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Guest Editorial

ASME J. Risk Uncertainty Part B. 2017;4(3):030301-030301-1. doi:10.1115/1.4038467.
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The importance of safety, security, and risk management has been recognized in nuclear multiscale systems modeling, simulation, and analysis applications. Since 2011, earthquake and tsunami led to the nuclear accident at Fukushima Daiichi-Japan; nuclear energy facilities have been under massive pressures to enhance the safety and security. Enormous number of researches was conducted on the area of nuclear safety and security including cybersecurity, stress testing, resilience analysis along with risk management.

Commentary by Dr. Valentin Fuster

Special Section Papers

ASME J. Risk Uncertainty Part B. 2017;4(3):030901-030901-10. doi:10.1115/1.4037878.

Severe accident facilities for European safety targets (SAFEST) is a European project networking the European experimental laboratories focused on the investigation of a nuclear power plant (NPP) severe accident (SA) with reactor core melting and formation of hazardous material system known as corium. The main objective of the project is to establish coordinated activities, enabling the development of a common vision and severe accident research roadmaps for the next years, and of the management structure to achieve these goals. In this frame, a European roadmap on severe accident experimental research has been developed to define research challenges to contribute to further reinforcement of Gen II and III NPP safety. The roadmap takes into account different SA phenomena and issues identified and prioritized in the analyses of severe accidents at commercial NPPs and in the results of the recent European stress tests carried out after the Fukushima accident. Nineteen relevant issues related to reactor core meltdown accidents have been selected during these efforts. These issues have been compared to a survey of the European SA research experimental facilities and corium analysis laboratories. Finally, the coherence between European infrastructures and R&D needs has been assessed and a table linking issues and infrastructures has been derived. The comparison shows certain important lacks in SA research infrastructures in Europe, especially in the domains of core late reflooding impact on source term, reactor pressure vessel failure and molten core release modes, spent fuel pool (SFP) accidents, as well as the need for a large-scale experimental facility operating with up to 500 kg of chemically prototypic corium melt.

Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(3):030902-030902-9. doi:10.1115/1.4037877.

The objective of this paper is to develop a probabilistic risk assessment (PRA) methodology against volcanic eruption for decay heat removal function of sodium-cooled fast reactors (SFRs). In the volcanic PRA methodology development, only the effect of volcanic tephra (pulverized magma) is taken into account, because there is a great distance between a plant site assumed in this study and volcanoes. The volcanic tephra (ash) could potentially clog air filters of air-intakes that are essential for the decay heat removal. The degree of filter clogging can be calculated by atmospheric concentration of ash and tephra fallout duration and also suction flow rate of each component. This study evaluated a volcanic hazard using a combination of tephra fragment size, layer thickness, and duration. In this paper, functional failure probability of each component is defined as a failure probability of filter replacement obtained by using a grace period to filter failure. Finally, based on an event tree, a core damage frequency has been estimated by multiplying discrete hazard frequencies by conditional decay heat removal failure probabilities. A dominant sequence has been identified as well. In addition, sensitivity analyses have investigated the effects of a tephra arrival reduction factor and prefilter covering.

Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(3):030903-030903-7. doi:10.1115/1.4037879.

This study presents an assessment of the RELAP5/MOD3.3 using the experimental work upon the rewetting mechanism of bottom flooding of a vertical annular water flow inside a channel enclosing concentrically a heated rod. The experiments have been carried out in the experimental rig 1 of the Nuclear Engineering Department of National Technical University of Athens (NTUA-NED-ER1) inside which the dry out and the rewetting process of a hot vertical rod can be simulated. Experiments have been conducted at atmospheric conditions with liquid coolant flow rate within the range of 0.008 and 0.050 kg·s−1 and two levels of subcooling 25 and 50 K. The initial average surface temperature of the rod for each experiment was set at approximately 823 K. The predicted rod surface temperatures during rewetting of the RELAP5/MOD3.3 calculations were compared against the experimental values. The results presented in this study show that RELAP5/MOD3.3 provides temperature estimations of the reflooding mechanism within acceptable marginal error. However, larger deviations between predicted and experimental values have been observed when subcooled water was used instead of saturated one.

Commentary by Dr. Valentin Fuster

Research Papers

ASME J. Risk Uncertainty Part B. 2017;4(3):031001-031001-9. doi:10.1115/1.4037725.

Vehicle door latch performance testing presently utilizes uniaxial quasi-static loading conditions. Current technology enables sophisticated virtual testing of a broad range of systems. Door latch failures have been observed in vehicles under a variety of conditions. Typically, these conditions involve multi-axis loading conditions. The loading conditions presented during rollovers on passenger vehicle side door latches have not been published. Rollover crash test results, rollover crashes, and physical Federal Motor Vehicle Safety Standard (FMVSS) 206 latch testing results are reviewed. The creation and validation of a passenger vehicle door latch model is described. The multi-axis loading conditions observed in virtual rollover testing at the latch location are characterized and applied to the virtual testing of a latch in the secondary latch position. The results are then compared with crash test and real world rollover results for the same latch. The results indicate that a door latch that meets the secondary latch position requirements may fail at loads substantially below the FMVSS 206 uniaxial failure loads. In the side impact mode, risks associated with door handle designs and the potential for inertial release can be considered prior to manufacturing with virtual testing. An example case showing the effects of material and spring selection illustrates the potential issues that can be detected in advance of manufacturing. The findings suggest the need for re-examining the relevance of existing door latch testing practices in light of the prevalence of rollover impacts and other impact conditions in today's vehicle fleet environment.

Topics: Doors , Stress , Testing , Failure , Vehicles
Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(3):031002-031002-14. doi:10.1115/1.4038318.

Time-dependent system reliability is computed as the probability that the responses of a system do not exceed prescribed failure thresholds over a time duration of interest. In this work, an efficient time-dependent reliability analysis method is proposed for systems with bivariate responses which are general functions of random variables and stochastic processes. Analytical expressions are derived first for the single and joint upcrossing rates based on the first-order reliability method (FORM). Time-dependent system failure probability is then estimated with the computed single and joint upcrossing rates. The method can efficiently and accurately estimate different types of upcrossing rates for the systems with bivariate responses when FORM is applicable. In addition, the developed method is applicable to general problems with random variables, stationary, and nonstationary stochastic processes. As the general system reliability can be approximated with the results from reliability analyses for individual responses and bivariate responses, the proposed method can be extended to reliability analysis of general systems with more than two responses. Three examples, including a parallel system, a series system, and a hydrokinetic turbine blade application, are used to demonstrate the effectiveness of the proposed method.

Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(3):031003-031003-7. doi:10.1115/1.4038340.

Prestress applied on bridges affects the dynamic interaction between bridges and vehicles traveling over them. In this paper, the prestressed bridge is modeled as a beam subjected to eccentric prestress force at the two ends, and a half-vehicle model with four degrees-of-freedom is used to represent the vehicle passing the bridge. A new bridge–vehicle interaction model considering the effect of prestress with eccentricity is developed through the principle of virtual work. The correctness and accuracy of the model are validated with literature results. Based on the developed model, numerical simulations have been conducted using Newmark's β method to study the effects of vehicle speed, eccentricity and amplitude of the prestress, and presence of multiple vehicles. It is shown that prestress has an important effect on the maximum vertical acceleration of vehicles, which may provide a good index for detecting the change of prestress. It is also interesting to find that the later-entering vehicle on the prestressed bridge will largely reduce the maximum vertical acceleration of the vehicle ahead of it.

Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(3):031004-031004-12. doi:10.1115/1.4038170.

The influence of component errors on the final error is a key point of error modeling of computer numerical control (CNC) machine tool. Nevertheless, the mechanism by which the errors in mechanical parts accumulate to result in the component errors and then impact the final error of CNC machine tool has not been identified; the identification of this mechanism is highly relevant to precision design of CNC machine. In this study, the error modeling based on the Jacobian-torsor theory is applied to determine how the fundamental errors in mechanical parts influence and accumulate to the comprehensive error of single-axis assembly. First, a brief introduction of the Jacobian-torsor theory is provided. Next, the Jacobian-torsor model is applied to the error modeling of a single-axis assembly in a three-axis machine center. Furthermore, the comprehensive errors of the single-axis assembly are evaluated by Monte Carlo simulation based on the synthesized error model. The accuracy and efficiency of the Jacobian-torsor model are verified through a comparison between the simulation results and the measured data from a batch of similar vertical machine centers. Based on the Jacobian-torsor model, the application of quantitative sensitivity analysis of single-axis assembly is investigated, along with the analysis of key error sources to the synthetical error ranges of the single-axis assembly. This model provides a comprehensive method to identify the key error source of the single-axis assembly and has the potential to enhance the tolerance/error allocation of the single axis and the whole machine tool.

Commentary by Dr. Valentin Fuster
ASME J. Risk Uncertainty Part B. 2017;4(3):031005-031005-11. doi:10.1115/1.4038372.

In the present study, a general probabilistic design framework is developed for cyclic fatigue life prediction of metallic hardware using methods that address uncertainty in experimental data and computational model. The methodology involves: (i) fatigue test data conducted on coupons of Ti6Al4V material, (ii) continuum damage mechanics (CDM) based material constitutive models to simulate cyclic fatigue behavior of material, (iii) variance-based global sensitivity analysis, (iv) Bayesian framework for model calibration and uncertainty quantification, and (v) computational life prediction and probabilistic design decision making under uncertainty. The outcomes of computational analyses using the experimental data prove the feasibility of the probabilistic design methods for model calibration in the presence of incomplete and noisy data. Moreover, using probabilistic design methods results in assessment of reliability of fatigue life predicted by computational models.

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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