基于.NET Framework和Direct3D技术实现危险性液体储罐泄漏过程的三维仿真

由于windows操作系统的大面积使用,使得基于windows操作系统的Direct3D技术在游戏开发和三维仿真方面日益重要,已经成为事实上的3D标准,基于.NET Framework的3D技术的开发也是未来一个趋势,本文研究建立了描述危险性液体储罐泄漏过程的数值模型,基于.NETFramework,运用Direct3D技术开发了动态模拟软件,不仅实现了泄漏过程的三维动态效果,提高仿真的逼真程度,而且可以获取泄漏速率、泄漏量、液面高度和时间的关系。实例分析结果表明,本文所建立的数值模型和仿真方法是可行的,模拟仿真结果为危险性液体储罐泄漏事故后果定量风险评价和事故应急救援提供理论依据和基础数据,也可以应用于科研方面,进一步研究液体储罐泄漏机理,节省研究时人力物力和时间的消耗。     

基于计划行为理论的矿工违章行为研究

矿工违章行为是诱发煤矿重大事故的关键因素之一,以计划行为理论(TPB)为构架,加入过去行为和风险倾向2个变量,提出矿工违章行为影响因素之间的假设关系。通过问卷调查并运用结构方程模型(SEM)探讨违章行为影响因素之间的关系。结果表明:行为态度、主观规范、行为控制认知、风险倾向这4个变量对违章行为均有显著影响,主观规范和过去行为通过行为态度这一中介变量又间接地影响违章行为。实证研究结果表明,TPB模型在解释矿工违章行为问题上的适用性。     

基于结构方程模型的安全生产行政执法绩效分析

为加强对企业安全生产的监督和完善行政执法的评估体系,构建了企业安全生产行政执法绩效评估指标体系。利用调查问卷的方式,获得行政执法部门的绩效评价数据。根据结构方程模型(SEM)相关原理设计绩效评价的测量模型,通过AMOS17.0软件对评价体系进行分析,得到各指标的标准化估计值。利用标准化估计值分析各潜变量对企业安全生产执法的影响权重,各观察变量对企业安全生产执法的影响权重,并进行排序,结果显示:行政执法的合法性>执法人员的素质>执法的合理性>执法的文明性>执法的公开性。     

Random parameter models for accident prediction on two-lane undivided highways in India

Introduction

Generalized linear modeling (GLM), with the assumption of Poisson or negative binomial error structure, has been widely employed in road accident modeling. A number of explanatory variables related to traffic, road geometry, and environment that contribute to accident occurrence have been identified and accident prediction models have been proposed. The accident prediction models reported in literature largely employ the fixed parameter modeling approach, where the magnitude of influence of an explanatory variable is considered to be fixed for any observation in the population. Similar models have been proposed for Indian highways too, which include additional variables representing traffic composition. The mixed traffic on Indian highways comes with a lot of variability within, ranging from difference in vehicle types to variability in driver behavior. This could result in variability in the effect of explanatory variables on accidents across locations. Random parameter models, which can capture some of such variability, are expected to be more appropriate for the Indian situation.

Method

The present study is an attempt to employ random parameter modeling for accident prediction on two-lane undivided rural highways in India. Three years of accident history, from nearly 200 km of highway segments, is used to calibrate and validate the models.

Results

The results of the analysis suggest that the model coefficients for traffic volume, proportion of cars, motorized two-wheelers and trucks in traffic, and driveway density and horizontal and vertical curvatures are randomly distributed across locations.

Conclusions

The paper is concluded with a discussion on modeling results and the limitations of the present study.     

Scale-up modeling of the twin roll casting process for AZ31 magnesium alloy

In the present study, a 2-D finite-element method (FEM) thermal-fluid-stress model has been developed and validated for the twin roll casting (TRC) of AZ31 magnesium alloy. The model was then used to quantify how the thermo-mechanical history experienced by the strip during TRC would change as the equipment was scaled up from a laboratory size (roll diameter = 355 mm) to a pilot scale (roll diameter = 600 mm) and to an industrial scale (roll diameter = 1150 mm) machine. The model predictions showed that the thermal history and solidification cooling rate experienced by the strip are not affected significantly by caster scale-up. However, the mechanical history experienced by the strip did change remarkably depending on the roll diameters. Casting with bigger rolls led to the development of higher stress levels at the strip surface. The roll separating force/mm width of strip was also predicted to increase significantly when the TRC was scaled to larger sizes. Using the model predicted results, the effect of both casting speed and roll diameter was integrated into an empirical equation to predict the exit temperature and the roll separating force for AZ31. Using this approach, a TRC process map was generated for AZ31 which included roll diameter and casting speed.     

Watershed Regressions for Pesticides (warp) Models for Predicting Atrazine Concentrations in Corn Belt Streams1

Stone, Wesley W. and Robert J. Gilliom, 2012. Watershed Regressions for Pesticides (WARP) Models for Predicting Atrazine Concentrations in Corn Belt Streams. Journal of the American Water Resources Association (JAWRA) 48(5): 970‐986. DOI: 10.1111/j.1752‐1688.2012.00661.x Abstract: Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region‐specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP‐CB) were developed for annual maximum moving‐average (14‐, 21‐, 30‐, 60‐, and 90‐day durations) and annual 95th‐percentile atrazine concentrations in streams of the Corn Belt region. The WARP‐CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model‐development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model‐development sites. The WARP‐CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine‐use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP‐CB models. The WARP‐CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine‐use intensities of 17 kg/km² of watershed area or greater.     

Comparison of Stream Invertebrate Response Models for Bioassessment Metrics1

Waite, Ian R., Jonathan G. Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, and James L. Orlando, 2012. Comparison of Stream Invertebrate Response Models for Bioassessment Metrics. Journal of the American Water Resources Association (JAWRA) 48(3): 570-583. DOI: 10.1111/j.1752-1688.2011.00632.x Abstract: We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BRT). We used tolerance of taxa based on richness (RICHTOL) and ratio of observed to expected taxa (O/E) as response variables and land use/land cover as explanatory variables. Responses were generally linear; therefore, there was little improvement to the MLR models when compared to models using CART and RF. In general, the four modeling techniques (MLR, CART, RF, and BRT) consistently selected the same primary explanatory variables for each region. However, results from the BRT models showed significant improvement over the MLR models for each region; increases in R² from 0.09 to 0.20. The O/E metric that was derived from models specifically calibrated for Oregon consistently had lower R² values than RICHTOL for the two regions tested. Modeled O/E R² values were between 0.06 and 0.10 lower for each of the four modeling methods applied in the Willamette Valley and were between 0.19 and 0.36 points lower for the Blue Mountains. As a result, BRT models may indeed represent a good alternative to MLR for modeling species distribution relative to environmental variables.     

Evaluation of geometrically personalized THUMS pedestrian model response against sedan–pedestrian PMHS impact test data

Objective: Evaluating the biofidelity of pedestrian finite element models (PFEM) using postmortem human subjects (PMHS) is a challenge because differences in anthropometry between PMHS and PFEM could limit a model's capability to accurately capture cadaveric responses. Geometrical personalization via morphing can modify the PFEM geometry to match the specific PMHS anthropometry, which could alleviate this issue. In this study, the Total Human Model for Safety (THUMS) PFEM (Ver 4.01) was compared to the cadaveric response in vehicle–pedestrian impacts using geometrically personalized models.

Methods: The AM50 THUMS PFEM was used as the baseline model, and 2 morphed PFEM were created to the anthropometric specifications of 2 obese PMHS used in a previous pedestrian impact study with a mid-size sedan. The same measurements as those obtained during the PMHS tests were calculated from the simulations (kinematics, accelerations, strains), and biofidelity metrics based on signals correlation (correlation and analysis, CORA) were established to compare the response of the models to the experiments. Injury outcomes were predicted deterministically (through strain-based threshold) and probabilistically (with injury risk functions) and compared with the injuries reported in the necropsy.

Results: The baseline model could not accurately capture all aspects of the PMHS kinematics, strain, and injury risks, whereas the morphed models reproduced biofidelic response in terms of trajectory (CORA score = 0.927 ± 0.092), velocities (0.975 ± 0.027), accelerations (0.862 ± 0.072), and strains (0.707 ± 0.143). The personalized THUMS models also generally predicted injuries consistent with those identified during posttest autopsy.

Conclusions: The study highlights the need to control for pedestrian anthropometry when validating pedestrian human body models against PMHS data. The information provided in the current study could be useful for improving model biofidelity for vehicle–pedestrian impact scenarios.     

Perceived mastery climate,felt trust,and knowledge sharing

Interpersonal trust is associated with a range of adaptive outcomes, including knowledge sharing. However, to date, our knowledge of antecedents and consequences of employees feeling trusted by supervisors in organizations remains limited. On the basis of a multisource, multiwave field study among 956 employees from 5 Norwegian organizations, we examined the predictive roles of perceived mastery climate and employee felt trust for employees' knowledge sharing. Drawing on the achievement goal theory, we develop and test a model to demonstrate that when employees perceive a mastery climate, they are more likely to feel trusted by their supervisors at both the individual and group levels. Moreover, the relationship between employees' perceptions of a mastery climate and supervisor‐rated knowledge sharing is mediated by perceptions of being trusted by the supervisor. Theoretical contributions and practical implications of our findings are discussed.     

INASUD project findings on integrated assessment of climate policies

This communication summarizes the main findings of INASUD, an European-wide research project on integrated assessment of climate policies. The project aimed at improving the framing of climate policy analysis through the parallel use of various existing integrated assessment models. It provides a comprehensive examination of the link between uncertainty regarding damages and inertia in economic systems. Results show that the Kyoto targets and timing are consistent with the precautionary principle but offers little insurance for longer-term climate protection. Flexibility mechanisms offer potentials for cooperation with developing countries, and are necessary to tap the environmental and economic benefits of joint carbon and sulfur emissions abatement.