Effects Of Parameter Variations Research Articles

Influence of the connection topology on the performance of lithium-ion battery pack under cell-to-cell parameters variations

In order to meet the energy and power requirements of large-scale battery applications, lithium-ion cells have to be electrically connected by various serial-parallel connection topologies to form battery pack. However, due to the cell-to-cell parameters variations, different connection topologies lead to different performance of the battery pack. Therefore, knowledge of correlations of the connection topology on the performance of battery pack is worth investigating. Based on a simplified analytical circuit model, this paper derives the capacity, voltage, discharge power and energy of the pack with different connection topologies by transformation algorithm. Thus, we use Monte Carlo simulation to quantify the effects of parameters variations on usable capacity and power of the pack under four typical connection topologies under random sampling. The capacity mean and variance expressions of the battery pack with different topologies are obtained. The results show that the battery pack with cell firstly connected in parallel and then assembled in series can better reduce the influence of cell parameters variation, achieve more performance and greatly increase the usable capacity and energy utilization. Moreover, increasing the quantity of serial or parallel connected cells can reduce the discrete coefficients of capacity of the packs. The main conclusions are of great benefit to the battery manufacturer, electric vehicles and energy storage systems applications.

Uncovering the effects of heterogeneity and parameter sensitivity on within-host dynamics of disease: malaria as a case study

BackgroundThe fidelity and reliability of disease model predictions depend on accurate and precise descriptions of processes and determination of parameters. Various models exist to describe within-host dynamics during malaria infection but there is a shortage of clinical data that can be used to quantitatively validate them and establish confidence in their predictions. In addition, model parameters often contain a degree of uncertainty and show variations between individuals, potentially undermining the reliability of model predictions. In this study models were reproduced and analysed by means of robustness, uncertainty, local sensitivity and local sensitivity robustness analysis to establish confidence in their predictions.ResultsComponents of the immune system are responsible for the most uncertainty in model outputs, while disease associated variables showed the greatest sensitivity for these components. All models showed a comparable degree of robustness but displayed different ranges in their predictions. In these different ranges, sensitivities were well-preserved in three of the four models.ConclusionAnalyses of the effects of parameter variations in models can provide a comparative tool for the evaluation of model predictions. In addition, it can assist in uncovering model weak points and, in the case of disease models, be used to identify possible points for therapeutic intervention.

Optimal design of two viscous dampers for multi-mode control of a cable covering broad frequency range

For the conventional design of viscous dampers attached to cables, only the first few modes are of interest. However, a recent cable vibration event occurred on the Sutong Bridge highlights that the higher mode vibrations of cables also need to be controlled. To this end, a novel optimal design of two viscous dampers near to a cable anchorage is explored which can broaden the control frequency range covering both the lower and higher modes. In the proposed design scheme, the one damper nearest to the cable anchorage is targeted for lower-mode control and the other damper is targeted for higher-mode control. The mode shape characteristics of a cable with two viscous dampers, which is prerequisite for optimal damper design, are investigated. Based on that, the optimal design of the two dampers in a cable is simply reduced to two individual designs of one single viscous damper, which can lower the design complexity. The control performance of the proposed design both for lower and higher vibration modes is numerically validated by a cable on the Sutong Bridge and compared with the conventional design considering only lower vibration modes. Finally, the effects of parametric variations of the two dampers in the proposed design are discussed. It is shown that the proposed design using two dampers can both increase damping ratios of cables for lower and higher vibration modes, and the acceleration response of the cable is effectively reduced to around 60% of that using the conventional design.

Effect of variations in layer thickness and resilience modulus on flexible pavement performance

A pavement mechanistic-empirical analysis is based on a pre-designed structure checked for required performance criteria. In case the latter are not met, this structure is modified and reprocessed. In this context, analyzing the effect of variations in project parameters on pavement performance prediction subsidizes a better understanding of results provided by computer programs. The objective of this study is to assess the effect of layer thickness and resilience modulus variations on flexible pavement performance. To do so, performance was estimated for the 20th project year through Elastic Layered System Model 5 (ELSYM5) software and American Association of State Highway and Transportation Officials (AASHTO) Mechanistic-Empirical method (ME). Using multiple regression models for result adjustment and through statistical assessments on regression coefficients calculated, it can be concluded that pavement lifespan consumption, predicted by simulations on ELSYM5, is sensitive to variations in coating and subbase thickness and in subgrade resilience modulus. For AASHTO ME method, predicted values for distresses were significantly sensitive to variations in coating, base and subbase thickness, and in base and subgrade resilience modulus. Comparing both approaches, it is concluded that ELSYM5 can be a viable alternative to the application of a ME pavement design method.

Hybrid power management for DC microgrid cluster

DC microgrid clusters enhance reliability and effective utilization of resources. In this paper, a hierarchical power management strategy is proposed for two DC microgrids interconnected through dual active bridge (DAB) converter. The control hierarchy consists of droop control to ensure proportional power sharing within the microgrid, DC bus signalling control which controls power exchange between two microgrids through DAB and droop shifting control to compensate the voltage drop caused by droop control. The amount of power to be exchanged between microgrids is determined through fuzzy logic controller based on DC bus voltages of microgrids. Then small signal model is developed to analyse the effect of parameter variation for stable operation of system. Finally the proposed strategy is validated through simulation using Matlab/Simulink.

CNTFET-based design of ternary logic gates with interchangeable standard positive and negative ternary output

This paper presents a novel CNTFET based design of ternary logics gates where all three ternary logics including standard, positive and negative ternary logic (ST, PT and NT) outputs for each gate are obtained from one structure and are interchangeable through some control inputs. Ternary logic overpowers the conventional binary logic in simplicity and energy efficiency as it reduces number of interconnects and chip area. In this paper design of ternary inverter, buffer, NAND, AND, NOR, OR, XOR and XNOR gates are presented where a unique feature of conversion between ST, PT, NT logic through a single output is being introduced. Besides a single logic gate is designed for a particular logic function and its complement combining both ternary and binary logic gate design technique. The proposed designs utilize the unique property of CNTFET, such as assigning the required threshold voltage value of the FET by changing the diameter of the carbon nanotube (CNT) through its chiral vector values which is very useful in designing multiple- valued logic (here ternary logic). The proposed circuits are simulated using Synopsys HSPICE with 32 nm CNTFET model provided by Stanford University and in each case average power values and propagation delays are duly noted. The effects of variation in some process parameters like channel length, dielectric oxide thickness and number of carbon nanotubes also have been discussed.

Measurement of changes in torsional stiffness of press‐formed paperboard packages induced by heat load utilizing a developed measuring device

AbstractThe press‐forming process and the effects of parameter variation on the forming process have attracted great interest lately. The dimensional accuracy of the formed trays and the rigidity and stability of the packages are crucial factors for functionality in packaging lines, especially in fast operating machinery. The torsional stiffness of trays must be at a sufficient level to ensure the functionality in subsequent processes and logistics. The objective of this study was to develop and build a device for measuring the torsional stiffness of whole tray packages, to verify its functionality and to investigate the effect of heat load transferred to paperboard material on the torsional stiffness of the formed trays. The operation of the novel torsional stiffness tester was confirmed, and the tester was found to be suitable for measuring the thermal response of the sample materials and the effect of the fibre direction. Thus, the analysed material does not need to have a homogeneous stiffness property since the differences are noticeable in the measurement results. In addition, the results indicate that tray blanks should be die cut in the machine direction of the paperboard. The torsional stiffness of the tray packages increases, and the outer dimensions decrease as a function of the heat input. The first feature is desirable for packaging functionality and the second feature can be compensated by competent packaging design. To conclude, the use of higher mould temperatures is recommendable if the integrity of the package material is not compromised.

A new adaptive deep neural network controller based on sparse auto‐encoder for the antilock bracking system systems subject to high constraints

AbstractWe contribute in the current paper to extend the universal function approximation property of deep learning hybrid strategy to design both : (a) adaptive deep neural network observer to estimate derivatives of the tracking error dynamics (b) and robust deep neural network (DNN) output feedback control scheme (OFCS) that will overcome successfully effects of both parametric variations and modeling errors. First, the designed controller employs OFCS to linearize the partially known antilock bracking (ABS) dynamics, and then, the dynamic compensator is involved to stabilize the linearized system. However, conventional controllers suffer from limitations due to the presence of these high uncertainties. Therefore, we aim to demonstrate for the first time in the control area the feasibility of applying deep learning algorithm based on sparse auto‐encoder as an approximator for neglected dynamics and uncertain parameters of the ABS. The estimated states are used as inputs to the neural network (NN) and in the adaptation laws as an error signal. Simulations of the proposed control algorithm based adaptive DNN observer are conducted then compared to bang–bang controller, PI controller, and adaptive controller‐based single hidden layer‐neural network with only one‐neuron in hidden layers (SHL(1N)NN) to demonstrate its practical potential. Furthermore, both feasibility and efficiency of involving deep learning algorithm (DLA) in the control area have been successfully confirmed through robustness test.

Modeling of crystallization fouling on a horizontal-tube falling-film evaporator for thermal desalination

Scale formation within horizontal-tube falling-film evaporators is an important issue for thermal desalination, because of the deterioration of heat transfer performance and added maintenance costs. Predicting the fouling process is crucial for desalination plant design, operation, and maintenance. In this paper, a model is developed to predict the crystallization fouling process during seawater falling-film flow over a horizontal tube bundle. The scaling is estimated based on deposition theory, with couple heat transfer including the in-tube steam condensation, conduction through the tube wall and the scale layer, and falling-film evaporation. The spatial and temporal variations of temperature, heat transfer coefficient, and scale thickness are predicted, and the effects of variations in process parameters of steam, feed seawater, and tube properties on the scale thickness, evaporation rate, and heat transfer coefficient for falling-film evaporation are analyzed. Comparisons to existing experimental data show the scaling layer thickness falls in the general range of reported measurements, with a slight overestimation due to neglecting the delay of scaling onset under real conditions. The scale layer thickness increases dramatically as the in-tube steam pressure is increased or the seawater flow rate is decreased. In general, the scaling layer becomes thicker on the lower tubes in the tube bundle, due to the heat and mass transfer of the falling film. The effect of tube material on scaling appears mainly dependent on thermal conductivity; thus, using polymer rather than a stainless steel tube decreases scaling and evaporation rate 96% and 88%, respectively. This work has potential to guide thermal desalination plant design, material selection, and operating parameter optimization.

Effects of Mill Speed and Air Classifier Speed on Performance of an Industrial Ball Mill

Nowadays, ball mills are widely used in cement plants to grind clinker and gypsum to produce cement. The research focuses on the mill speed as well as air classifier speed effect on the two compartment Cement ball mill performance in terms of Blaine, Sulphur trioxide contents, mill power, mill residue and mill residence time. Special importance was assigned to the study of the specific surface area and the surface area production rate, both during the variation with the mill speed and the air classifier speed. Within the content of this work, sampling campaigns were organized around a cement grinding circuit and varying cement ball mill speed as well as an air classifier speed at various dosage feed rate. The fact that such an examination has not been made previously by using industrial data rather than lab scale makes this work unique. The fineness is measured in terms of Blaine number. Mill speed and air classifier speed were the investigating parameters. It was deduced that depending on the speed of mill and air classifier, their effects on Blaine, SO3, mill power and mill performance were varied, ultimately all of them improved the performance of grinding and classification operations. The rapid expansion of ceramic wastes in China has raised great many interests in their sustainable uses in building materials The micro ceramic powder can be taken as a supplementary cementitious material to replace cement up to 40% for tuning the microstructure and mechanical properties of blend cement materials. The Blaine quality dictates strength, setting time and overall performance of cement. Optimum performance of ball mill could potentially refine Blaine fineness, thereby improving the cement quality. This study investigates the effects of separator speed and mill speed on Blaine fineness, mill residue, consumed power. Five speed levels used in closed cycle grinding mill are 200, 400, 600, 800 and 1000 rpm. The capacities were determined to obtain product Blaine surface areas in the limits between 2000 cm2 / gram and Variations in clinker feed rate, mill speed and separator speed could proportionally impact the grain quality of Blaine. When the separator speed is increased from 850 to 900 rpm the Blaine is increased from 2800 to 3000 cm2/g and mill residue decrease from 15 to 10 microns. Therefore, optimum parametric combination could reduce power consumption while improving the cement quality. Knowledge of effects of parametric variations on the quality of end product could be helpful for controlling product quality. Furthermore, proper grinding of clinker produces fine Blaine at first place and reduces the need for recycling of coarse grains.

Unbalanced currents effect on the thermal characteristic and reliability of parallel connected power switches

In many industrial applications, parallel connection of power semiconductor switches is widely used to achieve higher power levels and fault-tolerant operation. But there is a current imbalance between parallel connected switches in practical applications. In this research, the impact of unbalanced currents on the junction temperature and the reliability of parallel connected switches are quantified and analyzed. Markov based reliability model is developed for quantitative assessment of reliability for parallel switches under different current sharing. The Mean Time to Failure (MTTF) is calculated for different conditions to be used as reliability metric for comparison of various conditions. A sensitivity analysis is also presented to show the effect of parameter variation on the junction temperatures of devices and reliability of the system. At last, a downscaled setup has been built up and tested. Experimental results verify the theoretical analysis and confirm procedure. Also, junction temperatures of power semiconductor devices are measured using thermal camera.

Suppression of Residual Vibration in Nonlinear Systems With Temporal Variation and Uncertainty in Parameters by Elimination of the Natural Frequency Component

Abstract A systematic approach is developed for determining a control input for the point-to-point control of an overhead crane that exhibits temporal variation of rope length in addition to damping and nonlinearity, without inducing residual vibration. Complete suppression of the residual vibration is achieved by eliminating the natural frequency component of the cargo from the apparent external force, which is defined to include the effects of damping, nonlinearity, and parameter variation. Furthermore, an effective technique previously proposed by the authors for improving robustness to the modeling error of the natural frequency is extended. Numerical simulation results show that, even when cargo is hoisted up or down during operation, the proposed method realizes accurate positioning of the cargo without inducing residual vibration and sufficiently improves robustness. To the best of our knowledge, this is the first frequency-domain robust open-loop control strategy that ensures a theoretical zero amplitude for residual vibration in the absence of modeling error in nonlinear crane hoisting operation. The developed method is not only a contribution to the realization of low-cost and efficient crane hoisting operation, but is also applicable to the control of other nonlinear damped systems that include time-varying parameters.

Energy, exergy, exergoenvironmental, and economic assessments of the multigeneration system powered by geothermal energy

In this article, a new geothermal powered multigeneration system is proposed and analyzed via energy, exergy, economic, and exergoenvironmental points of view as well as parametric study to see the effects of main parameter variations. This multigeneration system includes a new configuration of the organic Rankine cycle with two evaporators and expanders, heater, NaClO system, and reverse osmosis. The products of this proposed system are electricity, hydrogen, heating, potable water, and salt. Due to theoretical analysis, this system produces 1.264 GWh of electrical energy, 15.93 GWh heating, 1919 Ton salt, 86400 m3 of potable water, and 4.397 × 107 m3 of hydrogen, annually with 60% and 21% of the system energy and exergy efficiencies. The organic Rankine cycle and reverse osmosis systems have the highest and lowest percentage of exergy destruction rates. The economic analysis reveals that the system payback period is 5.3 years. The system's net present value is 668.2 million US$. The exergoenvironmental analysis shows that the exergoenvironmental, environmental damage effectiveness, and the exergy stability factors for the proposed system are 0.86, 4.414, and 0.8, respectively. The parametric study shows that increasing the geo-fluid mass flow rate, increases the system's electrical power production and exergy efficiency while decreases the system exergy efficiency.

Expected seismic performance of gravity dams using machine learning techniques

Methods for the seismic analysis of dams have improved extensively in the last several decades. Advanced numerical models have become more feasible and constitute the basis of improved procedures for design and assessment. A probabilistic framework is required to manage the various sources of uncertainty that may impact system performance and fragility analysis is a promising approach for depicting conditional probabilities of limit state exceedance under such uncertainties. However, the effect of model parameter variation on the seismic fragility analysis of structures with complex numerical models, such as dams, is frequently overlooked due to the costly and time-consuming revaluation of the numerical model. To improve the seismic assessment of such structures by jointly reducing the computational burden, this study proposes the implementation of a polynomial response surface metamodel to emulate the response of the system. The latter will be computationally and visually validated and used to predict the continuous relative maximum base sliding of the dam in order to build fragility functions and show the effect of modelling parameter variation. The resulting fragility functions are used to assess the seismic performance of the dam and formulate recommendations with respect to the model parameters. To establish admissible ranges of the model parameters in line with the current guidelines for seismic safety, load cases corresponding to return periods for the dam classification are used to attain target performance limit states.

MRI-Based Radiomics Analysis for the Pretreatment Prediction of Pathologic Complete Tumor Response to Neoadjuvant Systemic Therapy in Breast Cancer Patients: A Multicenter Study.

Simple SummaryThe prediction of pathologic complete response (pCR) to neo-adjuvant systemic therapy (NST) based on radiological assessment of pretreatment MRI exams in breast cancer patients is not possible to date. In this study, we investigated the value of pretreatment MRI-based radiomics analysis for the prediction of pCR to NST. Radiomics, clinical, and combined models were developed and validated based on MRI exams containing 320 tumors collected from two hospitals. The clinical models significantly outperformed the radiomics models for the prediction of pCR to NST and were of similar or better performance than the combined models. This indicates poor performance of the radiomics features and that in these scenarios the radiomic features did not have an added value for the clinical models developed. Due to previous and current work, we tentatively attribute the lack of significant improvement in clinical models following the addition of radiomics features to the effects of variations in acquisition and reconstruction parameters. The lack of reproducibility data meant this effect could not be analyzed. These results indicate the need for reproducibility studies to preselect reproducible features in order to properly assess the potential of radiomics.This retrospective study investigated the value of pretreatment contrast-enhanced Magnetic Resonance Imaging (MRI)-based radiomics for the prediction of pathologic complete tumor response to neoadjuvant systemic therapy in breast cancer patients. A total of 292 breast cancer patients, with 320 tumors, who were treated with neo-adjuvant systemic therapy and underwent a pretreatment MRI exam were enrolled. As the data were collected in two different hospitals with five different MRI scanners and varying acquisition protocols, three different strategies to split training and validation datasets were used. Radiomics, clinical, and combined models were developed using random forest classifiers in each strategy. The analysis of radiomics features had no added value in predicting pathologic complete tumor response to neoadjuvant systemic therapy in breast cancer patients compared with the clinical models, nor did the combined models perform significantly better than the clinical models. Further, the radiomics features selected for the models and their performance differed with and within the different strategies. Due to previous and current work, we tentatively attribute the lack of improvement in clinical models following the addition of radiomics to the effects of variations in acquisition and reconstruction parameters. The lack of reproducibility data (i.e., test-retest or similar) meant that this effect could not be analyzed. These results indicate the need for reproducibility studies to preselect reproducible features in order to properly assess the potential of radiomics.

Analytical Modeling and Performance Analysis of Surface Potential for Junctionless MOSFET

The advancement in semiconductor technology requires small devices with low power consumption. This paper presents an analytical modeling of surface potential for junctionless MOSFET. Parabolic approximation is utilized to find out the surface potential. The effect of device parameter variation on surface potential and electric field has been studied. The variation in gate work function has been investigated for surface potential. Moreover, the consequence of variations in device parameters like drain bias, gate length ratio, radius of silicon pillar and doping concentration are also inspected. It is found that present device shows an excellent behaviour for future VLSI chips. The analytical results are matched with the TCAD results which validates the model.

WITHDRAWN: Characterizing flow due to segmental contraction of the small intestine and their impact on digestion

Abstract A theoretical model for segmental contractions of the small intestine is developed using lubrication method. Here, the nonlinear partial differential equations governing the fluid flow were normalized in viscous regime and solved semi-analytically for a power law fluid under long wavelength approximation on a MatlabTM platform. The segmental contraction was defined as a sinusoid with choice for variation in the wavelength, occlusion and frequency of luminal closure to study the effects of parametric variation (base values of the parameters were chosen as – n = 1.0, f*=6 wave•min-1, t*=T*3/4 sec, L*=20 cm, R*=1 cm, λ*=2 cm, and pocc, max*=0.5) on the flow for fluid of different viscosity, and flow behavior index of 0.5 (pseudo-plastic), 1.0 (Newtonian), 1.2 (dilatants) and 1.5 (dilatants). Pressure was specified as Dirichlet boundary conditions at the ends of the intestinal segment and velocity as no-slip boundary condition on the wall. Flow was characterized by determining the spatial distribution of the pressure, shear stress and flow rate along the length of the intestine during luminal closure at its maximal radial velocity. Study indicates that segmentation leads to the pressurization of the lumen (with a formation of a plateau at the middle) during closure and generation of vacuum during opening of the lumen. For four-wave segmentation, shearing is highest at the 1st and 4th mid-occlusion in comparison to 2nd and 3rd mid-occlusion. Parametric study indicates that the flow is sensitive to – the span of segmentation or wavelength of the wave, occlusion of the wave and frequency of the contraction; with shearing being highest for dilatants. Wavelength has an effect of altering the flow to within the span of the wavelength of the wave with no change in magnitude of shearing. However, contractions show preference for an optimal value of wavelength; above and below this values leads to inefficiency. Shearing is more prominent at higher occlusion (>50%) and frequency (>6Hz). Further, mixing is more prominent at the steep regions of the wave; having intensity of mixing highest for the outer waves in comparison to waves at mid-region of the segmentation. The degree of friction offered to the non-Newtonian fluids increases for increase in frequency, wavelength and occlusion; but less sensitive to flow behavior index. Simulation indicate that the power demand is more when peristalsis is driven at higher frequency (f = 12wpm) in comparison to lower frequency (f = 1wpm). The power demand is found to be greater in segmentation and has the following precedence - frequency, wavelength, flow behavior index, and occlusion (up to 80%). The spatial variation of the mixing parameter, Rm, indicates that the mixing is confined, majorly, at the steep edges of the wave. Further, multiplicity of the wave gives rise to multiple zones of mixing which increases the rate of mixing of the contents. Suggesting that, the segmentation primarily serves the purpose of mixing. In conclusion, we speculate that the segmentation facilitates digestion of the contents by enhancing the mixing, developing to-and-fro motion of the contents during events of periodic opening and closing of the lumen, increasing the enzymatic breakdown by increasing the surface area of solutes and delivering them within the proximity of the enzymes, and absorption.

Dual-band fiber optical parametric amplification in a structure of highly nonlinear photonic crystal fiber

We investigate fiber optical parametric amplification (FOPA) in a structure of an As2S3 core and TeO2 cladding photonic crystal fiber (PCF). Various amplification features such as wavelength area, parametric gain value, and bandwidth are investigated. In order to design the FOPA system with optimal features, effects of different structural parameters variation on optical features of the PCF and parametric gain subsequently are also investigated numerically based on the finite-difference time domain numerical method. Using 15 cm of this fiber and a continuous wave pump laser of 1.1 W, we attain a gain spectrum of 350 nm with a maximum value of 37 dB around 1550 and 1310 nm, which are favored wavelengths in optical telecommunication systems. In fact, our structure ends in a wideband amplifier in an absolutely compact size, which is optimized exactly for optical telecommunication applications.

Parameter variations in personalized electrophysiological models of human heart ventricles.

The objectives of this study were to evaluate the accuracy of personalized numerical simulations of the electrical activity in human ventricles by comparing simulated electrocardiograms (ECGs) with real patients' ECGs and analyzing the sensitivity of the model output to variations in the model parameters. We used standard 12-lead ECGs and up to 224 unipolar body-surface ECGs to record three patients with cardiac resynchronization therapy devices and three patients with focal ventricular tachycardia. Patient-tailored geometrical models of the ventricles, atria, large vessels, liver, and spine were created using computed tomography data. Ten cases of focal ventricular activation were simulated using the bidomain model and the TNNP 2006 cellular model. The population-based values of electrical conductivities and other model parameters were used for accuracy analysis, and their variations were used for sensitivity analysis. The mean correlation coefficient between the simulated and real ECGs varied significantly (from r = 0.29 to r = 0.86) among the simulated cases. A strong mean correlation (r > 0.7) was found in eight of the ten model cases. The accuracy of the ECG simulation varied widely in the same patient depending on the localization of the excitation origin. The sensitivity analysis revealed that variations in the anisotropy ratio, blood conductivity, and cellular apicobasal heterogeneity had the strongest influence on transmembrane potential, while variation in lung conductivity had the greatest influence on body-surface ECGs. Futhermore, the anisotropy ratio predominantly affected the latest activation time and repolarization time dispersion, while the cellular apicobasal heterogeneity mainly affected the dispersion of action potential duration, and variation in lung conductivity mainly led to changes in the amplitudes of ECGs and cardiac electrograms. We also found that the effects of certain parameter variations had specific regional patterns on the cardiac and body surfaces. These observations are useful for further developing personalized cardiac models.

Trigonal warping, satellite Dirac points, and multiple field tuned topological transitions in twisted double bilayer graphene

We show that the valley Chern number of the low energy band in twisted double bilayer graphene can be tuned through two successive topological transitions, where the direct bandgap closes, by changing the electric field perpendicular to the plane of the graphene layers. The two transitions with Chern number changes of -3 and +1 can be explained by the formation of three satellite Dirac points around the central Dirac cone in the moir\'e Brillouin zone due to the presence of trigonal warping. The satellite cones have opposite chirality to the central Dirac cone. Considering the overlap of the bands in energy, which lead to metallic states, we construct the experimentally observable phase diagram of the system in terms of the indirect bandgap and the anomalous valley Hall conductivity. We show that while most of the intermediate phase becomes metallic, there is a narrow parameter regime where the transition through three insulating phases with different quantized valley Hall conductivity can be seen. We systematically study the effects of variations in the model parameters on the phase diagram of the system to reveal the importance of particle-hole asymmetry and trigonal warping in constructing the phase diagram. We also study the effect of changes in interlayer tunneling on this phase diagram.