数学

摘要： 1.1This practice establishes lot or batch sampling plans and procedures for inspection by attributes using MIL-STD-105E as a basis for sampling a steady stream of lots indexed by acceptance quality limit (AQL).1.2This practice provides the sampling plans of MIL-STD-105E in ASTM format for use by ASTM committees and others. It recognizes the continuing usage of MIL-STD-105E in industries supported by ASTM. Most of the original text in MIL-STD-105E is preserved in Sections4 –6of this practice.1.3No system of units is specified in this standard.1.4This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.1.5This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ======4.1Purpose—This publication establishes lot or batch sampling plans and procedures for inspection by attributes. This publication shall not be interpreted to supersede or conflict with any contractual requirements. The words “accept,” “acceptance,” “acceptable,” etc, refer only to the contractor’s use of the sampling plans contained in this standard and do not imply an agreement by the customer (formerly “Government” in original text) to accept any product. Determination of acceptability by the customer shall be as described in contractual documents. The sampling plans described in this standard are applicable to AQL’s of 0.01 % or higher and are therefore not suitable for applications where quality levels in the range of parts per million levels can be realized.4.2Application—Sampling plans designated in this publication are applicable, but not limited, to inspection of the following: (1) end items, (2) components and raw materials, (3) operations or services, (4) materials in process, (5) supplies in storage, (6) maintenance operations, (7) data or records, (8) administrative procedures. These plans are intended primarily to be used for a continuing series of lots or batches. The plans may also be used for the inspection of isolated lots or batches, but, in this latter case, the user is cautioned to consult the operating characteristic curves to find a plan which will yield the desired protection (see6.11).

摘要： 1.1This guide identifies statistical procedures for use in developing new test methods or revising or evaluating existing test methods, or both.1.2This guide also cites statistical procedures especially useful in the application of test methods.1.3This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ======4.1The creation of a standardized test method generally follows a series of steps from inception to approval and ongoing use. In all such stages there are questions of how well the test method performs.4.1.1Assessments of a new or existing test method generally involve statistical planning and analysis. This standard recommends what approaches may be taken and indicates which standards may be used to perform such assessments.4.2This standard introduces a series of phases which are recommended to be considered during the life cycle of a test method as depicted inFig. 1. These begin with adesign phasewhere the standard is initially prepared. Adevelopment phaseinvolves a variety of experiments that allow further refinement and understanding of how the test method performs within a laboratory. In anevaluation phasethe test method is then examined by way of interlaboratory studies resulting in precision and bias statistics which are published in the standard. Finally, the test method is subject to amonitoring phase.FIG. 1Sequence of Steps4.3All ASTM test methods are required to include statements on precision and bias.34.4Since ASTM began to require all test methods to have precision and bias statements that are based on interlaboratory studies, there has been increased concern regarding what statistical experiments and procedures to use during the development of the test methods. Although there exists a wide range of statistical procedures, there is a small group of generally accepted techniques that are beneficial to follow. This guide is designed to provide a brief overview of these procedures and to suggest an appropriate sequence of conducting these procedures.4.5Statistical procedures often result in interpretations that are not absolutes. Sometimes the information obtained may be inadequate or incomplete, which may lead to additional questions and the need for further experimentation. Information outside the data is also important in establishing standards and in the interpretation of numerical results.

摘要： 1.1This guide identifies statistical procedures for use in developing new test methods or revising or evaluating existing test methods, or both.1.2This guide also cites statistical procedures especially useful in the application of test methods.1.3This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ======4.1The creation of a standardized test method generally follows a series of steps from inception to approval and ongoing use. In all such stages there are questions of how well the test method performs.4.1.1Assessments of a new or existing test method generally involve statistical planning and analysis. This standard recommends what approaches may be taken and indicates which standards may be used to perform such assessments.4.2This standard introduces a series of phases which are recommended to be considered during the life cycle of a test method as depicted inFig. 1. These begin with adesign phasewhere the standard is initially prepared. Adevelopment phaseinvolves a variety of experiments that allow further refinement and understanding of how the test method performs within a laboratory. In anevaluation phasethe test method is then examined by way of interlaboratory studies resulting in precision and bias statistics which are published in the standard. Finally, the test method is subject to amonitoring phase.FIG. 1Sequence of Steps4.3All ASTM test methods are required to include statements on precision and bias.34.4Since ASTM began to require all test methods to have precision and bias statements that are based on interlaboratory test methods, there has been increased concern regarding what statistical experiments and procedures to use during the development of the test methods. Although there exists a wide range of statistical procedures, there is a small group of generally accepted techniques that are beneficial to follow. This guide is designed to provide a brief overview of these procedures and to suggest an appropriate sequence of carrying out these procedures.4.5Statistical procedures often result in interpretations that are not absolutes. Sometimes the information obtained may be inadequate or incomplete, which may lead to additional questions and the need for further experimentation. Information outside the data is also important in establishing standards and in the interpretation of numerical results.

摘要： 1.1This standard is the general terminology standard for terms defined in the standards of Committee E11 on Quality and Statistics.1.2A term in this standard which lists an attribution to an E11 technical standard indicates that the standard is normative for that term. Any changes in the term definition in the normative standard will be editorially changed in this standard. Any terms added to an E11 standard will be editorially added to this standard with an attribution to that standard.1.3Term definitions that are similar to ISO 3534 will be noted in this standard, but ISO 3534 will not be considered normative for any E11 terms.1.4This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

摘要： 本文件规定了页岩气调查测井的设计、作业、原始资料质量控制及验收、资料处理、资料解释、报告编写与资料提交等要求。本文件适用于页岩气调查测井工作

摘要： 范围:本文件规定了人诱导多能干细胞的技术要求、检测方法、使用说明、标签、包装、储存、运输和废弃物处理要求。本文件适用于人诱导多能干细胞的生产和检测;主要技术内容:前言1 范围2 规范性引用文件3 术语和定义4 缩略语5 技术要求6 检验方法7 检验规则8 使用说明9 标签10 包装、储存及运输11 废弃物处理附录

摘要： 1.1Using significant digits in geotechnical data involves the processes of collecting, calculating, and recording either measured values or calculated values (results) or both. This practice is intended to promote uniformity in recording significant digits for measured and calculated values involving geotechnical data.1.2The guidelines presented are industry standard and are representative of the significant digits that should be retained in general. The guidelines do not consider material variation, the purpose for obtaining the data, special purpose studies, or any considerations for the user's objectives, and it is common practice to increase or reduce significant digits of reported data to be commensurate with these considerations.1.3It is beyond the scope of this practice to consider significant digits used in analysis methods for engineering design.1.4This practice accepts a variation of the traditional rounding method that recognizes the algorithm common to most hand-held calculators and computers, see6.2.3. The traditional rounding method (see6.2) is in accordance with PracticeE29, ASTM Manual 7, orIEEE/ASTM SI 10.Note 1:Calculators and computers often present and use many digits in their output and calculations, which may not all be significant. It is the responsibility of the programmer and user to make sure that the measured and calculated values are handled, interpreted and reported properly using these guidelines.1.5This practice offers a set of instructions for performing one or more specific operations. This document cannot replace education or experience and should be used in conjunction with professional judgment. Not all aspects of this practice may be applicable in all circumstances. This ASTM standard is not intended to represent or replace the standard of care by which the adequacy of a given professional service must be judged, nor should this document be applied without consideration of a project’s many unique aspects. The word “Standard” in the title means only that the document has been approved through the ASTM consensus process.1.6This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ======5.1The guidelines presented in this practice for retaining significant digits and rounding numbers may be adopted by the using agency or user. Their adoption should generally be used to calculate and record data when specified requirements are not included in a standard.5.2While this practice originated when most geotechnical data were manually collected and recorded on data forms, tables, or into computers, the use of digital acquisition, calculations, and reporting of data has become more common. When calculators and computers are used for data collection, the significant digits may not meet the requirements specified in this standard. Nevertheless, their use shall not be regarded as nonconforming with this practice.5.3The guidelines presented herein should not be interpreted as absolute rules but as guides to calculate and report observed or test data without exaggerating or degrading the precision of the values.5.3.1The guidelines presented emphasize recording data to enough significant digits or the number of decimal places to allow sensitivity and variability analyses to be performed.

摘要： 1.1This practice presents a procedure and related tables of factors for adapting PracticeE2234(equivalent to MIL-STD-105) sampling plans to acceptance sampling inspection when the item quality of interest is life length or reliability. Factors are provided for three alternative criteria for lot evaluation: mean life, hazard rate, and reliable life. Inspection of the sample is by attributes with testing truncated at the end of some prearranged period of time. The Weibull distribution, together with the exponential distribution as a special case, is used as the underlying statistical model.1.2A system of units is not specified by this practice.1.3This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.1.4This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ======4.1The procedure and tables presented in this practice are based on the use of the Weibull distribution in acceptance sampling inspection. Details of this work, together with tables of sampling plans of other forms, have been published previously. See Refs(1-3).4Since the basic computations required have already been made, it has been quite easy to provide these new factors. No changes in method or details of application have been made over those described in the publications referenced above. For this reason, the text portion of this report has been briefly written. Readers interested in further details are referred to these previous publications. Other sources of material on the underlying theory and approach are also available(4-7).4.2The procedure to be used is essentially the same as the one normally used for attribute sampling inspection. The only difference is that sample items are tested for life or survival instead of for some other property. For single sampling, the following are the required steps:4.2.1Using the tables of factors provided inAnnex A1, select a suitable sampling inspection plan from those tabulated in PracticeE2234.4.2.2Draw at random a sample of items of the size specified by the selected PracticeE2234plan.4.2.3Place the sample of items on life test for the specified period of time,t.4.2.4Determine the number of sample items that failed during the test period.4.2.5Compare the number of items that failed with the number allowed under the selected PracticeE2234plan.4.2.6If the number that failed is equal to or less than the acceptable number, accept the lot; if the number failing exceeds the acceptable number, reject the lot.4.3Both the sample sizes and the acceptance numbers used are those specified by PracticeE2234plans. It will be assumed in the section on examples that single sampling plans will be used. However, the matching double sampling and multiple sampling plans provided in MIL-STD-105 can be used if desired. The corresponding sample sizes and acceptance and rejection numbers are used in the usual way. The specified test truncation time,t, must be used for all samples.4.4The probability of acceptance for a lot under this procedure depends only on the probability of a sample item failing before the end of the test truncation time,t. For this reason, the actual life at failure need not be determined; only the number of items failing is of interest. Life requirements and test time specifications need not necessarily be measured in chronological terms such as minutes or hours. For example, the life measure may be cycles of operation, revolutions, or miles of travel.4.5The underlying life distribution assumed in this standard is the Weibull distribution (note that the exponential distribution is a special case of the Weibull). The Weibull model has three parameters. One parameter is a scale or characteristic life parameter. For these plans and procedures, the value for this parameter need not be known; the techniques used are independent of its magnitude. A second parameter is a location or “guaranteed life” parameter. In these plans and procedures, it is assumed that this parameter has a value of zero and that there is some risk of item failure right from the start of life. If this is not the case for some applications, a simple modification in procedure is available. The third parameter, and the one of importance, is the shape parameter, β.5The magnitude of the conversion factors used in the procedures described in this report depends directly on the value for this parameter. For this reason, the magnitude of the parameter shall be known through experience with the product or shall be estimated from past research, engineering, or inspection data. Estimation procedures are available and are outlined in Ref(1).4.6For the common case of random chance failures with the failure rate constant over time, rather than failures as a result of “infant mortality” or wearout, a value of 1 for the shape parameter shall be assumed. With this parameter value, the Weibull distribution reduces to the exponential. Tables of conversion factors are provided inAnnex A1for 15 selected shape parameter values ranging from1/2to 10, the range commonly encountered in industrial and technical practice. The value 1, used for the exponential case, is included. Factors for other required shape parameter values within this range may be obtained approximately by interpolation. A more complete discussion of the relationship between failure patterns and the Weibull parameters can be found in Refs(1-3).4.7One possible acceptance criterion is the mean life for items making up the lot (μ). Mean life conversion factors or values for the dimensionless ratio 100t/μ have been determined to correspond to or replace all thep'or percent defective values associated with PracticeE2234plans. In this factor,trepresents the specified test truncation time and μ the mean item life for the lot. For reliability or life-length applications, these factors are used in place of the correspondingp'values normally used in the use of PracticeE2234plans for attribute inspection of other item qualities. The use of these factors will be demonstrated by several examples (see Sections5,7, and9).4.8Annex Table 1A lists, for each selected shape parameter value, 100t/μ ratios for each of the PracticeE2234AQL [p'(%)] values. With acceptance inspection plans selected in terms of these ratios, the probability of acceptance will be high for lots whose mean life meets the specified requirement. The actual probability of acceptance will vary from plan to plan and may be read from the associated operating characteristic curves supplied in MIL-STD-105. The curves are entered by using the correspondingp'(%) value. Annex Table 1B lists 100t/μ ratios at the LQL for the quality level at which the consumer's risk is 0.10. Annex Table 1C lists corresponding 100t/μ ratios for a consumer's risk of 0.05.4.8.1These ratios are to be used directly for the usual case for which the value for the Weibull location or threshold parameter (γ) can be assumed as zero. If γ is not zero but has some other known value, all that shall be done is to subtract the value for γ fromtto gett0and frommto getm0. These transformed values,t0andm0, are then employed in the use of the tables and for all other computations. A solution in terms ofm0andt0can then be converted back to actual or absolute values by adding the value for γ to each.

摘要： 1.1This guide describes different mathematical methods that may be used to calculate absorbed dose and criteria for their selection. Absorbed-dose calculations can determine the effectiveness of the radiation process, estimate the absorbed-dose distribution in product, or supplement or complement, or both, the measurement of absorbed dose.1.2Radiation processing is an evolving field and annotated examples are provided inAnnex A6to illustrate the applications where mathematical methods have been successfully applied. While not limited by the applications cited in these examples, applications specific to neutron transport, radiation therapy and shielding design are not addressed in this document.1.3This guide covers the calculation of radiation transport of electrons and photons with energies up to 25 MeV.1.4The mathematical methods described include Monte Carlo, point kernel, discrete ordinate, semi-empirical and empirical methods.1.5This guide is limited to the use of general purpose software packages for the calculation of the transport of charged or uncharged particles and photons, or both, from various types of sources of ionizing radiation. This standard is limited to the use of these software packages or other mathematical methods for the determination of spatial dose distributions for photons emitted following the decay of137Cs or60Co, for energetic electrons from particle accelerators, or for X-rays generated by electron accelerators.1.6This guide assists the user in determining if mathematical methods are a useful tool. This guide may assist the user in selecting an appropriate method for calculating absorbed dose. The user must determine whether any of these mathematical methods are appropriate for the solution to their specific application and what, if any, software to apply.Note 1:The user is urged to apply these predictive techniques while being aware of the need for experience and also the inherent limitations of both the method and the available software. Information pertaining to availability and updates to codes for modeling radiation transport, courses, workshops and meetings can be found inAnnex A1. For a basic understanding of radiation physics and a brief overview of method selection, refer toAnnex A3.1.7This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.1.8This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ======4.1Use as an Analytical Tool—Mathematical methods provide an analytical tool to be employed for many applications related to absorbed dose determinations in radiation processing. Mathematical calculations may not be used as a substitute for routine dosimetry in some applications (for example, medical device sterilization, food irradiation).4.2Dose Calculation—Absorbed-dose calculations may be performed for a variety of photon/electron environments and irradiator geometries.4.3Evaluate Process Effectiveness—Mathematical models may be used to evaluate the impact of changes in product composition, loading configuration, and irradiator design on dose distribution.4.4Complement or Supplement to Dosimetry—Dose calculations may be used to establish a detailed understanding of dose distribution, providing a spatial resolution not obtainable through measurement. Calculations may be used to reduce the number of dosimeters required to characterize a procedure or process (for example, dose mapping).4.5Alternative to Dosimetry—Dose calculations may be used when dosimetry is impractical (for example, granular materials, materials with complex geometries, material contained in a package where dosimetry is not practical or possible).4.6Facility Design—Dose calculations are often used in the design of a new irradiator and can be used to help optimize dose distribution in an existing facility or radiation process. The use of modeling in irradiator design can be found in Refs(2-7).4.7Validation—The validation of the model should be done through comparison with reliable and traceable dosimetric measurements. The purpose of validation is to demonstrate that the mathematical method makes reliable predictions of dose and other transport quantities. Validation compares predictions or theory to the results of an appropriate experiment. The degree of validation is commensurate with the application. Guidance is given in the documents referenced inAnnex A2.4.8Verification—Verification is the confirmation of the mathematical correctness of a computer implementation of a mathematical method. This can be done, for example, by comparing numerical results with known analytic solutions or with other computer codes that have been previously verified. Verification should be done to ensure that the simulation is appropriate for the intended application. Refer to3.1.24.Note 2:Certain applications of the mathematical model deal with Operational Qualification (OQ), Performance Qualification (PQ) and process control in radiation processing such as the sterilization of healthcare products. The application and use of the mathematical model in these applications may have to meet regulatory requirements. Refer to Section6for prerequisites for application of a mathematical method and Section8for requirements before routine use of the mathematical method.4.9Uncertainty—An absorbed dose prediction should be accompanied by an estimate of overall uncertainty, as it is with absorbed-dose measurement (refer to ISO/ASTM 51707 and JCGM100:2008 and JCGM200:2012). In many cases, absorbed-dose measurement helps to establish the uncertainty in the dose calculation.4.10This guide should not be used as the only reference in the selection and use of mathematical models. The user is encouraged to contact individuals who are experienced in mathematical modelling and to read the relevant publications in order to select the best tool for their application. Radiation processing is an evolving field and the references cited in the annotated examples ofAnnex A6are representative of the various published applications. Where a method is validated with dosimetry, it becomes a benchmark for that particular application.

摘要： 1.1This practice presents a procedure and related tables of factors for adapting PracticeE2234(equivalent to MIL-STD-105) sampling plans to acceptance sampling inspection when the item quality of interest is life length or reliability. Factors are provided for three alternative criteria for lot evaluation: mean life, hazard rate, and reliable life. Inspection of the sample is by attributes with testing truncated at the end of some prearranged period of time. The Weibull distribution, together with the exponential distribution as a special case, is used as the underlying statistical model.1.2A system of units is not specified by this practice.1.3This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.1.4This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ======4.1The procedure and tables presented in this practice are based on the use of the Weibull distribution in acceptance sampling inspection. Details of this work, together with tables of sampling plans of other forms, have been published previously. See Refs(1-3).4Since the basic computations required have already been made, it has been quite easy to provide these new factors. No changes in method or details of application have been made over those described in the publications referenced above. For this reason, the text portion of this report has been briefly written. Readers interested in further details are referred to these previous publications. Other sources of material on the underlying theory and approach are also available(4-7).4.2The procedure to be used is essentially the same as the one normally used for attribute sampling inspection. The only difference is that sample items are tested for life or survival instead of for some other property. For single sampling, the following are the required steps:4.2.1Using the tables of factors provided inAnnex A1, select a suitable sampling inspection plan from those tabulated in PracticeE2234.4.2.2Draw at random a sample of items of the size specified by the selected PracticeE2234plan.4.2.3Place the sample of items on life test for the specified period of time,t.4.2.4Determine the number of sample items that failed during the test period.4.2.5Compare the number of items that failed with the number allowed under the selected PracticeE2234plan.4.2.6If the number that failed is equal to or less than the acceptable number, accept the lot; if the number failing exceeds the acceptable number, reject the lot.4.3Both the sample sizes and the acceptance numbers used are those specified by PracticeE2234plans. It will be assumed in the section on examples that single sampling plans will be used. However, the matching double sampling and multiple sampling plans provided in MIL-STD-105 can be used if desired. The corresponding sample sizes and acceptance and rejection numbers are used in the usual way. The specified test truncation time,t, must be used for all samples.4.4The probability of acceptance for a lot under this procedure depends only on the probability of a sample item failing before the end of the test truncation time,t. For this reason, the actual life at failure need not be determined; only the number of items failing is of interest. Life requirements and test time specifications need not necessarily be measured in chronological terms such as minutes or hours. For example, the life measure may be cycles of operation, revolutions, or miles of travel.4.5The underlying life distribution assumed in this standard is the Weibull distribution (note that the exponential distribution is a special case of the Weibull). The Weibull model has three parameters. One parameter is a scale or characteristic life parameter. For these plans and procedures, the value for this parameter need not be known; the techniques used are independent of its magnitude. A second parameter is a location or “guaranteed life” parameter. In these plans and procedures, it is assumed that this parameter has a value of zero and that there is some risk of item failure right from the start of life. If this is not the case for some applications, a simple modification in procedure is available. The third parameter, and the one of importance, is the shape parameter, β.5The magnitude of the conversion factors used in the procedures described in this report depends directly on the value for this parameter. For this reason, the magnitude of the parameter shall be known through experience with the product or shall be estimated from past research, engineering, or inspection data. Estimation procedures are available and are outlined in Ref(1).4.6For the common case of random chance failures with the failure rate constant over time, rather than failures as a result of “infant mortality” or wearout, a value of 1 for the shape parameter shall be assumed. With this parameter value, the Weibull distribution reduces to the exponential. Tables of conversion factors are provided inAnnex A1for 15 selected shape parameter values ranging from1/2to 10, the range commonly encountered in industrial and technical practice. The value 1, used for the exponential case, is included. Factors for other required shape parameter values within this range may be obtained approximately by interpolation. A more complete discussion of the relationship between failure patterns and the Weibull parameters can be found in Refs(1-3).4.7One possible acceptance criterion is the mean life for items making up the lot (μ). Mean life conversion factors or values for the dimensionless ratio 100t/μ have been determined to correspond to or replace all thep'or percent defective values associated with PracticeE2234plans. In this factor,trepresents the specified test truncation time and μ the mean item life for the lot. For reliability or life-length applications, these factors are used in place of the correspondingp'values normally used in the use of PracticeE2234plans for attribute inspection of other item qualities. The use of these factors will be demonstrated by several examples (see Sections5,7, and9).4.8Annex Table 1A lists, for each selected shape parameter value, 100t/μ ratios for each of the PracticeE2234AQL [p'(%)] values. With acceptance inspection plans selected in terms of these ratios, the probability of acceptance will be high for lots whose mean life meets the specified requirement. The actual probability of acceptance will vary from plan to plan and may be read from the associated operating characteristic curves supplied in MIL-STD-105. The curves are entered by using the correspondingp'(%) value. Annex Table 1B lists 100t/μ ratios at the LQL for the quality level at which the consumer's risk is 0.10. Annex Table 1C lists corresponding 100t/μ ratios for a consumer's risk of 0.05.4.8.1These ratios are to be used directly for the usual case for which the value for the Weibull location or threshold parameter (γ) can be assumed as zero. If γ is not zero but has some other known value, all that shall be done is to subtract the value for γ fromtto gett0and frommto getm0. These transformed values,t0andm0, are then employed in the use of the tables and for all other computations. A solution in terms ofm0andt0can then be converted back to actual or absolute values by adding the value for γ to each.

摘要： 1.1This guide describes different mathematical methods that may be used to calculate absorbed dose and criteria for their selection. Absorbed-dose calculations can determine the effectiveness of the radiation process, estimate the absorbed-dose distribution in product, or supplement or complement, or both, the measurement of absorbed dose.1.2Radiation processing is an evolving field and annotated examples are provided inAnnex A6to illustrate the applications where mathematical methods have been successfully applied. While not limited by the applications cited in these examples, applications specific to neutron transport, radiation therapy and shielding design are not addressed in this document.1.3This guide covers the calculation of radiation transport of electrons and photons with energies up to 25 MeV.1.4The mathematical methods described include Monte Carlo, point kernel, discrete ordinate, semi-empirical and empirical methods.1.5This guide is limited to the use of general purpose software packages for the calculation of the transport of charged or uncharged particles and photons, or both, from various types of sources of ionizing radiation. This standard is limited to the use of these software packages or other mathematical methods for the determination of spatial dose distributions for photons emitted following the decay of137Cs or60Co, for energetic electrons from particle accelerators, or for X-rays generated by electron accelerators.1.6This guide assists the user in determining if mathematical methods are a useful tool. This guide may assist the user in selecting an appropriate method for calculating absorbed dose. The user must determine whether any of these mathematical methods are appropriate for the solution to their specific application and what, if any, software to apply.Note 1:The user is urged to apply these predictive techniques while being aware of the need for experience and also the inherent limitations of both the method and the available software. Information pertaining to availability and updates to codes for modeling radiation transport, courses, workshops and meetings can be found inAnnex A1. For a basic understanding of radiation physics and a brief overview of method selection, refer toAnnex A3.1.7This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.1.8This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ======4.1Use as an Analytical Tool—Mathematical methods provide an analytical tool to be employed for many applications related to absorbed dose determinations in radiation processing. Mathematical calculations may not be used as a substitute for routine dosimetry in some applications (for example, medical device sterilization, food irradiation).4.2Dose Calculation—Absorbed-dose calculations may be performed for a variety of photon/electron environments and irradiator geometries.4.3Evaluate Process Effectiveness—Mathematical models may be used to evaluate the impact of changes in product composition, loading configuration, and irradiator design on dose distribution.4.4Complement or Supplement to Dosimetry—Dose calculations may be used to establish a detailed understanding of dose distribution, providing a spatial resolution not obtainable through measurement. Calculations may be used to reduce the number of dosimeters required to characterize a procedure or process (for example, dose mapping).4.5Alternative to Dosimetry—Dose calculations may be used when dosimetry is impractical (for example, granular materials, materials with complex geometries, material contained in a package where dosimetry is not practical or possible).4.6Facility Design—Dose calculations are often used in the design of a new irradiator and can be used to help optimize dose distribution in an existing facility or radiation process. The use of modeling in irradiator design can be found in Refs(2-7).4.7Validation—The validation of the model should be done through comparison with reliable and traceable dosimetric measurements. The purpose of validation is to demonstrate that the mathematical method makes reliable predictions of dose and other transport quantities. Validation compares predictions or theory to the results of an appropriate experiment. The degree of validation is commensurate with the application. Guidance is given in the documents referenced inAnnex A2.4.8Verification—Verification is the confirmation of the mathematical correctness of a computer implementation of a mathematical method. This can be done, for example, by comparing numerical results with known analytic solutions or with other computer codes that have been previously verified. Verification should be done to ensure that the simulation is appropriate for the intended application. Refer to3.1.24.Note 2:Certain applications of the mathematical model deal with Operational Qualification (OQ), Performance Qualification (PQ) and process control in radiation processing such as the sterilization of healthcare products. The application and use of the mathematical model in these applications may have to meet regulatory requirements. Refer to Section6for prerequisites for application of a mathematical method and Section8for requirements before routine use of the mathematical method.4.9Uncertainty—An absorbed dose prediction should be accompanied by an estimate of overall uncertainty, as it is with absorbed-dose measurement (refer to ISO/ASTM 51707 and NIST Technical Note 1297). In many cases, absorbed-dose measurement helps to establish the uncertainty in the dose calculation.4.10This guide should not be used as the only reference in the selection and use of mathematical models. The user is encouraged to contact individuals who are experienced in mathematical modelling and to read the relevant publications in order to select the best tool for their application. Radiation processing is an evolving field and the references cited in the annotated examples ofAnnex A6are representative of the various published applications. Where a method is validated with dosimetry, it becomes a benchmark for that particular application.

摘要： 1.1Purpose—This practice establishes lot or batch sampling plans and procedures for inspection by variables using MIL-STD-414 as a basis for sampling a steady stream of lots indexed by AQL.1.2This practice provides the sampling plans of MIL-STD-414 in ASTM format for use by ASTM committees and others. It recognizes the continuing usage of MIL-STD-414 in industries supported by ASTM. Most of the original text in MIL-STD-414 is preserved in Sections6 –9of this practice.1.3The values stated in inch-pound units are to be regarded as standard. No other units of measurement are included in this standard.1.4This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.1.5This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ======5.1This practice was prepared to meet a growing need for the use of standard sampling plans for inspection by variables in customer procurement, supply and storage, and maintenance inspection operations. The variables sampling plans apply to a single quality characteristic which can be measured on a continuous scale, and for which quality is expressed in terms of percent defective. The theory underlying the development of the variables sampling plans, including the operating characteristic curves, assumes that measurements of the quality characteristic are independent, identically distributed normal random variables.5.2In comparison with attributes sampling plans, variables sampling plans have the advantage of usually resulting in considerable savings in sample size for comparable assurance as to the correctness of decisions in judging a single quality characteristic, or for the same sample size, greater assurance is obtained using variables plans. Attributes sampling plans have the advantage of greater simplicity, of being applicable to either single or multiple quality characteristics, and of requiring no knowledge about the distribution of the continuous measurements of any of the quality characteristics.5.3It is important to note that variables sampling plans are not to be used indiscriminately, simply because it is possible to obtain variables measurement data. In considering applications where the normality or independence assumptions may be questioned, the user is advised to consult his technical agency to determine the feasibility of application.5.4Application—Sampling plans designated in this publication are applicable, but not limited, to inspection of the following:(1)end items,(2)components and raw materials,(3)operations or services,(4)materials in process,(5)supplies in storage,(6)maintenance operations,(7)data or records, and(8)administrative procedures.

摘要： 范围:本标准规定了用于计算辐射加工吸收剂量的蒙特卡罗方法、点核法、离散坐标法、经验方法和半经验方法的选择和使用。本标准适用于137Cs或60Co发射的γ射线、辐射加工用电子加速器产生的电子束或X射线的剂量和分布的计算;主要技术内容:本标准主要描述了用于计算吸收剂量的五种数学方法：第4 章节对五种方法进行了概要性的描述：第5 章节介绍了五种方法的优点和不足，以便使用者进行对比并选择合适的方法；第6 章节介绍了计算结果确认和验证的要求；第7 章节介绍了计算结果的不确定度，包括影响计算结果的因素；第8 章节介绍了文件和记录的要求，包括一般要求、文件要求等；附录A 提供了蒙特卡罗方法、点核法和经验方法的建立和使用的要求，并提供了方法的应用实例，对使用者具有重要参考意义