The Fog computing paradigm is becoming prominent in supporting time-sensitive applications that are related to the smart Internet of Things (IoT) services, such as smart city and smart healthcare. ...Although Cloud computing is a promising paradigm for IoT in data processing, due to the high latency limitation of the Cloud, it is unable to satisfy the requirements for time-sensitive applications. Resource allocation and provisioning in the Fog-Cloud environment, considering dynamic changes in user requirements and limited available resources in Fog devices, is a challenging task. Among dynamic changes in the parameters of user requirements, the deadline is the most important challenge in the Fog computing environment. Current works on Fog computing address the resource provisioning without considering the dynamic changes in users’ requirements. To address the problem of satisfying deadline-based dynamic user requirements, we propose resource allocation and provisioning algorithms by using resource ranking and provision of resources in a hybrid and hierarchical fashion. The proposed algorithms are evaluated in a simulation environment by extending the CloudSim toolkit to simulate a realistic Fog environment. The experimental results indicate that the performance of the proposed algorithms is better compared with existing algorithms in terms of overall data processing time, instance cost and network delay, with the increasing number of application submissions. The average processing time and cost are decreased by 12% and 15% respectively, compared with existing solutions.
•A novel resource allocation method by ranking the resources based on their constraints.•A new resource provisioning algorithm for the Fog-Cloud environment.•A resource provisioning method to satisfy the user dynamic requirements.
•A comprehensive hybrid transient CFD-thermal resistance model is proposed.•The ultra-high instantaneous efficiency of the ATEG system occurs due to thermal inertia.•The output power presents a more ...stable variation than the exhaust temperature.•The steady-state model overestimates the power and underestimates the efficiency.•The effect of the topological relationship of TEMs on the performance is investigated.
This paper proposes a comprehensive hybrid transient CFD-thermal resistance model to predict the dynamic behaviour of an automobile thermoelectric generator (ATEG) system. The model takes into account the temperature dependences, the topological connection of thermoelectric modules, and the dynamic characteristics, which has the merits of high accuracy and short computational time. The dynamic behaviour of the ATEG system is determined and thoroughly examined using the transient exhaust heat as the heat source input. According to the transient model results, the dynamic output power of the ATEG system keeps the same variation trend with the exhaust temperature, but the variation of output power is more stable. Under the whole driving cycle, the mean power and efficiency of the 1/4 ATEG system are 8.91 W and 3.39% respectively, which are 3.39% lower and 47.52% higher than those expected by steady-state analysis. Beside, the model is validated experimentally, and the mean deviations of the output voltage and outlet air temperature are 7.70% and 1.12% respectively. This model is convenient to evaluate the behaviour of the ATEG system under different topological connections and gives a fresh tool for assessing the dynamic behaviour of ATEG systems.
Machine learning (ML) methods with good applicability to complex and highly nonlinear sequences have been attracting much attention in recent years for predictions of complicated mechanical ...properties of various materials. As one of the widely known ML methods, back-propagation (BP) neural networks with and without optimization by genetic algorithm (GA) are also established for comparisons of time cost and prediction error. With the aim to further increase the prediction accuracy and efficiency, this paper proposes a long short-term memory (LSTM) networks model to predict the dynamic compressive performance of concrete-like materials at high strain rates. Dynamic explicit analysis is performed in the finite element (FE) software ABAQUS to simulate various waveforms in the split Hopkinson pressure bar (SHPB) experiments by applying different stress waves in the incident bar. The FE simulation accuracy is validated against SHPB experimental results from the viewpoint of dynamic increase factor. In order to cover more extensive loading scenarios, 60 sets of FE simulations are conducted in this paper to generate three kinds of waveforms in the incident and transmission bars of SHPB experiments. By training the proposed three networks, the nonlinear mapping relations can be reasonably established between incident, reflect, and transmission waves. Statistical measures are used to quantify the network prediction accuracy, confirming that the predicted stress-strain curves of concrete-like materials at high strain rates by the proposed networks agree sufficiently with those by FE simulations. It is found that compared with BP network, the GA-BP network can effectively stabilize the network structure, indicating that the GA optimization improves the prediction accuracy of the SHPB dynamic responses by performing the crossover and mutation operations of weights and thresholds in the original BP network. By eliminating the long-time dependencies, the proposed LSTM network achieves better results than the BP and GA-BP networks, since smaller mean square error (MSE) and higher correlation coefficient are achieved. More importantly, the proposed LSTM algorithm, after the training process with a limited number of FE simulations, could replace the time-consuming and laborious FE pre- and post-processing and modelling.
The use of steel fibre reinforced concrete (SFRC) in protective structures has gained worldwide interest due to its superior mechanical characteristics. At present, hydrocode material models have ...been frequently used to simulate the dynamic behaviour of SFRC subjected to impact and blast loads. However, as these material models are developed for normal concrete, much effort is required for model calibration, and their other drawbacks, such as the neglect of shear dilation and the inappropriate consideration of strain-rate effect, may lead to inaccuracies in numerical predictions. In this study, a new constitutive material model is developed for SFRC, in which the damage evolution, shear dilation and strain-rate dependent material properties are properly taken into account. The new material model could accurately capture the mechanical behaviours of SFRC (i.e. strain hardening and softening in both compression and tension) with simple input parameters. It is then incorporated into the commercial finite element code LS-DYNA to simulate the structural behaviour of SFRC components under various loading conditions. The effectiveness and accuracy of the new material model are validated against the reported experimental results.
The main goal of the present work was to investigate the effect of infill density on dynamic behavior of 3D printed parts. The short carbon-fibre-reinforced PolyEtherKetoneKetone composites (CF-PEKK) ...was selected as material which has an excellent mechanical, physical, thermal and energy absorbing performance. It’s employed widely in a vast range of industries due to their ultra-low density, multi-functionality and ability to undergo large deformations at low loads. For this purpose, a procedure for characterizing the dynamic behavior of this material fabricated with Fused Filament Fabrication (FFF) is presented in this research. Three infill densities (20%, 50% and 100%) were experimentally compressed for different impact pressures (1,4 bar; 1,7 bar; 2 bar and 2,4 bar) using Split Hopkinson Pressure Bar (SHPB). A FASTCAM high-speed camera was positioned in front of the SHPB test set-up to capture the dynamic deformation processes. The special attention is also given to examine the dynamic response of 3D printed CF-PEKK (100% infill density) subjected to repeated impacts. The obtained results proved that the low density and high-density infills were more cost-effective when compared to solid samples. The repeated impact drastically changed the dynamic behavior of the material compared to standard impact. With increasing the number of impact loading to the final failure, the dynamic parameters (i.e dynamic modulus, maximum stress…etc.) decreased remarkably and the material suffered catastrophic cumulated damage.
•A stretching hub-beam model for the 1st deployment of IKAROS solar sail is proposed.•A structure-preserving method is used to study the dynamic behaviors of the model.•Coupling dynamic behaviors of ...the flexible stretching hub-beam system are reproduced.
In the 1st stage deployment of the IKAROS solar sail, the flexible beam with comparable mass relative to the mass of the rotor is stretching actively in the axial direction, which brings new challenge in the dynamic analysis for the 1st stage deployment of the IKAROS solar sail. Considering the active axial stretching of the flexible beam, a simplified coupling dynamic model for the 1st stage deployment of the IKAROS solar sail is proposed based on the non-holonomic Hamilton least-action principle firstly. And then, a structure-preserving approach combining the generalized multi-symplectic method and the symplectic Runge-Kutta method is constructed to simulate the evolution of the transverse vibration of the beam as well as the evolution of the rotation of the hub. Finally, the associated numerical results in three stages are reported. From the numerical results, it can be found that the coupling effects between the deformation of the beam, the active stretching of the beam and the rotation of the hub are reflected in the stretching stage. In this stage, the transverse vibration of the beam is enhanced by the stretching effect of the beam, and the increase of the energy of the beam in this stage is derived from the decrease of the rotational energy of the hub. In addition, the structure-preserving properties and the validity of the numerical results are verified by the tiny relative energy dissipation of the flexible stretching hub-beam system in the stretching stage.
As one of important characteristics of the nonlinear system containing the quadratic or cubic nonlinearity, the internal resonance between the system's modes may occur and affect the nonlinear ...properties of the system. In this paper, the internal resonance conditions of the spatial flexible beam suspended by two springs in a spatial on-orbit tethered system are obtained based on the method of multiple scales firstly. And then, the effects of the internal resonances on the attitude stability and the energy transfer tendency of the tethered system are investigated by the structure-preserving approach in detail. In the numerical simulation, the attitude angle always tends to zero in a finite interval when the internal resonance of the spatial flexible beam occurs even if the mass of the platform is close to that of the beam, which implies that, the occurrence of the internal resonance will improve the attitude stability of the tethered system. In addition, it can be found that, when the internal resonance occurs, the elastic potential energy stored in the springs tends to transfer to the beam even if the initial attitude angle is small, which will shorten the vibration control time of the spatial flexible beam if the damping of the beam is considered. The above findings permit us to optimize the system parameters or select the appropriate initial conditions to improve the attitude stability and to accelerate the total energy dissipation of the tethered system if the damping of the spatial flexible beam is considered.
•The internal resonance conditions of the on-orbit flexible beam suspended by two springs are obtained.•The effects of the internal resonances on the attitude stability of the tethered system are investigated.•The effects of the internal resonances on the energy transfer tendency of the tethered system are investigated.
The nowadays-available dynamic monitoring equipment integrating sensitive low-noise sensors creates an opportunity to implement continuously operating dynamic monitoring systems in dams and validate ...the suitability of these systems to monitor such massive structures with the goal of detecting damage. The continuous characterisation of the dam modal properties during important variations of the water level and temperature is a unique experimental result, which is particularly interesting for the calibration of numerical models that consider water–structure interaction.
Using a quite rare database collected in a large concrete dam, the Baixo Sabor dam in this case study, a methodology based on machine learning techniques and soft computing is proposed for the analysis and interpretation of observed dynamic behaviour of concrete dams based on models HST (hydrostatic, seasonal, time). For this model, two methodologies are applied, Multiple Linear Regression and MultilLayer Perceptron Neural Network, to characterise the water level effect and the thermal effect related to the seasonal variation of temperature during one year period. A spectral analysis based on wavelet transform is also presented to characterise the thermal effect of daily temperature variations.
The Baixo Sabor dam is a concrete double-curvature arch dam, 123 meters high, located in the northeast of Portugal, which is being monitored by a dynamic monitoring system that comprises 20 uniaxial accelerometers. The results are compared and discussed. The results of this study show that the methodology proposed is suitable for a better understating of the observed dynamic behaviour and opens new opportunities for dam safety control activities.
•Time–frequency analysis to identify predominant natural frequency observed in a large arch dam.•Natural frequency variations resulting from the water level and air temperature variations.•Signature of the daily air temperature variation on the structural dam behaviour response.
Water management in fuel cells is important for avoiding the phenomenon of flooding or dehydration in the stack and for maintaining good fuel cell performance and durability. This study focuses on ...the evaluation of the dynamic performance and behaviour (purge cycle) of the commercial Polymer Electrolyte Membrane (PEM) fuel cell stack towards water transport (water balance) at different operating conditions. The stack was operated at different current loads (0–10 A) and operating temperature (ambient to 50 °C). The results indicated that the measured water accumulation in the stack increased with the increase in current load. The optimal current load was 4 A, with calculated efficiency of 62.8%. The optimal operating temperature was 40 °C, resulting in calculated efficiency of 52.3%. At higher temperature, the fuel cell performance decreased, and the measured water balance was not properly distributed, which could be due to the dehydration and low conductivity of the electrolyte membrane. It can be concluded that the behaviour and performance of the stack, as well as the water balance in the stack, were influenced by the operating conditions. Moreover, this study improves the understanding of fuel cell performance and behaviour based on evaluation of the water balance.
•Sixteen upright CFFT columns subjected to repeated and sequential lateral impact using a 220 kg pendulum.•Steel reinforced CFFT columns exhibited superior performance in damage control.•Increasing ...the FRP tube thickness of unreinforced CFFT columns slightly improved the deformation behaviour.•Polypropylene fiber (PPF) in the CFFT columns did not affect the impact load but slightly improved the deformation.
The experimental work conducted in this study aims to develop more understanding of the dynamic response of concrete-filled fiber reinforced polymer (FRP) tubes (CFFTs) columns under lateral impact load by testing 16 specimens. Three different types including reinforced concrete (RC), unreinforced CFFT and steel reinforced CFFT columns were tested. The specimens were tested under both repeated and sequential impact load testing protocols. Four parameters were investigated: the cross-section size, the thickness of the FRP tube, and the presence of longitudinal reinforcement. In addition, the effect of adding polypropylene fibers (PPF) to the concrete was also studied. Based on the experimental results, the damage mechanism, impact loads, deflections and strains were monitored and discussed. The results of this investigation confirmed that steel reinforced CFFT columns exhibited superior damage control characteristics when compared to RC columns. Increasing the thickness of the FRP tube decreased the displacement by up to 18 % and the residual displacement by up to 15 %. Adding PPF delayed the failure of the specimen and slightly enhanced its response. The experimental findings showed that longitudinal internal steel reinforcement played an important role in columns’ overall behavior and increased impact capacity.
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