Resistance-capacitance Network Research Articles

Economic model predictive control for building HVAC system: A comparative analysis of model-based and data-driven approaches using the BOPTEST Framework

Model Predictive Control (MPC) has demonstrated its capability to significantly enhance energy efficiency while ensuring indoor comfort. This study focuses on the development and fair comparison of two Economic Model Predictive Control(EMPC) frameworks with the goal of optimizing demand response for utility cost reduction and ensuring thermal comfort in residential buildings. The first framework, known as RC-MPC, utilizes a reduced-order thermal Resistance–Capacitance network model to represent the thermal dynamics of the building. It formulates the optimization problem as a Linear Programming (LP) task, which is solved using CPLEX. The second framework, known as ANN-MPC, employs an Artificial Neural Network model capture the thermal behavior of the building, It addresses a non-convex optimization problem through projected stochastic gradient descent. To evaluate the performance of these frameworks, experiments are conducted using a single-zone dwelling within the BOPTEST framework. The results demonstrate that both approaches effectively reduce operational costs and enhance comfort, achieving comparable performance and outperforming the baseline Rule-Based Control (RBC) method. The discomfort reductions range from 30% to 95%, and energy expense savings range from 17% to 34%. Furthermore, the study examines the impact of various MPC hyperparameters. The findings highlight that a proper control horizon and formulating the objective function accurately are crucial for achieving optimal control performance. Additionally, tightening the comfort range is found to be important in managing the comfort violations, and the choice of solver can influence both the control performance and computational efficiency.

Development of ECG Common Mode Rejection Ratio Automatic Test System

To comprehensively meet the test requirements for the common mode rejection ratio (CMRR) across different ECG-particular standards, this paper presents the design of an ECG CMRR automatic test system. The hardware component primarily consists of a test signal generation module, an automatic control network (which includes a resistance-capacitance network control module and a polarization voltage control module), and a noise level switching module. The software portion enables automatic control and user interaction. Experimental results indicate that the system is stable, reliable, and highly automated, capable of satisfying the test requirements of various ECG-particular standards, thus demonstrating a promising application prospect.

A dynamic discrete model of ventilated concrete floor integrated with solar air collector under the effect of uneven direct solar radiation

Abstract A system combining the ventilated concrete floor (VCF) with solar air collector (SAC) in buildings has been applied in the western Sichuan Plateau for nighttime heating. However, the dynamic model coupled with uneven solar radiation of SAC-VCF is absent, thus the thermal behavior of the system is difficult to predict in practice. In this research, a coupled model is built to predict the thermal characteristics of the room with the SAC-VCF system under uneven solar radiation. The calculation model of VCF considers the uneven distribution of solar radiation on the floor surface, established by combining the resistance-capacitance (RC) network model and the number of transfer unit model (NTU) using the discrete method and validated by experimental data. A 3R2C model is utilized to model envelopes, validated by simulation results. The calculation error of surface temperature and room air temperature is within 5%. Then a case study is conducted with the validated model to predict the thermal performance of the SAC-VCF system with even and uneven solar radiation. Results indicate that under uneven solar radiation, the local surface temperature significantly increases to 35.1 °C, 9.1 °C higher than even solar radiation. Meanwhile, under uneven solar radiation, the heat transfer of supply air and surface of VCF is increased by 14% and 6%, respectively. Besides, the room air temperature is almost equal of two cases, while the operative temperature is 0.4 °C lower under uneven solar radiation. The model is beneficial to further study the influencing factors of this system.

The lithium battery state of charge estimation based on the fractional order unscented kalman filter algorithm

Abstract In the assessment of the state of charge (SOC) of lithium batteries, it has been observed that the conventional integer-order second-order resistance-capacitance (RC) network falls short in accurately replicating the non-linear attributes and the precision of SOC estimation influenced by the internal polarization reaction within the battery. Thus, we present the incorporation of constant-phase element (CPE) and Warburg components to achieve a model with superior recognition accuracy compared to the conventional second-order equivalent circuit model(ECM). The parameterization is carried out using the particle swarm optimization algorithm, resulting in enhanced robustness of parameter identification. Later on, when we mixed the regular Unscented Kalman Filter (UKF) algorithm with the fractional-order model (FOM), we obtained an algorithm to estimate the SOC of lithium battery in real time, named FOUKF, and compared FOUKF with the integer-order Extended Kalman Filter (EKF) and UKF algorithms. This confirms that the model is reliable and the algorithm’s estimation is accurate.

Design of illusion device in the electro-quasi-static field

Abstract Illusion devices have important applications in military fields because they can change the scattering pattern of objects. In this paper, the illusion conditions in the electro-quasi-static (EQS) field when transient excitation is applied are first deduced. According to the conditions derived, the illusion in the EQS field can be realized. Three representative cases are considered, one for the invisibility situation and two for the illusion situation. Moreover, the evolution of potential with time and its relationship with the excitation is determined. The result has been verified by analytical solution and finite element simulation. Finally, the possible realization of the illusion is discussed by equating the illusion device to the resistance-capacitance network. We also discuss the potential improvement of the device by using reconfigurable components in the device.

The impact of ECPELLA on haemodynamics and global oxygen delivery: a comprehensive simulation of biventricular failure

BackgroundECPELLA, a combination of veno-arterial (VA) extracorporeal membrane oxygenation (ECMO) and Impella, a percutaneous left ventricular (LV) assist device, has emerged as a novel therapeutic option in patients with severe cardiogenic shock (CS). Since multiple cardiovascular and pump factors influence the haemodynamic effects of ECPELLA, optimising ECPELLA management remains challenging. In this study, we conducted a comprehensive simulation study of ECPELLA haemodynamics. We also simulated global oxygen delivery (DO2) under ECPELLA in severe CS and acute respiratory failure as a first step to incorporate global DO2 into our developed cardiovascular simulation.Methods and resultsBoth the systemic and pulmonary circulations were modelled using a 5-element resistance‒capacitance network. The four ventricles were represented by time-varying elastances with unidirectional valves. In the scenarios of severe LV dysfunction, biventricular dysfunction with normal pulmonary vascular resistance (PVR, 0.8 Wood units), and biventricular dysfunction with high PVR (6.0 Wood units), we compared the changes in haemodynamics, pressure–volume relationship (PV loop), and global DO2 under different VA-ECMO flows and Impella support levels.ResultsIn the simulation, ECPELLA improved total systemic flow with a minimising biventricular pressure–volume loop, indicating biventricular unloading in normal PVR conditions. Meanwhile, increased Impella support level in high PVR conditions rendered the LV–PV loop smaller and induced LV suction in ECPELLA support conditions. The general trend of global DO2 was followed by the changes in total systemic flow. The addition of veno-venous ECMO (VV-ECMO) augmented the global DO2 increment under ECPELLA total support conditions.ConclusionsThe optimal ECPELLA support increased total systemic flow and achieved both biventricular unloading. The VV-ECMO effectively improves global DO2 in total ECPELLA support conditions.

A comparison between grey-box models and neural networks for indoor air temperature prediction in buildings

Model Predictive Control has gained much attention due to its potential to improve building operations by reducing costs, integrating renewable energy sources, and increasing thermal comfort. This paper aims to compare the accuracy of grey-box models based on resistance–capacitance (RC) networks and Long-Short-Term Memory (LSTM) neural networks in the prediction of the buildings’ thermal response, which is a key feature for the successful implementation of predictive controllers. Indoor air temperature prediction tests have been performed on simulated and measured data from buildings with different thermal insulation and thermal mass during both heating and cooling seasons. Results show that neural networks have, on average, a better prediction performance than grey-box models. Both modelling approaches are affected by the building characteristics and by the season considered. The grey-box models require less training data, although the latter seems to play a role only in the worse-performing tests. When user setpoint changes in the testing phase, the LSTM neural network shows a significant drop in the root mean square error. In conclusion, although LSTM outperforms grey-box models on average, the reduced training data and higher reliability under normal operating conditions, as well as their linearity, make RC models a strong alternative for predictive controllers.

Frequency adaptive conductivity measurement based on reverse approximation

Accurately measuring the solution conductivity is important both for environmental assessment and process monitoring. A reverse approximation frequency adaptive conductivity test method is proposed in this paper. This method avoids the complex calculation of the time constant τ of the first-order resistance-capacitance network and eliminates the influence of the accessory capacitance on the measurement results to the greatest extent. Through 9 groups of optimal frequency selection experiments, the optimal measurement frequency of R1 and Rx fixed ratio in a certain range is obtained. The optimal measurement frequency and dimensionless relationship model constitute a complete frequency adaptive solution conductivity measurement method.Through comparative analysis, the mean absolute percentage error of the measurement results is 2.65%, which not only improves the measurement accuracy of the existing self-developed equipment but also provides a new solution to solve the influence of additional capacitance in the conductivity measurement process.

A Comparative Assessment of Different Aerogel-Insulated Building Walls for Enhanced Thermal Insulation Performance.

Aerogel is widely recognized as a superinsulating material with great potential for enhancing the thermal insulation performance of building walls. It can be applied in various forms such as aerogel plasters (AP), aerogel fibrous composites (AFC), and aerogel concrete (AC) in practical engineering applications. This study aims to investigate the most efficient application form for maximizing building insulation performance while minimizing the amount of aerogel used. To predict the thermal insulation performance of aerogel-insulated walls, a resistance-capacitance network model integrating the aerogels' effective thermal conductivity model was developed and was validated by comparing it with Fluent simulation software results in terms of surface temperature. Using the validated models, the thermophysical parameters, transient thermal properties, and transmission load were predicted and compared among AP, AFC, and AC walls. The results indicate that using AFC can result in approximately 50% cost savings to achieve the same thermal resistance. After adding a 20 mm thickness of aerogel to the reference wall without aerogel, the AFC wall exhibited the highest improvement in thermal insulation performance, reaching 46.0-53.5%, followed by the AP wall, and then the AC wall, aligning with considerations of microstructural perspectives, thermal resistance distributions, and thermal non-uniformity factors. Therefore, giving priority to AFC use could reduce the required amount of silica aerogel and enhance economic efficiency. These results provide valuable insights for theoretical models and the application of aerogel-insulated walls in building engineering insulation.

An extended Kalman-Bucy filter for state of charge estimation of 2-RC network modelled Li-ion battery

Li-ion batteries have increased dramatically in the automobile industry over the past few decades. Lithium-ion batteries are viewed more favourably due to their high energy density, specific energy, etc. Optimising the performance of lithium-ion batteries requires accurate modelling and estimation of the state of charge (SOC). This article introduces an efficient second-order resistor-capacitor (2RC) network battery model and an optimised extended Kalman-Bucy filter (EKBF) as the most effective way to model a battery and estimate its state of charge (SOC). The operating parameters of a lithium-ion battery are measured with the least-squares curve fitting method. At a temperature of 20 °C, the proposed method for estimating SOC has a mean absolute error (MAE) of 0.72 % and a root mean square error (RMSR) of 0.71 %. In addition, the operational characteristics of the proposed EKBF were validated by simulating its operation at temperatures ranging from 0 °C to 40 °C. Under all conditions, the proposed method maintained an average error rate of 0.40%. The output of the proposed topology was validated using OPAL-RT (OP5700) hardware-in-the-loop real-time simulator. Consequently, the proposed method is preferable for accurate and dependable SOC estimation in real-time battery management system (BMS) applications.

The effect of intra-aortic balloon pumping on hemodynamics and left ventricular load in Impella-supported condition: A simulation study

Abstract Introduction Intra-aortic balloon pumping (IABP) is a commonly used percutaneous mechanical circulatory support device. Although IABP combined with Impella, a percutaneous left ventricular assist device, has shown positive outcomes in a few case reports of acute heart failure, its hemodynamic and left ventricular (LV) unloading effects remain unclear. Purpose We conducted a simulation study to clarify the clinical benefits of adding IABP to Impella-supported conditions. Methods We used SimulinkⓇ for cardiovascular simulation. The systemic and pulmonary circulation were modelled by using a 5-element resistance-capacitance network with four ventricles represented by time-varying elastance and unidirectional valves (Figure 1A). We compared total systemic flow, coronary perfusion pressure (CPP), and pressure-volume relationships (PV loop) in severe LV dysfunction (LV end-systolic elastance: 0.2 mmHg/mL) under three scenarios: IABP with a 40 mL balloon volume added to baseline, IABP added to Impella CP support at P2 (partial support) and P8 (total support) (Figure 1B). Results As shown in Figure 2A, IABP increased total systemic flow and CPP, and shifted the PV loop to the left. In P2-Impella condition, the addition of IABP increased native cardiac output (0.3 to 0.7 L/min) and total systemic flow (2.7 to 2.9 L/min), while decreased Impella pump flow due to increased afterload of Impella during diastole. IABP further moved PV loop leftward and reduced LV pressure-volume area (PVA) by -3.8% from Impella only and -7.8% from baseline (Figure 2B). In P8-Impella condition, IABP did not change total systemic flow, CPP, or PV loop (Figure 2C). Conclusions The addition of IABP to Impella could increase CPP while increasing Impella pump afterload and decreasing Impella flow. Overall, IABP slightly increased total systemic flow and decreased LV workload in Impella partial support condition. In specific clinical situations, IABP has the potential to be used as adjuvant therapy alongside Impella partial support.Figure 1

Insight into the evolution of electrical properties for Schottky-barrier IGZO thin-film transistors with Cu-based Schottky contacts

In this work, we performed systematic electrical characterization and analysis of indium–gallium–zinc oxide (IGZO) Schottky-barrier thin-film transistors (SBTFTs) with different Cu-based Schottky contact structures. It was found that the Schottky barrier height (ΦB) between the IGZO layer and the Cu electrode could be modulated notably by changing the thickness of the AlOx tunnel layer, and the variation in ΦB significantly changed the saturation drain current (Idsat) of the IGZO SBTFTs based on the Schottky contacts but only had a minor influence on the saturation voltage (Vdsat) of the devices. Furthermore, Cu/Al stacked source/drain electrodes and silicon nitride (SiNx) passivation were employed to tailor the contact resistance and channel resistance of the IGZO SBTFTs, which led to an increase in Idsat and a variation in Vdsat. A universal resistance–capacitance network model was proposed to explain the observed evolution of Vdsat of the SBTFTs with different device structures. This work provides meaningful insight into developing low-cost metal oxide SBTFTs with tailored device performances.

Reachable set estimation and stochastic sampled-data exponential synchronization of Markovian jump neural networks with time-varying delays

In this paper, the stochastic sampled-data exponential synchronization problem for Markovian jump neural networks (MJNNs) with time-varying delays and the reachable set estimation (RSE) problem for MJNNs subjected to external disturbances are investigated. Firstly, assuming that two sampled-data periods satisfy Bernoulli distribution, and introducing two stochastic variables to represent the unknown input delay and the sampled-data period respectively, the mode-dependent two-sided loop-based Lyapunov functional (TSLBLF) is constructed, and the conditions for the mean square exponential stability of the error system are derived. Furthermore, a mode-dependent stochastic sampled-data controller is designed. Secondly, by analyzing the unit-energy bounded disturbance of MJNNs, a sufficient condition is proved that all states of MJNNs are confined to an ellipsoid under zero initial condition. In order to make the target ellipsoid contain the reachable set of the system, a stochastic sampled-data controller with RSE is designed. Eventually, two numerical examples and an analog resistor–capacitor network circuit are provided to show that the textual approach can obtain a larger sampled-data period than the existing approach.

The impact of aortic valve regurgitation on the combination therapy of VA-ECMO and Imeplla support in severe cardiogenic shock: a simulation study

Background: The utilization of a combination of veno-arterial extracorporeal membrane oxygenation (VA-ECMO) and Impella, ECPELLA, has become widespread among patients with cardiogenic shock. The utilization of VA-ECMO in the presence of aortic regurgitation (AR) can result in significant left ventricular (LV) distention. Additionally, the implantation of Impella via the aortic valve frequently induces AR clinically. We established a simulation model and evaluated the impact of AR on hemodynamics under ECPELLA. Furthermore, assuming that the reverse flow of AR is strongly determined by aortic pressure (AP) level, we simulated a scenario where AP was further decreased. Methods: We employed Simulink® (Mathworks, Inc.). The systemic and pulmonary circulations were modeled using a 5-element resistance-capacitance network. Four cardiac chambers were represented by time-varying elastance. We compared the aortic regurgitant flow (Far), total systemic flow (Ftotal), and LV pressure-volume relationship under various severities of AR and varying Impella (0-3.7 L/min) and VA-ECMO (0-5 L/min) flows. AR grades were adjusted by the regurgitant resistance and classified as mild, moderate, and severe, mimicking a clinical scenario. Results: Without AR, ECMO significantly increased Ftotal and raised LV end-diastolic pressure (LVEDP). Impella increased Ftotal and decreased LVEDP. The concomitant presence of AR exacerbated the increase of LVEDP by ECMO and the reduction of LVEDP by Impella. Under ECPELLA support (VA-ECMO: 3 L/min) with mild AR, the increase of Impella support (1 to 3.5 L) increased Ftotal and Far, while decreasing LVEDP, indicating the prevention of AR-induced LV distention. Additionally, the presence of mild AR prevented the Impella-induced left ventricular suction that is commonly observed under ECPELLA support with high-flow VA-ECMO. In the case of moderate AR, while the hemodynamic trends were similar to those observed under mild AR, Impella was unable to prevent the increment of LVEDP to a critical level (< 20 mmHg). However, by decreasing AP through reducing resistance (e.g. vasodilators), both Far and LVEDP were dramatically reduced and Ftotal was increased under ECPELLA support. Conclusion: The concomitant presence of AR in ECPELLA condition increased LV load, while prevented LV suction. The use of vasodilator in ECPELLA with AR could attenuate AR, increase systemic perfusion, and reduce LV load. The optimal control of Impella and VA-ECMO flows and AP can maximize the hemodynamic and LV unloading impacts of ECPELLA. no funding This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Preliminary neutronics and thermal analysis of a heat pipe cooled traveling wave reactor

Heat pipe cooled traveling wave reactor (HPTWR) is a novel concept of heat pipe reactor, which adopts neutron breeding wave to pursue Uranium-Plutonium breeding. In this paper, the cladding material, power output, and axial breeding fuel region length of the HPTWR are optimized in order to achieve the safe operation of reactor with reactor neutronics and HP thermal analysis. Monte Carlo neutron transport code RMC is used to obtain the neutronics results (reactivity, consumption and breeding of nuclear fuel, and power distribution). A heat pipe (HP) code based on thermal resistance–capacitance network model (TRCNM) is developed to analyze the heat transfer characteristics of HP using the power distribution of fuel element obtained by RMC code in the optimized HPTWR. Results show the optimized HPTWR can achieve 70 MWth power output and 46 years continuous operation. The highest temperature peak of HP wall in the highest power fuel element of reactor appears at beginning of cycle (BOC) and is about 1800 K. Due to the flattening of axial power distribution with propagation of traveling wave, the temperature peak of HP wall gradually decreases to about 1784.6 K at end of cycle (EOC), which can reduce the thermal stress of HP wall and improve the safety of reactor. The corresponding heat transfer margin of HP in the highest power fuel element is always above 19.0% during the whole reactor operation, which helps to ensure the safe operation of the optimized HPTWR.

Li-ion battery charge transfer stability studies with direct current impedance spectroscopy

The safety of lithium-ion batteries is closely related to the charge transfer process inside the battery. With the rapid increase in battery usage, battery safety issues have become increasingly prominent. Due to technical limitations, the current battery thermal failure management system cannot realize risk early warning. Charge transfer resistance (Rct) is a macroscopic parameter characterizing the battery transport process, which can be detected by electrochemical impedance spectroscopy (EIS). Due to the high cost of EIS test equipment and high signal-to-noise ratio requirements, it is still not applicable to electric vehicles. In addition, Rct is affected by ambient temperature and battery aging, which brings challenges to online safety diagnosis. Here we propose a method to obtain the activation energy of a battery using direct current impedance spectroscopy (DCIS), which enables the stability diagnosis of the charge transport process. DCIS is a time-domain impedance spectroscopy technique. It uses the time constant characteristic of the internal resistor–capacitor network to detect battery parameters. Activation energy is the energy barrier for lithium-ions to cross the electrode/electrolyte interface and can indicate the stability of the charge transport process. Since activation energy is a microscopic parameter, it is not affected by temperature and aging, which is beneficial for battery safety diagnosis. The experimental results show that the charge transfer process of the sample cells with a state of health (SOH) greater than 80% is stable. When the SOH is less than 80%, the activation energy drops rapidly from 0.55 eV to 0.16 eV, indicating an increased risk of thermal runaway. Since DCIS supports online detection, it provides an option for safety diagnosis of electric vehicle batteries.

Distributed state-of-charge estimation for lithium-ion batteries with random sensor failure under dynamic event-triggering protocol

The state of charge (SOC) performs as an indicator of the remaining capacity of the Lithium-ion batteries (LBs). An accurate SOC estimation of LB is of great significance for its operation optimization and life extension of the battery. In this article, the issue of distributed SOC estimation is addressed for LBs. To design the distributed filter for SOC estimation, the equivalent circuit model comprised of the resistor–capacitor networks, Warburg element, ohmic resistance, battery current and voltage is established. In order to reflect the properties of the random sensor failure (RSF) well, a set of Bernoulli-distributed sequences with known probabilities is introduced. The communication resources over the wireless networks are usually limited, for the purpose of saving communication resources, the dynamic event-triggering mechanism (DETM) is adopted to regulate transmission of the signals. The main objective of this article is to design a distributed SOC estimation approach for LBs subject to RSF under DETM over the sensor networks. The upper bound of the estimation error covariance is first ensured and then such upper bound is minimized by parameterizing the estimator gain. In addition, by virtue of the matrix simplification technique, the issue of sensor network topology’s sparseness is effectively tackled. At last, experimental examples are employed to validate the feasibility of the developed distributed SOC estimation algorithm.

Mixed [formula omitted] and passive exponential synchronization for singular Markov jump neural networks based on hybrid event trigger scheme

This article considers the driving-response-based exponential synchronization issue for delayed singular Markov jump neural networks by virtue of hybrid event triggering strategy. By employing singular value decomposition method, the regularity and impulse-freeness of synchronization error system are obtained. Under the framework of hybrid event-triggered scheme, the novel exponential admissibility conditions, mixed H∞ and passive performance are acquired by establishing improved Lyapunov–Krasovskill functional and dealing with nonlinear neuron activation function. Furthermore, the desired synchronization state feedback controller is designed by virtue of linear matrix inequalities. Finally, a numerical example and an analog resistance-capacitance network circuit are used to verify the effectiveness and practicability of the method.

Research on Transient Temperature Rise Measurement Method for Semiconductor Devices Based on Photothermal Reflection

In this article, a transient temperature rise measurement method for semiconductor devices based on photothermal reflection is proposed. The relationship between the reflectivity of a 360 nm laser beam and the device temperature is studied. Through the appropriate design of the optical circuit and the data acquisition system, measurement of the transient temperature rise characteristics of GaN-based microwave power devices is realized. In combination with resistor-capacitor network impulse response theory, the transient temperature rise curve is processed using the Bayesian iterative deconvolution method. By extracting the thermal time constant, nondestructive characterization of the temperature increase and thermal resistance characteristics of each material layer in the heat flow path is achieved, and the complementary relationship between the temperature change in the active region during heating and the device heat dissipation characteristics is verified. Additionally, the forward Schottky junction characteristics method and infrared thermal imaging are used to measure the channel temperature for verification of the proposed thermal reflection method. These measurements indicate that the proposed method can provide accurate results.

Abstract 13632: The Optimization of Mechanical Circulatory Support Device Combination Considering Ventricular Load in Biventricular Failure Condition: A Simulation Study

Backgrounds: Recently, the combination of Impella, a percutaneous transvalvular left ventricular assist device, and veno-arterial extracorporeal membrane oxygenation (ECMO) have improved the survival rate of cardiogenic shock by its powerful hemodynamic support effect. Meanwhile, the optimal flow control of those devices remains unclear, especially in biventricular failure (BVF). In this study, we established the mathmatical cardiovasular simulation model, and evaluated how the combination therapy impacts both right (RV) and left (LV) ventricular loading. Methods: We used SimulinkⓇ (Mathworks, Inc.) for the simulation. Both the systemic and pulmonary circulation were modeled by using 5-element resistance-capacitance net-work. Four cardiac chambers were represented by time-varying elastance with unidirectional valves (Fig. 1). In LV dysfunction (LV end-systolic elastace was set at low level: 0.4 mmHg/ml), we compared the changes of right (RAP) and left (LAP) atrial pressure, as the marker of ventricular loading, under various RV function and Impella and ECMO flows. Results: Impella slightly increased RAP and reduced LAP regardless of RV systolic function (Fig. 2). In high pulmonary vascular resistance (PVR), the increase of Impella flow augumented RAP, while Impella could not be up-titrated more than 2.8 L/min due to LV suction (Fig. 3). In BVF with high PVR, ECMO decreased RAP and increased LAP in each Impella flow (Fig. 4). Higher ECMO and Impella flows rendered LV extremely small, induced suction, and increased RV preload and RAP. Conclusion: PVR is the major determinant of stable Impella support without inducing RV loading and LV suction. In BVF with high PVR, ECMO reduced RV loading, while decreased LV filling and induced LV suction by Impella. The preemptive simulation study for an individual patient may help the optimal use of mechanical circulatory support device to maximize RV and LV unloading with improving hemodynamics.