203 results about "Life-cycle assessment" patented technology

The present invention relates to the technical field of energy saving and carbon reduction of iron and steel enterprises. Disclosed are an iron and steel product carbon footprint management method and management system based on life cycle assessment. Aiming at an iron and steel enterprise with the characteristic of a blast furnace-converter long process, the present invention establishes an iron and steel product carbon footprint calculation model, an iron and steel product carbon footprint prediction model and an iron and steel product carbon footprint optimization model at a production device level by relying on the conversion relationship and the flow relationship of a substance flow and an energy flow in an iron and steel product production process during carbon footprint management. A plurality of carbon footprint management methods such as carbon footprint calculation, analysis, prediction and optimization are realized in view of the characteristic of path diversity in the iron and steel product production process, and a carbon footprint management system is formed on this basis. The carbon footprint management method overcomes the defect whereby existing carbon footprint management methods only analyze carbon footprints from the perspective of result comparison, and realizes targeted, interlocked and systematic carbon footprint management during the life cycle of an iron and steel product.

The invention relates to the technical field of distributed resource management and optimization, in particular to a distributed resource life cycle evaluation and dynamic updating method, which comprises the following steps: data acquisition: collecting multi-modal data of distributed resources, including resource state data, use behavior data, environment data and historical maintenance data; feature extraction: carrying out feature engineering processing on the multi-modal data, and extracting key indexes such as a resource health state, a degradation rate and environmental sensitivity; building a life cycle evaluation model, building the model by using the time sequence data of the resources based on a multi-task learning framework, and predicting the health state and the residual life of the resources; and optimizing a dynamic updating strategy, and monitoring and dynamically adjusting in real time. The method provided by the invention overcomes the problems of insufficient life cycle dynamics and rigid updating strategy in a traditional method, has the characteristics of high efficiency, intelligence and accuracy, and is suitable for intelligent management and optimization of new energy equipment, industrial assets and other distributed resources.

The invention relates to the technical field of supply chain management, and discloses a product supply chain carbon footprint accounting method, which comprises the following steps: (1) data collection and arrangement: collecting time sequence activity data of each link of a supply chain, including production data, transportation data and supplier data; acquiring corresponding emission factors including emission factors with specific areas and time; (2) constructing a dynamic life cycle evaluation model: establishing the dynamic life cycle evaluation model containing time dynamics, and taking activity data and emission factors as time-dependent input parameters; by introducing dynamic life cycle evaluation, the method can capture the time change of carbon emission of each link of the supply chain, including seasonal fluctuation, policy change, market demand change and other factors, and considers the influence of geographic positions, transportation routes and regional energy structures on carbon emission in detail in combination with the GIS technology, so that the method has the advantages of high efficiency and high reliability. The supply chain carbon footprint accounting precision is significantly improved, and the result is more accurate and reliable.

The invention discloses a fatigue life simulation evaluation method for a lightweight aluminum alloy material of a new energy automobile, and relates to the technical field of material life evaluation. A microstructure image is collected, coupling features are extracted through machine learning, and heterogeneous data fusion and enhancement are completed; generating a topological optimization structure based on a GAN, introducing a VPSC model to describe anisotropy according to a stress gradient dynamic grid, and constructing a dynamic finite element model; fusing vehicle driving data, predicting a load by using LSTM, performing VMD decomposition and environment correction, and realizing space-time correlation load spectrum reconstruction; a phase field model is used in a microcosmic mode, cracks are tracked in a macroscopic mode through XFEM, damage parameters are transmitted in a bidirectional coupling mode, and multi-physics field coupling simulation is carried out; fusing simulation and test data by adopting Bayesian reasoning, calculating life probability distribution, and correcting parameters when errors exceed the limit; according to the method, the fatigue life prediction error is finally reduced, the time consumption of single simulation is reduced, full-life-cycle evaluation and visual early warning are realized, an efficient scheme is provided for lightweight design, and industrial technology upgrading is promoted.

The invention relates to an infrastructure carbon emission evaluation method and system based on dynamic and static fusion prediction. The method comprises the following steps: calculating carbon emission in a design stage and a construction stage through life cycle evaluation; obtaining carbon emission related data in the whole life cycle of the infrastructure, wherein the carbon emission related data comprises static data and dynamic data collected by a sensor; aiming at heterogeneous data of different data sources in carbon emission related data, screening data playing a key role through an attention mechanism, calculating a fusion weight of a sensor level based on reliability, information entropy and historical accuracy of a sensor, and realizing fusion of multi-source heterogeneous data through adaptive weight distribution; extracting features of the time sequence type data by utilizing Bi-GRU, and extracting features of the space correlation type data by utilizing GCN to obtain fused features; on the basis of the fused features, carbon emission in the operation and maintenance stage is predicted through a deep learning algorithm; and realizing infrastructure carbon emission evaluation by combining the carbon emission of each stage.

The invention relates to the technical field of sewage plant-oriented carbon neutralization regulation and control scheme design, in particular to a sewage plant-oriented carbon neutralization regulation and control method and a sewage plant-oriented carbon neutralization regulation and control system. The method comprises the steps of collecting water quality, energy consumption and gas emission data in real time through a multi-source sensor, inputting the data into a space-time diagram convolutional network to predict a carbon emission trend after edge computing node cleaning, and dynamically optimizing an aeration rate and a sludge reflux ratio based on a fuzzy PID controller. A whole-process carbon footprint is tracked by adopting a life cycle evaluation method, a multi-target compensation strategy is generated in combination with an improved NSGA-III algorithm, and photovoltaic, biogas and green power resources are scheduled preferentially. A digital twin platform and a block chain evidence storage module are innovatively integrated, the former calibrates model parameters in real time, and the latter generates a non-tampering carbon neutralization voucher. According to the method, the problems of one-sided data, regulation and control lag and insufficient credibility of a traditional method are solved, and minute-level sensing, prediction and offset closed-loop control of carbon emission in the sewage treatment process is realized.

The present invention relates to the technical field of carbon footprint accounting. Disclosed are a carbon footprint accounting method and system for a power grid material product based on life cycle assessment (LCA). The method comprises: on the basis of an LCA method, building a product carbon footprint model for a power grid material product; collecting power grid material product data, and on the basis of the collected data, accounting the carbon emission of the power grid material product from the raw material acquisition stage to the scrap recovery stage; during carbon footprint accounting, selecting power carbon emission factors of different grades in each stage, and accounting the power carbon emission; and on the basis of the accounted data, performing high-precision real-time carbon footprint accounting of the power grid material product in the whole life cycle. The environmental impacts of the product are assessed more accurately. Moreover, real-time accounting can reflect any change or improvement effect in time. By means of the comprehensive carbon footprint analysis, detailed carbon footprint accounting can reveal high-emission activities, provide data support for optimization of the product design and production process, and reduce the overall carbon emission.

The invention belongs to the field of forestry carbon neutralization, relates to a forest fire loss and forest restoration carbon emission accounting method, and constructs a forest fire ecological loss and forest restoration carbon emission accounting framework based on full life cycle evaluation. The framework is divided into two stages of forest operation and fire damage, input and output of each stage are tracked in details, and a life cycle list is formed; an accounting model is developed in combination with an activity emission factor and a biomass conversion coefficient, and the reliability of the model is ensured through sensitivity analysis; the framework fills the theoretical blank of forest fire full-life-cycle carbon footprint accounting, and the accounting transparency and accuracy are improved; the system assists in environment decision making, provides a tool for monitoring fire influence and evaluating recovery benefits for forestry managers, promotes low-carbon management strategy and technical innovation, optimizes a supply chain, and reduces overall carbon emission. The system has a remarkable promotion effect on green economy and sustainable development.

The invention provides a multi-dimensional adsorbent performance evaluation method, and belongs to the technical field of performance evaluation, and the method comprises the following steps: carrying out a first test on an adsorbent, recording the mass change of the adsorbent after each cycle, and evaluating the adsorption performance of the adsorbent to obtain a first test result; and carrying out a second test on the adsorbent to determine the anti-sintering capability and the cycling stability of the adsorbent so as to obtain a second test result. Microscopic form change, influence condition and crystal structure of the adsorbent before and after the test are observed, and microscopic characterization of the adsorbent is obtained. And performing multi-scale simulation on the adsorbent according to the microscopic representation, and performing life cycle evaluation on the adsorbent by using a simulation result to obtain a life cycle evaluation result. And an optimization direction is provided for comprehensive performance evaluation of the adsorbent. The invention aims to realize an efficient and low-cost carbon capture technology and promote effective utilization of solid waste resources, and provides a systematic evaluation method to promote the development of the carbon capture technology.

The invention relates to a highway and waterway infrastructure whole-process carbon emission refined evaluation method and system. The method comprises the steps that carbon emission original data in the design, construction and operation and maintenance stages of highway and waterway infrastructures are acquired; carrying out preprocessing on the carbon emission original data; constructing a carbon emission factor library for carbon emission sources of highway and waterway infrastructures; evaluating the carbon emission of each stage based on the carbon emission factor library through life cycle evaluation; based on the original carbon emission data, obtaining a carbon emission prediction result under constraints through high-dimensional feature extraction, long-term and short-term feature modeling and inter-stage data interaction; and generating optimization suggestions based on carbon emission evaluation and carbon emission prediction results. Compared with the prior art, the method has the advantages of full-process coverage, high dynamic prediction capability and the like.

The invention discloses a digital twinning and AI analysis sewage treatment control system, and relates to the technical field of sewage equipment control, and the system comprises the steps: deploying a sensor to obtain a sewage treatment acoustic signal to form an acoustic energy matrix, and synchronously obtaining the operation data of a treatment plant to construct an operation data matrix; fusing the acoustic energy matrix and the operation data matrix to form a high-dimensional data matrix; mapping the high-dimensional data matrix into a low-dimensional point cloud, constructing a point cloud adjacent matrix, recognizing topological features according to the adjacent matrix, analyzing abnormal topological features by combining persistent coherence with topological entropy, and calculating an abnormal confidence coefficient; and establishing a hierarchical agent based on the abnormal confidence coefficient, defining a reward function through life cycle evaluation, adjusting a hierarchical agent optimization strategy by adopting DDPG reinforcement learning, predicting the performance of the optimization strategy in combination with a multi-step prediction loss function, and outputting the optimization strategy. According to the invention, the control strategy of the sewage treatment equipment is continuously optimized, and the strategy implementation efficiency is improved.

The invention discloses a network security event vulnerability detection method and system, particularly relates to the field of network security event detection, and is used for solving the problems of vulnerability life cycle evaluation and dynamic risk quantification in a containerized environment. According to the method, the defect of traditional static scanning in vulnerability life cycle measurement is overcome, vulnerability risk time-sensitive evaluation is realized, and resource waste caused by misinformation of expired vulnerabilities is reduced. Analyzing a vulnerability component position by using micro-service call chain topology, calculating a position contribution weight in combination with path contribution and a downstream dependency ratio, deducing an actual attack surface influence coefficient in linkage with a vulnerability survival time probability, accurately depicting a vulnerability propagation potential and an influence range, calculating a container instance level dynamic risk score, and calculating a vulnerability level dynamic risk score; the asset list and the risk score are updated in real time after the container capacity expansion and contraction event is triggered, and it is ensured that the evaluation result is synchronous with the actual operation state.

The invention discloses a rectification process carbon emission reduction optimization method based on carbon footprint evaluation, and solves the problems that the existing carbon emission reduction optimization mainly focuses on the intelligent optimization design of a rectification tower and the optimization design of a process and is lack of carbon footprint evaluation and carbon emission reduction optimization of the whole life cycle of the rectification process. The method comprises the following steps: determining a functional unit and a system boundary of rectification process carbon footprint evaluation; analyzing the rectification process according to greenhouse gas emission, and obtaining substances and energy related to carbon footprints; based on life cycle evaluation, establishing a rectification process carbon footprint evaluation model; and calculating the carbon footprint in the rectification process according to the model, analyzing the contribution rate of the carbon footprint in the rectification process, and determining a main carbon emission source to carry out corresponding carbon emission reduction optimization. According to the method, the carbon footprint is checked from the aspect of whole life cycle evaluation of the rectification process, the carbon footprint of the rectification process is accurately evaluated, a reference is provided for subsequent carbon footprint optimization, and a carbon emission reduction optimization scheme is better proposed.

The invention discloses a crop planting structure space optimization method, which comprises the steps of S1, collecting crop planting structure space layout, meteorological data, statistical data, soil data and the like, and identifying uncertainty related to a crop planting decision; s2, establishing a multi-target interval optimization model, deducing an optimal interval solution by using an existing algorithm, establishing a carbon footprint target function by using life cycle evaluation, and establishing a water footprint target function based on a Penman-Monteith formula; s3, constructing a Dyna-CLUE model based on a quantity optimization result, analyzing a relationship between crop spatial distribution and driving environment factors by adopting logistic regression, and simulating and optimizing a crop planting structure spatial layout; the method not only quantifies and balances economic and ecological influences of a crop planting structure under multiple targets, but also provides a specific spatial position, and reveals optimization results of carbon footprints and water footprints of crops; the number optimization of crop planting structures is expanded to space optimization, and basic data and scientific support are provided for guiding actual production and agricultural sustainable management.

The invention discloses a life cycle evaluation missing data completion method, system and device and a medium, and the method comprises the steps: defining a data template, and determining a target range of life cycle evaluation in the data template; obtaining input data, and filling the data template with the input data; determining missing data in the data template; according to the method, the system, the equipment and the medium, the missing data in the data template is predicted by utilizing the large model, the predicted missing data is written into the data template, and the missing data in life cycle evaluation can be complemented based on the large model.

The invention discloses an RFID-based blowout preventer group full life cycle evaluation method, which belongs to the field of petroleum well safety monitoring, and comprises the following steps: installing an RFID tag on a blowout preventer, monitoring functional data such as pressure, flow, temperature and sulfur content parameters in a blowout preventer group cavity, and establishing a blowout preventer group simulation model; further establishing a blowout preventer group full information storage database; correcting and predicting the simulation model; carrying out full life cycle monitoring on the blowout preventer group according to the RFID tag; according to the simulation model and the prediction model, performing safety prediction on a blowout preventer group flashboard, a blowout preventer group rubber core and a blowout preventer group flange connection seal of the blowout preventer assembly; and S6, the blowout preventer assembly is maintained according to the safety prediction result, based on the RFID technology, the pressure, the temperature, the sulfur content, the flow and other environmental parameters in a blowout preventer cavity under the blowout working condition can be more truly sensed, and more reliable data are provided for safety prediction of the blowout preventer assembly.

The invention discloses an evaluation method and device for a farmland soil remediation technology. The environment data acquired from the preset farmland covers all stages divided according to the to-be-evaluated soil remediation technology, and the stages comprise the whole life cycle process from resource and energy consumption to pollutant emission. An environment influence data set constructed through the data is input into eFootprint software for modeling, and the software outputs environment influence indexes and carbon footprint values of all stages according to a life cycle evaluation model, preset input and output types, transportation information and data sources. The indexes and the numerical values are further used for calculating the proportion of the influence of each stage on the environment, and the specific influence of each stage on a specific area is evaluated according to the proportion, so that a comprehensive environment influence analysis framework is provided, and optimization and improvement of a soil remediation technology are supported.

The present invention provides a source-sink matching method based on hydrate method and saline CO2 storage, which can improve the efficiency of carbon dioxide storage and reduce environmental risks. The method comprises the following steps: optimizing the terrestrial carbon source distribution points through a mixed integer linear programming (MILP) model to minimize the transportation cost and path. Accurately determine the geological characteristics of the storage target area using three-dimensional seismic data. Comprehensively evaluate the storage capacity of saline aquifers and hydrate method through numerical models, considering three mechanisms of structural storage, dissolution storage and residual gas storage. The MILP model is applied again for cost analysis and source-sink matching. The environmental footprint is analyzed through life cycle assessment (LCA) to ensure the sustainability of the storage scheme. The method provides an efficient, economical and environmentally friendly solution for geological storage of carbon dioxide.

The invention relates to the technical field of carbon emission, in particular to an on-chain enterprise carbon emission accounting method and system. The method comprises the following steps: acquiring energy consumption, process flow and supply chain collaborative data of an enterprise in links of raw material acquisition, production processing, logistics transportation, equipment operation and recovery processing through Internet of Things equipment, and generating a carbon emission data set; based on a life cycle evaluation theory, boundaries of direct emission, indirect energy emission and supply chain associated emission are divided, and enterprise-level, product-level and supply chain-level carbon emission accounting models are constructed. A machine learning algorithm is utilized to analyze production fluctuation data in real time, carbon emission factor weights and accounting boundary parameters are dynamically adjusted, and an accounting result is optimized. And outputting a result to a green purchase decision-making system, a carbon asset management system and a supply chain collaboration platform. The system integrates industrial Internet of Things equipment, block chain nodes and enterprise resource planning system interfaces, collects and verifies full-link data in real time, solves the problem of data collection, and improves the accounting reliability.

The invention relates to the technical field of tracking management, in particular to an electric power building engineering material tracking and management system, which comprises a material identification module, a material management module, a material management module and a material management module, and is characterized in that all materials entering and exiting from a warehouse are identified and tracked in real time by using an RFID technology to ensure the traceability of material flows; the database management module is used for storing material related information; the material scheduling module is used for automatically analyzing project requirements and optimizing material distribution and scheduling strategies based on a scheduling algorithm; the environmental adaptability analysis module is used for evaluating the influence of different environmental factors on the material performance; the data analysis and prediction module is used for evaluating a material demand trend and price fluctuation by adopting a big data analysis technology; and the material compatibility and life cycle evaluation module is used for evaluating compatibility among different materials. According to the method, the high traceability of the material flow is ensured, the material distribution and scheduling strategy is optimized through the artificial intelligence algorithm, the resource waste is remarkably reduced, and the material use efficiency is improved.

A present invention embodiment provides a Life Cycle Assessment (LCA) system that addresses the limitations of existing systems. The system offers an intuitive, user-friendly interface that simplifies the complexity of LCA methodologies, making environmental impact assessment accessible to a broader audience. It incorporates advanced algorithms and real-time data integration, ensuring accurate and up-to-date assessments. Additionally, the system is designed with a modular architecture and is highly configurable, allowing seamless integration with various industries and accommodating diverse items including products, services, and processes.

The invention provides a lithium battery pollution reduction and carbon reduction collaborative optimization method, device and equipment based on LCA and a storage medium. Raw material composition, sintering temperature, energy consumption, tail gas pollutant concentration and key process parameters are collected in real time through an Internet of Things sensor network and fused with data of a life cycle evaluation database to generate standardized life cycle data so as to accurately reflect carbon emission and pollutant emission conditions. And calculating a carbon emission value and a pollution emission value in the production process based on the data to form a combined environment evaluation index, establishing an objective function according to the combined environment evaluation index, and solving by adopting a multi-objective optimization algorithm to obtain optimized process parameters meeting preset performance constraints. Optimized parameters are then transmitted to a production control system, real-time adjustment of key process parameters is achieved, production data are continuously monitored, closed-loop control is formed, collaborative optimization of pollution reduction and carbon reduction is ensured, and the problem that overall optimization is difficult to achieve in the prior art is solved.

The invention discloses a crane full life cycle evaluation method based on digital twinning, and relates to the technical field of cranes, the method comprises the following steps: determining a primary loss structural component set and a secondary loss structural component set; constructing an initial digital twin structure model; performing time sequence updating on the initial digital twinning structure model to obtain a digital twinning structure monitoring model sequence; performing multi-receptive-field space-time state interaction enhancement on the digital twin structure monitoring model sequence, and determining digital twin space-time state features of the target crane; and carrying out life evaluation based on the digital twin space-time state characteristics of the target crane, and determining a full life cycle stage and a life evaluation result of the target crane. The technical problems that in the prior art, crane operation data analysis depth is not enough, so that full life cycle evaluation is not comprehensive, and hysteresis exists are solved. The technical effects of carrying out multi-level component interaction analysis on the crane and improving the accuracy of full-life-cycle evaluation are achieved.

The present invention embodiments provide a forecasting system that derives carbon intensity, emissions, and environmental impact forecasts from a life cycle assessment (LCA). The forecasting system offers an intuitive, user-friendly interface that simplifies the complexity of forecasting methodologies, making generating forecasts of carbon intensity, emissions, and environmental impacts accessible to a broader audience. It incorporates advanced algorithms and real-time data integration, ensuring accurate and up-to-date forecasts. Additionally, the forecasting system is designed with a modular architecture and is highly configurable, allowing seamless integration with various industries and accommodating diverse products and processes.

The invention belongs to the related technical field of pressure tests, and particularly discloses a gas inlet pipeline test device for a gas generator, which comprises a first base and a second base, a round frame is fixedly mounted on one side of the upper end surface of the first base, an annular pipe is embedded in the round frame, and a connecting rod is mounted at one end in the annular pipe through an arranged telescopic mechanism. The outer side of the connecting rod is externally connected with a ring rod through an inner chuck fixedly connected in a sleeving mode, a sealing rotating ring is arranged on the outer wall of one side of the round frame, a test air inlet pipe movably penetrates through the sealing rotating ring in a penetrating mode, and a particle feeding simulation mechanism is arranged at the end, away from the sealing rotating ring, of the test air inlet pipe. By simulating multi-field coupling environments such as pressure fluctuation, particle scouring and mechanical vibration under real working conditions, the problem that data deviation is large due to the fact that complex working conditions cannot be reproduced in a traditional test is solved, and precise detection and full-life-cycle evaluation of the performance such as wear resistance, pressure resistance and blockage resistance of the pipeline are achieved.

The invention relates to a photovoltaic recovery economic and environmental benefit evaluation method based on material flow and scene analysis, and belongs to the field of environmental analysis, and the method comprises the steps: carrying out the modeling evaluation of photovoltaic scrap through employing a dynamic material flow model in combination with a Weibull probability distribution function, and obtaining the spatial and temporal distribution of the photovoltaic scrap amount of different regions; using a life cycle evaluation method to analyze life cycle environmental influences of different recovery processes in the recovery process, and obtaining environmental benefits E brought by local recovery decommissioning components; evaluating the economic benefit of photovoltaic recovery; the environmental benefit is combined with the economic benefit, and the comprehensive environmental economic benefit of photovoltaic recovery is obtained; and evaluating the comprehensive environmental and economic benefits of photovoltaic recovery under different policies based on a scenario analysis method. According to the method, more accurate space-time distribution prediction is carried out on the scrap amount of the photovoltaic module, a standardized evaluation method is provided for photovoltaic recovery of different recovery processes, consistency and transparency are ensured, and environmental and economic benefits of different technical governance can be accurately evaluated and compared.

The invention provides a carbon footprint tracing method and device suitable for a copper product, and relates to the technical field of carbon tracing. The method comprises the following steps: acquiring data of a copper product in a full life cycle, calling a preset emission factor library and an industry carbon intensity database, and calculating carbon emission of the copper product in the full life cycle by adopting a mixed life cycle evaluation method to obtain a carbon emission accounting result of each stage; based on the carbon emission accounting result of each stage, combining with a multi-region input-output model, constructing copper product supply chain carbon emission distribution throughout the country, and quantifying an inter-provincial implicit carbon flow path; using the structure decomposition analysis model to decompose the driving factors; and performing time sequence prediction and supply chain high-carbon node identification on the carbon emission accounting result and the trans-provincial carbon distribution data by using a deep learning model to obtain a carbon traceability result. The method is used in the carbon footprint tracing process of the copper product, and solves the technical problem that national scale copper product carbon flow tracking cannot be carried out in the prior art.

The invention relates to the technical field of livestock and poultry manure and crop straw resourceful treatment, and particularly provides a four-flow coupling full life cycle evaluation method for planting and breeding waste resource treatment based on a graph neural network, and the method comprises the steps: obtaining four-flow real-time working condition data representing a system state, and constructing a heterogeneous process map; constructing a topology generation network, and generating a group of candidate process topology adjacency matrixes; calculating to obtain a total topology expected value, a path robustness score and a reconstruction conversion cost corresponding to each candidate process topology adjacent matrix; and obtaining a final decision score, selecting the candidate process topology adjacency matrix with the highest final decision score as the optimal process topology, and outputting a self-adaptive execution strategy corresponding to the optimal process topology. According to the method, the limitation that only parameter optimization can be carried out in a traditional fixed technological process is broken through, and dynamic reconstruction of the whole technological topological structure is achieved.

The invention discloses a ceramic product carbon footprint accounting method and system, and relates to the technical field of carbon emission calculation. The method comprises the following steps: establishing a process flow framework of a target product based on input data and output data of each process device in a production flow and a sequence of each process device in the production flow; determining the data integrity of the input data and the output data of each process device, and dividing the process flow framework of the target product into a plurality of modules according to the data integrity; and for the plurality of modules, constructing a carbon footprint accounting model corresponding to each module by adopting a life cycle evaluation method, and carrying out carbon footprint accounting on the target product through the carbon footprint accounting model corresponding to each module. According to the scheme, accurate carbon footprint accounting can be carried out on specific types of ceramic products.

The invention belongs to the technical field of bridge engineering and rail transit, and particularly relates to a high-speed rail long-span cable-stayed bridge traffic safety analysis method and system. Comprising the following steps: establishing a physical constraint relation model between vehicle body vertical acceleration and secondary suspension vertical force resultant force; obtaining a vehicle dynamic response predicted value by using the German track irregularity spectrum, the track deformation quantity and a PI-LSTM model; obtaining a prediction interval of the vehicle dynamic response predicted value by using a cGANs model, the random noise variable, the real error value and the vehicle dynamic response predicted value; the maximum value between the peak value of the prediction interval and the vehicle dynamic response prediction value is obtained; comparing the maximum value with a standard limit value to obtain a comparison result; the comparison result is used for traffic safety evaluation. According to the method, high-precision and high-robustness full-life-cycle evaluation is provided for the traffic safety of the large-span cable-stayed bridge of the high-speed rail.