Na_(3)V_(2)(PO_(4))_(3)(NVP)has garnered great attentions as a prospective cathode material for sodium-ion batteries(SIBs)by virtue of its decent theoretical capacity,superior ion conductivity and high structural stab...Na_(3)V_(2)(PO_(4))_(3)(NVP)has garnered great attentions as a prospective cathode material for sodium-ion batteries(SIBs)by virtue of its decent theoretical capacity,superior ion conductivity and high structural stability.However,the inherently poor electronic conductivity and sluggish sodium-ion diffusion kinetics of NVP material give rise to inferior rate performance and unsatisfactory energy density,which strictly confine its further application in SIBs.Thus,it is of significance to boost the sodium storage performance of NVP cathode material.Up to now,many methods have been developed to optimize the electrochemical performance of NVP cathode material.In this review,the latest advances in optimization strategies for improving the electrochemical performance of NVP cathode material are well summarized and discussed,including carbon coating or modification,foreign-ion doping or substitution and nanostructure and morphology design.The foreign-ion doping or substitution is highlighted,involving Na,V,and PO_(4)^(3−)sites,which include single-site doping,multiple-site doping,single-ion doping,multiple-ion doping and so on.Furthermore,the challenges and prospects of high-performance NVP cathode material are also put forward.It is believed that this review can provide a useful reference for designing and developing high-performance NVP cathode material toward the large-scale application in SIBs.展开更多
Hydrocracking is one of the most important petroleum refining processes that converts heavy oils into gases,naphtha,diesel,and other products through cracking reactions.Multi-objective optimization algorithms can help...Hydrocracking is one of the most important petroleum refining processes that converts heavy oils into gases,naphtha,diesel,and other products through cracking reactions.Multi-objective optimization algorithms can help refining enterprises determine the optimal operating parameters to maximize product quality while ensuring product yield,or to increase product yield while reducing energy consumption.This paper presents a multi-objective optimization scheme for hydrocracking based on an improved SPEA2-PE algorithm,which combines path evolution operator and adaptive step strategy to accelerate the convergence speed and improve the computational accuracy of the algorithm.The reactor model used in this article is simulated based on a twenty-five lumped kinetic model.Through model and test function verification,the proposed optimization scheme exhibits significant advantages in the multiobjective optimization process of hydrocracking.展开更多
Carbon dioxide-enhanced oil recovery(CO_(2)-EOR)and storage is recognized as an economically feasible technique if used in suitable reservoirs.The type or form and capacity of this CO_(2) sequestration technique is sy...Carbon dioxide-enhanced oil recovery(CO_(2)-EOR)and storage is recognized as an economically feasible technique if used in suitable reservoirs.The type or form and capacity of this CO_(2) sequestration technique is synergistically affected by heat,flow,stress,and chemical reactions.Aimed at addressing the technological issues in applying CO_(2)-EOR and storage in a high water-cut reservoir in Xinjiang,China,this paper proposes a thermo-hydro-mechanical-chemical coupling method during CO_(2) flooding.The potential of CO_(2) sequestration and EOR in the target reservoir is discussed in combination with the surrogate optimization method.This method works better as it considers the evolution of structural trapping,capillary trapping,solubility trapping,and mineral trapping during CO_(2) injection as well as the influence the physical field has on the sequestration capacity for different forms of CO_(2) sequestration.The main mechanisms of CO_(2) sequestration in the high water-cut reservoir is structural trapping,followed by capillary trapping.Solubility trapping and mineral trapping have less contribution to the total sequestration capacity of CO_(2).After optimization,the cumulative oil production was 2.36×10^(6)m^(3),an increase of 0.25×10^(6)m3or 11.9%compared to the pre-optimization value.The CO_(2) sequestration capacity after optimization was 1.39×10^(6)t,which is an increase of 0.23×10^(6)t compared to values obtained before optimization;this effectively increases the area affected by CO_(2) by 24.4%.Of the four trapping mechanisms,capillary trapping and structural trapping showed a high increase of 32.5%and17.28%,respectively,while solubility trapping and mineral trapping only led to an increase of 5.1%and0.43%,respectively.This research could provide theoretical support for fully utilizing the potential of CO_(2)-EOR and sequestration technology.展开更多
CO_(2) Water-Alternating-Gas(CO_(2)-WAG)injection is not only a method to enhance oil recovery but also a feasible way to achieve CO_(2) sequestration.However,inappropriate injection strategies would prevent the attai...CO_(2) Water-Alternating-Gas(CO_(2)-WAG)injection is not only a method to enhance oil recovery but also a feasible way to achieve CO_(2) sequestration.However,inappropriate injection strategies would prevent the attainment of maximum oil recovery and cumulative CO_(2) storage.Furthermore,the optimization of CO_(2)-WAG is computationally expensive as it needs to frequently call the compositional simulation model that involves various CO_(2) storage mechanisms.Therefore,the surrogate-assisted evolutionary optimization is necessary,which replaces the compositional simulator with surrogate models.In this paper,a surrogate-based multi-objective optimization algorithm assisted by the single-objective pre-search method is proposed.The results of single-objective optimization will be used to initialize the solutions of multi-objective optimization,which accelerates the exploration of the entire Pareto front.In addition,a convergence criterion is also proposed for the single-objective optimization during pre-search,and the gradient of surrogate models is adopted as the convergence criterion.Finally,the method proposed in this work is applied to two benchmark reservoir models to prove its efficiency and correctness.The results show that the proposed algorithm achieves a better performance than the conventional ones for the multi-objective optimization of CO_(2)-WAG.展开更多
The growing demand for carbon neutrality has heightened the focus on CO_(2)hydrogenation as a viable strategy for transforming carbon dioxide into valuable chemicals and fuels.Advanced machine learning(ML)approaches i...The growing demand for carbon neutrality has heightened the focus on CO_(2)hydrogenation as a viable strategy for transforming carbon dioxide into valuable chemicals and fuels.Advanced machine learning(ML)approaches integrate materials science with artificial intelligence,enabling scientists to identify hidden patterns in datasets,make informed decisions,and reduce the need for labor-intensive,repetitive experimentation.This review provides a comprehensive overview of ML applications in the thermocatalytic hydrogenation of CO_(2).Following an introduction to ML tools and workflows,various ML algorithms employed in CO_(2)hydrogenation are systematically categorized and reviewed.Next,the application of ML in catalyst discovery is discussed,highlighting its role in identifying optimal compositions and structures.Then,ML-driven strategies for process optimization,particularly in enhancing CO_(2)conversion and product selectivity,are examined.Studies modeling descriptors,spanning catalyst properties and reaction conditions,to predict catalytic performance are analyzed.Consequently,ML-based mechanistic studies are reviewed to elucidate reaction pathways,identify key intermediates,and optimize catalyst performance.Finally,key challenges and future perspectives in leveraging ML for advancing CO_(2)hydrogenation research are presented.展开更多
Carbon dioxide Enhanced Oil Recovery(CO_(2)-EOR)technology guarantees substantial underground CO_(2) sequestration while simultaneously boosting the production capacity of subsurface hydrocarbons(oil and gas).However,...Carbon dioxide Enhanced Oil Recovery(CO_(2)-EOR)technology guarantees substantial underground CO_(2) sequestration while simultaneously boosting the production capacity of subsurface hydrocarbons(oil and gas).However,unreasonable CO_(2)-EOR strategies,encompassing well placement and well control parameters,will lead to premature gas channeling in production wells,resulting in large amounts of CO_(2) escape without any beneficial effect.Due to the lack of prediction and optimization tools that integrate complex geological and engineering information for the widely used CO_(2)-EOR technology in promising industries,it is imperative to conduct thorough process simulations and optimization evaluations of CO_(2)-EOR technology.In this paper,a novel optimization workflow that couples the AST-GraphTrans-based proxy model(Attention-based Spatio-temporal Graph Transformer)and multi-objective optimization algorithm MOPSO(Multi-objective Particle Swarm Optimization)is established to optimize CO_(2)-EOR strategies.The workflow consists of two outstanding components.The AST-GraphTrans-based proxy model is utilized to forecast the dynamics of CO_(2) flooding and sequestration,which includes cumulative oil production,CO_(2) sequestration volume,and CO_(2) plume front.And the MOPSO algorithm is employed for achieving maximum oil production and maximum sequestration volume by coordinating well placement and well control parameters with the containment of gas channeling.By the collaborative coordination of the two aforementioned components,the AST-GraphTrans proxy-assisted optimization workflow overcomes the limitations of rapid optimization in CO_(2)-EOR technology,which cannot consider high-dimensional spatio-temporal information.The effectiveness of the proposed workflow is validated on a 2D synthetic model and a 3D field-scale reservoir model.The proposed workflow yields optimizations that lead to a significant increase in cumulative oil production by 87%and 49%,and CO_(2) sequestration volume enhancement by 78%and 50%across various reservoirs.These findings underscore the superior stability and generalization capabilities of the AST-GraphTrans proxy-assisted framework.The contribution of this study is to provide a more efficient prediction and optimization tool that maximizes CO_(2) sequestration and oil recovery while mitigating CO_(2) gas channeling,thereby ensuring cleaner oil production.展开更多
To solve the problems of deformation,micro-cracks,and residual tensile stress in laser cladding coatings,the technique of laser cladding with Fe-based memory alloy can be considered.However,the process of in-situ synt...To solve the problems of deformation,micro-cracks,and residual tensile stress in laser cladding coatings,the technique of laser cladding with Fe-based memory alloy can be considered.However,the process of in-situ synthesis of Fe-based memory alloy coatings is extremely complex.At present,there is no clear guidance scheme for its preparation process,which limits its promotion and application to some extent.Therefore,in this study,response surface methodology(RSM)was used to model the response surface between the target values and the cladding process parameters.The NSGA-2 algorithm was employed to optimize the process parameters.The results indicate that the composite optimization method consisting of RSM and the NSGA-2 algorithm can establish a more accurate model,with an error of less than 4.5%between the predicted and actual values.Based on this established model,the optimal scheme for process parameters corresponding to different target results can be rapidly obtained.The prepared coating exhibits a uniform structure,with no defects such as pores,cracks,and deformation.The surface roughness and microhardness of the coating are enhanced,the shaping quality of the coating is effectively improved,and the electrochemical corrosion performance of the coating in 3.5%NaCl solution is obviously better than that of the substrate,providing an important guide for engineering applications.展开更多
The park-level integrated energy system(PIES)is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration.However,current carbon trading mechanis...The park-level integrated energy system(PIES)is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration.However,current carbon trading mechanisms lack sufficient incentives for emission reductions,and traditional optimization algorithms often face challenges with convergence and local optima in complex PIES scheduling.To address these issues,this paper introduces a low-carbon dispatch strategy that combines a reward-penalty tiered carbon trading model with P2G-CCS integration,hydrogen utilization,and the Secretary Bird Optimization Algorithm(SBOA).Key innovations include:(1)A dynamic reward-penalty carbon trading mechanism with coefficients(μ=0.2,λ=0.15),which reduces carbon trading costs by 47.2%(from$694.06 to$366.32)compared to traditional tiered models,incentivizing voluntary emission reductions.(2)The integration of P2G-CCS coupling,which lowers natural gas consumption by 41.9%(from$4117.20 to$2389.23)and enhances CO_(2) recycling efficiency,addressing the limitations of standalone P2G or CCS technologies.(3)TheSBOA algorithm,which outperforms traditionalmethods(e.g.,PSO,GWO)in convergence speed and global search capability,avoiding local optima and achieving 24.39%faster convergence on CEC2005 benchmark functions.(4)A four-energy PIES framework incorporating electricity,heat,gas,and hydrogen,where hydrogen fuel cells and CHP systems improve demand response flexibility,reducing gas-related emissions by 42.1%and generating$13.14 in demand response revenue.Case studies across five scenarios demonstrate the strategy’s effectiveness:total operational costs decrease by 14.7%(from$7354.64 to$6272.59),carbon emissions drop by 49.9%(from 5294.94 to 2653.39kg),andrenewable energyutilizationincreases by24.39%(from4.82%to8.17%).These results affirmthemodel’s ability to reconcile economic and environmental goals,providing a scalable approach for low-carbon transitions in industrial parks.展开更多
The dynamic traveling salesman problem(DTSP)is significant in logistics distribution in real-world applications in smart cities,but it is uncertain and difficult to solve.This paper proposes a scheme library-based ant...The dynamic traveling salesman problem(DTSP)is significant in logistics distribution in real-world applications in smart cities,but it is uncertain and difficult to solve.This paper proposes a scheme library-based ant colony optimization(ACO)with a two-optimization(2-opt)strategy to solve the DTSP efficiently.The work is novel and contributes to three aspects:problemmodel,optimization framework,and algorithmdesign.Firstly,in the problem model,traditional DTSP models often consider the change of travel distance between two nodes over time,while this paper focuses on a special DTSP model in that the node locations change dynamically over time.Secondly,in the optimization framework,the ACO algorithm is carried out in an offline optimization and online application framework to efficiently reuse the historical information to help fast respond to the dynamic environment.The framework of offline optimization and online application is proposed due to the fact that the environmental change inDTSPis caused by the change of node location,and therefore the newenvironment is somehowsimilar to certain previous environments.This way,in the offline optimization,the solutions for possible environmental changes are optimized in advance,and are stored in a mode scheme library.In the online application,when an environmental change is detected,the candidate solutions stored in the mode scheme library are reused via ACO to improve search efficiency and reduce computational complexity.Thirdly,in the algorithm design,the ACO cooperates with the 2-opt strategy to enhance search efficiency.To evaluate the performance of ACO with 2-opt,we design two challenging DTSP cases with up to 200 and 1379 nodes and compare them with other ACO and genetic algorithms.The experimental results show that ACO with 2-opt can solve the DTSPs effectively.展开更多
Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Althou...Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Although IT2 FNNs have more advantages in processing uncertain, incomplete, or imprecise information compared to their type-1 counterparts, a large number of parameters need to be tuned in the IT2 FNNs,which increases the difficulties of their design. In this paper,big bang-big crunch(BBBC) optimization and particle swarm optimization(PSO) are applied in the parameter optimization for Takagi-Sugeno-Kang(TSK) type IT2 FNNs. The employment of the BBBC and PSO strategies can eliminate the need of backpropagation computation. The computing problem is converted to a simple feed-forward IT2 FNNs learning. The adoption of the BBBC or the PSO will not only simplify the design of the IT2 FNNs, but will also increase identification accuracy when compared with present methods. The proposed optimization based strategies are tested with three types of interval type-2 fuzzy membership functions(IT2FMFs) and deployed on three typical identification models. Simulation results certify the effectiveness of the proposed parameter optimization methods for the IT2 FNNs.展开更多
A microwave-H202 process for sludge pretreatment exhibited high efticiencies of releasing organics, nitrogen, and phosphorus, but large quantifies of H202 residues were detected. A uniform design method was thus emplo...A microwave-H202 process for sludge pretreatment exhibited high efticiencies of releasing organics, nitrogen, and phosphorus, but large quantifies of H202 residues were detected. A uniform design method was thus employed in this study to further optimize H202 dosage by investigating effects of pH and H202 dosage on the amount of 1-I202 residue and releases of organics, nitrogen, and phosphorus. A regression model was established with pH and H202 dosage as the independent variables, and H202 residue and releases of organics, nitrogen, and phosphorus as the dependent variables. In the optimized microwave-H202 process, the pH value of the sludge was firstly adjusted to 11.0, then the sludge was heated to 80~C and H202 was dosed at a H202 ：mixed liquor suspended solids （MLSS） ratio of 0.2, and the sludge was finally heated to 100~C by microwave irradiation. Compared to the microwave-H202 process without optimization, the H202 dosage and the utilization rate of H202 in the optimized microwave-H202 process were reduced by 80% and greatly improved by 3.87 times, respectively, when the H202：MLSS dosage ratio was decreased from 1.0 to 0.2, resulting in nearly the same release rate of soluble chemical oxygen demand in the microwave-H202 process without optimization at H202：MLSS ratio of 0.5.展开更多
Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed...Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed. One was the disorderly charging and discharging mode based on travel habits, and the other was the orderly charging and discharging mode based on time-of-use(TOU) price;Monte Carlo method was used to verify the case. The scheme of the capacity optimization of photovoltaic charging station under two different charging and discharging modes with V2 G was proposed. The mathematical models of the objective function with the maximization of energy efficiency, the minimization of the investment and the operation cost of the charging system were established. The range of decision variables, constraints of the requirements of the power balance and the strategy of energy exchange were given. NSGA-Ⅱ and NSGA-SA algorithm were used to verify the cases, respectively. In both algorithms, by comparing with the simulation results of the two different modes, it shows that the orderly charging and discharging mode with V2 G is obviously better than the disorderly charging and discharging mode in the aspects of alleviating the pressure of power grid, reducing system investment and improving energy efficiency.展开更多
In the present study, a great effort was made to improve the performance of an industrial liquefied petroleum gas(LPG) and natural gas liquid(NGL) production unit in one of the major gas refinery located at Pars speci...In the present study, a great effort was made to improve the performance of an industrial liquefied petroleum gas(LPG) and natural gas liquid(NGL) production unit in one of the major gas refinery located at Pars special economic zone in Iran. To demonstrate and obtain the optimal condition, the unit was simulated by using a steady-state flowsheet simulator, i.e. Aspen Plus, under different operational conditions. According to the simulation results,the unit was not operational under its optimal conditions due to some defects in the cooling system at top stage of the debutanizer tower(DBT) during hot and humid seasons. Additionally, the vapor pressure of produced LPG and accordingly the amount of its flaring were decreased by reducing the temperature of debutanizer tower at top stages. In the optimization section, the DBT condenser and reboiler heat duty, temperature, and pressure were regulated as adjustable parameters. The simulation results demonstrated that by applying the optimum suggestion in the hot months, the reflux stream temperature was reached about 55 ℃ which caused an efficient increment in LPG production(about 4%) with adjusting the propane component in LPG, based on the standard range as the plant criteria. Moreover, after applying modifications, about 750 t of LPG product was saved from flaring during five hot months of the year, which resulted in 360000 USD extra annual income for the company.Finally, from environmental point of view, this optimization caused to reduce 81 t of CO_2 emission to the environment. Therefore, the current investigation must be introduced as a friendly environmentally process.展开更多
In order to clarify the slag system of high Cr2O3 vanadium-titanium magnetite smelting in BF （blast furnace）, the melting properties of slag samples prepared by analytically pure reagents were measured. By means of ...In order to clarify the slag system of high Cr2O3 vanadium-titanium magnetite smelting in BF （blast furnace）, the melting properties of slag samples prepared by analytically pure reagents were measured. By means of orthogonal test synthetic weighted score method, the optimal slag for high Cr2O3 vanadium-titanium magnetite was obtained, which contained 10% MgO, 8% TiO2 and 15% Al2O3, with the binary basicity being 1.15. In addition, the effects of basicity, MgO, TiO2 and A12 03 on slag melting properties were investigated by single factor test, and the results showed that, with increasing the basicity or TiO2 content, melting temperature （Tin） increased, whereas initial vis- cosity （r/0） and high temperature viscosity （r/h） decreased. With increasing the MgO content, Tm decreased firstly and then increased. With increasing the Al2 O3 content, Tm increased, and η0 and r/h decreased firstly and then increased.展开更多
In situ formed TiB2 particle reinforced aluminum matrix composites （TiB2/Al MMCs） have some extraordinary properties which make them be a promising material for high performance aero-engine blade. Due to the influen...In situ formed TiB2 particle reinforced aluminum matrix composites （TiB2/Al MMCs） have some extraordinary properties which make them be a promising material for high performance aero-engine blade. Due to the influence of TiB2 particles, the machinability is still a problem which restricts the application of TiB2/Al MMCs. In order to meet the industrial requirements, the influence of TiB2 particles on the machinability of TiB2/Al MMCs was investigated experimentally. Moreover, the optimal machining conditions for this kind of MMCs were investigated in this study. The major conclusions are： （1） the machining force of TiB2/Al MMCs is bigger than that of non- reinforced alloy and mainly controlled by feed rate; （2） the residual stress of TiB2/AI MMCs is compressive while that of non-reinforced alloy is nearly neutral; （3） the surface roughness of TiB2/Al MMCs is smaller than that of non-reinforced alloy under the same cutting speed, but reverse result was observed when the feed rate increased; （4） a multi-objective optimization model for surface roughness and material removal rate （MRR） was established, and a set of optimal parameter combinations of the machining was obtained. The results show a great difference from SiC particle reinforced MMCs and provide a useful guide for a better control of machining process of this material.展开更多
The objective of this research was to investigate CO2adsorption capacity of tetraethylenepentamine-functionalized basic-modified calcined hydrotalcite（TEPA/b-c HT）sorbents at atmospheric pressure formed under varyin...The objective of this research was to investigate CO2adsorption capacity of tetraethylenepentamine-functionalized basic-modified calcined hydrotalcite（TEPA/b-c HT）sorbents at atmospheric pressure formed under varying TEPA loading levels,temperatures,sorbent weight to total gaseous flow rate（W/F）ratios and CO2concentrations in the influent gas.The TEPA/b-c HT sorbents were characterized by means of X-ray diffraction（XRD）,Fourier transform infrared spectrometry（FT–IR）,thermal gravimetric analysis（TGA）,Brunauer–Emmet–Teller（BET）analysis of nitrogen（N2）adsorption/desorption and carbon–hydrogen–nitrogen（CHN）elemental analysis.Moreover,a full 2~4factorial design with three central points at a 95%confidence interval was used to screen important factor（s）on the CO2adsorption capacity.It revealed that85.0%variation in the capacity came from the influence of four main factors and the15.0%one was from their interactions.A face-centered central composite design response surface method（FCCCD–RSM）was then employed to optimize the condition,the maximal capacity of 5.5–6.1 mmol/g was achieved when operating with a TEPA loading level of 39%–49%（W/W）,temperature of 76–90℃,W/F ratio of 1.7–2.60（g·sec）/cm^3and CO2concentration of 27%–41%（V/V）.The model fitted sufficiently the experimental data with an error range of±1.5%.From cyclical adsorption/desorption and selectivity at the optimal condition,the 40%TEPA/b-c HT still expressed its effective performance after eight cycles.展开更多
In this study,flower-like MoS2 constructed by nanosheets was synthesized by a simple hydrothermal method.The hydrothermal process was optimized and the effects of hydrothermal condition,including reaction temperature,...In this study,flower-like MoS2 constructed by nanosheets was synthesized by a simple hydrothermal method.The hydrothermal process was optimized and the effects of hydrothermal condition,including reaction temperature,reaction time and the ratio of Mo source to S source(Mo:S)in precursor,on microwave absorption performances and dielectric properties were investigated.Our results showed that when the reaction temperature was 180℃,the reaction time was 18 h,and the Mo:S was 1:3.5,the synthesized MoS2 had the best performance:Its minimum reflection loss could reach-55.78 dB,and the corresponding matching thickness was 2.30 mm with a wide effective bandwidth of 5.17 GHz.Further researches on the microwave absorption mechanism revealed that in addition to the destructive interference of electromagnetic waves,various polarization phenomena such as defect dipole polarization were the main reasons for microwave loss.We believe that MoS2 is a candidate for a practical microwave absorbent.展开更多
The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayto...The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.展开更多
基金partly supported by the National Natural Science Foundation of China(Grant No.52272225).
文摘Na_(3)V_(2)(PO_(4))_(3)(NVP)has garnered great attentions as a prospective cathode material for sodium-ion batteries(SIBs)by virtue of its decent theoretical capacity,superior ion conductivity and high structural stability.However,the inherently poor electronic conductivity and sluggish sodium-ion diffusion kinetics of NVP material give rise to inferior rate performance and unsatisfactory energy density,which strictly confine its further application in SIBs.Thus,it is of significance to boost the sodium storage performance of NVP cathode material.Up to now,many methods have been developed to optimize the electrochemical performance of NVP cathode material.In this review,the latest advances in optimization strategies for improving the electrochemical performance of NVP cathode material are well summarized and discussed,including carbon coating or modification,foreign-ion doping or substitution and nanostructure and morphology design.The foreign-ion doping or substitution is highlighted,involving Na,V,and PO_(4)^(3−)sites,which include single-site doping,multiple-site doping,single-ion doping,multiple-ion doping and so on.Furthermore,the challenges and prospects of high-performance NVP cathode material are also put forward.It is believed that this review can provide a useful reference for designing and developing high-performance NVP cathode material toward the large-scale application in SIBs.
基金supported by National Key Research and Development Program of China (2023YFB3307800)National Natural Science Foundation of China (Key Program: 62136003, 62373155)+1 种基金Major Science and Technology Project of Xinjiang (No. 2022A01006-4)the Fundamental Research Funds for the Central Universities。
文摘Hydrocracking is one of the most important petroleum refining processes that converts heavy oils into gases,naphtha,diesel,and other products through cracking reactions.Multi-objective optimization algorithms can help refining enterprises determine the optimal operating parameters to maximize product quality while ensuring product yield,or to increase product yield while reducing energy consumption.This paper presents a multi-objective optimization scheme for hydrocracking based on an improved SPEA2-PE algorithm,which combines path evolution operator and adaptive step strategy to accelerate the convergence speed and improve the computational accuracy of the algorithm.The reactor model used in this article is simulated based on a twenty-five lumped kinetic model.Through model and test function verification,the proposed optimization scheme exhibits significant advantages in the multiobjective optimization process of hydrocracking.
文摘Carbon dioxide-enhanced oil recovery(CO_(2)-EOR)and storage is recognized as an economically feasible technique if used in suitable reservoirs.The type or form and capacity of this CO_(2) sequestration technique is synergistically affected by heat,flow,stress,and chemical reactions.Aimed at addressing the technological issues in applying CO_(2)-EOR and storage in a high water-cut reservoir in Xinjiang,China,this paper proposes a thermo-hydro-mechanical-chemical coupling method during CO_(2) flooding.The potential of CO_(2) sequestration and EOR in the target reservoir is discussed in combination with the surrogate optimization method.This method works better as it considers the evolution of structural trapping,capillary trapping,solubility trapping,and mineral trapping during CO_(2) injection as well as the influence the physical field has on the sequestration capacity for different forms of CO_(2) sequestration.The main mechanisms of CO_(2) sequestration in the high water-cut reservoir is structural trapping,followed by capillary trapping.Solubility trapping and mineral trapping have less contribution to the total sequestration capacity of CO_(2).After optimization,the cumulative oil production was 2.36×10^(6)m^(3),an increase of 0.25×10^(6)m3or 11.9%compared to the pre-optimization value.The CO_(2) sequestration capacity after optimization was 1.39×10^(6)t,which is an increase of 0.23×10^(6)t compared to values obtained before optimization;this effectively increases the area affected by CO_(2) by 24.4%.Of the four trapping mechanisms,capillary trapping and structural trapping showed a high increase of 32.5%and17.28%,respectively,while solubility trapping and mineral trapping only led to an increase of 5.1%and0.43%,respectively.This research could provide theoretical support for fully utilizing the potential of CO_(2)-EOR and sequestration technology.
基金financial support provided by the National Key R&D Program of China(No.2023YFB4104203 and No.2022YFE0129900)financial support from the National Natural Science Foundation of China(No.U22B2075)The funding from the Shandong Postdoctoral Science Foundation(No.SDBX2023017)is also greatly appreciated.
文摘CO_(2) Water-Alternating-Gas(CO_(2)-WAG)injection is not only a method to enhance oil recovery but also a feasible way to achieve CO_(2) sequestration.However,inappropriate injection strategies would prevent the attainment of maximum oil recovery and cumulative CO_(2) storage.Furthermore,the optimization of CO_(2)-WAG is computationally expensive as it needs to frequently call the compositional simulation model that involves various CO_(2) storage mechanisms.Therefore,the surrogate-assisted evolutionary optimization is necessary,which replaces the compositional simulator with surrogate models.In this paper,a surrogate-based multi-objective optimization algorithm assisted by the single-objective pre-search method is proposed.The results of single-objective optimization will be used to initialize the solutions of multi-objective optimization,which accelerates the exploration of the entire Pareto front.In addition,a convergence criterion is also proposed for the single-objective optimization during pre-search,and the gradient of surrogate models is adopted as the convergence criterion.Finally,the method proposed in this work is applied to two benchmark reservoir models to prove its efficiency and correctness.The results show that the proposed algorithm achieves a better performance than the conventional ones for the multi-objective optimization of CO_(2)-WAG.
文摘The growing demand for carbon neutrality has heightened the focus on CO_(2)hydrogenation as a viable strategy for transforming carbon dioxide into valuable chemicals and fuels.Advanced machine learning(ML)approaches integrate materials science with artificial intelligence,enabling scientists to identify hidden patterns in datasets,make informed decisions,and reduce the need for labor-intensive,repetitive experimentation.This review provides a comprehensive overview of ML applications in the thermocatalytic hydrogenation of CO_(2).Following an introduction to ML tools and workflows,various ML algorithms employed in CO_(2)hydrogenation are systematically categorized and reviewed.Next,the application of ML in catalyst discovery is discussed,highlighting its role in identifying optimal compositions and structures.Then,ML-driven strategies for process optimization,particularly in enhancing CO_(2)conversion and product selectivity,are examined.Studies modeling descriptors,spanning catalyst properties and reaction conditions,to predict catalytic performance are analyzed.Consequently,ML-based mechanistic studies are reviewed to elucidate reaction pathways,identify key intermediates,and optimize catalyst performance.Finally,key challenges and future perspectives in leveraging ML for advancing CO_(2)hydrogenation research are presented.
基金supported by the National Natural Science Foundation of China(Nos.52374064,52274056)China Scholarship Council(No.202406450086).
文摘Carbon dioxide Enhanced Oil Recovery(CO_(2)-EOR)technology guarantees substantial underground CO_(2) sequestration while simultaneously boosting the production capacity of subsurface hydrocarbons(oil and gas).However,unreasonable CO_(2)-EOR strategies,encompassing well placement and well control parameters,will lead to premature gas channeling in production wells,resulting in large amounts of CO_(2) escape without any beneficial effect.Due to the lack of prediction and optimization tools that integrate complex geological and engineering information for the widely used CO_(2)-EOR technology in promising industries,it is imperative to conduct thorough process simulations and optimization evaluations of CO_(2)-EOR technology.In this paper,a novel optimization workflow that couples the AST-GraphTrans-based proxy model(Attention-based Spatio-temporal Graph Transformer)and multi-objective optimization algorithm MOPSO(Multi-objective Particle Swarm Optimization)is established to optimize CO_(2)-EOR strategies.The workflow consists of two outstanding components.The AST-GraphTrans-based proxy model is utilized to forecast the dynamics of CO_(2) flooding and sequestration,which includes cumulative oil production,CO_(2) sequestration volume,and CO_(2) plume front.And the MOPSO algorithm is employed for achieving maximum oil production and maximum sequestration volume by coordinating well placement and well control parameters with the containment of gas channeling.By the collaborative coordination of the two aforementioned components,the AST-GraphTrans proxy-assisted optimization workflow overcomes the limitations of rapid optimization in CO_(2)-EOR technology,which cannot consider high-dimensional spatio-temporal information.The effectiveness of the proposed workflow is validated on a 2D synthetic model and a 3D field-scale reservoir model.The proposed workflow yields optimizations that lead to a significant increase in cumulative oil production by 87%and 49%,and CO_(2) sequestration volume enhancement by 78%and 50%across various reservoirs.These findings underscore the superior stability and generalization capabilities of the AST-GraphTrans proxy-assisted framework.The contribution of this study is to provide a more efficient prediction and optimization tool that maximizes CO_(2) sequestration and oil recovery while mitigating CO_(2) gas channeling,thereby ensuring cleaner oil production.
基金financial supports from the National Natural Science Foundation of China-Youth Project(51801076)the Provincial Colleges and Universities Natural Science Research Project of Jiangsu Province(18KJB430009)+1 种基金the Postdoctoral Research Support Project of Jiangsu Province(1601055C)the Senior Talents Research Startup of Jiangsu University(14JDG126)。
文摘To solve the problems of deformation,micro-cracks,and residual tensile stress in laser cladding coatings,the technique of laser cladding with Fe-based memory alloy can be considered.However,the process of in-situ synthesis of Fe-based memory alloy coatings is extremely complex.At present,there is no clear guidance scheme for its preparation process,which limits its promotion and application to some extent.Therefore,in this study,response surface methodology(RSM)was used to model the response surface between the target values and the cladding process parameters.The NSGA-2 algorithm was employed to optimize the process parameters.The results indicate that the composite optimization method consisting of RSM and the NSGA-2 algorithm can establish a more accurate model,with an error of less than 4.5%between the predicted and actual values.Based on this established model,the optimal scheme for process parameters corresponding to different target results can be rapidly obtained.The prepared coating exhibits a uniform structure,with no defects such as pores,cracks,and deformation.The surface roughness and microhardness of the coating are enhanced,the shaping quality of the coating is effectively improved,and the electrochemical corrosion performance of the coating in 3.5%NaCl solution is obviously better than that of the substrate,providing an important guide for engineering applications.
基金funded by State Grid Beijing Electric Power Company Technology Project,grant number 520210230004.
文摘The park-level integrated energy system(PIES)is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration.However,current carbon trading mechanisms lack sufficient incentives for emission reductions,and traditional optimization algorithms often face challenges with convergence and local optima in complex PIES scheduling.To address these issues,this paper introduces a low-carbon dispatch strategy that combines a reward-penalty tiered carbon trading model with P2G-CCS integration,hydrogen utilization,and the Secretary Bird Optimization Algorithm(SBOA).Key innovations include:(1)A dynamic reward-penalty carbon trading mechanism with coefficients(μ=0.2,λ=0.15),which reduces carbon trading costs by 47.2%(from$694.06 to$366.32)compared to traditional tiered models,incentivizing voluntary emission reductions.(2)The integration of P2G-CCS coupling,which lowers natural gas consumption by 41.9%(from$4117.20 to$2389.23)and enhances CO_(2) recycling efficiency,addressing the limitations of standalone P2G or CCS technologies.(3)TheSBOA algorithm,which outperforms traditionalmethods(e.g.,PSO,GWO)in convergence speed and global search capability,avoiding local optima and achieving 24.39%faster convergence on CEC2005 benchmark functions.(4)A four-energy PIES framework incorporating electricity,heat,gas,and hydrogen,where hydrogen fuel cells and CHP systems improve demand response flexibility,reducing gas-related emissions by 42.1%and generating$13.14 in demand response revenue.Case studies across five scenarios demonstrate the strategy’s effectiveness:total operational costs decrease by 14.7%(from$7354.64 to$6272.59),carbon emissions drop by 49.9%(from 5294.94 to 2653.39kg),andrenewable energyutilizationincreases by24.39%(from4.82%to8.17%).These results affirmthemodel’s ability to reconcile economic and environmental goals,providing a scalable approach for low-carbon transitions in industrial parks.
基金supported in part by the National Research Foundation of Korea (NRF-2021H1D3A2A01082705).
文摘The dynamic traveling salesman problem(DTSP)is significant in logistics distribution in real-world applications in smart cities,but it is uncertain and difficult to solve.This paper proposes a scheme library-based ant colony optimization(ACO)with a two-optimization(2-opt)strategy to solve the DTSP efficiently.The work is novel and contributes to three aspects:problemmodel,optimization framework,and algorithmdesign.Firstly,in the problem model,traditional DTSP models often consider the change of travel distance between two nodes over time,while this paper focuses on a special DTSP model in that the node locations change dynamically over time.Secondly,in the optimization framework,the ACO algorithm is carried out in an offline optimization and online application framework to efficiently reuse the historical information to help fast respond to the dynamic environment.The framework of offline optimization and online application is proposed due to the fact that the environmental change inDTSPis caused by the change of node location,and therefore the newenvironment is somehowsimilar to certain previous environments.This way,in the offline optimization,the solutions for possible environmental changes are optimized in advance,and are stored in a mode scheme library.In the online application,when an environmental change is detected,the candidate solutions stored in the mode scheme library are reused via ACO to improve search efficiency and reduce computational complexity.Thirdly,in the algorithm design,the ACO cooperates with the 2-opt strategy to enhance search efficiency.To evaluate the performance of ACO with 2-opt,we design two challenging DTSP cases with up to 200 and 1379 nodes and compare them with other ACO and genetic algorithms.The experimental results show that ACO with 2-opt can solve the DTSPs effectively.
基金supported by the National Natural Science Foundation of China (61873079,51707050)
文摘Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Although IT2 FNNs have more advantages in processing uncertain, incomplete, or imprecise information compared to their type-1 counterparts, a large number of parameters need to be tuned in the IT2 FNNs,which increases the difficulties of their design. In this paper,big bang-big crunch(BBBC) optimization and particle swarm optimization(PSO) are applied in the parameter optimization for Takagi-Sugeno-Kang(TSK) type IT2 FNNs. The employment of the BBBC and PSO strategies can eliminate the need of backpropagation computation. The computing problem is converted to a simple feed-forward IT2 FNNs learning. The adoption of the BBBC or the PSO will not only simplify the design of the IT2 FNNs, but will also increase identification accuracy when compared with present methods. The proposed optimization based strategies are tested with three types of interval type-2 fuzzy membership functions(IT2FMFs) and deployed on three typical identification models. Simulation results certify the effectiveness of the proposed parameter optimization methods for the IT2 FNNs.
基金supported by the National Natural Science Foundation of China (No. 51008297)the Hi-Tech Research and Development Program (863) of China(No. 2007AA06Z347)the National Major Science & Technology Projects for Water Pollution Control and Management (No. 2012ZX07202-005)
文摘A microwave-H202 process for sludge pretreatment exhibited high efticiencies of releasing organics, nitrogen, and phosphorus, but large quantifies of H202 residues were detected. A uniform design method was thus employed in this study to further optimize H202 dosage by investigating effects of pH and H202 dosage on the amount of 1-I202 residue and releases of organics, nitrogen, and phosphorus. A regression model was established with pH and H202 dosage as the independent variables, and H202 residue and releases of organics, nitrogen, and phosphorus as the dependent variables. In the optimized microwave-H202 process, the pH value of the sludge was firstly adjusted to 11.0, then the sludge was heated to 80~C and H202 was dosed at a H202 ：mixed liquor suspended solids （MLSS） ratio of 0.2, and the sludge was finally heated to 100~C by microwave irradiation. Compared to the microwave-H202 process without optimization, the H202 dosage and the utilization rate of H202 in the optimized microwave-H202 process were reduced by 80% and greatly improved by 3.87 times, respectively, when the H202：MLSS dosage ratio was decreased from 1.0 to 0.2, resulting in nearly the same release rate of soluble chemical oxygen demand in the microwave-H202 process without optimization at H202：MLSS ratio of 0.5.
基金Project(3502Z20179026)supported by Xiamen Science and Technology Project,China。
文摘Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed. One was the disorderly charging and discharging mode based on travel habits, and the other was the orderly charging and discharging mode based on time-of-use(TOU) price;Monte Carlo method was used to verify the case. The scheme of the capacity optimization of photovoltaic charging station under two different charging and discharging modes with V2 G was proposed. The mathematical models of the objective function with the maximization of energy efficiency, the minimization of the investment and the operation cost of the charging system were established. The range of decision variables, constraints of the requirements of the power balance and the strategy of energy exchange were given. NSGA-Ⅱ and NSGA-SA algorithm were used to verify the cases, respectively. In both algorithms, by comparing with the simulation results of the two different modes, it shows that the orderly charging and discharging mode with V2 G is obviously better than the disorderly charging and discharging mode in the aspects of alleviating the pressure of power grid, reducing system investment and improving energy efficiency.
文摘In the present study, a great effort was made to improve the performance of an industrial liquefied petroleum gas(LPG) and natural gas liquid(NGL) production unit in one of the major gas refinery located at Pars special economic zone in Iran. To demonstrate and obtain the optimal condition, the unit was simulated by using a steady-state flowsheet simulator, i.e. Aspen Plus, under different operational conditions. According to the simulation results,the unit was not operational under its optimal conditions due to some defects in the cooling system at top stage of the debutanizer tower(DBT) during hot and humid seasons. Additionally, the vapor pressure of produced LPG and accordingly the amount of its flaring were decreased by reducing the temperature of debutanizer tower at top stages. In the optimization section, the DBT condenser and reboiler heat duty, temperature, and pressure were regulated as adjustable parameters. The simulation results demonstrated that by applying the optimum suggestion in the hot months, the reflux stream temperature was reached about 55 ℃ which caused an efficient increment in LPG production(about 4%) with adjusting the propane component in LPG, based on the standard range as the plant criteria. Moreover, after applying modifications, about 750 t of LPG product was saved from flaring during five hot months of the year, which resulted in 360000 USD extra annual income for the company.Finally, from environmental point of view, this optimization caused to reduce 81 t of CO_2 emission to the environment. Therefore, the current investigation must be introduced as a friendly environmentally process.
基金Item Sponsored by National Natural Science Foundation of China(51090384)National High Technology Research and Development Program(863 Program)of China(2012AA062302,2012AA062304)Fundamental Research Funds for the Central Universities of China(N110202001)
文摘In order to clarify the slag system of high Cr2O3 vanadium-titanium magnetite smelting in BF （blast furnace）, the melting properties of slag samples prepared by analytically pure reagents were measured. By means of orthogonal test synthetic weighted score method, the optimal slag for high Cr2O3 vanadium-titanium magnetite was obtained, which contained 10% MgO, 8% TiO2 and 15% Al2O3, with the binary basicity being 1.15. In addition, the effects of basicity, MgO, TiO2 and A12 03 on slag melting properties were investigated by single factor test, and the results showed that, with increasing the basicity or TiO2 content, melting temperature （Tin） increased, whereas initial vis- cosity （r/0） and high temperature viscosity （r/h） decreased. With increasing the MgO content, Tm decreased firstly and then increased. With increasing the Al2 O3 content, Tm increased, and η0 and r/h decreased firstly and then increased.
基金co-supported by the National Natural Science Foundation of China(No.51505387)the China Postdoctoral Science Foundation funded project(No.2016M602860)the 111 project(No.B13044)
文摘In situ formed TiB2 particle reinforced aluminum matrix composites （TiB2/Al MMCs） have some extraordinary properties which make them be a promising material for high performance aero-engine blade. Due to the influence of TiB2 particles, the machinability is still a problem which restricts the application of TiB2/Al MMCs. In order to meet the industrial requirements, the influence of TiB2 particles on the machinability of TiB2/Al MMCs was investigated experimentally. Moreover, the optimal machining conditions for this kind of MMCs were investigated in this study. The major conclusions are： （1） the machining force of TiB2/Al MMCs is bigger than that of non- reinforced alloy and mainly controlled by feed rate; （2） the residual stress of TiB2/AI MMCs is compressive while that of non-reinforced alloy is nearly neutral; （3） the surface roughness of TiB2/Al MMCs is smaller than that of non-reinforced alloy under the same cutting speed, but reverse result was observed when the feed rate increased; （4） a multi-objective optimization model for surface roughness and material removal rate （MRR） was established, and a set of optimal parameter combinations of the machining was obtained. The results show a great difference from SiC particle reinforced MMCs and provide a useful guide for a better control of machining process of this material.
基金supported by the Rachadapisek Sompote Fund for Postdoctoral Fellowshipthe Thailand Research Fund (No. IRG5780001)+1 种基金Chulalongkorn University and Faculty of Science of Chulalongkorn Universitythe Department of Chemical Technology, Faculty of Science, Chulalongkorn University for the instrument support in this work
文摘The objective of this research was to investigate CO2adsorption capacity of tetraethylenepentamine-functionalized basic-modified calcined hydrotalcite（TEPA/b-c HT）sorbents at atmospheric pressure formed under varying TEPA loading levels,temperatures,sorbent weight to total gaseous flow rate（W/F）ratios and CO2concentrations in the influent gas.The TEPA/b-c HT sorbents were characterized by means of X-ray diffraction（XRD）,Fourier transform infrared spectrometry（FT–IR）,thermal gravimetric analysis（TGA）,Brunauer–Emmet–Teller（BET）analysis of nitrogen（N2）adsorption/desorption and carbon–hydrogen–nitrogen（CHN）elemental analysis.Moreover,a full 2~4factorial design with three central points at a 95%confidence interval was used to screen important factor（s）on the CO2adsorption capacity.It revealed that85.0%variation in the capacity came from the influence of four main factors and the15.0%one was from their interactions.A face-centered central composite design response surface method（FCCCD–RSM）was then employed to optimize the condition,the maximal capacity of 5.5–6.1 mmol/g was achieved when operating with a TEPA loading level of 39%–49%（W/W）,temperature of 76–90℃,W/F ratio of 1.7–2.60（g·sec）/cm^3and CO2concentration of 27%–41%（V/V）.The model fitted sufficiently the experimental data with an error range of±1.5%.From cyclical adsorption/desorption and selectivity at the optimal condition,the 40%TEPA/b-c HT still expressed its effective performance after eight cycles.
基金financially supported by the National Natural Science Foundation of China(No.21403298)。
文摘In this study,flower-like MoS2 constructed by nanosheets was synthesized by a simple hydrothermal method.The hydrothermal process was optimized and the effects of hydrothermal condition,including reaction temperature,reaction time and the ratio of Mo source to S source(Mo:S)in precursor,on microwave absorption performances and dielectric properties were investigated.Our results showed that when the reaction temperature was 180℃,the reaction time was 18 h,and the Mo:S was 1:3.5,the synthesized MoS2 had the best performance:Its minimum reflection loss could reach-55.78 dB,and the corresponding matching thickness was 2.30 mm with a wide effective bandwidth of 5.17 GHz.Further researches on the microwave absorption mechanism revealed that in addition to the destructive interference of electromagnetic waves,various polarization phenomena such as defect dipole polarization were the main reasons for microwave loss.We believe that MoS2 is a candidate for a practical microwave absorbent.
基金This work was supported of National Natural Science Foundation of China Fund(No.52306033)State Key Laboratory of Engines Fund(No.SKLE-K2022-07)the Jiangxi Provincial Postgraduate Innovation Special Fund(No.YC2022-s513).
文摘The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.
