Multi-criteria decision-making considering risk and uncertainty in physical asset management

In this work we present a method for risk-informed decision-making in the physical asset management context whereby risk evaluation and cost-benefit analysis are considered in a common framework. The methodology uses quantitative risk measures to prioritize projects based on a combination of risk tolerance criteria, cost-benefit analysis and uncertainty reduction metrics. There is a need in the risk and asset management literature for a unified framework through which quantitative risk can be evaluated against tolerability criteria and trade-off decisions can be made between risk treatment options. The methodology uses quantitative risk measures for loss of life, loss of production and loss of property. A risk matrix is used to classify risk as intolerable, As Low As Reasonably Practicable (ALARP) or broadly tolerable. Risks in the intolerable and ALARP region require risk treatment, and risk treatment options are generated. Risk reduction benefit of the treatment options is quantified, and cost-benefit analysis is performed using discounted cashflow analysis. The Analytic Hierarchy Process is used to derive weights for prioritization criteria based on decision-maker preferences. The weights, along with prioritization criteria for risk reduction, tolerance criteria and project cost, are used to prioritize projects using the Technique for Order Preference by Similarity to Ideal Solution. The usefulness of the methodology for improved decision-making is illustrated using a numerical example.     

An LC-MS/MS method for creatine and creatinine analysis in paraquat-intoxicated patients

Abstract

A sudden increase in serum creatinine after paraquat intoxication has been reported in several clinical studies. However, this dramatic change of creatinine may be possibly due to an interconversion of creatine-creatinine in relation to paraquat toxicity. In order to investigate the creatine-creatinine relationship, a liquid chromatography tandem mass spectrometry in combination with electrospray ionization was developed and validated for simultaneous determination of creatine and creatinine in the serum. The chromatographic separation was achieved on a Gemini® C₆-Phenyl column with a gradient elution consisting of 0.1% formic acid in ultrapure water and methanol as the mobile phase. The method yielded suitable levels of specificity and selectivity, and calibration curves of creatine and creatinine in serum were linear over the concentration range of 0.5–200?µg mL^?1. The limit of quantification of both compounds was 0.5?µg mL^?1, and the method was accurate within the recovery range of 96.23–102.75%, indicating the robustness of the method. The method was successfully applied to toxicological samples from paraquat-intoxicated patients, and the concentrations of creatine and creatinine were quantified. High creatine concentrations in serum samples were observed which may lead to high serum creatinine despite normal kidney function as creatine is converted to creatinine in proportion to its concentration.     

A thermal hazard risk evaluation of emulsion polymerisation and vinyl acetate monomers in the latex manufacturing process

Latex is extensively used in industrial products. However, completing some processes at scale leads to unacceptable levels of risk that need to be quantified and mitigated. Systemic risks must be eliminated wherever possible, and safety takes priority over efficiency and quality. To assess the process risks accurately, four raw materials were examined in this study: polyvinyl acetate (PVA), latex process-initiator-ammonium persulfate (APS) and hydrogen peroxide (H₂O₂), and vinyl acetate monomer (VAM). The physicochemical composition of the PVA latex process was determined via calorimeters, including differential scanning calorimetry (DSC) and vent sizing package 2 (VSP2). The calorimetry results showed that the protective colloid was a critical component in the polymerisation reaction. In addition, when adding initiators to the system, it is vital to observe the normal ratio of materials and keep the stirring system operating. The scenario system also simulated the effects of shutting down various inhibitory programs, including the build-up of free radicals that could result in a runaway reaction when the initiator was added in excess. On the other hand, the result of the risk matrix displayed as a medium level, indicating that although the probability of an accident is low, the resulting severity is at disaster level. As a result, this study provides process safety engineers with a reliable frame of reference for assessing the potential dangers in the PVA latex manufacturing process.     

Prediction of vortex height from mechanical mixing in metal matrix nanocomposite processing by means of dimensional analysis and scaling

Mechanical mixing can be used for initial dispersion and distribution of nanoparticle agglomerates in metal matrix nanocomposite (MMNC) fabrication. As vortex height increases, flow is enhanced as well as the risk of oxidate melt contamination. The goal of this study was to examine and predict vortex height using dimensional analysis while varying fluid and the angular speed of a pitched square-blade impeller. An equation proposed by Markopoulos et al. was verified for the present experimental conditions. The relevant dimensionless numbers were the Reynolds (Re), Froude (Fr) and Galilei (Ga) numbers. A modified Fr was defined (Fr*) including the shaft and blade angles of the impeller. Experiments allowed calculation of the dimensionless numbers. Two fluids, water and 50 vol% aqueous glycerine, were used. Angular clockwise speed varied from 200 to 900 rpm in 100 rpm increments. Vortex height was measured in lateral view digital images. Correlations of the dimensionless numbers yielded, first, a linear relationship of the product of dimensionless vortex height (H) and specific gravity (ρ*) with respect to Fr*. A polynomial relationship was found between H and ReFr* for each fluid. The polynomial coefficients, in turn, follow a power law behavior with respect to Ga. This allows a prediction of vortex height in other Newtonian fluids that satisfy the single-phase isothermal flow condition. Perhaps, molten aluminum used in MMNC fabrication, can be analyzed based on a simple, room temperature, low cost transparent fluid system. For the experimental conditions in this study, the equation proposed by Markopoulos et al. was valid. The predicting methodology was verified with experimental results using 25 vol% aqueous glycerine, resulting in an absolute percent error of 5.29%, comparable and lower than an error of 9.12% obtained by predicting vortex height with Markopoulos’ equation.     

Population viability and harvest sustainability for Madagascar lemurs

Subsistence hunting presents a conservation challenge by which biodiversity preservation must be balanced with safeguarding of human livelihoods. Globally, subsistence hunting threatens primate populations, including Madagascar's endemic lemurs. We used population viability analysis to assess the sustainability of lemur hunting in Makira Natural Park, Madagascar. We identified trends in seasonal hunting of 11 Makira lemur species from household interview data, estimated local lemur densities in populations adjacent to focal villages via transect surveys, and quantified extinction vulnerability for these populations based on species-specific demographic parameters and empirically derived hunting rates. We compared stage-based Lefkovitch with periodic Leslie matrices to evaluate the impact of regional dispersal on persistence trajectories and explored the consequences of perturbations to the timing of peak hunting relative to the lemur birth pulse, under assumptions of density-dependent reproductive compensation. Lemur hunting peaked during the fruit-abundant wet season (March–June). Estimated local lemur densities were roughly inverse to body size across our study area. Life-history modeling indicated that hunting most severely threatened the species with the largest bodies (i.e., Hapalemur occidentalis, Avahi laniger, Daubentonia madagascariensis, and Indri indi), characterized by late-age reproductive onsets and long interbirth intervals. In model simulations, lemur dispersal within a regional metapopulation buffered extinction threats when a majority of local sites supported growth rates above the replacement level but drove regional extirpations when most local sites were overharvested. Hunt simulations were most detrimental when timed to overlap lemur births (a reality for D. madagascariensis and I. indri). In sum, Makira lemurs were overharvested. Regional extirpations, which may contribute to broad-scale extinctions, will be likely if current hunting rates persist. Cessation of anthropogenic lemur harvest is a conservation priority, and development programs are needed to help communities switch from wildlife consumption to domestic protein alternatives.     

建筑安全风险因素分级排序的风险矩阵法

为减少风险分级排序时产生的风险结,在引入施工安全事故频率的基础上,采用单元格细化和Borda序值法改进原有的风险矩阵法。改进后的方法使得风险等级数量增加,风险结数量减少。将该方法应用于脚手架工程的风险因素的分级与排序,风险等级分为6级,且实现了12个因素的明确排序。     

Before the crash: A systematic analysis of police narratives to determine the prevalence of pre-crash factors in fatality road transport crashes

Abstract

Objectives: The objectives of this study were to identify the prevalence of pre-crash factors that were present in fatal road transport crashes for the deceased and counterpart road user.

Methods: The study is a retrospective population-based case series study of transport-related deaths reported to coroners in Australia from 2013 to 2016. Data was extracted from the National Coronial Information System.

Results: In total, 6,137 fatality crashes occurred during the study period. Police reports were available for 5,523 crashes (89.9%). The most frequently reported pre-crash factors reported behaviour specifically drivers (e.g., driving without a license or while license was disqualified). Presence of intoxicating substances were also reported in the deceased and counterparts. Analyses of toxicology reports are continuing to determine if rates are comparable to level of use in community.

Conclusions: Coronial report provide detailed information that may be pertinent to understanding and potentially preventing crashes. Also emerging from the data is the extent of pre-crash factors that relate to illegal or deviant behavior and whether these are contextual or contributory factors.     

基于生态—经济协调发展的乡镇空间功能分区

按提供产品的类别,乡镇尺度空间由生态空间、农业空间和建设空间组成,这3部分空间共同承载着乡镇社会经济发展的重任。坚持生态保护对发展的约束与支撑功能并存的理念,建立以生态约束为前提,并与开发建设协同推进的分区指标体系、技术方法及应用模式,是生态文明战略下空间功能分区的有益探讨。以南京市六合区雄州街道为案例,借助Arc GIS空间分析工具,采用互斥性矩阵分类法,通过对生态约束、农业发展、工业发展与人居环境等建设开发适宜性的单项与综合评价的集成,构建生态、农业和建设空间布局的总体架构,实现了街镇空间功能的整合与科学定位;划分禁止建设区、限制建设区、适宜建设区和已建设区等四大类功能区,并提出各功能区的生态环境保护措施与产业发展导向,为实施区域发展与生态保护的协同推进提供了依据。     

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting

● MSWNet was proposed to classify municipal solid waste. ● Transfer learning could promote the performance of MSWNet. ● Cyclical learning rate was adopted to quickly tune hyperparameters. An intelligent and efficient methodology is needed owning to the continuous increase of global municipal solid waste (MSW). This is because the common methods of manual and semi-mechanical screenings not only consume large amount of manpower and material resources but also accelerate virus community transmission. As the categories of MSW are diverse considering their compositions, chemical reactions, and processing procedures, etc., resulting in low efficiencies in MSW sorting using the traditional methods. Deep machine learning can help MSW sorting becoming into a smarter and more efficient mode. This study for the first time applied MSWNet in MSW sorting, a ResNet-50 with transfer learning. The method of cyclical learning rate was taken to avoid blind finding, and tests were repeated until accidentally encountering a good value. Measures of visualization were also considered to make the MSWNet model more transparent and accountable. Results showed transfer learning enhanced the efficiency of training time (from 741 s to 598.5 s), and improved the accuracy of recognition performance (from 88.50% to 93.50%); MSWNet showed a better performance in MSW classsification in terms of sensitivity (93.50%), precision (93.40%), F1-score (93.40%), accuracy (93.50%) and AUC (92.00%). The findings of this study can be taken as a reference for building the model MSW classification by deep learning, quantifying a suitable learning rate, and changing the data from high dimensions to two dimensions.     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.