Input Load Research Articles

Development of a procedure for model selection in machine learning-based methods for structural damage detection

Output-only methods based on machine/deep-learning algorithms are highly practical approaches for timely detecting potential damages in civil structures as they directly employ measured vibration signals but do notrequire exact knowledge of input loading nor the service interruption for manual inspection. However, there isno one-size-fits-all model that is optimal for all problems in different perspectives; hence, it is necessary todiscover the advantages as well as drawbacks of different models, then leverage these understandings to selectthe most appropriate model for specific structures in reality. Therefore, this study develops a framework thatfacilitate the model selection by extensively comparing various machine learning-based methods ranging fromrelatively simple ones such as Na¨ıve Bayes to complex ones such as the extreme boosting tree-based ensemblemodel. The framework can provide comparison results include various aspects such as model complexity, training time, detection accuracy, and inference time.

Fatigue life prediction of steel spiral cases in pumped-storage power plants: Factors to be considered

Pumped-storage power plants are playing an increasingly critical role in electricity grids by providing them with great operational flexibility. The flexibility requires frequent operation-mode switches of pump turbines, which leads to frequent variations in internal water pressure (IWP) resisted by steel spiral cases (SSCs). Such IWP variations are usually of large amplitudes due to their high design heads. Consequently, SSCs in pumped-storage power plants should be confronted with relatively high fatigue failure risks in their service lives. The specific objective of this study is therefore to identify key factors that significantly affect fatigue life prediction of SSCs in pumped-storage power plants. The authors perform a numerical simulation of a spiral case structure of the Liyang pumped-storage power plant on the finite element analysis platform ABAQUS, with its temporary-pressurization construction process carefully modeled using the complete simulation procedure. Then the finite element analysis results are used as input for fatigue analysis of the SSC on the ANSYS nCode DesignLife platform. The case study suggests that the concrete damage should be considered in fatigue life prediction of a SSC as the damage (even local) weakens the restraining effect on the SSC. The second major factor identified is the cyclic loading input strategy. The key to the loading strategy is to capture the essential features of IWP variations, i.e. to repeat the IWP loading roughly between the upper- and lower-reservoir heads. The study has also shown that the effect of the mean stress correction is less important than expected. The factors identified therefore assist in our understanding of the role of adequate fatigue design and analysis of SSCs in pumped-storage power plants.

Robust control of a single-ended primary inductor converter using adrc technique

Control of a single-ended primary inductor converter (SEPIC) is a challenging task as it is a fourth-order non-linear system. In this paper, an active disturbance rejection control (ADRC) scheme is proposed for the SEPIC converter with a high switching frequency. Selection of the observers and controller bandwidth is done according to the maximum sensitivity requirement to achieve robust performance towards varying input voltage and load. The effectiveness of the suggested ADRC is shown by calculating power and efficiencies for different loading conditions.

Impact of Low Catalyst Loading and Incorporation of Additives on Structure and Performance of PEM Electrolyzer Catalyst Layers

Polymer electrolyte membrane water electrolyzers (PEMWEs) are an important technology that can produce renewable hydrogen on demand, although with challenges posed by the slow kinetics of the anodic oxygen evolution reaction (OER) and degradation issues. The degradation of membrane electrode assemblies (MEAs) prepared with Ir-based catalysts is not well understood, especially with lower-loading catalyst layers and intermittent load inputs. This work investigates low-loading IrO2 catalyst layers made with different carbon-based additives, including high-surface-area carbon (HSC), graphitized HSC (gHSC), Vulcan, graphitic carbon nanofibers (gCNFs), graphitic nanoplatelets (gNPs), nitrogen-doped carbon spheres (NCs), Ti carbide (TiC) and Ti carbonitride (TiCN). While carbon-based supports have issues with corrosion at high oxidizing potentials, these materials provide a range of variations in morphology, shape, size, surface area, graphitization, and composition, allowing exploration of the impact of these parameters on catalyst layer structure to identify promising routes to improve catalyst layer structures. Catalyst layers were characterized with electron microscopy and x-ray spectroscopy to assess the distribution of catalyst, carbon additive, and ionomer. This information was correlated with electrochemical performance measurements to elucidate the impact on kinetic site access and mass transport. Selected samples were also subjected to more extended operation to investigate how the initial structures and their performance evolved.

SYNTHESIS OF A COMPUTER NETWORK FOR CONTROLLING MOVING OBJECTS

Today, there are many methods of synthesis of the basic network of the computer control system. But they do not take into account the mobility of control objects. Therefore, the purpose of the article is to develop a method of synthesis of the basic network of the computer control system, which takes into account the mobility of control objects. The method is based on the use of the function of the average loss of messages in the network at the input load and the dynamic resource allocation plan. Regardless of the selected class of the basic network, the developed method assumes: the selection of an appropriate management efficiency assessment function; synthesis of control algorithms for restricting access to the network; synthesis of adaptive routing algorithms that ensure optimal distribution of flows on the short-circuit network. The direction of further research is to take into account the placement of base stations of the computer system.

An industrial design of 400 V – 48 V, 98.2% peak efficient charger usingE‐mode GaNtechnology with wide operating ranges for xEV applications

AbstractThis paper offers a wide‐operating range electric vehicle charger design by employing an interleaved inductor–inductor–capacitor iL2C DC–DC converter. It uses two parallel L2C converters with 8‐GaN switches on the primary side and a shared rectifier circuit on the secondary side, which it also enhances the circulating current, conduction losses, and current sharing. For iL2C converter, a constant voltage charging mode of operation is designed, also it proposes a hybrid control scheme of variable frequency + phase shift modulation (VFPSM). The entire concept is designed, simulated, and validated with a rated input voltage and load voltage of three different load conditions with converter line and load regulations are analyzed. To evaluate controller and converter performance, the idea is proven experimentally for variable load condition of full load, half load, light load with a rated input and output voltage of 400Vin–48V0. In addition, line regulation is also performed and validated for wide input voltage application of 300Vin–500 Vinwith an output voltage of 48V0at full load and peak efficiency of 98.2% is determined. Further, to provide the system effectiveness converter efficiencies are presented at various load operations from 3.3 kW to 330 W.

Output Ripple Voltage Analysis of Quadratic Buck–Boost Converters with Switched Inductor Network in the Entire Dynamic Range

In order to provide theoretical guidance for the design of quadratic Buck–Boost converter with switched inductor network, the minimum current flowing through the energy storage inductor L 3 is compared with the output current and zero, the working mode of the converter can be divided into the complete inductor supply in continuous conduction mode(CISM-CCM), the incomplete inductor supply in continuous conduction mode(IISM-CCM)and the incomplete inductor supply in discontinuous conduction mode(IISM-DCM). Within the given input voltage and load range, the working region of the converter is divided into five parts according to the different value of the inductor L 3. By analyzing the output ripple voltage of the converter in the five working areas, and the maximum output ripple voltage of the converter is obtained. Based on the relationship between the maximum output ripple voltage of the entire dynamic range and the value of the inductor L 3, it is pointed out that the output voltage ripple of the converter in CISM-CCM is the smallest and independent of the inductor L 3, and that the output voltage ripple in IISM-CCM and IISM-DCM is much larger and increasing with the decreasing of the inductor L 3. Meanwhile, it is concluded that the minimum inductance to guarantee the lowest output ripple voltage is the critical inductance between CISM-CCM and IISM-CCM. Finally, the experimental results verify the rationality and correctness of the theoretical analysis.

Indirect measurement method for high frequency response of complex structure based on statistical energy analysis

The harsh working environments often make it difficult to measure high frequency responses of complex structures in the fields such as aerospace and aeronautic, which severely hinders the evaluation of structural performance and safety. An indirect measurement method is proposed to estimate the high frequency responses of non-measurable subsystems using a statistical energy analysis (SEA) framework. Whether or not the non-measurable subsystem includes input load, two indirect measurement approaches are developed by constructing an overdetermined problem and a well-posed problem respectively. Both utilize only the power flow balance equations of unexcited subsystems to solve the problems and thus do not require solving for input loads. The approaches are validated numerically and experimentally through case study of a rocket engine structure. Furthermore, the interval error analyses indicate that the approaches are robust against SEA modeling errors and response measuring errors.

Development of graphical user interface for boost converter employing visual studio

In power electronics, the boost converter is a typical circuit that raises the voltage from the input to the desired output voltage. For learning how a boost converter works, you need an easy-to-use GUI that lets you change the input voltage, output voltage, and load resistance. In this study, we look at how to use Visual Studio to make a boost converter’s simple user interface (GUI). Details are given about how the software was programmed and how the interface was made, as well as how the graphical user interface was made. This circuit has a total of four devices, two for current and two for voltage. Voltage sensors can measure both the input and output voltage, while current sensors can measure both the input and output current. The Arduino Uno microcontroller is used as a processor for getting data and as a link between sensor devices and personal computers. The results show that the GUI we made works well for analyzing the features of the boost converter circuit.

A loading contribution degree analysis-based strategy for time-variant reliability analysis of structures under multiple loading stochastic processes

This paper proposes a new single-loop method based on the loading contribution degree analysis (LCDA) and decoupling strategy for analyzing the time-variant reliability of structures considering multiple loading stochastic processes and degradation processes. In this method, the loading stochastic processes are first discretized using the expansion optimal linear estimation method. Then, the LCDA is carried out to obtain a total weighted loading stochastic process used to accurately reflects the structural response, thus constructing a single loading stochastic process analysis problem. Subsequently, a decoupling strategy is applied to decouple the degradation processes and the total weighted loading stochastic process to obtain the equivalent extreme-value limit state function (EEV-LSF) of the structure. Finally, an efficient probability distribution reconstruction tool is applied to derive the probability density function of EEV-LSF. Notably, the proposed LCDA can avoid the calculation of the response time series of a structure under the input loading stochastic processes, providing a novel perspective to simplify the calculation of structural extreme-value response. Additionally, the proposed method requires only one round of deterministic analysis to obtain the structural time-variant failure probability at the specified time, constructing an efficient single-loop analysis method. Three numerical examples are used to validate the proposed method.

Experimental characterization of an ammonia – water – hydrogen diffusion absorption refrigeration system

A diffusion absorption refrigerator (DAR) is a heat powered refrigeration system. It uses the ammonia-water mixture as a working fluid in addition to an auxiliary inert gas. In the present work, experimental investigation and dynamic analysis of the H2O-NH3-H2 diffusion absorption refrigeration system have been carried out using different values of thermal power input to the generator and evaporator load. Experimental results show that the temperature evolution of system components, transient response, amount of cooling below ambient, and coefficient of performance are significantly sensitive to the values of generator power input and evaporator load. Analysis of DAR system behavior for different start up conditions is used to estimate the time and energy required for the initiation of cooling effect. Steady-state experimental results obtained over a wide range of generator input power and evaporator load are used to characterize the unit performance. Performance maps useful for the design and integration of DAR systems with low-temperature energy sources are developed. These maps can be used to estimate the generator input power required for a given cooling load at a specified value of cooling temperature below ambient.

Analysis of the Mechanical Characteristics of Tunnels Under the Coupling Effect of Submarine Active Faults and Ground Vibrations

With the rapid development of modern transportation construction, the construction of cross-harbor tunnels has solved the problem of traffic connection between cross-straits, bays and islands. The construction of sub-sea tunnels has technical difficulties such as high difficulty of marine geological survey, close hydraulic connection between strata and seawater, and more developed adverse geology. Based on this, this paper studies the mechanical characteristics of the submarine tunnel under seismic action at the active fault. Firstly, the mechanical model of the universal fault interface is established, and the calculation model of the fault interface is theoretically derived by the method of vibration mechanics, and the influence of the change of the strength of the contact surface and the stiffness of the surrounding rock on both sides of the fault on the transfer coefficient is obtained. Secondly, based on the ground motion input method of two-dimensional homogeneous half-space field, the relevant program of viscoelastic artificial boundary ground motion input is written by MATLAB program, which lays the foundation and premise of load input for mechanical response calculation. Finally, the outcomes of the tunnel parameters and the interplay between the tunnel and the surrounding rock on the cracking of the tunnel lining shape and the mechanical response of the cross-fault sub-sea tunnel underneath seismic motion are mentioned, and it is concluded that the increase in seismic intensity for different seismic intensities under the sea floor has an essentially constant proportion to the increase in acceleration of the seismic response; the seepage effect under the sea floor for the tunnel lining structure reduces the seismic response displacement, velocity and The seabed seepage for the tunnel lining structure reduces the peak seismic response displacement, velocity and acceleration by about 20–35%.

Numerical simulation of the dynamical behavior of a spinning cylinder partially filled with liquid

The flow pattern and transient response of a spinning cylinder partially filled with fluid are investigated in this paper. A two-dimensional finite element model of the fluid domain in the cylinder cavity is developed via the structured tetrahedral element. By using the volume of fluid model, the flow pattern of the liquid is examined numerically. Also, the effects of fluid type, rotating speed, and liquid height on the flow pattern are investigated. Then, the obtained fluid pressure exerted on the inner wall of the cylinder is considered as the input load, and transient dynamic analysis of the spinning liquid-filled cylinder is carried out. Finally, a comprehensive parametric study is conducted to evaluate the effects of liquid type, spinning speed, and fluid height on the dynamical behavior of the system. The results show that these parameters greatly influence the fluid flow pattern and dynamic characteristics of the spinning liquid-filled cylinder system.

Synthesis of a Discontinuous Control Law for a Step-Down Voltage Converter

This paper presents a nonlinear discontinuous control law that allows stabilizing the output voltage of a step-down voltage converter in conditions when the input voltage and load current are unknown. The main idea is based on the use of the so-called vortex algorithms, which ensure invariance with respect to external unmatched disturbances. The efficiency of the developed algorithms is shown by numerical simulation.

Influence of ring gear flexibility on the fatigue reliability of planetary gear systems in heavy helicopters

Flexibility of ring gear rims significantly affects the mechanical properties of planetary transmissions at both levels of gear tooth meshing and system power sharing, and is one of the important design factors determining the service reliability of large aviation planetary systems. Therefore, to analyze the mechanism by which the flexibility of ring gear rims affects the fatigue reliability of planetary systems, in the framework of the stress-strength interference theory, a reliability assessment model for the planetary system is constructed based on a calculation logic extension for the full probability formula. Starting from balancing evaluation accuracy and evaluation cost, a hybrid finite element method and a gear tooth lifetime transformation test are employed to provide load and strength input variables for the reliability model respectively. Finally, a mapping relationship from ring gear rim flexibility to planetary system fatigue reliability is established. For the specific design scheme of planetary systems, a lower limit of the ring gear rim thickness can be determined according to the requirements of reliability indexes, so that the balance between reliability and lightweight can be achieved to some extent.

Prognosis of Li-ion Batteries Under Large Load Variations Using Hybrid Physics-Informed Neural Networks

The development of new modes of transportation such as electric vertical takeoff and landing aircraft and the use of drones for package and medical delivery have increased the demand for reliable and powerful electric batteries. Therefore, accurately predicting the degradation of a battery’s state-ofhealth (SOH) and state-of-charge (SOC) is a crucial albeit still challenging task. There is a need for models that can accurately predict the SOH and SOC while taking into account the specific characteristics of a battery cell and its usage profile. While traditional physics-based and data-driven approaches are used to monitor the SOH and SOC, they both have limitations related to computational costs or that require engineers to continually update their prediction models as new battery cells are developed and put into use in battery-powered vehiclefleets.Battery capacity degradation can vary from battery to battery and can also be influenced by changes in load due to internal thermal stress. While sophisticated electrochemistry-based models can provide precise predictions of the SOC during adischarge cycle when parameters are well-tuned, using highfidelity models for prognostics purposes can be computationally expensive. Those models also require tuning to specific battery types and at times to specific specimens, thus hindering generalization. In contrast, purely data-driven approaches can learn the relationship between input and output for SOC prediction based on load input, but they require a large and diverse training dataset and lack any physical or electrochemical understanding, making far-ahead predictions challenging if test loading conditions fall outside the training distribution. To address some of the drawbacks of the aforementioned modeling approaches, in this paper, we enhance a hybrid physics-informed machine learning version of a battery SOC model we presented in previous work to predict voltage dropduring discharge. The enhanced model captures the effect of wide variation of load levels, in the form of input current,which causes large thermal stress cycles. The cell temperature build-up during a discharge cycle is used to identify temperature-sensitive model parameters. Additionally, we enhance an existing aging model built upon cumulative energy drawn by introducing the effect of the load level. We then map cumulative energy and load level to battery capacity with a Gaussian process model. To validate our approach we use a battery aging dataset collected on a self-developed testbed, where we used a wide current level range to age battery packs in accelerated fashion. Prediction results show that our model can be successfully calibrated and generalizes across all applied load levels.

Parametric optimisation on the performance of the journal bearing using Taguchi approach

Hydrodynamic journal bearings are widely used to support high-speed rotating equipment due to their excellent strength and load-bearing capacity. Therefore, bearings are essential mechanical elements to improve the quality of rotating equipment. Bearing performance depends on various factors but pressure and frictional torque plays a vital role in load carrying capacity of bearing. In this present work, both experimental and analytical approach of a typical journal bearing has been carried out to determine the optimal performance of the bearing. Taguchi-based optimisation method has been proposed for journal bearing. Taguchi L27 orthogonal array has been planned to study peak pressure and frictional torque with three input parameters speed, load and viscosity index. The result shows that loading criterion influences much on performance of bearing. The experimental data is obtained from a journal bearing test rig and the analytical data are generated by MINITAB 18. From the experiment, it can be confirmed that speed – 2000 rpm, load – 600 N and viscosity index – 150 are the ideal process parameters for lower peak pressure and less frictional torque.

Coupling analysis of timing gear dynamics and three-dimensional mixed lubrication under multi-branch shafting of marine diesel engine

Timing gears are the fundamental transmission components of marine diesel engines, and their operational reliability and efficiency are significantly impacted by their health status. The performance of timing gears is influenced by external excitations from the branch drive shaft and load input, as well as internal excitations caused by time-varying meshing stiffness and transmission errors. Therefore, it exhibits pronounced nonlinear characteristics as a result of the coupling effect between variable dynamic loading and micro-mixed lubrication induced by surface roughness and shaft vibration. The timing gear of a specific marine 20 V diesel engine is selected as the subject of investigation in this study, taking into account the impact of various types of internal and external comprehensive excitation. The three-dimensional (3D) mixed lubrication state analysis model, influenced by the coupling dynamic effect, was expanded based on the dynamic load and speed fluctuation in conjunction with the 3D line contact mixed lubrication model. The results demonstrate that the accuracy of the model can be validated through vibration testing, simulation testing, and empirical formulas for elastohydrodynamic lubrication (EHL). Additionally, the meshing process results in significant rough peak contact between the shaved surface and the ground surface, leading to potential lubrication failure. By implementing an optimization scheme that incorporates shock absorbers, the maximum contact area ratio of the four actual machining surfaces is reduced to only 16.06 %. This effectively mitigates the issue of severe rough peak contact, enhances the lubrication condition of gear pairs, and offers theoretical guidance for tribological optimization design in marine diesel engine timing gears.

On 3D printed polyvinylidene fluoride-based smart energy storage devices

Polyvinylidene fluoride (PVDF) is one of the established thermoplastics with inherent piezoelectric characteristics. In the past two decades, a lot of work has been reported on the use of virgin Polyvinylidene fluoride thermoplastics for sensing applications. But hitherto little has been reported on 3D printing of secondary (2°) recycled Polyvinylidene fluoride as a smart energy storage device (ESD). This work is focused on exploring the possibilities for 3D printing of smart energy storage device comprising of Polyvinylidene fluoride having (melt flow index (MFI) 30 g/(10 min) as per ASTM D 1238) reinforced with MnO2, graphite, ZnCl2, and N [Formula: see text] Cl in different weight proportions to form a feedstock filament for fused deposition modeling (FDM) in the first stage. The MFI of Polyvinylidene fluoride composites reinforced with MnO2, graphite, ZnCl2, and N [Formula: see text] Cl (34.095, 8.480, 42.982, 11.807 g/(10 min) respectively) was ascertained for possible 3D printing on FDM. The results suggest that even with an acceptable MFI of prepared 2° recycled Polyvinylidene fluoride, the same was not printable. Further for possible 3D printing on FDM, low-density polyethylene (LDPE) was blended in a Polyvinylidene fluoride matrix, and successful 3D printing-based energy storage device was prepared in the second stage. The study also highlights the mechanical, and morphological properties of Polyvinylidene fluoride composites have been improved after processing with a twin-screw extruder (TSE) by using different input parameters (screw temperature (T), screw speed (S), and load (L)). Overall, the study suggests that the proportion of LDPE, MnO2, graphite, ZnCl2, and N [Formula: see text] Cl has a significant effect on the rheological, mechanical, and morphological properties. The results have been supported with scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and Fourier-transformed infrared spectroscopy (FTIR) analysis.

Optimal intensity measures in probabilistic seismic demand model of subway station

Ground motion intensity measure (IM), which is a key link between the seismic hazard analysis and structural seismic response analysis, plays an important role in the performance-based earthquake engineering framework. The objective of this paper is to evaluate the most commonly used IMs with respect to their capability to predict the seismic response of underground subway station structures. Because the properties of the surrounding soil has significant influence on the seismic response of subway station structure, four typical classes of engineering sites ranging from Class I to IV according to Chinese code for seismic design of urban rail transit structures are selected in this study. Dynamic time history analyses considering nonlinear soil-structure interaction (SSI) are performed on four two-dimensional finite element models consisting of two-storey three-span subway stations embedded in four different engineering sites in this paper. Both the near-fault without velocity pulse and far-fault ground motions are used as the seismic inputs for the nonlinear SSI models in this study. Ground motion excitation is converted into equivalent seismic load at the artificial boundary for the discretized finite element model to realize the seismic load input. The applicability of 20 ground motion IMs commonly used in earthquake engineering research are investigated in this study. Statistical regression analysis is carried out for those IMs and engineering demand parameters (EDPs) of the subway station structure measured by maximum inter-storey displacement ratio obtained from nonlinear time history analyses. Based on the criteria of efficiency, practicality, proficiency and sufficiency, the optimal IMs in probabilistic seismic demand model that can best estimate the seismic response of the subway station structure are identified among those commonly used IMs. It is found that for sites of Class I and Class II, the Arias intensity followed by the velocity spectrum intensity are the optimal candidates, and for sites of Class III and Class IV, the Arias intensity is the optimal IM.