17 results about "Life-cycle assessment" patented technology

The application provides a comprehensive decision-making and evaluation method for halogenated hydrocarbon contaminated soil and groundwater remediation strategy, comprising: establishing a site baseline and conducting technical preliminary screening based on health and ecological risk assessment (HERA) and a three-level evidence system; conducting rapid resource efficiency assessment based on environmental footprint analysis (EFA); conducting global long-term assessment based on life cycle assessment (LCA) and cost-benefit analysis (CBA); and dynamic evaluation and closed-loop control based on digital twinning and multi-criteria decision analysis (MCDA) coupling. In the dynamic evaluation stage, an adaptive hybrid dynamic weighting mechanism is constructed, the subjective benchmark weight and the objective fluctuation weight calculated based on real-time data information entropy are integrated, and the comprehensive utility score is calculated; at the same time, the apparent degradation rate constant of the pollutant is solved in real time, and when it is lower than the target rate and the strategy is replaced, the intervention instruction is automatically output. The application realizes the deep integration of multi-dimensional indicators, dynamic adaptive evaluation and closed-loop intelligent regulation and control, and solves the problems of single, static and lack of feedback of the existing evaluation method.

This invention relates to the field of carbon footprint assessment technology, and discloses a method and system for allocating the carbon footprint of co-products based on life cycle assessment. The method includes: determining the chemical reaction equation based on the chemical reaction process of the process to be assessed; identifying all reactants and all co-products, and the corresponding balancing coefficient for each; calculating the sum of the balancing coefficients of all co-products as the total molarity baseline; calculating the carbon footprint allocation ratio for each co-product based on the ratio of the balancing coefficient of each co-product to the total molarity baseline; obtaining the total carbon footprint of the chemical reaction unit process; and allocating the total carbon footprint to each co-product according to the carbon footprint allocation ratio. This invention solves the technical problems of distorted results from existing mass allocation methods and the narrow applicability and computational complexity of energy allocation methods, achieving a scientific, accurate, and universally applicable allocation of carbon footprints.

One embodiment of the present invention sets forth a technique for processing a query of a life cycle assessment (LCA) database. The technique includes searching one or more hierarchical structures included in the LCA database for data nodes that match a set of parameters that is (i) included in the query and (ii) specifies one or more properties of an entity. The technique also includes upon determining that a data node includes an unknown consumption or an unknown emission, matching a second set of parameters associated with the data node to an entry in a cache and computing one or more environmental impacts based on a functional unit that is (i) included in the entry and (ii) includes a quantity associated with the unknown consumption or the unknown emission. The technique further includes causing the one or more environmental impacts to be outputted in a response to the query.

This invention provides a green building life cycle assessment method and system based on pile foundation data. It acquires material and energy consumption data during the construction phase, including pile foundation data, and calculates the building's inherent environmental load by combining this data with an environmental impact factor database. During the service life, it collects pile foundation structural response monitoring data and uses a structure-foundation correlation model to invert and obtain the equivalent load time series of the superstructure reflecting the building's actual usage state. The equivalent load time series is input into a pile foundation performance degradation model to generate a maintenance plan and calculate the maintenance environmental load. Simultaneously, it identifies the building's actual usage mode and calibrates the building energy consumption model to calculate the operational environmental load. Based on the predicted state of the pile foundation performance degradation model at the end of the planned lifespan, it assesses the remaining bearing capacity of the pile foundation, formulates demolition, renovation, or reuse disposal strategies, and calculates the disposal environmental load. Finally, it summarizes the inherent, maintenance, operational, and disposal environmental loads to obtain the building's full life cycle environmental load assessment results.

1. Name of the product in this design: Graphical User Interface for AI-based Interpretation of Carbon Footprint and Establishment of Databases and Models for Electronic Devices. 2. Application of this design: This design is intended for use in an electronic device. 3. The key design feature of this product is its graphical user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Uses of the graphical user interface: for AI to interpret carbon footprint / life cycle assessment images and data, and to build a database. 6. Human-computer interaction method of graphical user interface: The main view is the main interface of the database, used to display existing database information; after clicking "Create Product Data", the interface changes to state 1, used to select product category and upload screenshot; after clicking "Select Category", the interface changes to state 2, used to select product category; click the box in front of the product category to select, as shown in state 3; after selecting the product category, click "Confirm" and "Paste Image" to enter state 4; then click "Image Interpretation" to enter state 5; after the AI ​​analysis is completed, the interface changes to state 6; move the cursor down on the right to enter state 7, used to display the AI ​​score. The analysis results include data input / output tables, cut-off tables, supplementary information, and pending tables. Clicking "Upload Data" leads to interface state change diagram 8; clicking "Start Interpretation" leads to interface state change diagram 9; moving the right cursor down leads to interface state change diagram 10; clicking the second green icon after the product name leads to interface state change diagram 11, used to save the product name and parameters to the saved data list information column; clicking "Substitute to Option Column" leads to interface state change diagram 12, used to fill in the list data; clicking "Confirm" leads to interface state change diagram 13, used to match other lists; after matching, clicking the "Match Icon after Product Name" leads to interface state change diagram 14.

The application relates to the technical field of mobile phones, in particular to a mobile phone middle frame film pasting risk assessment method based on process data, which comprises process analysis and electromagnetic characteristic identification based on monitoring data; self-recurrence model is adopted to predict interference intensity trend; a relief scheme is formulated through optimization theory; lattice Boltzmann model is used to evaluate signal compatibility; a signal enhancement process is designed in combination with system dynamics; a comprehensive process risk assessment is generated by adopting genetic algorithm and particle swarm optimization for multi-objective trade-off; and finally, production planning is completed through life cycle assessment. The application can realize accurate analysis of material composition and thickness, scientifically predict high-risk interference frequency bands, effectively reduce the shielding effect of film pasting on radio frequency signals while guaranteeing production efficiency and cost, and improve the communication quality of the whole machine.

This application relates to a method, apparatus, electronic device, and medium for optimizing a power battery recycling network. It is applied in the field of power battery recycling technology. The method includes: predicting the mass of retired power batteries in the current and future periods based on the technical characteristics related to electric vehicles within each target area; calculating the recycling cost per unit mass of retired power batteries in each target area in the current period based on battery recycling-related parameters, and determining the recycling cost for future periods by combining the cumulative mass of retired power batteries in the current and future periods; calculating the recycling emissions of each target area in the current and future periods based on life cycle assessment; constructing decision variables, constraints, and an objective function for multi-objective optimization based on the mass, recycling cost, and recycling emissions of retired power batteries corresponding to a single period; solving the objective function based on the constraints to obtain the values ​​of the decision variables corresponding to that period. This method can improve the accuracy and applicability of the optimization results.

The embodiment discloses a building carbon emission digital calculation method based on an IFC data standard, is based on BIM modeling software, is based on life cycle assessment theory, constructs a BIM model of the whole life cycle of building carbon emission, divides the life cycle of the whole building unit into four main stages: building design and transportation stage, building construction stage, operation and maintenance stage and demolition disposal stage, and obtains the carbon emission of each stage based on the carbon emission calculation model of each stage, and then realizes the comprehensive evaluation of building carbon emission in the building project management process, realizes the carbon emission accurate quantification, visual analysis and intelligent decision-making of the whole process from building transportation, construction, operation to demolition.

This application relates to the technical field of intelligent construction monitoring, and more particularly to an intelligent construction monitoring system and method for retaining walls based on distributed sensing. The system includes: a sensor network module configured with two switchable operating modes: construction monitoring and operation and maintenance monitoring; a data processing and mode switching module, used to generate mode switching signals based on external construction progress information or instructions, controlling the sensor network module to switch between the two modes; and a central control unit, used to provide information, respond to instructions, and process data to generate monitoring results. In construction mode, the sensor network module operates according to a first strategy; in operation and maintenance mode, it operates according to a second strategy. This application achieves seamless switching from construction to operation and maintenance through a single system, solving the problems of repeated equipment investment, broken data links, and difficulties in full life cycle assessment, and represents a technological advancement in simplified architecture, cost reduction, and data integration.

This invention discloses a carbon footprint management method and system for steel products based on life cycle assessment, relating to the field of energy conservation and carbon reduction technology in steel enterprises. Targeting steel enterprises characterized by a long blast furnace-converter process, this invention relies on the transformation and flow relationships of material and energy flows during steel product production to establish a carbon footprint calculation, prediction, and optimization model at the production equipment level. Considering the diverse paths in the steel product production process, it implements various carbon footprint management methods, including calculation, analysis, prediction, and optimization, and forms a carbon footprint management system based on these methods. This overcomes the shortcomings of existing carbon footprint management methods that only analyze carbon footprints through result comparison, achieving targeted, interconnected, and systematic life cycle carbon footprint management for steel products.

The application discloses a naringin high-efficiency extraction process optimization and multi-dimensional biological activity research method based on a low eutectic solvent. Through systematic screening of 11 kinds of low eutectic solvents (Deep Eutectic Solvents, DESs) and 2 kinds of traditional organic solvents on the extraction efficiency of naringin, it is determined that the low eutectic solvent composed of tetraethyl ammonium bromide and 1,2-propanediol is the optimal solvent, the extraction process parameters are optimized through single factor experiment and response surface method, and the optimal extraction conditions of naringin are obtained. The extracted naringin is subjected to antioxidant and antibacterial activity detection, the MoGAPI method is used for life cycle assessment of the extraction process, and through network pharmacology and molecular docking technology, the potential action target, signal pathway and molecular binding mechanism of naringin in treating gastric cancer are explored. The method is high in extraction efficiency, green in environmental protection and safe in operation, and further systematically clarifies the multi-dimensional biological activity and potential pharmacological action of naringin, thereby providing reliable process and theoretical support for the green industrialized production and subsequent development and application of naringin.

This invention discloses a method for quantifying the carbon footprint of bamboo and wood products based on life cycle assessment, belonging to the field of green and low-carbon technology. For bamboo and wood products, the method scientifically divides the key life cycle stages, including raw material collection, transportation, processing, use, disposal, and recycling. It combines on-site IoT sensors with enterprise and industry databases to achieve real-time collection and multi-level weighting of energy consumption and emissions data. The method compiles greenhouse gas emission inventories for each stage, uses the mass balance algorithm and carbon emission factor method for quantification, and sets up dedicated modules for carbon storage and delayed carbon emissions. A machine learning model is introduced to dynamically evaluate the carbon release process during disposal and recycling. After integrating the entire process, uncertainty analysis is conducted using Monte Carlo simulation to obtain highly reliable full life cycle carbon footprint accounting results.

Provided is an operating method of a server that performs a life-cycle assessment on a battery. The operating method of the server includes, in a battery pack manufacturing operation, receiving identification information of a battery pack from a battery pack manufacturer, in an operation of mounting the battery pack on a device, receiving device identification information about the device on which the battery pack is mounted and the identification information of a battery pack, from a device manufacturer, mapping the identification information of a battery pack to the device identification information, in the operating operation of the device, receiving user identification information about a user of the device and the device identification information, from a user, and mapping the user identification information to the device identification information, receiving battery data information generated during driving of the device and device data information from the device and analyzing the received information, generating evaluation information for the battery pack according to an analysis result and storing the generated information in the database. The evaluation information for the battery pack includes remaining life and whether to recycle of each of battery cells included in the battery pack.

The present application relates to the technical field of life cycle assessment, and discloses a method for improving the accuracy of full life cycle assessment real scene data filling, comprising: obtaining a benchmark real scene data set and a to-be-verified real scene data set; performing consistency deviation verification on product data of the to-be-verified real scene data set based on the benchmark real scene data set, and outputting a first layer verification result; sequentially performing consistency deviation verification on multiple input data of the to-be-verified real scene data set based on the benchmark real scene data set after verification, and outputting a second layer verification result; updating the currently approved to-be-verified real scene data set to a benchmark data set of the next period after verification, and iteratively completing the calibration of full-period real scene data. The method solves the problem of large real scene data filling deviation and many statistical errors leading to distorted LCA calculation results, improves the accuracy of full life cycle assessment real scene data filling, and guarantees the efficiency and reliability of carbon emission accounting.

This application relates to a method, system, and medium for intelligent management of the entire lifecycle of laboratory equipment, belonging to the field of lifecycle management technology. The intelligent lifecycle management method includes: digitally converting basic equipment information and binding it with equipment identification codes to construct a dynamic digital equipment file; collecting and monitoring equipment operation data according to equipment type, and determining the operating status of each component in the experimental equipment by combining the equipment status perception mechanism, predicting and identifying potential equipment failures; generating equipment operation and maintenance plans based on equipment operation data and preset maintenance cycles, and linking them to the dynamic digital equipment file to form an equipment maintenance trajectory; monitoring and analyzing equipment operation data and component operating status according to a lifecycle assessment model, and assessing the equipment health index by combining the equipment maintenance trajectory; and avoiding premature scrapping or overuse of experimental equipment through data-driven assessment, reducing equipment waste costs and lowering safety hazards.

This application relates to the field of collaborative analysis technology of Building Information Modeling (BIM) and Life Cycle Assessment (LCA), specifically disclosing a multi-level BIM-LCA collaborative review system for modular pipeline units. The system includes a BIM parsing unit, a life cycle carbon emission assessment unit, a topology optimization calculation unit, a logistics constraint coupling unit, and a dynamic boundary adjustment unit. By extracting BIM model parameters and combining full life cycle carbon emission accounting, structural topology optimization, and logistics constraint modeling, it dynamically and iteratively adjusts the module segmentation boundaries to achieve a synergistic balance between structural rationality, transportation feasibility, and low-carbon goals. Through the above technical solution, this application can avoid module over-limit rework, accurately balance the technical issues of prefabrication carbon reduction and transportation carbon increase, and support multi-level module management and visual decision-making, thereby improving the intelligence and green construction level of modular pipeline system design.