锰铬不锈钢在化工应用中的风险及对策

对聚丙烯二装置丙烯球罐液位计不锈钢螺栓失效的原因进行了分析,结合锰铬不锈钢(200系列)的性能和国内市场上的现状,分析了锰铬不锈钢在化工生产中应用的风险,提出了应对方法。     

A Bayesian approach to the multivariate Behrens-Fisher problem under the assumption of proportional covariance matrices

Summary Two independent random samples of sizesN ₁ andN ₂ from multivariate normal populationsN _p (θ₁,∑₁) andN _p (θ₂,∑₂) are considered. Under the null hypothesisH ₀: θ₁=θ₂, a single θ is generated from aN _p(μ, Σ) prior distribution, while underH ₁: θ₁≠θ₂ two means are generated from the exchangeable priorN _p(μ,σ). In both cases Σ will be assumed to have a vague prior distribution. For a simple covariance structure, the Bayes factorB and minimum Bayes factor in favour of the null hypotheses is derived. The Bayes risk for each hypothesis is derived and a strategy is discussed for using the Bayes factor and Bayes risks to test the hypothesis.     

Hydrocarbon exploration risk evaluation through uncertainty and sensitivity analyses techniques

The evaluation of the exploration risk in the oil industry is a fundamental component of the decision process related to the exploratory phase. In this paper the two basic components of the exploratory risk: trap geometry and trapped hydrocarbon quantities (fluid), are compounded in a single coherent uncertainty and sensitivity approach. The results clarify that the model geometry influences each Petroleum System Modeling step and that the geometric uncertainty is correlated with the fluid uncertainty. The geometric uncertainty evaluation makes use of geostatistical techniques that produce a number of possible realizations of the trap geometry, all compatible with available data. The evaluation of the fluid uncertainty, through a Monte Carlo methodology, allows us to compute the possible quantities of oil and gas, generated in a basin and migrated from the hydrocarbon source location to each single trap. The final result is the probability distribution of oil and gas for each trap in the basin, together with other useful indicators like: the hydrocarbon filling probability map, the closure probability map, the drainage area probability map, the spilling paths probabilities, the trap-filling scenarios.     

A coordinated reverse logistics system for regional management of multi-source hazardous wastes

This paper presents a coordinated reverse logistics (CRL) management system for the treatment of multi-source hazardous wastes in a given region, in this case, a specific high-technology manufacturing zone. A linear multi-objective analytical model is formulated that systematically minimizes both the total reverse logistics operating costs and corresponding risks. In addition to inter-organizational logistics operating factors, environmental concerns are considered and formulated as corresponding risk-related constraints. Using the proposed model, results of numerical studies indicate that when the aspect of risk-induced penalties is not considered, the operational costs of regional hazardous-waste management can be efficiently reduced by 58%, compared to the existing operational costs at the study site. In addition, it is also observed that the corresponding weight associated with the risk-induced objective function embedded in the proposed model seems to have a significant effect on the CRL costs.     

A study of the effects of the location of flashing inception on maximum and minimum critical two-phase flow rates:: Part II: analysis and modelling

A general unified model is developed to predict one-component critical two-phase pipe flow. An extension of the Henry [Henry, R.E., 1970. The Two-Phase Critical Discharge of Initially Saturated or Subcooled Liquid. Nucl. Sci. Eng. 41, 336-342.] and Henry and Fauske [Henry, R.E., Fauske, H.K., 1970. The two-Phase critical Flow of One-Component Mixtures in Nozzles; Orifices and Short Tubes, ASME J. Heat Transfer, May 1970.] models to incorporate the effects of wall friction and the location of flashing inception is proposed. Modelling of the two-phase flow is accomplished by describing the evolution of the flow between the location of flashing inception and the exit (critical) plane. The model approximates the nonequilibrium phase change process via thermodynamic equilibrium paths. Included are the relative effects of varying the location of flashing inception, pipe geometry, fluid properties and length to diameter ratio. The model predicts that a range of critical mass fluxes exist and is bound by a maximum and minimum value for a given thermodynamic state. This range is more pronounced at lower subcooled stagnation states and can be attributed to the variation in the location of flashing inception. The model is based on the experimental study of critical two-phase flow rates of saturated and subcooled water through long tubes given in Part I of this work. In that study, the location of flashing inception was accurately controlled and adjusted through the use of a new device. The data obtained revealed that for fixed stagnation conditions, the maximum critical mass fluxes occurred with flashing inception located near the pipe exit; while minimum critical mass fluxes occurred with the flashing front located further upstream. The results of the present study, as well as available data since 1970 are compared with the model predictions. These data cover a wide range of conditions and include test section L/D ratios from 25 to 302 and a temperature and pressure range of 110-280°C and 0.16-6.9 Mpa, respectively. The predicted maximum and minimum critical mass fluxes show an excellent agreement with the range observed in the experimental data.     

Hybrid Approach for Addressing Uncertainty in Risk Assessments

Parameter uncertainty is a major aspect of the model-based estimation of the risk of human exposure to pollutants. The Monte Carlo method, which applies probability theory to address model parameter uncertainty, relies on a statistical representation of available information. In recent years, other uncertainty theories have been proposed as alternative approaches to address model parameter uncertainty in situations where available information is insufficient to identify statistically representative probability distributions, due in particular to data scarcity. The simplest such theory is possibility theory, which uses so-called fuzzy numbers to represent model parameter uncertainty. In practice, it may occur that certain model parameters can be reasonably represented by probability distributions, because there are sufficient data available to substantiate such distributions by statistical analysis, while others are better represented by fuzzy numbers (due to data scarcity). The question then arises as to how these two modes of representation of model parameter uncertainty can be combined for the purpose of estimating the risk of exposure. This paper proposes an approach (termed a hybrid approach) which combines Monte Carlo random sampling of probability distribution functions with fuzzy calculus. The approach is applied to a real case of estimation of human exposure, via vegetable consumption, to cadmium present in the surficial soils of an industrial site located in the north of France. The application illustrates the potential of the proposed approach, which allows the uncertainty affecting model parameters to be represented in a way that is consistent with the information at hand. Also, because the hybrid approach takes advantage of the “rich” information provided by probability distributions, while retaining the conservative character of fuzzy calculus, it is believed to hold value in terms of a “reasonable” application of the precautionary principle.     

Safe and effective navigation of autonomous robots in hazardous environments

The development of autonomous mobile machines to perform useful tasks in real work environments is currently being impeded by concerns over effectiveness, commercial viability and, above all, safety. This paper introduces a case study of a robotic excavator to explore a series of issues around system development, navigation in unstructured environments, autonomous decision making and changing the behaviour of autonomous machines to suit the prevailing demands of users. The adoption of the Real-Time Control Systems (RCS) architecture (Albus, 1991) is proposed as a universal framework for the development of intelligent systems. In addition it is explained how the use of Partially Observable Markov Decision Processes (POMDP) (Kaelbling et al., 1998) can form the basis of decision making in the face of uncertainty and how the technique can be effectively incorporated into the RCS architecture. Particular emphasis is placed on ensuring that the resulting behaviour is both task effective and adequately safe, and it is recognised that these two objectives may be in opposition and that the desired relative balance between them may change. The concept of an autonomous system having “values” is introduced through the use of utility theory. Limited simulation results of experiments are reported which demonstrate that these techniques can create intelligent systems capable of modifying their behaviour to exhibit either ‘safety conscious’ or ‘task achieving’ personalities.     

Assessment of Highway Bridge Upgrading by Dynamic Testing and Finite-Element Model Updating

The Land Transport Authority of Singapore has a continuing program of highway bridge upgrading for refurbishing and strengthening bridges to allow for increasing vehicle traffic and increasing axle loads. One subject of this program has been a short-span bridge taking a busy main road across a coastal inlet near a major port facility. Experiment-based structural assessments of the bridge were conducted before and after upgrading works including strengthening. Each assessment exercise comprised three separate components: (1) a strain and acceleration monitoring exercise lasting approximately one month; (2) a full-scale dynamic test carried out in a single day without closing the bridge; and (3) a finite-element model updating exercise to identify structural parameters and mechanisms. This paper presents the dynamic testing and the modal analysis used to identify the vibration properties and the quantification of the effectiveness of the upgrading through the subsequent model updating. Before and after upgrade, similar sets of vibration modes were identified, resembling those of an orthotropic plate with relatively weak transverse bending stiffness. Conversion of bearings from nominal simple supports to nominal full fixity was shown via model updating to be the principal cause of natural frequency increases of up to 50%. The utility of the combined experimental and analytical process in direct identification of structural properties has been proven, and the procedure can be applied to other structures and their capacity assessments.     

Economic Model to Optimize Underground Utility Protection

The need for better protecting our vital infrastructure from being damaged or destroyed has received increased attention since the terrorist attacks on September 11, 2001. The tragedy of having thousands of innocent people die before the eyes of an entire nation awakened people to the reality of “managed” attacks of unthinkable magnitudes. However, tragedies of a smaller scale are a daily occurrence but accepted as “collateral damage” of work in an unsafe environment. This paper presents a cost-benefit analysis to address the question of how much money should be spent in protecting underground utilities from damage. During the study of an actual incident it was found that the total costs of such accidents are vastly underreported because only costs for emergency responses and repair are tallied up. This paper makes the case that a comprehensive approach for assessing the total economic impact of such incidents on the public, business, and government is the critical stepping stone to a mathematical optimization of expenditure for damage prevention. In addition, the reader will quickly realize that the use of the presented optimization model provides theoretical underpinning for the engineering profession in its effort to better protect our critical infrastructure from terrorist attacks.     

Uncertainty of Predictions of Embankment Dam Breach Parameters

Risk assessment studies considering the failure of embankment dams often require the prediction of basic geometric and temporal parameters of a breach, or the estimation of peak breach outflows. Many of the relations most commonly used to make these predictions were developed from statistical analyses of data collected from historic dam failures. The prediction uncertainties of these methods are widely recognized to be very large, but have never been specifically quantified. This paper presents an analysis of the uncertainty of many of these breach parameter and peak flow prediction methods. Application of the methods and the uncertainty analysis are illustrated through a case study of a risk assessment recently performed by the Bureau of Reclamation for a large embankment dam in North Dakota.