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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
ASME J. Risk Uncertainty Part B. 2018;4(2):021010-021010-9. doi:10.1115/1.4039016.

The early detection of a kick and mitigation with appropriate well control actions can minimize the risk of a blowout. This paper proposes a downhole monitoring system, and presents a dynamic numerical simulation of a compressible two-phase flow to study the kick dynamics at downhole during drilling operation. This approach enables early kick detection and could lead to the development of potential blowout prevention strategies. A pressure cell that mimics a scaled-down version of a downhole is used to study the dynamics of a compressible two-phase flow. The setup is simulated under boundary conditions that resemble realistic scenarios; special attention is given to the transient period after injecting the influx. The main parameters studied include pressure gradient, raising speed of a gas kick, and volumetric behavior of the gas kick with respect to time. Simulation results exhibit a sudden increase of pressure while the kick enters and volumetric expansion of gas as it flows upward. This improved understanding helps to develop effective well control and blowout prevention strategies. This study confirms the feasibility and usability of an intelligent drill pipe as a tool to monitor well conditions and develop blowout risk management strategies.

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;4(1):. doi:10.1061/AJRUA6.0000936.
Abstract 

Abstract  This paper presents a methodology for analyzing wind pressure data on cladding and components of low-rise buildings. The aerodynamic force acting on a specified area is obtained by summing up pressure time series measured at that area’s pressure taps times their respective tributary areas. This operation is carried out for all sums of tributary areas that make up rectangles with aspect ratios not exceeding four. The peak of the resulting area-averaged time series is extrapolated to a realistic storm duration by the translation method. The envelope of peaks over all wind directions is compared with current specifications. Results for one low-rise building for one terrain condition indicate that these specifications can seriously underestimate pressures on gable roofs and walls. Comparison of the proposed methodology with an alternative method for assignment of tributary areas and area averaging is shown as well.

Topics:
Structures , Wind pressure , Cladding systems (Building)
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2017;4(1):. doi:10.1061/AJRUA6.0000938.
Abstract 

Abstract  Risk identification is adversely affected by the still existing definitional and applicational discrepancy regarding risks and other related notions, such as hazards and impacts. A paradigm shift is beginning to be in effect, proposing the preliminary identification of risk sources to ameliorate the aforementioned adversities. However, apart from identifying risk sources from the outset, the bulk of the already conducted project risk-related research, from which risk sources could be derived, is still not free of discrepancies and is falling short of use. In this paper, a new linguistic clustering algorithm, using the k-means++ procedure in addition to the semantics tools of stop world removal and word stemming is developed and codified. Then, the algorithm is applied on a vast risk notions set, emanated from an exhaustive review of the relative literature. The clustered and semantically processed results of the application are then used for the deduction of risk sources. Thus, this paper provides a compact, general, and encompassing master set of risk sources, discretized among distinct overhead categories.

Topics:
Algorithms , Semantics , Risk , Hazards

Case Studies

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2017;4(1):. doi:10.1061/AJRUA6.0000935.
Abstract 

Abstract  This study investigates the availability-based reliability-centered maintenance scheduling of domestic (building-integrated) hot water (DHW) of HVAC systems. The keeping system availability (KSA) method is adopted, which provides maintenance scheduling by incorporating the effect of the maintenance activities. This method has been developed for maintenance scheduling in power plants in which the continual ability to generate power is a critical issue. This approach is applied to the case of the DHW system of HVACs, which is also a critical system in provision of hot water in buildings during the long cold seasons in Canada. The mean time to failure (MTTF) and mean time to repair (MTTR) are used to measure the availability of the DHW system. Components with different maintenance timings are sorted according to the effect of maintenance on availability of the system. At the end, a combination of maintenance schedules for the components of the DHW system is provided to ensure its availability while avoiding overmaintenance.

Topics:
Maintenance , Reliability , Hot water

Technical Papers

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2018;4(1):. doi:10.1061/AJRUA6.0000949.
Abstract 

Abstract  This study investigates the use of big data analytics in uncertainty quantification and applies the proposed framework to structural diagnosis and prognosis. With smart sensor technology making progress and low-cost online monitoring becoming increasingly possible, large quantities of data can be acquired during monitoring, thus exceeding the capacity of traditional data analytics techniques. The authors explore a software application technique to parallelize data analytics and efficiently handle the high volume, velocity, and variety of sensor data. Next, both forward and inverse problems in uncertainty quantification are investigated with this efficient computational approach. The authors use Bayesian methods for the inverse problem of diagnosis and parallelize numerical integration techniques such as Markov-chain Monte Carlo simulation and particle filter. To predict damage growth and the structure’s remaining useful life (forward problem), Monte Carlo simulation is used to propagate the uncertainties (both aleatory and epistemic) to the future state. The software approach is again applied to drive the parallelization of multiple finite-element analysis (FEA) runs, thus greatly saving on the computational cost. The proposed techniques are illustrated for the efficient diagnosis and prognosis of alkali-silica reactions in a concrete structure.

Topics:
Uncertainty quantification
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2017;4(1):. doi:10.1061/AJRUA6.0000948.
Abstract 

Abstract  Timely completion of dam and hydroelectric power plant (HEPP) projects is indispensable for the countries constructing them due to their economic, political, and social impacts. Robust and stable schedules should be created at the beginning of these projects in order to realistically estimate project durations considering uncertainties and variations. This paper proposes a buffer sizing methodology based on fuzzy risk assessment which can be used to calculate time buffers accurately for concrete gravity dam and HEPP projects by considering the vulnerability of activities to various risk factors as well as their interdependencies. A generic schedule is developed and 89 potential causes of delay/risk factors are identified for the concrete gravity dam and HEPP projects. Risk assessment is conducted at the activity level. The inputs of the model are frequency and severity of risk factors, and the output is estimated time buffer as a percentage of original duration. Implementation of the model is illustrated by an example project. Results show that outputs of the model can be used for scheduling, estimation of time buffers, and risk management of concrete gravity dam and HEPP projects. Although the model and its outputs are specific for concrete gravity dams, the buffer sizing methodology based on fuzzy risk assessment can easily be adapted to other types of construction projects.

Topics:
Gravity (Force) , Dams , Concretes , Polishing equipment , Risk assessment , Hydroelectric power stations

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