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Specifications for TianGong Database Construction

This document details the specific requirements for collection tools and principles in the process of TianGong data construction.

Basic Conditions

Table Structure

  • The table is divided by industry or theme. Each industry and theme has three tables: "Basic Information", "Input-Output", and "Data Source".

The "Data Source" table stores the source of the process data, including the source of the process data.

The "Process Basic Information" table stores the basic information of the process.

The "Input-Output" table stores the input flow and output flow information of the unit process.

  • The code table contains standard data that can be referenced during the data entry process, including Flow, Location, and Unit.

The "Code Table - Flow" stores standard Flow information, mainly for reference when entering Flow information in the Input-Output table.

The "Code Table - Location" stores standard spatial attribute information, mainly for reference when entering Location information in the Basic Information table.

The "Code Table - Unit" stores standard unit information, mainly supporting the unit information in the Code Table - Flow.

The "Code Table - Participant" stores information about the individuals participating in data recording.

Data Logic

Language Requirements

To facilitate the establishment of a bilingual database, all content involves both Chinese and English fields. The contents of the fields with 'EN' in the table field names should be filled in English.

Data Entry Phase 1: Fill in according to the language of the data source, that is, if it comes from Chinese literature, fill in Chinese, if it comes from English literature, fill in English, to maintain consistency with the description related to the data source to the greatest extent.

After finalizing the data: Carry out professional translation from Chinese to English or English to Chinese to fill in the missing language fields. Note: The use of language should be consistent and professional.

To avoid duplicate work, during the data entry phase, only the original text is respected and excerpts are made from the original text. No translation work is done. After the content of the data table and the data verification are correct, the finalized data table is translated.

Things to Note

When multiple people are processing a table at the same time, clicking '+' may result in no new blank records being created. Please refresh the page, and then the blank records with continuous IDs that have been created will appear.

Table Filling Instructions

Data Source Table

Table Description

 The table stores information about the data sources of unit processes and input-output flows. Each industry's table is independent, and the data structure of all industry tables is consistent.

  This data table is a code table for the data source field in the Basic Process Information Table, i.e., the data source in the Basic Information Table needs to be selected and inserted from this table.

  When a data source appears for the first time, a record needs to be entered in this table first, and then selected in the Basic Process Information Table.

  It is named "Data Source-xx", where xx represents the subject name, such as building materials, aluminum, etc.

Instructions for Filling Fields

ID

This refers to the unique index field of the table, which has no actual meaning. The ID of the newly created record is automatically incremented by 1 from the last existing record ID.

Literature/Report Information

This field is used to record literature information. The literature information is exported based on Zotero, in the Nature style.

  1. Import the literature into the corresponding folder in Zotero.

  2. Right-click on the literature and select "Create Bibliography from Selected Item".

  3. In the pop-up window, select the Nature style, output the bibliography, and copy to the clipboard.

  4. Paste into the Literature Information field in the table.

For instructions on how to use Zotero操作

The main contact person for each team has been set as the person in charge of the Zotero group, who can manage the team members.

DOI

If available, you need to enter the literature DOI (Digital Object Identifier) or URL (Uniform Resource Locator), including the DOI web address. For example: https://doi.org/10.16521/j.cnki.issn.1001-9642.2008.07.016

Publication Date

Record the publication date of the document. If it is not precise, enter the first day of that time period. For example, if you only know it is December 2022, then select 2022-12-01. This field cannot be left blank.

Data source types

It refers to the type of literature/report, single-choice. Options include literature, national or regional statistical yearbooks, industry statistical reports, national or industry standards, environmental impact assessment reports, patents. If the type you encountered is not covered by the above options, please select "Other" and provide additional explanation in the remarks section.

Creator

Record the creator of this entry. It will be automatically filled in based on the user's name, and no manual operation is required.

Creation time

Record the creation time of this entry. It will be automatically filled in based on the creation time and no manual operation is required.

Basic Information Form for Process Operations

Table description

Store basic information about process operations (Process). Each industry has an independent table, and the data structure remains consistent across all industry tables. The table is named "Process Basic Information-XX," where XX represents the theme name, such as construction materials, aluminum, etc.

Field Entry Instructions

ID

Unique Index Field in the Table: This field is a unique identifier and holds no actual significance. When creating a new record, the ID for the new record is automatically generated by incrementing the last recorded ID by 1.

Process Name

The name of the process, which refers to a general descriptive name for the unit process and/or its major products, services, or technologies. This field cannot be left blank.

Naming Convention:

The process name should follow the following format:

Processing/Production Object + Process Objective (required) | Product (required) Characteristics | Technological Process (required) | Raw Material

Examples:

Cement Production | Ordinary Portland Cement 42.5MPa | New Dry Process 2000t/d | Fly Ash

Cement Production | General Portland Cement | Large-scale New Dry Process >4000 t-cl/d

Municipal Sludge Dewatering | Dewatered Sludge with 80% Moisture Content | Pressure Filtration Dewatering

For the product, select the flow name from the input and output streams of the corresponding process that has a reference quantitative selection as TRUE.

If you encounter a special case that is not covered by the above situations, please contact the research team for confirmation.

Description/ Remarks

In this field, you can provide general information about the dataset and give a brief introduction to the basic details of the process. It is recommended to include summary information from the data source that provides an overview of the process. This field should not be left empty.

You can also record basic information from literature sources, including more detailed process steps (which cannot be extracted as separate processes).

Additionally, you can include technical descriptions from the data source that explain the process, highlighting technical characteristics and operating conditions, especially when the process name reflects technological attributes.

Furthermore, you may include general (unaudited) quality statements and information about the sources used.

Note: Please check the content in fields such as "Technical Description," "Completeness Description," "Data Selection Description," "Inventory Calculation Description," "Data Processing Method Description," "Sampling Description," and "Modeling Process Description" to avoid duplicate entries.

Flowchart

A flowchart or photograph representing the items, services, technologies, factories, etc., represented by this dataset can be used to illustrate the boundaries and internal processes of the process. In order to provide a clear illustration and documentation of the dataset, you may include saved figures from literature or create your own process diagram document. This field can be left blank if not applicable.

The data collection form is used in conjunction with an online shared folder. The folder is created and access permissions are set during the initialization of topic categorization.

Process Categorization

Record the type of this Process dataset, including whether to include/exclude upstream or downstream processes, transparency and internal (hidden) multifunctionality, and modeling completeness, including:

  • Unit Process (Single Operation): A unit process refers to a specific process step that includes basic flows, product flows, and/or waste flows. It represents a single operation within the overall process.

  • Unit Process (Black Box): A unit process, also known as a black box, represents a combination of several process steps. It includes basic flows, product flows, and/or waste flows. The internal details of the individual process steps are not explicitly shown or considered.

  • LCI Results (Life Cycle Inventory, Cradle to Gate): LCI, or Life Cycle Inventory, represents data for the complete life cycle of a product, from the extraction of natural resources to the gate of the manufacturing facility. The life cycle is also referred to as a system process, where inputs and outputs are elementary flows.

  • Carbon Emission Factor (Unit Process): This category includes unit process data that exclusively focuses on carbon emission factors. It consists of data related to carbon emission factors only, specifically within the context of unit processes.

  • Carbon Emission Factor (LCI Result): This category includes life cycle inventory (LCI) data that exclusively focuses on carbon emission factors. It represents LCI data for the entire life cycle of a product, from cradle to gate, where the data primarily consists of carbon emission factors.

Note: If you encounter any special questions that are not covered by the above information, please contact the research team for confirmation.

Geographical Location ID

Geographical Location ID: Please record the spatial location ID of this process, which is generally the administrative region ID of its data development or sampling location. The ID should be referenced from the code table for geographical locations and should be in UUID format.

When entering the information, click on the dropdown menu to open the code table for geographical locations. You can use filtering and searching to find the corresponding record, and then click on it to confirm.

This field cannot be left empty, and only one record can be selected.

Code table - Geographical Locations supports spatial resolution down to the city level. Please select the finest spatial location based on the following guidelines:

If the data explicitly originates from a specific city, select that city.

If the data is sourced from a known province but the city is unknown, select the province.

If the province of data origin is unknown, select China.

Geographical Location & Geographical Location Abbreviation

Please record the spatial location of this process, which is generally the administrative region where the data development or sampling location is located. Please reference the name from the code table for geographical locations.

    This field does not need to be manually entered. It will automatically be populated with the selected data when choosing the Geographical Location ID.

Geographical Location Description

Additional Explanation Regarding Location: For example, this can include descriptions and addresses of companies and/or facilities, clarification on whether certain sub-regions within the "location" are not applicable to the dataset, information on whether the data is only applicable to specific regions within the indicated location, or if certain elementary flows or intermediate product flows are derived from another geographical area. This field can be left blank if there is no additional information to provide.

Effective Start Date

The starting year of the time period during which the dataset is valid, typically based on the data development, calculation, sampling time reflected in the data source, or the publication date of the literature. For datasets that combine data from different years, experts or data entry personnel should determine and enter the year that is most representative of the overall environmental impact. This field cannot be left blank.

Effective End Date

The ending year of the time period during which the dataset remains valid or sufficiently representative. This date also determines when dataset revision or reshaping is required or recommended due to anticipated changes in the environmental or technological background within the system. It is typically determined based on the timeframe specified in the data source or can be determined through expert judgment or professional assessment if not explicitly mentioned in the data source. If the information is not available, this field can be left blank.

Effective Date Explanation

Further explanation and clarification regarding the setting of the effective date time period, including whether it was determined by expert judgment and based on what information the effective date was established. It can also include any information that is not covered within the mentioned time period (e.g., literature reports data sourced from summer, therefore May 1st is chosen as the starting date). This field can be left blank if there is no additional information to provide.

Technical Description

Description of Technical Characteristics, including Operational Conditions of the Process or Product System. For the latter, this includes the relevant upstream and downstream processes contained within the dataset. Professional terminology should be used.

Data Selection Explanation

Explanation of the sources and criteria used for selecting detailed data, such as quantities of input and output flows, calculation parameters, etc. This can be understood as the rationale behind choosing a particular source for the database, considering that multiple life cycle assessment (LCA) studies may exist for the same process.

Explanation of Data Processing Methods

This section provides an explanation of the methods used for processing the data. It includes the techniques, sources, and assumptions employed during data adjustments, including data derivation or fitting based on data reported from another time period, geographical region, or technology. This may involve data simulation, fitting, extrapolation of trends, and related assumptions.

Specifically, it can be understood as the processing methods applied by the data reporters (selected data sources or literature) such as parameter fitting of data reported in ten technical research articles. It also includes any simple operations (addition, subtraction, multiplication, division) performed by the data entry personnel on the data.

Please note that the translation provided is a general interpretation of the content. The actual technical terminology and specific details may vary based on the context and requirements of the dataset.

The following image provides an example of data selection and data processing explanations (from the ELCD database).

Explanation of the Modeling Process

This section provides an explanation of the modeling process. It includes the mathematical relationships or fitting descriptions involved in the data used during the process. For example, if the process involves calculations with multiple parameter parameters based on certain data, it should be documented. This includes information such as the parameters, equations, mathematical relationships, constraints, as well as the advantages and disadvantages of the model.

Sampling Explanation

This section provides an explanation of the sampling process. It includes recording field information if field data testing is involved, such as factory details and sample size. The sampling procedures used to quantify input and output quantities should be described. Any potential issues that may arise when combining different sampling procedures should also be mentioned.

Please note that the translation provided is a general interpretation of the content. The specific terminology and details may vary based on the context and requirements of the study or project.

LCI principle

LCI method principle followed in the product system modelling, i.e. regarding using average data (= attributional = non-marginal) or modelling effects in a change-oriented way (= consequential = marginal).

LCI method

Brief Explanation of Specific Methods Used in LCI Modeling, such as Allocation and Substitution:

This section provides a concise explanation of the specific methods used in Life Cycle Inventory (LCI) modeling, such as allocation and substitution. It also includes the methods applied within the included background systems in the case of LCI results and partially terminated system datasets.

In LCI modeling, allocation is a method used to distribute environmental burdens or benefits among co-products or shared processes based on specific allocation rules or criteria. It ensures that the impacts associated with multiple products or processes are appropriately allocated according to their contributions.

Substitution, on the other hand, involves replacing one material, energy source, or process with an alternative that serves the same function. This method allows for the assessment of different scenarios or options by considering the environmental implications of using alternative inputs or processes.

When dealing with LCI results and partially terminated system datasets, it is important to consider the methods applied within the background systems included in the analysis. These methods can involve using existing life cycle inventory databases, statistical data, or other sources to estimate missing or incomplete data, ensuring a more comprehensive assessment.

Explanation of LCI Principles and Methods

This section provides an explanation of the principles and methods used in Life Cycle Inventory (LCI) calculations. It includes a description of the underlying principles, references used for selecting the processing methods, and specific methods employed.

LCI calculations involve quantifying the inputs, outputs, and environmental impacts associated with a product or process throughout its life cycle. The principles behind LCI methods typically include the systematic assessment of raw material extraction, manufacturing, transportation, use, and end-of-life stages.

When dealing with LCI results and incomplete system datasets, it is important to consider the methods used within the background systems included in the analysis. These methods may involve using established life cycle inventory databases, statistical data, or other sources to estimate missing or incomplete data, ensuring a more comprehensive evaluation.

The selection of processing methods in LCI calculations should be based on reliable references or guidelines. These references provide guidance on choosing appropriate methods for data collection, allocation, data quality assessment, and other relevant aspects.

Overall, the principles and methods in LCI aim to provide a systematic and comprehensive assessment of the environmental impacts associated with a product or process throughout its life cycle.

Example: The allocation is made in accordance with the provisions of EN 15804. Incoming energy and water and waste production in-house is allocated equally among all products through mass allocation. Effects of primary production of recycled materials is allocated to the main product in which the material was used. The recycling process and transportation of the material is allocated to the analysis in this EPD. For bitumen production, crude oil extraction and transport are allocated by mass, while the final products from oil refineries are allocated by economic factors.

Explanation of Function Unit

Detailed Explanation of Function Unit Used in LCI Calculation Process:

The function unit is a term used in Life Cycle Inventory (LCI) calculations to define the specific unit of measurement or reference for comparing the environmental performance of different products or systems. It provides a quantitative measure of the function or service that a product or system delivers.

The function unit is an essential component of LCI calculations as it establishes a common basis for evaluating and comparing the environmental impacts of different alternatives. By defining a consistent function unit, LCI practitioners can assess the environmental performance of various products or systems in a meaningful and standardized manner.

When determining the function unit, it is crucial to accurately capture the essential characteristics and performance requirements of the product or system under study. For example, in the case of a light bulb, the function unit could be defined as "one hour of illumination" or "providing a specific amount of light output."

The selection and specification of the function unit should be clearly documented in LCI studies to ensure transparency and reproducibility. It allows for accurate comparisons and facilitates decision-making processes related to product development, resource allocation, and environmental management.

Explanation of Input-Output Flow Completeness

This section provides an explanation of the completeness of input-output flows in data collection. It includes a description of the completeness of product, input, and output data, specifically regarding the integrity of product flows, waste flows, and elementary flows. This explanation also encompasses the cut-off criteria for data collection and the systematic exclusion of infrastructure, services, or auxiliary facilities.

In the process of data collection for life cycle assessment (LCA) or life cycle inventory (LCI), it is important to ensure the completeness of the input-output flows. This involves gathering comprehensive data on the inputs (e.g., raw materials, energy, water) and outputs (e.g., products, emissions, waste) associated with a specific product or system.

To determine the completeness of the flows, cut-off criteria are established. These criteria define what is included and what is excluded from the analysis based on certain thresholds or standards. For example, certain infrastructure elements, services, or auxiliary facilities may be systematically excluded if they do not significantly contribute to the overall environmental impact or if their inclusion would lead to excessive complexity or data collection burden.

Additionally, the completeness of flows involves considering the integrity of product flows, waste flows, and elementary flows. Product flows refer to the materials and energy inputs and outputs directly associated with the product being assessed. Waste flows encompass the emissions and waste generated throughout the product's life cycle. Elementary flows represent the individual substances or pollutants emitted or released during the life cycle stages.

By ensuring the completeness of input-output flows, LCA practitioners can obtain a more accurate and reliable assessment of the environmental impacts associated with a product or system, enabling informed decision-making and potential areas for improvement.

 Example: All major raw materials and all the essential energy is included. The production processes for raw materials and energy flows with very small amounts (less than 1%) are not included. These cut-off criteria do not apply for hazardous materials and substances.

Data Source ID:

This field records the ID of the data source for the process. It refers to the ID in the reference data source table.

When entering the data, click on the dropdown menu to open the data source table window. You can filter and search within the table to find the corresponding record. Clicking on "Confirm" will select the record.

This field must not be left blank, but only one record can be selected.

If it is a new data source that has not been previously included, you need to first enter a new record in the data source table.

This field is of utmost importance, and it is essential to ensure that the entered data can be fully traced back to the literature source.

Data Source Information:

This field records the data source for the process. Typically, it includes the name of the data source and the literature/report information from the reference data source table.

There is no need to enter data in this field directly. The selected data source ID will automatically populate the chosen data source information.

Copyright Protection

Specify whether the data can be made publicly available or is authorized for use. If there are no restrictions, select "No." If there are restrictions, select "Yes." This field must not be left blank.

If the data is from publicly accessible literature, it is assumed to be "No" by default.

Creator

This field records the creator of the record and is automatically filled based on the user's name. No manual operation is required.

Modifier

This field records the last modifier of the record and is automatically filled based on the user's name. No manual operation is required.

Creation Time

This field records the creation time of the record and is automatically filled based on the creation time. No manual operation is required.

Last Update Time

This field records the last modification time of the record and is automatically filled based on the modification time. No manual operation is required.

Input/Output table

Table Description

The table stores information about the input-output flows in a unit process. This data table is a subtable of the basic information table, meaning that one record in the basic information table corresponds to multiple records (multiple input-output flows) in this data table. All input-output flow data for various unit processes are displayed in the same table.

The table is named "Input-Output-XX," where XX represents the theme or topic name, such as "Construction Materials" or "Aluminum."

Please note that the supplementary material in literature may contain additional information beyond what is included in the main text. When conducting research or referencing a study, it is important to consider any supplementary material provided alongside the published article. This supplementary material can provide valuable data, figures, tables, methodologies, or other relevant details that are not presented in the main text. It is recommended to review both the main text and any accompanying supplementary material to ensure a comprehensive understanding of the research findings.

Field Filling Instructions

ID

This field serves as the unique index field for the table and does not have any practical meaning. When creating a new record, the ID is automatically assigned as the last recorded ID plus 1. It is used to uniquely identify each record in the table.

Field Filling Instructions:

Process ID:

This field records the ID of the unit process and references the ID in the unit process basic information table.

When entering the data, click on the dropdown menu to open the unit process basic information table window. You can filter and search within the table to find the corresponding record. Clicking on "Confirm" will select the record.

This field must not be left blank, and only one record can be selected.

Process Name:

This field records the name of the unit process and automatically populates the selected data from the unit process basic information table when selecting the Process ID. There is no need to enter data directly in this field.

Input/Output:

Mark this record as an input flow (Input) or an output flow (Output) by selecting from the dropdown menu. This field must not be left blank.

Reference Quantity:

Mark this flow as a unit process reference flow by selecting True or False from the dropdown menu. Only one flow in each unit process should be marked as the reference flow, typically representing the main product or output. This field must not be left blank.

Selecting True for the reference quantity does not necessarily mean that the flow quantity should be 1. It signifies that the flow can be used to normalize the entire unit process.

You can set the reference quantity based on the purpose of the unit process. For example, if the unit process is aluminum production, you can designate the output flow of aluminum as the reference quantity. This allows you to normalize the entire unit process based on the production of aluminum. The selection of the reference quantity should align with the specific goals and objectives of the unit process.

Flow ID:

Based on the material/product of the input/output, select the corresponding ID. If there is no detailed description in the literature, list it in the description first. Then, through expert judgment or other methods, match it with the closest available flow. If a new flow needs to be created, please contact Chang Huimin.

When entering the data, click on the dropdown menu to open the Code Table-Flow table window. You can filter and search within the table to find the corresponding record. Clicking on "Confirm" will select the record.

This field must not be left blank, and only one record can be selected.

Our complete Flow code table contains over 40,000 entries. Due to the limitations of multidimensional tables, the current Code Table-Flow table only includes approximately 2,500 elementary flows that require a complete match according to ILCD (International Reference Life Cycle Data System). While this coverage is likely to encompass common flows, it is not comprehensive.

If you are unable to find the desired flow, please refer to theFlow匹配方法Flow matching methods to search for it in the complete Flow table.

Flow Name:

This field records the name of the flow and automatically populates the selected data from the Code Table-Flow's flow name when selecting the Flow ID. There is no need to enter data directly into this field. The populated data will be in English.

Flow Category:

This field records the category of the flow and automatically populates the selected data from the Code Table-Flow's flow category when selecting the Flow ID. There is no need to enter data directly into this field. The populated data will be in English.

Quantity:

Record the quantity of the input/output flow. Only numerical values can be entered, and this field must not be left blank.

If the literature provides a range for the quantity of the input/output flow, follow the guidelines below:

  1. Determine if the range includes distribution information, such as a normal distribution.

  2. If distribution information is available, use the following principles to fill in the quantity (and complete the corresponding uncertainty-related fields):

    1. Lognormal distribution: Enter the geometric mean.

    2. Normal distribution: Enter the arithmetic mean.

    3. Uniform distribution: Enter the mean value (may require manual calculation).

    4. Triangular distribution: Enter the mode.

  3. If no distribution information is provided, assume a uniform distribution. Calculate the mean value and enter the maximum and minimum values in the uncertainty-related fields. Select "Uniform Distribution" as the type of uncertainty.

  4. Provide sufficient documentation in the description field. For example: "The literature provides a data range (X-Y). The average value is entered here, and the maximum and minimum values are recorded as uncertainties. Since the literature does not specify the data distribution, a uniform distribution is assumed by default."

Unit ID:

Record the ID of the unit for the flow data. This field references the ID from the Code Table-Unit.

When entering the data, click on the dropdown menu to open the Code Table-Unit window. You can filter and search within the table to find the corresponding record. Clicking on "Confirm" will select the record.

This field must not be left blank, and only one record can be selected.

Unit Name:

This field records the unit of the flow and automatically populates the selected data from the Code Table-Unit's unit name when selecting the Unit ID. There is no need to enter data directly into this field.

Unit Characteristic

This field records the characteristic of the selected unit for the flow (e.g., mass, volume). It serves as a prompt after selecting the data and helps avoid selecting the wrong unit. This field automatically populates the selected data from the Code Table-Unit's unit characteristic when selecting the Unit ID. There is no need to enter data directly into this field.

Description

This field allows for further supplementary information regarding the flow. You can use it to record detailed parameters or any other data that is relevant to the flow but not directly related to its quantity.

If the flow name in the original data does not exactly match the selected flow name, please first record the flow name as it appears in the original data in this field. This will help provide additional context and ensure accurate documentation of the flow information.

Data Acquisition Method

Record the data acquisition method(s) indicated in the data source for this flow. You can select multiple options from the following:

  • Literature: Sourced from other literature.

  • Calculation based on formula/chemical equation: Calculated based on formulas or chemical balance equations.

  • Field survey data: Data obtained through on-site sampling and testing.

  • Database: Data obtained from other LCA databases.

  • Experimental measurement data: Data obtained through testing in experiments, such as laboratory-scale process development.

  • Assumption: Results based on assumptions.

  • Simple estimation: Unclear estimation.

  • Unclear: No explicit explanation provided.

Note:

  1. The reference quantity (functional unit) for each process can be left blank if not applicable.

  2. If you encounter a special case that is not covered by the above situations, please contact the research team for confirmation. Uncertainty Type

Record the uncertainty distribution of the flow data. You can select from the following options:

  • Lognormal distribution

  • Normal distribution

  • Triangular distribution

  • Uniform distribution

Note: If you encounter a special case that is not covered by the above situations, please contact the research team for confirmation.

Geometric Mean

Record the geometric mean value (used for lognormal distribution). If you have selected the lognormal distribution, please provide the geometric mean value. This field cannot be left blank.

Geometric Standard Deviation

Record the geometric standard deviation value (used for lognormal distribution). If you have selected the lognormal distribution, please provide the geometric standard deviation value. This field cannot be left blank.

Arithmetic Mean

Record the arithmetic mean value (used for normal distribution). If you have selected the normal distribution, please provide the arithmetic mean value. This field cannot be left blank.

Arithmetic Standard Deviation

Record the arithmetic standard deviation value (used for normal distribution). If you have selected the normal distribution, please provide the arithmetic standard deviation value. This field cannot be left blank.

Maximum Value

Record the maximum value (used for uniform distribution and triangular distribution). If you have selected the uniform distribution or triangular distribution, please provide the maximum value. This field cannot be left blank.

Minimum Value

Record the minimum value (used for uniform distribution and triangular distribution). If you have selected the uniform distribution or triangular distribution, please provide the minimum value. This field cannot be left blank.

Mode

Record the mode (used for triangular distribution). If you have selected the triangular distribution, please provide the mode value. This field cannot be left blank.

Creator

The creator of this record will be automatically filled based on your user name. No action is required.

Modifier

The last modifier of this record will be automatically filled based on your user name. No action is required.

Last Update Time

The last update time of this record will be automatically filled based on the modification time. No action is required.

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