Assessing effectiveness of existing building energy-saving reconstruction policy adapted to market development

The market development and policy matching of existing building energy-saving retrofits determine the effectiveness of policies in promoting the operation of existing building energy-saving retrofit market.Based on the perspective of market development to evaluate the effectiveness of existing building energy-saving transformation policy,it is necessary to clarify the basic connotation of the effectiveness of existing building energy-saving transformation policy,systematically analyze the evaluation content,construct a multi-level evaluation index system,and select scientific and effective quantitative evaluation methods to implement a strict evaluation process.

Existing building energy-saving reconstruction market in China: Characteristics and prospect

The development of existing building energy saving reconstruction market depends on the interaction among service market, capital market and technology market. Analysis of the characteristics of both building energy-saving service market, capital market and technology market, and analysis on the role of existing building energy saving reconstruction market development in energy conservation and emission reduction development strategy, energy-saving transformation policy implementation and promotion of other industries landing, will be conducive to energy-saving renovation of existing buildings market cultivation and development.

Sparse Modal Decomposition Method Addressing Underdetermined Vortex-Induced Vibration Reconstruction Problem for Marine Risers

When investigating the vortex-induced vibration(VIV)of marine risers,extrapolating the dynamic response on the entire length based on limited sensor measurements is a crucial step in both laboratory experiments and fatigue monitoring of real risers.The problem is conventionally solved using the modal decomposition method,based on the principle that the response can be approximated by a weighted sum of limited vibration modes.However,the method is not valid when the problem is underdetermined,i.e.,the number of unknown mode weights is more than the number of known measurements.This study proposed a sparse modal decomposition method based on the compressed sensing theory and the Compressive Sampling Matching Pursuit(Co Sa MP)algorithm,exploiting the sparsity of VIV in the modal space.In the validation study based on high-order VIV experiment data,the proposed method successfully reconstructed the response using only seven acceleration measurements when the conventional methods failed.A primary advantage of the proposed method is that it offers a completely data-driven approach for the underdetermined VIV reconstruction problem,which is more favorable than existing model-dependent solutions for many practical applications such as riser structural health monitoring.

Estimation-free spatial-domain image reconstruction of structured illumination microscopy

Structured illumination microscopy(SIM)achieves super-resolution(SR)by modulating the high-frequency information of the sample into the passband of the optical system and subsequent image reconstruction.The traditional Wiener-filtering-based reconstruction algorithm operates in the Fourier domain,it requires prior knowledge of the sinusoidal illumination patterns which makes the time-consuming procedure of parameter estimation to raw datasets necessary,besides,the parameter estimation is sensitive to noise or aberration-induced pattern distortion which leads to reconstruction artifacts.Here,we propose a spatial-domain image reconstruction method that does not require parameter estimation but calculates patterns from raw datasets,and a reconstructed image can be obtained just by calculating the spatial covariance of differential calculated patterns and differential filtered datasets(the notch filtering operation is performed to the raw datasets for attenuating and compensating the optical transfer function(OTF)).Experiments on reconstructing raw datasets including nonbiological,biological,and simulated samples demonstrate that our method has SR capability,high reconstruction speed,and high robustness to aberration and noise.

Post-disaster spatial reconstruction from the perspective of a rural settlement niche in the upper reaches of the Minjiang River

Post-disaster recovery and reconstruction provide an effective way to reduce the disaster vulnerability of, and promote leapfrog development in, an affected area. To date, studies that have used administrative boundaries to investigate the reconstruction of settlement space have not been able to clearly define the real boundaries of land use changes or quantify the degree of response to the ‘Build-Back-Better’ initiative, and have lacked any consideration of the fourth reconstruction stage–development period(10 years). This study constructed a mountain settlement niche and analyzed the characteristics, spatial reconstruction, and drivers of rural settlements during 2009–2019 in the upper reaches of the Minjiang River, southwest China. The results showed the following:(1) Natural factors were the basis for the formation and development of mountain settlement niches. The scale of the settlement niche and its land use structure depended on the physical geography features and the ethnic farming and grazing traditions. The settlement niche provided a realistic boundary for the spatial reconstruction.(2) The layout of residential land around cropland was the common feature of the mountain settlement niche. Of all the land use types, the roads and rural residential lands showed the most change over the 10 years;13,860 residential patches increased in size and 4,742 patches were abandoned.(3) The area of orchards, planted to reconstruct the economy in the mountains, increased by nearly 2.5 times.(4) Collapses, landslides, and debris flow disasters and the ecological red line influenced the spatial reconstruction. While the main focus of post-disaster recovery is spatial reconstruction, initiatives should include economic and spiritual recovery, and should also achieve sustainable development of the region.

Quantitative geochemical reconstruction of Eocene paleoenvironment in Fushun Basin,northeast China

The quantitative estimation of key parameters of paleotemperature and paleoprecipitation is crucial for paleoclimate reconstruction.Geochemical data from mod-ern sediments are highly consistent with climate data,and their relationship can provide an important reference for the quantitative reconstruction of the paleoclimate.In this study,detailed inorganic geochemical analysis was carried out using high-precision sampling of the Paleogene(LFD-1 well)Guchengzi,Jijuntun and Xiloutian Formations in the Fushun Basin located in the mid-latitudes of the Northern Hemisphere.The Eocene Guchengzi Formation(54.51–47.8 Ma)and Jijuntun Formation(47.8–41.2 Ma)in the Fushun Basin were found to have been deposited under a humid climate.The lower(41.2–40.1 Ma)and upper(40.1–37.8 Ma)parts of the Xiloutian Formation were character-ized by semiarid and semihumid–semiarid climates,respec-tively,which is very similar to the paleoclimatic information reflected by organic carbon isotopes.The Eocene Thermal Maximum 2(ETM2,~53.7 Ma),Early Eocene Climatic Optimum(EECO,~53.1–46.5 Ma),Eocene Thermal Maxi-mum 3(ETM 3,~52.8 Ma),and Middle Eocene Climatic Optimum(MECO,~40.7–40.1 Ma)events significantly enhanced chemical weathering during these periods.The rapid increase in pCO_(2)concentration leads to an increase in temperature,precipitation,and surface runoff,exhibiting strong chemical weathering.The mean annual temperature(MATa)and mean annual precipitation(MAPa,MAPb,and MAPc)were estimated using parameters,such as the corrosion index without potassium(CIA-K),CaO/Al_(2)O_(3),and(Na_(2)O+K_(2)O)/Al_(2)O_(3).Comparing MAPa,MAPb,and MAPc with the MAP estimated using pollen data,MAPa and MAPb were found to be more sensitive to the climate during high precipitation periods(precipitation>1000 mm,Guchengzi Formation),and the recovered average precipi-tation was similar to MAP.In contrast,MAPc was more sensitive to the climate during low precipitation periods(precipitation<1000 mm,Jijuntun,and Xiloutian Forma-tions),with higher accuracy.To fully consider the influence of soluble inorganic salts Ca^(2+)and Na^(+),multivariate linear equations of CIA-K and CaO/Al_(2)O_(3)with CIA,and CIA-K and CaO/Al_(2)O_(3)with MAP were constructed,namely MAPd and MAPe.The results show that MAPe has the highest per-formance and can be effectively used to estimate the change of paleoprecipitation in Northeast Asia.

Comparative analysis of two digestive tract reconstruction methods in total laparoscopic radical total gastrectomy

BACKGROUND The incidence of gastric cancer has significantly increased in recent years.Surgical resection is the main treatment,but the method of digestive tract reconstruction after gastric cancer surgery remains controversial.In the current study,we sought to explore a reasonable method of digestive tract reconstruction and improve the quality of life and nutritional status of patients after surgery.To this end,we statistically analyzed the clinical results of patients with gastric cancer who underwent jejunal interposition double-tract reconstruction(DTR)and esophageal jejunum Roux-en-Y reconstruction(RY).AIM To explore the application effect of DTR in total laparoscopic radical total gastrectomy(TLTG)and evaluate its safety and efficacy.METHODS We collected the relevant data of 77 patients who underwent TLTG at the Fourth Hospital of Hebei Medical University from October 2021 to January 2023.Among them,35 cases were treated with DTR,and the remaining 42 cases were treated with traditional RY.After 1:1 propensity score matching,the cases were grouped into 31 cases per group,with evenly distributed data.The clinical characteristics and short-and long-term clinical outcomes of the two groups were statistically analyzed.RESULTS The two groups showed no significant differences in basic data,intraoperative blood loss,number of lymph node dissections,first defecation time after operation,postoperative hospital stay,postoperative complications,and laboratory examination results on the 1st,3rd,and 5th days after operation.The operation time of the DTR group was longer than that of the RY group[(307.58±65.14)min vs(272.45±62.09)min,P=0.016],but the first intake of liquid food in the DTR group was shorter than that in the RY group[(4.45±1.18)d vs(6.0±5.18)d,P=0.028].The incidence of reflux heartburn(Visick grade)and postoperative gallbladder disease in the DTR group was lower than that in the RY group(P=0.033 and P=0.038).Although there was no significant difference in body weight,hemoglobin,prealbumin,and albumin between the two groups at 1,3 and 6 months after surgery,the diet of patients in the DTR group was better than that in the RY group(P=0.031).CONCLUSION The clinical effect of DTR in TLTG is better than that of RY,indicating that it is a more valuable digestive tract reconstruction method in laparoscopic gastric cancer surgery.

Development of D_α band symmetrical visible optical diagnostic for boundary reconstruction on EAST tokamak

To investigate the potential of utilizing visible spectral imaging for controlling the plasma boundary shape during stable operation of plasma in future tokamak, a D_α band symmetric visible light diagnostic system was designed and implemented on the Experimental Advanced Superconducting Tokamak(EAST). This system leverages two symmetric optics for joint plasma imaging. The optical system exhibits a spatial resolution less than 2 mm at the poloidal cross-section, distortion within the field of view below 10%, and relative illumination of 91%.The high-quality images obtained enable clear observation of both the plasma boundary position and the characteristics of components within the vacuum vessel. Following system calibration and coordinate transformation, the image coordinate boundary features are mapped to the tokamak coordinate system. Utilizing this system, the plasma boundary was reconstructed, and the resulting representation showed alignment with the EFIT(Equilibrium Fitting) results. This underscores the system's superior performance in boundary reconstruction applications and provides a diagnostic foundation for boundary shape control based on visible spectral imaging.

Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling schemes.To further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.

Application of multi-planar reconstruction technique in endovascular repair of aortic dissection

BACKGROUND Endovascular repair of aortic dissection is an effective method commonly used in the treatment of Stanford type B aortic dissection.Stent placement during the operation was one-time and could not be repeatedly adjusted during the operation.Therefore,it is of great significance for cardiovascular physicians to fully understand the branch status,position,angle,and other information regarding aortic arch dissection before surgery.AIM To provide more references for clinical cardiovascular physicians to develop treatment plans.METHODS Data from 153 patients who underwent endovascular repair of aortic dissection at our hospital between January 2021 and December 2022 were retrospectively collected.All patients underwent multi-slice spiral computed tomography angiography.Based on distinct post-image processing techniques,the patients were categorized into three groups:Multiplanar reconstruction(MPR)(n=55),volume reconstruction(VR)(n=46),and maximum intensity projection(MIP)(n=52).The detection rate of aortic rupture,accuracy of the DeBakey classification,rotation,and tilt angles of the C-arm during the procedure,dispersion after stent release,and the incidence of late complications were recorded and compared.RESULTS The detection rates of interlayer rupture in the MPR and VR groups were significantly higher than that in the MIP group(P<0.05).The detection rates of De-Bakey subtypesⅠ,Ⅱ,andⅢin the MPR group were higher than those in the MIP group,and the detection rate of typeⅢin the MPR group was significantly higher than that in the VR group(P<0.05).There was no statistically significant difference in the detection rates of typesⅠandⅡcompared to the VR group(P>0.05).The scatter rate of markers and the incidence of complications in the MPR group were significantly lower than those in the VR and MIP groups(P<0.05).CONCLUSION The application of MPR in the endovascular repair of aortic dissection has improved the detection rate of dissection rupture,the accuracy of anatomical classification,and safety.

Scene 3-D Reconstruction System in Scattering Medium

Research on neural radiance fields for novel view synthesis has experienced explosive growth with the development of new models and extensions.The NeRF(Neural Radiance Fields)algorithm,suitable for underwater scenes or scattering media,is also evolving.Existing underwater 3D reconstruction systems still face challenges such as long training times and low rendering efficiency.This paper proposes an improved underwater 3D reconstruction system to achieve rapid and high-quality 3D reconstruction.First,we enhance underwater videos captured by a monocular camera to correct the image quality degradation caused by the physical properties of the water medium and ensure consistency in enhancement across frames.Then,we perform keyframe selection to optimize resource usage and reduce the impact of dynamic objects on the reconstruction results.After pose estimation using COLMAP,the selected keyframes undergo 3D reconstruction using neural radiance fields(NeRF)based on multi-resolution hash encoding for model construction and rendering.In terms of image enhancement,our method has been optimized in certain scenarios,demonstrating effectiveness in image enhancement and better continuity between consecutive frames of the same data.In terms of 3D reconstruction,our method achieved a peak signal-to-noise ratio(PSNR)of 18.40 dB and a structural similarity(SSIM)of 0.6677,indicating a good balance between operational efficiency and reconstruction quality.

Model-driven CT reconstruction algorithm for nano-resolution x-ray phase contrast imaging

The low-density imaging performance of a zone plate-based nano-resolution hard x-ray computed tomography(CT)system can be significantly improved by incorporating a grating-based Lau interferometer. Due to the diffraction, however,the acquired nano-resolution phase signal may suffer splitting problem, which impedes the direct reconstruction of phase contrast CT(nPCT) images. To overcome, a new model-driven nPCT image reconstruction algorithm is developed in this study. In it, the diffraction procedure is mathematically modeled into a matrix B, from which the projections without signal splitting can be generated invertedly. Furthermore, a penalized weighted least-square model with total variation(PWLSTV) is employed to denoise these projections, from which nPCT images with high accuracy are directly reconstructed.Numerical experiments demonstrate that this new algorithm is able to work with phase projections having any splitting distances. Moreover, results also reveal that nPCT images of higher signal-to-noise-ratio(SNR) could be reconstructed from projections having larger splitting distances. In summary, a novel model-driven nPCT image reconstruction algorithm with high accuracy and robustness is verified for the Lau interferometer-based hard x-ray nano-resolution phase contrast imaging.

High formability Mg-Zn-Gd wire facilitates ACL reconstruction via its swift degradation to accelerate intra-tunnel endochondral ossification

After reconstructing the anterior cruciate ligament(ACL),unsatisfactory bone tendon interface healing may often induce tunnel enlargement at the early healing stage.With good biological features and high formability,Magnesium-Zinc-Gadolinium(ZG21)wires are developed to bunch the tendon graft for matching the bone tunnel during transplantation.Microstructure,tensile strength,degradation,and cytotoxicity of ZG21 wire are evaluated.The rabbit model is used for assessing the biological effects of ZG21 wire by Micro-CT,histology,and mechanical test.The SEM/EDS,immunochemistry,and in vitro assessments are performed to investigate the underlying mechanism.Material tests demonstrate the high formability of ZG21 wire as surgical suture.Micro-CT shows ZG21 wire degradation accelerates tunnel bone formation,and histologically with earlier and more fibrocartilage regeneration at the healing interface.The mechanical test shows higher ultimate load in the ZG21 group.The SEM/EDS presents ZG21 wire degradation triggered calcium phosphate(Ca-P)deposition.IHC results demonstrate upregulation of Wnt3a,BMP2,and VEGF at the early phase and TGFβ3 and Type II collagen at the late phase of healing.In vitro tests also confirmed the Ca-P in the metal extract could elevate the expression of Wnt3a,βcatenin,ocn and opn to stimulate osteogenesis.Ex vivo tests of clinical samples indicated suturing with ZG21 wire did not weaken the ultimate loading of human tendon tissue.In conclusion,the ZG21 wire is feasible for tendon graft bunching.Its degradation products accelerated intra-tunnel endochondral ossification at the early healing stage and therefore enhanced bone-tendon interface healing in ACL reconstruction.

FPGA-based position reconstruction method for neutron beam flux spatial distribution measurement in BNCT

A new measurement method for the spatial distribution of neutron beam flux in boron neutron capture therapy(BNCT)is being developed based on the two-dimensional Micromegas detector.To address the issue of long processing times in traditional offline position reconstruction methods,this paper proposes a field programmable gate array based online position reconstruction method utilizing the micro-time projection chamber principle.This method encapsulates key technical aspects:a self-adaptive serial link technique built upon the dynamical adjustment of the delay chain length,fast sorting,a coordinate-matching technique based on the mapping between signal timestamps and random access memory(RAM)addresses,and a precise start point-merging technique utilizing a circular combined RAM.The performance test of the selfadaptive serial link shows that the bit error rate of the link is better than 10-12 at a confidence level of 99%,ensuring reliable data transmission.The experiment utilizing the readout electronics and Micromegas detector shows a spatial resolution of approximately 1.4 mm,surpassing the current method’s resolution level of 5 mm.The beam experiment confirms that the readout electronics system can obtain the flux spatial distribution of neutron beams online,thus validating the feasibility of the position reconstruction method.The online position reconstruction method avoids traditional methods,such as bubble sorting and traversal searching,simplifies the design of the logic firmware,and reduces the time complexity from O(n2)to O(n).This study contributes to the advancement in measuring neutron beam flux for BNCT.

Stabilizing iridium sites via interface and reconstruction regulations for water oxidation in alkaline and acidic media

Exploring effective iridium(Ir)-based electrocatalysts with stable iridium centers is highly desirable for oxygen evolution reaction(OER).Herein,we regulated the incorporation manner of Ir in Co_(3)O_(4)support to stabilize the Ir sites for effective OER.When anchored on the surface of Co_(3)O_(4)in the form of Ir(OH)_6 species,the created Ir-OH-Co interface leads to a limited stability and poor acidic OER due to Ir leaching.When doped into Co_(3)O_(4)lattice,the analyses of X-ray absorption spectroscopy,in-situ Raman,and OER measurements show that the partially replacement of Co in Co_(3)O_(4)by Ir atoms inclines to cause strong electronic effect and activate lattice oxygen in the presence of Ir-O-Co interface,and simultaneously master the reconstruction effect to mitigate Ir dissolution,realizing the improved OER activity and stability in alkaline and acidic environments.As a result,Ir_(lat)@Co_(3)O_(4)with Ir loading of 3.67 wt%requires 294±4 mV/285±3 mV and 326±2 mV to deliver 10 mA cm^(-2)in alkaline(0.1 M KOH/1.0 M KOH)and acidic(0.5 M H_(2)SO_(4))solution,respectively,with good stability.

Steering surface reconstruction of hybrid metal oxides for efficient oxygen evolution reaction in water splitting and zinc-air batteries

Surface reconstruction yields real active species in electrochemical oxygen evolution reaction(OER)conditions;however,rationally regulating reconstruction in a targeted manner for constructing highly active OER electrocatalysts remains a formidable challenge.Here,an electrochemical activation strategy with selective etching was utilized to guide the reconstruction process of a hybrid cobalt-molybdenum oxide(CoMoO_(4)/Co_(3)O_(4)@CC)in a favorable direction to improve the OER performance.Both in-situ Raman and multiple ex-situ characterization tools demonstrate that controlled surface reconstruction can be easily achieved through Mo etching,with the formation of a dynamically stable amorphous-crystalline heterostructure.Theoretical calculations together with experimental results reveal that the synergistic effects between amorphous CoOOH and crystalline Co_(3)O_(4) are crucial in enhancing the catalytic performance.Consequently,the reconstructed CoMoO_(4)/Co_(3)O_(4)@CC exhibits a low overpotential of 250 mV to achieve a current density of 10 mA cm^(-2) in 1 M KOH,and more importantly it can be practiced in electrolytic water splitting and rechargeable zinc-air batteries devices,achieving ultra-long stability for over 500 and 1200 h,respectively.This work provides a promising route for the construction of high-performance electrocatalysts.

Trends in Event Understanding and Caption Generation/Reconstruction in Dense Video:A Review

Video description generates natural language sentences that describe the subject,verb,and objects of the targeted Video.The video description has been used to help visually impaired people to understand the content.It is also playing an essential role in devolving human-robot interaction.The dense video description is more difficult when compared with simple Video captioning because of the object’s interactions and event overlapping.Deep learning is changing the shape of computer vision(CV)technologies and natural language processing(NLP).There are hundreds of deep learning models,datasets,and evaluations that can improve the gaps in current research.This article filled this gap by evaluating some state-of-the-art approaches,especially focusing on deep learning and machine learning for video caption in a dense environment.In this article,some classic techniques concerning the existing machine learning were reviewed.And provides deep learning models,a detail of benchmark datasets with their respective domains.This paper reviews various evaluation metrics,including Bilingual EvaluationUnderstudy(BLEU),Metric for Evaluation of Translation with Explicit Ordering(METEOR),WordMover’s Distance(WMD),and Recall-Oriented Understudy for Gisting Evaluation(ROUGE)with their pros and cons.Finally,this article listed some future directions and proposed work for context enhancement using key scene extraction with object detection in a particular frame.Especially,how to improve the context of video description by analyzing key frames detection through morphological image analysis.Additionally,the paper discusses a novel approach involving sentence reconstruction and context improvement through key frame object detection,which incorporates the fusion of large languagemodels for refining results.The ultimate results arise fromenhancing the generated text of the proposedmodel by improving the predicted text and isolating objects using various keyframes.These keyframes identify dense events occurring in the video sequence.

Triple-path feature transform network for ring-array photoacoustic tomography image reconstruction

Photoacoustic imaging(PAI)is a noninvasive emerging imaging method based on the photoacoustic effect,which provides necessary assistance for medical diagnosis.It has the characteristics of large imaging depth and high contrast.However,limited by the equipment cost and reconstruction time requirements,the existing PAI systems distributed with annular array transducers are difficult to take into account both the image quality and the imaging speed.In this paper,a triple-path feature transform network(TFT-Net)for ring-array photoacoustic tomography is proposed to enhance the imaging quality from limited-view and sparse measurement data.Specifically,the network combines the raw photoacoustic pressure signals and conventional linear reconstruction images as input data,and takes the photoacoustic physical model as a prior information to guide the reconstruction process.In addition,to enhance the ability of extracting signal features,the residual block and squeeze and excitation block are introduced into the TFT-Net.For further efficient reconstruction,the final output of photoacoustic signals uses‘filter-then-upsample’operation with a pixel-shuffle multiplexer and a max out module.Experiment results on simulated and in-vivo data demonstrate that the constructed TFT-Net can restore the target boundary clearly,reduce background noise,and realize fast and high-quality photoacoustic image reconstruction of limited view with sparse sampling.

Kinetic equilibrium reconstruction with internal safety factor profile constraints on EAST tokamak

Reconstruction of plasma equilibrium plays an important role in the analysis and simulation of plasma experiments. The kinetic equilibrium reconstruction with pressure and edge current constraints has been employed on EAST tokamak. However, the internal safety factor(q) profile is not accurate. This paper proposes a new way of incorporating q profile constraints into kinetic equilibrium reconstruction. The q profile is yielded from the Polarimeter Interferometer(POINT)reconstruction. Virtual probes containing information on q profile constraints are added to inputs of the kinetic equilibrium reconstruction program to obtain the final equilibrium. The new equilibrium produces a more accurate internal q profile. This improved method would help analyze EAST experiments.

Reactor field reconstruction from sparse and movable sensors using Voronoi tessellation-assisted convolutional neural networks

The aging of operational reactors leads to increased mechanical vibrations in the reactor interior.The vibration of the incore sensors near their nominal locations is a new problem for neutronic field reconstruction.Current field-reconstruction methods fail to handle spatially moving sensors.In this study,we propose a Voronoi tessellation technique in combination with convolutional neural networks to handle this challenge.Observations from movable in-core sensors were projected onto the same global field structure using Voronoi tessellation,holding the magnitude and location information of the sensors.General convolutional neural networks were used to learn maps from observations to the global field.The proposed method reconstructed multi-physics fields(including fast flux,thermal flux,and power rate)using observations from a single field(such as thermal flux).Numerical tests based on the IAEA benchmark demonstrated the potential of the proposed method in practical engineering applications,particularly within an amplitude of 5 cm around the nominal locations,which led to average relative errors below 5% and 10% in the L_(2) and L_(∞)norms,respectively.