基于随机模拟的地下水污染物最优水力截获量

水力截获技术是净化或抑制地下水污染最为广泛使用的一种方法，而该技术实施过程中，如何确定最优水力截获量是其需要重点解决的关键问题.本文针对传统确定性方法计算最优水力截获量不合理的问题，从水文地质参数的随机性出发，应用基于随机理论的蒙特卡罗方法，通过实例来研究渗透系数的空间变异性对地下水污染物水力截获系统的影响，并寻求估算最优水力截获量的新方法.通过研究表明：基于确定性方法计算出最优水力截获量为110m³/d时恰好能完全截获污染区的污染物；应用随机模拟研究含水层渗透系数的空间变异性对水力截获系统的影响，发现当以传统确定性方法所计算的最优水力截获量（110m³/d）抽水时，并不能总是完全截获地下水污染物，其面临的稳定平均风险率高达24%；充分考虑了含水层渗透系数空间变异的Monte Carlo方法较以往传统确定性方法更为可靠，为此本文提出利用随机方法从截获系统可接受风险角度确定最优截获量的新思路.     

Development and Validation of the Total HUman Model for Safety (THUMS) Toward Further Understanding of Occupant Injury Mechanisms in Precrash and During Crash

Objective: Active safety devices such as automatic emergency brake (AEB) and precrash seat belt have the potential to accomplish further reduction in the number of the fatalities due to automotive accidents. However, their effectiveness should be investigated by more accurate estimations of their interaction with human bodies. Computational human body models are suitable for investigation, especially considering muscular tone effects on occupant motions and injury outcomes. However, the conventional modeling approaches such as multibody models and detailed finite element (FE) models have advantages and disadvantages in computational costs and injury predictions considering muscular tone effects. The objective of this study is to develop and validate a human body FE model with whole body muscles, which can be used for the detailed investigation of interaction between human bodies and vehicular structures including some safety devices precrash and during a crash with relatively low computational costs.

Methods: In this study, we developed a human body FE model called THUMS (Total HUman Model for Safety) with a body size of 50th percentile adult male (AM50) and a sitting posture. The model has anatomical structures of bones, ligaments, muscles, brain, and internal organs. The total number of elements is 281,260, which would realize relatively low computational costs. Deformable material models were assigned to all body parts. The muscle–tendon complexes were modeled by truss elements with Hill-type muscle material and seat belt elements with tension-only material. The THUMS was validated against 35 series of cadaver or volunteer test data on frontal, lateral, and rear impacts. Model validations for 15 series of cadaver test data associated with frontal impacts are presented in this article. The THUMS with a vehicle sled model was applied to investigate effects of muscle activations on occupant kinematics and injury outcomes in specific frontal impact situations with AEB.

Results and Conclusions: In the validations using 5 series of cadaver test data, force–time curves predicted by the THUMS were quantitatively evaluated using correlation and analysis (CORA), which showed good or acceptable agreement with cadaver test data in most cases. The investigation of muscular effects showed that muscle activation levels and timing had significant effects on occupant kinematics and injury outcomes. Although further studies on accident injury reconstruction are needed, the THUMS has the potential for predictions of occupant kinematics and injury outcomes considering muscular tone effects with relatively low computational costs.     

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.     

A new approach to determine relieving temperature and thermodynamic behavior of trapped single and multi-phase fluid exposed to fire

Process safety plays a key role in modern industries. This is more significant specifically in off-shore oil and gas platforms where releasing hydrocarbons could cause irreversible damages to both environment and personnel. An important instrument device which can provide safety for process equipment in oil and gas fields is safety relief valve. Correct sizing procedure of such devices depends strongly on physical properties of fluid and relieving condition. The present study revolved around applying thermodynamic concepts and modeling to throw some light on the behavior of trapped fluid exposed to fire in order to evaluate precise temperature and fluid properties at relieving condition. Peng–Robinson equation of state together with a three phase flash has been utilized to handle the calculation. Effect of different design parameters has been evaluated for three distinct categories of fluids namely natural gas, gas-condensate mixture, and gas-oil mixtures. These parameters encompass of operating temperature, operating pressure, Difference of Operating and Design Pressure, gas and oil specific gravities, gas-oil ratio, and water cut. The study depicted that American Petroleum Institute practice number 521 which suggests an ideal gas assumption fails to provide reliable predictions as it significantly overestimate the relieving temperature. Moreover, black oil correlations were also used for the relief temperature estimation of gas-oil-water mixtures. Comparison with HYSYS results as a prominent engineering software proved that black oil models are reliable tools to predict relief temperature.     

A Modeling System to Assess Land Cover Land Use Change Effects on SAV Habitat in the Mobile Bay Estuary

Estuarine ecosystems are largely influenced by watersheds directly connected to them. In the Mobile Bay, Alabama watersheds we examined the effect of land cover and land use (LCLU) changes on discharge rate, water properties, and submerged aquatic vegetation, including freshwater macrophytes and seagrasses, throughout the estuary. LCLU scenarios from 1948, 1992, 2001, and 2030 were used to influence watershed and hydrodynamic models and evaluate the impact of LCLU change on shallow aquatic ecosystems. Overall, our modeling results found that LCLU changes increased freshwater flows into Mobile Bay altering temperature, salinity, and total suspended sediments (TSS). Increased urban land uses coupled with decreased agricultural/pasture lands reduced TSS in the water column. However, increased urbanization or agricultural/pasture land coupled with decreased forest land resulted in higher TSS concentrations. Higher sediment loads were usually strongly correlated with higher TSS levels, except in areas where a large extent of wetlands retained sediment discharged during rainfall events. The modeling results indicated improved water clarity in the shallow aquatic regions of Mississippi Sound and degraded water clarity in the Wolf Bay estuary. This integrated modeling approach will provide new knowledge and tools for coastal resource managers to manage shallow aquatic habitats that provide critical ecosystem services.     

Development of the Spatial Rainfall Generator (SRGEN) for the Agricultural Policy/Environmental Extender Model

Accurate spatial representation of climatic patterns is often a challenge in modeling biophysical processes at the watershed scale, especially where the representation of a spatial gradient in rainfall is not sufficiently captured by the number of weather stations. The spatial rainfall generator (SRGEN) is developed as an extension of the “weather generator” (WXGEN), a component of the Agricultural Policy/Environmental eXtender (APEX) model. SRGEN generates spatially distributed daily rainfall using monthly weather statistics available at multiple locations in a watershed. The spatial rainfall generator as incorporated in APEX is tested on the Cowhouse watershed (1,178 km²) in central Texas. The watershed presented a significant spatial rainfall gradient of 2.9 mm/km in the lateral (north‐south) directions based on four rainfall gages. A comparative analysis between SRGEN and WXGEN indicates that SRGEN performs well (PBIAS = 2.40%). Good results were obtained from APEX for streamflow (NSE = 0.99, PBIAS = 8.34%) and NO₃‐N and soluble P loads (PBIAS ≈ 6.00% for each, respectively). However, APEX underpredicted sediment yield and organic N and P loads (PBIAS: 24.75‐27.90%) with SRGEN, although its uncertainty in output was lower than WXGEN results (PBIAS: ?13.02 to ?46.13%). The overall improvement achieved in rainfall generation by SRGEN is demonstrated to be effective in the improving model performance on flow and water quality output.     

Structure and Content of the Discourse on Climate Change in the Blogosphere: The Big Picture

Based on the texts of 1.3 million blog posts and the structure of the links between the blogs in which these posts appeared, this study presents an analysis of the discourse on climate change in the English-language blogosphere. Our approach combines community detection with probabilistic topic modeling to show how topics related to climate change are discussed across various parts of the blogosphere. We find that there is one community of predominantly climate skeptical blogs but several accepter communities. The topic analysis reveals a series of issues that are characteristic of the climate change discourse in the blogosphere. Two topics, one related to climate change science and one related to climate change politics, are particularly important for characterizing the discourse. We also find that the distribution of topics over the communities cuts across the divide between skeptics and non-skeptics (accepters) and that there are differences in the patterns of interactions between the skeptics and different groups of accepters.     

Geographic range size and extinction risk assessment in nomadic species

Geographic range size is often conceptualized as a fixed attribute of a species and treated as such for the purposes of quantification of extinction risk; species occupying smaller geographic ranges are assumed to have a higher risk of extinction, all else being equal. However many species are mobile, and their movements range from relatively predictable to‐and‐fro migrations to complex irregular movements shown by nomadic species. These movements can lead to substantial temporary expansion and contraction of geographic ranges, potentially to levels which may pose an extinction risk. By linking occurrence data with environmental conditions at the time of observations of nomadic species, we modeled the dynamic distributions of 43 arid‐zone nomadic bird species across the Australian continent for each month over 11 years and calculated minimum range size and extent of fluctuation in geographic range size from these models. There was enormous variability in predicted spatial distribution over time; 10 species varied in estimated geographic range size by more than an order of magnitude, and 2 species varied by >2 orders of magnitude. During times of poor environmental conditions, several species not currently classified as globally threatened contracted their ranges to very small areas, despite their normally large geographic range size. This finding raises questions about the adequacy of conventional assessments of extinction risk based on static geographic range size (e.g., IUCN Red Listing). Climate change is predicted to affect the pattern of resource fluctuations across much of the southern hemisphere, where nomadism is the dominant form of animal movement, so it is critical we begin to understand the consequences of this for accurate threat assessment of nomadic species. Our approach provides a tool for discovering spatial dynamics in highly mobile species and can be used to unlock valuable information for improved extinction risk assessment and conservation planning.     

Physiologically based pharmacokinetic modeling of perfluoroalkyl substances in the human body

Currently, there are limited data on the levels of perfluoroalkyl substances other than perfluorooctane sulfonic acid and perfluorooctanoic acid in the human body. Most of this information has been extracted from biological monitoring of plasma while the occurrence of perfluoroalkyl substances in other human tissues is rarely studied. The objective of the present study was to develop a physiologically based pharmacokinetic model to assess the concentration of perfluoroalkyl substances in human tissues, based on an existing model previously validated for perfluorooctane sulfonic acid and perfluorooctanoic acid. Experimental data on concentrations of perfluoroalkyl substances in human tissues from individuals in Tarragona County (Catalonia, Spain) were used to estimate the values of some distribution and elimination parameters needed for the simulation. No significant correlations were found between these parameters and the chain lengths. The model was finally validated for five perfluoroalkyl substances.     

Machine learning based quantitative consequence prediction models for toxic dispersion casualty

Incidental release of toxic chemicals can pose extreme danger to life in the vicinity. Therefore, it is crucial for emergency responders, plant operators, and safety professionals to have a fast and accurate prediction to evaluate possible toxic dispersion life-threatening consequences. In this work, a toxic chemical dispersion casualty database that contains 450 leak scenarios of 18 toxic chemicals is constructed to develop a machine learning based quantitative property-consequence relationship (QPCR) model to estimate the affected area caused by toxic chemical release within a certain death rate. The results show that the developed QPCR model can predict the toxic dispersion casualty range with root mean square error of maximum distance, minimum distance, and maximum width less than 0.2, 0.4, and 0.3, which indicates that the constructed model has satisfying accuracy in predicting toxic dispersion ranges under different lethal consequences. The model can be further expanded to accommodate more toxic chemicals and leaking scenarios.