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IN THIS ISSUE

### Research Papers

ASME J. Risk Uncertainty Part B. 2017;4(2):021001-021001-4. doi:10.1115/1.4037866.
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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.
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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. 2016;3(3):. doi:10.1061/AJRUA6.0000899.
Abstract

Abstract  Traffic congestion is a serious challenge that urban transportation systems are facing. Variable speed limit (VSL) systems are one of the countermeasures to reduce traffic congestion and smooth traffic flow on roadways. The negative impacts of congestion, including road rage, air pollution, safety issues, and traffic delays, are well recognized. The impact of unexpected delays on road users is quantified through travel time reliability (TTR) measures. In this study, a bilevel optimization problem was introduced to determine location, speed limit reduction, start time, and duration of limited number of VSL signs while maximizing travel time reliability on selected critical paths on a network. The upper-level problem focuses on TTR optimization whereas the lower-level problem assigns traffic to the network using a dynamic traffic assignment simulation tool. A heuristic approach, simulated annealing, was used to solve the problem. The application of the methodology to a real roadway network is shown and results are discussed. The proposed methodology could assist traffic agencies in making proper decisions on how to allocate their limited resources to the network to maximize the benefits.

Topics:
Reliability , Simulation , Optimization
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2017;3(3):. doi:10.1061/AJRUA6.0000909.
Abstract

Topics:
Wind velocity , Climate change
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2017;3(3):. doi:10.1061/AJRUA6.0000904.
Abstract

Abstract  In some regions, sea level rise due to climate change is expected to increase saltwater intrusion in coastal aquifers, leading to increased salt levels in drinking water wells relying on these supplies. Seawater contains elevated concentrations of bromide, which has been shown to increase the formation and alter the speciation of disinfection by-products (DBPs) during the treatment process. DBPs have been associated with increased risk of cancer and negative reproductive outcomes, and they are regulated under drinking water standards to protect human health. This paper incorporates statistical simulation of changes in source water bromide concentrations as a result of potential increased saltwater intrusion to assess the associated impact on trihalomethane (THM) formation and speciation. Additionally, the health risk associated with these changes is determined using cancer slope factors and odds ratios. The analysis indicates that coastal utilities treating affected groundwater sources will likely meet regulatory levels for THMs, but even small changes in saltwater intrusion can have significant effects on finished water concentrations and may exceed desired health risk threshold levels due to the extent of bromination in the THM. As a result of climate change, drinking water utilities using coastal groundwater or estuaries should consider the implications of treating high bromide source waters. Additionally, extra consideration should be taken for surface water utilities considering mixing with groundwater sources, as elevated source water bromide could pose additional challenges for health risk, despite meeting regulatory requirements for THM.

Topics:
Public utilities , Groundwater , Shorelines , Climate change , Health risk assessment

### Corrections

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2017;3(3):. doi:10.1061/AJRUA6.0000907.

### Technical Papers

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2017;3(3):. doi:10.1061/AJRUA6.0000902.
Abstract

Abstract  The conventional simulation model used in the prediction of long-term infrastructure development systems such as public–private partnership (PPP)–build-operate-transfer (BOT) projects assumes single probabilistic values for all of the input variables. Traditionally, all the input risks and uncertainties in Monte Carlo simulation (MCS) are modeled based on probability theory. Its result is shown by a probability distribution function (PDF) and a cumulative distribution function (CDF), which are utilized for analyzing and decision making. In reality, however, some of the variables are estimated based on expert judgment and others are derived from historical data. Further, the parameters’ data of the probability distribution for the simulation model input are subject to change and difficult to predict. Therefore, a simulation model that is capable of handling both types of fuzzy and probabilistic input variables is needed and vital. Recently fuzzy randomness, which is an extension of classical probability theory, provides additional features and improvements for combining fuzzy and probabilistic data to overcome aforementioned shortcomings. Fuzzy randomness–Monte Carlo simulation (FR-MCS) technique is a hybrid simulation method used for risk and uncertainty evaluation. The proposed approach permits any type of risk and uncertainty in the input values to be explicitly defined prior to the analysis and decision making. It extends the practical use of the conventional MCS by providing the capability of choosing between fuzzy sets and probability distributions. This is done to quantify the input risks and uncertainties in a simulation. A new algorithm for generating fuzzy random variables is developed as part of the proposed FR-MCS technique based on the $α$-cut. FR-MCS output results are represented by fuzzy probability and the decision variables are modeled by fuzzy CDF. The FR-MCS technique is demonstrated in a PPP-BOT case study. The FR-MCS results are compared with those obtained from conventional MCS. It is shown that the FR-MCS technique facilitates decision making for both the public and private sectors’ decision makers involved in PPP-BOT projects. This is done by determining a negotiation bound for negotiable concession items (NCIs) instead of precise values as are used in conventional MCS results. This approach prevents prolonged and costly negotiations in the development phase of PPP-BOT projects by providing more flexibility for decision makers. Both parties could take advantage of this technique at the negotiation table.

Topics:
Simulation , Chaos