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Editorial

ASME J. Risk Uncertainty Part B. 2017;4(2):020201-020201-2. doi:10.1115/1.4038592.
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Topics: Risk
Commentary by Dr. Valentin Fuster

Research Papers

ASME J. Risk Uncertainty Part B. 2017;4(2):021001-021001-4. doi:10.1115/1.4037866.

This paper explores an infrequently encountered hazard associated with liquid fuel tanks on gasoline-powered equipment using unvented fuel tanks. Depending on the location of fuel reserve tanks, waste heat from the engine or other vehicle systems can warm the fuel during operation. In the event that the fuel tank is not vented and if the fuel is sufficiently heated, the liquid fuel may become superheated and pose a splash hazard if the fuel cap is suddenly removed. Accident reports often describe the ejection of liquid as a geyser. This geyser is a transient, two-phase flow of flashing liquid. This could create a fire hazard and result in splashing flammable liquid onto any bystanders. Many existing fuel tank systems are vented to ambient through a vented tank cap. It has been empirically determined that the hazard can be prevented by limiting fuel tank gauge pressure to 10 kPa (1.5 psi). However, if the cap does not vent at an adequate rate, pressure in the tank can rise and the fuel can become superheated. This phenomenon is explored here to facilitate a better understanding of how the hazard is created. The nature of the hazard is explained using thermodynamic concepts. The differences in behavior between a closed system and an open system are discussed and illustrated through experimental results obtained from two sources: experiments with externally heated fuel containers and operation of a gasoline-powered riding lawn mower. The role of the vented fuel cap in preventing the geyser phenomenon is demonstrated.

Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(2):021002-021002-12. doi:10.1115/1.4037122.

Loosely interconnected cooperative systems such as cable robots are particularly susceptible to uncertainty. Such uncertainty is exacerbated by addition of the base mobility to realize reconfigurability within the system. However, it also sets the ground for predictive base reconfiguration in order to reduce the uncertainty level in system response. To this end, in this paper, we systematically quantify the output wrench uncertainty based on which a base reconfiguration scheme is proposed to reduce the uncertainty level for a given task (uncertainty manipulation). Variations in the tension and orientation of the cables are considered as the primary sources of the uncertainty responsible for nondeterministic wrench output on the platform. For nonoptimal designs/configurations, this may require complex control structures or lead to system instability. The force vector corresponding to each agent (e.g., pulley and cable) is modeled as random vector whose magnitude and orientation are modeled as random variables with Gaussian and von Mises distributions, respectively. In a probabilistic framework, we develop the closed-form expressions of the means and variances of the output force and moment given the current state (tension and orientation of the cables) of the system. This is intended to enable the designer to efficiently characterize an optimal configuration (location) of the bases in order to reduce the overall wrench fluctuations for a specific task. Numerical simulations as well as real experiments with multiple iRobots are performed to demonstrate the effectiveness of the proposed approach.

Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(2):021003-021003-11. doi:10.1115/1.4037519.

The paper treats the important problem related to risk controlled by the simultaneous presence of critical events, randomly appearing on a time interval and shows that the expected time fraction of simultaneously present events does not depend on the distribution of events durations. In addition, the paper shows that the probability of simultaneous presence of critical events is practically insensitive to the distribution of the events durations. These counter-intuitive results provide the powerful opportunity to evaluate the risk of overlapping of random events through the mean duration times of the events only, without requiring the distributions of the events durations or their variance. A closed-form expression for the expected fraction of unsatisfied demand for random demands following a homogeneous Poisson process in a time interval is introduced for the first time. In addition, a closed-form expression related to the expected time fraction of unsatisfied demand, for a fixed number of consumers initiating random demands with a specified probability, is also introduced for the first time. The concepts stochastic separation of random events based on the probability of overlapping and the average overlapped fraction are also introduced. Methods for providing stochastic separation and optimal stochastic separation achieving balance between risk and cost of risk reduction are presented.

Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(2):021004-021004-7. doi:10.1115/1.4037219.

In this study, stochastic analysis is aimed for space structures (satellite in low earth orbit, made of aluminum 2024-T3), with the focus on fatigue failure. Primarily, the deterministic fatigue simulation is conducted using Walker and Forman models with constant amplitude loading. Deterministic crack growth was numerically simulated by the authors developed algorithm and is compared with commercial software for accuracy verification as well as validation with the experimental data. For the stochastic fatigue analysis of this study, uncertainty is estimated by using the Monte Carlo simulation. It is observed that by increasing the crack length, the standard deviation (the measure of uncertainty) increases. Also, it is noted that the reduction in stress ratio has the similar effect. Then, stochastic crack growth model, proposed by Yang and Manning, is employed for the reliability analysis. This model converts the existing deterministic fatigue models to stochastic one by adding a random coefficient. Applicability of this stochastic model completely depends on accuracy of base deterministic function. In this study, existing deterministic functions (power and second polynomial) are reviewed, and three new functions, (i) fractional, (ii) global, and (iii) exponential, are proposed. It is shown that the proposed functions are potentially used in the Yang and Manning model for better results.

Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(2):021005-021005-8. doi:10.1115/1.4037328.

An abnormal operating effect can be caused by different faults, and a fault can cause different abnormal effects. An information fusion model, with hybrid-type fusion frame, is built in this paper, so as to solve this problem. This model consists of data layer, feature layer and decision layer, based on an improved Dempster–Shafer (D-S) evidence algorithm. After the data preprocessing based on event reasoning in data layer and feature layer, the information will be fused based on the new algorithm in decision layer. Application of this information fusion model in fault diagnosis is beneficial in two aspects, diagnostic applicability and diagnostic accuracy. Additionally, this model can overcome the uncertainty of information and equipment to increase diagnostic accuracy. Two case studies are implemented by this information fusion model to evaluate it. In the first case, fault probabilities calculated by different methods are adopted as inputs to diagnose a fault, which is quite different to be detected based on the information from a single analytical system. The second case is about sensor fault diagnosis. Fault signals are planted into the measured parameters for the diagnostic system, to test the ability to consider the uncertainty of measured parameters. The case study result shows that the model can identify the fault more effectively and accurately. Meanwhile, it has good expansibility, which may be used in more fields.

Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(2):021006-021006-12. doi:10.1115/1.4037353.

Vibration induced fatigue (VIF) failure of topside piping is one of the most common causes of the hydrocarbon release on offshore oil and gas platforms operating in the North Sea region. An effective inspection plan for the identification of fatigue critical piping locations has the potential to minimize the hydrocarbon release. One of the primary challenges in preparation of inspection program for offshore piping is to identify the fatigue critical piping locations. At present, the three-staged risk assessment process (RAP) given in the Energy Institute (EI) guidelines is used by inspection engineers to determine the likelihood of failure (LoF) of process piping due to VIF. Since the RAP is afflicted by certain drawbacks, this paper presents an alternative risk assessment approach (RAA) to RAP for identification and prioritization of fatigue critical piping locations. The proposed RAA consists of two stages. The first stage involves a qualitative risk assessment using fuzzy-analytical hierarchy process (FAHP) methodology to identify fatigue critical systems (and the most dominant excitation mechanism) and is briefly discussed in the paper. The fatigue critical system identified during stage 1 of RAA undergoes further assessment in the second stage of the RAA. This stage employs a fuzzy-logic method to determine the LoF of the mainline piping. The outcome of the proposed RAA is the categorization of mainline piping, into high, medium, or low risk grouping. The mainline piping in the high-risk category is thereby prioritized for inspection. An illustrative case study demonstrating the usability of the proposed RAA is presented.

Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(2):021007-021007-10. doi:10.1115/1.4037647.

This study focuses on the effect of skull fracture on the load transfer to the head for low-velocity frontal impact of the head against a rigid wall or being impacted by a heavy projectile. The skull was modeled as a cortical–trabecular–cortical-layered structure in order to better capture the skull deformation and consequent failure. The skull components were modeled with an elastoplastic with failure material model. Different methods were explored to model the material response after failure, such as eroding element technique, conversion to fluid, and conversion to smoothed particle hydrodynamic (SPH) particles. The load transfer to the head was observed to decrease with skull fracture.

Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(2):021008-021008-15. doi:10.1115/1.4037485.

In the early development phase of complex technical systems, uncertainties caused by unknown design restrictions must be considered. In order to avoid premature design decisions, sets of good designs, i.e., designs which satisfy all design goals, are sought rather than one optimal design that may later turn out to be infeasible. A set of good designs is called a solution space and serves as target region for design variables, including those that quantify properties of components or subsystems. Often, the solution space is approximated, e.g., to enable independent development work. Algorithms that approximate the solution space as high-dimensional boxes are available, in which edges represent permissible intervals for single design variables. The box size is maximized to provide large target regions and facilitate design work. As a result of geometrical mismatch, however, boxes typically capture only a small portion of the complete solution space. To reduce this loss of solution space while still enabling independent development work, this paper presents a new approach that optimizes a set of permissible two-dimensional (2D) regions for pairs of design variables, so-called 2D-spaces. Each 2D-space is confined by polygons. The Cartesian product of all 2D-spaces forms a solution space for all design variables. An optimization problem is formulated that maximizes the size of the solution space, and is solved using an interior-point algorithm. The approach is applicable to arbitrary systems with performance measures that can be expressed or approximated as linear functions of their design variables. Its effectiveness is demonstrated in a chassis design problem.

Topics: Space , Design , Optimization
Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(2):021009-021009-8. doi:10.1115/1.4037970.

The probabilistic stress-number of cycles curve (P-S-N curve) approach is widely accepted for describing the fatigue strengths of materials. It is also a widely accepted fatigue theory for determining the reliability of a component under fatigue loadings. However, it is an unsolved issue in the P-S-N curve approach that the calculation of reliability of a component under several distributed cyclic numbers at the corresponding constant cyclic stress levels. Based on the commonly accepted concept of the equivalent fatigue damage, this paper proposes a new method to determine the reliability of the component under several distributed cyclic numbers at the corresponding constant cyclic stress levels. Four examples including two validation examples will be provided to demonstrate how to implement the proposed method for reliability calculation under such fatigue cyclic loading spectrum. The relative errors in validation examples are very small. So, the proposed method can be used to evaluate the reliability of a component under several distributed cyclic number at different stress levels.

Commentary by Dr. Valentin Fuster
Select Articles from Part A: Civil Engineering

Technical Papers

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2017;3(4):. doi:10.1061/AJRUA6.0000917.
Abstract 

Abstract  Stochastic descriptions and simulations of oceanographic variables are essential for coastal and marine engineering applications. In the past decade, copula-based approaches have become increasingly popular for estimating the multivariate distribution of some variables at the peak of a storm along with its duration. The modeling of the storm shape, which contributes to its impact, is often simplified. This article proposes a vine-copula approach to characterize hourly significant wave heights and corresponding mean zero-crossing periods as a random process in time. The model is applied to a data set in the North Sea, and time series with the duration of an oceanographic winter are simulated. The synthetic wave scenarios emulate storms as well as daily conditions. The results are useful, for example, as input for coastal risk analyses and for planning offshore operations. Nonetheless, selecting a vine structure, finding appropriate copula families, and estimating parameters is not straightforward. The validity of the model, as well as the conclusions that can be drawn from it, are sensitive to these choices. A valuable byproduct of the proposed vine-copula approach is the bivariate distribution of significant wave heights and corresponding mean zero-crossing periods at the given location. Its dependence structure is approximated by the flexible skew-t copula family and preserves the limiting wave steepness condition.

Topics:
Time series , North Sea , Significant wave heights

Special Collection Announcement

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2017;3(4):. doi:10.1061/AJRUA6.0000921.
Abstract
Topics:
Monte Carlo methods

Technical Papers

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2017;3(4):. doi:10.1061/AJRUA6.0000919.
Abstract 

Abstract  The economic input-output interdependency model is a quick decision tool for stakeholders of critical infrastructure to understand the economic impact of a disruptive event. To demonstrate its applications, two real case studies (Pulau Bukom refinery fire in Singapore in 2011 and Tohoku earthquake in Japan in 2011) are presented in the paper. The paper will describe how the model is used to compute the effects on other economic sectors. It also seeks to compare and analyze the computed cascading effects. Understanding the severity and extent of the disruptive event is very important and the input-output interdependency model serves as a quick and cost-effective decision deployment tool for use by relevant stakeholders.

Topics:
Fire , Earthquakes
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2017;3(4):. doi:10.1061/AJRUA6.0000929.
Abstract 

Abstract  Resilience, described in this work as a function of vulnerability and recoverability dimensions, is an increasingly important concept in preparing for and responding to disruptions in many kinds of cyber-physical-social systems, including networks. This paper focuses on the vulnerability dimension of resilience, proposing (1) a bi-objective optimization formulation to devise defense strategies across a range of diverse attack scenarios, and (2) a three-step solution approach of approximating Pareto-optimal defense strategies for each attack scenario and aggregating characteristics of strategies across attacks to identify a robust defense strategy. An example network illustrates the formulation and solution approach, identifying contributions to enhance network resilience analytics.

Topics:
Dimensions , Optimization , Defense industry , Resilience
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2017;3(4):. doi:10.1061/AJRUA6.0000914.
Abstract 

Abstract  In this paper two methodologies are investigated that contribute to better assessment of risks related to extreme rainfall events. Firstly, one-parameter bivariate copulas are used to analyze rain gauge data in the Netherlands. Out of three models considered, the Gumbel copula, which indicates upper tail dependence, represents the data most accurately for all 33 stations in the Netherlands. Seasonal variability is noticeable, with rank correlation reaching maximum in winter and minimum in summer as well as other temporal and spatial patterns. Secondly, an expert judgment elicitation was undertaken. The experts’ opinions were combined using Cooke’s classical method in order to obtain estimates of future changes in precipitation patterns. Experts predicted mostly an approximate 10% increase in rain amount, duration, intensity and the dependence between amount and duration. The results were in line with official national climate change scenarios, based on numerical modelling. Applicability of both methods was presented based on an example of an existing tunnel in the Netherlands, contributing to better estimates of the tunnel’s limit state function and therefore the probability of failure.

Topics:
Precipitation , Risk assessment

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