• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.4
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• pp.330-343
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• 2016

This paper presents results of an experimental investigation of vortex-induced vibration (VIV) of a flexibly mounted and rigid cylinder with two-degrees-of-freedom with respect to varying ratio of in-line natural frequency to cross-flow natural frequency, $f^*$, at a fixed low mass ratio. Combined in-line and cross-flow motion was observed in a sub-critical Reynolds number range. Three-dimensional displacement meter and tension meter were used to measure dynamic responses of the model. To validate the results and the experiment system, x and y response amplitudes and ratio of oscillation frequency to cross-flow natural frequency were compared with other experimental results. It has been found that the higher harmonics, such as third and more vibration components, can occur on a certain part of steel catenary riser under a condition of dual resonance mode. In the present work, however, due to the limitation of a size of circulating water channel, the whole test of a whole configuration of the riser at an adequate scale for VIV phenomenon was not able to be conducted. Instead, we have modeled a rigid cylinder and assumed that the cylinder is a part of steel catenary riser where the higher harmonic motions could occur. Through the experiment, we have found that even though the cylinder was assumed to be rigid, the occurrence of the higher harmonic motions was observed in a small reduced velocity ($V_r$) range, where the influence of the in-line response is relatively large. The transition of the vortex shedding mode from one to another was examined by using time history of x and y directional displacement over all experimental cases. We also observed the influence of in-line restoring force power spectral density with $f^*$.

• Steel and Composite Structures
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• v.25 no.1
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• pp.105-116
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• 2017

This paper presents the dynamic stability study of laminated composite plates with different force combinations and aspect ratios. Optimum non-diverging stacking is obtained for certain loading combination and aspect ratio. In addition, the stability force is maximized for a definite operating frequency. A dynamic version of the principle of virtual work for laminated composites is used to obtain force-frequency relation. Since dynamic stiffness governs the divergence or flutter, an efficient optimization method is necessary for the response functional and the relevant constraints. In this way, a model based on the ant colony optimization (ACO) algorithm is proposed to search for the proper stacking. The ACO algorithm is used since it treats with large number of dynamic stability parameters. Governing equations are formulated using classic laminate theory (CLT) and von-Karman plate technique. Load-frequency relations are explicitly obtained for fundamental and secondary flutter modes of simply supported composite plate with arbitrary aspect ratio, stacking and boundary load, which are used in optimization process. Obtained results are compared with the finite element method results for validity and accuracy convince. Results revealed that the optimum stacking with stable dynamic response and maximum critical load is in angle-ply mode with almost near-unidirectional fiber orientations for fundamental flutter mode. In addition, short plates behave better than long plates in combined axial-shear load case regarding stable oscillation. The interaction of uniaxial and shear forces intensifies the instability in long plates than short ones which needs low-angle layup orientations to provide required dynamic stiffness. However, a combination of angle-ply and cross-ply stacking with a near-square aspect ratio is appropriate for the composite plate regarding secondary flutter mode.

• Safety and Health at Work
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• v.9 no.1
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• pp.84-94
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• 2018

Background: This paper describes a simple-to-use and reliable screening tool called Critical Task Exposure Screening (CTES), developed by a chemical company. The tool assesses if the exposure to a chemical for a task is likely to be within acceptable levels. Methods: CTES is a Microsoft Excel tool, where the inhalation risk score is calculated by relating the exposure estimate to the corresponding occupational exposure limit (OEL) or occupational exposure band (OEB). The inhalation exposure is estimated for tasks by preassigned ART1.5 activity classes and modifying factors. Results: CTES requires few inputs. The toxicological data, including OELs, OEBs, and vapor pressure are read from a database. Once the substance is selected, the user specifies its concentration and then chooses the task description and its duration. CTES has three outputs that may trigger follow-up: (1) inhalation risk score; (2) identification of the skin hazard with the skin warnings for local and systemic adverse effects; and (3) status for carcinogenic, mutagenic, or reprotoxic effects. Conclusion: The tool provides an effective way to rapidly screen low-concern tasks, and quickly identifies certain tasks involving substances that will need further review with, nevertheless, the appropriate conservatism. This tool shows that the higher-tier ART1.5 inhalation exposure assessment model can be included effectively in a screening tool. After 2 years of worldwide extensive use within the company, CTES is well perceived by the users, including the shop floor management, and it fulfills its target of screening tool.

• Nuclear Engineering and Technology
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• v.48 no.6
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• pp.1291-1302
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• 2016

This paper presents a new and efficient scheme to determine the optimal neutron source position in a model near-equilibrium pressurized water reactor, which is based on the OPR1000 Hanul Unit 3 Cycle 7 configuration. The proposed scheme particularly assigns importance of source positions according to the local adjoint flux distribution. In this research, detailed pin-by-pin reactor adjoint fluxes are determined by using the Monte Carlo KENO-VI code from solutions of the reactor homogeneous critical adjoint transport equations. The adjoint fluxes at each allowable source position are subsequently ranked to yield four candidate positions with the four highest adjoint fluxes. The study next simulates ex-core detector responses using the Monte Carlo MAVRIC code by assuming a neutron source is installed in one of the four candidate positions. The calculation is repeated for all positions. These detector responses are later converted into an inverse count rate ratio curve for each candidate source position. The study confirms that the optimal source position is the one with very high adjoint fluxes and detector responses, which is interestingly the original source position in the OPR1000 core, as it yields an inverse count rate ratio curve closest to the traditional 1/M line. The current work also clearly demonstrates that the proposed adjoint flux-based approach can be used to efficiently determine the optimal geometry for a neutron source and a detector in a modern pressurized water reactor core.

• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1540-1553
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• 2019

A nuclear power plant (NPP) is a highly complex system-of-systems as manifested through its internal systems interdependence. The negative impact of such interdependence was demonstrated through the 2011 Fukushima Daiichi nuclear disaster. As such, there is a critical need for new strategies to overcome the limitations of current risk assessment techniques (e.g. the use of static event and fault tree schemes), particularly through simulation of the nonlinear dynamic feedback mechanisms between the different NPP systems/components. As the first and key step towards developing an integrated NPP dynamic probabilistic risk assessment platform that can account for such feedback mechanisms, the current study adopts a system dynamics simulation approach to model the thermal dynamic processes in: the reactor core; the secondary coolant system; and the pressurized water reactor. The reactor core and secondary coolant system parameters used to develop system dynamics models are based on those of the Palo Verde Nuclear Generating Station. These three system dynamics models are subsequently validated, using results from published work, under different system perturbations including the change in reactivity, the steam valve coefficient, the primary coolant flow, and others. Moving forward, the developed system dynamics models can be integrated with other interacting processes within a NPP to form the basis of a dynamic system-level (systemic) risk assessment tool.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.22-32
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• 2019

On offshore platforms, oil and gas leaks are apt to be the initial events of major accidents that may result in significant loss of life and property damage. To prevent accidents induced by leakage, it is vital to perform a case-specific and accurate risk assessment. This paper presents an integrated method of Ddynamic Qquantitative Rrisk Aassessment (DQRA)-using the Decision Making Trial and Evaluation Laboratory (DEMATEL)-Bayesian Network (BN)-for evaluation of the system vulnerabilities and prediction of the occurrence probabilities of accidents induced by leakage. In the method, three-level indicators are established to identify factors, events, and subsystems that may lead to leakage, fire, and explosion. The critical indicators that directly influence the evolution of risk are identified using DEMATEL. Then, a sequential model is developed to describe the escalation of initial events using an Event Tree (ET), which is converted into a BN to calculate the posterior probabilities of indicators. Using the newly introduced accident precursor data, the failure probabilities of safety barriers and basic factors, and the occurrence probabilities of different consequences can be updated using the BN. The proposed method overcomes the limitations of traditional methods that cannot effectively utilize the operational data of platforms. This work shows trends of accident risks over time and provides useful information for risk control of floating marine platforms.

• Wind and Structures
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• v.35 no.1
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• pp.55-66
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• 2022

Tall buildings are often subjected to steady and unsteady forces due to external wind flows. Measurement and mitigation of these forces becomes critical to structural design in engineering applications. Over the last few decades, many approaches such as modification of the external geometry of structures have been investigated to mitigate wind-induced load. One such proven geometric modification involved the rounding of sharp corners. In this work, we systematically analyze the impact of rounded corner radii on the reducing the flow-induced loading on a square cylinder. We perform 3-Dimensional (3D) simulations for high Reynolds number flows (Re=1 × 105) which are more likely to be encountered in practical applications. An Improved Delayed Detached Eddy Simulation (IDDES) method capable of capturing flow accurately at large Reynolds numbers is employed in this study. The IDDES formulation uses a k-ω Shear Stress Transport (SST) model for near-wall modelling that prevents mesh-induced separation of the boundary layer. The effects of these corner modifications are analyzed in terms of the resulting variations in the mean and fluctuating components of the aerodynamic forces compared to a square cylinder with no geometric changes. Plots of the angular distribution of the mean and fluctuating coefficient of pressure along the square cylinder's surface illustrate the effects of corner modifications on the different parts of the cylinder. The windward corner's separation angle was observed to decrease with an increase in radius, resulting in a narrower and longer recirculation region. Furthermore, with an increase in radius, a reduction in the fluctuating lift, mean drag, and fluctuating drag coefficients has been observed.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Smart Structures and Systems
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• v.29 no.1
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• pp.17-28
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• 2022

The cable component of cable-stayed bridges is gradually impacted by weather conditions, vehicle loads, and material corrosion. The stayed cable is a critical load-carrying part that closely affects the operational stability of a cable-stayed bridge. Damaged cables might lead to the bridge collapse due to their tension capacity reduction. Thus, it is necessary to develop structural health monitoring (SHM) techniques that accurately identify damaged cables. In this work, a combinational identification method of three efficient techniques, including statistical analysis, clustering, and neural network models, is proposed to detect the damaged cable in a cable-stayed bridge. The measured dataset from the bridge was initially preprocessed to remove the outlier channels. Then, the theory and application of each technique for damage detection were introduced. In general, the statistical approach extracts the parameters representing the damage within time series, and the clustering approach identifies the outliers from the data signals as damaged members, while the deep learning approach uses the nonlinear data dependencies in SHM for the training model. The performance of these approaches in classifying the damaged cable was assessed, and the combinational identification method was obtained using the voting ensemble. Finally, the combination method was compared with an existing outlier detection algorithm, support vector machines (SVM). The results demonstrate that the proposed method is robust and provides higher accuracy for the damaged cable detection in the cable-stayed bridge.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2188-2208
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• 2023

Quality of Service (QoS) is a critical feature of Wireless Sensor Networks (WSNs) with routing algorithms. Data packets are moved between cluster heads with QoS using a number of energy-efficient routing techniques. However, sustaining high scalability while increasing the life of a WSN's networks scenario remains a challenging task. Thus, this research aims to develop an energy-balancing component that ensures equal energy consumption for all network sensors while offering flexible routing without congestion, even at peak hours. This research work proposes a Gravitational Blackhole Search Optimised splay tree routing framework. Based on the splay tree topology, the routing procedure is carried out by the suggested method using three distinct steps. Initially, the proposed GBSO decides the optimal route at initiation phases by choosing the root node with optimum energy in the splay tree. In the selection stage, the steps for energy update and trust update are completed by evaluating a novel reliance function utilising the Parent Reliance (PR) and Grand Parent Reliance (GPR). Finally, in the routing phase, using the fitness measure and the minimal distance, the GBSO algorithm determines the best route for data broadcast. The model results demonstrated the efficacy of the suggested technique with 99.52% packet delivery ratio, a minimum delay of 0.19 s, and a network lifetime of 1750 rounds with 200 nodes. Also, the comparative analysis ensured that the suggested algorithm surpasses the effectiveness of the existing algorithm in all aspects and guaranteed end-to-end delivery of packets.