The prediction of safe lifting behavior: an application of the theory of planned behavior

PROBLEM: Injuries resulting from lifting are costly, and create significant pain and discomfort. While engineering controls are the most effective means of reducing risks, most organizations continue to rely on manual lifting techniques. The problem, however, is that the use of safe-lifting techniques is inconsistent and managers have a difficult time motivating use of these techniques. Consequently, it is important to understand the factors driving safe-lifting behaviors. METHODS: This study used a survey to apply the theory of planned behavior (Ajzen., I., 1991. The theory of planned behavior. Organization Behavior and Human Processes, 50, 179-211) to safe-lifting among 136 materials management employees at a heavy manufacturing organization. Structural equation modeling and factor analysis were employed to analyze relationships among constructs. RESULTS: Results revealed that perceived behavioral control and intention were the strongest predictors of safe-lifting behavior. Subjective norms, to a lesser degree, were also important influences on intention. Attitudes did not surface as effective direct predictors of safe-lifting behavior, but did affect behavior and intent via mediating factors (subjective norms and perceived behavioral control). Finally, the theory of planned behavior was supported as an effective model explaining safe-lifting behavior, and had potential application for many other safety-related behaviors. IMPACT ON INDUSTRY: Results from this study emphasize the importance of perceived behavioral control as a factor associated with safety-related behavior.     

A stochastic-advective transport model for NAPL dissolution and degradation in non-uniform flows in porous media

Remediation schemes for contaminated sites are often evaluated to assess their potential for source zone reduction of mass, or treatment of the contaminant between the source and a control plane (CP) to achieve regulatory limits. In this study, we utilize a stochastic stream tube model to explain the behavior of breakthrough curves (BTCs) across a CP. At the local scale, mass dissolution at the source is combined with an advection model with first-order decay for the dissolved plume. Field-scale averaging is then employed to account for spatial variation in mass within the source zone, and variation in the velocity field. Under the assumption of instantaneous mass transfer from the source to the moving liquid, semi-analytical expressions for the BTC and temporal moments are developed, followed by derivation of expressions for effective velocity, dispersion, and degradation coefficients using the method of moments. It is found that degradation strongly influences the behavior of moments and the effective parameters. While increased heterogeneity in the velocity field results in increased dispersion, degradation causes the center of mass of the plume to shift to earlier times, and reduces the dispersion of the BTC by lowering the concentrations in the tail. Modified definitions of effective parameters are presented for degrading solutes to account for the normalization constant (zeroth moment) that keeps changing with time or distance to the CP. It is shown that anomalous dispersion can result for high degradation rates combined with wide variation in velocity fluctuations. Implications of model results on estimating cleanup times and fulfillment of regulatory limits are discussed. Relating mass removal at the source to flux reductions past a control plane is confounded by many factors. Increased heterogeneity in velocity fields causes mass fluxes past a control plane to persist, however, aggressive remediation between the source and CP can reduce these fluxes.     

Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)

Leakage diagnosis of hydrocarbon pipelines can prevent environmental and financial losses. This work proposes a novel method that not only detects the occurrence of a leakage fault, but also suggests its location and severity. The OLGA software is employed to provide the pipeline inlet pressure and outlet flow rates as the training data for the Fault Detection and Isolation (FDI) system. The FDI system is comprised of a Multi-Layer Perceptron Neural Network (MLPNN) classifier with various feature extraction methods including the statistical techniques, wavelet transform, and a fusion of both methods. Once different leakage scenarios are considered and the preprocessing methods are done, the proposed FDI system is applied to a 20-km pipeline in southern Iran (Goldkari-Binak pipeline) and a promising severity and location detectability (a correct classification rate of 92%) and a low False Alarm Rate (FAR) were achieved.     

Prediction of minimum ignition energy of aerosols using flame kernel modeling combined with flame front propagation theory

Flammable aerosols have created many fire and explosion hazards in the process industry, but the flammability of aerosols has not been fully understood. The minimum ignition energy has been widely used as an indicator for flammability of combustible mixtures, but the amount of experimental data on the minimum ignition energy of aerosols is very limited. In this work, the minimum ignition energy of tetralin aerosols is predicted using an integrated model. The model applies the flame front propagation theory in aerosol systems to the growth of the flame kernel, which was created during the spark discharge in the ignition process. The aerosol minimum ignition energy was defined as the minimum level of energy in the initial flame kernel to maintain the kernel temperature above the minimum ignition temperature of 1073 K specific for tetralin aerosols during the kernel growth. The minimum ignition energy obtained in the model is influenced by the fuel-air equivalence ratio and the size of the aerosol droplets. For tetralin aerosols of 40 μm diameter, E_min decreases significantly from 0.32 mJ to 4.3 × 10 e⁻³ mJ when the equivalence ratio rises from 0.57 to 1.0. For tetralin aerosols of 0.57 equivalence ratio, E_min increases from as 0.09 mJ to 0.32 mJ when the droplet diameter rises from 10 μm to 60 μm. The trends are in agreement with previous experimental observations. The method used in current work has the potential to prediction of the minimum ignition energy of aerosol.     

突发性大气污染事件数字化动态应急预案系统及其应用

针对近些年频繁发生的突发性大气污染事件,构建了数字化动态应急预案系统。该系统由基础信息数据库、气象环境模式与健康风险评估系统、数字化动态应急预案三部分组成,并利用地理信息系统将三者有机结合,将事故基本信息、事故发展预测及救援状况直观、动态地展现在系统界面,使应急行动得以及时、高效地展开。实地外场综合应急演习证明,该系统技术路线稳定畅通,运行高效,功能强大,具有较好的可行性和实效性。     

Electrocoagulation process for the treatment of metal-plating wastewater: Kinetic modeling and energy consumption

The wastewater from industrial area was treated by EC via Fe and Al electrodes. Cu, Ni, Cr and Zn were highly removed at the first minutes, simultaneously. Pseudo-2nd-order was found to be more suitable for kinetics. Adsorption capacities based on kinetic modeling were observed as Cr>Cu>Ni>Zn. The chemical cost in the case of pH adjustment after EC was less as 3.83 $/m³. It is known that wastewater produced by the metal-plating industry contains several heavy metals, which are acidic in nature and therefore toxic for the environment and for living creatures. In particular, heavy metals enter the food chain and accumulate in vital organs and cause serious illness. The precipitation of these metals is mostly achieved by pH adjustment, but as an alternative to this method, the electrocoagulation process has investigated in this study using iron and aluminum electrodes. The effects of the pH adjustment on removal before and after the electrocoagulation process were investigated, and cost analyses were also compared. It was observed that a high proportion of removal was obtained during the first minutes of the electrocoagulation process; thus, the current density did not have a great effect. In addition, the pH adjustment after the electrocoagulation process using iron electrodes, which are 10% more effective than aluminum electrodes, was found to be much more efficient than before the electrocoagulation process. In the process where kinetic modeling was applied, it was observed that the heavy metal removal mechanism was not solely due to the collapse of heavy metals at high pH values, and with this modeling, it was seen that this mechanism involved adsorption by iron and aluminum hydroxides formed during the electrocoagulation process. When comparing the ability of heavy metals to be adsorbed, the sequence was observed to be Cr>Cu>Ni>Zn, respectively.     

Improving inferences about private land conservation by accounting for incomplete reporting

Private lands provide key habitat for imperiled species and are core components of function protectected area networks; yet, their incorporation into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid conflict and clarify trade-offs between ecological benefits and sociopolitical costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete, which complicates these assessments. We used a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We compared multiple formulations of occupancy models with a logistic regression model to predict the locations of conservation easements based on a spatially explicit social–ecological systems framework. We combined a simulation experiment with a case study of easement data in Idaho and Montana (United States) to illustrate the utility of the occupancy framework for modeling conservation on private land. Occupancy models that explicitly accounted for variation in reporting produced estimates of predictors that were substantially less biased than estimates produced by logistic regression under all simulated conditions. Occupancy models produced estimates for the 6 predictors we evaluated in our case study that were larger in magnitude, but less certain than those produced by logistic regression. These results suggest that occupancy models result in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression and highlight the importance of integrating variable and incomplete reporting of participation in empirical analysis of conservation initiatives. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting.     

综合拉底、扩漏和出矿全过程的底部结构安全性颗粒流模拟技术研究

为探明自然崩落法从拉底崩落至出矿全过程中底部结构节理连续扩展过程与破坏过程规律，采用PFC2D软件，结合RocLab软件反演节理岩体参数，建立229 m×129 m的岩体扩大模型，对拉底崩落至出矿过程进行连续综合计算。研究结果表明:模拟结果及破坏现象与现场监测结果相近，建模与细观参数反演方法适用于该类岩体工程研究；裂纹扩展贯通导致岩体失稳破坏，破坏过程与裂纹扩展具有相对应的阶段特征，裂纹扩展分为崩落前稳定扩展期，崩落与聚矿槽开挖过程加速扩展期和后续持续扩展期；结构破坏分为蕴育过程，扰动失稳过程和宏观破坏过程；较大范围的宏观破坏主要在出矿阶段。该模拟方法与结果可为底部结构维护以及节理岩体长期稳定性研究提供参考。     

Investigating cumulative effects across ecological scales

Species, habitats, and ecosystems are increasingly exposed to multiple anthropogenic stressors, fueling a rapidly expanding research program to understand the cumulative impacts of these environmental modifications. Since the 1970s, a growing set of methods has been developed through two parallel, sometimes connected, streams of research within the applied and academic realms to assess cumulative effects. Past reviews of cumulative effects assessment (CEA) methods focused on approaches used by practitioners. Academic research has developed several distinct and novel approaches to conducting CEA. Understanding the suite of methods that exist will help practitioners and academics better address various ecological foci (physiological responses, population impacts, ecosystem impacts) and ecological complexities (synergistic effects, impacts across space and time). We reviewed 6 categories of methods (experimental, meta-analysis, single-species modeling, mapping, qualitative modeling, and multispecies modeling) and examined the ability of those methods to address different levels of complexity. We focused on research gaps and emerging priorities. We found that no single method assessed impacts across the 4 ecological foci and 6 ecological complexities considered. We propose that methods can be used in combination to improve understanding such that multimodel inference can provide a suite of comparable outputs, mapping methods can help prioritize localized models or experimental gaps, and future experiments can be paired from the outset with models they will inform.     

Investigation of pool spreading and vaporization behavior in medium-scale LNG tests

A failure of a Liquefied Natural Gas (LNG) tanker can occur due to collision or rupture in loading/unloading lines resulting in spillage of LNG on water. Upon release, a spreading liquid can form a pool with rapid vaporization leading to the formation of a flammable vapor cloud. Safety analysis for the protection of public and property involves the determination of consequences of such accidental releases. To address this complex pool spreading and vaporization phenomenon of LNG, an investigation is performed based on the experimental tests that were conducted by the Mary Kay O'Connor Process Safety Center (MKOPSC) in 2007. The 2007 tests are a part of medium-scale experiments carried out at the Brayton Fire Training Field (BFTF), College Station. The dataset represents a semi-continuous spill on water, where LNG is released on a confined area of water for a specified duration of time. The pool spreading and vaporization behavior are validated using empirical models, which involved determination of pool spreading parameters and vaporization rates with respect to time. Knowledge of the pool diameter, pool height and spreading rate are found to be important in calculating the vaporization rates of the liquid pool. The paper also presents a method to determine the vaporization mass flux of LNG using water temperature data that is recorded in the experiment. The vaporization rates are observed to be high initially and tend to decrease once the pool stopped spreading. The results of the analysis indicated that a vaporization mass flux that is varying with time is required for accurate determination of the vaporization rate. Based on the data analysis, sources of uncertainties in the experimental data were identified to arise from ice formation and vapor blocking.