Zero-dimensional Model Research Articles

The 2021 release of the Quantemol database (QDB) of plasma chemistries and reactions

The Quantemol database (QDB) provides cross sections and rates of processes important for plasma models; heavy particle collisions (chemical reactions) and electron collision processes are considered. The current version of QDB has data on 28 917 processes between 2485 distinct species plus data for surface processes. These data are available via a web interface or can be delivered directly to plasma models using an application program interface; data are available in formats suitable for direct input into a variety of popular plasma modeling codes including HPEM, COMSOL, ChemKIN, CFD-ACE+, and VisGlow. QDB provides ready assembled plasma chemistries plus the ability to build bespoke chemistries. The database also provides a Boltzmann solver for electron dynamics and a zero-dimensional model. Thesedevelopments, use cases involving O2, Ar/NF3, Ar/NF3/O2, and He/H2O/O2 chemistries, and plans for the future are presented.

Modeling Multiphase Heat and Mass Transfer in an Agitated Filter Dryer by Integrating Experiment, Computations, and Analytical Solutions.

The drying of a wet cake consisting of an active pharmaceutical ingredient and solvent in an agitated filter-dryer is a critical and challenging unit operation in the pharmaceutical industry. The complexity of this operation is attributed to the constraints on product quality in terms of its physical properties in addition to the residual solvent content. In this manuscript, a better understanding of the drying mechanism is gained by integrating insights from three-dimensional analytical solutions and computational fluid dynamics simulations into a zero-dimensional model to explain experimental data. The approach provides the time evolution of the mass flow rate of solvent from the wet cake and the center-point temperature of the cake with good accuracy. Further investigation of the zero-dimensional model reveals important parameters such as the mass transfer rate number that predicts whether the process is convection-controlled or diffusion-controlled, and the thermal load of vaporization that estimates the fraction of solvent vaporized per unit time. These parameters can be useful in devising a drying protocol for agitated-filter dryers.

Kinetic investigation of plasma catalytic synthesis of ammonia: insights into the role of excited states and plasma-enhanced surface chemistry

The present work investigates the kinetics of catalytic ammonia synthesis in a N2/H2 mixture activated by a nanosecond pulsed discharge plasma experimentally and numerically. X-ray diffraction, high-resolution transmission electron microscopy and x-ray photoelectron spectroscopy are combined to characterize the morphology and surface electronic properties of the catalyst. Special attention is placed on the role of excited species in promoting the formation of important intermediates and the plasma-enhanced surface chemistry. A detailed kinetic mechanism consisting of atoms, radicals, excited species, molecules, ions, and surface species is developed and studied by incorporating a set of the electron impact reactions, reactions involving excited species, ionic reactions, direct and dissociative adsorption reactions, and surface reactions. A zero-dimensional model incorporating the plasma kinetics solver is used to calculate the temporal evolution of species densities in a N2/H2 plasma catalysis system. The results show that the coupling of Fe/γ–Al2O3 catalyst with plasma is much more effective in ammonia synthesis than the Fe/γ–Al2O3 catalyst alone and plasma alone. The numerical model has a good agreement with experiments in ammonia formation. The path flux analysis shows the significant roles of excited species N(2D), H2(v1), N2(v) in stimulating the formation of precursors NH, NH2, and adsorbed N(s) through the pathways N(2D) + H2 → NH + H, H2(v1) + NH → NH2 + H and N2(v) + 2Fe(s) → N(s) + N(s), respectively. Furthermore, the results show that the adsorption reaction N + Fe(s) → N(s) and Eley–Ridel interactions N(s) + H → NH(s), N + H(s) → NH(s), NH + H(s) → NH2(s) and NH2 + H(s) → NH3(s) can kinetically enhance the formation of ammonia, which further highlights the plasma-enhanced surface chemistry. This work provides new insights into the roles of excited species and plasma-enhanced surface chemistry in the plasma catalytic ammonia synthesis.

Investigation of suction pressure pulsation prediction of rotary compressor with total variation diminishing scheme and one-dimensional accumulator model

The suction pressure pulsation plays a significant role in rotary compressor performance, so employing gas dynamic model for simulation is critical for compressor performance prediction and structure design. Comparing with the conventional Lax-wendroff two-step (LW2) scheme which has been usually utilized with good behaviors of speed and stability, this paper adopted the total variation diminishing scheme with higher convergence speed and less dispersion. And the common zero-dimensional model for the accumulator is updated to a one-dimensional model achieving more accurate pressure results at the suction pipe inlet. The simulation results of instantaneous pressure are also compared with experimental measured data under different conditions. The Pearson Correlation Coefficient of simulated pressure curves are all higher than 0.9 and the relative errors of predicted performance are almost all less than 5%, which indicates better agreement on pressure pulsation simulation and performance prediction.

The Combined Effect of the Piston Bowl Geometry and Injection Fuel Pressure on the Compression Ignition Engine Characteristics

In this study, the combined effect of the piston bowl geometry and fuel injection pressures on combustion, performance and emission characteristics of compression ignition (CI) engine fueled with baseline Diesel (D100) and microalgae-biodiesel (MA100) was studied. In this paper, the comparison study for the two different piston bowl geometry, namely: hemispherical combustion chamber (HCC) and toroidal re-entrant combustion chamber (TRCC), was carried out with the various fuel injection pressures (200-240 bar) performed. A single-cylinder, direct injection, and four strokes were chosen to simulate the compression ignition (CI) engine by developing a zero-dimensional simulation model using Diesel-RK commercial software. The data was validated by comparing the results against experimental data, which showed that the results obtained from the numerical simulation were in good agreement with the experimental results. MPRR, EGT, HRR, BTE, and NOx exhibited an increase with increased fuel injection pressure, while an inverse trend was observed with ID, CO, and HC. When using MA100 biodiesel with HCC piston bowl geometry at fuel injection pressure (200 bar), the maximum predicted brake specific fuel consumption (BSFC) was 0.545 kg/kWh. A significant reduction of nitrogen (NOx) oxides emissions was also observed with low fuel injection pressures. In contrast, the emission characteristics such as hydrocarbons and CO were enhanced by increasing fuel injection pressure and modifying the piston bowl geometry.

An equivalent model of discharge instability in the discharge chamber of Kaufman ion thruster

The industrial application of the Kaufman ion thruster in its arc stage is limited owing to the instability of the discharge pulse. Presently, a complete prediction model that can predict the discharge pulse in the high-current stage does not exist. In this study, a complete prediction model for the pulse in the ion thruster is established using the zero-dimensional plasma discharge model and equivalent circuit model. The zero-dimensional plasma discharge model is used to obtain the corresponding plasma parameters by calculating the beam current, discharge current, voltage, and gas flow under actual working conditions. The input parameters of the equivalent circuit model are calculated using empirical formulae to acquire the estimated discharge waveforms. The pulse waveforms obtained using the model are found to be consistent with the experimental results. The model is used to evaluate the process of rapid changes in plasma density. Additionally, this model is employed to predict changes in the pulse waveforms when the volume of the discharge chamber and grid plate transmittance are changed.

Investigation of the scavenging process in two-stroke uniflow scavenging marine engines by a real-time multi-stage model

The increasing demand of digital twin marine engine requires real-time physical models for prediction. In two-stroke uniflow scavenging marine engines, a real-time physical model for the scavenging process is rarely found since it is difficult to describe the complex in-cylinder air motion. Without an accurate prediction of the fresh air loss and residual burned gas in the cylinder, the precision of combustion and emission simulation cannot be guaranteed as well. In a marine engine digital twin system, the scavenging ratio and fresh air skip are the vital for the further simulation of combustion and emission. To predict them in real-time, a novel zero-dimensional (0D) multi-stage scavenging model is proposed in this article. In the cylinder zone, the complex gas motion is ideally divided to four stages: exhaust gas blowdown, perfect displacement, displacement-mixing, and perfect mixing. The duration of each stage is determined by the engine design and control parameters. Then, the thermodynamic conditions at each stage are simulated to obtain the mass of residual burned gas, fresh air inlet, and outlet. The results of the 0D model agree well with the results of the CFD simulation, and the mean relative errors of temperature, pressure, and total mass do not exceed 3%, 4%, and 2%, respectively, which indicates the potential for the two-stroke marine engine digital twin system. It could also be applied in a control-oriental engine model or engine diagnostics in the future.

Automated generation of 0D and 1D reduced-order models of patient-specific blood flow.

Three-dimensional (3D) cardiovascular fluid dynamics simulations typically require hours to days of computing time on a high-performance computing cluster. One-dimensional (1D) and lumped-parameter zero-dimensional (0D) models show great promise for accurately predicting blood bulk flow and pressure waveforms with only a fraction of the cost. They can also accelerate uncertainty quantification, optimization, and design parameterization studies. Despite several prior studies generating 1D and 0D models and comparing them to 3D solutions, these were typically limited to either 1D or 0D and a singular category of vascular anatomies. This work proposes a fully automated and openly available framework to generate and simulate 1D and 0D models from 3D patient-specific geometries, automatically detecting vessel junctions and stenosis segments. Our only input is the 3D geometry; we do not use any prior knowledge from 3D simulations. All computational tools presented in this work are implemented in the open-source software platform SimVascular. We demonstrate the reduced-order approximation quality against rigid-wall 3D solutions in a comprehensive comparison with N=72 publicly available models from various anatomies, vessel types, and disease conditions. Relative average approximation errors of flows and pressures typically ranged from 1% to 10% for both 1D and 0D models, measured at the outlets of terminal vessel branches. In general, 0D model errors were only slightly higher than 1D model errors despite requiring only a third of the 1D runtime. Automatically generated ROMs can significantly speed up model development and shift the computational load from high-performance machines to personal computers.

On combustion instability induced by water condensation in a low-pressure exhaust gas recirculation system for spark-ignition engines

Water condensation in low-pressure exhaust gas recirculation systems is a concern because of a potential impact on components durability, but its implication into the operation of modern spark-ignition engines has not been investigated in detail. In this work, such aspects are evaluated by tests in a turbocharged multi-cylinder engine installed in a climatic test bench. First, a previously developed and validated zero-dimensional model is used to identify conditions where condensation is produced inside the water charge-air cooler, so that the compressor durability and operation is not affected. Then, different engine points are tested with a constant 25% of recirculated rate. Results show that combustion instability can increase up to 6% (absolute) due to droplets accumulation and release inside the water charge-air cooler, confirmed by an endoscope at the WCAC outlet . The evaporation of these droplets during the intake stroke causes charge overleaning in specific cycles, affecting combustion and inducing occasional misfires. Consequently, the fuel consumption and unburned hydrocarbons can be increased up to 4% and 30%, respectively, compared to the results achieved without condensation. The low speed and load condition was clearly the most affected by the sudden dilution given the lower in-cylinder temperatures. The combustion model shows that condensation formation and eventual overleaning phenomenon is increased if low or zero-carbon fuels such as natural gas, methanol, hydrogen or ammonia are used. Results showed an increased temperature for condensation compared to a traditional gasoline, around 10 ∘C for methane and methanol and 20 ∘C for hydrogen and ammonia.

Numerical simulation method of surge experiments on gas turbine engines

In order to obtain the surge margin of an aero-engine during its operation, an engine surge experiment is required. A multi-dimensional simulation method for an aero-engine is established in this paper. The simulation of a surge experiment using high-pressure air-injection is then carried out on a turbo-shaft engine to obtain the surge boundary using this method. More specifically, firstly, a body-force model is employed to calculate the compressor performance owing to its capability of capturing the main three-dimensional features of compressor surge and avoiding excessive simulation time required by the traditional fully-three-dimensional Reynolds Averaged Navier-Stokes (RANS) method. Then, a one-dimensional model combining a lumped-parameter plenum model is used for the combustor to account for the propagation of pressure waves and the heat-release process, and a zero-dimensional throttle model is used to mimic the choking effect at the turbine nozzle. Finally, the air-injection system is modeled by imposing an injection boundary condition, which can be used conveniently in changing injection parameters. Based on the established method, the influences of different test parameters, such as the air-injection location, the pressure, the orifice size, the number of injection orifices, and the injection time duration on the surge characteristics and boundary are further studied, which offer effective guidance to optimize an actual experimental design.

Prediction of heat release and NOx emissions for direct-injection diesel engines using an innovative zero-dimensional multi-phase combustion model

Most of the current zero-dimensional (0D) predictive combustion models for diesel engines are based on their simple artificial assumptions rather than actual diesel spray processes, resulting in poor prediction accuracy. Conventional multi-zone models have good prediction performance but a long CPU time. This paper presents an innovative mechanism-based 0D multi-phase combustion model for direct-injection diesel engines. This model was primarily developed to reduce the CPU time for the zero/one-dimensional (0D/1D) simulation of engine performance and improve the optimization efficiency. The main idea of the model was accurately partitioning the spray zone according to different combustion mechanisms based on the concentration field of diesel spray. A representation method of each combustion phase based on the information of concentration field and equivalent injection velocity was proposed. In particular, some special modeling efforts were made to describe the diffusion combustion phase entirely and concisely. Diffusion combustion in different concentration areas exhibited different mechanisms, and diffusion combustion after the end of injection showed a slower burn rate than that during the injection process. All the different conditions of diffusion combustion were considered in this model based on the proposed representation method. Moreover, the in-cylinder temperature was divided into two zones to evaluate the NOx emissions. Extensive experiments were performed using two different diesel engines. The influence of engine speed, injection timing, load, and injection pressure on the combustion process and NOx emissions were investigated. High prediction accuracy was confirmed over a wide operating range. The prediction accuracy of both the heat release rate and NOx emissions of the proposed model was found to be comparable to that of a conventional multi-zone packet model. Compared with the packet model, the proposed model could reduce more than 90% of the CPU time, which significantly improved the engine performance simulation and optimization efficiency.

Model for Rating a Vanadium Redox Flow Battery Stack through Constant Power Charge–Discharge Characterization

A method for estimating the stack rating of vanadium redox flow batteries (VRFBs) through constant power characterization was developed. A stack of 22 cells, each with 1500 cm2 of nominal electrode area, was constructed and tested using constant current and constant power protocols. Typical ratios of charging to discharging power that prevail in various applications (e.g., peak shaving, wind power/solar photovoltaic power integration) were employed in the test protocols. The results showed that fractional energy storage capacity utilization and round-trip energy efficiency varied linearly with the power at which the energy was charged or discharged. A zero-dimensional electrochemical model was proposed based on the area-specific resistance to account for the energy stored/extracted during constant power discharge in the state of charge (SoC) window of 20% to 80%. It was shown that this could be used to rate a given stack in terms of charging and discharging power from the point of view of its application as a power unit. The proposed method enables stack rating based on a single polarization test and can be extended to flow battery systems in general.

A novel liquid metal MHD enhanced Closed-Brayton-Cycle power generation system for hypersonic vehicles: Thermodynamic analysis and performance evaluation with finite cold source

Closed-Brayton-cycle (CBC) is a potential thermodynamic cycle for high-power dynamic electricity generation on hypersonic vehicles, but finite cold source onboard limits its power level. This study presents a liquid metal MHD (LMMHD) enhanced CBC power generation system and exhibits its theoretical advantages through thermodynamic analysis. The influence of cold source temperature rise, turbine inlet temperature and LMMHD conversion efficiency on system performance is investigated by a zero-dimensional power optimization model, and the electric power and power generation efficiency between LMMHD enhanced CBC and standalone CBC are compared. Results indicate that LMMHD enhanced CBC can theoretically meet the demand for megawatt-class power generation on hypersonic vehicles, the electric power per unit fuel mass flowrate of which can reach 637.84 kW. High-temperature liquid metal and well-designed LMMHD generator are extremely essential to improve the turbine inlet temperature and LMMHD conversion efficiency. Compared with standalone CBC, the electric power increased percentage of LMMHD enhanced CBC is as high as 92.44 %. This paper provides primary performance evaluation for LMMHD enhanced CBC, the key technical issues of which, including the LMMHD generator structure design, mixing and separation process optimization, will be the focus in our next work.

Low-cost numerical lumped modelling of lithium-ion battery pack with phase change material and liquid cooling thermal management system

This study is aimed at developing a low cost lumped model for simulating a Li-ion battery pack with thermal management systems (TMS) under continuous charging/discharging cycles. The considered system is composed of twenty-four commercial Li-ion batteries with phase change material (PCM) and nine aluminium tubes for liquid coolant circulation. A zero-dimensional numerical model is developed based on the transient energy balances and the analogy between heat transfer and electrical transfer using resistances and capacitors. The simulations were carried at 3-C discharging/0.5-C charging rates and obtained results were compared with both three-dimensional computational fluid dynamic (CFD) results and experimental results from the literature. The effect of various system design and operating characteristics such as the cooling method, the coolant temperature and its velocity, the number of coolant pipes and the ambient conditions on the system performance were presented and analysed. Results show that combining both PCM and liquid cooling for battery thermal management leads to reduce the maximal battery temperature by about 38 °C and 4 °C compared to natural convection thermal management mode and to passive PCM thermal management mode, respectively. Increasing the number of cooling pipes improves the performance of the system and its optimal number in this system is up to 9 pipes. The maximal battery cells temperature is reduced from 31 °C to 20 °C as the used liquid coolant inlet temperature is reduced from 25 °C to 10 °C. Finally, the suggested low cost lumped model is a promising tool for simulating, designing and optimising battery pack with thermal management systems under real exploitation conditions.

A zero-dimensional model for atmospheric non-thermal plasma CO2 hydrogenation: insights into the reaction mechanism

Recently, plasma CO2 hydrogenation to generate valuable products (e.g. CO and CH4, hydrocarbons and oxygenates) has attracted more and more attention. The conversion of carbon dioxide (CO2) and hydrogen (H2) in an atmospheric non-thermal plasma was investigated by a zero-dimensional plasma kinetic model. This paper focuses on the effect of different feed gas composition ratios (H2/CO2 volume ratio) on the plasma CO2 hydrogenation reaction mechanisms. It is found that H2 addition in plasma not only promotes CO2 dissociation but also changes the plasma chemistry, which seems to significantly enhance the electron density and temperature. Besides, larger H2 content in the H2/CO2 mixture is beneficial to obtaining a higher number density of methanol, which is in good agreement with published experimental data. The temporal distributions of abundant radicals, ions and molecule densities are determined under a series of initial hydrogen content. Conversions of inlet H2/CO2 and selections toward CO and CH4 are calculated and presented. The primary reaction channels related to the production and destruction of CO, H, CH2O, CH3OH, CH4 and H2O are determined. Finally, the underlying overall reaction mechanisms regarding the plasma CO2 hydrogenation are analyzed in detail by the chemical reaction flow chart.

(Digital Presentation) A Zero-Dimensional Physics-Based Model for Lithium Carbon Monofluoride (Li/CFx) Batteries

Lithium carbon monofluoride primary batteries have a high energy density (2180 Wh/kg of active materials based on the typical discharge potential) and low self-discharge. They have traditionally been used in medical devices like pacemakers with low rates of several years [1]. The high energy density of Li/CFx batteries also make them attractive for higher rate uses like aerospace or military applications; however, rate capability and heat generation can pose a significant challenge at higher rates. The theoretical potential of a CFx battery is around 4.5 V, but practical cells operate at 3 V or lower. The ~1.5 V overpotential is attributed to the strength of the C-F bonds, which results in slow kinetics and significant heat generation, especially when considering high rate (e.g., >C/10) and energy dense cell designs. Other challenges include the deposition of insulating lithium fluoride and large volume changes in each electrode [2].Our work focuses on a high-energy density primary battery with a CFx cathode and lithium anode, designed for high rates with intermittent pulse power requirements. Physics-based modeling is an important tool that can clarify underlying mechanisms and help guide design to satisfy multiple constraints. To understand the challenges posed by this chemistry at higher rates, we have developed a zero-dimensional (0D) physics-based model that captures some of the complex phenomena within the CFx cathode. Included in the model are kinetics described by a concentration-dependent expression, changing porosity and electrochemical active area, and Nernstian thermodynamics. The model may also include a treatment of methods that increase the capabilities beyond the typical limits for the CFx chemistry. The implications of various conditions will be explored, such as the effect of the porosity and loading. The model results will be compared to experimental data from coin cells.AcknowledgmentsThe authors would like to thank the Intelligence Advanced Research Projects Agency for funding this work.References Zhang, K. J. Takeuchi, E. S. Takeuchi, and A. C. Marschilok, Phys. Chem. Chem. Phys., 17, 22504 (2015).S. Zhang, D. Foster, J. Wolfenstine, and J. Read, J. Power Sources, 187, 233 (2009).

Understanding Capacity Fade in Organic Redox-Flow Batteries Using Uncertainty Quantification Techniques and Zero-Dimensional Modeling

We introduce the use of Bayesian uncertainty quantification to provide data-informed assessments of the probability of different hypotheses of reactant decay, and to estimate reactant decay parameters from experimental data with quantified uncertainty. As a case study, we use these techniques to extract rate constants describing the nucleophilic attack of quinone-based RFB reactants by water, as measured using in operando ultraviolet-visible spectrophotometry. We then introduce a zero-dimensional electrochemical flow cell model3 which can simulate capacity fade given a reactant decay mechanism and associated parameters, and the cycling protocol. This work has the potential to shed light on the relationship between capacity fade and reactant decay in various organic RFB chemistries, and to enable prediction of the lifetimes of commercial-scale RFBs.(1) Brushett, F. R.; Aziz, M. J.; Rodby, K. E. On Lifetime and Cost of Redox-Active Organics for Aqueous Flow Batteries. ACS Energy Letters 2020, 879-884. DOI: 10.1021/acsenergylett.0c00140. Dieterich, V.; Milshtein, J.; Barton, J.; Carney, T.; Darling, R.; Brushett, F. Estimating the Cost of Organic Battery Active Materials: A Case Study on Anthraquinone Disulfonic Acid. Translational Materials Research 2018.(2) Kwabi, D. G.; Ji, Y.; Aziz, M. J. Electrolyte Lifetime in Aqueous Organic Redox Flow Batteries: A Critical Review. Chemical Reviews 2020.(3) Modak, S.; Kwabi, D. G. A Zero-Dimensional Model for Electrochemical Behavior and Capacity Retention in Organic Flow Cells. Journal of The Electrochemical Society 2021, 168 (8), 080528. DOI: 10.1149/1945-7111/ac1c1f.

Predicting Cell Cycling Performance in Redox Flow Batteries Using Reduced-Order Analytical Models

Achieving decarbonization across multiple sectors (e.g., electricity generation, transportation, manufacturing) requires widespread adoption of renewable energy technologies, which demand energy storage solutions to enable sustainable, reliable, and resilient power delivery.1 To this end, redox flow batteries (RFBs) are a promising grid-scale energy storage platform, owing to their improved scalability, simplified manufacturing, and long service life.2 However, state-of-the-art RFBs remain too expensive for broad adoption, motivating the development of novel electrolyte formulations and reactor designs to meet performance, cost, and scale targets for emerging applications.3 While many recently-reported next-generation materials offer short-term performance improvements and the potential for cost reductions when produced at-scale, they often complicate system operation over extended durations due to a multitude of interrelated parasitic processes (e.g., side reactions, crossover, species decomposition) which lead to capacity fade and efficiency losses.3,4 Such processes challenge the establishment of quantitative and unambiguous connections between individual component properties and overall cell behavior. Here, we aim to develop mathematical models that translate fundamental material properties to cell performance metrics, enabling more informed design criteria for system engineering.In this presentation, we introduce an analytically-derived, zero-dimensional modeling framework to predict cell cycling behavior in RFBs. While previously-developed zero- and one-dimensional models demonstrate accurate performance predictions when compared to experimental systems, they must solve coupled differential equations using numerical methods.5,6 As a result, these approaches become computationally expensive for multi-cycle simulations (i.e., 10s – 100s of cycles), frustrating their implementation in system design and optimization. By deriving analytical solutions to these models, we can markedly reduce computation times and enable analyses hitherto unachievable.To demonstrate the utility of this modeling framework, we explore several representative scenarios that examine the connection between RFB material properties, operating conditions, and performance (i.e., power output, accessible capacity, efficiency). Additionally, we investigate the impact of different parasitic processes on capacity fade, highlighting the effects of species decomposition and crossover in durational cell cycling. Finally, we discuss several modalities for expanding this framework to include additional sources of performance losses and for integrating these models into larger computational schemes (e.g., optimization, parameter estimation, techno-economic assessments). The mathematical models developed in this work have potential to advance foundational understanding in RFB design, leading to quantitatively informed selection criteria for emerging candidate materials. Acknowledgments This work was supported by the Joint Center for Energy Storage Research, an Energy Innovation Hub funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences. B.J.N gratefully acknowledges the NSF Graduate Research Fellowship Program under Grant Number 1122374. J.L gratefully acknowledges support from the MIT Materials Research Laboratory REU Program, as part of the MRSEC Program of the NSF under grant number DMR-14-19807. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. References S. Chu and A. Majumdar, Nature, 488, 294–303 (2012).M. L. Perry and A. Z. Weber, J. Electrochem. Soc., 163, A5064–A5067 (2016).F. R. Brushett, M. J. Aziz, and K. E. Rodby, ACS Energy Lett., 5, 879–884 (2020).M. L. Perry, J. D. Saraidaridis, and R. M. Darling, Current Opinion in Electrochemistry, 21, 311–318 (2020).M. Pugach, M. Kondratenko, S. Briola, and A. Bischi, Applied Energy, 226, 560–569 (2018).S. Modak and D. G. Kwabi, J. Electrochem. Soc., 168, 080528 (2021).

Organic Redox Flow Batteries: Insights from Experimental and Numerical Study

Secondary batteries are the key technology for the sustainable development of electrical grids with a high share of renewable power generation. Among different battery technologies, Organic Redox Flow Batteries (ORFBs) are considered one of the most promising solutions for low-cost large-scale energy storage systems thus avoiding the social and environmental issues associated with extraction of raw materials for large batteries. Mathematical modeling of ORFBs, that complements experimental testing, is a key tool that helps to understand and analyze the behavior of particular candidates, including electrolytes, membranes and geometrical parameters, on a battery level at operating conditions that are close to operational.In this study, we present a single-cell zero-dimensional model based on our previous works [1,2] extended for simulation of redox flow batteries with different organic redox-couples. The model is based on the general mass and charge conservation principles. Hence, it can simulate a wide range of RFB systems with different scales and electrolytes. The key feature of the model is the approach for the determination of integral mass-transfer coefficient on the electrode-electrolyte interface that allows describing non-linear polarization behavior at high current densities. Such approach makes the model very flexible and esilty extadable even to the other types of batteries with hybrid configurations (e.g. solid boosters). The kinetic parameters were also fitted for the effective single-step heterogeneous redox mechanisms at positive and negative electrodes in the case when activation losses treatment was needed to reproduce the experimental polarization curves. In addition, the model simulates the dynamic behavior of the cells working with different redox-couples in the wide range of loading currents and electrolyte flow rate and thus allowing to explore their performance at different operating conditions. Validation of the model showed a good agreement with experimental data (average error less than 5%) in the range of current decities of 20 – 150 mA cm-2.The model was also used for investigation of scalability of the considered ORFBs analyzing their performance on the level of industial-scale systems.The influence of internal processes on the battery behavior has been studied and the effect of mass-transport limitations has been estimated. The key parameters (coulombic, voltage, energy efficiencies and electrolyte utilization) of the batteries have been computed for the wide range of current densities and flow rates. The obtained results provide important insights for reserachers and ingeneers to develop reliable and efficient organic RFB systems applicable for grid-scale energy storage systems.

Energy loss and comprehensive performance analysis of a novel high-efficiency hybrid cycle hydrogen-gasoline rotary engine under off-design conditions

The rotary engine is a potential power device for unmanned aerial vehicle. In this paper, a novel X-type hydrogen-gasoline rotary engine using high efficiency hybrid cycles (HEHCs) is proposed to realize the high efficiency and low carbon dioxide emission. Firstly, the zero-dimensional single-zone models are established for the X-type rotary engine using theoretical (ideal cycle and ideal working fluid of air), ideal (ideal cycle and real working fluid) and real (real cycle and real working fluid) HEHCs. The type I and II losses are introduced to indicate the energy losses from theoretical HEHC to ideal HEHC and from ideal HEHC to real HEHC, respectively. Furthermore, the effects of hydrogen doping fraction of gasoline-hydrogen hybrid fuel, ignition angle and rotational speed on type I and II losses are studied. Finally, the variation trends of cycle efficiency, indicated power, indicated fuel cost and indicated carbon dioxide emission (ICDE) are revealed under different operation conditions. The results show that the increasing hydrogen doping fraction rises the type I and II losses, while the increasing ignition angle or rotational speed declines the above losses. The maximum cycle efficiencies of real HEHC with pure gasoline and hydrogen doping fraction of 0.3 are 42.6% and 41.5% at the optimal ignition angles of 330° and 345°, respectively. The cycle efficiency of real HEHC is increased by 1.3% at the rotational speed of 9000 rpm with the increase of hydrogen doping fraction of 0.3. The indicated fuel cost and ICDE for the hydrogen doping fraction of 0.3 is 19.2% higher and 28.2% lower than that for pure gasoline under optimal ignition angles, respectively. The increasing hydrogen doping fraction reduces the effect of rotational speed on the cycle efficiency, indicated fuel cost and ICDE.