尘效果间的关系。基于自行设计的喷雾降尘试验系统,采用马尔文实时高速喷雾粒度分析仪、高速摄像仪及粉尘浓度测定仪对不同直径喷嘴的雾化特性参数和降尘效率进行测定。结果表明,在相同喷雾压力下,随着喷嘴直径的增大,全尘降尘效率持续增加,而呼吸性粉尘降尘效率先增加后减小,并在喷嘴直径为1.5 mm时达到最大值;在耗水量相同的情况下,随着喷嘴直径的增大,全尘和呼吸性粉尘降尘效率均下降。在井下喷雾降尘中,当耗水量不受限制时,为同时确保全尘和呼吸性粉尘降尘效率,宜选择直径为1.5 mm的喷嘴;当耗水量受限制时,宜选择直径为1.2 mm的喷嘴。     

The Contribution of Pre-impact Posture on Restrained Occupant Finite Element Model Response in Frontal Impact

Objective: The objective of this study was to discuss the influence of the pre-impact posture to the response of a finite element human body model (HBM) in frontal impacts.

Methods: This study uses previously published cadaveric tests (PMHS), which measured six realistic pre-impact postures. Seven postured models were created from the THUMS occupant model (v4.0): one matching the standard UMTRI driving posture as it was the target posture in the experiments, and six matching the measured pre-impact postures. The same measurements as those obtained during the cadaveric tests were calculated from the simulations, and biofidelity metrics based on signals correlation (CORA) were established to compare the response of the seven models to the experiments.

Results: The HBM responses showed good agreement with the PMHS responses for the reaction forces (CORA = 0.80 ± 0.05) and the kinematics of the lower part of the torso but only fair correlation was found with the head, the upper spine, rib strains (CORA= 0.50 ± 0.05) and chest deflections (CORA = 0.67 ± 0.08). All models sustained rib fractures, sternal fracture and clavicle fracture. The average number of rib fractures for all the models was 5.3 ± 1.0, lower than in the experiments (10.8 ± 9.0).

Variation in pre-impact posture greatly altered the time histories of the reaction forces, deflections and the rib strains, mainly in terms of time delay, but no definite improvement in HBM response or injury prediction was observed. By modifying only the posture of the HBM, the variability in the impact response was found to be equivalent to that observed in the experiments. The postured HBM sustained from 4 to 8 rib fractures, confirming that the pre-impact posture influenced the injury outcome predicted by the simulation.

Conclusions: This study tries to answer an important question: what is the effect of occupant posture on kinematics and kinetics. Significant differences in kinematics observed between HBM and PMHS suggesting more coupling between the pelvis and the spine for the models which makes the model response very sensitive to any variation in the spine posture. Consequently, the findings observed for the HBM cannot be extended to PMHS. Besides, pre-impact posture should be carefully quantified during experiments and the evaluation of HBM should take into account the variation in the predicted impact response due to the variation in the model posture.     

Estimated Injury Risk for Specific Injuries and Body Regions in Frontal Motor Vehicle Crashes

Objective: Injury risk curves estimate motor vehicle crash (MVC) occupant injury risk from vehicle, crash, and/or occupant factors. Many vehicles are equipped with event data recorders (EDRs) that collect data including the crash speed and restraint status during a MVC. This study's goal was to use regulation-required data elements for EDRs to compute occupant injury risk for (1) specific injuries and (2) specific body regions in frontal MVCs from weighted NASS-CDS data.

Methods: Logistic regression analysis of NASS-CDS single-impact frontal MVCs involving front seat occupants with frontal airbag deployment was used to produce 23 risk curves for specific injuries and 17 risk curves for Abbreviated Injury Scale (AIS) 2+ to 5+ body region injuries. Risk curves were produced for the following body regions: head and thorax (AIS 2+, 3+, 4+, 5+), face (AIS 2+), abdomen, spine, upper extremity, and lower extremity (AIS 2+, 3+). Injury risk with 95% confidence intervals was estimated for 15–105 km/h longitudinal delta-Vs and belt status was adjusted for as a covariate.

Results: Overall, belted occupants had lower estimated risks compared to unbelted occupants and the risk of injury increased as longitudinal delta-V increased. Belt status was a significant predictor for 13 specific injuries and all body region injuries with the exception of AIS 2+ and 3+ spine injuries. Specific injuries and body region injuries that occurred more frequently in NASS-CDS also tended to carry higher risks when evaluated at a 56 km/h longitudinal delta-V. In the belted population, injury risks that ranked in the top 33% included 4 upper extremity fractures (ulna, radius, clavicle, carpus/metacarpus), 2 lower extremity fractures (fibula, metatarsal/tarsal), and a knee sprain (2.4–4.6% risk). Unbelted injury risks ranked in the top 33% included 4 lower extremity fractures (femur, fibula, metatarsal/tarsal, patella), 2 head injuries with less than one hour or unspecified prior unconsciousness, and a lung contusion (4.6–9.9% risk). The 6 body region curves with the highest risks were for AIS 2+ lower extremity, upper extremity, thorax, and head injury and AIS 3+ lower extremity and thorax injury (15.9–43.8% risk).

Conclusions: These injury risk curves can be implemented into advanced automatic crash notification (AACN) algorithms that utilize vehicle EDR measurements to predict occupant injury immediately following a MVC. Through integration with AACN, these injury risk curves can provide emergency medical services (EMS) and other patient care providers with information on suspected occupant injuries to improve injury detection and patient triage.     

The Real-World Safety Potential of Connected Vehicle Technology

Objective: This article estimates the safety potential of a current commercially available connected vehicle technology in real-world crashes.

Method: Data from the Centre for Automotive Safety Research's at-scene in-depth crash investigations in South Australia were used to simulate the circumstances of real-world crashes. A total of 89 crashes were selected for inclusion in the study. The crashes were selected as representative of the most prevalent crash types for injury or fatal crashes and had potential to be mitigated by connected vehicle technology. The trajectory, speeds, braking, and impact configuration of the selected in-depth cases were replicated in a software package and converted to a file format allowing “replay” of the scenario in real time as input to 2 Cohda Wireless MK2 onboard units. The Cohda Wireless onboard units are a mature connected vehicle technology that has been used in both the German simTD field trial and the U.S. Department of Transport's Safety Pilot project and have been tuned for low false alarm rates when used in the real world. The crash replay was achieved by replacing each of the onboard unit Global Positioning System (GPS) inputs with the simulated data of each of the involved vehicles. The time at which the Cohda Wireless threat detection software issued an elevated warning was used to calculate a new impact speed using 3 different reaction scenarios and 2 levels of braking.

Results: It was found that between 37 and 86% of the simulated crashes could be avoided, with highest percentage due a fully autonomous system braking at 0.7 g. The same system also reduced the impact speed relative to the actual crash in all cases. Even when a human reaction time of 1.2 s and moderate braking of 0.4 g was assumed, the impact speed was reduced in 78% of the crashes. Crash types that proved difficult for the threat detection engine were head-on crashes where the approach angle was low and right turn–opposite crashes.

Conclusions: These results indicate that connected vehicle technology can be greatly beneficial in real-world crash scenarios and that this benefit would be maximized by having the vehicle intervene autonomously with heavy braking. The crash types that proved difficult for the connected vehicle technology could be better addressed if controller area network (CAN) information is available, such as steering wheel angle, so that driver intent can be inferred sooner. More accurate positioning in the real world (e.g., combining satellite positioning and accelerometer data) would allow the technology to be more effective for near-collinear head-on and rear-end crashes, because the low approach angles that are common in such crashes are currently ignored in order to minimize false alarms due to positioning uncertainty.     

Lower Leg Injury Reference Values and Risk Curves from Survival Analysis for Male and Female Dummies: Meta-analysis of Postmortem Human Subject Tests

Objective: Derive lower leg injury risk functions using survival analysis and determine injury reference values (IRV) applicable to human mid-size male and small-size female anthropometries by conducting a meta-analysis of experimental data from different studies under axial impact loading to the foot–ankle–leg complex.

Methods: Specimen-specific dynamic peak force, age, total body mass, and injury data were obtained from tests conducted by applying the external load to the dorsal surface of the foot of postmortem human subject (PMHS) foot–ankle–leg preparations. Calcaneus and/or tibia injuries, alone or in combination and with/without involvement of adjacent articular complexes, were included in the injury group. Injury and noninjury tests were included. Maximum axial loads recorded by a load cell attached to the proximal end of the preparation were used. Data were analyzed by treating force as the primary variable. Age was considered as the covariate. Data were censored based on the number of tests conducted on each specimen and whether it remained intact or sustained injury; that is, right, left, and interval censoring. The best fits from different distributions were based on the Akaike information criterion; mean and plus and minus 95% confidence intervals were obtained; and normalized confidence interval sizes (quality indices) were determined at 5, 10, 25, and 50% risk levels. The normalization was based on the mean curve. Using human-equivalent age as 45 years, data were normalized and risk curves were developed for the 50th and 5th percentile human size of the dummies.

Results: Out of the available 114 tests (76 fracture and 38 no injury) from 5 groups of experiments, survival analysis was carried out using 3 groups consisting of 62 tests (35 fracture and 27 no injury). Peak forces associated with 4 specific risk levels at 25, 45, and 65 years of age are given along with probability curves (mean and plus and minus 95% confidence intervals) for PMHS and normalized data applicable to male and female dummies. Quality indices increased (less tightness-of-fit) with decreasing age and risk level for all age groups and these data are given for all chosen risk levels.

Conclusions: These PMHS-based probability distributions at different ages using information from different groups of researchers constituting the largest body of data can be used as human tolerances to lower leg injury from axial loading. Decreasing quality indices (increasing index value) at lower probabilities suggest the need for additional tests. The anthropometry-specific mid-size male and small-size female mean human risk curves along with plus and minus 95% confidence intervals from survival analysis and associated IRV data can be used as a first step in studies aimed at advancing occupant safety in automotive and other environments.     

Comparing Green and Grey Infrastructure Using Life Cycle Cost and Environmental Impact: A Rain Garden Case Study in Cincinnati,OH

Green infrastructure (GI) is quickly gaining ground as a less costly, greener alternative to traditional methods of stormwater management. One popular form of GI is the use of rain gardens to capture and treat stormwater. We used life cycle assessment (LCA) to compare environmental impacts of residential rain gardens constructed in the Shepherd's Creek watershed of Cincinnati, Ohio to those from a typical detain and treat system. LCA is an internationally standardized framework for analyzing the potential environmental performance of a product or service by including all stages in its life cycle, including material extraction, manufacturing, use, and disposal. Complementary to the life cycle environmental impact assessment, the life cycle costing approach was adopted to compare the equivalent annual costs of each of these systems. These analyses were supplemented by modeling alternative scenarios to capture the variability in implementing a GI strategy. Our LCA models suggest rain garden costs and impacts are determined by labor requirement; the traditional alternative's impacts are determined largely by the efficiency of wastewater treatment, while costs are determined by the expense of tunnel construction. Gardens were found to be the favorable option, both financially (~42% cost reduction) and environmentally (62‐98% impact reduction). Wastewater utilities may find significant life cycle cost and environmental impact reductions in implementing a rain garden plan.