Application of thermal comfort theory in probabilistic safety assessment of a nuclear power plant

Human factor errors in probabilistic safety assessment(PSA) of a nuclear power plant(NPP) can be prevented using thermal comfort analysis.In this paper,the THERP+HCR model is modified by using PMV (Predicted Mean Vote) and PPD(Predicted Percentage Dissatisfied) index system,so as to obtain the operator cognitive reliability,and to reflect and analyze human perception,thermal comfort status,and cognitive ability in a specific NPP environment.The mechanism of human factors in the PSA is analyzed by operators of skill,rule and knowledge types.The THERP+HCR model modified by thermal comfort theory can reflect the conditions in actual environment,and optimize reliability analysis of human factors.Improving human thermal comfort for different types of operators reduces adverse factors due to human errors,and provides a safe and optimum decision-making for NPPs.

The Fukushima Nuclear Accident: Insights on the Safety Aspects

The Fukushima nuclear accident has generated doubts and questions which need to be properly understood and addressed. This scientific attitude became necessary to allow the use of the nuclear technology for electricity generation around the world. The nuclear stakeholders are working to obtain these technical answers for the Fukushima questions. We believe that, such challenges will be, certainly, implemented in the next reactor generation, following the technological evolution. The purpose of this work is to perform a critical analysis of the Fukushima nuclear accident, focusing at the common cause failures produced by tsunami, as well as an analysis of the main redundant systems. This work also assesses the mitigative procedures and the subsequent consequences of such actions, which gave results below expectations to avoid the progression of the accident, discussing the concept of sharing of structures, systems and components at multi-unit nuclear power plants, and its eventual inappropriate use in safety-related devices which can compromise the nuclear safety, as well as its consequent impact on the Fukushima accident scenario. The lessons from Fukushima must be better learned, aiming the development of new procedures and new safety systems. Thus, the nuclear technology could reach a higher evolution level in its safety requirements. This knowledge will establish a conceptual milestone in the safety system design, becoming necessary the review of the current acceptance criteria of safety-related systems.

Switching Control Method for Optimal State Feedback Controller of Nuclear Reactor Power System

Due to the nonlinearity of the reactor power system, the load tracking situation is closely related to the initial steady-state power and the final steady-state power after the introduction of the state feedback controller. Therefore, when the initial power and the final stable power are determined, the particle swarm optimization algorithm is used to find the optimal controller parameters to minimize the load tracking error. Since there are many combinations of initial stable power and final stable power, it is not possible to find the optimal controller parameters for all combinations, so the neural network is used to take the final stable power and the initial stable power as input, and the optimal controller parameters as the output. This method obtains the optimal state feedback controller switching control method can achieve a very excellent load tracking effect in the case of continuous power change, in the power change time point, the response is fast, in the controller parameter switching time point, the actual power does not fluctuate due to the change of controller parameters. .

Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

Development of CONTHAC-3D and hydrogen distribution analysis of HPR1000

An in-house code,CONTHAC-3D,was developed to calculate and analyze thermal-hydraulic phenomena in containments during severe accidents.CONTHAC-3D is a three-dimensional computational fluid dynamics code that can be applied to predict gas flow,diffusion,and steam condensation in a containment during a severe hypothetical accident,as well as to obtain an estimate of the local hydrogen concentration in various zones of the containment.CONTHAC-3D was developed using multiple models to simulate the features of the proprietary systems and equipment of HPR1000 and ACP100,such as the passive cooling system,passive autocatalytic recombiners and the passive air cooling system.To validate CONTHAC-3D,a GX6 test was performed at the Battelle Model Containment facility.The hydrogen concentration and temperature monitored by the GX6 test are accurately predicted by CONTHAC-3D.Subsequently,the hydrogen distribution in the HPR1000 containment during a severe accident was studied.The results show that the hydrogen removal rates calculated using CONTHAC-3D for different types of PARs agree well with the theoretical values,with an error of less than 1%.As the accident progresses,the hydrogen concentration in the lower compartment becomes higher than that in the large space,which implies that the lower compartment has a higher hydrogen risk than the dome and large space at a later stage of the accident.The amount of hydrogen removed by the PARs placed on the floor of the compartment is small;therefore,raising the installation height of these recombiners appropriately is recommended.However,we do not recommend installing all autocatalytic recombiners at high positions.The study findings in regard to the hydrogen distribution in the HPR1000 containment indicate that CONTHAC-3D can be applied to the study of hydrogen risk containment.

Trial application of the envelope method to the potential ambiguity problem

The optical potential ambiguity is a long-standing problem in the analysis of elastic scattering data.For a specific collid-ing system,ambiguous potential families can lead to different behaviors in the nearside and farside scattering components.By contrast,the envelope method can decompose the experimental data into two components with negative and positive deflection angles,respectively.Hence,a question arises as to whether the comparison between the calculated nearside(or farside)component and the derived positive-deflection-angle(or negative-deflection-angle)component can help analyze the potential ambiguity problem.In this study,we conducted a trial application of the envelope method to the potential ambiguity problem.The envelope method was improved by including uncertainties in the experimental data.The colliding systems of 16O+28Si at 215.2 MeV and 12C+12C at 1016 MeV were considered in the analyses.For each colliding system,the angular distribution experimental data were described nearly equally well by two potential sets,one of which is“surface transpar-ent”and the other is refractive.The calculated angular distributions were decomposed into nearside and farside scattering components.Using the improved envelope method,the experimental data were decomposed into the positive-deflection-angle and negative-deflection-angle components,which were then compared with the calculated nearside and farside components.The capability of the envelope method to analyze the potential ambiguities was also discussed.

Effects of counter-current driven by electron cyclotron waves on neoclassical tearing mode suppression

Through theoretical analysis,we construct a physical model that includes the influence of counter-external driven current opposite to the plasma current direction in the neoclassical tearing mode(NTM).The equation is used with this model to obtain the modified Rutherford equation with co-current and counter-current contributions.Consistent with the reported experimental results,numerical simulations have shown that the localized counter external current can only partially suppress NTM when it is far from the resonant magnetic surface.Under some circumstances,the Ohkawa mechanism dominated current drive(OKCD)by electron cyclotron waves can concurrently create both co-current and counter-current.In this instance,the minimal electron cyclotron wave power that suppresses a particular NTM was calculated by the Rutherford equation.The result is marginally less than when taking co-current alone into consideration.As a result,to suppress NTM using OKCD,one only needs to align the co-current with a greater OKCD peak well with the resonant magnetic surface.The effect of its lower counter-current does not need to be considered because the location of the counter-current deviates greatly from the resonant magnetic surface.

Directly predicting N_(2) electroreduction reaction free energy using interpretable machine learning with non-DFT calculated features

Electrocatalytic nitrogen reduction to ammonia has garnered significant attention with the blooming of single-atom catalysts(SACs),showcasing their potential for sustainable and energy-efficient ammonia production.However,cost-effectively designing and screening efficient electrocatalysts remains a challenge.In this study,we have successfully established interpretable machine learning(ML)models to evaluate the catalytic activity of SACs by directly and accurately predicting reaction Gibbs free energy.Our models were trained using non-density functional theory(DFT)calculated features from a dataset comprising 90 graphene-supported SACs.Our results underscore the superior prediction accuracy of the gradient boosting regression(GBR)model for bothΔg(N_(2)→NNH)andΔG(NH_(2)→NH_(3)),boasting coefficient of determination(R^(2))score of 0.972 and 0.984,along with root mean square error(RMSE)of 0.051 and 0.085 eV,respectively.Moreover,feature importance analysis elucidates that the high accuracy of GBR model stems from its adept capture of characteristics pertinent to the active center and coordination environment,unveilling the significance of elementary descriptors,with the colvalent radius playing a dominant role.Additionally,Shapley additive explanations(SHAP)analysis provides global and local interpretation of the working mechanism of the GBR model.Our analysis identifies that a pyrrole-type coordination(flag=0),d-orbitals with a moderate occupation(N_(d)=5),and a moderate difference in covalent radius(r_(TM-ave)near 140 pm)are conducive to achieving high activity.Furthermore,we extend the prediction of activity to more catalysts without additional DFT calculations,validating the reliability of our feature engineering,model training,and design strategy.These findings not only highlight new opportunity for accelerating catalyst design using non-DFT calculated features,but also shed light on the working mechanism of"black box"ML model.Moreover,the model provides valuable guidance for catalytic material design in multiple proton-electron coupling reactions,particularly in driving sustainable CO_(2),O_(2),and N_(2) conversion.

Nonlinear dynamics of the reversed shear Alfvén eigenmode in burning plasmas

In a tokamak fusion reactor operated at steady state,the equilibrium magnetic field is likely to have reversed shear in the core region,as the noninductive bootstrap current profile generally peaks off-axis.The reversed shear Alfvén eigenmode(RSAE)as a unique branch of the shear Alfvén wave in this equilibrium,can exist with a broad spectrum in wavenumber and frequency,and be resonantly driven unstable by energetic particles(EP).After briefly discussing the RSAE linear properties in burning plasma condition,we review several key topics of the nonlinear dynamics for the RSAE through both wave-EP resonance and wave-wave coupling channels,and illustrate their potentially important role in reactor-scale fusion plasmas.By means of simplified hybrid MHD-kinetic simulations,the RSAEs are shown to have typically broad phase space resonance structure with both circulating and trapped EP,as results of weak/vanishing magnetic shear and relatively low frequency.Through the route of wave-EP nonlinearity,the dominant saturation mechanism is mainly due to the transported resonant EP radially decoupling with the localized RSAE mode structure,and the resultant EP transport generally has a convective feature.The saturated RSAEs also undergo various nonlinear couplings with other collective oscillations.Two typical routes as parametric decay and modulational instability are studied using nonlinear gyrokinetic theory,and applied to the scenario of spontaneous excitation by a finite amplitude pump RSAE.Multiple RSAEs could naturally couple and induce the spectral energy cascade into a low frequency Alfvénic mode,which may effectively transfer the EP energy to fuel ions via collisionless Landau damping.Moreover,zero frequency zonal field structure could be spontaneously excited by modulation of the pump RSAE envelope,and may also lead to saturation of the pump RSAE by both scattering into stable domain and local distortion of the continuum structure.

An Improved CREAM Model Based on DS Evidence Theory and DEMATEL

Cognitive Reliability and Error Analysis Method(CREAM)is widely used in human reliability analysis(HRA).It defines nine common performance conditions(CPCs),which represent the factors thatmay affect human reliability and are used to modify the cognitive failure probability(CFP).However,the levels of CPCs are usually determined by domain experts,whichmay be subjective and uncertain.What’smore,the classicCREAMassumes that the CPCs are independent,which is unrealistic.Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability evaluation.To address the issue of uncertain information modeling and processing,this paper introduces evidence theory to evaluate the CPC levels in specific scenarios.To address the issue of dependence modeling,the Decision-Making Trial and Evaluation Laboratory(DEMATEL)method is used to process the dependence among CPCs and calculate the relative weights of each CPC,thus modifying the multiplier of the CPCs.The detailed process of the proposed method is illustrated in this paper and the CFP estimated by the proposed method is more reasonable.

Radioisotope production using lasers:From basic science to applications

The discovery of chirped pulse amplification has led to great improvements in laser technology,enabling energetic laser beams to be compressed to pulse durations of tens of femtoseconds and focused to a few micrometers.Protons with energies of tens of MeV can be accelerated using,for instance,target normal sheath acceleration and focused on secondary targets.Under such conditions,nuclear reactions can occur,with the production of radioisotopes suitable for medical application.The use of high-repetition lasers to produce such isotopes is competitive with conventional methods mostly based on accelerators.In this paper,we study the production of^(67)Cu,^(63)Zn,^(18)F,and^(11)C,which are currently used in positron emission tomography and other applications.At the same time,we study the reactions^(10)B(p,α)^(7)Be and^(70)Zn(p,4n)^(67)Ga to put further constraints on the proton distributions at different angles,as well as the reaction^(11)B(p,α)^(8)Be relevant for energy production.The experiment was performed at the 1 PW laser facility at VegaⅢin Salamanca,Spain.Angular distributions of radioisotopes in the forward(with respect to the laser direction)and backward directions were measured using a high purity germanium detector.Our results are in reasonable agreement with numerical estimates obtained following the approach of Kimura and Bonasera[Nucl.Instrum.Methods Phys.Res.,Sect.A 637,164–170(2011)].

Collisionless shock acceleration of protons in a plasma slab produced in a gas jet by the collision of two laser-driven hydrodynamic shockwaves

We have recently proposed a new technique of plasma tailoring by laser-driven hydrodynamic shockwaves generated on both sides of a gas jet[Marquès et al.,Phys.Plasmas 28,023103(2021)].In a continuation of this numerical work,we study experimentally the influence of the tailoring on proton acceleration driven by a high-intensity picosecond laser in three cases:without tailoring,by tailoring only the entrance side of the picosecond laser,and by tailoring both sides of the gas jet.Without tailoring,the acceleration is transverse to the laser axis,with a low-energy exponential spectrum,produced by Coulomb explosion.When the front side of the gas jet is tailored,a forward acceleration appears,which is significantly enhanced when both the front and back sides of the plasma are tailored.This forward acceleration produces higher-energy protons,with a peaked spectrum,and is in good agreement with the mechanism of collisionless shock acceleration(CSA).The spatiotemporal evolution of the plasma profile is characterized by optical shadowgraphy of a probe beam.The refraction and absorption of this beam are simulated by post-processing 3D hydrodynamic simulations of the plasma tailoring.Comparison with the experimental results allows estimation of the thickness and near-critical density of the plasma slab produced by tailoring both sides of the gas jet.These parameters are in good agreement with those required for CSA.

Nonlinear Impact Damage Evolution of Charpy Type and Analysis of Its Key Influencing Factors

The current research of Charpy impact mainly focuses on obtaining the ductile brittle transition temperature of materials by experiments.Compared with experiments,numerical simulation can study many problems with harsh conditions.However,there are still few studies on the influence of geometric factors such as side grooves.In this paper,the geometry of standard Charpy impact test is designed.Specimens with different widths and side grooves are tested.The finite element model of Charpy impact was established by ABAQUS software.Use test results and simulation results to verify each other.The effects of sample width,side groove depth and side groove bottom fillet on the impact fracture resistance of the sample were studied.The results show that the specimen width is positively correlated with the impact toughness of the specimen.The side groove greatly reduces the impact toughness of the material;the toughness of side groove decreases with the increase of depth;the fracture toughness of side groove decreases with the increase of fillet at the bottom of side groove.The proportion of toughness energy to impact energy of samples was analyzed.The results show that the toughness energy accounts for about 70%of the impact energy of the sample,which has little to do with the geometric characteristics of the sample.This study presents a reliable method for studying Charpy impact tests.The influence of geometric parameters is obtained,which provides a reference method for the study of impact toughness of high toughness materials.

The large-scale modular BGO detection array(LAMBDA)design and test

Total absorption gamma-ray spectroscopy(TAGS)is a powerful tool for measuring complexγ transitions,which has been effectively applied to the study of reactor decay heat.This paper presents the design of a new TAGS detector,the large-scale modular BGO detection array(LAMBDA),tailored for measuringβ-decay intensity distributions of fission products.The modular design allows the LAMBDA detectors to be assembled in various configurations.The final version of LAMBDA consists of 102 identical 60 mm×60 mm×120 mm BGO crystals and exhibits a high full-energy peak efficiency exceeding 80%at 0.5∼8 MeV based on a Monte Carlo simulation.Currently,approximately half of the LAMBDA modules have been manufactured.Tests usingγ-ray sources and nuclear reactions demonstrated favorable energy resolution,energy linearity,and efficiency uniformity across the modules.Forty-eight modules have been integrated into the prototype LAMBDA-I.The capability of LAMBDA-I inβ-delayed-decay experiments was evaluated by commissioning measurements using the ^(152)Eu source.

Development of a PARCS/Serpent model for neutronics analysis of the Dalat nuclear research reactor

Cross-sectional homogenization for full-core calculations of small and complex reactor configurations,such as research reactors,has been recently recognized as an interesting and challenging topic.This paper presents the development of a PARCS/Serpent model for the neutronics analysis of a research reactor type TRIGA Mark-II loaded with Russian VVR-M2 fuel(known as the Dalat Nuclear Research Reactor or DNRR).The full-scale DNRR model and a supercell model for a shim/safety rod and its surrounding fuel bundles with the Monte Carlo code Serpent 2 were proposed to generate homogenized fewgroup cross sections for full-core diffusion calculations with PARCS.The full-scale DNRR model with Serpent 2 was also utilized as a reference to verify the PARCS/Serpent calculations.Comparison of the effective neutron multiplication factors,radial and axial core power distributions,and control rod worths showed a generally good agreement between PARCS and Serpent 2.In addition,the discrepancies between the PARCS and Serpent 2 results are also discussed.Consequently,the results indicate the applicability of the PARCS/Serpent model for further steady state and transient analyses of the DNRR.

k_(eff)uncertainty quantification and analysis due to nuclear data during the full lifetime burnup calculation for a small-sized prismatic high temperature gas-cooled reactor

To benefit from recent advances in modeling and computational algorithms,as well as the availability of new covariance data,sensitivity and uncertainty analyses are needed to quantify the impact of uncertain sources on the design parameters of small prismatic high-temperature gascooled reactors(HTGRs).In particular,the contribution of nuclear data to the k_(eff)uncertainty is an important part of the uncertainty analysis of small-sized HTGR physical calculations.In this study,a small-sized HTGR designed by China Nuclear Power Engineering Co.,Ltd.was selected for k_(eff)uncertainty analysis during full lifetime burnup calculations.Models of the cold zero power(CZP)condition and full lifetime burnup process were constructed using the Reactor Monte Carlo Code RMC for neutron transport calculation,depletion calculation,and sensitivity and uncertainty analysis.For the sensitivity analysis,the Contribution-Linked eigenvalue sensitivity/Uncertainty estimation via Track length importance Characterization(CLUTCH)method was applied to obtain sensitive information,and the "sandwich" method was used to quantify the k_(eff)uncertainty.We also compared the k_(eff)uncertainties to other typical reactors.Our results show that ^(235)U is the largest contributor to k_(eff)uncertainty for both the CZP and depletion conditions,while the contribution of ^(239)Pu is not very significant because of the design of low discharge burnup.It is worth noting that the radioactive capture reaction of ^(28)Si significantly contributes to the k_(eff)uncertainty owing to its specific fuel design.However,the k_(eff)uncertainty during the full lifetime depletion process was relatively stable,only increasing by 1.12%owing to the low discharge burnup design of small-sized HTGRs.These numerical results are beneficial for neutronics design and core parameters optimization in further uncertainty propagation and quantification study for small-sized HTGR.

Rapid interrogation of special nuclear materials by combining scattering and transmission nuclear resonance fluorescence spectroscopy

The smuggling of special nuclear materials(SNMs)across national borders is becoming a serious threat to nuclear nonproliferation.This paper presents a feasibility study on the rapid interrogation of concealed SNMs by combining scattering and transmission nuclear resonance fluorescence(s NRF and t NRF)spectroscopy.In s NRF spectroscopy,SNMs such as^(235,238)U are excited by a wide-band photon beam of appropriate energy and exhibit unique NRF signatures.Monte Carlo simulations show that one-dimensional scans can realize isotopic identification of concealed^(235,238)U when the detector array used for interrogation has sufficiently high energy resolution.The simulated isotopic ratio^(235U/238)U is in good agreement with the theoretical value when the SNMs are enclosed in relatively thin iron.This interrogation is followed by t NRF spectroscopy using a narrow-band photon beam with the goal of obtaining tomographic images of the concealed SNMs.The reconstructed image clearly reveals the position of the isotope^(235)U inside an iron rod.It is shown that the interrogation time of s NRF and t NRF spectroscopy is one order of magnitude lower than that when only t NRF spectroscopy is used and results in a missed-detection rate of 10^(-3).The proposed method can also be applied for isotopic imaging of other SNMs such as^(239,240)Pu and^(237)Np.

Loss of offsite power (LOOP) accident analysis by integration of deterministic and probabilistic approaches in Bushehr-1 VVER-1000/V446 nuclear power plant

The results of an accident analysis for the loss of offsite power(LOOP)scenario in a reference Bushehr-1 VVER-1000/V446 nuclear power plant(NPP)are presented in this paper.This study attempted to provide a better analysis of LOOP accident management by integrating deterministic and probabilistic approaches.The RELAP5 code was used to investigate the occurrence of specific thermal–hydraulic phenomena.The probabilistic safety assessment of the LOOP accident is presented using the SAPHIRE software.LOOP accident data were extracted from the Bushehr NPP final safety analysis reports and probabilistic safety analysis reports.A deterministic approach was used to reduce the core damage frequency in the probabilistic analysis of LOOP accidents.The probabilistic approach was used to better observe the philosophy of defense in depth and safety margins in the deterministic analysis of the LOOP accident.The results show that the integration of the two approaches in LOOP accident investigations improved accident control.

Fault prediction method for nuclear power machinery based on Bayesian PPCA recurrent neural network model

Early fault warning for nuclear power machinery is conducive to timely troubleshooting and reductions in safety risks and unnecessary costs. This paper presents a novel intelligent fault prediction method, integrated probabilistic principal component analysis(PPCA), multi-resolution wavelet analysis, Bayesian inference, and RNN model for nuclear power machinery that consider data uncertainty and chaotic time series. After denoising the source data, the Bayesian PPCA method is employed for dimensional reduction to obtain a refined data group. A recurrent neural network(RNN) prediction model is constructed, and a Bayesian statistical inference approach is developed to quantitatively assess the prediction reliability of the model. By modeling and analyzing the data collected on the steam turbine and components of a nuclear power plant, the results of the goodness of fit, mean square error distribution, and Bayesian confidence indicate that the proposed RNN model can implement early warning in the fault creep period. The accuracy and reliability of the proposed model are quantitatively verified.

Enhanced graph-based fault diagnostic system for nuclear power plants

Scheduled maintenance and condition-based online monitoring are among the focal points of recent research to enhance nuclear plant safety.One of the most effective ways to monitor plant conditions is by implementing a full-scope,plant-wide fault diagnostic system.However,most of the proposed diagnostic techniques are perceived as unreliable by operators because they lack an explanation module,their implementation is complex,and their decision/inference path is unclear.Graphical formalism has been considered for fault diagnosis because of its clear decision and inference modules,and its ability to display the complex causal relationships between plant variables and reveal the propagation path used for fault localization in complex systems.However,in a graphbased approach,decision-making is slow because of rule explosion.In this paper,we present an enhanced signed directed graph that utilizes qualitative trend evaluation and a granular computing algorithm to improve the decision speed and increase the resolution of the graphical method.We integrate the attribute reduction capability of granular computing with the causal/fault propagation reasoning capability of the signed directed graph and comprehensive rules in a decision table to diagnose faults in a nuclear power plant.Qualitative trend analysis is used to solve the problems of fault diagnostic threshold selection and signed directed graph node state determination.The similarity reasoning and detection ability of the granular computing algorithm ensure a compact decision table and improve the decision result.The performance of the proposed enhanced system was evaluated on selected faults of the Chinese Fuqing 2 nuclear reactor.The proposed method offers improved diagnostic speed and efficient data processing.In addition,the result shows a considerable reduction in false positives,indicating that the method provides a reliable diagnostic system to support further intervention by operators.