Wide Range Of Operating Conditions Research Articles

SPH-based numerical modelling and performance analysis of a heaving point absorber type wave energy converter with a novel buoy geometry

Heaving point absorber (HPA) is one of the most promising technologies to absorb wave energy. Accordingly in this work, performance of a HPA in terms of capture-width-ratio (CWR) under the effect of hydrodynamics forces were analysed using the SPH-based open-source package: DualSPHysics. 395 cases of simulations, which include five different geometries with different densities of the buoy, different buoy height to wave height ratios, and damping coefficients of the WEC over a range of wave frequencies were studied and optimum operational parameters were found for the novel buoy geometry named: “Super cuboid”. Compared to other geometries, it produced up to 23 % of efficiency increment over a wide range of operational conditions. Furthermore, the flow patterns and pressure variation around different buoy geometries were studied and found that an increase in the projected area of the buoy in vertical direction tends to increase the pressure force which results in increase of CWR. The CWR is also slightly enhanced by the bottom shape of the buoy. Hence it is expected that the use of this novel buoy shape, will contribute to the design of more sustainable and reliable WECs in the future.

A traction coefficient formula for EHL point contacts operating in the linear isothermal region

Many mechanical systems including rolling/sliding parts, require traction data across a spectrum of operating conditions to predict their motion effectively. Numerous studies have examined the thermal effects and shear-thinning concerning the traction curve, but only a few have focused on the traction coefficient in the linear isothermal regime for low SRR. In this work, we investigate traction coefficient characteristics of EHL point contacts in the linear isothermal regime, over a wide range of operational conditions. To this end, we conduct numerical simulations utilizing a fully-coupled finite element-based model, resulting in a prediction formula for the traction coefficient slope. With this formula, the traction coefficient slope could be predicted for the operating conditions considered.

Microwave-assisted hydrothermal processing of pine nut shells for oligosaccharide production

AbstractPine nut shells, a biomass residue from the Mediterranean Pinus pinea pine nut industrial processing, were treated by microwave-assisted autohydrolysis to produce xylo-oligosaccharides. Microwave-assisted processes provide alternative heating that may reduce energy input and increase overall process efficiency. The autohydrolysis treatments were performed under isothermal and non-isothermal operations within a wide range of operational conditions (temperature/reaction times) covering several severity regimes (as measured by the log R0 severity factor). The composition of the autohydrolysis liquors was determined in terms of oligo- and monosaccharides, aliphatic acids and degradation compounds. The process was highly selective towards hemicelluloses hydrolysis and liquid streams containing a mixture of oligomeric compounds (mainly xylo-oligosaccharides) could be obtained under relatively mild operation conditions (190 °C, 30 min) with a maximal oligosaccharides’ concentration of 18.48 g/L. The average polymerization degree of the obtained oligosaccharides was characterised by HPLC, showing that for the optimal conditions a mixture of oligomers with DPs from 2 to 6.

Dynamic Stabilization of a Centralized Weak Grid-Tied VSC System Considering PV Generator Dynamics

This paper addresses the instabilities and dynamic interactions in a centralized vector-controlled voltage-source converter interfacing a single-stage utility-scale photovoltaic (PV) generator to a high-impedance grid system. The dynamic resistance of the PV generator is considered, and effective active stabilization methods to guarantee the entire system's stability are proposed. Further, a complete state-space linearized model is developed, and different operating conditions alongside the maximum-power operation (MPO) are considered, such as fixed-voltage operation (FVO) and fixed-current operation (FCO). It is found that with the change of the PV generator operation from the FVO or MPO to the FCO region under the weak grid and nominal dc-link capacitance conditions, the dominant eigenmodes are relocated to the open-right-half-plane of the S-plane. This eventually induces inevitable high- and low-frequency oscillation instabilities. Further, it is found that medium-frequency oscillation instability is induced in the FVO region under a weak grid and reduced dc-link capacitance conditions. Active compensators are proposed to reduce the interaction dynamics and stabilize the entire system by reshaping the converter transfer functions; hence, the Nyquist stability criterion is maintained. Finally, detailed nonlinear time-domain simulation results are provided, showing the effectiveness of the proposed method in preserving the system's stability under a wide range of operation conditions.

A Fuel Cell’s Big Brother: Artificial Intelligence for Monitoring Fuel Cells

The operation of fuel cell stacks on test benches today is typically monitored by constantalarm threshold values for selected operating conditions. However, due to the wide range ofoperating conditions of the stacks, this type of monitoring only works for extreme maximumand minimum operating conditions. Wide setting ranges for thresholds prevent the detectionof minor faults, whereas too narrow limits will interrupt the tests unnecessarily. A particularchallenge is the monitoring of faults that either do not result in a directly measured responsefrom the fuel-cell stack or that only become noticeable with a time delay. The continuousimprovement of fuel cell stacks over the last years necessarily requires much-improvedmonitoring methods, especially for durability tests with an operating time of thousands ofhours. For this reason, a novel monitoring concept using AI-based methods for the operationof PEM fuel cells on test benches was developed and is being presented.Firstly, machine-learning based mechanisms for monitoring the operating conditions as setand controlled by the test bench are shown. Due to the cyclic operation during durabilitytests, the operating conditions set at a load point can be compared to the past operatingconditions at the same load point. This proceeding allows the early and accurate detection offaults caused by the test bench and thereby ensures the usability of the measured data aswell as an early alarm in case of problems.In addition, a digital twin based method for monitoring the condition of the fuel cell stack ispresented. The deep-learning based digital twin calculates a probabilistic prediction of theexpected voltage of the fuel cell stack based on the current and past operating conditions.The comparison of expected and measured cell voltage taking the model’s confidence intoaccount enables the early and precise detection of unforeseen events such as contaminationand thus averts consequential damage to the fuel cell stack. In contrast to physical models,the digital twin represents a data driven model-ling approach for fuel cells.The presented methods are applied to real testing data to demonstrate the detection of faultsduring the operation of fuel cell stacks on test benches that would have remainedundiscovered by today’s monitoring mechanisms. It shows that the data driven digital twin isable to predict the fuel cell’s stack voltage with an accuracy of 2.5 mV over 1000 h of unseendata. Figure 1

A numerical study on the blade–vortex interaction of a two-dimensional Darrieus–Savonius combined vertical axis wind turbine

To investigate power losses of a Darrieus–Savonius combined vertical axis wind turbine (hybrid VAWT) associated with the interaction between blades and wake, it is crucial to understand the flow phenomena around the turbine. This study presents a two-dimensional numerical analysis of vortex dynamics for a hybrid VAWT. The integration of a Savonius rotor in the hybrid VAWT improves self-starting capability but introduces vortices that cause transient load fluctuations on the Darrieus blades. This study attempts to characterize the flow features around the hybrid VAWT and correlate them with the Darrieus blade force variation in one revolution. Results demonstrate the capability of numerical modeling in handling a wide range of operational conditions: the relevant position of Savonius and Darrieus blades (attachment angle γ=0°−90°) and Savonius' tip speed ratio λS (0.2–0.8, varied Savonius' rotational speed). The torque increase in the Darrieus blade in hybrid VAWT (compared to a single Darrieus rotor) due to the appearance of the vortex shedding from the advanced Savonius blade is independent of the attachment angle and tip speed ratio. Apart from start-up and power performances of the hybrid VAWT, the most rapid force fluctuation is identified when the Darrieus blade interacts with Savonius' wake at γ=0° and λS=0.8, which is considered undesirable. Furthermore, attachment angles of 60° and 90° exhibit better power coefficients compared to those of 0° and 30° for the hybrid VAWT. This study contributes to a comprehensive understanding of flow dynamics in hybrid VAWTs, revealing the correlation between torque variation and vortex development.

A kinetic study on oxygen redox reaction of a double-perovskite reversible oxygen electrode—Part I: Experimental analysis

The carbon-free energy transition requires the spread of advanced technologies based on high-performing materials. In this framework and particularly referring to electrochemical energy converting systems, double perovskites are arousing more and more interest as mixed ionic electronic conductors with flexible manufacturing, appropriate tailoring for many tasks and high chemical stability. Among their possible applications, they form excellent oxygen electrodes in solid oxide cell technology used as fuel cells, steam/CO2 electrolysis cells and electrochemical air separation units. In view of the encouraging results shown by SmBa1−x Ca x Co2O5+δ co-doped double perovskite, this research work aims at a detailed analysis of SmBa0.8Ca0.2Co2O5+δ performance and the identification of kinetic paths for oxygen reduction and oxidation reactions. The electrochemical characterization was performed over a wide range of operation conditions to evaluate the electrode reversible behaviour and the interplay of the recognized phenomena governing the overall electrode kinetics.

Thermo-Economic Performance of Organic Rankine Cycle-Based Waste Heat Recovery for Power Generation at a Wide Range of Operating Conditions

This study assesses the performance of organic Rankine cycle-based waste heat recovery systems under different working fluids and operating conditions. The basic ORC (BORC) and ORC with recuperator (RORC) are investigated for power generation and economy using toluene and benzene. Thermodynamic and economic indicators are studied at various expander inlet temperatures, expander inlet pressure, evaporation temperature, and condensation temperature. RORC achieves higher ηth by reducing heat source in the evaporator whereas BORC recovers more waste heat and improves Pnet. With toluene, BORC improves Pnet when increasing the expander inlet temperature and pressure. The lowest LCOE of 0.0532 US$/kWh is from BORC operated with toluene at a Pnet of 349 kW and decreases with an increase in expander inlet temperature. The addition of a recuperator adds to the costs of initial investment and LCOE and slightly improves the performance of the ORCs for waste heat recovery.

Dynamic transmission policy for enhancing LoRa network performance: A deep reinforcement learning approach

Long Range (LoRa) communications, operating through the LoRaWAN protocol, have received increasing attention from the low-power and wide-area network communities. Efficient energy consumption and reliable communication performance are critical aspects of LoRa-based applications. However, current scientific literature tends to focus on minimizing energy consumption while disregarding channel changes affecting communication performance. Other works attain appropriate communication performance without adequately considering energy expenditure. To fill this gap, we propose a novel solution to maximize the energy efficiency of devices while considering the desired network performance. This is done using a maximum allowed Bit Error Rate (BER) that can be specified by users and applications. We characterize this problem as a Markov Decision Process and solve it using Deep Reinforcement Learning to dynamically and quickly select the transmission parameters that jointly satisfy energy and performance requirements over time. Moreover, we support different payload sizes, ensuring suitability for applications with varying packet lengths. The proposed selection of parameters is evaluated in three different scenarios by comparing it with the traditional Adaptive Data Rate (ADR) mechanism of LoRaWAN. The first scenario involves static nodes with varying BER requirements. The second one realistically simulates urban environments with mobile nodes and fluctuating channel conditions. Finally, the third scenario studies the proposed solution under dynamic frame payload length variations. These scenarios cover a wide range of operational conditions to ensure a comprehensive evaluation. The results of our experiments demonstrate that our proposal achieves a 60% improvement in performance metrics over the default ADR mechanism.

Robust PLL-Based Grid Synchronization and Frequency Monitoring

Nowadays, the penetration of inverter-based energy resources is continuously increasing in low-voltage distribution grids. Their applications cover traditional renewable energy production and energy storage but also new applications such as charging points for electric vehicles, heat pumps, electrolyzers, etc. The power ratings range from a couple of kW to hundreds of kW. Utilities have, in the last few years, reported more challenges regarding power quality in distribution grids, e.g., high harmonic content, high unbalances, large voltage and frequency excursions, etc. Phase-Lock-Loop (PLL) algorithms are typically used for grid synchronization and decoupled control of power converters connected to the grid. Most of the research within PLLs is mainly focusing on grid voltage angle estimation while the byproducts of the algorithms, e.g., frequency and voltage magnitude, are often overlooked. However, both frequency and voltage magnitude estimations are crucial for grid code compliance. Practical considerations for implementation on microcontroller boards of these algorithms are also missing in most of the cases. The present paper proposes a modified PLL algorithm based on a Synchronous Reference Frame that is suitable for both grid synchronization and frequency monitoring, i.e., the estimation of RMS phase voltages and frequencies in highly distorted distribution grids. It also provides the tuning methodology and practical considerations for implementation on commercial DSP boards. The performance of the proposed approach is assessed through simulation studies and laboratory tests under a wide range of operational conditions, showing that the proposed PLL can estimate the grid frequency, for all considered grid events, with an accuracy of less than ±5 mHz, which is a significant improvement on the current state-of-the-art solutions, having an accuracy of at least ±20 mHz or more.

Proposal of a double ejector-two flash tank absorption refrigeration cycle: Energy, exergy and thermoeconomic evaluation

This research presents the proposal of a double ejector-two flash tank absorption refrigeration cycle, in which vapor and liquid ejectors are implemented simultaneously before the condensers and absorbers components. For the vapor ejector simulation, the shock circle approach is used. The internal environment of the vapor ejector, including the chocking phenomenon and the irreversible shock process, is also thoroughly examined. It is proposed that ejectors and flash tanks can improve the system performance. It is possible to improve the ejector entrainment ratio by incorporating a flash tank between the evaporator and condenser, which would also increase the evaporator cooling effect. Moreover, a second flash tank is installed between the generator and the absorber, which allows the generator to operate at a lower temperature and thus reduces the generator heat load. Consequently, the system's COP (coefficient of performance) increases. Furthermore, the unit cost of the final product in a wide range of operational conditions is calculated. The findings revealed up to 56.8% increase in the COP. The improvement of the maximum exergetic efficiency in the new cycle compared to the basic cycle also reaches 22.5%. Moreover, the thermoeconomic investigation show up to 34.6%. reduction in product cost.

Effect of three-orifice baffles orientation on the flow and thermal–hydraulic performance: Experimental analysis for net and oscillatory flows

Three-orifice baffles equally spaced along a circular tube are investigated as a means for heat transfer enhancement under net, oscillatory and compound flows. An unprecedented, systematic analysis of the relative orientation of consecutive baffles – aligned or opposed – is accomplished to assess the changes induced on the flow structure and their impact on the thermal–hydraulic performance. The results cover the Nusselt number, the net and oscillatory friction factors and the instantaneous velocity fields using PIV in an experimental campaign with a 32 mm tube diameter. The study is conducted in the range of net Reynolds numbers 50<Ren<1000 and oscillatory Reynolds numbers 0<Reosc<750, for a dimensionless amplitude x0/D=0.5 and Pr=65. In absence of oscillatory flow, opposed baffles advance the transition to turbulence from Ren=100 to 50, increasing the net friction factor (40%) for Ren>50 and the Nusselt number (maximum of 27%) for Ren<150. When an oscillatory flow is applied, augmentations caused by opposed baffles are only observed for Ren<150 and Reosc<150. Above Ren, Reosc>150, opposed baffles are not recommended for the promotion of heat transfer, owing to friction penalties. However, the chaotic mixing and lack of short-circuiting between baffles observed with flow velocimetry over a wide range of operational conditions point out the interest of this configuration to achieve plug flow.

Polymerization of isoprene, myrcene, and butadiene catalyzed by cobalt complexes supported with 2‐acetyl‐6‐iminopyridine ligand

Cobalt complexes carrying 2‐acetyl‐6‐iminopyridine ligand are synthesized and characterized. Single‐crystal X‐ray diffraction reveals the cobalt ion is chelated with two nitrogen atoms and an acetyl oxygen atom additionally. A significant prolonged Co–O distance (2.3960(57) Å) is found, indicative of a labile character. Activated by diethylchloroaluminum, all complexes show high conversion rates for isoprene and myrcene polymerizations, affording cis‐1,4/3,4 regulated 1,3‐diene polymers. The polymerization of butadiene, interestingly, gives predominant cis‐1,4 selectivity (&gt;99.2%) with moderate activity. The substituent at ortho‐position of arylimine plays a minor role in controlling activity and selectivity as well as the molecular weight of the resultant polymers. The properties of resultant poly(1,3‐diene)s are stable even in a wide range of operational conditions, such as [Al]/[Co] varied from 20 to 600, temperature spanning from 0°C to 60°C, and monomer–catalyst ratio from 1000 to 4000. These additional benefits of minimum fluctuation in catalytic performances may be suitable for industrial polymerization process.

Mass flow characteristics and correlations of R454C flow through an electrical expansion valve in a heat pump split system

The use of electronic expansion valves (EEVs) in heat pump systems has seen a rapid increase in recent years due to their advantages such as fast response, accurate control, and ability to improve seasonal performance. Modeling of the refrigerant flow characteristics through EEVs is needed during design for optimizing system performance and operation. Previous studies have not led to any generalized correlations for EEVs that accurately predict performance for different refrigerants. When working with a new refrigerant and/or EEV, it is necessary to perform mass flow measurements for the EEV over a wide range of operating conditions that are then used to develop and validate a refrigerant and EEV specific correlation. R454C, a low-GWP refrigerant mixture, is gaining attention as a potential replacement for R404A and R410A systems. However, there is currently no available EEV experimental data or correlation specifically for R454C in the literature. The objective of this paper is to present experimental results and characterization of R454C flowing through an EEV in a heat pump split system across a wide range of operational conditions. The impacts of valve opening, subcooling degree and inlet pressure on mass flow rate though the EEV were investigated. Two semi-empirical correlations were developed that map the experimental data based on the Buckingham π theorem and a polynomial function. Both mapping methods predicted mass flow rate for test data within 10%. The Buckingham π correlation was slightly more accurate. Both correlations were developed to enable mass flow rate predictions for R454C passing through EEVs with different valve sizes. Finally, a relationship between refrigerant molar mass and mass flow coefficient was observed that could be useful in developing a general EEV correlation that can be applied for different refrigerants. However, further investigation is needed to validate this relationship.

Experimental Investigation of the Effect of Suction Valve Opening on the Performance and Detection of Cavitation in the Centrifugal Pump Based on Acoustic Analysis Technique

The pump performance and occurrence of cavitation directly depends on different operating conditions. To cover a wide range of operation conditions for detecting cavitation in this work, investigations on the effect of various suction valve openings on cavitation in the pump were carried out. In order to analyse various levels of cavitation in different operation conditions, the effect of the decrease in the inlet suction pressure of the centrifugal pump by controlling the inlet suction valve opening was investigated using this experimental setup. Hence, the acoustic and pressure signals under different inlet valve openings and different flow rates, namely, 103, 200, 302 l/min were collected for this purpose. A detailed analysis of the results obtained from the acoustic signal was carried out to predict cavitation in the pump under different operating conditions. Also, the acoustic signal was investigated in time domain through the use of the same statistical features. The FFT technique was used to analyse the acoustic signal in the frequency domain. In addition, in this work an attempt was made to find a relationship between the cavitation and noise characteristics using the acoustic technique for identifying cavitation within a pump.

Exploring key operational factors for improving hydrogen production in a pilot-scale microbial electrolysis cell treating urban wastewater

Bioelectrochemical systems (BES) are becoming popular technologies with a plethora of applications in the environmental field. However, research on the scale-up of these systems is scarce. To understand the limiting factors of hydrogen production in microbial electrolysis cell (MEC) at pilot-scale, a 135 L MEC was operated for six months under a wide range of operational conditions: applied potential [0.8–1.1 V], hydraulic residence time [1.1–3.9 d], and temperature [18–30 °C], using three types of wastewater; synthetic (900 mg CODs L−1), raw urban wastewater (200 mg CODs L−1) and urban wastewater amended with acetate (1000 mg CODs L−1). The synthetic wastewater yielded the maximum current density (1.23 A m−2) and hydrogen production (0.1 m3 m−3 d−1) ever reported in a pilot scale MEC, with a cathodic recovery of 70% and a coulombic efficiency of 27%. In contrast, the use of low COD urban wastewater limited the plant performance. Interestingly, it was possible to improve hydrogen production by reducing the hydraulic residence time, finding the optimal applied potential or increasing the temperature. Further, the pilot plant demonstrated a robust capacity to remove the organic matter present in the wastewater under different conditions, with removal efficiencies above 70%. This study shows improved results compared to similar MEC pilot plants treating domestic wastewater in terms of hydrogen production and treatment efficiency and also compares its performance against conventional activated sludge processes.

Bi-reforming of methane in a carbon deposit-free plasmatron with high operational adaptability

An atmospheric plasmatron reactor with two-stage inlets was developed for bi-reforming of methane (CO2/CH4/H2O) to produce syngas (H2 + CO) and value-added liquid products. The influence of CH4 inlet position, gas flow rate and reactant composition were investigated. The results showed that the two-stage-inlet design allows for a wide range of operational conditions in terms of the CO2/CH4/H2O ratio (2–7:0–6:0–3) and total flow rate (4.5-11 L/min). A CO2 and CH4 conversion of 24% and 12.9%, respectively, was obtained at flow rates of up to 7-8 L/min, with no observable carbon deposit formed. A closer injection of CH4 to the core plasma area was more beneficial for both reactant conversion and syngas selectivity. Interestingly, value-added oxygenated products (e.g., methanol, ethanol, acetic acid) were produced simultaneously, offering a promising power-to-liquid (PtL) route. In particular, the direct synthesis of acetic acid from CH4 and CO2 was achieved, which is infeasible in thermocatalytic processes. A small addition of H2O (14.3%) favorably enhanced the formation of acetic acid by up to 160%, likely due to the improved generation of CH3 and COOH intermediates. Overall, this work offers a promising route for syngas and oxygenated products generation in a scalable plasmatron reactor with high operational adaptability.

Local volumetric mass transfer coefficients in sections of multiple-impeller stirred tank reactors: Data analysis

The analysis of local values of volumetric mass transfer coefficient, kLa, was performed to identify the effects of local hydrodynamics on the mass transfer rate in multiple-impeller stirred tank reactors. The database of kLa values measured by Dynamic Pressure Method was analysed. The database provides data for two vessel sizes (laboratory and pilot-scale reactor), a wide range of operational conditions (gas flow rate, impeller speed), various impeller geometries and sizes and four different batches including viscous media. The local kLa values in multiple impeller configurations were measured in several positions corresponding to the individual impeller regions. The overall kLa value averaged through the whole volume is considered as the best representation of the correct kLa value. Different hydrodynamic effects on mass transfer rate were obtained in the two end regions. In the bottom region, the local kLa values increase with impeller speed faster than the overall kLa. The opposite behaviour was obtained in the uppermost region corresponding to the decrease of power consumption and the mass transfer rate with increasing surface aeration under high impeller speeds. The best representation of the overall kLa value was obtained in the middle position of the vessel, where the exchange flows bring the liquid saturated to different measure from the end regions. Even if the local kLa data in individual impellers' regions are shifted to the average values due to the inter-impeller exchange flows, the differences between them are still significant. We show the local kLa values by the combination of the data measured at different liquid level heights. The results can be used in the fermenter design with various impeller combinations.

Modelling minimum miscibility pressure of CO2-crude oil systems using deep learning, tree-based, and thermodynamic models: Application to CO2 sequestration and enhanced oil recovery

The energy demand is still increasing across the globe, while environmental concerns about global warming effect and greenhouse gases have augmented recently. CO2 injection into mature oil reservoirs is an interesting operation that could help us supply the uprising demand while saving the environment. Having accurate knowledge about CO2 minimum miscibility pressure (MMP) is of utmost importance in designing a successful operation. This study mainly focuses on proposing several tools based on powerful tree-based and deep learning algorithms for estimating the MMP of CO2-crude oil system based on an extensive databank. The models employed in this study include extreme gradient boosting (XGBoost), categorical boosting (CatBoost), light gradient boosting machine (LGBM), random forest (RF), deep multi-layer neural network (deep MLN), deep belief network (DBN), and convolutional neural network (CNN). The models were trained and verified using 310 data points. Along with intelligent models, seven popular empirical correlations and two computational approaches, which are based on thermodynamics, were utilized to be compared with the proposed models. The outcomes expressed that the CatBoost model could estimate CO2 MMP values, using mole percent of volatile (C1 and N2) and intermediate (CO2, H2S, and C2–C5) fractions of oil, the average critical temperature of injection gas (Tcave), reservoir temperature (Tres), and molecular weight of C5+ fraction of oil (MWc5+) as input variables, with a total AARD of 1.34 %. Moreover, the variable impact examination showed that reservoir temperature greatly affects the MMP predictions. Finally, the Leverage approach verified the reliability of the databank and wide applicability domain of the developed CatBoost model spotting 5 outlier points (out of 310 points) only. The findings of this communication shed light on the high accuracy and reliability of CatBoost model in estimating CO2 MMP in a wide range of operational conditions.

Kinetics, Model Discrimination, and Parameters Estimation of CO2 Methanation on Highly Active Ni/CeO2 Catalyst

The reaction kinetics of CO2 methanation over a highly active 8.5% Ni/CeO2 catalyst was determined in a fixed-bed reactor, in the absence of heat- and mass-transfer limitations. Once the catalyst activity was stabilized, more than 120 kinetic experiments (with varying values of reaction temperature, total pressure, space velocity (GHSV), and partial pressure of products and reactants) were performed. From initial reaction rates, an apparent activation energy of 103.9 kJ mol–1 was determined, as well as the effect of reactants (positive) and water partial pressures (negative) on CO2 methanation rate. Three mechanistic models reported in the literature, in which CO2 is adsorbed dissociatively (carbon and formyl routes) or directly (formate route), were explored for modeling the entire reaction kinetics. For that, the corresponding rate equations were developed through the Langmuir–Hinshelwood–Hougen–Watson (LHHW) approach. In agreement with DRIFTS experiments, formate route, in which the hydrogenation of bicarbonate to formate is considered to be the rate-determining step, reflects the kinetic data accurately, operating from differential conversion to thermodynamic equilibrium. In fact, this mechanism results in a mean deviation (D) of 10.38%. Based on previous own mechanistic studies, the participation of two different active sites has been also considered. Formate route on two active sites maintains a high fitting quality of experimental data, providing kinetics parameters with a higher physical significance. Thus, the LHHW mechanism, in which Ni0 sites as well as oxygen vacant near to Ni-CeO2 interface participate in CO2 methanation, is able to predict the kinetics of Ni/CeO2 catalyst accurately for a wide range of operational conditions.