Applying Hierarchical Loglinear Models to Nonfatal Underground Coal Mine Accidents for Safety Management

Underground mining is considered to be one of the most dangerous industries and mining remains the most hazardous occupation. Categorical analysis of accident records may present valuable information for preventing accidents. In this study, hierarchical loglinear analysis was applied to occupational injuries that occurred in an underground coal mine. The main factors affecting the accidents were defined as occupation, area, reason, accident time and part of body affected. By considering subfactors of the main factors, multiway contingency tables were prepared and, thus, the probabilities that might affect nonfatal injuries were investigated. At the end of the study, important accident risk factors and job groups with a high probability of being exposed to those risk factors were determined. This article presents important information on decreasing the number accidents in underground coal mines.     

Participation for understanding: an interactive method

INTRODUCTION: There are many available models that help evaluate the effectiveness of safety and health measures, but many are complex and require input from many departments within an organization. There is a need to develop a more user-friendly model. METHOD: A participative model was developed that involves face-to-face interviewers with workers, maintenance department, purchasing department and health and safety experts. They were asked about costs, efforts, benefits, and effects of gauging the effects of prevention efforts. RESULTS: Cost effectiveness analyses are essential in all cases and can include whatever the end-user requires, whether it is a small or lasting improvement. Having management participate helps validate the data. CONCLUSIONS: Organizations who collaborate with someone with at least some skill in cost-benefit evaluations will find that they will be able to establish policies and procedures from the data. The end result is a calculation that is understood by all involved.     

The potential-method--an economic evaluation tool

INTRODUCTION: Measuring the effect of safety and health on production is a difficult value to gauge. METHOD: This article introduces the Potential, which is an instrument for economic analysis that incorporates different changes in conditions. RESULTS: While there are a number of problems associated with methods to determine these calculations, this method is a good indicator of the effects of safety and health and produces more than 300 variables with much less input. IMPACT ON INDUSTRY: Organizations can use this method effectively to determine how safety and health measure can improve their bottom line. A positive business case is highlighted.     

The estimated reduction in the odds of loss-of-control type crashes for sport utility vehicles equipped with electronic stability control

INTRODUCTION: Using data from the NASS General Estimates System (GES), the method of induced exposure was used to assess the effects of electronic stability control (ESC) on loss-of-control type crashes for sport utility vehicles. METHOD: Sport utility vehicles were classified into crash types generally associated with loss of control and crash types most likely not associated with loss of control. Vehicles were then compared as to whether ESC technology was present or absent in the vehicles. A generalized additive model was fit to assess the effects of ESC, driver age, and driver gender on the odds of loss of control. In addition, the effects of ESC on roads that were not dry were compared to effects on roads that were dry. RESULTS: Overall, the estimated percentage reduction in the odds of a loss-of-control crash for sport utility vehicles equipped with ESC was 70.3%. Both genders and all age groups showed reduced odds of loss-of-control crashes, but there was no significant difference between males and females. With respect to driver age, the maximum percentage reduction of 73.6% occurred at age 27. The positive effects of ESC on roads that were not dry were significantly greater than on roads that were dry.     

抽出式通风煤巷掘进过程中粉尘浓度分布规律的数值模拟

根据气固两相流理论，针对矿井掘进工作面的特点，采用计算流体力学的离散相模型（DPM）对掘进工作面通风过程中粉尘浓度进行数值模拟，总结抽出式通风掘进巷道中粉尘浓度的沿程分布及变化规律。     

改善太仓城区水环境原型调水实验研究及模型建立

为达到改善太仓城区水环境的目的,于2004年4月21日进行了调水实验.调水历时14 h,期间向城区调水21.8万m3.通过对监测点采样,得到水量、水质实测数据.根据实验数据,建立了符合太仓河网的水量水质数学模型,分析了从长江引水对太仓城区水环境的改善程度.同时对不同引水方案情况下城区水环境改善效果,以及截污和清淤对水环境的影响做了分析.研究表明,引水只能短期改善水环境;要根治水环境,必须从源头抓起,进行截污.     

Efficient Delineation of Nested Depression Hierarchy in Digital Elevation Models for Hydrological Analysis Using Level‐Set Method

In terrain analysis and hydrological modeling, surface depressions (or sinks) in a digital elevation model (DEM) are commonly treated as artifacts and thus filled and removed to create a depressionless DEM. Various algorithms have been developed to identify and fill depressions in DEMs during the past decades. However, few studies have attempted to delineate and quantify the nested hierarchy of actual depressions, which can provide crucial information for characterizing surface hydrologic connectivity and simulating the fill‐merge‐spill hydrological process. In this paper, we present an innovative and efficient algorithm for delineating and quantifying nested depressions in DEMs using the level‐set method based on graph theory. The proposed level‐set method emulates water level decreasing from the spill point along the depression boundary to the lowest point at the bottom of a depression. By tracing the dynamic topological changes (i.e., depression splitting/merging) within a compound depression, the level‐set method can construct topological graphs and derive geometric properties of the nested depressions. The experimental results of two fine‐resolution Light Detection and Ranging‐derived DEMs show that the raster‐based level‐set algorithm is much more efficient (~150 times faster) than the vector‐based contour tree method. The proposed level‐set algorithm has great potential for being applied to large‐scale ecohydrological analysis and watershed modeling.     

Maximizing Returns from Payments for Water‐Based Ecosystem Services: Incorporating Externality Effects of Land Management

Given the expansion of payments for water‐based ecosystem services (PWES) worldwide, two relevant issues are as follows: (1) determination of efficient allocations of payments among land managers, and (2) how this might change when paying one manager to implement a best management practice (BMP) to enhance an ecosystem service impacts the cost‐effectiveness of BMPs considered by other land managers not currently involved in PWES. Such externalities may be negative if diminishing returns dominate, or positive if mechanisms such as “social diffusion” dominate. We analyze how a planner should optimally allocate payments, depending on whether the expected externalities are negligible, negative, or positive. We employ (1) an optimal control model to gain insights on the problem’s dynamics, and (2) stochastic dynamic programming to determine optimal funding strategies using a specific application. The study contributes to the literature by identifying dynamically optimal PWES payment patterns, and illustrates how they should change when one accounts for externalities induced by the program. Because such impacts have not been addressed previously in a rigorous way, this treatment provides useful value added for PWES design and implementation.     

Air‐Water Temperature Relationships in the Trout Streams of Southeastern Minnesota's Carbonate‐Sandstone Landscape

Carbonate‐sandstone geology in southeastern Minnesota creates a heterogeneous landscape of springs, seeps, and sinkholes that supply groundwater into streams. Air temperatures are effective predictors of water temperature in surface‐water dominated streams. However, no published work investigates the relationship between air and water temperatures in groundwater‐fed streams (GWFS) across watersheds. We used simple linear regressions to examine weekly air‐water temperature relationships for 40 GWFS in southeastern Minnesota. A 40‐stream, composite linear regression model has a slope of 0.38, an intercept of 6.63, and R² of 0.83. The regression models for GWFS have lower slopes and higher intercepts in comparison to surface‐water dominated streams. Regression models for streams with high R² values offer promise for use as predictive tools for future climate conditions. Climate change is expected to alter the thermal regime of groundwater‐fed systems, but will do so at a slower rate than surface‐water dominated systems. A regression model of intercept vs. slope can be used to identify streams for which water temperatures are more meteorologically than groundwater controlled, and thus more vulnerable to climate change. Such relationships can be used to guide restoration vs. management strategies to protect trout streams.     

Hydro-abrasive erosion in hydro turbines: a review

The flow of sediment particles in rivers is a big challenge to develop hydropower plants across the sediment-laden rivers. Hard particles such as quartz and feldspar are available in high amount in the Asian mountain range. The abrasive action of these particles causes the hydro turbines to suffer from erosion in particular at high- and medium-head hydroelectric power plants. This has become a serious economic issue due to maintenance costs and production losses. The treatment without prevention is simply unsustainable. Facilities for sediment exclusion, typically sand traps as well as turbine design, and materials have been improved considerably. In the present paper, studies have been discussed extensively undertaken by several investigators in this field. Based on literature survey several aspects related to reducing the sediment load on turbines, useful ways to improve the turbine surface performance and various erosion models to characterize the effect of erosion on the performance of turbines have been discussed. To calibrate and validate the developed erosion models, more measurements from both physical model tests in laboratories and continuous monitoring of sediment parameters and their impact on the operational hydro turbines are required. As well as the state-of-art in the modeling and simulation using computational fluid dynamics (CFD) has made it possible to optimize the hydraulic design of hydro turbines in order to minimize the erosion level without much sacrifice in the efficiency. To mitigate the hydro-abrasive erosion effects on the performance of turbines, significant improvements have been achieved so far and development is ongoing.